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1
Chou, Ming-Dah, Kyu-Tae Lee, Si-Chee Tsay, and Qiang Fu. "Parameterization for Cloud Longwave Scattering for Use in Atmospheric Models." Journal of Climate 12, no. 1 (January 1, 1999): 159–69. http://dx.doi.org/10.1175/1520-0442-12.1.159.
Повний текст джерелаАнотація:
Abstract A parameterization for the scattering of thermal infrared (longwave) radiation by clouds has been developed based on discrete-ordinate multiple-scattering calculations. The effect of backscattering is folded into the emission of an atmospheric layer and the absorption between levels by scaling the cloud optical thickness. The scaling is a function of the single-scattering albedo and asymmetry factor. For wide ranges of cloud particle size, optical thickness, height, and atmospheric conditions, flux errors induced by the parameterization are small. They are <4 W m−2 (2%) in the upward flux at the top of the atmosphere and <2 W m−2 (1%) in the downward flux at the surface. Compared to the case that scattering by clouds is neglected, the flux errors are more than a factor of 2 smaller. The maximum error in cooling rate is ≈8%, which occurs at the top of clouds, as well as at the base of high clouds where the difference between the cloud and surface temperatures is large. With the scaling approximation, radiative transfer equations for a cloudy atmosphere are identical with those for a clear atmosphere, and the difficulties in applying a multiple-scattering algorithm to a partly cloudy atmosphere (assuming homogeneous clouds) are avoided. The computational efficiency is practically the same as that for a clear atmosphere. The parameterization represents a significant reduction in one source of the errors involved in the calculation of longwave cooling in cloudy atmospheres.
2
Komacek, Thaddeus D., Xianyu Tan, Peter Gao, and Elspeth K. H. Lee. "Patchy Nightside Clouds on Ultra-hot Jupiters: General Circulation Model Simulations with Radiatively Active Cloud Tracers." Astrophysical Journal 934, no. 1 (July 1, 2022): 79. http://dx.doi.org/10.3847/1538-4357/ac7723.
Повний текст джерелаАнотація:
Abstract The atmospheres of ultra-hot Jupiters have been characterized in detail through recent phase curve and low- and high-resolution emission and transmission spectroscopic observations. Previous numerical studies have analyzed the effect of the localized recombination of hydrogen on the atmospheric dynamics and heat transport of ultra-hot Jupiters, finding that hydrogen dissociation and recombination lead to a reduction in the day-to-night contrasts of ultra-hot Jupiters relative to previous expectations. In this work, we add to previous efforts by also considering the localized condensation of clouds in the atmospheres of ultra-hot Jupiters, their resulting transport by the atmospheric circulation, and the radiative feedback of clouds on the atmospheric dynamics. To do so, we include radiatively active cloud tracers into the existing MITgcm framework for simulating the atmospheric dynamics of ultra-hot Jupiters. We take cloud condensate properties appropriate for the high-temperature condensate corundum from CARMA cloud microphysics models. We conduct a suite of general circulation model (GCM) simulations with varying cloud microphysical and radiative properties, and we find that partial cloud coverage is a ubiquitous outcome of our simulations. This patchy cloud distribution is inherently set by atmospheric dynamics in addition to equilibrium cloud condensation, and causes a cloud greenhouse effect that warms the atmosphere below the cloud deck. Nightside clouds are further sequestered at depth due to a dynamically induced high-altitude thermal inversion. We post-process our GCMs with the Monte Carlo radiative transfer code gCMCRT and find that the patchy clouds on ultra-hot Jupiters do not significantly impact transmission spectra but can affect their phase-dependent emission spectra.
3
Harrop, Bryce E., and Dennis L. Hartmann. "The Relationship between Atmospheric Convective Radiative Effect and Net Energy Transport in the Tropical Warm Pool." Journal of Climate 28, no. 21 (October 30, 2015): 8620–33. http://dx.doi.org/10.1175/jcli-d-15-0151.1.
Повний текст джерелаАнотація:
Abstract Reanalysis data and radiation budget data are used to calculate the role of the atmospheric cloud radiative effect in determining the magnitude of horizontal export of energy by the tropical atmosphere. Because tropical high clouds result in net radiative heating of the atmosphere, they increase the requirement for the atmosphere to export energy from convective regions. Increases in upper-tropospheric water vapor associated with convection contribute about a fifth of the atmospheric radiative heating anomaly associated with convection. Over the warmest tropical oceans, the radiative effect of convective clouds and associated water vapor is roughly two-thirds the value of the atmospheric energy transport. Cloud radiative heating and atmospheric heat transport increase at the same rate with increasing sea surface temperature, suggesting that the increased energy export is supplied by the radiative heating associated with convective clouds. The net cloud radiative effect at the top of the atmosphere is insensitive to changes in SST over the warm pool. Principal component analysis of satellite-retrieved cloud data reveals that the insensitivity of the net cloud radiative effect to SST is the result of changes in cloud amount offsetting changes in cloud optical thickness and cloud-top height. While increasing upward motion makes the cloud radiative effect more negative, that decrease is offset by reductions in outgoing longwave radiation owing to increases in water vapor.
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Errico, Ronald M., George Ohring, Fuzhong Weng, Peter Bauer, Brad Ferrier, Jean-François Mahfouf, and Joe Turk. "Assimilation of Satellite Cloud and Precipitation Observations in Numerical Weather Prediction Models: Introduction to the JAS Special Collection." Journal of the Atmospheric Sciences 64, no. 11 (November 1, 2007): 3737–41. http://dx.doi.org/10.1175/2007jas2622.1.
Повний текст джерелаАнотація:
Abstract To date, the assimilation of satellite measurements in numerical weather prediction (NWP) models has focused on the clear atmosphere. But satellite observations in the visible, infrared, and microwave provide a great deal of information on clouds and precipitation. This special collection describes how to use this information to initialize clouds and precipitation in models. Since clouds and precipitation often occur in sensitive regions for forecast impacts, such improvements are likely necessary for continuing to acquire significant gains in weather forecasting. This special collection of the Journal of the Atmospheric Sciences is devoted to articles based on papers presented at the International Workshop on Assimilation of Satellite Cloud and Precipitation Observations in Numerical Weather Prediction Models, in Lansdowne, Virginia, in May 2005. This introduction summarizes the findings of the workshop. The special collection includes review articles on satellite observations of clouds and precipitation (Stephens and Kummerow), parameterizations of clouds and precipitation in NWP models (Lopez), radiative transfer in cloudy/precipitating atmospheres (Weng), and assimilation of cloud and precipitation observations (Errico et al.), as well as research papers on these topics.
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Koren, I., L. Oreopoulos, G. Feingold, L. A. Remer, and O. Altaratz. "How small is a small cloud?" Atmospheric Chemistry and Physics 8, no. 14 (July 21, 2008): 3855–64. http://dx.doi.org/10.5194/acp-8-3855-2008.
Повний текст джерелаАнотація:
Abstract. The interplay between clouds and aerosols and their contribution to the radiation budget is one of the largest uncertainties of climate change. Most work to date has separated cloudy and cloud-free areas in order to evaluate the individual radiative forcing of aerosols, clouds, and aerosol effects on clouds. Here we examine the size distribution and the optical properties of small, sparse cumulus clouds and the associated optical properties of what is considered a cloud-free atmosphere within the cloud field. We show that any separation between clouds and cloud free atmosphere will incur errors in the calculated radiative forcing. The nature of small cumulus cloud size distributions suggests that at any resolution, a significant fraction of the clouds are missed, and their optical properties are relegated to the apparent cloud-free optical properties. At the same time, the cloudy portion incorporates significant contribution from non-cloudy pixels. We show that the largest contribution to the total cloud reflectance comes from the smallest clouds and that the spatial resolution changes the apparent energy flux of a broken cloudy scene. When changing the resolution from 30 m to 1 km (Landsat to MODIS) the average "cloud-free" reflectance at 1.65 μm increases from 0.0095 to 0.0115 (>20%), the cloud reflectance decreases from 0.13 to 0.066 (~50%), and the cloud coverage doubles, resulting in an important impact on climate forcing estimations. The apparent aerosol forcing is on the order of 0.5 to 1 Wm−2 per cloud field.
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Kato, Seiji, Fred G. Rose, David A. Rutan, and Thomas P. Charlock. "Cloud Effects on the Meridional Atmospheric Energy Budget Estimated from Clouds and the Earth’s Radiant Energy System (CERES) Data." Journal of Climate 21, no. 17 (September 1, 2008): 4223–41. http://dx.doi.org/10.1175/2008jcli1982.1.
Повний текст джерелаАнотація:
Abstract The zonal mean atmospheric cloud radiative effect, defined as the difference between the top-of-the-atmosphere (TOA) and surface cloud radiative effects, is estimated from 3 yr of Clouds and the Earth’s Radiant Energy System (CERES) data. The zonal mean shortwave effect is small, though it tends to be positive (warming). This indicates that clouds increase shortwave absorption in the atmosphere, especially in midlatitudes. The zonal mean atmospheric cloud radiative effect is, however, dominated by the longwave effect. The zonal mean longwave effect is positive in the tropics and decreases with latitude to negative values (cooling) in polar regions. The meridional gradient of the cloud effect between midlatitude and polar regions exists even when uncertainties in the cloud effect on the surface enthalpy flux and in the modeled irradiances are taken into account. This indicates that clouds increase the rate of generation of the mean zonal available potential energy. Because the atmospheric cooling effect in polar regions is predominately caused by low-level clouds, which tend to be stationary, it is postulated here that the meridional and vertical gradients of the cloud effect increase the rate of meridional energy transport by the dynamics of the atmosphere from the midlatitudes to the polar region, especially in fall and winter. Clouds then warm the surface in the polar regions except in the Arctic in summer. Clouds, therefore, contribute toward increasing the rate of meridional energy transport from the midlatitudes to the polar regions through the atmosphere.
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Mollière, P., T. Stolker, S. Lacour, G. P. P. L. Otten, J. Shangguan, B. Charnay, T. Molyarova, et al. "Retrieving scattering clouds and disequilibrium chemistry in the atmosphere of HR 8799e." Astronomy & Astrophysics 640 (August 2020): A131. http://dx.doi.org/10.1051/0004-6361/202038325.
