Journal articles on the topic 'Sesimic source parameter retrieval'
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1
Meiser, Thorsten. "Analyzing Stochastic Dependence of Cognitive Processes in Multidimensional Source Recognition." Experimental Psychology 61, no. 5 (May 15, 2014): 402–15. http://dx.doi.org/10.1027/1618-3169/a000261.
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Stochastic dependence among cognitive processes can be modeled in different ways, and the family of multinomial processing tree models provides a flexible framework for analyzing stochastic dependence among discrete cognitive states. This article presents a multinomial model of multidimensional source recognition that specifies stochastic dependence by a parameter for the joint retrieval of multiple source attributes together with parameters for stochastically independent retrieval. The new model is equivalent to a previous multinomial model of multidimensional source memory for a subset of the parameter space. An empirical application illustrates the advantages of the new multinomial model of joint source recognition. The new model allows for a direct comparison of joint source retrieval across conditions, it avoids statistical problems due to inflated confidence intervals and does not imply a conceptual imbalance between source dimensions. Model selection criteria that take model complexity into account corroborate the new model of joint source recognition.
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Allen, Douglas R., Karl W. Hoppel, Gerald E. Nedoluha, Stephen D. Eckermann, and Cory A. Barton. "Ensemble-Based Gravity Wave Parameter Retrieval for Numerical Weather Prediction." Journal of the Atmospheric Sciences 79, no. 3 (March 2022): 621–48. http://dx.doi.org/10.1175/jas-d-21-0191.1.
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Abstract Gravity wave (GW) momentum and energy deposition are large components of the momentum and heat budgets of the stratosphere and mesosphere, affecting predictability across scales. Since weather and climate models cannot resolve the entire GW spectrum, GW parameterizations are required. Tuning these parameterizations is time-consuming and must be repeated whenever model configurations are changed. We introduce a self-tuning approach, called GW parameter retrieval (GWPR), applied when the model is coupled to a data assimilation (DA) system. A key component of GWPR is a linearized model of the sensitivity of model wind and temperature to the GW parameters, which is calculated using an ensemble of nonlinear forecasts with perturbed parameters. GWPR calculates optimal parameters using an adaptive grid search that reduces DA analysis increments via a cost-function minimization. We test GWPR within the Navy Global Environmental Model (NAVGEM) using three latitude-dependent GW parameters: peak momentum flux, phase-speed width of the Gaussian source spectrum, and phase-speed weighting relative to the source-level wind. Compared to a baseline experiment with fixed parameters, GWPR reduces analysis increments and improves 5-day mesospheric forecasts. Relative to the baseline, retrieved parameters reveal enhanced source-level fluxes and westward shift of the wave spectrum in the winter extratropics, which we relate to seasonal variations in frontogenesis. The GWPR reduces stratospheric increments near 60°S during austral winter, compensating for excessive baseline nonorographic GW drag. Tropical sensitivity is weaker due to significant absorption of GW in the stratosphere, resulting in less confidence in tropical GWPR values.
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Jin, Sheng, Xiaojian Ding, Su Wang, Yao Dong, and Jianghui Ji. "Nii: a Bayesian orbit retrieval code applied to differential astrometry." Monthly Notices of the Royal Astronomical Society 509, no. 3 (November 17, 2021): 4608–19. http://dx.doi.org/10.1093/mnras/stab3317.
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ABSTRACT Here, we present an open source python-based Bayesian orbit retrieval code (Nii) that implements an automatic parallel tempering Markov chain Monte Carlo (APT-MCMC) strategy. Nii provides a module to simulate the observations of a space-based astrometry mission in the search for exoplanets, a signal extraction process for differential astrometric measurements using multiple reference stars, and an orbital parameter retrieval framework using APT-MCMC. We further verify the orbit retrieval ability of the code through two examples corresponding to a single-planet system and a dual-planet system. In both cases, efficient convergence on the posterior probability distribution can be achieved. Although this code specifically focuses on the orbital parameter retrieval problem of differential astrometry, Nii can also be widely used in other Bayesian analysis applications.
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Bressler, I., B. R. Pauw, and A. F. Thünemann. "McSAS: software for the retrieval of model parameter distributions from scattering patterns." Journal of Applied Crystallography 48, no. 3 (May 22, 2015): 962–69. http://dx.doi.org/10.1107/s1600576715007347.
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A user-friendly open-source Monte Carlo regression package (McSAS) is presented, which structures the analysis of small-angle scattering (SAS) using uncorrelated shape-similar particles (or scattering contributions). The underdetermined problem is solvable, provided that sufficient external information is available. Based on this, the user picks a scatterer contribution model (or `shape') from a comprehensive library and defines variation intervals of its model parameters. A multitude of scattering contribution models are included, including prolate and oblate nanoparticles, core–shell objects, several polymer models, and a model for densely packed spheres. Most importantly, the form-free Monte Carlo nature ofMcSASmeans it is not necessary to provide further restrictions on the mathematical form of the parameter distribution; without prior knowledge,McSASis able to extract complex multimodal or odd-shaped parameter distributions from SAS data. When provided with data on an absolute scale with reasonable uncertainty estimates, the software outputs model parameter distributions in absolute volume fraction, and provides the modes of the distribution (e.g.mean, varianceetc.). In addition to facilitating the evaluation of (series of) SAS curves,McSASalso helps in assessing the significance of the results through the addition of uncertainty estimates to the result. TheMcSASsoftware can be integrated as part of an automated reduction and analysis procedure in laboratory instruments or at synchrotron beamlines.
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Zhang, Yun, Xu Chen, Wanting Meng, Jiwei Yin, Yanling Han, Zhonghua Hong, and Shuhu Yang. "Wind Direction Retrieval Using Support Vector Machine from CYGNSS Sea Surface Data." Remote Sensing 13, no. 21 (November 5, 2021): 4451. http://dx.doi.org/10.3390/rs13214451.
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In view of the difficulty of wind direction retrieval in the case of the large space and time span of the global sea surface, a method of sea surface wind direction retrieval using a support vector machine (SVM) is proposed. This paper uses the space-borne global navigation satellite systems reflected signal (GNSS-R) as the remote sensing signal source. Using the Cyclone Global Navigation Satellite System (CYGNSS) satellite data, this paper selects a variety of feature parameters according to the correlation between the features of the sea surface reflection signal and the wind direction, including the Delay Doppler Map (DDM), corresponding to the CYGNSS satellite parameters and geometric feature parameters. The Radial Basis Function (RBF) is selected, and parameter optimization is performed through cross-validation based on the grid search method. Finally, the SVM model of sea surface wind direction retrieval is established. The result shows that this method has a high retrieval classification accuracy using the dataset with wind speed greater than 10 m/s, and the root mean square error (RMSE) of the retrieval result is 26.70°.
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Mercieca, Thomas, and Joseph G. Vella. "Multi-Dimensional Indexes in DBMSs." Journal of Cases on Information Technology 21, no. 3 (July 2019): 40–50. http://dx.doi.org/10.4018/jcit.2019070103.
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Multi-dimensional data is present across multimedia, data mining and other data-driven applications. The R-Tree is a popular index structure that DBMSs are implementing as core for efficient retrieval of such data. The gap between the best and worst-case performance is very wide in an R-tree. Thus, building quality R-trees quickly is desirable. Variations differ in how node overflow are approached during the building process. This article studies the R-Tree technique that the open-source PostgreSQL DBMS uses. Focus is on a specific parameter controlling node overflows as an optimisation target, and improved configurations are proposed. This parameter is hard-wired into the DBMS, and therefore, an implementation is presented to allow this parameter to become accessible through an SQL construct. The access method designer can resort to configuring this parameter when trying to meet specific storage or time-related performance targets. With this study, the reader can gain an insight into the effects of changing the parameter by considering the spatial indexes on well-known workloads.
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Muckenhuber, Stefan, Anton Andreevich Korosov, and Stein Sandven. "Open-source feature-tracking algorithm for sea ice drift retrieval from Sentinel-1 SAR imagery." Cryosphere 10, no. 2 (April 26, 2016): 913–25. http://dx.doi.org/10.5194/tc-10-913-2016.
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Abstract. A computationally efficient, open-source feature-tracking algorithm, called ORB, is adopted and tuned for sea ice drift retrieval from Sentinel-1 SAR (Synthetic Aperture Radar) images. The most suitable setting and parameter values have been found using four Sentinel-1 image pairs representative of sea ice conditions between Greenland and Severnaya Zemlya during winter and spring. The performance of the algorithm is compared to two other feature-tracking algorithms, namely SIFT (Scale-Invariant Feature Transform) and SURF (Speeded-Up Robust Features). Having been applied to 43 test image pairs acquired over Fram Strait and the north-east of Greenland, the tuned ORB (Oriented FAST and Rotated BRIEF) algorithm produces the highest number of vectors (177 513, SIFT: 43 260 and SURF: 25 113), while being computationally most efficient (66 s, SIFT: 182 s and SURF: 99 s per image pair using a 2.7 GHz processor with 8 GB memory). For validation purposes, 314 manually drawn vectors have been compared with the closest calculated vectors, and the resulting root mean square error of ice drift is 563 m. All test image pairs show a significantly better performance of the HV (horizontal transmit, vertical receive) channel due to higher informativeness. On average, around four times as many vectors have been found using HV polarization. All software requirements necessary for applying the presented feature-tracking algorithm are open source to ensure a free and easy implementation.
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Blecic, Jasmina, Joseph Harrington, Patricio E. Cubillos, M. Oliver Bowman, Patricio M. Rojo, Madison Stemm, Ryan C. Challener, et al. "An Open-source Bayesian Atmospheric Radiative Transfer (BART) Code. III. Initialization, Atmospheric Profile Generator, Post-processing Routines." Planetary Science Journal 3, no. 4 (April 1, 2022): 82. http://dx.doi.org/10.3847/psj/ac3515.
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Abstract This and companion papers by Harrington et al. and Cubillos et al. describe an open-source retrieval framework, Bayesian Atmospheric Radiative Transfer (BART), available to the community under the reproducible-research license via https://github.com/exosports/BART. BART is a radiative transfer code (transit; https://github.com/exosports/transit; Rojo et al.), initialized by the Thermochemical Equilibrium Abundances (TEA; https://github.com/dzesmin/TEA) code (Blecic et al.), and driven through the parameter phase space by a differential-evolution Markov Chain Monte Carlo (MC3; https://github.com/pcubillos/mc3) sampler (Cubillos et al.). In this paper we give a brief description of the framework and its modules that can be used separately for other scientific purposes; outline the retrieval analysis flow; present the initialization routines, describing in detail the atmospheric profile generator and the temperature and species parameterizations; and specify the post-processing routines and outputs, concentrating on the spectrum band integrator, the best-fit model selection, and the contribution functions. We also present an atmospheric analysis of WASP-43b secondary eclipse data obtained from space- and ground-based observations. We compare our results with the results from the literature and investigate how the inclusion of additional opacity sources influences the best-fit model.
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Nikonovas, T., P. R. J. North, and S. H. Doerr. "Smoke aerosol properties and ageing effects for Northern temperate and boreal regions derived from AERONET source and age attribution." Atmospheric Chemistry and Physics Discussions 15, no. 5 (March 5, 2015): 6445–79. http://dx.doi.org/10.5194/acpd-15-6445-2015.
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Abstract. Particulate emissions from wildfires impact human health and have a large but uncertain effect on climate. Modelling schemes depend on information about emission factors, emitted particle microphysical and optical properties and ageing effects, while satellite retrieval algorithms make use of characteristic aerosol models to improve retrieval. Ground based remote sensing provides detailed aerosol characterisation, but does not contain information on source. Here, a method is presented to estimate plume origin land cover type and age for AERONET aerosol observations, employing trajectory modelling using the HYSPLIT model, and satellite active fire and aerosol optical thickness (AOT) observations from MODIS and AATSR. It is applied to AERONET stations located in or near Northern temperate and boreal forests, for the period 2002–2013. The results from 629 fire attributions indicate significant differences in size distributions and particle optical properties between different land cover types. Smallest fine mode median radius are attributed to plumes from cropland – natural vegetation mosaic (0.143 μm) and grasslands (0.147 μm) fires. Evergreen needleleaf forest emissions show a significantly smaller fine mode median radius (0.164 μm) than plumes from woody savannas (0.184 μm) and mixed forest (0.193 μm) fires. Smoke plumes are predominantly scattering for all of the classes with median single scattering albedo at 440 nm (SSA(440)) values close to 0.95 except the cropland emissions which have a SSA(440) value of 0.9. Overall fine mode volume median radius increase rate is 0.0095 μm per day for the first 4 days of ageing and 0.0084 μm per day for seven days of ageing. Changes in size were consistent with a decrease in Angstrom Exponent and increase in Asymmetry parameter. No significant changes in SSA(λ) with ageing were found. These estimates have implications for improved modelling of aerosol radiative effects, relevant to both climate modelling and satellite aerosol retrieval schemes.
