scholarly journals An Algorithm for the Constraining of Radiative Transfer Calculations to CERES-Observed Broadband Top-of-Atmosphere Irradiance

2013 ◽  
Vol 30 (6) ◽  
pp. 1091-1106 ◽  
Author(s):  
Fred G. Rose ◽  
David A. Rutan ◽  
Thomas Charlock ◽  
G. Louis Smith ◽  
Seiji Kato
Keyword(s):  
Radiative Transfer ◽  
Radiant Energy ◽  
Tropical Rainfall Measuring Mission ◽  
Energy System ◽  
Atmospheric Temperature ◽  
Radiative Transfer Model ◽  
Bias Error ◽  
Transfer Model ◽  
Lagrangian Multipliers ◽  
Cloud Properties

Abstract NASA’s Clouds and the Earth’s Radiant Energy System (CERES) project is responsible for operation and data processing of observations from scanning radiometers on board the Tropical Rainfall Measuring Mission (TRMM), Terra, Aqua, and Suomi National Polar-Orbiting Partnership (NPP) satellites. The clouds and radiative swath (CRS) CERES data product contains irradiances computed using a radiative transfer model for nearly all CERES footprints in addition to top-of-atmosphere (TOA) irradiances derived from observed radiances by CERES instruments. This paper describes a method to constrain computed irradiances by CERES-derived TOA irradiances using Lagrangian multipliers. Radiative transfer model inputs include profiles of atmospheric temperature, humidity, aerosols and ozone, surface temperature and albedo, and up to two sets of cloud properties for a CERES footprint. Those inputs are adjusted depending on predefined uncertainties to match computed TOA and CERES-derived TOA irradiance. Because CERES instantaneous irradiances for an individual footprint also include uncertainties, primarily due to the conversion of radiance to irradiance using anisotropic directional models, the degree of the constraint depends on CERES-derived TOA irradiance as well. As a result of adjustment, TOA computed-minus-observed standard deviations are reduced from 8 to 4 W m−2 for longwave irradiance and from 15 to 6 W m−2 for shortwave irradiance. While agreement of computed TOA with CERES-derived irradiances improves, comparisons with surface observations show that model constrainment to the TOA does not reduce computation bias error at the surface. After constrainment, shortwave down at the surface has an increased bias (standard deviation) of 1% (0.5%) and longwave increases by 0.2% (0.1%). Clear-sky changes are negligible.

scholarly journals Longwave Radiative Effect of the Cloud-Aerosol Transition Zone Based on CERES Observations

2021 ◽  
Author(s):  
Babak Jahani ◽  
Hendrik Andersen ◽  
Josep Calbó ◽  
Josep-Abel González ◽  
Jan Cermak
Keyword(s):  
Radiative Transfer ◽  
Transition Zone ◽  
Radiant Energy ◽  
Energy System ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Radiative Effect ◽  
Radiative Effects ◽  
Clear Sky ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. This study presents an approach for quantification of cloud-aerosol transition zone broadband longwave radiative effects at the top of the atmosphere (TOA) during daytime over the ocean, based on satellite observations and radiative transfer simulation. Specifically, we used several products from MODIS (Moderate Resolution Imaging Spectroradiometer) and CERES (Clouds and the Earth’s Radiant Energy System) sensors for identification and selection of CERES footprints with horizontally homogeneous transition zone and clear-sky conditions. For the selected transition zone footprints, radiative effect was calculated as the difference between the instantaneous CERES TOA upwelling broadband longwave radiance observations and corresponding clear-sky radiance simulations. The clear-sky radiances were simulated using the Santa Barbara DISORT Atmospheric Radiative Transfer model fed by the hourly ERA5 reanalysis (fifth generation ECMWF reanalysis) atmospheric and surface data. The CERES radiance observations corresponding to the clear-sky footprints detected were also used for validating the simulated clear-sky radiances. We tested this approach using the radiative measurements made by the MODIS and CERES instruments onboard Aqua platform over the south-eastern Atlantic Ocean during August 2010. For the studied period and domain, transition zone radiative effect (given in flux units) is on average equal to 8.0 ± 3.7 W m−2 (heating effect; median: 5.4 W m−2), although cases with radiative effects as large as 50 W m−2 were found.