Повний текст джерелаАнотація:
Context. Clouds are ubiquitous in exoplanet atmospheres and they represent a challenge for the model interpretation of their spectra. When generating a large number of model spectra, complex cloud models often prove too costly numerically, whereas more efficient models may be overly simplified. Aims. We aim to constrain the atmospheric properties of the directly imaged planet HR 8799e with a free retrieval approach. Methods. We used our radiative transfer code petitRADTRANS for generating the spectra, which we coupled to the PyMultiNest tool. We added the effect of multiple scattering which is important for treating clouds. Two cloud model parameterizations are tested: the first incorporates the mixing and settling of condensates, the second simply parameterizes the functional form of the opacity. Results. In mock retrievals, using an inadequate cloud model may result in atmospheres that are more isothermal and less cloudy than the input. Applying our framework on observations of HR 8799e made with the GPI, SPHERE, and GRAVITY, we find a cloudy atmosphere governed by disequilibrium chemistry, confirming previous analyses. We retrieve that C/O = 0.60−0.08+0.07. Other models have not yet produced a well constrained C/O value for this planet. The retrieved C/O values of both cloud models are consistent, while leading to different atmospheric structures: either cloudy or more isothermal and less cloudy. Fitting the observations with the self-consistent Exo-REM model leads to comparable results, without constraining C/O. Conclusions. With data from the most sensitive instruments, retrieval analyses of directly imaged planets are possible. The inferred C/O ratio of HR 8799e is independent of the cloud model and thus appears to be a robust. This C/O is consistent with stellar, which could indicate that the HR 8799e formed outside the CO2 or CO iceline. As it is the innermost planet of the system, this constraint could apply to all HR 8799 planets.
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Shupe, Matthew D., David D. Turner, Von P. Walden, Ralf Bennartz, Maria P. Cadeddu, Benjamin B. Castellani, Christopher J. Cox, et al. "High and Dry: New Observations of Tropospheric and Cloud Properties above the Greenland Ice Sheet." Bulletin of the American Meteorological Society 94, no. 2 (February 1, 2013): 169–86. http://dx.doi.org/10.1175/bams-d-11-00249.1.
Повний текст джерелаАнотація:
Cloud and atmospheric properties strongly influence the mass and energy budgets of the Greenland Ice Sheet (GIS). To address critical gaps in the understanding of these systems, a new suite of cloud- and atmosphere-observing instruments has been installed on the central GIS as part of the Integrated Characterization of Energy, Clouds, Atmospheric State, and Precipitation at Summit (ICECAPS) project. During the first 20 months in operation, this complementary suite of active and passive ground-based sensors and radiosondes has provided new and unique perspectives on important cloud–atmosphere properties. High atop the GIS, the atmosphere is extremely dry and cold with strong near-surface static stability predominating throughout the year, particularly in winter. This low-level thermodynamic structure, coupled with frequent moisture inversions, conveys the importance of advection for local cloud and precipitation formation. Cloud liquid water is observed in all months of the year, even the particularly cold and dry winter, while annual cycle observations indicate that the largest atmospheric moisture amounts, cloud water contents, and snowfall occur in summer and under southwesterly flow. Many of the basic structural properties of clouds observed at Summit, Greenland, particularly for low-level stratiform clouds, are similar to their counterparts in other Arctic regions. The ICECAPS observations and accompanying analyses will be used to improve the understanding of key cloud–atmosphere processes and the manner in which they interact with the GIS. Furthermore, they will facilitate model evaluation and development in this data-sparse but environmentally unique region.
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Burley, Jarred L., Steven T. Fiorino, Brannon J. Elmore, and Jaclyn E. Schmidt. "A Remote Sensing and Atmospheric Correction Method for Assessing Multispectral Radiative Transfer through Realistic Atmospheres and Clouds." Journal of Atmospheric and Oceanic Technology 36, no. 2 (February 1, 2019): 203–16. http://dx.doi.org/10.1175/jtech-d-18-0078.1.
Повний текст джерелаАнотація:
Abstract The ability to quickly and accurately model actual atmospheric conditions is essential to remote sensing analyses. Clouds present a particularly complex challenge, as they cover up to 70% of Earth’s surface, and their highly variable and diverse nature necessitates physics-based modeling. The Laser Environmental Effects Definition and Reference (LEEDR) is a verified and validated atmospheric propagation and radiative transfer code that creates physically realizable vertical and horizontal profiles of meteorological data. Coupled with numerical weather prediction (NWP) model output, LEEDR enables analysis, nowcasts, and forecasts for radiative effects expected for real-world scenarios. A recent development is the inclusion of the U.S. Air Force’s World-Wide Merged Cloud Analysis (WWMCA) cloud data in a new tool set that enables radiance calculations through clouds from UV to radio frequency (RF) wavelengths. This effort details the creation of near-real-time profiles of atmospheric and cloud conditions and the resulting radiative transfer analysis for virtually any wavelength(s) of interest. Calendar year 2015 data are analyzed to establish climatological limits for diffuse transmission in the 300–1300-nm band, and the impacts of various geometry, cloud microphysical, and atmospheric conditions are examined. The results show that 80% of diffuse band transmissions are estimated to fall between 0.248 and 0.889 under the assumptions of cloud homogeneity and maximum overlap and are sufficient for establishing diffuse transmission percentiles. The demonstrated capability provides an efficient way to extend optical wavelength cloud parameters across the spectrum for physics-based multiple-scattering effects modeling through cloudy and clear atmospheres, providing an improvement to atmospheric correction for remote sensing and cloud effects on system performance metrics.
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Voiculescu, Mirela. "Special Issue Atmospheric Composition and Cloud Cover Observations." Atmosphere 12, no. 1 (December 31, 2020): 56. http://dx.doi.org/10.3390/atmos12010056.
Повний текст джерелаАнотація:
A Special Issue of Atmosphere, “Atmospheric Composition and Cloud Cover Observations”, is focused on presenting some of the latest results of observations of clouds and atmospheric composition, mainly by referring to new equipment or experimental set-ups [...]
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Marshak, A., Y. Knyazikhin, J. C. Chiu, and W. J. Wiscombe. "Spectrally Invariant Approximation within Atmospheric Radiative Transfer." Journal of the Atmospheric Sciences 68, no. 12 (December 1, 2011): 3094–111. http://dx.doi.org/10.1175/jas-d-11-060.1.
Повний текст джерелаАнотація:
Abstract Certain algebraic combinations of single scattering albedo and solar radiation reflected from, or transmitted through, vegetation canopies do not vary with wavelength. These “spectrally invariant relationships” are the consequence of wavelength independence of the extinction coefficient and scattering phase function in vegetation. In general, this wavelength independence does not hold in the atmosphere, but in cloud-dominated atmospheres the total extinction and total scattering phase function vary only weakly with wavelength. This paper identifies the atmospheric conditions under which the spectrally invariant approximation can accurately describe the extinction and scattering properties of cloudy atmospheres. The validity of the assumptions and the accuracy of the approximation are tested with 1D radiative transfer calculations using publicly available radiative transfer models: Discrete Ordinate Radiative Transfer (DISORT) and Santa Barbara DISORT Atmospheric Radiative Transfer (SBDART). It is shown for cloudy atmospheres with cloud optical depth above 3, and for spectral intervals that exclude strong water vapor absorption, that the spectrally invariant relationships found in vegetation canopy radiative transfer are valid to better than 5%. The physics behind this phenomenon, its mathematical basis, and possible applications to remote sensing and climate are discussed.
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Poser, Anna Julia, Nadine Nettelmann, and Ronald Redmer. "The Effect of Clouds as an Additional Opacity Source on the Inferred Metallicity of Giant Exoplanets." Atmosphere 10, no. 11 (October 30, 2019): 664. http://dx.doi.org/10.3390/atmos10110664.
Повний текст джерелаАнотація:
Atmospheres regulate the planetary heat loss and therefore influence planetary thermal evolution. Uncertainty in a giant planet’s thermal state contributes to the uncertainty in the inferred abundance of heavy elements it contains. Within an analytic atmosphere model, we here investigate the influence that different cloud opacities and cloud depths can have on the metallicity of irradiated extrasolar gas giants, which is inferred from interior models. In this work, the link between inferred metallicity and assumed cloud properties is the thermal profile of atmosphere and interior. Therefore, we perform coupled atmosphere, interior, and evolution calculations. The atmosphere model includes clouds in a much simplified manner; it includes long-wave absorption but neglects shortwave scattering. Within that model, we show that optically thick, high clouds have negligible influence, whereas deep-seated, optically very thick clouds can lead to warmer deep tropospheres and therefore higher bulk heavy element mass estimates. For the young hot Jupiter WASP-10b, we find a possible enhancement in inferred metallicity of up to 10% due to possible silicate clouds at ∼0.3 bar. For WASP-39b, whose observationally derived metallicity is higher than predicted by cloudless models, we find an enhancement by at most 50%. However, further work on cloud properties and their self-consistent coupling to the atmospheric structure is needed in order to reduce uncertainties in the choice of model parameter values, in particular of cloud opacities.
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Prather, M. J. "Photolysis rates in correlated overlapping cloud fields: Cloud-J 7.3c." Geoscientific Model Development 8, no. 8 (August 14, 2015): 2587–95. http://dx.doi.org/10.5194/gmd-8-2587-2015.
Повний текст джерелаАнотація:
Abstract. A new approach for modeling photolysis rates (J values) in atmospheres with fractional cloud cover has been developed and is implemented as Cloud-J – a multi-scattering eight-stream radiative transfer model for solar radiation based on Fast-J. Using observations of the vertical correlation of cloud layers, Cloud-J 7.3c provides a practical and accurate method for modeling atmospheric chemistry. The combination of the new maximum-correlated cloud groups with the integration over all cloud combinations by four quadrature atmospheres produces mean J values in an atmospheric column with root mean square (rms) errors of 4 % or less compared with 10–20 % errors using simpler approximations. Cloud-J is practical for chemistry–climate models, requiring only an average of 2.8 Fast-J calls per atmosphere vs. hundreds of calls with the correlated cloud groups, or 1 call with the simplest cloud approximations. Another improvement in modeling J values, the treatment of volatile organic compounds with pressure-dependent cross sections, is also incorporated into Cloud-J.
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Prather, M. J. "Photolysis rates in correlated overlapping cloud fields: Cloud-J 7.3." Geoscientific Model Development Discussions 8, no. 5 (May 27, 2015): 4051–73. http://dx.doi.org/10.5194/gmdd-8-4051-2015.
Повний текст джерелаАнотація:
Abstract. A new approach for modeling photolysis rates (J values) in atmospheres with fractional cloud cover has been developed and implemented as Cloud-J – a multi-scattering eight-stream radiative transfer model for solar radiation based on Fast-J. Using observed statistics for the vertical correlation of cloud layers, Cloud-J 7.3 provides a practical and accurate method for modeling atmospheric chemistry. The combination of the new maximum-correlated cloud groups with the integration over all cloud combinations represented by four quadrature atmospheres produces mean J values in an atmospheric column with root-mean-square errors of 4% or less compared with 10–20% errors using simpler approximations. Cloud-J is practical for chemistry-climate models, requiring only an average of 2.8 Fast-J calls per atmosphere, vs. hundreds of calls with the correlated cloud groups, or 1 call with the simplest cloud approximations. Another improvement in modeling J values, the treatment of volatile organic compounds with pressure-dependent cross sections is also incorporated into Cloud-J.
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Zhou, Daniel K., William L. Smith, Xu Liu, Allen M. Larar, Stephen A. Mango, and Hung-Lung Huang. "Physically Retrieving Cloud and Thermodynamic Parameters from Ultraspectral IR Measurements." Journal of the Atmospheric Sciences 64, no. 3 (March 1, 2007): 969–82. http://dx.doi.org/10.1175/jas3877.1.