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Knobelspiesse, Kirk, Amir Ibrahim, Bryan Franz, Sean Bailey, Robert Levy, Ziauddin Ahmad, Joel Gales, et al. "Analysis of simultaneous aerosol and ocean glint retrieval using multi-angle observations." Atmospheric Measurement Techniques 14, no. 5 (May 3, 2021): 3233–52. http://dx.doi.org/10.5194/amt-14-3233-2021.
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Abstract. Since early 2000, NASA's Multi-angle Imaging SpectroRadiometer (MISR) instrument has been performing remote sensing retrievals of aerosol optical properties from the polar-orbiting Terra spacecraft. A noteworthy aspect of MISR observations over the ocean is that, for much of the Earth, some of the multi-angle views have contributions from solar reflection by the ocean surface (glint, or glitter), while others do not. Aerosol retrieval algorithms often discard these glint-influenced observations because they can overwhelm the signal and are difficult to predict without knowledge of the (wind-speed-driven) ocean surface roughness. However, theoretical studies have shown that multi-angle observations of a location at geometries with and without reflected sun glint can be a rich source of information, sufficient to support simultaneous retrieval of both the aerosol state and the wind speed at the ocean surface. We are in the early stages of creating such an algorithm. In this paper, we describe our assessment of the appropriate level of parameterization for simultaneous aerosol and ocean surface property retrievals using sun glint. For this purpose, we use generalized nonlinear retrieval analysis (GENRA), an information content assessment (ICA) technique employing Bayesian inference, and simulations from the Ahmad–Fraser iterative radiative transfer code. We find that four parameters are suitable: aerosol optical depth (τ), particle size distribution (expressed as the fine mode fraction f of small particles in a bimodal size distribution), surface wind speed (w), and relative humidity (r, to define the aerosol water content and complex refractive index). None of these parameters define ocean optical properties, as we found that the aerosol state could be retrieved with the nine MISR near-infrared views alone, where the ocean body is strongly absorbing in the open ocean. We also found that retrieval capability varies with observation geometry and that as τ increases so does the ability to determine aerosol intensive optical properties (r and f, while it decreases for w). Increases in w decrease the ability to determine the true value of that parameter but have minimal impact on retrieval of aerosol properties. We explored the benefit of excluding the two most extreme MISR view angles for which radiative transfer with the plane-parallel approximation is less certain, but we found no advantage in doing so. Finally, the impact of treating wind speed as a scalar parameter, rather than as a two-parameter directional wind, was tested. While the simpler scalar model does contribute to overall aerosol uncertainty, it is not sufficiently large to justify the addition of another dimension to parameter space. An algorithm designed upon these principles is in development. It will be used to perform an atmospheric correction with MISR for coincident ocean color (OC) observations by the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument, also on the NASA Terra spacecraft. Unlike MISR, MODIS is a single-view-angle instrument, but it has a more complete set of spectral channels ideal for determination of optical ocean properties. The atmospheric correction of MODIS OC data can therefore benefit from MISR aerosol retrievals. Furthermore, higher-spatial-resolution data from coincident MISR observations may also improve glint screening.
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Oveisgharan, Shadi, Daniel Esteban-Fernandez, Duane Waliser, Randall Friedl, Son Nghiem, and Xubin Zeng. "Evaluating the Preconditions of Two Remote Sensing SWE Retrieval Algorithms over the US." Remote Sensing 12, no. 12 (June 24, 2020): 2021. http://dx.doi.org/10.3390/rs12122021.
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A large amount of fresh water resources are stored in the snowpack, which is the primary source of water for streamflow in many places at middle-to-high latitude areas. Therefore, snow water equivalent (SWE) is a key parameter in the water cycle. Active and passive microwave remote sensing methods have been used to retrieve SWE due to relatively poor resolution of current in situ interpolated maps with good accuracy. However, estimation of SWE has proved challenging, despite several decades of efforts to develop retrieval approaches. Active sensors provide higher-resolution observations. Two recent promising retrieval algorithms using active data are dual frequency dual polarization backscattered power and differential interferometry. These retrieval algorithms have some restrictions on snow characteristics, the environment, and instrument properties. The restrictions limit the snow that is suitable for the specific retrieval algorithm. In order to better understand how much of the snowpack satisfies the precondition of these retrieval approaches, we use a 4 km gridded snowpack product over the contiguous US for years 1997 and 2015. We use a simple scattering model to simulate the scattering characteristics of snow. The snow property maps, simulated scattering characteristics of snow, and environmental conditions are used to filter the suitable snow for each retrieval algorithm. We show that snow wetness and vegetation coverage are the two main limiting conditions for these retrieval algorithms. We show that 39% and 44% of the grid-points with snow satisfy the preconditions of dual polarization dual frequency retrieval algorithms at 13.5 GHz (one of the recommended frequencies for this algorithm in the literature) in 1997 and 2015, respectively. The most important limiting factors for dual polarization dual frequency retrieval method are dryness of snow, penetration depth, and vegetation-free constraints. The backscattered power in dual polarization dual frequency method is more sensitive to snow density and grain radius rather than to snow depth. We also show that 55% and 53% of the grid-points with snow satisfy the precondition of differential interferometry retrieval algorithms at 1 GHz (one of the recommended frequencies for this algorithm in the literature) in 1997 and 2015, respectively. The most important precondition-limiting factors for differential interferometry are dryness of snow and vegetation-free constraints. The differential interferometry phase retrieval algorithm is equally sensitive to snow height and snow density variations and is independent of snow grain radius.
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Zhou, Lu, Shiming Xu, Jiping Liu, and Bin Wang. "On the retrieval of sea ice thickness and snow depth using concurrent laser altimetry and L-band remote sensing data." Cryosphere 12, no. 3 (March 22, 2018): 993–1012. http://dx.doi.org/10.5194/tc-12-993-2018.
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Abstract. The accurate knowledge of sea ice parameters, including sea ice thickness and snow depth over the sea ice cover, is key to both climate studies and data assimilation in operational forecasts. Large-scale active and passive remote sensing is the basis for the estimation of these parameters. In traditional altimetry or the retrieval of snow depth with passive microwave remote sensing, although the sea ice thickness and the snow depth are closely related, the retrieval of one parameter is usually carried out under assumptions over the other. For example, climatological snow depth data or as derived from reanalyses contain large or unconstrained uncertainty, which result in large uncertainty in the derived sea ice thickness and volume. In this study, we explore the potential of combined retrieval of both sea ice thickness and snow depth using the concurrent active altimetry and passive microwave remote sensing of the sea ice cover. Specifically, laser altimetry and L-band passive remote sensing data are combined using two forward models: the L-band radiation model and the isostatic relationship based on buoyancy model. Since the laser altimetry usually features much higher spatial resolution than L-band data from the Soil Moisture Ocean Salinity (SMOS) satellite, there is potentially covariability between the observed snow freeboard by altimetry and the retrieval target of snow depth on the spatial scale of altimetry samples. Statistically significant correlation is discovered based on high-resolution observations from Operation IceBridge (OIB), and with a nonlinear fitting the covariability is incorporated in the retrieval algorithm. By using fitting parameters derived from large-scale surveys, the retrievability is greatly improved compared with the retrieval that assumes flat snow cover (i.e., no covariability). Verifications with OIB data show good match between the observed and the retrieved parameters, including both sea ice thickness and snow depth. With detailed analysis, we show that the error of the retrieval mainly arises from the difference between the modeled and the observed (SMOS) L-band brightness temperature (TB). The narrow swath and the limited coverage of the sea ice cover by altimetry is the potential source of error associated with the modeling of L-band TB and retrieval. The proposed retrieval methodology can be applied to the basin-scale retrieval of sea ice thickness and snow depth, using concurrent passive remote sensing and active laser altimetry based on satellites such as ICESat-2 and WCOM.
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Hodrius, M., S. Migdall, H. Bach, and T. Hank. "The Impact of Multi-Sensor Data Assimilation on Plant Parameter Retrieval and Yield Estimation for Sugar Beet." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-7/W3 (April 28, 2015): 19–25. http://dx.doi.org/10.5194/isprsarchives-xl-7-w3-19-2015.
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Yield Maps are a basic information source for site-specific farming. For sugar beet they are not available as in-situ measurements. This gap of information can be filled with Earth Observation (EO) data in combination with a plant growth model (PROMET) to improve farming and harvest management. The estimation of yield based on optical satellite imagery and crop growth modelling is more challenging for sugar beet than for other crop types since the plants’ roots are harvested. These are not directly visible from EO. In this study, the impact of multi-sensor data assimilation on the yield estimation for sugar beet is evaluated. Yield and plant growth are modelled with PROMET. This multi-physics, raster-based model calculates photosynthesis and crop growth based on the physiological processes in the plant, including the distribution of biomass into the different plant organs (roots, stem, leaves and fruit) at different phenological stages. <br><br> The crop variable used in the assimilation is the green (photosynthetically active) leaf area, which is derived as spatially heterogeneous input from optical satellite imagery with the radiative transfer model SLC (Soil-Leaf-Canopy). Leaf area index was retrieved from RapidEye, Landsat 8 OLI and Landsat 7 ETM+ data. It could be shown that the used methods are very suitable to derive plant parameters time-series with different sensors. The LAI retrievals from different sensors are quantitatively compared to each other. Results for sugar beet yield estimation are shown for a test-site in Southern Germany. The validation of the yield estimation for the years 2012 to 2014 shows that the approach reproduced the measured yield on field level with high accuracy. Finally, it is demonstrated through comparison of different spatial resolutions that small-scale in-field variety is modelled with adequate results at 20 m raster size, but the results could be improved by recalculating the assimilation at a finer spatial resolution of 5 m.
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Muckenhuber, S., A. Korosov, and S. Sandven. "Sea ice drift from Sentinel-1 SAR imagery using open source feature tracking." Cryosphere Discussions 9, no. 6 (December 21, 2015): 6937–59. http://dx.doi.org/10.5194/tcd-9-6937-2015.
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Abstract. A computational efficient, open source feature tracking algorithm, called ORB, is adopted and tuned for sea ice drift retrieval from Sentinel-1 SAR images. The best suitable setting and parameter values have been found using four representative Sentinel-1 image pairs. A new quality measure for feature tracking algorithms is introduced utilising the distribution of the resulting vector field. The performance of the algorithm is compared with two other feature tracking algorithms (SIFT and SURF). Applied on a test image pair acquired over Fram Strait, the tuned ORB algorithm produces the highest number of vectors (6920, SIFT: 1585 and SURF: 518) while being computational most efficient (66 s, SIFT: 182 s and SURF: 99 s using a 2,7 GHz processor with 8 GB memory). For validation purpose, 350 manually drawn vectors have been compared with the closest calculated vectors and the resulting root mean square distance is 609.9 m (equivalent to 7.5 pixel). All test image pairs show a significant better performance of the HV channel. On average, around 4 times more vectors have been found using HV polarisation. All software requirements necessary for applying the presented feature tracking algorithm are open source to ensure a free and easy implementation.
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Niroumand-Jadidi, M., and F. Bovolo. "WATER QUALITY RETRIEVAL AND ALGAL BLOOM DETECTION USING HIGH-RESOLUTION CUBESAT IMAGERY." ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences V-3-2021 (June 17, 2021): 191–95. http://dx.doi.org/10.5194/isprs-annals-v-3-2021-191-2021.
