Journal articles on the topic 'Radiation Bias'
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Diaz, Dayssy Alexandra, Gita Suneja, Reshma Jagsi, Parul Barry, Charles R. Thomas, Curtiland Deville, Karen Winkfield, Malika Siker, and Terri Bott-Kothari. "Mitigating Implicit Bias in Radiation Oncology." Advances in Radiation Oncology 6, no. 5 (September 2021): 100738. http://dx.doi.org/10.1016/j.adro.2021.100738.
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Hu, Zhiyuan, Zhangli Liu, Hua Shao, Zhengxuan Zhang, Bingxu Ning, Ming Chen, Dawei Bi, and Shichang Zou. "Radiation Hardening by Applying Substrate Bias." IEEE Transactions on Nuclear Science 58, no. 3 (June 2011): 1355–60. http://dx.doi.org/10.1109/tns.2011.2138160.
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Schneider, David P., and David B. Reusch. "Antarctic and Southern Ocean Surface Temperatures in CMIP5 Models in the Context of the Surface Energy Budget*." Journal of Climate 29, no. 5 (February 24, 2016): 1689–716. http://dx.doi.org/10.1175/jcli-d-15-0429.1.
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Abstract This study examines the biases, intermodel spread, and intermodel range of surface air temperature (SAT) across the Antarctic ice sheet and Southern Ocean in 26 structurally different climate models. Over the ocean (40°–60°S), an ensemble-mean warm bias peaks in late austral summer concurrently with the peak in the intermodel range of SAT. This warm bias lags a spring–summer positive bias in net surface radiation due to weak shortwave cloud forcing and is gradually reduced during autumn and winter. For the ice sheet, inconsistencies among reanalyses and observational datasets give low confidence in the ensemble-mean bias of SAT, but a small summer warm bias is suggested in comparison with nonreanalysis SAT data. The ensemble mean hides a large intermodel range of SAT, which peaks during the summer insolation maximum. In summer on the ice sheet, the SAT intermodel spread is largely associated with the surface albedo. In winter, models universally exhibit a too-strong deficit in net surface radiation related to the downward longwave radiation, implying that the lower atmosphere is too stable. This radiation deficit is balanced by the transfer of sensible heat toward the surface (which largely explains the intermodel spread in SAT) and by a subsurface heat flux. The winter bias in downward longwave radiation is due to the longwave cloud radiative effect, which the ensemble mean underestimates by a factor of 2. The implications of these results for improving climate simulations over Antarctica and the Southern Ocean are discussed.
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Fiddes, Sonya L., Alain Protat, Marc D. Mallet, Simon P. Alexander, and Matthew T. Woodhouse. "Southern Ocean cloud and shortwave radiation biases in a nudged climate model simulation: does the model ever get it right?" Atmospheric Chemistry and Physics 22, no. 22 (November 17, 2022): 14603–30. http://dx.doi.org/10.5194/acp-22-14603-2022.
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Abstract. The Southern Ocean radiative bias continues to impact climate and weather models, including the Australian Community Climate and Earth System Simulator (ACCESS). The radiative bias, characterised by too much shortwave radiation reaching the surface, is attributed to the incorrect simulation of cloud properties, including frequency and phase. To identify cloud regimes important to the Southern Ocean, we use k-means cloud histogram clustering, applied to a satellite product and then fitted to nudged simulations of the latest-generation ACCESS atmosphere model. We identify instances when the model correctly or incorrectly simulates the same cloud type as the satellite product for any point in time or space. We then evaluate the cloud and radiation biases in these instances. We find that when the ACCESS model correctly simulates the cloud type, cloud property and radiation biases of equivalent, or in some cases greater, magnitude remain compared to when cloud types are incorrectly simulated. Furthermore, we find that even when radiative biases appear small on average, cloud property biases, such as liquid or ice water paths or cloud fractions, remain large. Our results suggest that simply getting the right cloud type (or the cloud macrophysics) is not enough to reduce the Southern Ocean radiative bias. Furthermore, in instances where the radiative bias is small, it may be so for the wrong reasons. Considerable effort is still required to improve cloud microphysics, with a particular focus on cloud phase.
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Tuononen, Minttu, Ewan J. O'Connor, and Victoria A. Sinclair. "Evaluating solar radiation forecast uncertainty." Atmospheric Chemistry and Physics 19, no. 3 (February 14, 2019): 1985–2000. http://dx.doi.org/10.5194/acp-19-1985-2019.
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Abstract. The presence of clouds and their characteristics have a strong impact on the radiative balance of the Earth and on the amount of solar radiation reaching the Earth's surface. Many applications require accurate forecasts of surface radiation on weather timescales, for example solar energy and UV radiation forecasts. Here we investigate how operational forecasts of low and mid-level clouds affect the accuracy of solar radiation forecasts. A total of 4 years of cloud and solar radiation observations from one site in Helsinki, Finland, are analysed. Cloud observations are obtained from a ceilometer and therefore we first develop algorithms to reliably detect cloud base, precipitation, and fog. These new algorithms are widely applicable for both operational use and research, such as in-cloud icing detection for the wind energy industry and for aviation. The cloud and radiation observations are compared to forecasts from the Integrated Forecast System (IFS) run operationally and developed by the European Centre for Medium-Range Weather Forecasts (ECMWF). We develop methods to evaluate the skill of the cloud and radiation forecasts. These methods can potentially be extended to hundreds of sites globally. Over Helsinki, the measured global horizontal irradiance (GHI) is strongly influenced by its northerly location and the annual variation in cloudiness. Solar radiation forecast error is therefore larger in summer than in winter, but the relative error in the solar radiation forecast is more or less constant throughout the year. The mean overall bias in the GHI forecast is positive (8 W m−2). The observed and forecast distributions in cloud cover, at the spatial scales we are considering, are strongly skewed towards clear-sky and overcast situations. Cloud cover forecasts show more skill in winter when the cloud cover is predominantly overcast; in summer there are more clear-sky and broken cloud situations. A negative bias was found in forecast GHI for correctly forecast clear-sky cases and a positive bias in correctly forecast overcast cases. Temporal averaging improved the cloud cover forecast and hence decreased the solar radiation forecast error. The positive bias seen in overcast situations occurs when the model cloud has low values of liquid water path (LWP). We attribute this bias to the model having LWP values that are too low or the model optical properties for clouds with low LWP being incorrect.
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Črnivec, Nina, and Bernhard Mayer. "Quantifying the bias of radiative heating rates in numerical weather prediction models for shallow cumulus clouds." Atmospheric Chemistry and Physics 19, no. 12 (June 20, 2019): 8083–100. http://dx.doi.org/10.5194/acp-19-8083-2019.