Повний текст джерелаАнотація:
Abstract A physical inversion scheme has been developed dealing with cloudy as well as cloud-free radiance observed with ultraspectral infrared sounders to simultaneously retrieve surface, atmospheric thermodynamic, and cloud microphysical parameters. A fast radiative transfer model, which applies to the clouded atmosphere, is used for atmospheric profile and cloud parameter retrieval. A one-dimensional (1D) variational multivariable inversion solution is used to improve an iterative background state defined by an eigenvector-regression retrieval. The solution is iterated in order to account for nonlinearity in the 1D variational solution. It is shown that relatively accurate temperature and moisture retrievals can be achieved below optically thin clouds. For optically thick clouds, accurate temperature and moisture profiles down to cloud-top level are obtained. For both optically thin and thick cloud situations, the cloud-top height can be retrieved with relatively high accuracy (i.e., error <1 km). National Polar-orbiting Operational Environmental Satellite System (NPOESS) Airborne Sounder Testbed Interferometer (NAST-I) retrievals from the The Observing-System Research and Predictability Experiment (THORPEX) Atlantic Regional Campaign are compared with coincident observations obtained from dropsondes and the nadir-pointing cloud physics lidar (CPL). This work was motivated by the need to obtain solutions for atmospheric soundings from infrared radiances observed for every individual field of view, regardless of cloud cover, from future ultraspectral geostationary satellite sounding instruments, such as the Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS). However, this retrieval approach can also be applied to the ultraspectral sounding instruments to fly on polar satellites, such as the Infrared Atmospheric Sounding Interferometer (IASI) on the European MetOp satellite, the Cross-track Infrared Sounder (CrIS) on the NPOESS Preparatory Project, and the follow-on NPOESS series of satellites.
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Voigt, Aiko, Nicole Albern, and Georgios Papavasileiou. "The Atmospheric Pathway of the Cloud-Radiative Impact on the Circulation Response to Global Warming: Important and Uncertain." Journal of Climate 32, no. 10 (May 6, 2019): 3051–67. http://dx.doi.org/10.1175/jcli-d-18-0810.1.
Повний текст джерелаАнотація:
Abstract Previous work showed that the poleward expansion of the annual-mean zonal-mean atmospheric circulation in response to global warming is strongly modulated by changes in clouds and their radiative heating of the surface and atmosphere. Here, a hierarchy and an ensemble of global climate models are used to study the circulation impact of changes in atmospheric cloud-radiative heating in the absence of changes in sea surface temperature (SST), which is referred to as the atmospheric pathway of the cloud-radiative impact. For the MPI-ESM model, the atmospheric pathway is responsible for about half of the total cloud-radiative impact, and in fact half of the total circulation response. Changes in atmospheric cloud-radiative heating are substantial in both the lower and upper troposphere. However, because SST is prescribed the atmospheric pathway is dominated by changes in upper-tropospheric cloud-radiative heating, which in large part results from the upward shift of high-level clouds. The poleward circulation expansion via the atmospheric pathway and changes in upper-tropospheric cloud-radiative heating are qualitatively robust across three global models, yet their magnitudes vary by a factor of 3. A substantial part of these magnitude differences are related to the upper-tropospheric radiative heating by high-level clouds in the present-day climate. A comparison with observations highlights the model deficits in representing the radiative heating by high-level clouds and indicates that reducing these deficits can contribute to improved predictions of regional climate change.
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Tomita, Hiroyuki, Shang-Ping Xie, Hiroki Tokinaga, and Yoshimi Kawai. "Cloud Response to the Meandering Kuroshio Extension Front." Journal of Climate 26, no. 23 (December 2013): 9393–98. http://dx.doi.org/10.1175/jcli-d-13-00133.1.
Повний текст джерелаАнотація:
A unique set of observations on board research vessel (R/V) Mirai in April 2010 captured a striking cloud hole over a cold meander of the Kuroshio Extension (KE) east of Japan as corroborated by atmospheric soundings, ceilometer, shipboard radiation data, and satellite cloud images. Distinct differences were also observed between the warm meander farther to the north and warm water south of the KE. The atmosphere is highly unstable over the warm meander, promoting a well-mixed marine atmospheric boundary layer (MABL) and a layer of solid stratocumulus clouds capped by a strong inversion. Over the warm water south of the KE, MABL deepens and is decoupled from the ocean surface. Scattered cumulus clouds develop as captured by rapid variations in ceilometer-derived cloud base. The results show that the meandering KE front affects the entire MABL and the clouds. Such atmospheric response can potentially intensify the baroclinicity in the lower atmosphere.
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Cox, Christopher J., Penny M. Rowe, Steven P. Neshyba, and Von P. Walden. "A synthetic data set of high-spectral-resolution infrared spectra for the Arctic atmosphere." Earth System Science Data 8, no. 1 (May 12, 2016): 199–211. http://dx.doi.org/10.5194/essd-8-199-2016.
Повний текст джерелаАнотація:
Abstract. Cloud microphysical and macrophysical properties are critical for understanding the role of clouds in climate. These properties are commonly retrieved from ground-based and satellite-based infrared remote sensing instruments. However, retrieval uncertainties are difficult to quantify without a standard for comparison. This is particularly true over the polar regions, where surface-based data for a cloud climatology are sparse, yet clouds represent a major source of uncertainty in weather and climate models. We describe a synthetic high-spectral-resolution infrared data set that is designed to facilitate validation and development of cloud retrieval algorithms for surface- and satellite-based remote sensing instruments. Since the data set is calculated using pre-defined cloudy atmospheres, the properties of the cloud and atmospheric state are known a priori. The atmospheric state used for the simulations is drawn from radiosonde measurements made at the North Slope of Alaska (NSA) Atmospheric Radiation Measurement (ARM) site at Barrow, Alaska (71.325° N, 156.615° W), a location that is generally representative of the western Arctic. The cloud properties for each simulation are selected from statistical distributions derived from past field measurements. Upwelling (at 60 km) and downwelling (at the surface) infrared spectra are simulated for 260 cloudy cases from 50 to 3000 cm−1 (3.3 to 200 µm) at monochromatic (line-by-line) resolution at a spacing of ∼ 0.01 cm−1 using the Line-by-line Radiative Transfer Model (LBLRTM) and the discrete-ordinate-method radiative transfer code (DISORT). These spectra are freely available for interested researchers from the NSF Arctic Data Center data repository (doi:10.5065/D61J97TT).
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Mieslinger, Theresa, Bjorn Stevens, Tobias Kölling, Manfred Brath, Martin Wirth, and Stefan A. Buehler. "Optically thin clouds in the trades." Atmospheric Chemistry and Physics 22, no. 10 (May 30, 2022): 6879–98. http://dx.doi.org/10.5194/acp-22-6879-2022.
Повний текст джерелаАнотація:
Abstract. We develop a new method to describe the total cloud cover including optically thin clouds in trade wind cumulus cloud fields. Climate models and large eddy simulations commonly underestimate the cloud cover, while estimates from observations largely disagree on the cloud cover in the trades. Currently, trade wind clouds significantly contribute to the uncertainty in climate sensitivity estimates derived from model perturbation studies. To simulate clouds well, especially how they change in a future climate, we have to know how cloudy it is. In this study we develop a method to quantify the cloud cover from a cloud-free perspective. Using well-known radiative transfer relations we retrieve the cloud-free contribution in high-resolution satellite observations of trade cumulus cloud fields during EUREC4A. Knowing the cloud-free part, we can investigate the remaining cloud-related contributions consisting of areas detected by common cloud-masking algorithms and undetected areas related to optically thin clouds. We find that the cloud-mask cloud cover underestimates the total cloud cover by 33 %. Aircraft lidar measurements support our findings by showing a high abundance of optically thin clouds during EUREC4A. Mixing the undetected optically thin clouds into the cloud-free signal can cause an underestimation of the cloud radiative effect of up to −7.5 %. We further discuss possible artificial correlations in aerosol–cloud cover interaction studies that might arise from undetected optically thin low clouds. Our analysis suggests that the known underestimation of trade wind cloud cover and simultaneous overestimation of cloud brightness in models are even higher than assumed so far.
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Lefèvre, Maxence, Xianyu Tan, Elspeth K. H. Lee, and R. T. Pierrehumbert. "Cloud-convection Feedback in Brown Dwarf Atmospheres." Astrophysical Journal 929, no. 2 (April 1, 2022): 153. http://dx.doi.org/10.3847/1538-4357/ac5e2d.
Повний текст джерелаАнотація:
Abstract Numerous observational evidence has suggested the presence of active meteorology in the atmospheres of brown dwarfs. A near-infrared brightness variability has been observed. Clouds have a major role in shaping the thermal structure and spectral properties of these atmospheres. The mechanism of such variability is still unclear, and neither 1D nor global circulation models can fully study this topic due to resolution. In this study, a convective-resolving model is coupled to gray-band radiative transfer in order to study the coupling between the convective atmosphere and the variability of clouds over a large temperature range with a domain of several hundred kilometers. Six types of clouds are considered, with microphysics including settling. The clouds are radiatively active through the Rosseland mean coefficient. Radiative cloud feedback can drive spontaneous atmospheric variability in both temperature and cloud structure, as modeled for the first time in three dimensions. Silicate clouds have the most effect on the thermal structure with the generation of a secondary convective layer in some cases, depending on the assumed particle size. Iron and aluminum clouds also have a substantial impact on the atmosphere. Thermal spectra were computed, and we find the strongest effect of the clouds is the smoothing of spectral features at optical wavelengths. Compared to observed L and T dwarfs on the color–magnitude diagram, the simulated atmospheres are redder for most of the cases. Simulations with the presence of cloud holes are closer to observations.
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Lefèvre, Maxence, Xianyu Tan, Elspeth K. H. Lee, and R. T. Pierrehumbert. "Cloud-convection Feedback in Brown Dwarf Atmospheres." Astrophysical Journal 929, no. 2 (April 1, 2022): 153. http://dx.doi.org/10.3847/1538-4357/ac5e2d.
Повний текст джерелаАнотація:
Abstract Numerous observational evidence has suggested the presence of active meteorology in the atmospheres of brown dwarfs. A near-infrared brightness variability has been observed. Clouds have a major role in shaping the thermal structure and spectral properties of these atmospheres. The mechanism of such variability is still unclear, and neither 1D nor global circulation models can fully study this topic due to resolution. In this study, a convective-resolving model is coupled to gray-band radiative transfer in order to study the coupling between the convective atmosphere and the variability of clouds over a large temperature range with a domain of several hundred kilometers. Six types of clouds are considered, with microphysics including settling. The clouds are radiatively active through the Rosseland mean coefficient. Radiative cloud feedback can drive spontaneous atmospheric variability in both temperature and cloud structure, as modeled for the first time in three dimensions. Silicate clouds have the most effect on the thermal structure with the generation of a secondary convective layer in some cases, depending on the assumed particle size. Iron and aluminum clouds also have a substantial impact on the atmosphere. Thermal spectra were computed, and we find the strongest effect of the clouds is the smoothing of spectral features at optical wavelengths. Compared to observed L and T dwarfs on the color–magnitude diagram, the simulated atmospheres are redder for most of the cases. Simulations with the presence of cloud holes are closer to observations.