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Abstract. Recent advancements in developing small satellites known as CubeSats provide an increasingly viable means of characterizing the dynamics of inland and nearshore waters with an unprecedented combination of high revisits (< 1 day) with a high spatial resolution (meter-scale). Estimation of water quality parameters can benefit from the very high spatiotemporal resolution of CubeSat imagery for monitoring subtle variations and identification of hazardous events like algal blooms. In this study, we present the first study on retrieving lake chlorophyll-a (Chl-a) concentration and detecting algal blooms using imagery acquired by the PlanetScope constellation which is currently the most prominent source of CubeSat data. Moreover, the concentration of total suspended matter (TSM) is retrieved that is an indicator of turbidity. The retrievals are based upon inverting the radiative transfer model. The low spectral resolution (four bands) of PlanetScope imagery poses challenges for such a physics-based inversion due to spectral ambiguities in optically-complex waters like inland waters. To deal with this issue, the number of variable parameters is minimized through inverse modeling. Given the significance of having high-quality water-leaving reflectance for physics-based models, a variable parameter (gdd) is considered to compensate for the atmospheric and sun-glint artifacts. The results compared to the in-situ data indicate high potentials of PlanetScope imagery in retrieving water quality parameters and detection of algal blooms in our case study (Lake Trasimeno, Italy).
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Iwabuchi, Hironobu, Soichiro Yamada, Shuichiro Katagiri, Ping Yang, and Hajime Okamoto. "Radiative and Microphysical Properties of Cirrus Cloud Inferred from Infrared Measurements Made by the Moderate Resolution Imaging Spectroradiometer (MODIS). Part I: Retrieval Method." Journal of Applied Meteorology and Climatology 53, no. 5 (May 2014): 1297–316. http://dx.doi.org/10.1175/jamc-d-13-0215.1.
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AbstractAn optimal estimation–based algorithm is developed to infer the global-scale distribution of cirrus cloud radiative and microphysical properties from the measurements made by the Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) at three infrared (IR) window bands centered at 8.5, 11, and 12 μm. Cloud-top and underlying surface temperatures, as a priori information, are obtained from the MODIS operational products. A fast-forward model based on semianalytical equations for the brightness temperature is used. The modeling errors in brightness temperature are mainly from the uncertainties in model parameters including surface emissivity, precipitable water, and cloud-base temperature. The total measurement–model errors are well correlated for the three bands, which are considered in the retrieval. The most important factors for the accurate retrieval of cloud optical thickness and the effective particle radius are cloud-top and surface temperatures, whereas model parameter uncertainties constitute a moderately significant error source. The three-band IR method is suitable for retrieving optical thickness and effective radius for cloud optical thicknesses within a range of 0.5–6, where the typical root-mean-square error is less than 20% in optical thickness and less than 40% in effective particle radius. A tropical-region case study demonstrates the advantages of the method—in particular, the ability to be applied to more pixels in optically thin cirrus in comparison with a solar-reflection-based method—and the ability of the optimal estimation framework to produce useful diagnostics of the retrieval quality. Collocated comparisons with spaceborne active remote sensing data exhibit reasonable consistency with respect to retrieved particle size.
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Yu, Lihong, Jiali Shang, Zhiqiang Cheng, Zebin Gao, Zixin Wang, Luo Tian, Dantong Wang, et al. "Assessment of Cornfield LAI Retrieved from Multi-Source Satellite Data Using Continuous Field LAI Measurements Based on a Wireless Sensor Network." Remote Sensing 12, no. 20 (October 11, 2020): 3304. http://dx.doi.org/10.3390/rs12203304.
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Accurate and continuous monitoring of leaf area index (LAI), a widely-used vegetation structural parameter, is crucial to characterize crop growth conditions and forecast crop yield. Meanwhile, advancements in collecting field LAI measurements have provided strong support for validating remote-sensing-derived LAI. This paper evaluates the performance of LAI retrieval from multi-source, remotely sensed data through comparisons with continuous field LAI measurements. Firstly, field LAI was measured continuously over periods of time in 2018 and 2019 using LAINet, a continuous LAI measurement system deployed using wireless sensor network (WSN) technology, over an agricultural region located at the Heihe watershed at northwestern China. Then, cloud-free images from optical satellite sensors, including Landsat 7 the Enhanced Thematic Mapper Plus (ETM+), Landsat 8 the Operational Land Imager (OLI), and Sentinel-2A/B Multispectral Instrument (MSI), were collected to derive LAI through inversion of the PROSAIL radiation transfer model using a look-up-table (LUT) approach. Finally, field LAI data were used to validate the multi-temporal LAI retrieved from remote-sensing data acquired by different satellite sensors. The results indicate that good accuracy was obtained using different inversion strategies for each sensor, while Green Chlorophyll Index (CIgreen) and a combination of three red-edge bands perform better for Landsat 7/8 and Sentinel-2 LAI inversion, respectively. Furthermore, the estimated LAI has good consistency with in situ measurements at vegetative stage (coefficient of determination R2 = 0.74, and root mean square error RMSE = 0.53 m2 m−2). At the reproductive stage, a significant underestimation was found (R2 = 0.41, and 0.89 m2 m−2 in terms of RMSE). This study suggests that time-series LAI can be retrieved from multi-source satellite data through model inversion, and the LAINet instrument could be used as a low-cost tool to provide continuous field LAI measurements to support LAI retrieval.
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Hou, W. Z., H. F. Wang, Z. Q. Li, L. L. Qie, B. Y. Ge, C. Fan, and S. Li. "PRELIMINARY SENSITIVITY STUDY OF AEROSOL LAYER HEIGHT FROM SYNTHETIC MULTIANGLE POLARIMETRIC REMOTE SENSING MEASUREMENTS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3/W9 (October 25, 2019): 63–69. http://dx.doi.org/10.5194/isprs-archives-xlii-3-w9-63-2019.
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Abstract. Many previous studies have shown that multiangle, multispectral polarimetric remote sensing can provide valuable information on aerosol microphysical and optical properties, in which the aerosol layer height (ALH) is an important parameter but with less studies, especially in the near-ultraviolet (near-UV) and visible (VIS) wavelength bands. Based on the optimal estimation (OE) theory and information content analysis method, we focus on the sensitivity study of ALH with the synthetic data in the near-UV and VIS wavelength in the range of 410–865 nm, and further to assess the capability of multiangle intensity and polarization measurements for the retrieval of ALH. Unified Linearized Vector Radiative Transfer Model (UNL-VRTM) has been used as the forward model to simulate the intensity and polarized radiance at the top of atmosphere (TOA), as well as the Jacobians of TOA results with respective to corresponding parameters. The degree of freedom for signal (DFS) and a posteriori error are introduced to quantity the information content of ALH from the intensity and polarization measurements, respectively. By assuming the surface type, aerosol model, aerosol loads, prior errors and observation geometries, the sensitivity of ALH has been preliminarily investigated. The sensitivity study results show that the near-UV and polarization measurements are the important source of information content for the aerosol height retrieval in satellite remote sensing.
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Aloisio, Isobel A., David M. Paganin, Christopher A. Wright, and Kaye S. Morgan. "Exploring experimental parameter choice for rapid speckle-tracking phase-contrast X-ray imaging with a paper analyzer." Journal of Synchrotron Radiation 22, no. 5 (July 21, 2015): 1279–88. http://dx.doi.org/10.1107/s1600577515011406.
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Phase-contrast X-ray imaging using a paper analyzer enables the visualization of X-ray transparent biological structures using the refractive properties of the sample. The technique measures the sample-induced distortions of a spatially random reference pattern to retrieve quantitative sample information. This phase-contrast method is promising for biomedical application due to both a simple experimental set-up and a capability for real-time imaging. The authors explore the experimental configuration required to achieve robustness and accuracy in terms of (i) the paper analyzer feature size, (ii) the sample-to-detector distance, and (iii) the exposure time. Results using a synchrotron source confirm that the technique achieves accurate phase retrieval with a range of paper analyzers and at exposures as short as 0.5 ms. These exposure times are sufficiently short relative to characteristic physiological timescales to enable real-time dynamic imaging of living samples. A theoretical guide to the choice of sample-to-detector distance is also derived. While the measurements are specific to the set-up, these guidelines, the example speckle images, the strategies for analysis in the presence of noise and the experimental considerations and discussion will be of value to those who wish to use the speckle-tracking paper analyzer technique.
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Nikonovas, T., P. R. J. North, and S. H. Doerr. "Smoke aerosol properties and ageing effects for northern temperate and boreal regions derived from AERONET source and age attribution." Atmospheric Chemistry and Physics 15, no. 14 (July 17, 2015): 7929–43. http://dx.doi.org/10.5194/acp-15-7929-2015.
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Abstract. Particulate emissions from wildfires impact human health and have a large but uncertain effect on climate. Modelling schemes depend on information about emission factors, emitted particle microphysical and optical properties and ageing effects, while satellite retrieval algorithms make use of characteristic aerosol models to improve retrieval. Ground-based remote sensing provides detailed aerosol characterisation, but does not contain information on source. Here, a method is presented to estimate plume origin land cover type and age for AERONET aerosol observations, employing trajectory modelling using the HYSPLIT model, and satellite active fire and aerosol optical thickness (AOT) observations from Moderate Resolution Imaging Spectroradiometer (MODIS) and Along Track Scanning Radiometer (AATSR). It is applied to AERONET stations located in or near northern temperate and boreal forests for the period 2002–2013. The results from 629 fire attributions indicate significant differences in size distributions and particle optical properties between different land cover types and plume age. Smallest fine mode median radius (Rfv) are attributed to plumes from cropland and/or natural vegetation mosaic (0.143 μm) and grassland (0.157 μm) fires. North American evergreen needleleaf forest emissions show a significantly smaller Rfv (0.164 μm) than plumes from Eurasian mixed forests (0.193 μm) and plumes attributed to the land cover types with sparse tree cover – open shrubland (0.185 μm) and woody savannas (0.184 μm). The differences in size distributions are related to inferred variability in plume concentrations between the land cover types. Significant differences are observed between day and night emissions, with daytime emissions showing larger particle sizes. Smoke is predominantly scattering for all of the classes with median single scattering albedo at 440 nm (SSA(440)) values close to 0.95 except the cropland emissions which have an SSA(440) value of 0.9. Plumes aged for 4 days or older have median Rfv larger by ~0.02 μm compared to young smoke. Differences in size were consistent with a decrease in the Ångström Exponent and increase in the asymmetry parameter. Only an insignificant increase in SSA(λ) with ageing was found.
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Cubillos, Patricio E., Joseph Harrington, Jasmina Blecic, Michael D. Himes, Patricio M. Rojo, Thomas J. Loredo, Nate B. Lust, et al. "An Open-source Bayesian Atmospheric Radiative Transfer (BART) Code. II. The Transit Radiative Transfer Module and Retrieval of HAT-P-11b." Planetary Science Journal 3, no. 4 (April 1, 2022): 81. http://dx.doi.org/10.3847/psj/ac348b.
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Abstract This and companion papers by Harrington et al. and Blecic et al. present the Bayesian Atmospheric Radiative Transfer (bart) code, an open-source, open-development package to characterize extrasolar planet atmospheres. bart combines a thermochemical equilibrium abundance (tea), a radiative transfer (Transit), and a Bayesian statistical (mc3) module to constrain atmospheric temperatures and molecular abundances for given spectroscopic observations. Here we describe the Transit radiative transfer package, an efficient line-by-line radiative transfer C code for one-dimensional atmospheres, developed by P. Rojo and further modified by the UCF exoplanet group. This code produces transmission and hemisphere-integrated emission spectra. Transit handles line-by-line opacities from HITRAN, Partridge & Schwenke (H2O), Schwenke (TiO), and Plez (VO) and collision-induced absorption from Borysow, HITRAN, and ExoMol. Transit emission spectra models agree with models from C. Morley (private communication) within a few percent. We applied bart to the Spitzer and Hubble transit observations of the Neptune-sized planet HAT-P-11b. Our analysis of the combined HST and Spitzer data generally agrees with those from previous studies, finding atmospheric models with enhanced metallicity (≳100× solar) and high-altitude clouds (≲1 mbar level). When analyzing only the HST data, our models favor high-metallicity atmospheres, in contrast with the previous analysis by Chachan et al. We suspect that this discrepancy arises from the different choice of chemistry modeling (free constant-with-altitude versus thermochemical equilibrium) and the enhanced parameter correlations found when neglecting the Spitzer observations. The bart source code and documentation are available at https://github.com/exosports/BART.
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Fevola, Giovanni, Erik Bergbäck Knudsen, Tiago Ramos, Dina Carbone, and Jens Wenzel Andreasen. "A Monte Carlo ray-tracing simulation of coherent X-ray diffractive imaging." Journal of Synchrotron Radiation 27, no. 1 (January 1, 2020): 134–45. http://dx.doi.org/10.1107/s1600577519014425.