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Abstract. The interaction between radiation and clouds represents a source of uncertainty in numerical weather prediction (NWP) due to both intrinsic problems of one-dimensional radiation schemes and poor representation of clouds. The underlying question addressed in this study is how large the NWP radiative bias is for shallow cumulus clouds and how it scales with various input parameters of radiation schemes, such as solar zenith angle, surface albedo, cloud cover and liquid water path. A set of radiative transfer calculations was carried out for a realistically evolving shallow cumulus cloud field stemming from a large-eddy simulation (LES). The benchmark experiments were performed on the highly resolved LES cloud scenes (25 m grid spacing) using a three-dimensional Monte Carlo radiation model. An absence of middle and high clouds is assumed above the shallow cumulus cloud layer. In order to imitate the poor representation of shallow cumulus in NWP models, cloud optical properties were horizontally averaged over the cloudy part of the boxes with dimensions comparable to NWP horizontal grid spacing (several kilometers), and the common δ-Eddington two-stream method with maximum-random overlap assumption for partial cloudiness was applied (denoted as the “1-D” experiment). The bias of the 1-D experiment relative to the benchmark was investigated in the solar and thermal parts of the spectrum, examining the vertical profile of heating rate within the cloud layer and the net surface flux. It is found that, during daytime and nighttime, the destabilization of the cloud layer in the benchmark experiment is artificially enhanced by an overestimation of the cooling at cloud top and an overestimation of the warming at cloud bottom in the 1-D experiment (a bias of about −15 K d−1 is observed locally for stratocumulus scenarios). This destabilization, driven by the thermal radiation, is maximized during nighttime, since during daytime the solar radiation has a stabilizing tendency. The daytime bias at the surface is governed by the solar fluxes, where the 1-D solar net flux overestimates (underestimates) the corresponding benchmark at low (high) Sun. The overestimation at low Sun (bias up to 80 % over land and ocean) is largest at intermediate cloud cover, while the underestimation at high Sun (bias up to −40 % over land and ocean) peaks at larger cloud cover (80 % and beyond). At nighttime, the 1-D experiment overestimates the amount of benchmark surface cooling with the maximal bias of about 50 % peaked at intermediate cloud cover. Moreover, an additional experiment was carried out by running the Monte Carlo radiation model in the independent column mode on cloud scenes preserving their LES structure (denoted as the “ICA” experiment). The ICA is clearly more accurate than the 1-D experiment (with respect to the same benchmark). This highlights the importance of an improved representation of clouds even at the resolution of today's regional (limited-area) numerical models, which needs to be considered if NWP radiative biases are to be efficiently reduced. All in all, this paper provides a systematic documentation of NWP radiative biases, which is a necessary first step towards an improved treatment of radiation–cloud interaction in atmospheric models.
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Bisht, Uma. "FinFET Response under Radiation and Bias Stress." International Journal for Research in Applied Science and Engineering Technology 9, no. 8 (August 31, 2021): 2895–900. http://dx.doi.org/10.22214/ijraset.2021.37893.
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Abstract: The study of FinFET Response under various parameters change is widely studied in many branches of Electronics Engineering. FinFET structure is going beyond the downscaling limit of the conventional planar CMOS technology. The major applications of FinFET have been mainly devoted to digital circuits, analog circuits, and targeting a successful mixed integration of analog and digital circuits. The purpose of this paper is to provide a clear and exhaustive understanding of the state of the art, challenges, and future trends of the FinFET technology from a microwave modeling perspective. Inspired by the traditional modeling techniques for conventional MOSFETs, different strategies have been proposed over the last years to model the FinFET behavior at gamma radiation. With the aim to support the development of this technology, a comparative study of the achieved results is carried out to gain both useful feedbacks to investigate the microwave FinFET performance as well as valuable modeling. Keywords: CMOS, MOSFET, FinFET, Hot carriers, Gamma Chamber, SCE, DIBL, Oslo Si-Bulk FinFET, Wafer probe station.
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Barton, Neil P., Stephen A. Klein, and James S. Boyle. "On the Contribution of Longwave Radiation to Global Climate Model Biases in Arctic Lower Tropospheric Stability." Journal of Climate 27, no. 19 (September 24, 2014): 7250–69. http://dx.doi.org/10.1175/jcli-d-14-00126.1.
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Abstract Previous research has found that global climate models (GCMs) usually simulate greater lower tropospheric stabilities compared to reanalysis data. To understand the origins of this bias, the authors examine hindcast simulations initialized with reanalysis data of six GCMs and find that four of the six models simulate within five days a positive bias in Arctic lower tropospheric stability during the Arctic polar night over sea ice regions. These biases in lower tropospheric stability are mainly due to cold biases in surface temperature, as very small potential temperature biases exist aloft. Similar to previous research, polar night surface temperature biases in the hindcast runs relate to all-sky downwelling longwave radiation in the models, which very much relates to the cloud liquid water. Also found herein are clear-sky longwave radiation biases and a fairly large clear-sky longwave radiation bias in the day one hindcast. This clear-sky longwave bias is analyzed by running the same radiation transfer model for each model’s temperature and moisture profile, and the model spread in clear-sky downwelling longwave radiation with the same radiative transfer model is found to be much less, suggesting that model differences other than temperature and moisture are aiding in the spread in downwelling longwave radiation. The six models were also analyzed in Atmospheric Model Intercomparison Project (AMIP) mode to determine if hindcast simulations are analogous to free-running simulations. Similar winter lower tropospheric stability biases occur in four of the six models with surface temperature biases relating to the winter lower tropospheric stability values.
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Haddeland, I., J. Heinke, F. Voß, S. Eisner, C. Chen, S. Hagemann, and F. Ludwig. "Effects of climate model radiation, humidity and wind estimates on hydrological simulations." Hydrology and Earth System Sciences 16, no. 2 (February 2, 2012): 305–18. http://dx.doi.org/10.5194/hess-16-305-2012.
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Abstract. Due to biases in the output of climate models, a bias correction is often needed to make the output suitable for use in hydrological simulations. In most cases only the temperature and precipitation values are bias corrected. However, often there are also biases in other variables such as radiation, humidity and wind speed. In this study we tested to what extent it is also needed to bias correct these variables. Responses to radiation, humidity and wind estimates from two climate models for four large-scale hydrological models are analysed. For the period 1971–2000 these hydrological simulations are compared to simulations using meteorological data based on observations and reanalysis; i.e. the baseline simulation. In both forcing datasets originating from climate models precipitation and temperature are bias corrected to the baseline forcing dataset. Hence, it is only effects of radiation, humidity and wind estimates that are tested here. The direct use of climate model outputs result in substantial different evapotranspiration and runoff estimates, when compared to the baseline simulations. A simple bias correction method is implemented and tested by rerunning the hydrological models using bias corrected radiation, humidity and wind values. The results indicate that bias correction can successfully be used to match the baseline simulations. Finally, historical (1971–2000) and future (2071–2100) model simulations resulting from using bias corrected forcings are compared to the results using non-bias corrected forcings. The relative changes in simulated evapotranspiration and runoff are relatively similar for the bias corrected and non bias corrected hydrological projections, although the absolute evapotranspiration and runoff numbers are often very different. The simulated relative and absolute differences when using bias corrected and non bias corrected climate model radiation, humidity and wind values are, however, smaller than literature reported differences resulting from using bias corrected and non bias corrected climate model precipitation and temperature values.
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Haddeland, I., J. Heinke, F. Voß, S. Eisner, C. Chen, S. Hagemann, and F. Ludwig. "Effects of climate model radiation, humidity and wind estimates on hydrological simulations." Hydrology and Earth System Sciences Discussions 8, no. 4 (August 22, 2011): 7919–45. http://dx.doi.org/10.5194/hessd-8-7919-2011.
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Abstract. Due to biases in the output of climate models, a bias correction is often needed to make the output suitable for use in hydrological simulations. In most cases only the temperature and precipitation values are bias corrected. However, often there are also biases in other variables such as radiation, humidity and wind speed. In this study we tested to what extent it is also needed to bias correct these variables. Responses to radiation, humidity and wind estimates from two climate models for four large-scale hydrological models are analysed. For the period 1971–2000 these hydrological simulations are compared to simulations using meteorological data based on observations and reanalysis; i.e. the baseline simulation. In both forcing datasets originating from climate models precipitation and temperature are bias corrected to the baseline forcing dataset. Hence, it is only effects of radiation, humidity and wind estimates that are tested here. The direct use of climate model outputs result in substantial different evapotranspiration and runoff estimates, when compared to the baseline simulations. A simple bias correction method is implemented and tested by rerunning the hydrological models using bias corrected radiation, humidity and wind values. The results indicate that bias correction can successfully be used to match the baseline simulations. Finally, historical (1971–2000) and future (2071–2100) model simulations resulting from using bias corrected forcings are compared to the results using non-bias corrected forcings. The relative changes in simulated evapotranspiration and runoff are relatively similar for the bias corrected and non bias corrected hydrological projections, although the absolute evapotranspiration and runoff numbers are often very different. The simulated relative and absolute differences when using bias corrected and non bias corrected climate model radiation, humidity and wind values are, however, smaller than literature reported differences resulting from using bias corrected and non bias corrected climate model precipitation and temperature values.