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Sun, J., H. Leighton, M. K. Yau, and P. Ariya. "Numerical evidence for cloud droplet nucleation at the cloud-environment interface." Atmospheric Chemistry and Physics 12, no. 24 (December 21, 2012): 12155–64. http://dx.doi.org/10.5194/acp-12-12155-2012.
Повний текст джерелаАнотація:
Abstract. Cumulus clouds have long been recognized as being the results of ascending moist air from below the cloud base. Cloud droplet nucleation is understood to take place near the cloud base and inside accelerating rising cloudy air. Here we describe circumstances under which cloud droplet nucleation takes place at the interface of ascending cloudy air and clear air. Evaporation is normally expected to occur at this interface. However, continuity of moving air requires cloud-free air above the boundary of rising cloudy air to move upwards in response to the gradient force of perturbation pressure. We used a one and half dimensional non-hydrostatic cloud model and the Weather Research and Forecast model to investigate the impacts of this force on the evolution of cloud spectra. Our study shows that expansion and cooling of ascending moist air above the cloud top causes it to become supersaturated with condensation rather than evaporation occurring at the interface. We also confirm that Eulerian models can describe the cloud droplet activation and prohibit spurious activation at this interface. The continuous feeding of newly activated cloud droplets at the cloud summit may accelerate warm rain formation.
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Dybbroe, Adam, Karl-Göran Karlsson, and Anke Thoss. "NWCSAF AVHRR Cloud Detection and Analysis Using Dynamic Thresholds and Radiative Transfer Modeling. Part I: Algorithm Description." Journal of Applied Meteorology 44, no. 1 (January 1, 2005): 39–54. http://dx.doi.org/10.1175/jam-2188.1.
Повний текст джерелаАнотація:
Abstract New methods and software for cloud detection and classification at high and midlatitudes using Advanced Very High Resolution Radiometer (AVHRR) data are developed for use in a wide range of meteorological, climatological, land surface, and oceanic applications within the Satellite Application Facilities (SAFs) of the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT), including the SAF for Nowcasting and Very Short Range Forecasting Applications (NWCSAF) project. The cloud mask employs smoothly varying (dynamic) thresholds that separate fully cloudy or cloud-contaminated fields of view from cloud-free conditions. Thresholds are adapted to the actual state of the atmosphere and surface and the sun–satellite viewing geometry using cloud-free radiative transfer model simulations. Both the cloud masking and the cloud-type classification are done using sequences of grouped threshold tests that employ both spectral and textural features. The cloud-type classification divides the cloudy pixels into 10 different categories: 5 opaque cloud types, 4 semitransparent clouds, and 1 subpixel cloud category. The threshold method is fuzzy in the sense that the distances in feature space to the thresholds are stored and are used to determine whether to stop or to continue testing. They are also used as a quality indicator of the final output. The atmospheric state should preferably be taken from a short-range NWP model, but the algorithms can also run with climatological fields as input.
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Emde, Claudia, Huan Yu, Arve Kylling, Michel van Roozendael, Kerstin Stebel, Ben Veihelmann, and Bernhard Mayer. "Impact of 3D cloud structures on the atmospheric trace gas products from UV–Vis sounders – Part 1: Synthetic dataset for validation of trace gas retrieval algorithms." Atmospheric Measurement Techniques 15, no. 5 (March 18, 2022): 1587–608. http://dx.doi.org/10.5194/amt-15-1587-2022.
Повний текст джерелаАнотація:
Abstract. Retrievals of trace gas concentrations from satellite observations are mostly performed for clear regions or regions with low cloud coverage. However, even fully clear pixels can be affected by clouds in the vicinity, either by shadowing or by scattering of radiation from clouds in the clear region. Quantifying the error of retrieved trace gas concentrations due to cloud scattering is a difficult task. One possibility is to generate synthetic data by three-dimensional (3D) radiative transfer simulations using realistic 3D atmospheric input data, including 3D cloud structures. Retrieval algorithms may be applied on the synthetic data, and comparison to the known input trace gas concentrations yields the retrieval error due to cloud scattering. In this paper we present a comprehensive synthetic dataset which has been generated using the Monte Carlo radiative transfer model MYSTIC (Monte Carlo code for the phYSically correct Tracing of photons In Cloudy atmospheres). The dataset includes simulated spectra in two spectral ranges (400–500 nm and the O2A-band from 755–775 nm). Moreover it includes layer air mass factors (layer-AMFs) calculated at 460 nm. All simulations are performed for a fixed background atmosphere for various sun positions, viewing directions and surface albedos. Two cloud setups are considered: the first includes simple box clouds with various geometrical and optical thicknesses. This can be used to systematically investigate the sensitivity of the retrieval error on solar zenith angle, surface albedo and cloud parameters. Corresponding 1D simulations are also provided. The second includes realistic three-dimensional clouds from an ICON large eddy simulation (LES) for a region covering Germany and parts of surrounding countries. The scene includes cloud types typical of central Europe such as shallow cumulus, convective cloud cells, cirrus and stratocumulus. This large dataset can be used to quantify the trace gas concentration retrieval error statistically. Along with the dataset, the impact of horizontal photon transport on reflectance spectra and layer-AMFs is analysed for the box-cloud scenarios. Moreover, the impact of 3D cloud scattering on the NO2 vertical column density (VCD) retrieval is presented for a specific LES case. We find that the retrieval error is largest in cloud shadow regions, where the NO2 VCD is underestimated by more than 20 %. The dataset is available for the scientific community to assess the behaviour of trace gas retrieval algorithms and cloud correction schemes in cloud conditions with 3D structure.
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Kim, Hye-Sil, Bryan A. Baum, and Yong-Sang Choi. "Use of spectral cloud emissivities and their related uncertainties to infer ice cloud boundaries: methodology and assessment using CALIPSO cloud products." Atmospheric Measurement Techniques 12, no. 9 (September 19, 2019): 5039–54. http://dx.doi.org/10.5194/amt-12-5039-2019.
Повний текст джерелаАнотація:
Abstract. Satellite-imager-based operational cloud property retrievals generally assume that a cloudy pixel can be treated as being plane-parallel with horizontally homogeneous properties. This assumption can lead to high uncertainties in cloud heights, particularly for the case of optically thin, but geometrically thick, clouds composed of ice particles. This study demonstrates that ice cloud emissivity uncertainties can be used to provide a reasonable range of ice cloud layer boundaries, i.e., the minimum to maximum heights. Here ice cloud emissivity uncertainties are obtained for three IR channels centered at 11, 12, and 13.3 µm. The range of cloud emissivities is used to infer a range of ice cloud temperature and heights, rather than a single value per pixel as provided by operational cloud retrievals. Our methodology is tested using MODIS observations over the western North Pacific Ocean during August 2015. We estimate minimum–maximum heights for three cloud regimes, i.e., single-layered optically thin ice clouds, single-layered optically thick ice clouds, and multilayered clouds. Our results are assessed through comparison with CALIOP version 4 cloud products for a total of 11873 pixels. The cloud boundary heights for single-layered optically thin clouds show good agreement with those from CALIOP; biases for maximum (minimum) heights versus the cloud-top (base) heights of CALIOP are 0.13 km (−1.01 km). For optically thick and multilayered clouds, the biases of the estimated cloud heights from the cloud top or cloud base become larger (0.30/−1.71 km, 1.41/−4.64 km). The vertically resolved boundaries for ice clouds can contribute new information for data assimilation efforts for weather prediction and radiation budget studies. Our method is applicable to measurements provided by most geostationary weather satellites including the GK-2A advanced multichannel infrared imager.
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Stubenrauch, C. J., S. Cros, A. Guignard, and N. Lamquin. "A 6-year global cloud climatology from the Atmospheric InfraRed Sounder AIRS and a statistical analysis in synergy with CALIPSO and CloudSat." Atmospheric Chemistry and Physics 10, no. 15 (August 6, 2010): 7197–214. http://dx.doi.org/10.5194/acp-10-7197-2010.
Повний текст джерелаАнотація:
Abstract. We present a six-year global climatology of cloud properties, obtained from observations of the Atmospheric Infrared Sounder (AIRS) onboard the NASA Aqua satellite. Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) combined with CloudSat observations, both missions launched as part of the A-Train in 2006, provide a unique opportunity to evaluate the retrieved AIRS cloud properties such as cloud amount and height. In addition, they permit to explore the vertical structure of different cloud types. AIRS-LMD cloud detection agrees with CALIPSO about 85% over ocean and about 75% over land. Global cloud amount has been estimated from 66% to 74%, depending on the weighting of not cloudy AIRS footprints by partial cloud cover from 0 to 0.3. 42% of all clouds are high clouds, and about 42% of all clouds are single layer low-level clouds. The "radiative" cloud height determined by the AIRS-LMD retrieval corresponds well to the height of the maximum backscatter signal and of the "apparent middle" of the cloud. Whereas the real cloud thickness of high opaque clouds often fills the whole troposphere, their "apparent" cloud thickness (at which optical depth reaches about 5) is on average only 2.5 km. The real geometrical thickness of optically thin cirrus as identified by AIRS-LMD is identical to the "apparent" cloud thickness with an average of about 2.5 km in the tropics and midlatitudes. High clouds in the tropics have slightly more diffusive cloud tops than at higher latitudes. In general, the depth of the maximum backscatter signal increases nearly linearly with increasing "apparent" cloud thickness. For the same "apparent" cloud thickness optically thin cirrus show a maximum backscatter about 10% deeper inside the cloud than optically thicker clouds. We also show that only the geometrically thickest opaque clouds and (the probably surrounding anvil) cirrus penetrate the stratosphere in the tropics.
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Fournier, N., P. Stammes, M. de Graaf, R. van der A, A. Piters, M. Grzegorski, and A. Kokhanovsky. "Improving cloud information over deserts from SCIAMACHY Oxygen A-band measurements." Atmospheric Chemistry and Physics 6, no. 1 (January 25, 2006): 163–72. http://dx.doi.org/10.5194/acp-6-163-2006.
Повний текст джерелаАнотація:
Abstract. The retrieval of column densities and concentration profiles of atmospheric trace gas species from satellites is sensitive to light scattered by clouds. The SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY (SCIAMACHY) instrument on the Envisat satellite, principally designed to retrieve trace gases in the atmosphere, is also capable of detecting clouds. FRESCO (Fast Retrieval Scheme for Clouds from the Oxygen A-band) is a fast and robust algorithm providing cloud information from the O2 A-band for cloud correction of ozone. FRESCO provides a consistent set of cloud products by retrieving simultaneously effective cloud fraction and cloud top pressure. The FRESCO retrieved values are compared with the SCIAMACHY Level 2 operational cloud fraction of OCRA (Optical Cloud Recognition Algorithm) but, also, with cloud information from HICRU (Heidelberg Iterative Cloud Retrieval Utilities), SACURA (SemiAnalytical CloUd Retrieval Algorithm) and the MODIS (Moderate Resolution Imaging Spectroradiometer) instrument. The results correlate well, but FRESCO overestimates cloud fraction over deserts. Thus, to improve retrievals at these locations, the FRESCO surface albedo databases are decontaminated from the presence of desert dust aerosols. This is achieved by using the GOME Absorbing Aerosol Index. It is shown that this approach succeeds well in producing more accurate cloud information over the Sahara.