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Coherent diffractive imaging (CDI) experiments are adequately simulated assuming the thin sample approximation and using a Fresnel or Fraunhofer wavefront propagator to obtain the diffraction pattern. Although this method is used in wave-based or hybrid X-ray simulators, here the applicability and effectiveness of an alternative approach that is based solely on ray tracing of Huygens wavelets are investigated. It is shown that diffraction fringes of a grating-like source are accurately predicted and that diffraction patterns of a ptychography dataset from an experiment with realistic parameters can be sampled well enough to be retrieved by a standard phase-retrieval algorithm. Potentials and limits of this approach are highlighted. It is suggested that it could be applied to study imperfect or non-standard CDI configurations lacking a satisfactory theoretical formulation. The considerable computational effort required by this method is justified by the great flexibility provided for easy simulation of a large-parameter space.
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Bauduin, S., L. Clarisse, J. Hadji-Lazaro, N. Theys, C. Clerbaux, and P. F. Coheur. "Retrieval of near-surface sulfur dioxide (SO<sub>2</sub>) concentrations at a global scale using IASI satellite observations." Atmospheric Measurement Techniques Discussions 8, no. 10 (October 26, 2015): 11029–75. http://dx.doi.org/10.5194/amtd-8-11029-2015.
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Abstract. SO2 from volcanic eruptions is now operationally monitored from space in both ultraviolet (UV) and thermal infrared (TIR) spectral range, but anthropogenic SO2 has almost solely been measured from UV sounders. Indeed, TIR instruments are well-known to have a poor sensitivity to the boundary layer (PBL), due to generally low thermal contrast (TC) between the ground and the air above it. Recent studies have demonstrated the capability of the Infrared Atmospheric Sounding Interferometer (IASI) to measure near-surface SO2 locally, for specific atmospheric conditions. In this work, we develop a retrieval method allowing the inference of SO2 near-surface concentrations from IASI measurements at a global scale. This method consists of two steps. Both are based on the computation of radiance indexes representing the strength of the SO2 ν3 band in IASI spectra. The first step allows retrieving the peak altitude of SO2 and selecting near-surface SO2. In the second step, 0–4 km columns of SO2 are inferred using a look-up table (LUT) approach. Using this new retrieval method, we obtain the first global distribution of near-surface SO2 from IASI-A, and identify the dominant anthropogenic hotspot sources and volcanic degassing. The 7-year daily time evolution of SO2 columns above two industrial source areas (Beijing in China and Sar Cheshmeh in Iran) is investigated and correlated to the seasonal variations of the parameters that drive the IASI sensitivity to the PBL composition. Apart from TC, we show that humidity is the most important parameter which determines IR sensitivity to near-surface SO2. As IASI provides twice daily global measurements, the differences between the retrieved columns for the morning and evening orbits are investigated. This paper finally presents a first intercomparison of the measured 0–4 km columns with an independent iterative retrieval method and with observations of the Ozone Monitoring Instrument (OMI).
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Dos Santos, Leonardo A., Aline A. Vidotto, Shreyas Vissapragada, Munazza K. Alam, Romain Allart, Vincent Bourrier, James Kirk, Julia V. Seidel, and David Ehrenreich. "p-winds: An open-source Python code to model planetary outflows and upper atmospheres." Astronomy & Astrophysics 659 (March 2022): A62. http://dx.doi.org/10.1051/0004-6361/202142038.
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Atmospheric escape is considered to be one of the main channels for evolution in sub-Jovian planets, particularly in their early lives. While there are several hypotheses proposed to explain escape in exoplanets, testing them with atmospheric observations remains a challenge. In this context, high-resolution transmission spectroscopy of transiting exoplanets for the metastable helium triplet (He 23S) at 1083 nm has emerged as a reliable technique for observing and measuring escape. To aid in the prediction and interpretation of metastable He transmission spectroscopy observations, we developed the code p-winds. This is an open-source, fully documented, scalable Python implementation of the one-dimensional, purely H+He Parker wind model for upper atmospheres coupled with ionization balance, ray-tracing, and radiative transfer routines. We demonstrate an atmospheric retrieval by fitting p-winds models to the observed metastable He transmission spectrum of the warm Neptune HAT-P-11 b and take the variation in the in-transit absorption caused by transit geometry into account. For this planet, our best fit yields a total atmospheric escape rate of approximately 2.5 × 1010 g s−1 and an outflow temperature of 7200 K. The range of retrieved mass loss rates increases significantly when we let the H atom fraction be a free parameter, but its posterior distribution remains unconstrained by He observations alone. The stellar host limb darkening does not have a significant impact on the retrieved escape rate or outflow temperature for HAT-P-11 b. Based on the non-detection of escaping He for GJ 436 b, we are able to rule out total escape rates higher than 3.4 × 1010 g s−1 at 99.7% (3σ) confidence.
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Bauduin, Sophie, Lieven Clarisse, Juliette Hadji-Lazaro, Nicolas Theys, Cathy Clerbaux, and Pierre-François Coheur. "Retrieval of near-surface sulfur dioxide (SO<sub>2</sub>) concentrations at a global scale using IASI satellite observations." Atmospheric Measurement Techniques 9, no. 2 (February 29, 2016): 721–40. http://dx.doi.org/10.5194/amt-9-721-2016.
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Abstract. SO2 from volcanic eruptions is now operationally monitored from space in both the ultraviolet (UV) and thermal infrared (TIR) spectral range, but anthropogenic SO2 has almost solely been measured from UV sounders. Indeed, TIR instruments are well known to have a poor sensitivity to the planetary boundary layer (PBL), due to generally low thermal contrast (TC) between the ground and the air above it. Recent studies have demonstrated the capability of the Infrared Atmospheric Sounding Interferometer (IASI) to measure near-surface SO2 locally, for specific atmospheric conditions. In this work, we develop a retrieval method allowing the inference of SO2 near-surface concentrations from IASI measurements at a global scale. This method consists of two steps. Both are based on the computation of radiance indexes representing the strength of the SO2 ν3 band in IASI spectra. The first step allows the peak altitude of SO2 to be retrieved and near-surface SO2 to be selected. In the second step, 0–4 km columns of SO2 are inferred using a look-up table (LUT) approach. Using this new retrieval method, we obtain the first global distribution of near-surface SO2 from IASI-A, and identify the dominant anthropogenic hotspot sources and volcanic degassing. The 7-year daily time evolution of SO2 columns above two industrial source areas (Beijing in China and Sar Cheshmeh in Iran) is investigated and correlated to the seasonal variations of the parameters that drive the IASI sensitivity to the PBL composition. Apart from TC, we show that humidity is the most important parameter which determines IR sensitivity to near-surface SO2 in the ν3 band. As IASI provides global measurements twice daily, the differences between the retrieved columns for the morning and evening orbits are investigated. This paper finally presents a first intercomparison of the measured 0–4 km columns with an independent iterative retrieval method and with observations of the Ozone Monitoring Instrument (OMI).
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Smallman, Thomas Luke, David Thomas Milodowski, Eráclito Sousa Neto, Gerbrand Koren, Jean Ometto, and Mathew Williams. "Parameter uncertainty dominates C-cycle forecast errors over most of Brazil for the 21st century." Earth System Dynamics 12, no. 4 (November 23, 2021): 1191–237. http://dx.doi.org/10.5194/esd-12-1191-2021.
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Abstract. Identification of terrestrial carbon (C) sources and sinks is critical for understanding the Earth system as well as mitigating and adapting to climate change resulting from greenhouse gas emissions. Predicting whether a given location will act as a C source or sink using terrestrial ecosystem models (TEMs) is challenging due to net flux being the difference between far larger, spatially and temporally variable fluxes with large uncertainties. Uncertainty in projections of future dynamics, critical for policy evaluation, has been determined using multi-TEM intercomparisons, for various emissions scenarios. This approach quantifies structural and forcing errors. However, the role of parameter error within models has not been determined. TEMs typically have defined parameters for specific plant functional types generated from the literature. To ascertain the importance of parameter error in forecasts, we present a Bayesian analysis that uses data on historical and current C cycling for Brazil to parameterise five TEMs of varied complexity with a retrieval of model error covariance at 1∘ spatial resolution. After evaluation against data from 2001–2017, the parameterised models are simulated to 2100 under four climate change scenarios spanning the likely range of climate projections. Using multiple models, each with per pixel parameter ensembles, we partition forecast uncertainties. Parameter uncertainty dominates across most of Brazil when simulating future stock changes in biomass C and dead organic matter (DOM). Uncertainty of simulated biomass change is most strongly correlated with net primary productivity allocation to wood (NPPwood) and mean residence time of wood (MRTwood). Uncertainty of simulated DOM change is most strongly correlated with MRTsoil and NPPwood. Due to the coupling between these variables and C stock dynamics being bi-directional, we argue that using repeat estimates of woody biomass will provide a valuable constraint needed to refine predictions of the future carbon cycle. Finally, evaluation of our multi-model analysis shows that wood litter contributes substantially to fire emissions, necessitating a greater understanding of wood litter C cycling than is typically considered in large-scale TEMs.
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Ye, Xin, Huazhong Ren, Pengxin Wang, Zhongqiu Sun, and Jian Zhu. "Mid-Infrared Emissivity Retrieval from Nighttime Sentinel-3 SLSTR Images Combining Split-window Algorithms and the Radiance Transfer Method." International Journal of Environmental Research and Public Health 20, no. 1 (December 20, 2022): 37. http://dx.doi.org/10.3390/ijerph20010037.
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Land surface emissivity is a key parameter that affects energy exchange and represents the spectral characteristics of land cover. Large-scale mid-infrared (MIR) emissivity can be efficiently obtained using remote sensing technology, but current methods mainly rely on prior knowledge and multi-temporal or multi-angle remote sensing images, and additional errors may be introduced due to the uncertainty of external data such as atmospheric profiles and the inconsistency of multiple source data in spatial resolution, observation time, and other information. In this paper, a new practical method was proposed which can retrieve MIR emissivity with only a single image input by combining the radiance properties of TIR and MIR channels and the spatial information of remote sensing images based on the Sentinel-3 Sea and land surface temperature radiometer (SLSTR) data. Two split-window (SW) algorithms that use TIR channels only and MIR and TIR channels to retrieve land surface temperature (LST) were developed separately, and the initial values of MIR emissivity were obtained from the known LST and TIR emissivity. Under the assumption that the atmospheric conditions in the local area are constant, the radiance transfer equations for adjacent pixels are iterated to optimize the initial values to obtain stable estimation results. The experimental results based on the simulation dataset and real SLSTR images showed that the proposed method can achieve accurate MIR emissivity results. In future work, factors such as angular effects, solar radiance, and the influence of atmospheric water vapor will be further considered to improve performance.
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Guo, Lijie, Liangke Huang, Junyu Li, Lilong Liu, Ling Huang, Bolin Fu, Shaofeng Xie, Hongchang He, and Chao Ren. "A Comprehensive Evaluation of Key Tropospheric Parameters from ERA5 and MERRA-2 Reanalysis Products Using Radiosonde Data and GNSS Measurements." Remote Sensing 13, no. 15 (July 30, 2021): 3008. http://dx.doi.org/10.3390/rs13153008.
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Tropospheric delay is a major error source in the Global Navigation Satellite System (GNSS), and the weighted mean temperature (Tm) is a key parameter in precipitable water vapor (PWV) retrieval. Although reanalysis products like the National Centers for Environmental Prediction (NCEP) and the European Center for Medium-Range Weather Forecasts (ECMWF) Re-Analysis-Interim (ERA-Interim) data have been used to calculate and model the tropospheric delay, Tm, and PWV, the limitations of the temporal and spatial resolutions of the reanalysis data have affected their performance. The release of the fifth-generation accurate global atmospheric reanalysis (ERA5) and the second Modern-Era Retrospective analysis for Research and Applications (MERRA-2) provide the opportunity to overcome these limitations. The performances of the zenith tropospheric delay (ZTD), zenith wet delay (ZWD), Tm, and zenith hydrostatic delay (ZHD) of ERA5 and MERRA-2 data from 2016 to 2017 were evaluated in this work using GNSS ZTD and radiosonde data over the globe. Taking GNSS ZTD as a reference, the ZTD calculated from MERRA-2 and ERA5 pressure-level data were evaluated in temporal and spatial scales, with an annual mean bias and root mean square (RMS) of 2.3 and 10.9 mm for ERA5 and 4.5 and 13.1 mm for MERRA-2, respectively. Compared to radiosonde data, the ZHD, ZWD, and Tm derived from ERA5 and MERRA-2 data were also evaluated on temporal and spatial scales, with annual mean bias values of 1.1, 1.7 mm, and 0.14 K for ERA5 and 0.5, 4.8 mm, and –0.08 K for MERRA-2, respectively. Meanwhile, the annual mean RMS was 4.5, 10.5 mm, and 1.03 K for ERA5 and 4.4, 13.6 mm, and 1.17 K for MERRA-2, respectively. Tropospheric parameters derived from MERRA-2 and ERA5, with improved temporal and spatial resolutions, can provide a reference for GNSS positioning and PWV retrieval.