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Bowman, K. W., D. T. Shindell, H. M. Worden, J. F. Lamarque, P. J. Young, D. S. Stevenson, Z. Qu, et al. "Evaluation of ACCMIP outgoing longwave radiation from tropospheric ozone using TES satellite observations." Atmospheric Chemistry and Physics 13, no. 8 (April 18, 2013): 4057–72. http://dx.doi.org/10.5194/acp-13-4057-2013.
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Abstract. We use simultaneous observations of tropospheric ozone and outgoing longwave radiation (OLR) sensitivity to tropospheric ozone from the Tropospheric Emission Spectrometer (TES) to evaluate model tropospheric ozone and its effect on OLR simulated by a suite of chemistry-climate models that participated in the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP). The ensemble mean of ACCMIP models show a persistent but modest tropospheric ozone low bias (5–20 ppb) in the Southern Hemisphere (SH) and modest high bias (5–10 ppb) in the Northern Hemisphere (NH) relative to TES ozone for 2005–2010. These ozone biases have a significant impact on the OLR. Using TES instantaneous radiative kernels (IRK), we show that the ACCMIP ensemble mean tropospheric ozone low bias leads up to 120 mW m−2 OLR high bias locally but zonally compensating errors reduce the global OLR high bias to 39 ± 41 m Wm−2 relative to TES data. We show that there is a correlation (R2 = 0.59) between the magnitude of the ACCMIP OLR bias and the deviation of the ACCMIP preindustrial to present day (1750–2010) ozone radiative forcing (RF) from the ensemble ozone RF mean. However, this correlation is driven primarily by models whose absolute OLR bias from tropospheric ozone exceeds 100 m Wm−2. Removing these models leads to a mean ozone radiative forcing of 394 ± 42 m Wm−2. The mean is about the same and the standard deviation is about 30% lower than an ensemble ozone RF of 384 ± 60 m Wm−2 derived from 14 of the 16 ACCMIP models reported in a companion ACCMIP study. These results point towards a profitable direction of combining satellite observations and chemistry-climate model simulations to reduce uncertainty in ozone radiative forcing.
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Budaev, Bair V., and David B. Bogy. "The role of EM wave polarization on radiative heat transfer across a nanoscale gap." Journal of Applied Physics 132, no. 5 (August 7, 2022): 054903. http://dx.doi.org/10.1063/5.0094382.
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This work presents a novel study of radiative heat transfer between closely separated plates based on an extension of Planck’s spectrum of thermal radiations to systems with a steady heat flux. This extension together with electromagnetic wave theory is chosen specifically to avoid the commonly used so-called fluctuation dissipation theory, which is also limited to equilibrium systems. The spectrum of thermal radiation with a heat flux is described by the introduction of an analog of a chemical potential, which creates a bias toward the direction of heat transfer. This is the first comprehensive study of radiative heat transfer based on the generalization of Planck’s spectrum for systems with a heat flux, which eliminates contradictions arising when a heat flux is described in terms of the laws limited to equilibrium systems. The total heat flux is split into fluxes carried by waves with different frequencies, directions of propagation, and polarizations. This simplifies the analysis because due to the stochastic independence, the energy fluxes of such waves are additive, and this also reveals that the heat carrying capacity of radiation with the parallel polarization is significantly higher than that of the perpendicularly polarized radiation. This suggests that the rate of radiative heat transfer may be noticeably increased by the control of the polarization of thermal radiation.
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Paquin-Ricard, Danahé, Colin Jones, and Paul A. Vaillancourt. "Using ARM Observations to Evaluate Cloud and Clear-Sky Radiation Processes as Simulated by the Canadian Regional Climate Model GEM." Monthly Weather Review 138, no. 3 (March 1, 2010): 818–38. http://dx.doi.org/10.1175/2009mwr2745.1.
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Abstract The total downwelling shortwave (SWD) and longwave (LWD) radiation and its components are assessed for the limited-area version of the Global Environmental Multiscale Model (GEM-LAM) against Atmospheric Radiation Measurements (ARM) at two sites: the southern Great Plains (SGP) and the North Slope of Alaska (NSA) for the 1998–2005 period. The model and observed SWD and LWD are evaluated as a function of the cloud fraction (CF), that is, for overcast and clear-sky conditions separately, to isolate and analyze different interactions between radiation and 1) atmospheric aerosols and water vapor and 2) cloud liquid water. Through analysis of the mean diurnal cycle and normalized frequency distributions of surface radiation fluxes, the primary radiation error in GEM-LAM is seen to be an excess in SWD in the middle of the day. The SWD bias results from a combination of underestimated CF and clouds, when present, possessing a too-high solar transmissivity, which is particularly the case for optically thin clouds. Concurrent with the SWD bias, a near-surface warm bias develops in GEM-LAM, particularly at the SGP site in the summer. The ultimate cause of this warm bias is difficult to uniquely determine because of the range of complex interactions between the surface, atmospheric, and radiation processes that are involved. Possible feedback loops influencing this warm bias are discussed. The near-surface warm bias is the primary cause of an excess clear-sky LWD. This excess is partially balanced with respect to the all-sky LWD by an underestimated CF, which causes a negative bias in simulated all-sky emissivity. It is shown that there is a strong interaction between all the components influencing the simulated surface radiation fluxes with frequent error compensation, emphasizing the need to evaluate the individual radiation components at high time frequency.
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CHAKRABORTY, ARINDAM, and J. SRINIVASAN. "Comparison of radiative fluxes at the top of the atmosphere from INSAT and ERBE." MAUSAM 54, no. 1 (January 18, 2022): 299–314. http://dx.doi.org/10.54302/mausam.v54i1.1514.
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An accurate knowledge of radiative fluxes at the Top of the Atmosphere (TOA) is necessary to study the variability of climate. Many geostationary satellites have been measuring radiative fluxes in a narrow spectral band in the infrared and visible regions during the past 30 years. This data will be useful for climate studies if it can be converted to total radiative fluxes. In this paper we demonstrate that the errors in monthly mean Outgoing Longwave Radiation (OLR) at the TOA obtained from the Indian geostationary satellite INSAT-1B is less than 15 W m-2 in most of the regions when compared to the data from the Earth Radiation Budget Experiment (ERBE). This indicates that the conversion of INSAT narrowband flux to broadband flux does not result in large errors. This could be on account of high water vapour content in the Indian region. The error in INSAT OLR has been shown to be dependent on number of images available per month. INSAT albedo has a negative bias over ocean when compared to ERBE on account of the isotropic reflectance assumption. No such bias was noticed over land. This low albedo bias in INSAT was removed by adding a constant term equal to 2% over ocean. It has been shown that the effect of Sun Glint in clear sky albedo can be removed if two images per day are used for the calculation of albedo. The difference in net radiation at the TOA between INSAT and ERBE has been shown to be within 10 W m-2. In some regions, such as Saudi Arabia (from December 1988 to March 1989) the difference between ERBE and INSAT estimated net radiation (~10 W m-2) was found to be less than the difference between two ERBE satellite observations (~20 W m-2). This indicates clearly that diurnal variation of net radiation can cause large errors in the estimates of monthly mean net radiation.