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Vukicevic, T., M. Sengupta, A. S. Jones, and T. Vonder Haar. "Cloud-Resolving Satellite Data Assimilation: Information Content of IR Window Observations and Uncertainties in Estimation." Journal of the Atmospheric Sciences 63, no. 3 (March 1, 2006): 901–19. http://dx.doi.org/10.1175/jas3639.1.
Повний текст джерелаАнотація:
Abstract This study addresses the problem of four-dimensional (4D) estimation of a cloudy atmosphere on cloud-resolving scales using satellite remote sensing measurements. The motivation is to develop a methodology for accurate estimation of cloud properties and the associated atmospheric environment on small spatial scales but over large regions to aid in better understanding of the clouds and their role in the atmospheric system. The problem is initially approached by the study of the assimilation of the Geostationary Operational Environmental Satellite (GOES) imager observations into a cloud-resolving model with explicit bulk cloud microphysical parameterization. A new 4D variational data assimilation (4DVAR) research system with the cloud-resolving capability is applied to a case of a multilayered cloud evolution without convection. In the experiments the information content of the IR window channels is addressed as well as the sensitivity of estimation to lateral boundary condition errors, model first guess, decorrelation length in the background statistical error model, and the use of a generic linear model error. The assimilation results are compared with independent observations from the Atmospheric Radiation Measurement (ARM) central facility archive. The modeled 3D spatial distribution and short-term evolution of the ice cloud mass is significantly improved by the assimilation of IR window channels when the model already contains conditions for the ice cloud formation. The assimilated ice cloud in this case is in good agreement with the independent cloud radar measurements. The simulation of liquid clouds below thick ice clouds is not influenced by the IR window observations. The assimilation results clearly demonstrate that increasing the observational constraint from individual to combined channel measurements and from less to more frequent observation times systematically improves the assimilation results. The experiments with the model error indicate that the current specification of this error in the form of a generic linear forcing, which was adopted from other data assimilation studies, is not suitable for the cloud-resolving data assimilation. Instead, a parameter estimation approach may need to be explored in the future. The experiments with varying decorrelation lengths suggest the need to use the model horizontal grid spacing that is several times smaller than the GOES imager native resolution to achieve equivalent spatial variability in the assimilation.
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Di Natale, Gianluca, Giovanni Bianchini, Massimo Del Guasta, Marco Ridolfi, Tiziano Maestri, William Cossich, Davide Magurno, and Luca Palchetti. "Characterization of the Far Infrared Properties and Radiative Forcing of Antarctic Ice and Water Clouds Exploiting the Spectrometer-LiDAR Synergy." Remote Sensing 12, no. 21 (October 31, 2020): 3574. http://dx.doi.org/10.3390/rs12213574.
Повний текст джерелаАнотація:
Optical and microphysical cloud properties are retrieved from measurements acquired in 2013 and 2014 at the Concordia base station in the Antarctic Plateau. Two sensors are used synergistically: a Fourier transform spectroradiometer named REFIR-PAD (Radiation Explorer in Far Infrared-Prototype for Applications and Developments) and a backscattering-depolarization LiDAR. First, in order to identify the cloudy scenes and assess the cloud thermodynamic phase, the REFIR-PAD spectral radiances are ingested by a machine learning algorithm called Cloud Identification and Classification (CIC). For each of the identified cloudy scenes, the nearest (in time) LiDAR backscattering profile is processed by the Polar Threshold (PT) algorithm that allows derivation of the cloud top and bottom heights. Subsequently, using the CIC and PT results as external constraints, the Simultaneous Atmospheric and Clouds Retrieval (SACR) code is applied to the REFIR-PAD spectral radiances. SACR simultaneously retrieves cloud optical depth and effective dimensions and atmospheric vertical profiles of water vapor and temperature. The analysis determines an average effective diameter of 28 μm with an optical depth of 0.76 for the ice clouds. Water clouds are only detected during the austral Summer, and the retrieved properties provide an average droplet diameter of 9 μm and average optical depth equal to four. The estimated retrieval error is about 1% for the ice crystal/droplet size and 2% for the cloud optical depth. The sensitivity of the retrieved parameters to the assumed crystal shape is also assessed. New parametrizations of the optical depth and the longwave downwelling forcing for Antarctic ice and water clouds, as a function of the ice/liquid water path, are presented. The longwave downwelling flux, computed from the top of the atmosphere to the surface, ranges between 70 and 220 W/m2. The estimated cloud longwave forcing at the surface is (31 ± 7) W/m2 and (29 ± 6) W/m2 for ice clouds and (64 ± 12) and (62 ± 11) W/m2 for water clouds, in 2013 and 2014, respectively. The total average cloud forcing for the two years investigated is (46 ± 9) W/m2.
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Črnivec, Nina, та Bernhard Mayer. "The incorporation of the Tripleclouds concept into the <i>δ</i>-Eddington two-stream radiation scheme: solver characterization and its application to shallow cumulus clouds". Atmospheric Chemistry and Physics 20, № 17 (14 вересня 2020): 10733–55. http://dx.doi.org/10.5194/acp-20-10733-2020.
Повний текст джерелаАнотація:
Abstract. The treatment of unresolved cloud–radiation interactions in weather and climate models has considerably improved over the recent years, compared to conventional plane-parallel radiation schemes, which previously persisted in these models for multiple decades. One such improvement is the state-of-the-art Tripleclouds radiative solver, which has one cloud-free and two cloudy regions in each vertical model layer and is thereby capable of representing cloud horizontal inhomogeneity. Inspired by the Tripleclouds concept, primarily introduced by Shonk and Hogan (2008), we incorporated a second cloudy region into the widely employed δ-Eddington two-stream method with the maximum-random overlap assumption for partial cloudiness. The inclusion of another cloudy region in the two-stream framework required an extension of vertical overlap rules. While retaining the maximum-random overlap for the entire layer cloudiness, we additionally assumed the maximum overlap of optically thicker cloudy regions in pairs of adjacent layers. This extended overlap formulation implicitly places the optically thicker region towards the interior of the cloud, which is in agreement with the core–shell model for convective clouds. The method was initially applied on a shallow cumulus cloud field, evaluated against a three-dimensional benchmark radiation computation. Different approaches were used to generate a pair of cloud condensates characterizing the two cloudy regions, testing various condensate distribution assumptions along with global cloud variability estimate. Regardless of the exact condensate setup, the radiative bias in the vast majority of Tripleclouds configurations was considerably reduced compared to the conventional plane-parallel calculation. Whereas previous studies employing the Tripleclouds concept focused on researching the top-of-the-atmosphere radiation budget, the present work applies Tripleclouds to atmospheric heating rate and net surface flux. The Tripleclouds scheme was implemented in the comprehensive libRadtran radiative transfer package and can be utilized to further address key scientific issues related to unresolved cloud–radiation interplay in coarse-resolution atmospheric models.
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Wang, P., P. Stammes, R. van der A, G. Pinardi, and M. van Roozendael. "FRESCO+: an improved O<sub>2</sub> A-band cloud retrieval algorithm for tropospheric trace gas retrievals." Atmospheric Chemistry and Physics 8, no. 21 (November 14, 2008): 6565–76. http://dx.doi.org/10.5194/acp-8-6565-2008.
Повний текст джерелаАнотація:
Abstract. The FRESCO (Fast Retrieval Scheme for Clouds from the Oxygen A-band) algorithm has been used to retrieve cloud information from measurements of the O2 A-band around 760 nm by GOME, SCIAMACHY and GOME-2. The cloud parameters retrieved by FRESCO are the effective cloud fraction and cloud pressure, which are used for cloud correction in the retrieval of trace gases like O3 and NO2. To improve the cloud pressure retrieval for partly cloudy scenes, single Rayleigh scattering has been included in an improved version of the algorithm, called FRESCO+. We compared FRESCO+ and FRESCO effective cloud fractions and cloud pressures using simulated spectra and one month of GOME measured spectra. As expected, FRESCO+ gives more reliable cloud pressures over partly cloudy pixels. Simulations and comparisons with ground-based radar/lidar measurements of clouds show that the FRESCO+ cloud pressure is about the optical midlevel of the cloud. Globally averaged, the FRESCO+ cloud pressure is about 50 hPa higher than the FRESCO cloud pressure, while the FRESCO+ effective cloud fraction is about 0.01 larger. The effect of FRESCO+ cloud parameters on O3 and NO2 vertical column density (VCD) retrievals is studied using SCIAMACHY data and ground-based DOAS measurements. We find that the FRESCO+ algorithm has a significant effect on tropospheric NO2 retrievals but a minor effect on total O3 retrievals. The retrieved SCIAMACHY tropospheric NO2 VCDs using FRESCO+ cloud parameters (v1.1) are lower than the tropospheric NO2VCDs which used FRESCO cloud parameters (v1.04), in particular over heavily polluted areas with low clouds. The difference between SCIAMACHY tropospheric NO2 VCDs v1.1 and ground-based MAXDOAS measurements performed in Cabauw, The Netherlands, during the DANDELIONS campaign is about −2.12×1014molec cm−2.
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Harshvardhan, Guang Guo, Robert N. Green, Zheng Qu, and Takashi Y. Nakajima. "Remotely Sensed Microphysical and Thermodynamic Properties of Nonuniform Water Cloud Fields." Journal of the Atmospheric Sciences 61, no. 21 (November 1, 2004): 2574–87. http://dx.doi.org/10.1175/jas3301.1.
Повний текст джерелаАнотація:
Abstract Visible and near-infrared reflected radiances have been used to estimate the cloud optical depth and effective radius of cloud-filled global area coverage (GAC) pixels from the Advanced Very High Resolution Radiometer (AVHRR) for two cases in the North Atlantic Ocean. One is representative of clouds having low concentrations of cloud condensation nuclei (CCN), while the other is an example of maritime clouds forming in continental air, in this case, intruding from Europe around a cutoff low pressure system. It is shown that an estimate of the cloud drop concentration can be obtained from remotely sensed cloud radiative properties and standard meteorological analyses. These concentrations show very clearly the influence of enhanced CCN on cloud microphysics. However, conclusions regarding the indirect radiative effect of aerosol on cloud must wait for the development of a framework for analyzing changes in cloud liquid water path (LWP). It is shown that estimates of LWP are greatly influenced by the scheme that is used to identify cloudy pixels at the AVHRR GAC resolution. Application of a very strict thermal channel spatial coherence criterion for identifying cloud-filled pixels yields mean LWP estimates for cloudy pixels alone that are 40%–75% higher than mean LWP estimates for the much larger sample of possibly cloudy pixels identified by a reflectance threshold criterion.