Radiative Transfer Modeling for the CLAMS Experiment

2005 ◽  
Vol 62 (4) ◽  
pp. 1053-1071 ◽  
Author(s):  
Zhonghai Jin ◽  
Thomas P. Charlock ◽  
Ken Rutledge ◽  
Glenn Cota ◽  
Ralph Kahn ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Near Infrared ◽  
Radiant Energy ◽  
Energy System ◽  
Temporal Variations ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Near Surface ◽  
Validation Experiment ◽  
Surface Measurements

Abstract Spectral and broadband radiances and irradiances (fluxes) were measured from surface, airborne, and spaceborne platforms in the Chesapeake Lighthouse and Aircraft Measurements for Satellites (CLAMS) campaign. The radiation data obtained on the 4 clear days over ocean during CLAMS are analyzed here with the Coupled Ocean–Atmosphere Radiative Transfer (COART) model. The model is successively compared with observations of broadband fluxes and albedos near the ocean surface from the Clouds and the Earth's Radiant Energy System (CERES) Ocean Validation Experiment (COVE) sea platform and a low-level OV-10 aircraft, of near-surface spectral albedos from COVE and OV-10, of broadband radiances at multiple angles and inferred top-of-atmosphere (TOA) fluxes from CERES, and of spectral radiances at multiple angles from Airborne Multiangle Imaging Spectroradiometer (MISR), or “AirMISR,” at 20-km altidude. The radiation measurements from different platforms are shown to be consistent with each other and with model results. The discrepancies between the model and observations at the surface are less than 10 W m−2 for downwelling and 2 W m−2 for upwelling fluxes. The model–observation discrepancies for shortwave ocean albedo are less than 8%; some discrepancies in spectral albedo are larger but less than 20%. The discrepancies between low-altitude aircraft and surface measurements are somewhat larger than those between the model and the surface measurements; the former are due to the effects of differences in height, aircraft pitch and roll, and the noise of spatial and temporal variations of atmospheric and oceanic properties. The discrepancy between the model and the CERES observations for the upwelling radiance is 5.9% for all angles; this is reduced to 4.9% if observations within 15° of the sun-glint angle are excluded. The measurements and model agree on the principal impacts that ocean optical properties have on upwelling radiation at low levels in the atmosphere. Wind-driven surface roughness significantly affects the upwelling radiances measured by aircraft and satellites at small sun-glint angles, especially in the near-infrared channel of MISR. Intercomparisons of various measurements and the model show that most of the radiation observations in CLAMS are robust, and that the coupled radiative transfer model used here accurately treats scattering and absorption processes in both the air and the water.

Examining Biases in Diurnally Integrated Shortwave Irradiances due to Two- and Four-Stream Approximations in a Cloudy Atmosphere

2020 ◽  
Vol 77 (2) ◽  
pp. 551-581
Author(s):  
Seung-Hee Ham ◽  
Seiji Kato ◽  
Fred G. Rose
Keyword(s):  
Radiant Energy ◽  
Energy System ◽  
Radiation Budget ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Polar Regions ◽  
Angle Variation ◽  
Cloud Properties ◽  
Cloudy Atmosphere ◽  
Earth’S Radiation Budget

Abstract Shortwave irradiance biases due to two- and four-stream approximations have been studied for the last couple of decades, but biases in estimating Earth’s radiation budget have not been examined in earlier studies. To quantify biases in diurnally averaged irradiances, we integrate the two- and four-stream biases using realistic diurnal variations of cloud properties from Clouds and the Earth’s Radiant Energy System (CERES) synoptic (SYN) hourly product. Three approximations are examined in this study: delta-two-stream-Eddington (D2strEdd), delta-two-stream-quadrature (D2strQuad), and delta-four-stream-quadrature (D4strQuad). Irradiances computed by the Discrete Ordinate Radiative Transfer model (DISORT) and Monte Carlo (MC) methods are used as references. The MC noises are further examined by comparing with DISORT results. When the biases are integrated with one day of solar zenith angle variation, regional biases of D2strEdd and D2strQuad reach up to 8 W m−2, while biases of D4strQuad reach up to 2 W m−2. When the biases are further averaged monthly or annually, regional biases of D2strEdd and D2strQuad can reach −1.5 W m−2 in SW top-of-atmosphere (TOA) upward irradiances and +3 W m−2 in surface downward irradiances. In contrast, regional biases of D4strQuad are within +0.9 for TOA irradiances and −1.2 W m−2 for surface irradiances. Except for polar regions, monthly and annual global mean biases are similar, suggesting that the biases are nearly independent to season. Biases in SW heating rate profiles are up to −0.008 K day−1 for D2strEdd and −0.016 K day−1 for D2strQuad, while the biases of the D4strQuad method are negligible.