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Oyedele, J. A. "The bias in radiation diagnosis of fluctuating voids." Applied Radiation and Isotopes 50, no. 4 (April 1999): 773–81. http://dx.doi.org/10.1016/s0969-8043(98)00091-8.
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Serry, Mohamed, AbdelHameed Sharaf, Ahmed Emira, Ahmed Abdul-Wahed, and Asmaa Gamal. "Nanostructured graphene–Schottky junction low-bias radiation sensors." Sensors and Actuators A: Physical 232 (August 2015): 329–40. http://dx.doi.org/10.1016/j.sna.2015.04.031.
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Kottayil, Ajil, Stefan A. Buehler, Viju O. John, Larry M. Miloshevich, M. Milz, and G. Holl. "On the Importance of Vaisala RS92 Radiosonde Humidity Corrections for a Better Agreement between Measured and Modeled Satellite Radiances." Journal of Atmospheric and Oceanic Technology 29, no. 2 (February 1, 2012): 248–59. http://dx.doi.org/10.1175/jtech-d-11-00080.1.
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Abstract A study has been carried out to assess the importance of radiosonde corrections in improving the agreement between satellite and radiosonde measurements of upper-tropospheric humidity. Infrared [High Resolution Infrared Radiation Sounder (HIRS)-12] and microwave [Advanced Microwave Sounding Unit (AMSU)-18] measurements from the NOAA-17 satellite were used for this purpose. The agreement was assessed by comparing the satellite measurements against simulated measurements using collocated radiosonde profiles of the Atmospheric Radiation Measurement (ARM) Program undertaken at tropical and midlatitude sites. The Atmospheric Radiative Transfer Simulator (ARTS) was used to simulate the satellite radiances. The comparisons have been done under clear-sky conditions, separately for daytime and nighttime soundings. Only Vaisala RS92 radiosonde sensors were used and an empirical correction (EC) was applied to the radiosonde measurements. The EC includes correction for mean calibration bias and for solar radiation error, and it removes radiosonde bias relative to three instruments of known accuracy. For the nighttime dataset, the EC significantly reduces the bias from 0.63 to −0.10 K in AMSU-18 and from 1.26 to 0.35 K in HIRS-12. The EC has an even greater impact on the daytime dataset with a bias reduction from 2.38 to 0.28 K in AMSU-18 and from 2.51 to 0.59 K in HIRS-12. The present study promises a more accurate approach in future radiosonde-based studies in the upper troposphere.
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Cavallo, Steven M., Jimy Dudhia, and Chris Snyder. "A Multilayer Upper-Boundary Condition for Longwave Radiative Flux to Correct Temperature Biases in a Mesoscale Model." Monthly Weather Review 139, no. 6 (June 1, 2011): 1952–59. http://dx.doi.org/10.1175/2010mwr3513.1.
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Abstract An upper-level cold bias in potential temperature tendencies of 10 K day−1, strongest at the top of the model, is observed in Weather Research and Forecasting (WRF) model forecasts. The bias originates from the Rapid Radiative Transfer Model longwave radiation physics scheme and can be reduced substantially by 1) modifying the treatment within the scheme by adding a multilayer buffer between the model top and top of the atmosphere and 2) constraining stratospheric water vapor to remain within the estimated climatology in the stratosphere. These changes reduce the longwave heating rate bias at the model top to ±0.5 K day−1. Corresponding bias reductions are also seen, particularly near the tropopause.
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Hassan, Mahmoud A. "Negative Capacitance Phenomena in CZT Room Temperature Radiation Detectors." Materials Science Forum 480-481 (March 2005): 399–404. http://dx.doi.org/10.4028/www.scientific.net/msf.480-481.399.
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CdZnTe , Cadmium zinc telluride (CZT) is an interesting room temperature radiation detector. This research paper is reporting a negative capacitance behavior of CZT detectors at bias voltages around 60V. Initially at 0V, the CZT capacitance is positive and decreases with bias voltage increase. At around 60V, the measured capacitance approaches zero, then with small voltage increase , capacitance value reverses sign and starts to increase in the negative direction with increasing bias voltage . This effect is stable at 100 kHz. The behavior of low and other quality detectors can differ, low quality detectors can show negative capacitance at low bias voltages and low frequencies. The initial explanation of this phenomena is due to non-uniform distribution of impurities inside the bulk material.
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Mochizuki, Toshimitsu, Iwao Kawayama, Masayoshi Tonouchi, Yoshihiko Nishihara, Msayuki Chikamatsu, Yuji Yoshida, and Hidetaka Takato. "Instantaneous Photocarrier Transport at the Interface in Perovskite Solar Cells to Generate Photovoltage." Photonics 9, no. 5 (May 6, 2022): 316. http://dx.doi.org/10.3390/photonics9050316.
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The instantaneous photocarrier transport of perovskite solar cells was evaluated by assessing laser-induced terahertz (THz) emission to understand carrier dynamics in perovskite solar cells. The waveform of laser-induced THz radiation from an interface between the TiO2 electron transport layer and perovskite active layer of an n-i-p perovskite solar cell with varying external bias was measured using THz-time domain spectroscopy. The amplitude of the THz radiation decreased with increasing reverse bias voltage. The waveform of the THz radiation was inverted at a strong reverse bias. The measured bias voltage dependence suggests that the transient current generated at the interface between perovskite and TiO2 owing to the higher mobility of electrons than that of holes, namely the photo-Dember effect, is the dominant source of THz radiation and the destructive contribution of the interfacial electric field inverts the transient current when a reverse bias causes a strong interfacial electric field. The significant contribution of the interfacial electric field has not been previously reported in perovskite thin films and is unique to solar cells. We believe that band bending at interfaces in perovskite solar cells will be determined from the THz emission with proper modeling.
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Dipu, S., G. Pandithurai, A. S. Panicker, T. Takamura, Dong-In Lee, and Dongchul Kim. "Assessment and Validation of i-Skyradiometer Retrievals Using Broadband Flux and MODIS Data." Advances in Meteorology 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/849279.
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Ground-based network of cloud measurements is presently limited and there exists uncertainty in the cloud microphysical parameters derived from ground-based measurements. Bias in the i-skyradiometer derived cloud optical depth (τc) and droplet effective radius (Reff) and the importance of these parameters in the parameterization of clouds in climate models have made us intend to develop a possible method for improving these parameters. A new combination method, which uses zenith sky transmittance and surface radiation measurements, has been proposed in the present study to improve the retrievals. The i-skyradiometer derived parametersτcandReffhave been provided as a first guess to a radiative transfer model (SBDART) and a new retrieval algorithm has been implemented to obtain the best combination ofτcandReffhaving minimum bias (−0.09 and −2.5) between the simulated global and diffuse fluxes at the surface with the collocated surface radiation measurements. The new retrieval method has improvedτcandReffvalues compared to those derived using the transmittance only method and are in good agreement with the MODIS satellite retrievals. The study therefore suggests a possible improvement of the i-skyradiometer derived cloud parameters using observed radiation fluxes and a radiative transfer model.
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Zrnić, Dusan, Richard Doviak, Guifu Zhang, and Alexander Ryzhkov. "Bias in Differential Reflectivity due to Cross Coupling through the Radiation Patterns of Polarimetric Weather Radars." Journal of Atmospheric and Oceanic Technology 27, no. 10 (October 1, 2010): 1624–37. http://dx.doi.org/10.1175/2010jtecha1350.1.