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Mang, James, Peter Gao, Callie E. Hood, Jonathan J. Fortney, Natasha Batalha, Xinting Yu, and Imke de Pater. "Microphysics of Water Clouds in the Atmospheres of Y Dwarfs and Temperate Giant Planets." Astrophysical Journal 927, no. 2 (March 1, 2022): 184. http://dx.doi.org/10.3847/1538-4357/ac51d3.
Повний текст джерелаАнотація:
Abstract Water clouds are expected to form on Y dwarfs and giant planets with equilibrium temperatures near or below that of Earth, drastically altering their atmospheric compositions and their albedos and thermal emission spectra. Here we use the 1D Community Aerosol and Radiation Model for Atmospheres (CARMA) to investigate the microphysics of water clouds on cool substellar worlds to constrain their typical particle sizes and vertical extent, taking into consideration nucleation and condensation, which have not been considered in detail for water clouds in H/He atmospheres. We compute a small grid of Y-dwarf and temperate giant-exoplanet atmosphere models with water clouds forming through homogeneous nucleation and heterogeneous nucleation on cloud condensation nuclei composed of meteoritic dust, organic photochemical hazes, and upwelled potassium chloride cloud particles. We present comparisons with the Ackerman & Marley parameterization of cloud physics to extract the optimal sedimentation efficiency parameter (f sed) using Virga. We find that no Virga model replicates the CARMA water clouds exactly and that a transition in f sed occurs from the base of the cloud to the cloud top. Furthermore, we generate simulated thermal emission and geometric albedo spectra and find large, wavelength-dependent differences between the CARMA and Virga models, with different gas absorption bands reacting differently to the different cloud distributions and particularly large differences in the M band. Therefore, constraining the vertically dependent properties of water clouds will be essential to estimate the gas abundances in these atmospheres.
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Sedlar, Joseph. "Implications of Limited Liquid Water Path on Static Mixing within Arctic Low-Level Clouds." Journal of Applied Meteorology and Climatology 53, no. 12 (December 2014): 2775–89. http://dx.doi.org/10.1175/jamc-d-14-0065.1.
Повний текст джерелаАнотація:
AbstractObservations of cloud properties and thermodynamics from two Arctic locations, Barrow, Alaska, and Surface Heat Budget of the Arctic (SHEBA), are examined. A comparison of in-cloud thermodynamic mixing characteristics for low-level, single-layer clouds from nearly a decade of data at Barrow and one full annual cycle over the sea ice at SHEBA is performed. These cloud types occur relatively frequently, evident in 27%–30% of all cloudy cases. To understand the role of liquid water path (LWP), or lack thereof, on static in-cloud mixing, cloud layers are separated into optically thin and optically thick LWP subclasses. Clouds with larger LWPs tend to have a deeper in-cloud mixed layer relative to optically thinner clouds. However, both cloud LWP subclasses are frequently characterized by an in-cloud stable layer above the mixed layer top. The depth of the stable layer generally correlates with an increased temperature gradient across the layer. This layer often contains a specific humidity inversion, but it is more frequently present when cloud LWP is optically thinner (LWP < 50 g m−2). It is suggested that horizontal thermodynamic advection plays a key role modifying the vertical extent of in-cloud mixing and likewise the depth of in-cloud stable layers. Furthermore, longwave atmospheric opacity above the cloud top is generally enhanced during cases with optically thinner clouds. Thermodynamic advection, cloud condensate distribution within the stable layer, and enhanced atmospheric radiation above the cloud are found to introduce a thermodynamic–radiative feedback that potentially modifies the extent of LWP and subsequent in-cloud mixing.
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Coakley, James A., Michael A. Friedman, and William R. Tahnk. "Retrieval of Cloud Properties for Partly Cloudy Imager Pixels." Journal of Atmospheric and Oceanic Technology 22, no. 1 (January 1, 2005): 3–17. http://dx.doi.org/10.1175/jtech-1681.1.
Повний текст джерелаАнотація:
Abstract Retrievals of cloud properties from satellite imagery often invoke the assumption that the fields of view are overcast when cloud-contaminated, even though a significant fraction are only partially cloud-covered. The overcast assumption leads to biases in the retrieved cloud properties: cloud amounts and droplet effective radii are typically overestimated, while visible optical depths, cloud altitudes, cloud liquid water amounts, and column droplet number concentrations are typically underestimated. In order to estimate these biases, a retrieval scheme was developed to obtain the properties of clouds for partially covered imager fields of view. The partly cloudy pixel retrieval scheme is applicable to single-layered cloud systems and invokes the assumption that clouds that only partially cover a field of view are at the same altitude as nearby clouds from the same layer that completely cover imager pixels. The properties of the retrieval are illustrated through its application to 2-km Visible and Infrared Scanner (VIRS) data from the Tropical Rainfall Measuring Mission (TRMM) for a marine stratocumulus scene. The scene was chosen because the cloud properties are typical of such systems based on an analysis of VIRS data for February and March 1998. Comparisons of properties for clouds in partly cloudy pixels and those for clouds in nearby overcast pixels reveal that the optical depths and droplet effective radii are generally smaller for the clouds in the partly cloudy pixels. In addition, for pixel-scale cloud fractions between 0.2 and 0.8, optical depth, droplet effective radius, and column droplet number concentration decrease slowly with decreasing cloud cover fraction. The changes are only about 20%–30%, while cloud cover fraction changes by 80%. For comparison, changes in optical depth and column number concentration retrieved using a threshold method decrease by 80%–90%. As long as the cloud cover in partly cloudy pixels is greater than about 0.1, uncertainties in the estimates of the cloud altitudes and of the radiances for the cloud-free portions of the fields of view give rise to uncertainties in the retrieved cloud properties that are comparable to the uncertainties in the properties retrieved for overcast pixels.
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Chang, Fu-Lung, and James A. Coakley. "Relationships between Marine Stratus Cloud Optical Depth and Temperature: Inferences from AVHRR Observations." Journal of Climate 20, no. 10 (May 15, 2007): 2022–36. http://dx.doi.org/10.1175/jcli4115.1.
Повний текст джерелаАнотація:
Abstract Studies using International Satellite Cloud Climatology Project (ISCCP) data have reported decreases in cloud optical depth with increasing temperature, thereby suggesting a positive feedback in cloud optical depth as climate warms. The negative cloud optical depth and temperature relationships are questioned because ISCCP employs threshold assumptions to identify cloudy pixels that have included partly cloudy pixels. This study applies the spatial coherence technique to one month of Advanced Very High Resolution Radiometer (AVHRR) data over the Pacific Ocean to differentiate overcast pixels from the partly cloudy pixels and to reexamine the cloud optical depth–temperature relationships. For low-level marine stratus clouds studied here, retrievals from partly cloudy pixels showed 30%–50% smaller optical depths, 1°–4°C higher cloud temperatures, and slightly larger droplet effective radii, when they were compared to retrievals from the overcast pixels. Despite these biases, retrievals for the overcast and partly cloudy pixels show similar negative cloud optical depth–temperature relationships and their magnitudes agree with the ISCCP results for the midlatitude and subtropical regions. There were slightly negative droplet effective radius–temperature relationships, and considerable positive cloud liquid water content–temperature relationships indicated by aircraft measurements. However, cloud thickness decreases appear to be the main reason why cloud optical depth decreases with increasing temperature. Overall, cloud thickness thinning may explain why similar negative cloud optical depth–temperature relationships are found in both overcast and partly cloudy pixels. In addition, comparing the cloud-top temperature to the air temperature at 740 hPa indicates that cloud-top height generally rises with warming. This suggests that the cloud thinning is mainly due to the ascending of cloud base. The results presented in this study are confined to the midlatitude and subtropical Pacific and may not be applicable to the Tropics or other regions.
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Ahlgrimm, Maike, David A. Randall, and Martin Köhler. "Evaluating Cloud Frequency of Occurrence and Cloud-Top Height Using Spaceborne Lidar Observations." Monthly Weather Review 137, no. 12 (December 1, 2009): 4225–37. http://dx.doi.org/10.1175/2009mwr2937.1.
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Abstract A strategy for model evaluation using spaceborne lidar observations is presented. Observations from the Geoscience Laser Altimeter System are recast onto the model grid to assess the ability of two versions of the Integrated Forecasting System to model marine stratocumulus clouds. The two model versions differ primarily in their treatment of clear and cloudy boundary layers. For each grid column, a representative cloud fraction and cloud-top height are derived from the observations, as well as from the model. By applying the same threshold criteria for cloud fraction and cloud-top height independently to model and observations, samples containing marine stratocumulus clouds can be identified. The frequency of occurrence, cloud fraction, and cloud-top height distributions for all samples thus identified are compared. The evaluation shows improvements in the frequency of occurrence and cloud-top height of marine stratocumulus, though modeled cloud tops remain lower than observed. Additional runs reveal a sensitivity to the strength of the environmental mixing that occurs during the test parcel ascent of the boundary layer parameterization. With a more aggressive parcel, the modeled clouds agree even better with observations.
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Sun, Lu, Anita D. Rapp, Tristan S. L’Ecuyer, Anne S. Daloz, and Ethan Nelson. "Environmental Response in Coupled Energy and Water Cloud Impact Parameters Derived from A-Train Satellites, ERA-Interim, and MERRA-2." Journal of Applied Meteorology and Climatology 61, no. 3 (March 2022): 261–76. http://dx.doi.org/10.1175/jamc-d-21-0078.1.
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Abstract Understanding the connections between latent heating from precipitation and cloud radiative effects is essential for accurately parameterizing cross-scale links between cloud microphysics and global energy and water cycles in climate models. Although commonly examined separately, this study adopts two cloud impact parameters (CIPs), the surface radiative cooling efficiency Rc and atmospheric radiative heating efficiency Rh, that explicitly couple cloud radiative effects and precipitation to characterize how efficiently precipitating cloud systems influence the energy budget and water cycle using A-Train observations and two reanalyses. These CIPs exhibit distinct global distributions that suggest cloud energy and water cycle coupling are highly dependent on cloud regime. The dynamic regime ω500 controls the sign of Rh, whereas column water vapor (CWV) appears to be the larger control on the magnitude. The magnitude of Rc is highly coupled to the dynamic regime. Observations show that clouds cool the surface very efficiently per unit rainfall at both low and high sea surface temperature (SST) and CWV, but reanalyses only capture the former. Reanalyses fail to simulate strong Rh and moderate Rc in deep convection environments but produce stronger Rc and Rh than observations in shallow, warm rain systems in marine stratocumulus regions. Although reanalyses generate fairly similar climatologies in the frequency of environmental states, the response of Rc and Rh to SST and CWV results in systematic differences in zonal and meridional gradients of cloud atmospheric heating and surface cooling relative to A-Train observations that may have significant implications for global circulations and cloud feedbacks. Significance Statement Studying climate change requires understanding coupled interactions between clouds, precipitation, and their environment. Here we calculate two parameters to reveal how efficiently clouds can heat the atmosphere or cool the surface per unit rain. The satellite observations and reanalyses show similar global patterns, but there are some differences in areas of deep convection and low cloud regions. Examination of these parameters as a function of their environment shows that reanalyses cool the atmosphere too much per unit rain in environments with low sea surface temperatures and water vapor. Vertical velocity determines whether clouds heat or cool the atmosphere. Both observations and reanalyses suggest that water vapor is the stronger control on how much clouds heat the atmosphere per unit rain.