scholarly journals Retrieval of Gridded Aerosol Direct Radiative Forcing Based on Multiplatform Datasets

2019 ◽  
Author(s):  
Yanyu Wang ◽  
Rui Lyu ◽  
Xin Xie ◽  
Meijin Huang ◽  
Junshi Wu ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Radiative Forcing ◽  
Radiant Energy ◽  
Energy System ◽  
East China ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Radiative Fluxes ◽  
Direct Radiative Forcing

Abstract. Atmospheric aerosols play a crucial role in regional radiative budgets. Previous studies on clear-sky aerosol direct radiative forcing (ADRF) have mainly been limited to site-scale observations or model simulations for short-term cases, and long-term distributions of ADRF in China has not been portrayed yet. In this study, an accurate fine-resolution ADRF estimate at the surface was proposed. Multiplatform datasets, including satellite (Terra and Aqua) and reanalysis datasets, served as inputs to the Santa Barbara Discrete Atmospheric Radiative Transfer (SBDART) model for ADRF simulation with consideration of the aerosol vertical profile over East China during 2000–2016. Specifically, single scattering albedo (SSA) from the Modern-Era Retrospective Analysis for Research and Application, version 2 (MERRA-2) was validated with sunphotometers over East China. The gridded asymmetry parameter (ASY) was then simulated by matching the calculated top-of-atmosphere (TOA) radiative fluxes from the radiative transfer model with satellite observations (Clouds and the Earth's Radiant Energy System (CERES)). The high correlation and small discrepancy (6–8 W m-2) between simulated and observed radiative fluxes at three sites (Baoshan, Fuzhou, and Yong'an) indicated that ADRF retrieval is feasible and has high accuracy over East China. Then this method was applied in each grid of East China and the overall picture of ADRF distributions over East China during 2000–2016 was displayed. ADRF ranges from −220 to −20 W m-2, and annual mean ADRF is −100.21 W m-2, implying that aerosols have strong cooling effect at the surface during past 16 years. Finally, uncertainty analysis was also evaluated. Our method provides the long-term ADRF distribution over East China for the first time, with highlighting the importance of aerosol radiative impact under the climate change.

A 10-Year Climatology of Tropical Radiative Heating and Its Vertical Structure from TRMM Observations

2010 ◽  
Vol 23 (3) ◽  
pp. 519-541 ◽  
Author(s):  
Tristan S. L’Ecuyer ◽  
Greg McGarragh
Keyword(s):  
Heating Rate ◽  
Large Scale ◽  
Vertical Structure ◽  
Radiant Energy ◽  
Tropical Rainfall Measuring Mission ◽  
Energy System ◽  
Radiative Heating ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Deterministic Framework

Abstract This paper outlines recent advances in estimating atmospheric radiative heating rate profiles from the sensors aboard the Tropical Rainfall Measuring Mission (TRMM). The approach employs a deterministic framework in which four distinct retrievals of clouds, precipitation, and other atmospheric and surface properties are combined to form input to a broadband radiative transfer model that simulates profiles of upwelling and downwelling longwave and shortwave radiative fluxes in the atmosphere. Monthly, 5° top of the atmosphere outgoing longwave and shortwave flux estimates agree with corresponding observations from the Clouds and the Earth’s Radiant Energy System (CERES) to within 7 W m−2 and 3%, respectively, suggesting that the resulting products can be thought of as extending the eight-month CERES dataset to cover the full lifetime of TRMM. The analysis of a decade of TRMM data provides a baseline climatology of the vertical structure of atmospheric radiative heating in today’s climate and an estimate of the magnitude of its response to environmental forcings on weekly to interannual time scales. In addition to illustrating the scope and properties of the dataset, the results highlight the strong influence of clouds, water vapor, and large-scale dynamics on regional radiation budgets and the vertical structure of radiative heating in the tropical and subtropical atmospheres. The combination of the radiative heating rate product described here, with profiles of latent heating that are now also being generated from TRMM sensors, provides a unique opportunity to develop large-scale estimates of vertically resolved atmospheric diabatic heating using satellite observations.