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Chernyshov, Pavel, Katrin Hessner, Andrey Zavadsky, and Yaron Toledo. "On the Effect of Interferences on X-Band Radar Wave Measurements." Sensors 22, no. 10 (May 18, 2022): 3818. http://dx.doi.org/10.3390/s22103818.
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X-band radars are in growing use for various oceanographic purposes, providing spatial real-time information about sea state parameters, surface elevations, currents, and bathymetry. Therefore, it is very appealing to use such systems as operational aids to harbour management. In an installation of such a remote sensing system in Haifa Port, consistent radially aligned spikes of brightness randomly distributed with respect to azimuth were identified. These streak noise patterns were found to be interfering with the common approach of oceanographic analysis. Harbour areas are regularly frequented with additional electromagnetic transmissions from other ship and land-based radars, which may serve as a source of such interference. A new approach is proposed for the filtering of such undesirable interference patterns from the X-band radar images. It was verified with comparison to in-situ measurements of a nearby wave buoy. Regardless of the actual source of the corresponding pseudo-wave energy, it was found to be crucial to apply such filtration in order to improve the performance of the standard oceanographic parameter retrieval algorithm. This results in better estimation of the mean sea state parameters towards lower values of the significant wave height. For the commercial WaMoSII system this enhancement was clearly apparent in the improvement of the built-in quality control criteria marks. The developed prepossessing procedure improves the robustness of the directional spectra estimation practically eliminating pseudo-wave energy components. It also extends the system’s capability to measure storm events earlier on, a fact that is of high importance for harbour operational decision making.
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Kalms, Lester, Pedram Amini Rad, Muhammad Ali, Arsany Iskander, and Diana Göhringer. "A Parametrizable High-Level Synthesis Library for Accelerating Neural Networks on FPGAs." Journal of Signal Processing Systems 93, no. 5 (March 15, 2021): 513–29. http://dx.doi.org/10.1007/s11265-021-01651-5.
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AbstractIn recent years, Convolutional Neural Network CNN have been incorporated in a large number of applications, including multimedia retrieval and image classification. However, CNN based algorithms are computationally and resource intensive and therefore difficult to be used in embedded systems. FPGA based accelerators are becoming more and more popular in research and industry due to their flexibility and energy efficiency. However, the available resources and the size of the on-chip memory can limit the performance of the FPGA accelerator for CNN. This work proposes an High-Level Synthesis HLS library for CNN algorithms. It contains seven different streaming-capable CNN (plus two conversion) functions for creating large neural networks with deep pipelines. The different functions have many parameter settings (e.g. for resolution, feature maps, data types, kernel size, parallelilization, accuracy, etc.), which also enable compile-time optimizations. Our functions are integrated into the HiFlipVX library, which is an open source HLS FPGA library for image processing and object detection. This offers the possibility to implement different types of computer vision applications with one library. Due to the various configuration and parallelization possibilities of the library functions, it is possible to implement a high-performance, scalable and resource-efficient system, as our evaluation of the MobileNets algorithm shows.
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Muckenhuber, Stefan, and Stein Sandven. "Open-source sea ice drift algorithm for Sentinel-1 SAR imagery using a combination of feature tracking and pattern matching." Cryosphere 11, no. 4 (August 7, 2017): 1835–50. http://dx.doi.org/10.5194/tc-11-1835-2017.
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Abstract. An open-source sea ice drift algorithm for Sentinel-1 SAR imagery is introduced based on the combination of feature tracking and pattern matching. Feature tracking produces an initial drift estimate and limits the search area for the consecutive pattern matching, which provides small- to medium-scale drift adjustments and normalised cross-correlation values. The algorithm is designed to combine the two approaches in order to benefit from the respective advantages. The considered feature-tracking method allows for an efficient computation of the drift field and the resulting vectors show a high degree of independence in terms of position, length, direction and rotation. The considered pattern-matching method, on the other hand, allows better control over vector positioning and resolution. The preprocessing of the Sentinel-1 data has been adjusted to retrieve a feature distribution that depends less on SAR backscatter peak values. Applying the algorithm with the recommended parameter setting, sea ice drift retrieval with a vector spacing of 4 km on Sentinel-1 images covering 400 km × 400 km, takes about 4 min on a standard 2.7 GHz processor with 8 GB memory. The corresponding recommended patch size for the pattern-matching step that defines the final resolution of each drift vector is 34 × 34 pixels (2.7 × 2.7 km). To assess the potential performance after finding suitable search restrictions, calculated drift results from 246 Sentinel-1 image pairs have been compared to buoy GPS data, collected in 2015 between 15 January and 22 April and covering an area from 80.5 to 83.5° N and 12 to 27° E. We found a logarithmic normal distribution of the displacement difference with a median at 352.9 m using HV polarisation and 535.7 m using HH polarisation. All software requirements necessary for applying the presented sea ice drift algorithm are open-source to ensure free implementation and easy distribution.
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Du, Wenhui, Zhihao Qin, Jinlong Fan, Chunliang Zhao, Qiuyan Huang, Kun Cao, and Bilawal Abbasi. "Land Surface Temperature Retrieval from Fengyun-3D Medium Resolution Spectral Imager II (FY-3D MERSI-II) Data with the Improved Two-Factor Split-Window Algorithm." Remote Sensing 13, no. 24 (December 14, 2021): 5072. http://dx.doi.org/10.3390/rs13245072.
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Land surface temperature (LST) is an essential parameter widely used in environmental studies. The Medium Resolution Spectral Imager II (MERSI-II) boarded on the second generation Chinese polar-orbiting meteorological satellite, Fengyun-3D (FY-3D), provides a new opportunity for LST retrieval at a spatial resolution of 250 m that is higher than that of the already widely used Moderate Resolution Imaging Spectrometer (MODIS) LST data of 1000 m. However, there is no operational LST product from FY-3D MERSI-II data available for free access. Therefore, in this study, we developed an improved two-factor split-window algorithm (TFSWA) of LST retrieval from this data source as it has two thermal-infrared (TIR) bands. The essential coefficients of the TFSWA algorithm have been carefully and precisely estimated for the FY-3D MERSI-II TIR thermal bands. A new approach for estimating land surface emissivity has been developed using the ASTER Global Emissivity Database (ASTER GED) and the International Geosphere-Biosphere Program (IGBP) data. A model to estimate the atmospheric water vapor content (AWVC) from the three atmospheric water vapor absorption bands (bands 16, 17, and 18) has been developed as AWVC has been recognized as the most important factor determining the variation of AT. Using MODTRAN 5.2, the equations for the AT estimate from the retrieved AWVC were established. In addition, the AT of the pixels at the far edge of FY-3D MERSI-II data may be strongly affected by the increase of the optical path. Viewing zenith angle (VZA) correction equations were proposed in the study to correct this effect on AT estimation. Field data from four stations were applied to validate the improved TFSWA in the study. Cross-validation with MODIS LST (MYD11) was also conducted to evaluate the improved TFSWA. The cross-validation result indicates that the FY-3D MERSI-II LST from the improved TFSWA are comparable with MODIS LST while the correlation coefficients between FY-3D MERSI-II LST and MODIS LST over the Mid-East China region are in the range of 0.84~0.98 for different seasons and land cover types. Validation with 318 field LST samples indicates that the average MAE and R2 of the scenes at the four stations are about 1.97 K and 0.98, respectively. Thus, it could be concluded that the improved TFSWA developed in the study can be a good algorithm for LST retrieval from FY-3D MERSI-II data with acceptable accuracy.
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Lu, Li, Zhaoning Gong, Yanan Liang, and Shuang Liang. "Retrieval of Chlorophyll-a Concentrations of Class II Water Bodies of Inland Lakes and Reservoirs Based on ZY1-02D Satellite Hyperspectral Data." Remote Sensing 14, no. 8 (April 12, 2022): 1842. http://dx.doi.org/10.3390/rs14081842.
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Chlorophyll-a is an important parameter that characterizes the eutrophication of water bodies. The advantage of ZY1-02D hyperspectral satellite subdivision in the visible light and near-infrared bands is that it highlights the unique characteristics of water bodies in the spectral dimension, and it helps to assess the Class II water bodies of inland lakes and reservoirs, making it an important tool for refined remote sensing detection of the environment. In this study, the Baiyangdian Nature Reserve in northern China, which contains a typical inland lake and wetland, was chosen as the study area. Using ZY1-02D hyperspectral synchronization transit images and in situ measured chlorophyll-a concentration as the data source, remote sensing of the chlorophyll-a concentration of inland lakes was conducted. By analyzing the correlation between the spectral reflectance of the ZY1-02D hyperspectral image and the chlorophyll-a concentration and using algorithms such as the single band, band ratio, and three bands to compare and filter characteristic wavelengths, a quantitative hyperspectral model of the chlorophyll-a concentration was established to determine the chlorophyll-a concentration of Baiyangdian Lake. The dynamic monitoring of the water body and the assessment of the nutritional status of the water body were determined. The results revealed that the estimation of the chlorophyll-a concentration of Baiyangdian Lake based on the hyperspectral Fluorescence Line Height (FLH) model was ideal, with an R2 value of 0.78. The FLH model not only comprehensively considers the effects of suspended solids, yellow substances, and backscattering of the water body on the estimation of the chlorophyll-a concentration, but also considers the influence of the elastic scattering efficiency of the chlorophyll. Based on the ZY1-02D hyperspectral data, a spatial distribution map of the chlorophyll-a concentration of Baiyangdian Lake was created to provide new ideas and technical support for monitoring inland water environments.
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Wu, Ying, Bo Qian, Yansong Bao, George P. Petropoulos, Xulin Liu, and Lin Li. "Microwave Land Emissivity Calculations over the Qinghai-Tibetan Plateau Using FY-3B/MWRI Measurements." Remote Sensing 11, no. 19 (September 20, 2019): 2206. http://dx.doi.org/10.3390/rs11192206.
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The Qinghai-Tibetan plateau plays an important role in climate change with its unique characteristics, and the surface emissivity is an important parameter to describe the surface characteristics. It is also very important for the accurate retrieval of surface and atmospheric parameters. Different types of surface features have their own radiation characteristics due to their differences in structure, water content and roughness. In this study, the microwave land surface emissivity (10.65, 18.7, 23.8, 36.5 and 89 GHz) of the Qinghai-Tibetan Plateau was calculated using the simplified microwave radiation transmission equation under clear atmospheric conditions based on Level 1 brightness temperatures from the Microwave Radiation Imager onboard the FY-3B meteorological satellite (FY-3B/MWRI) and the National Centers for Environmental Prediction Final (NCEP-FNL) Global Operational Analysis dataset. Furthermore, according to the IGBP (International Geosphere-Biosphere Program) classified data, the spectrum and spatial distribution characteristics of microwave surface emittance in Qinghai-Tibetan plateau were further analyzed. The results show that almost all 16 types of emissivity from IGBP at dual-polarization (vertical and horizontal) increase with the increase of frequency. The spatial distribution of the retrieving results is in line with the changes of surface cover types on the Qinghai-Tibetan plateau, showing the distribution characteristics of large polarization difference of surface emissivity in the northwest and small polarization difference in the southeast, and diverse vegetation can be clearly seen in the retrieving results. In addition, the emissivity is closely related to the type of land surface. Since the emissivity of vegetation is higher than that of bare soil, the contribution of bare soil increases and the surface emissivity decreases as the density of vegetation decreases. Finally, the source of retrieval error was analyzed. The errors in calculating the surface emissivity might mainly come from spatiotemporal collocation of reanalysis data with satellite measurements, the quality of these auxiliary datasets and cloud and precipitation pixel discrimination scheme. Further quantitative analysis of these errors is required, and even standard procedures may need to be improved as well to improve the accuracy of the calculation.