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Abstract Examined is bias in differential reflectivity and its effect on estimates of rain rate due to coupling of the vertically and horizontally polarized fields through the radiation patterns. To that end, a brief review of the effects of the bias on quantitative rainfall measurements is given. Suggestions for tolerable values of this bias are made. Of utmost interest is the bias produced by radars simultaneously transmitting horizontally and vertically polarized fields, as this configuration has been chosen for pending upgrades to the U.S. national network of radars (Weather Surveillance Radar-1988 Doppler; WSR-88D). The bias strongly depends on the cross-polar radiation pattern. Two patterns, documented in the literature, are considered.
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Djoman, Maurice Aka, Wanignon Ferdinand Fassinou, and Augustin Memeledje. "Calibration of Ångström-Prescott Coefficients to Estimate Global Solar Radiation in Côte d’Ivoire." European Scientific Journal, ESJ 17, no. 37 (October 30, 2021): 24. http://dx.doi.org/10.19044/esj.2021.v17n37p24.
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In this study, we used monthly mean daily global radiation data and sunshine durations from nine (9) weather stations in Côte d’Ivoire to determine the annual Ångström-Prescott coefficients. The calibration of the Ångström-Prescott equation has been done through linear regression using the least square method. The empirical coefficients obtained are utilized to predict the global horizontal irradiance over the nine (9) weather stations of interest. Estimated and measured global radiations were compared using the root mean square error (RMSE), the mean bias error (MBE), the mean absolute bias error (MABE), the mean percentage error (MPE), the Nash-Sutcliffe coefficient of efficiency (NSE), and the statistic -test (). The low values of the statistic t-test (from 0.10 to 1.07) and MPE (from -0.413 to 0.201) indicate a good performance of the model. The high values of the coefficient of determination R² (from 0.9776 to 0.9916) show a remarkable agreement between predicted and measured global solar radiations. This remark is also confirmed by the high values of NSE (from 0.8671 to 0.9819) closer to 1. The obtained values of MBE (from -18.17 to 8.69 kWh/m²), MABE (from 7.16 to 8.52 kWh/m²), and RMSE (69.1 to 167.3 kWh/m²) show a low deviation or bias between the estimate and the measurements. The Ångström-Prescott coefficients determinants are consistent and can be used to efficiently calculate the global horizontal irradiance. The model established can be recommended to be used in the nine (9) weather stations to accurately estimate global solar radiation on horizontal surfaces.
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Ruiz-Arias, José A., Clara Arbizu-Barrena, Francisco J. Santos-Alamillos, Joaquín Tovar-Pescador, and David Pozo-Vázquez. "Assessing the Surface Solar Radiation Budget in the WRF Model: A Spatiotemporal Analysis of the Bias and Its Causes." Monthly Weather Review 144, no. 2 (February 1, 2016): 703–11. http://dx.doi.org/10.1175/mwr-d-15-0262.1.
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Abstract Solar radiation plays a key role in the atmospheric system but its distribution throughout the atmosphere and at the surface is still very uncertain in atmospheric models, and further assessment is required. In this study, the shortwave downward total solar radiation flux (SWD) predicted by the Weather Research and Forecasting (WRF) Model at the surface is validated over Spain for a 10-yr period based on observations of a network of 52 radiometric stations. In addition to the traditional pointwise validation of modeled data, an original spatially continuous evaluation of the SWD bias is also conducted using a principal component analysis. Overall, WRF overestimates the mean observed SWD by 28.9 W m−2, while the bias of ERA-Interim, which provides initial and boundary conditions to WRF, is only 15.0 W m−2. An important part of the WRF SWD bias seems to be related to a very low cumulus cloud amount in the model and, possibly, a misrepresentation of the radiative impact of this type of cloud.
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Baek, Eun-Hyuk, Jungeun Bae, Hyun-Joon Sung, Euihyun Jung, Baek-Min Kim, and Jee-Hoon Jeong. "Characteristics of High-Latitude Climate and Cloud Simulation in Community Atmospheric Model Version 6 (CAM6)." Atmosphere 13, no. 6 (June 9, 2022): 936. http://dx.doi.org/10.3390/atmos13060936.
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Many global climate models (GCMs) have difficulty in simulating climate variabilities over high northern latitudes. One of the main reasons is the inability of GCMs to simulate proper cloud fraction and the amount of liquid-containing cloud over the region. This study assessed the impact of cloud simulation in high latitudes by comparing the long-term parallel simulations of Community Atmosphere Model version 6 (CAM6) and CAM5, the previous version. The results show that the CAM6 simulation exhibits a considerable improvement in the Arctic, especially by reducing the cold bias of CAM5 throughout the year. Over the sub-Arctic region, however, CAM6 produces an excessive cold bias in summer and a warm bias in winter compared to the observation, which is closely related to the overestimation of cloud fraction and the amount of cloud liquid. In summer, the overestimation of the cloud in CAM6 tends to alleviate the cold bias compared to CAM5 due to an increase in downward longwave radiation over the high latitudes, while causing the excessive cold bias by blocking downward shortwave radiation over the sub-Arctic land area. In winter, when there is little incidence of shortwave radiation, the overestimation of the cloud in CAM6 increases the downward longwave radiation, which alleviates the cold bias in CAM5 over the Arctic but induces an excessive warm bias over the sub-Arctic land. The excessive cloudiness in CAM6 could weaken the high-latitude internal variability, exacerbating the deteriorating climate variability and long-term trend simulations in the region.
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Bisht, Uma. "FinFET Response under Radiation and Bias Stress: A Review." International Journal for Research in Applied Science and Engineering Technology 9, no. 9 (September 30, 2021): 76–80. http://dx.doi.org/10.22214/ijraset.2021.37929.
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Abstract: Electronics devices are made on IC’s, the basic building block of these IC’s are transistors. Transistors are continuously upgraded to new forms from conventional BJT to the latest FinFET. The purpose of this paper is to provide a clear and exhaustive understanding of the state of the art, challenges, and future trends of silicon based devices to produced reliable output for a longer time period even in abnormal conditions like in space. The modeling techniques for the conventional transistor, different strategies have been proposed over the last years to model the FinFET behavior and increasing the storage capacity of the IC by increasing the number of transistors without occupying more space on the same IC. The behavior of the device is impacted by radiation, heat, and temperature, by which the overall performance of the devices is affected a lot. Keywords: CMOS, MOSFET, FinFET, diode, transistor, subthreshold voltage, threshold voltage, electromigration, and charge trapping.
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Gadgil, Sulochana, Asha Guruprasad, and J. Srinivasan. "Systematic Bias in the NOAA Outgoing Longwave Radiation Dataset?" Journal of Climate 5, no. 8 (August 1992): 867–75. http://dx.doi.org/10.1175/1520-0442(1992)005<0867:sbitno>2.0.co;2.
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Zhang, Enxia, Cher Xuan Zhang, Daniel M. Fleetwood, Ronald D. Schrimpf, Sarit Dhar, Sei-Hyung Ryu, Xiao Shen, and Sokrates T. Pantelides. "Bias-Temperature Instabilities and Radiation Effects on SiC MOSFETs." ECS Transactions 35, no. 4 (December 16, 2019): 369–80. http://dx.doi.org/10.1149/1.3572294.
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Mikuž, M., V. Cindro, G. Kramberger, and D. Žontar. "Bias dependence and bistability of radiation defects in silicon." Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 466, no. 2 (July 2001): 345–53. http://dx.doi.org/10.1016/s0168-9002(01)00584-8.
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Holmes-Siedle, A., L. Adams, B. Pauly, and S. Marsden. "Linearity of pMOS radiation dosimeters operated at zero bias." Electronics Letters 21, no. 13 (1985): 570. http://dx.doi.org/10.1049/el:19850403.