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Helling, Ch, and F. J. M. Rietmeijer. "Glittery clouds in exoplanetary atmospheres?" International Journal of Astrobiology 8, no. 1 (January 2009): 3–8. http://dx.doi.org/10.1017/s1473550408004382.
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AbstractCloud formation modelling has entered astrophysics as a new field of research for planetary and brown dwarf atmospheres. Clouds are a chemically and physically very active component of an atmosphere since they determine the remaining gas phase and change the object's albedo depending on their material composition. The grains can also provide a surface where the molecular constituents for life can be physisorbed for possible pre-biotic evolution. This paper summarizes our model for the kinetic formation of dirty dust grains which make up the atmospheric clouds of extraterrestrial giant gas planets. We include seed formation, surface growth and evaporation, the gravitational settling that influences the dust formation, element depletion that determines the remaining gas phase abundances, and convective overshooting that is needed for a dust model to be applicable to hydrostatic atmosphere simulations. We demonstrate the evolution of the material composition of the cloud itself and the distribution of the grain sizes in the cloud layer, exemplary for a giant gas planet parameter combinations (Teff, log g). In general, substellar clouds are composed of small, dirty grains with a high silicate content at the cloud deck. They grow in size and gradually purify to iron/corundum grains when they move into denser and hotter atmospheric regions. Comparing these results with experimental data from condensation experiments leads to the conclusion that cloud grains that gravitationally settle in the atmosphere of a giant planet can easily change their lattice structure from the disordered amorphous state they are forming in, into the ordered lattice of a crystal.
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Yang, S., and X. Zou. "Temperature Profiles and Lapse Rate Climatology in Altostratus and Nimbostratus Clouds Derived from GPS RO Data." Journal of Climate 26, no. 16 (August 6, 2013): 6000–6014. http://dx.doi.org/10.1175/jcli-d-12-00646.1.
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Abstract Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC) radio occultation (RO) refractivity profiles in altostratus and nimbostratus clouds from 2007 to 2010 are first identified based on collocated CloudSat data. Vertical temperature profiles in these clouds are then retrieved from cloudy refractivity profiles. Contributions of cloud liquid water content and ice water content are also included in the retrieval algorithm. The temperature profiles and their lapse rates are compared with those from a standard GPS RO wet retrieval without including cloud effects. On average, the temperatures from cloudy retrieval are about 0.5–1.0 K warmer than the GPS RO wet retrieval, except for the altitudes near the nimbostratus base. The differences of temperature between the two methods are largest in summer and smallest in winter. The lapse rate in altostratus clouds is around 6.5°–7.5°C km−1 and does not vary greatly with height. On the contrary, the lapse rate increases significantly with height in nimbostratus clouds, from about 2.5°–3.5°C km−1 near the cloud base to about 5.0°–6.0°C km−1 at cloud center and 6.5°–7.5°C km−1 below the cloud top. Seasonal variability of lapse rate derived from the cloudy retrieval is larger than that derived from the wet retrieval. The lapse rate within clouds is smaller in summer and larger in winter. The mean lapse rate decreases with temperature in all seasons.
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Gimeno García, S., T. Trautmann, and V. Venema. "Reduction of radiation biases by incorporating the missing cloud variability by means of downscaling techniques: a study using the 3-D MoCaRT model." Atmospheric Measurement Techniques 5, no. 9 (September 20, 2012): 2261–76. http://dx.doi.org/10.5194/amt-5-2261-2012.
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Abstract. Handling complexity to the smallest detail in atmospheric radiative transfer models is unfeasible in practice. On the one hand, the properties of the interacting medium, i.e., the atmosphere and the surface, are only available at a limited spatial resolution. On the other hand, the computational cost of accurate radiation models accounting for three-dimensional heterogeneous media are prohibitive for some applications, especially for climate modelling and operational remote-sensing algorithms. Hence, it is still common practice to use simplified models for atmospheric radiation applications. Three-dimensional radiation models can deal with complex scenarios providing an accurate solution to the radiative transfer. In contrast, one-dimensional models are computationally more efficient, but introduce biases to the radiation results. With the help of stochastic models that consider the multi-fractal nature of clouds, it is possible to scale cloud properties given at a coarse spatial resolution down to a higher resolution. Performing the radiative transfer within the cloud fields at higher spatial resolution noticeably helps to improve the radiation results. We present a new Monte Carlo model, MoCaRT, that computes the radiative transfer in three-dimensional inhomogeneous atmospheres. The MoCaRT model is validated by comparison with the consensus results of the Intercomparison of Three-Dimensional Radiation Codes (I3RC) project. In the framework of this paper, we aim at characterising cloud heterogeneity effects on radiances and broadband fluxes, namely: the errors due to unresolved variability (the so-called plane parallel homogeneous, PPH, bias) and the errors due to the neglect of transversal photon displacements (independent pixel approximation, IPA, bias). First, we study the effect of the missing cloud variability on reflectivities. We will show that the generation of subscale variability by means of stochastic methods greatly reduce or nearly eliminate the reflectivity biases. Secondly, three-dimensional broadband fluxes in the presence of realistic inhomogeneous cloud fields sampled at high spatial resolutions are calculated and compared to their one-dimensional counterparts at coarser resolutions. We found that one-dimensional calculations at coarsely resolved cloudy atmospheres systematically overestimate broadband reflected and absorbed fluxes and underestimate transmitted ones.
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Helling, Ch, N. Iro, L. Corrales, D. Samra, K. Ohno, M. K. Alam, M. Steinrueck, et al. "Understanding the atmospheric properties and chemical composition of the ultra-hot Jupiter HAT-P-7b." Astronomy & Astrophysics 631 (October 25, 2019): A79. http://dx.doi.org/10.1051/0004-6361/201935771.
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Context. Of the presently known ≈3900 exoplanets, sparse spectral observations are available for ≈100. Ultra-hot Jupiters have recently attracted interest from observers and theoreticians alike, as they provide observationally accessible test cases. Confronting detailed theoretical models with observations is of preeminent importance in preparation for upcoming space-based telescopes. Aims. We aim to study cloud formation on the ultra-hot Jupiter HAT-P-7b, the resulting composition of the local gas phase, and how their global changes affect wavelength-dependent observations utilised to derive fundamental properties of the planet. Methods. We apply a hierarchical modelling approach as a virtual laboratory to study cloud formation and gas-phase chemistry. We utilise 97 vertical 1D profiles of a 3D GCM for HAT-P-7b to evaluate our kinetic cloud formation model consistently with the local equilibrium gas-phase composition. We use maps and slice views to provide a global understanding of the cloud and gas chemistry. Results. The day/night temperature difference on HAT-P-7b (ΔT ≈ 2500 K) causes clouds to form on the nightside (dominated by H2/He) while the dayside (dominated by H/He) retains cloud-free equatorial regions. The cloud particles vary in composition and size throughout the vertical extension of the cloud, but also globally. TiO2[s]/Al2O3[s]/CaTiO3[s]-particles of cm-sized radii occur in the higher dayside-latitudes, resulting in a dayside dominated by gas-phase opacity. The opacity on the nightside, however, is dominated by 0.01…0.1μm particles made of a material mix dominated by silicates. The gas pressure at which the atmosphere becomes optically thick is ~10−4 bar in cloudy regions, and ~0.1 bar in cloud-free regions. Conclusions. HAT-P-7b features strong morning/evening terminator asymmetries, providing an example of patchy clouds and azimuthally-inhomogeneous chemistry. Variable terminator properties may be accessible by ingress/egress transmission photometry (e.g., CHEOPS and PLATO) or spectroscopy. The large temperature differences of ≈2500 K result in an increasing geometrical extension from the night- to the dayside. The H2O abundance at the terminator changes by <1 dex with altitude and ≲0.3 dex (a factor of 2) across the terminator for a given pressure, indicating that H2O abundances derived from transmission spectra can be representative of the well-mixed metallicity at P ≳ 10 bar. We suggest the atmospheric C/O as an important tool to trace the presence and location of clouds in exoplanet atmospheres. The atmospheric C/O can be sub- and supersolar due to cloud formation. Phase curve variability of HAT-P-7b is unlikely to be caused by dayside clouds.
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Seiki, Tatsuya, Chihiro Kodama, Akira T. Noda, and Masaki Satoh. "Improvement in Global Cloud-System-Resolving Simulations by Using a Double-Moment Bulk Cloud Microphysics Scheme." Journal of Climate 28, no. 6 (March 13, 2015): 2405–19. http://dx.doi.org/10.1175/jcli-d-14-00241.1.
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Abstract This study examines the impact of an alteration of a cloud microphysics scheme on the representation of longwave cloud radiative forcing (LWCRF) and its impact on the atmosphere in global cloud-system-resolving simulations. A new double-moment bulk cloud microphysics scheme is used, and the simulated results are compared with those of a previous study. It is demonstrated that improvements within the new cloud microphysics scheme have the potential to substantially improve climate simulations. The new cloud microphysics scheme represents a realistic spatial distribution of the cloud fraction and LWCRF, particularly near the tropopause. The improvement in the cirrus cloud-top height by the new cloud microphysics scheme substantially reduces the warm bias in atmospheric temperature from the previous simulation via LWCRF by the cirrus clouds. The conversion rate of cloud ice to snow and gravitational sedimentation of cloud ice are the most important parameters for determining the strength of the radiative heating near the tropopause and its impact on atmospheric temperature.
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Gielen, C., M. Van Roozendael, F. Hendrick, G. Pinardi, T. Vlemmix, V. De Bock, H. De Backer, et al. "A simple and versatile cloud-screening method for MAX-DOAS retrievals." Atmospheric Measurement Techniques 7, no. 10 (October 13, 2014): 3509–27. http://dx.doi.org/10.5194/amt-7-3509-2014.
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Abstract. We present a cloud-screening method based on differential optical absorption spectroscopy (DOAS) measurements, more specifically using intensity measurements and O4 differential slant-column densities (DSCDs). Using the colour index (CI), i.e. the ratio of the radiance at two wavelengths, we define different sky conditions including clear, thin clouds/polluted, fully-cloudy, and heavily polluted. We also flag the presence of broken and scattered clouds. The O4 absorption is a good tracer for cloud-induced light-path changes and is used to detect clouds and discriminate between instances of high aerosol optical depth (AOD) and high cloud optical depth (COD). We apply our cloud screening to MAX-DOAS (multi-axis DOAS) retrievals at three different sites with different typical meteorological conditions, more specifically suburban Beijing (39.75° N, 116.96° E), Brussels (50.78° N, 4.35° E) and Jungfraujoch (46.55° N, 7.98° E). We find that our cloud screening performs well characterizing the different sky conditions. The flags based on the colour index are able to detect changes in visibility due to aerosols and/or (scattered) clouds. The O4-based multiple-scattering flag is able to detect optically thick clouds, and is needed to correctly identify clouds for sites with extreme aerosol pollution. Removing data taken under cloudy conditions results in a better agreement, in both correlation and slope, between the MAX-DOAS AOD retrievals and measurements from other co-located instruments.