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Pisanti, A., S. Magrì, I. Ferrando, and B. Federici. "SEA WATER TURBIDITY ANALYSIS FROM SENTINEL-2 IMAGES: ATMOSPHERIC CORRECTION AND BANDS CORRELATION." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-4/W1-2022 (August 6, 2022): 371–78. http://dx.doi.org/10.5194/isprs-archives-xlviii-4-w1-2022-371-2022.
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Abstract. Turbidity is a visual property of water, related to the presence of suspended particles in waters. This parameter is measured in different water quality monitoring programmes as it can determine negative environmental effects both on the biotic and abiotic marine ecosystem. Traditional methods, e.g., in situ monitoring, offer high accuracy but provide sparse information in space and time. On the other hand, Earth Observation (EO) techniques have the potential to provide a comprehensive, fast and inexpensive monitoring system to observe the biophysical and biochemical conditions of water bodies. In the present work, a method for seawater turbidity retrieval from Sentinel-2 multispectral optical images, freely available within the EU Copernicus programme, is presented. The study explores different atmospheric correction methods available in open source software (QGIS, GRASS GIS and SNAP), in order to convert Level-1C (L1C) Top-Of-Atmosphere (TOA) images to Level-2A (L2A) Bottom-Of-Atmosphere (BOA), when the latter is not directly available. Once the proper method for atmospheric correction was identified and applied, the correlation between the in situ dataset and the individual bands known to be most sensitive to water turbidity, i.e., blue (B2), green (B3), red (B4) and near infrared (B8 and B8A) bands, were investigated and a linear regression model between selected band values and turbidity was identified.
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Zhang, Hu, Jing Li, Qinhuo Liu, Yadong Dong, Songze Li, Zhaoxing Zhang, Xinran Zhu, Liangyun Liu, and Jing Zhao. "Estimating Leaf Area Index with Dynamic Leaf Optical Properties." Remote Sensing 13, no. 23 (December 2, 2021): 4898. http://dx.doi.org/10.3390/rs13234898.
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Leaf area index (LAI) plays an important role in models of climate, hydrology, and ecosystem productivity. The physical model-based inversion method is a practical approach for large-scale LAI inversion. However, the ill-posed inversion problem, due to the limited constraint of inaccurate input parameters, is the dominant source of inversion errors. For instance, variables related to leaf optical properties are always set as constants or have large ranges, instead of the actual leaf reflectance of pixel vegetation in the current model-based inversions. This paper proposes to estimate LAI with the actual leaf optical property of pixels, calculated from the leaf chlorophyll content (Chlleaf) product, using a three-dimensional stochastic radiative transfer model (3D-RTM)-based, look-up table method. The parameter characterizing leaf optical properties in the 3D-RTM-based LAI inversion algorithm, single scattering albedo (SSA), is calculated with the Chlleaf product, instead of setting fixed values across a growing season. An algorithm to invert LAI with the dynamic SSA of the red band (SSAred) is proposed. The retrieval index (RI) increases from less than 42% to 100%, and the RMSE decreases to less than 0.28 in the simulations. The validation results show that the RMSE of the dynamic SSA decreases from 1.338 to 0.511, compared with the existing 3D-RTM-based LUT algorithm. The overestimation problem under high LAI conditions is reduced.
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Puthukkudy, Anin, J. Vanderlei Martins, Lorraine A. Remer, Xiaoguang Xu, Oleg Dubovik, Pavel Litvinov, Brent McBride, Sharon Burton, and Henrique M. J. Barbosa. "Retrieval of aerosol properties from Airborne Hyper-Angular Rainbow Polarimeter (AirHARP) observations during ACEPOL 2017." Atmospheric Measurement Techniques 13, no. 10 (October 5, 2020): 5207–36. http://dx.doi.org/10.5194/amt-13-5207-2020.
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Abstract. Multi-angle polarimetric (MAP) imaging of Earth scenes can be used for the retrieval of microphysical and optical parameters of aerosols and clouds. The Airborne Hyper-Angular Rainbow Polarimeter (AirHARP) is an aircraft MAP instrument with a hyper-angular imaging capability of 60 along-track viewing angles at 670 nm and 20 along-track viewing angles at other wavelengths – 440, 550, and 870 nm – across the full 114∘ (94∘) along-track (cross-track) field of view. Here we report the retrieval of aerosol properties using the Generalized Retrieval of Aerosols and Surface Properties (GRASP) algorithm applied to AirHARP observations collected during the NASA Aerosol Characterization from Polarimeter and Lidar (ACEPOL) campaign in October–November 2017. The retrieved aerosol properties include spherical fraction (SF), aerosol column concentration in multiple size distribution modes, and, with sufficient aerosol loading, complex aerosol refractive index. From these primary retrievals, we derive aerosol optical depth (AOD), Angstrom exponent (AE), and single scattering albedo (SSA). AODs retrieved from AirHARP measurements are compared with the High Spectral Resolution LiDAR-2 (HSRL2) AOD measurements at 532 nm and validated with measurements from collocated Aerosol Robotic NETwork (AERONET) stations. A good agreement with HSRL2 (ρ=0.940, |BIAS|=0.062, mean absolute error (MAE) = 0.122) and AERONET AOD (0.010≤MAE≤0.015, 0.002≤|BIAS|≤0.009) measurements is observed for the collocated points. There was a mismatch between the HSRL2- and AirHARP-retrieved AOD for the pixels close to the forest fire smoke source and to the edges of the plume due to spatial mismatch in the sampling. This resulted in a higher BIAS and MAE for the HSRL2 AOD comparison. For the case of AERONET AOD comparison, two different approaches are used in the GRASP retrievals, and the simplified aerosol component-based GRASP/Models kernel which retrieves fewer number of aerosol parameter performed well compared to a more generous GRASP/Five mode approach in the low aerosol loading cases. Forest fire smoke intercepted during ACEPOL provided a situation with homogenous plume and sufficient aerosol loading to retrieve the real part of the refractive index (RRI) of 1.55 and the imaginary part of the refractive index (IRI) of 0.024. The derived SSAs for this case are 0.87, 0.86, 0.84, and 0.81 at wavelengths of 440, 550, 670, and 870 nm, respectively. Finer particles with an average AE of 1.53, a volume median radius of 0.157 µm, and a standard deviation (SD) of 0.55 for fine mode is observed for the same smoke plume. These results serve as a proxy for the scale and detail of aerosol retrievals that are anticipated from future space mission data, as HARP CubeSat (mission begins 2020) and HARP2 (aboard the NASA PACE mission with launch in 2023) are near duplicates of AirHARP and are expected to provide the same level of aerosol characterization.
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Agustang, Agustang, Sri Mulyani, and Erni Indrawati. "ANALISIS KELAYAKAN LAHAN BUDIDAYA RUMPUT LAUT GRACILARIA sp DI TAMBAK KECAMATAN SINJAI UTARA KABUPATEN SINJAI." Journal of Aquaculture and Environment 2, no. 1 (December 9, 2019): 18–22. http://dx.doi.org/10.35965/jae.v2i1.332.
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Rumput laut Gracilaria sp merupakan sumber pangan dan memiliki nilai ekonomis tinggi sebagai sumber devisa serta usaha padat karya yang mampu menyerap banyak tenaga kerja. Penelitian ini bertujuan untuk mengetahui karakteristik dan tingkat kelayakan lahan tambak untuk budidaya rumput laut (Gracilaria sp) berdasarkan parameter fisika (Suhu, ,kedalaman dan kecerahan) dan kimia (salinitas, pH, oksigen terlarut, CO2,nitrat dan fosfat). Populasi dalam penelitian ini adalah kawasan tambak yang ada di Kecamatan Sinjai Utara Kabupaten Sinjai, sampelnya sebanyak 3 titik/stasiun pengamatan ditentukan dengan menggunakan metode purposive sampling berdasarkan letak dan sumber air tambak. Data hasil penelitian diperoleh dengan pengamatan, pengukuran langsung dilapangan(suhu, salinitas, kedalaman, kecerahan, oksigen terlarut dan pH) dan analisis laboratorium (fosfat, nitrat,) kemudian dianalisis dengan menggunakan metode pembobotan. Setelah diperoleh nilai skor dari setiap parameter pada setiap titik pengamatan, kemudian dilakukan penilaian yakni layak (S1) dengan kisaran nilai 68-87, cukup layak (S2) dengan kisaran nilai 48-67, dan tidak layak (N) dengan kisaran nilai 27-47.Hasil diperoleh bahwa ketiga stasiun masuk kategori cukup layak (S2) dengan nilai stasiun I (63), stasiun II (56) dan stasiun III (63). Dengan demikian kegiatan budidaya rumput laut Gracillaria sp cukup layak untuk dikembangkan di Kecamatan Sinjai Utara.
Seaweed Gracilaria sp is a source of food and having economic value high as a source of foreign exchange and efforts labor-intensive capable of absorbing a lot of labor. Research aims to understand the characteristics and the feasibility land farms to seaweed cultivation (gracilaria sp) based on physical parameters (temperature, deepness and brightness) and chemistry (salinitas , pH, oxygen dissolved,carbon dioxide, nitrate and phosphate). Population in this study of the farms in Sinjai sub district north, sample as many as 3 points/an observation station determined by using the method purposive sampling based on the layout and water sources farms. The data the results of the study obtained with the observation, the measurement of directly field (the temperature of, salinitas, depth, brightness, oxygen dissolved and pH) and an analysis of lab where internal conditions (phosphate, nitrate) then analyzed in order by using the method the weightings of the. After the recent retrieval of the value of a score of every parameter on each the point of observation, then be a assessment of bond issuance will be worthy of (s1) with a range of the value of 68-87, seemed worthy enough to operate ( s2 ) with a range of the value of 48-67 , but it is not suitable ( n ) with a range of the value of 27-47. Result obtained that all three renovation of the gas station is categorized as a seemed worthy enough to operate ( s2 ) with a value of up the first three months of station ( 63 ), renovation of the gas station II ( 56 ) and train stations III (63). As a result of this activities are to be implemented seaweed cultivation gracillaria sp seemed worthy enough to operate to be developed in Sinjai sub district north.
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Rooney, Caoimhe M., Natasha E. Batalha, Peter Gao, and Mark S. Marley. "A New Sedimentation Model for Greater Cloud Diversity in Giant Exoplanets and Brown Dwarfs." Astrophysical Journal 925, no. 1 (January 1, 2022): 33. http://dx.doi.org/10.3847/1538-4357/ac307a.
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Abstract The observed atmospheric spectrum of exoplanets and brown dwarfs depends critically on the presence and distribution of atmospheric condensates. The Ackerman and Marley methodology for predicting the vertical distribution of condensate particles is widely used to study cloudy atmospheres and has recently been implemented in an open-source python package, Virga. The model relies upon input parameter f sed, the sedimentation efficiency, which until now has been held constant. The relative simplicity of this model renders it useful for retrieval studies due to its rapidly attainable solutions. However, comparisons with more complex microphysical models such as CARMA have highlighted inconsistencies between the two approaches, namely that the cloud parameters needed for radiative transfer produced by Virga are dissimilar to those produced by CARMA. To address these discrepancies, we have extended the original Ackerman and Marley methodology in Virga to allow for non-constant f sed values, in particular, those that vary with altitude. We discuss one such parameterization and compare the cloud mass mixing ratio produced by Virga with constant and variable f sed profiles to that produced by CARMA. We find that the variable f sed formulation better captures the profile produced by CARMA with heterogeneous nucleation, yet performs comparatively to constant f sed for homogeneous nucleation. In general, Virga has the capacity to handle any f sed with an explicit anti-derivative, permitting a plethora of alternative cloud profiles that are otherwise unattainable by constant f sed values. The ensuing flexibility has the potential to better agree with increasingly complex models and observed data.
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Yang, Yanqing, Jianyun Zhang, Zhenxin Bao, Tianqi Ao, Guoqing Wang, Houfa Wu, and Jie Wang. "Evaluation of Multi-Source Soil Moisture Datasets over Central and Eastern Agricultural Area of China Using In Situ Monitoring Network." Remote Sensing 13, no. 6 (March 19, 2021): 1175. http://dx.doi.org/10.3390/rs13061175.