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Vömel, H., H. Selkirk, L. Miloshevich, J. Valverde-Canossa, J. Valdés, E. Kyrö, R. Kivi, W. Stolz, G. Peng, and J. A. Diaz. "Radiation Dry Bias of the Vaisala RS92 Humidity Sensor." Journal of Atmospheric and Oceanic Technology 24, no. 6 (June 2007): 953–63. http://dx.doi.org/10.1175/jtech2019.1.
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The comparison of simultaneous humidity measurements by the Vaisala RS92 radiosonde and by the Cryogenic Frostpoint Hygrometer (CFH) launched at Alajuela, Costa Rica, during July 2005 reveals a large solar radiation dry bias of the Vaisala RS92 humidity sensor and a minor temperature-dependent calibration error. For soundings launched at solar zenith angles between 10° and 30°, the average dry bias is on the order of 9% at the surface and increases to 50% at 15 km. A simple pressure- and temperature-dependent correction based on the comparison with the CFH can reduce this error to less than 7% at all altitudes up to 15.2 km, which is 700 m below the tropical tropopause. The correction does not depend on relative humidity, but is able to reproduce the relative humidity distribution observed by the CFH.
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Zhou, X. J., D. M. Fleetwood, J. A. Felix, E. P. Gusev, and C. D'Emic. "Bias-temperature instabilities and radiation effects in MOS devices." IEEE Transactions on Nuclear Science 52, no. 6 (December 2005): 2231–38. http://dx.doi.org/10.1109/tns.2005.860667.
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Los, Alexander, and Peter G. Duynkerke. "Parametrization of solar radiation in inhomogeneous stratocumulus: Albedo bias." Quarterly Journal of the Royal Meteorological Society 127, no. 575 (July 2001): 1593–614. http://dx.doi.org/10.1002/qj.49712757507.
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Kuai, Le, Kevin W. Bowman, Kazuyuki Miyazaki, Makoto Deushi, Laura Revell, Eugene Rozanov, Fabien Paulot, et al. "Attribution of Chemistry-Climate Model Initiative (CCMI) ozone radiative flux bias from satellites." Atmospheric Chemistry and Physics 20, no. 1 (January 8, 2020): 281–301. http://dx.doi.org/10.5194/acp-20-281-2020.
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Abstract. The top-of-atmosphere (TOA) outgoing longwave flux over the 9.6 µm ozone band is a fundamental quantity for understanding chemistry–climate coupling. However, observed TOA fluxes are hard to estimate as they exhibit considerable variability in space and time that depend on the distributions of clouds, ozone (O3), water vapor (H2O), air temperature (Ta), and surface temperature (Ts). Benchmarking present-day fluxes and quantifying the relative influence of their drivers is the first step for estimating climate feedbacks from ozone radiative forcing and predicting radiative forcing evolution. To that end, we constructed observational instantaneous radiative kernels (IRKs) under clear-sky conditions, representing the sensitivities of the TOA flux in the 9.6 µm ozone band to the vertical distribution of geophysical variables, including O3, H2O, Ta, and Ts based upon the Aura Tropospheric Emission Spectrometer (TES) measurements. Applying these kernels to present-day simulations from the Chemistry-Climate Model Initiative (CCMI) project as compared to a 2006 reanalysis assimilating satellite observations, we show that the models have large differences in TOA flux, attributable to different geophysical variables. In particular, model simulations continue to diverge from observations in the tropics, as reported in previous studies of the Atmospheric Chemistry Climate Model Intercomparison Project (ACCMIP) simulations. The principal culprits are tropical middle and upper tropospheric ozone followed by tropical lower tropospheric H2O. Five models out of the eight studied here have TOA flux biases exceeding 100 mW m−2 attributable to tropospheric ozone bias. Another set of five models have flux biases over 50 mW m−2 due to H2O. On the other hand, Ta radiative bias is negligible in all models (no more than 30 mW m−2). We found that the atmospheric component (AM3) of the Geophysical Fluid Dynamics Laboratory (GFDL) general circulation model and Canadian Middle Atmosphere Model (CMAM) have the lowest TOA flux biases globally but are a result of cancellation of opposite biases due to different processes. Overall, the multi-model ensemble mean bias is -133±98 mW m−2, indicating that they are too atmospherically opaque due to trapping too much radiation in the atmosphere by overestimated tropical tropospheric O3 and H2O. Having too much O3 and H2O in the troposphere would have different impacts on the sensitivity of TOA flux to O3 and these competing effects add more uncertainties on the ozone radiative forcing. We find that the inter-model TOA outgoing longwave radiation (OLR) difference is well anti-correlated with their ozone band flux bias. This suggests that there is significant radiative compensation in the calculation of model outgoing longwave radiation.
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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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Marchand, Mathilde, Yves-Marie Saint-Drenan, Laurent Saboret, Etienne Wey, and Lucien Wald. "Performance of CAMS Radiation Service and HelioClim-3 databases of solar radiation at surface: evaluating the spatial variation in Germany." Advances in Science and Research 17 (July 14, 2020): 143–52. http://dx.doi.org/10.5194/asr-17-143-2020.
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Abstract. The present work deals with the spatial consistency of two well-known databases of solar radiation received at ground level: the CAMS Radiation Service database version 3.2, abbreviated as CAMS-Rad and the HelioClim-3 database version 5, abbreviated as HC3v5. Both databases are derived from satellite images. They are validated against 10 min means of irradiance for the period 2010–2018 recorded in a network of 26 ground stations in Germany operated by the Deutscher Wetterdienst (DWD). For the CAMS-Rad database, the correlation coefficient between ground measurements and estimates ranges between 0.83 and 0.92 for all sky conditions. The bias ranges from −41 and 32 W m−2 (−11 % and 10 % of the mean irradiance). The standard deviation ranges between 89 and 129 W m−2 (25 % and 39 %). For the HC3v5 database, the correlation coefficient ranges between 0.90 and 0.95. The bias and the standard deviation are comprised between −22 and 16 W m−2 (−6 % and 5 %), and between respectively 70 and 104 W m−2 (20 % and 31 %). For the CAMS Rad database, overestimation is observed in the South, and underestimation in the North with a faint tendency of the bias to increase from East to West. For the HC3v5 database, the bias is fairly homogeneous across Germany. For both databases, there is no noticeable spatial trend in the standard deviation.
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Gimeno García, S., T. Trautmann, and V. Venema. "Reduction of radiation biases by incorporating the missing cloud variability via downscaling techniques: a study using the 3-D MoCaRT model." Atmospheric Measurement Techniques Discussions 5, no. 1 (February 14, 2012): 1543–73. http://dx.doi.org/10.5194/amtd-5-1543-2012.
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Abstract. To handle complexity to the smallest detail in atmospheric radiative transfer models is in practice unfeasible. 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, esp. for climate modeling 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 much more complexity than the one-dimensional ones providing a more accurate solution of the radiative transfer. In turn, one-dimensional models 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 finer resolution. Performing the radiative transfer within the spatially fine-resolved cloud fields noticeably helps to improve the radiation results. In the framework of this paper, we aim at characterizing cloud heterogeneity effects on radiances and broadband flux densities, 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 flux densities in the presence of realistic inhomogeneous cloud fields sampled at fine spatial resolutions are calculated and compared to their one-dimensional counterparts at coarser resolutions.
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Peng, Xiaomin, Jiangfeng She, Shuhua Zhang, Junzhong Tan, and Yang Li. "Evaluation of Multi-Reanalysis Solar Radiation Products Using Global Surface Observations." Atmosphere 10, no. 2 (January 22, 2019): 42. http://dx.doi.org/10.3390/atmos10020042.