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Gielen, C., M. Van Roozendael, F. Hendrick, G. Pinardi, T. Vlemmix, V. De Bock, H. De Backer, et al. "A simple and versatile cloud-screening method for MAX-DOAS retrievals." Atmospheric Measurement Techniques Discussions 7, no. 6 (June 12, 2014): 5883–920. http://dx.doi.org/10.5194/amtd-7-5883-2014.
Повний текст джерелаАнотація:
Abstract. We present a cloud-screening method based on differential optical absorption spectroscopy (DOAS) measurements, more specifically using zenith sky spectra and O4 differential slant-column densities (DSCDs). Using the colour index (CI), i.e. the ratio of the radiance at two wavelengths, we define different sky conditions including clear, thin clouds/polluted, fully-cloudy, and heavily polluted. We also flag the presence of broken and scattered clouds. The O4 absorption is a good tracer for cloud-induced light-path changes and is used to detect clouds and discriminate between instances of high aerosol optical depth (AOD) and high cloud optical depth (COD). We apply our cloud screening to MAX-DOAS (multi-axis DOAS) retrievals at three different sites with different typical meteorological conditions, more specifically suburban Beijing (39.75° N, 116.96° E), Brussels (50.78° N, 4.35° E) and Jungfraujoch (46.55° N, 7.98° E). We find that our cloud screening performs well characterizing the different sky conditions. The flags based on the colour index are able to detect changes in visibility due to aerosols and/or (scattered) clouds. The O4-based multiple-scattering flag is able to detect optically thick clouds, and is needed to correctly identify clouds for sites with extreme aerosol pollution. Removing data taken under cloudy conditions results in a better agreement, in both correlation and slope, between the AOD retrievals and measurements from other co-located instruments.
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Wang, P., O. N. E. Tuinder, L. G. Tilstra, M. de Graaf, and P. Stammes. "Interpretation of FRESCO cloud retrievals in case of absorbing aerosol events." Atmospheric Chemistry and Physics 12, no. 19 (October 4, 2012): 9057–77. http://dx.doi.org/10.5194/acp-12-9057-2012.
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Abstract. Cloud and aerosol information is needed in trace gas retrievals from satellite measurements. The Fast REtrieval Scheme for Clouds from the Oxygen A band (FRESCO) cloud algorithm employs reflectance spectra of the O2 A band around 760 nm to derive cloud pressure and effective cloud fraction. In general, clouds contribute more to the O2 A band reflectance than aerosols. Therefore, the FRESCO algorithm does not correct for aerosol effects in the retrievals and attributes the retrieved cloud information entirely to the presence of clouds, and not to aerosols. For events with high aerosol loading, aerosols may have a dominant effect, especially for almost cloud free scenes. We have analysed FRESCO cloud data and Absorbing Aerosol Index (AAI) data from the Global Ozone Monitoring Experiment (GOME-2) instrument on the Metop-A satellite for events with typical absorbing aerosol types, such as volcanic ash, desert dust and smoke. We find that the FRESCO effective cloud fractions are correlated with the AAI data for these absorbing aerosol events and that the FRESCO cloud pressure contains information on aerosol layer pressure. For cloud free scenes, the derived FRESCO cloud pressure is close to the aerosol layer pressure, especially for optically thick aerosol layers. For cloudy scenes, if the strongly absorbing aerosols are located above the clouds, then the retrieved FRESCO cloud pressure may represent the height of the aerosol layer rather than the height of the clouds. Combining FRESCO and AAI data, an estimate for the aerosol layer pressure can be given.
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Dinh, Tra, and Stephan Fueglistaler. "Cirrus, Transport, and Mixing in the Tropical Upper Troposphere." Journal of the Atmospheric Sciences 71, no. 4 (March 27, 2014): 1339–52. http://dx.doi.org/10.1175/jas-d-13-0147.1.
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Abstract The impact of cloud radiative heating on transport time scales from the tropical upper troposphere to the stratosphere is studied in two-dimensional numerical simulations. Clouds are idealized as sources of radiative heating and are stochastically distributed in space and time. A spatial probability function constrains clouds to occur in only part of the domain to depict heterogeneously distributed clouds in the atmosphere. The transport time from the lower to upper boundaries (age of air) is evaluated with trajectories. The spectra of age of air obtained in the simulations are bimodal, with the first mode composed of trajectories that remain in the cloudy part of the domain during their passages from the lower to upper boundaries, and the second mode composed of the remaining trajectories that visit the cloud-free regions. For the first group of trajectories only, the mean age scales inversely with the time-mean radiative heating in cloudy air, and the one-dimensional advection–diffusion equation provides an adequate model for transport. However, the exchange between the cloudy and cloud-free regions renders the mean age over all trajectories (including those that visit the cloud-free region) much longer than the time expected if all air parcels remain in cloudy air. In addition, the overall mean age is not inversely proportional to the time-mean heating rate in cloudy air. Sensitivity calculations further show that the sizes, durations, and amplitudes of the individual clouds are also important to the transport time. The results show that the frequently used decomposition of radiative heating into clear-sky and cloud radiative heating may give incorrect interpretations regarding the time scale of transport into the stratosphere.
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Cho, Hyoun-Myoung, Shaima L. Nasiri, and Ping Yang. "Application of CALIOP Measurements to the Evaluation of Cloud Phase Derived from MODIS Infrared Channels." Journal of Applied Meteorology and Climatology 48, no. 10 (October 1, 2009): 2169–80. http://dx.doi.org/10.1175/2009jamc2238.1.
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Abstract In this study, Moderate Resolution Imaging Spectroradiometer (MODIS) infrared-based cloud thermodynamic phase retrievals are evaluated using Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) retrievals for the 6 months from January to June of 2008. The CALIOP 5-km cloud-layer product provides information on cloud opacity, cloud-top height, midlayer cloud temperature, and cloud thermodynamic phase. Comparisons are made between MODIS IR phase and CALIOP observations for single-layer clouds (54% of the cloudy CALIOP scenes) and for the top layer of the CALIOP scenes. Both CALIOP and MODIS retrieve larger fractions of water clouds in the single-layer cases than in the top-layer cases, demonstrating that focusing on only single-layer clouds may introduce a water-cloud bias. Of the single-layer clouds, 60% are transparent and 40% are opaque (defined by the lack of a CALIOP ground return). MODIS tends to classify single-layer clouds with midlayer temperatures below −40°C as ice; around −30°C nearly equally as ice, mixed, and unknown; between −28° and −15°C as mixed; and above 0°C as water. Ninety-five percent of the single-layer CALIOP clouds not detected by MODIS are transparent. Approximately ⅓ of transparent single-layer clouds with temperatures below −30°C are not detected by MODIS and close to another ⅓ are classified as ice, with the rest assigned as water, mixed, or unknown. CALIOP classes nearly all of these transparent cold clouds as ice.
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Tjernström, Michael, Joseph Sedlar, and Matthew D. Shupe. "How Well Do Regional Climate Models Reproduce Radiation and Clouds in the Arctic? An Evaluation of ARCMIP Simulations." Journal of Applied Meteorology and Climatology 47, no. 9 (September 1, 2008): 2405–22. http://dx.doi.org/10.1175/2008jamc1845.1.
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Abstract Downwelling radiation in six regional models from the Arctic Regional Climate Model Intercomparison (ARCMIP) project is systematically biased negative in comparison with observations from the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment, although the correlations with observations are relatively good. In this paper, links between model errors and the representation of clouds in these models are investigated. Although some modeled cloud properties, such as the cloud water paths, are reasonable in a climatological sense, the temporal correlation of model cloud properties with observations is poor. The vertical distribution of cloud water is distinctly different among the different models; some common features also appear. Most models underestimate the presence of high clouds, and, although the observed preference for low clouds in the Arctic is present in most of the models, the modeled low clouds are too thin and are displaced downward. Practically all models show a preference to locate the lowest cloud base at the lowest model grid point. In some models this happens also to be where the observations show the highest occurrence of the lowest cloud base; it is not possible to determine if this result is just a coincidence. Different factors contribute to model surface radiation errors. For longwave radiation in summer, a negative bias is present both for cloudy and clear conditions, and intermodel differences are smaller when clouds are present. There is a clear relationship between errors in cloud-base temperature and radiation errors. In winter, in contrast, clear-sky cases are modeled reasonably well, but cloudy cases show a very large intermodel scatter with a significant bias in all models. This bias likely results from a complete failure in all of the models to retain liquid water in cold winter clouds. All models overestimate the cloud attenuation of summer solar radiation for thin and intermediate clouds, and some models maintain this behavior also for thick clouds.
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Parent, A., R. E. Falconer, G. K. H. Lee, K. A. Meyer, and C. R. Stark. "The effect of internal gravity waves on cloud evolution in sub-stellar atmospheres." Astronomy & Astrophysics 635 (March 2020): A159. http://dx.doi.org/10.1051/0004-6361/201937063.
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Context. Sub-stellar objects exhibit photometric variability, which is believed to be caused by a number of processes, such as magnetically-driven spots or inhomogeneous cloud coverage. Recent sub-stellar models have shown that turbulent flows and waves, including internal gravity waves, may play an important role in cloud evolution. Aims. The aim of this paper is to investigate the effect of internal gravity waves on dust nucleation and dust growth, and whether observations of the resulting cloud structures could be used to recover atmospheric density information. Methods. For a simplified atmosphere in two dimensions, we numerically solved the governing fluid equations to simulate the effect on dust nucleation and mantle growth as a result of the passage of an internal gravity wave. Furthermore, we derived an expression that relates the properties of the wave-induced cloud structures to observable parameters in order to deduce the atmospheric density. Results. Numerical simulations show that the density, pressure, and temperature variations caused by gravity waves lead to an increase of the dust nucleation rate by up to a factor 20, and an increase of the dust mantle growth rate by up to a factor 1.6, compared to their equilibrium values. Through an exploration of the wider sub-stellar parameter space, we show that in absolute terms, the increase in dust nucleation due to internal gravity waves is stronger in cooler (T dwarfs) and TiO2-rich sub-stellar atmospheres. The relative increase, however, is greater in warm (L dwarf) and TiO2-poor atmospheres due to conditions that are less suited for efficient nucleation at equilibrium. These variations lead to banded areas in which dust formation is much more pronounced, similar to the cloud structures observed on Earth. Conclusions. We show that internal gravity waves propagating in the atmosphere of sub-stellar objects can produce banded clouds structures similar to that observed on Earth. We propose a method with which potential observations of banded clouds could be used to estimate the atmospheric density of sub-stellar objects.