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Multi-source soil moisture (SM) products provide a vigorous tool for the estimation of soil moisture on a large scale, but it is crucial to carry out the evaluation of those products before further application. In the present work, an evaluation framework on multi-source SM datasets over central and eastern agricultural areas of China was firstly proposed, based on a dense in situ SM monitoring network of 838 stations from 11 July 2012 to 31 December 2017. Each station adopted the most accurate gravimetric method for measuring the actual soil moisture. The effects of land use types and wet–dry conditions on the performances of multi-source SM products were further analyzed. Most satellite/reanalysis SM products could capture the spatial–temporal changes in soil moisture, especially for ERA5 products that matched the closest to the station-measured SM; by contrast, those satellite products showed poor spatial–temporal performances. Such phenomenon was also quantitatively demonstrated by the four statistical metrics correlation coefficient (CC), p-value, bias and root mean squared error (RMSE) between the satellite/reanalysis SM products and the ground-observed SM series. Further, most satellite/reanalysis SM products had poor performances in Forestland and Grassland areas, with a lower CC and a larger positive bias and RMSE. Such overestimation on soil moisture is possibly influenced by the inestimable parameter vegetation geometry and the vegetation water content in the radiative transfer models. The arid areas showed the worst CC between the station-observed SM data and different satellite/reanalysis SM products; meanwhile, the humid and semi-arid areas presented larger SM estimation errors than the other areas, especially for the satellite products. The fairly dry surface soil (arid area) and open water surface contamination (humid area) are suggested to hinder the reading of microwave-based retrieval systems. Additionally, the reanalysis SM products outperformed the satellite SM products in the evaluated areas, with better spatial–temporal performances, seasonality reflection and higher accuracy on SM estimation (higher CC, and lower bias and RMSE). This is because the reanalysis datasets assimilated various sources of datasets, especially the ground-observed data, with high quality. The evaluated results could provide guidance for fusing different satellite/reanalysis products, as a new feasible alternative to monitoring SM information in the future.
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Gallegos, Andrea, and Jiakang Xie. "A multichannel deconvolution method to retrieve source–time functions: application to the regional Lg wave." Geophysical Journal International 223, no. 1 (June 25, 2020): 323–47. http://dx.doi.org/10.1093/gji/ggaa303.
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SUMMARY The retrieval of high-frequency seismic source–time functions (STFs) of similar earthquakes tends to be an ill-posed problem, causing unstable solutions. This is particularly true when waveforms are complex and band-limited, such as the regional phase Lg. We present a new procedure implementing the multichannel deconvolution (MCD) method to retrieve robust and objective STF solutions. The procedure relies on well-developed geophysical inverse theory to obtain stable STF solutions that jointly minimize the residual misfit, model roughness and data underfitting. MCD is formulated as a least-squares inverse problem with a Tikhonov regularization. The problem is solved using a convex optimization algorithm which rapidly converges to the global minimum while accommodating physical solution constraints including positivity, causality, finiteness and known seismic moments. We construct two L-shaped curves showing how the solution residual and roughness vary with trial solution durations. The optimal damping is chosen when the curves have acceptable levels while exhibiting no oscillations caused by solution instability. The optimal solution duration is chosen to avoid a rapidly decaying segment of the residual curve caused by parameter underfitting. We apply the MCD method to synthetic Lg data constructed by convolving a real Lg waveform with five pairs of simulated STFs. Four pairs consist of single triangular or parabolic pulses. The remaining pair consists of multipulse STFs with a complex, four-spike large STF. Without noise, the larger STFs in all single-pulse cases are well-recovered with Tikhonov regularization. Shape distortions are minor and duration errors are within 5 per cent. The multipulse case is a rare well-posed problem for which the true STFs are recovered without regularization. When a noise of ∼20 per cent is added to the synthetic data, the MCD method retrieves large single-pulse STFs with minor shape distortions and small duration errors (from 0 to 18 per cent). For the multipulse case, the retrieved large STF is overly smeared, losing details in the later portion. The small STF solutions for all cases are less resilient. Finally, we apply the MCD method to Lg data from two pairs of moderate earthquakes in central Asia. The problem becomes more ill-posed owing to lower signal-to-noise ratios (as low as 3) and non-identical Green's functions. A shape constraint of the small STF is needed. For the larger events with M5.7 and 5.8, the retrieved STFs are asymmetric, rising sharply and lasting about 2.0 and 2.5 s. We estimate radiated energies of 2.47 × 1013 and 2.53 × 1013 J and apparent stresses of 1.4 and 1.9 MPa, which are very reasonable. Our results are very consistent with those obtained in a previous study that used a very different, less objective ‘Landweber deconvolution’ method and a pre-fixed small STF duration. Novel improvements made by our new procedure include the application of a convex algorithm rather than a Newton-like method, a procedure for simultaneously optimizing regularization and solution duration parameters, a shape constraint for the smaller STF, and application to the complex Lg wave.
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Luo, Chengcheng, Feng Xiao, Li Gong, Jintao Lei, Wenhao Li, and Shengkai Zhang. "Comparison of Weighted Mean Temperature in Greenland Calculated by Four Reanalysis Data." Remote Sensing 14, no. 21 (October 28, 2022): 5431. http://dx.doi.org/10.3390/rs14215431.
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The weighted mean temperature ( Tm) is a critical parameter for precipitable water vapor (PWV) retrieval in global navigation satellite system (GNSS) meteorology. Reanalysis data are an important data source for Tm calculation and Tm empirical model establishment. This study uses radiosonde data to evaluate the accuracy and the spatiotemporal variation of Tm that is derived from four reanalysis data, namely, the release of the fifth-generation accurate global atmospheric reanalysis (ERA5), the modern-era retrospective analysis for research and applications version 2 (MERRA-2), the NCEP/DOE, and the NCEP/NCAR, from 2005 to 2019 in Greenland, due to the paucity of research on the performance of Tm in the polar region that is derived from reanalysis data, particularly on a long temporal scale. The results were as follows: (1) The 15-year mean bias errors (MBEs) and root mean square errors (RMSEs) of Tm that were obtained from the four reanalysis data are 0.267 and 0.691 K for the ERA5, −0.247 and 0.962 K for the MERRA-2, 0.192 and 1.148 K for the NCEP/DOE, and −0.069 and 1.37 K for the NCEP/NCAR. The Tm that was derived from the ERA5 (ERA5 Tm) has the highest accuracy, followed by the MERRA-2 Tm, the NCEP/DOE Tm, and the NCEP/NCAR Tm. (2) In the inter-annual stability of the Tm precision compared with the radiosonde data, the results of the ERA5 are the most stable, followed by the NCEP/DOE Tm, the NCEP/NCAR Tm, and the MERRA-2 Tm. The ERA5 Tm have improved from 2005 to 2019. (3) The Tm accuracy that was computed by the four reanalysis data exhibits significant seasonal variation characteristics in Greenland, as follows: the summer and the autumn accuracy is higher than that in the winter and the spring, which may be related to the variation of the surface temperature (Ts) accuracy. (4) The Tm that was estimated from the four reanalysis data exhibits a consistent spatial distribution, as follows: the Tm is smaller in the middle region of Greenland and is greater at the island’s edge. The comparative study of Tm that is obtained from the four reanalysis data can serve as a reference for future research on Tm model development and water vapor retrieval in polar regions by utilizing reanalysis data.
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Vargas, David, Ivan Vasconcelos, Matteo Ravasi, and Nick Luiken. "Time-Domain Multidimensional Deconvolution: A Physically Reliable and Stable Preconditioned Implementation." Remote Sensing 13, no. 18 (September 15, 2021): 3683. http://dx.doi.org/10.3390/rs13183683.
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Multidimensional deconvolution constitutes an essential operation in a variety of geophysical scenarios at different scales ranging from reservoir to crustal, as it appears in applications such as surface multiple elimination, target-oriented redatuming, and interferometric body-wave retrieval just to name a few. Depending on the use case, active, microseismic, or teleseismic signals are used to reconstruct the broadband response that would have been recorded between two observation points as if one were a virtual source. Reconstructing such a response relies on the the solution of an ill-conditioned linear inverse problem sensitive to noise and artifacts due to incomplete acquisition, limited sources, and band-limited data. Typically, this inversion is performed in the Fourier domain where the inverse problem is solved per frequency via direct or iterative solvers. While this inversion is in theory meant to remove spurious events from cross-correlation gathers and to correct amplitudes, difficulties arise in the estimation of optimal regularization parameters, which are worsened by the fact they must be estimated at each frequency independently. Here we show the benefits of formulating the problem in the time domain and introduce a number of physical constraints that naturally drive the inversion towards a reduced set of stable, meaningful solutions. By exploiting reciprocity, time causality, and frequency-wavenumber locality a set of preconditioners are included at minimal additional cost as a way to alleviate the dependency on an optimal damping parameter to stabilize the inversion. With an interferometric redatuming example, we demonstrate how our time domain implementation successfully reconstructs the overburden-free reflection response beneath a complex salt body from noise-contaminated up- and down-going transmission responses at the target level.
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Perron, Christophe, Christian Katlein, Simon Lambert-Girard, Edouard Leymarie, Louis-Philippe Guinard, Pierre Marquet, and Marcel Babin. "Development of a diffuse reflectance probe for in situ measurement of inherent optical properties in sea ice." Cryosphere 15, no. 9 (September 24, 2021): 4483–500. http://dx.doi.org/10.5194/tc-15-4483-2021.
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Abstract. Detailed characterization of the spatially and temporally varying inherent optical properties (IOPs) of sea ice is necessary to better predict energy and mass balances, as well as ice-associated primary production. Here we present the development of an active optical probe to measure IOPs of a small volume of sea ice (dm3) in situ and non-destructively. The probe is derived from the diffuse reflectance method used to measure the IOPs of human tissues. The instrument emits light into the ice by the use of an optical fibre. Backscattered light is measured at multiple distances away from the source using several receiving fibres. Comparison to a Monte Carlo simulated lookup table allows, in theory, retrieval of the absorption coefficient, the reduced scattering coefficient and a phase function similarity parameter γ, introduced by Bevilacqua and Depeursinge (1999). γ depends on the two first moments of the Legendre polynomials, allowing the analysis of the backscattered light not satisfying the diffusion regime. The depth reached into the medium by detected photons was estimated using Monte Carlo simulations: the maximum depth reached by 95 % of the detected photons was between 40±2 and 270±20 mm depending on the source–detector distance and on the ice scattering properties. The magnitude of the instrument validation error on the reduced scattering coefficient ranged from 0.07 % for the most scattering medium to 35 % for the less scattering medium over the 2 orders of magnitude we validated. Fixing the absorption coefficient and γ, which proved difficult to measure, vertical profiles of the reduced scattering coefficient were obtained with decimetre resolution on first-year Arctic interior sea ice on Baffin Island in early spring 2019. We measured values of up to 7.1 m−1 for the uppermost layer of interior ice and down to 0.15±0.05 m−1 for the bottommost layer. These values are in the range of polar interior sea ice measurements published by other authors. The inversion of the reduced scattering coefficient at this scale was strongly dependent on the value of γ, highlighting the need to define the higher moments of the phase function. This newly developed probe provides a fast and reliable means for measurement of scattering in sea ice.
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Rodriguez-Alvarez, Nereida, Sidharth Misra, and Mary Morris. "The Polarimetric Sensitivity of SMAP-Reflectometry Signals to Crop Growth in the U.S. Corn Belt." Remote Sensing 12, no. 6 (March 21, 2020): 1007. http://dx.doi.org/10.3390/rs12061007.
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Crop growth is an important parameter to monitor in order to obtain accurate remotely sensed estimates of soil moisture, as well as assessments of crop health, productivity, and quality commonly used in the agricultural industry. The Soil Moisture Active Passive (SMAP) mission has been collecting Global Positioning System (GPS) signals as they reflect off the Earth’s surface since August 2015. The L-band dual-polarization reflection measurements enable studies of the evolution of geophysical parameters during seasonal transitions. In this paper, we examine the sensitivity of SMAP-reflectometry signals to agricultural crop growth related characteristics: crop type, vegetation water content (VWC), crop height, and vegetation opacity (VOP). The study presented here focuses on the United States “Corn Belt,” where an extensive area is planted every year with mostly corn, soybean, and wheat. We explore the potential to generate regularly an alternate source of crop growth information independent of the data currently used in the soil moisture (SM) products developed with the SMAP mission. Our analysis explores the variability of the polarimetric ratio (PR), computed from the peak signals at V- and H-polarization, during the United States Corn Belt crop growing season in 2017. The approach facilitates the understanding of the evolution of the observed surfaces from bare soil to peak growth and the maturation of the crops until harvesting. We investigate the impact of SM on PR for low roughness scenes with low variability and considering each crop type independently. We analyze the sensitivity of PR to the selected crop height, VWC, VOP, and Normalized Differential Vegetation Index (NDVI) reference datasets. Finally, we discuss a possible path towards a retrieval algorithm based on Global Navigation Satellite System-Reflectometry (GNSS-R) measurements that could be used in combination with passive SMAP soil moisture algorithms to correct simultaneously for the VWC and SM effects on the electromagnetic signals.