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Solar radiation incident at the Earth’s surface is an essential driver of the energy exchange between the atmosphere and the surface and is also an important input variable in the research on the surface eco-hydrological process. The reanalysis solar radiation dataset is characterized by a long time series and wide spatial coverage and is used in the research of large-scale eco-hydrological processes. Due to certain errors in their production process of the reanalysis of solar radiation products, reanalysis products should be evaluated before application. In this study, three global solar-radiation reanalysis products (ERA-Interim; JRA-55; and NCEP-DOE) in different temporal scales and climate zones were evaluated using surface solar-radiation observations from the National Meteorological Information Center of the China Meteorological Administration (CMA, Beijing, China) and the Global Energy Balance Archive (GEBA, Zürich, Switzerland) from 2000 to 2009. All reanalysis products (ERA-Interim; JRA-55; and NCEP-DOE) overestimated with an annual bias of 14.86 W/m2, 22.61 W/m2, and 31.85 W/m2; monthly bias of 15.17 W/m2, 21.29 W/m2, and 36.91 W/m2; and seasonal bias of 15.08 W/m2, 21.21 W/m2, and 36.69 W/m2, respectively. In different Köppen climate zones, the annual solar radiation of ERA-Interim performed best in cold regions with a bias of 10.30 W/m2 and absolute relative error (ARE) of 8.98%. However, JRA-55 and NCEP-DOE showed the best performance in tropical regions with a bias of 20.08 W/m2 and −0.12 W/m2, and ARE of 11.00% and 9.68%, respectively. Overall, through the evaluations across different temporal and spatial scales, the rank of the three reanalysis products in order was the ERA-Interim, JRA-55, and NCEP-DOE. In addition, based on the evaluation, we analyzed the relationship between the error (ARE) of the reanalysis products and cloud cover, aerosol, and water vapor, which significantly influences solar radiation and we found that cloud was the main cause for errors in the three solar radiation reanalysis products. The above can provide a reference for the application and downscaling of the three solar radiation reanalysis products.
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Niu, Xiaolei, and Rachel T. Pinker. "Radiative Fluxes at Barrow, Alaska: A Satellite View." Journal of Climate 24, no. 21 (November 1, 2011): 5494–505. http://dx.doi.org/10.1175/jcli-d-11-00062.1.
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Abstract Satellite estimates of surface shortwave radiation (SWR) at high latitudes agree less with ground observations than at other locations; moreover, ground observations at such latitudes are scarce. The comprehensive observations of radiative fluxes made since 1977 by the Department of Energy Atmospheric Radiation Measurement (ARM) Program at the Barrow North Slope of Alaska (NSA) site are unique. They provide an opportunity to revisit accuracy estimates of remote sensing products at these latitudes, which are problematic because the melting of snow/ice and lower solar elevation make the satellite retrievals more difficult. A newly developed inference scheme for deriving SWR from the Moderate Resolution Imaging Spectroradiometer (MODIS; Terra and Aqua) that utilizes updated information on surface properties over snow and sea ice will be evaluated against these ground measurements and compared with other satellite and model products. Results show that the MODIS-based estimates are in good agreement with observations, with a bias of −5.3 W m−2 (−4% of mean observations) for the downward SWR, a bias of −5.3 W m−2 (−7%) for upward SWR, a bias of 1 (1%) for net SWR, and a bias of −0.001 (0%) for surface albedo. As such, the MODIS estimates of SWR can be useful for numerical model evaluations and for estimating the energy budgets at high latitudes.
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Wu, Rui Kun, and Guo Tai Chen. "Design of a Voltage-Controlled Beam Scanning Antenna Array Based on CRLH TL." Applied Mechanics and Materials 427-429 (September 2013): 628–31. http://dx.doi.org/10.4028/www.scientific.net/amm.427-429.628.
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The voltage-controlled beam scanning antenna array based on the CRLH transmission line is designed with series power divider and three small antenna. The resonant frequency of the open-termination power divider is 2.5GHz, and the varactor bias voltage of the small antenna is from 8V to 2V. At the operating frequency of 2.5GHz, the horizontally polarized pattern of the antenna array is measured. When the bias voltage of the varactor is changed, the antenna array radiation beam scanning range is up to 96 degrees, and its radiation from backward to forward can be achieved by controlling the varactor bias voltage.
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Александров, О. В., and С. А. Мокрушина. "Модель влияния смещения затвора при ионизирующем облучении МОП-структур." Физика и техника полупроводников 54, no. 2 (2020): 189. http://dx.doi.org/10.21883/ftp.2020.02.48902.9195.
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The new quantitative model of influence of gate bias on the threshold shift of MOS-structures at the ionizing radiation which is based on the accounting of holes trapping in a thin border layer of gate dielectric on interface with a silicon substrate is developed. The model allows to describe the smooth growth of threshold shift with gate bias – approximately linear from a dose for a surface component and nonlinear for a volume component. The threshold shift at a negative gate bias is modelled on the basis of the accounting of holes generation at ionizing radiation in the border layer.
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Suzuki, Kazumichi, Masaharu Sakagami, Eiichi Nishimura, and Kikuo Watanabe. "Bias Annealing of Radiation and Bias Induced Positive Charges in N- and P-Type MOS Capacitors." IEEE Transactions on Nuclear Science 32, no. 6 (1985): 3911–15. http://dx.doi.org/10.1109/tns.1985.4334042.
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Cronin, Timothy W. "On the Choice of Average Solar Zenith Angle." Journal of the Atmospheric Sciences 71, no. 8 (July 23, 2014): 2994–3003. http://dx.doi.org/10.1175/jas-d-13-0392.1.
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Abstract Idealized climate modeling studies often choose to neglect spatiotemporal variations in solar radiation, but doing so comes with an important decision about how to average solar radiation in space and time. Since both clear-sky and cloud albedo are increasing functions of the solar zenith angle, one can choose an absorption-weighted zenith angle that reproduces the spatial- or time-mean absorbed solar radiation. Calculations are performed for a pure scattering atmosphere and with a more detailed radiative transfer model and show that the absorption-weighted zenith angle is usually between the daytime-weighted and insolation-weighted zenith angles but much closer to the insolation-weighted zenith angle in most cases, especially if clouds are responsible for much of the shortwave reflection. Use of daytime-average zenith angle may lead to a high bias in planetary albedo of approximately 3%, equivalent to a deficit in shortwave absorption of approximately 10 W m−2 in the global energy budget (comparable to the radiative forcing of a roughly sixfold change in CO2 concentration). Other studies that have used general circulation models with spatially constant insolation have underestimated the global-mean zenith angle, with a consequent low bias in planetary albedo of approximately 2%–6% or a surplus in shortwave absorption of approximately 7–20 W m−2 in the global energy budget.
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Vergara-Temprado, Jesús, Annette K. Miltenberger, Kalli Furtado, Daniel P. Grosvenor, Ben J. Shipway, Adrian A. Hill, Jonathan M. Wilkinson, Paul R. Field, Benjamin J. Murray, and Ken S. Carslaw. "Strong control of Southern Ocean cloud reflectivity by ice-nucleating particles." Proceedings of the National Academy of Sciences 115, no. 11 (February 28, 2018): 2687–92. http://dx.doi.org/10.1073/pnas.1721627115.
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Large biases in climate model simulations of cloud radiative properties over the Southern Ocean cause large errors in modeled sea surface temperatures, atmospheric circulation, and climate sensitivity. Here, we combine cloud-resolving model simulations with estimates of the concentration of ice-nucleating particles in this region to show that our simulated Southern Ocean clouds reflect far more radiation than predicted by global models, in agreement with satellite observations. Specifically, we show that the clouds that are most sensitive to the concentration of ice-nucleating particles are low-level mixed-phase clouds in the cold sectors of extratropical cyclones, which have previously been identified as a main contributor to the Southern Ocean radiation bias. The very low ice-nucleating particle concentrations that prevail over the Southern Ocean strongly suppress cloud droplet freezing, reduce precipitation, and enhance cloud reflectivity. The results help explain why a strong radiation bias occurs mainly in this remote region away from major sources of ice-nucleating particles. The results present a substantial challenge to climate models to be able to simulate realistic ice-nucleating particle concentrations and their effects under specific meteorological conditions.