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Dutta, P. K., and O. P. Mishra. "Fractal analysis of INSAR and correlation with graph-cut based image registration for coastline deformation analysis: post seismic hazard assessment of the 2011 Tohoku earthquake region." Geoscientific Instrumentation, Methods and Data Systems Discussions 2, no. 1 (April 20, 2012): 149–75. http://dx.doi.org/10.5194/gid-2-149-2012.
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Abstract. Satellite imagery for 2011 earthquake off the Pacific coast of Tohoku has provided an opportunity to conduct image transformation analyses by employing multi-temporal images retrieval techniques. In this study, we used a new image segmentation algorithm to image coastline deformation by adopting graph cut energy minimization framework. Comprehensive analysis of available INSAR images using coastline deformation analysis helped extract disaster information of the affected region of the 2011 Tohoku tsunamigenic earthquake source zone. We attempted to correlate fractal analysis of seismic clustering behavior with image processing analogies and our observations suggest that increase in fractal dimension distribution is associated with clustering of events that may determine the level of devastation of the region. The implementation of graph cut based image registration technique helps us to detect the devastation across the coastline of Tohoku through change of intensity of pixels that carries out regional segmentation for the change in coastal boundary after the tsunami. The study applies transformation parameters on remotely sensed images by manually segmenting the image to recovering translation parameter from two images that differ by rotation. Based on the satellite image analysis through image segmentation, it is found that the area of 0.997 sq km for the Honshu region was a maximum damage zone localized in the coastal belt of NE Japan forearc region. The analysis helps infer using matlab that the proposed graph cut algorithm is robust and more accurate than other image registration methods. The analysis shows that the method can give a realistic estimate for recovered deformation fields in pixels corresponding to coastline change which may help formulate the strategy for assessment during post disaster need assessment scenario for the coastal belts associated with damages due to strong shaking and tsunamis in the world under disaster risk mitigation programs.
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Jurado-Navarro, Á. Aythami, Manuel López-Puertas, Bernd Funke, Maya García-Comas, Angela Gardini, Francisco González-Galindo, Gabriele P. Stiller, Thomas von Clarmann, Udo Grabowski, and Andrea Linden. "Global distributions of CO<sub>2</sub> volume mixing ratio in the middle and upper atmosphere from daytime MIPAS high-resolution spectra." Atmospheric Measurement Techniques 9, no. 12 (December 20, 2016): 6081–100. http://dx.doi.org/10.5194/amt-9-6081-2016.
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Abstract. Global distributions of the CO2 vmr (volume mixing ratio) in the mesosphere and lower thermosphere (from 70 up to ∼ 140 km) have been derived from high-resolution limb emission daytime MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) spectra in the 4.3 µm region. This is the first time that the CO2 vmr has been retrieved in the 120–140 km range. The data set spans from January 2005 to March 2012. The retrieval of CO2 has been performed jointly with the elevation pointing of the line of sight (LOS) by using a non-local thermodynamic equilibrium (non-LTE) retrieval scheme. The non-LTE model incorporates the new vibrational–vibrational and vibrational–translational collisional rates recently derived from the MIPAS spectra by [Jurado-Navarro et al.(2015)]. It also takes advantage of simultaneous MIPAS measurements of other atmospheric parameters (retrieved in previous steps), such as the kinetic temperature (derived up to ∼ 100 km from the CO2 15 µm region of MIPAS spectra and from 100 up to 170 km from the NO 5.3 µm emission of the same MIPAS spectra) and the O3 measurements (up to ∼ 100 km). The latter is very important for calculations of the non-LTE populations because it strongly constrains the O(3P) and O(1D) concentrations below ∼ 100 km. The estimated precision of the retrieved CO2 vmr profiles varies with altitude ranging from ∼ 1 % below 90 km to 5 % around 120 km and larger than 10 % above 130 km. There are some latitudinal and seasonal variations of the precision, which are mainly driven by the solar illumination conditions. The retrieved CO2 profiles have a vertical resolution of about 5–7 km below 120 km and between 10 and 20 km at 120–140 km. We have shown that the inclusion of the LOS as joint fit parameter improves the retrieval of CO2, allowing for a clear discrimination between the information on CO2 concentration and the LOS and also leading to significantly smaller systematic errors. The retrieved CO2 has an improved accuracy because of the new rate coefficients recently derived from MIPAS and the simultaneous MIPAS measurements of other key atmospheric parameters (retrieved in previous steps) needed for non-LTE modelling like kinetic temperature and O3 concentration. The major systematic error source is the uncertainty of the pressure/temperature profiles, inducing errors at midlatitude conditions of up to 15 % above 100 km (20 % for polar summer) and of ∼ 5 % around 80 km. The errors due to uncertainties in the O(1D) and O(3P) profiles are within 3–4 % in the 100–120 km region, and those due to uncertainties in the gain calibration and in the near-infrared solar flux are within ∼ 2 % at all altitudes. The retrieved CO2 shows the major features expected and predicted by general circulation models. In particular, its abrupt decline above 80–90 km and the seasonal change of the latitudinal distribution, with higher CO2 abundances in polar summer from 70 up to ∼ 95 km and lower CO2 vmr in the polar winter. Above ∼ 95 km, CO2 is more abundant in the polar winter than at the midlatitudes and polar summer regions, caused by the reversal of the mean circulation in that altitude region. Also, the solstice seasonal distribution, with a significant pole-to-pole CO2 gradient, lasts about 2.5 months in each hemisphere, while the seasonal transition occurs quickly.
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Bringi, Viswanathan, Mircea Grecu, Alain Protat, Merhala Thurai, and Christian Klepp. "Measurements of Rainfall Rate, Drop Size Distribution, and Variability at Middle and Higher Latitudes: Application to the Combined DPR-GMI Algorithm." Remote Sensing 13, no. 12 (June 20, 2021): 2412. http://dx.doi.org/10.3390/rs13122412.
Full textAbstract:
The Global Precipitation Measurement mission is a major U.S.–Japan joint mission to understand the physics of the Earth’s global precipitation as a key component of its weather, climate, and hydrological systems. The core satellite carries a dual-precipitation radar and an advanced microwave imager which provide measurements to retrieve the drop size distribution (DSD) and rain rates using a Combined Radar-Radiometer Algorithm (CORRA). Our objective is to validate key assumptions and parameterizations in CORRA and enable improved estimation of precipitation products, especially in the middle-to-higher latitudes in both hemispheres. The DSD parameters and statistical relationships between DSD parameters and radar measurements are a central part of the rainfall retrieval algorithm, which is complicated by regimes where DSD measurements are abysmally sparse (over the open ocean). In view of this, we have assembled optical disdrometer datasets gathered by research vessels, ground stations, and aircrafts to simulate radar observables and validate the scattering lookup tables used in CORRA. The joint use of all DSD datasets spans a large range of drop concentrations and characteristic drop diameters. The scaling normalization of DSDs defines an intercept parameter NW, which normalizes the concentrations, and a scaling diameter Dm, which compresses or stretches the diameter coordinate axis. A major finding of this study is that a single relationship between NW and Dm, on average, unifies all datasets included, from stratocumulus to heavier rainfall regimes. A comparison with the NW–Dm relation used as a constraint in versions 6 and 7 of CORRA highlights the scope for improvement of rainfall retrievals for small drops (Dm < 1 mm) and large drops (Dm > 2 mm). The normalized specific attenuation–reflectivity relationships used in the combined algorithm are also found to match well the equivalent relationships derived using DSDs from the three datasets, suggesting that the currently assumed lookup tables are not a major source of uncertainty in the combined algorithm rainfall estimates.
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Jiang, Maofei, Wenqing Zhong, Ke Xu, and Yongjun Jia. "Estimation of Arctic Sea Ice Thickness from Chinese HY-2B Radar Altimetry Data." Remote Sensing 15, no. 5 (February 21, 2023): 1180. http://dx.doi.org/10.3390/rs15051180.
Full textAbstract:
Sea ice thickness (SIT) is an important parameter in the study of climate change. During the past 20 years, satellite altimetry has been widely used to observe sea ice thickness. The Chinese Haiyang-2B (HY-2B) radar altimeter, launched in October 2018, can provide data up to 80.6° latitude and can be used as a supplementary means to observe polar sea ice. Reliable HY-2B SIT products will contribute to the sea ice community. In this study, we aimed to assess the Arctic sea ice thickness retrieval ability of the HY-2B radar altimetry data. We processed the HY-2B radar altimetry data from January 2019 to April 2022 and used the processed data to retrieve the Arctic SIT. The Alfred Wegener Institute (AWI) CryoSat-2 (CS-2) SIT products were used to calibrate the HY-2B SIT estimates with a linear regression method. The Goddard Space Flight Center (GSFC) CS-2, Jet Propulsion Laboratory (JPL), and GSFC ICESat-2 (IS-2) SIT products were used to validate the HY-2B calibrated SIT estimates. The HY-2B calibrated SIT estimates have good, consistent spatial distributions with the CS-2 and IS-2 SIT products. The comparison with the IS-2 and IS-2 SIT products shows the root-mean-square error (RMSE) and bias for the HY-2B SIT estimates are significantly reduced after calibration. The HY-2B SIT estimates were also validated using the ice thickness data from Operation IceBridge (OIB) and the ice draft data from the Beaufort Gyre Exploration Project (BGEP). Finally, the monthly variations of the HY-2B SIT estimates were analyzed. Results show that the HY-2B calibrated SIT estimates are reliable, especially when the SIT values are lower than 3 m. The HY-2B altimetry data is a possible source for sea ice thickness data at lower latitudes and will help us better understand the sea ice response to climate change.
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Heckl, Mareike, Andreas Fix, Matthias Jirousek, Franz Schreier, Jian Xu, and Markus Rapp. "Measurement characteristics of an airborne microwave temperature profiler (MTP)." Atmospheric Measurement Techniques 14, no. 2 (March 1, 2021): 1689–713. http://dx.doi.org/10.5194/amt-14-1689-2021.
Full textAbstract:
Abstract. The microwave temperature profiler (MTP), an airborne passive microwave radiometer, measures radiances, recorded as counts and calibrated to brightness temperatures, in order to estimate temperature profiles around flight altitude. From these data, quantities such as potential temperature gradients and static stability, indicating the state of the atmosphere, can be derived and used to assess important dynamical processes (e.g., gravity waves or stability assessments). DLR has acquired a copy of the MTP from NASA–JPL, which was designed as a wing-canister instrument and is deployed on the German High Altitude LOng range research aircraft (HALO). For this instrument a thorough analysis of instrument characteristics has been made in order to correctly determine the accuracy and precision of MTP measurements. Using a laboratory setup, the frequency response function and antenna diagram of the instrument were carefully characterized. A cold chamber was used to simulate the changing in-flight conditions and to derive noise characteristics as well as reliable calibration parameters for brightness temperature calculations, which are compared to those calculated from campaign data. The MTP shows quite large changes in the instrument state, imposing considerable changes in calibration parameters over the course of a single measurement flight; using a built-in heated target for calibration may yield large errors in brightness temperatures due to a misinterpretation of the measured absolute temperature. Applying the corrections presented herein to the calibration parameter calculations, the measurement noise becomes the dominant source of uncertainty and it is possible to measure the brightness temperatures around flight level (closely related to the absolute temperature close to the instrument) with a precision of 0.38 K. Furthermore, radiative transfer simulations, using the Py4CAtS package in a pencil-beam approach, indicate that the altitude range of the sensitivity of the MTP instrument can be increased by applying a modified measurement strategy. This is the first time such an extensive characterization of an MTP instrument, including a thorough calibration strategy assessment, has been published. The presented results, relevant for the wing-canister design of the MTP instrument, are important when processing MTP data: knowledge of the relevant uncertainties and instrument characteristics is essential for retrieval setup and is mandatory to correctly identify and interpret significant atmospheric temperature fluctuations.