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Ogura, Tomoo, Hideo Shiogama, Masahiro Watanabe, Masakazu Yoshimori, Tokuta Yokohata, James D. Annan, Julia C. Hargreaves, et al. "Effectiveness and limitations of parameter tuning in reducing biases of top-of-atmosphere radiation and clouds in MIROC version 5." Geoscientific Model Development 10, no. 12 (December 21, 2017): 4647–64. http://dx.doi.org/10.5194/gmd-10-4647-2017.
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Abstract. This study discusses how much of the biases in top-of-atmosphere (TOA) radiation and clouds can be removed by parameter tuning in the present-day simulation of a climate model in the Coupled Model Inter-comparison Project phase 5 (CMIP5) generation. We used output of a perturbed parameter ensemble (PPE) experiment conducted with an atmosphere–ocean general circulation model (AOGCM) without flux adjustment. The Model for Interdisciplinary Research on Climate version 5 (MIROC5) was used for the PPE experiment. Output of the PPE was compared with satellite observation data to evaluate the model biases and the parametric uncertainty of the biases with respect to TOA radiation and clouds. The results indicate that removing or changing the sign of the biases by parameter tuning alone is difficult. In particular, the cooling bias of the shortwave cloud radiative effect at low latitudes could not be removed, neither in the zonal mean nor at each latitude–longitude grid point. The bias was related to the overestimation of both cloud amount and cloud optical thickness, which could not be removed by the parameter tuning either. However, they could be alleviated by tuning parameters such as the maximum cumulus updraft velocity at the cloud base. On the other hand, the bias of the shortwave cloud radiative effect in the Arctic was sensitive to parameter tuning. It could be removed by tuning such parameters as albedo of ice and snow both in the zonal mean and at each grid point. The obtained results illustrate the benefit of PPE experiments which provide useful information regarding effectiveness and limitations of parameter tuning. Implementing a shallow convection parameterization is suggested as a potential measure to alleviate the biases in radiation and clouds.
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Jeong, Areum, Tae-Eun Kwon, Wonho Lee, and Sunhoo Park. "Bias-corrected <i>H</i><sub>p</sub>(10)-to-Organ-Absorbed Dose Conversion Coefficients for the Epidemiological Study of Korean Radiation Workers." Journal of Radiation Protection and Research 47, no. 3 (September 30, 2022): 158–66. http://dx.doi.org/10.14407/jrpr.2022.00052.
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Background: The effects of radiation on the health of radiation workers who are constantly susceptible to occupational exposure must be assessed based on an accurate and reliable reconstruction of organ-absorbed doses that can be calculated using personal dosimeter readings measured as <i>H</i><sub>p</sub>(10) and dose conversion coefficients. However, the data used in the dose reconstruction contain significant biases arising from the lack of reality and could result in an inaccurate measure of organ-absorbed doses. Therefore, this study quantified the biases involved in organ dose reconstruction and calculated the bias-corrected <i>H</i><sub>p</sub>(10)-to-organ-absorbed dose coefficients for the use in epidemiological studies of Korean radiation workers.Materials and Methods: Two major biases were considered: (a) the bias in <i>H</i><sub>p</sub>(10) arising from the difference between the dosimeter calibration geometry and the actual exposure geometry, and (b) the bias in air kerma-to-<i>H</i><sub>p</sub>(10) conversion coefficients resulting from geometric differences between the human body and slab phantom. The biases were quantified by implementing personal dosimeters on the slab and human phantoms coupled with a Monte Carlo method and considered to calculate the bias-corrected <i>H</i><sub>p</sub>(10)-to-organ-absorbed dose conversion coefficients.Results and Discussion: The bias in <i>H</i><sub>p</sub>(10) was significant for large incident angles and low energies (e.g., 0.32 for right lateral at 218 keV), whereas the bias in dose coefficients was significant for the posteroanterior (PA) geometry only (e.g., 0.79 at 218 keV). The bias-corrected <i>H</i><sub>p</sub>(10)-to-organ-absorbed dose conversion coefficients derived in this study were up to 3.09-fold greater than those from the International Commission on Radiological Protection publications without considering the biases.Conclusion: The obtained results will aid future studies in assessing the health effects of occupational exposure of Korean radiation workers. The bias-corrected dose coefficients of this study can be used to calculate organ doses for Korean radiation workers based on personal dose records.
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Tian, Di, Ming Pan, and Eric F. Wood. "Assessment of a High-Resolution Climate Model for Surface Water and Energy Flux Simulations over Global Land: An Intercomparison with Reanalyses." Journal of Hydrometeorology 19, no. 7 (July 1, 2018): 1115–29. http://dx.doi.org/10.1175/jhm-d-17-0156.1.
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Abstract Land surface water and energy fluxes from the ensemble mean of the Atmospheric Model Intercomparison Project (AMIP) simulations of a Geophysical Fluid Dynamics Laboratory (GFDL) high-resolution climate model (AM2.5) were evaluated using offline simulations of a calibrated land surface model [Princeton Global Forcing (PGF)/VIC] and intercompared with three reanalysis datasets: MERRA-Land, ERA-Interim/Land, and CFSR. Using PGF/VIC as the reference, the AM2.5 precipitation, evapotranspiration, and runoff showed a global positive bias of ~0.44, ~0.27, and ~0.15 mm day−1, respectively. For the energy budget, while the AM2.5 net radiation agreed very well with the PGF/VIC, the AM2.5 improperly partitioned the net radiation, with the latent heat showing positive bias and sensible heat showing negative bias. The AM2.5 net radiation, latent heat, and sensible heat relative to the PGF/VIC had a global negative bias of ~1.42 W m−2, positive bias of ~7.8 W m−2, and negative bias of ~8.7 W m−2, respectively. The three reanalyses show greater biases in net radiation, likely due to the deficiencies in cloud parameterizations. At a regional scale, the biases of the AM2.5 water and energy budget components are mostly comparable to the three reanalyses and PGF/VIC. While the AM2.5 well simulated the actual values of water and energy fluxes, the temporal anomaly correlations of the three reanalyses with PGF/VIC were mostly greater than the AM2.5, partly due to the ensemble mean of the AM2.5 members averaging out the intrinsic variability of the land surface fluxes. The discrepancies among land surface model simulations, reanalyses, and high-resolution climate model simulations demonstrate the challenges in estimating and evaluating land surface hydrologic fluxes at regional-to-global scales.
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Badapanda, MK, and PR Hannurkar. "Klystron Bias Power Supplies for Indus-2 Synchrotron Radiation Source." IETE Journal of Research 54, no. 6 (2008): 403. http://dx.doi.org/10.4103/0377-2063.48630.
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Galletti, Michele, and Dusan S. Zrnic. "Bias in Copolar Correlation Coefficient Caused by Antenna Radiation Patterns." IEEE Transactions on Geoscience and Remote Sensing 49, no. 6 (June 2011): 2274–80. http://dx.doi.org/10.1109/tgrs.2010.2095019.
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Surh, Michael P., and Wilhelm G. Wolfer. "Accurate Mean Field Void Bias Factors for Radiation Swelling Calculations." Journal of Computer-Aided Materials Design 14, no. 3 (August 4, 2007): 419–24. http://dx.doi.org/10.1007/s10820-007-9052-2.
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