scholarly journals Feasibility study of multi-pixel retrieval of optical thickness and droplet effective radius of inhomogeneous clouds using deep learning

2017 ◽  
Vol 10 (12) ◽  
pp. 4747-4759 ◽  
Author(s):  
Rintaro Okamura ◽  
Hironobu Iwabuchi ◽  
K. Sebastian Schmidt
Keyword(s):  
Deep Learning ◽  
Radiative Transfer ◽  
Optical Thickness ◽  
Cloud Droplet ◽  
Effective Radius ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Optical Remote Sensing ◽  
Transfer Effects ◽  
Cloud Properties

Abstract. Three-dimensional (3-D) radiative-transfer effects are a major source of retrieval errors in satellite-based optical remote sensing of clouds. The challenge is that 3-D effects manifest themselves across multiple satellite pixels, which traditional single-pixel approaches cannot capture. In this study, we present two multi-pixel retrieval approaches based on deep learning, a technique that is becoming increasingly successful for complex problems in engineering and other areas. Specifically, we use deep neural networks (DNNs) to obtain multi-pixel estimates of cloud optical thickness and column-mean cloud droplet effective radius from multispectral, multi-pixel radiances. The first DNN method corrects traditional bispectral retrievals based on the plane-parallel homogeneous cloud assumption using the reflectances at the same two wavelengths. The other DNN method uses so-called convolutional layers and retrieves cloud properties directly from the reflectances at four wavelengths. The DNN methods are trained and tested on cloud fields from large-eddy simulations used as input to a 3-D radiative-transfer model to simulate upward radiances. The second DNN-based retrieval, sidestepping the bispectral retrieval step through convolutional layers, is shown to be more accurate. It reduces 3-D radiative-transfer effects that would otherwise affect the radiance values and estimates cloud properties robustly even for optically thick clouds.

scholarly journals Retrieval of Ice Cloud Properties from AIRS and MODIS Observations Based on a Fast High-Spectral-Resolution Radiative Transfer Model

2013 ◽  
Vol 52 (3) ◽  
pp. 710-726 ◽  
Author(s):  
Chenxi Wang ◽  
Ping Yang ◽  
Steven Platnick ◽  
Andrew K. Heidinger ◽  
Bryan A. Baum ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Spectral Resolution ◽  
Spectral Response ◽  
Thermal Infrared ◽  
High Spectral Resolution ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Retrieval Method ◽  
Ice Cloud ◽  
Cloud Properties

AbstractA computationally efficient high-spectral-resolution cloudy-sky radiative transfer model (HRTM) in the thermal infrared region (700–1300 cm−1, 0.1 cm−1 spectral resolution) is advanced for simulating the upwelling radiance at the top of atmosphere and for retrieving cloud properties. A precomputed transmittance database is generated for simulating the absorption contributed by up to seven major atmospheric absorptive gases (H2O, CO2, O3, O2, CH4, CO, and N2O) by using a rigorous line-by-line radiative transfer model (LBLRTM). Both the line absorption of individual gases and continuum absorption are included in the database. A high-spectral-resolution ice particle bulk scattering properties database is employed to simulate the radiation transfer within a vertically nonisothermal ice cloud layer. Inherent to HRTM are sensor spectral response functions that couple with high-spectral-resolution measurements in the thermal infrared regions from instruments such as the Atmospheric Infrared Sounder (AIRS) and Infrared Atmospheric Sounding Interferometer. When compared with the LBLRTM and the discrete ordinates radiative transfer model (DISORT), the root-mean-square error of HRTM-simulated single-layer cloud brightness temperatures in the thermal infrared window region is generally smaller than 0.2 K. An ice cloud optical property retrieval scheme is developed using collocated AIRS and Moderate Resolution Imaging Spectroradiometer (MODIS) data. A retrieval method is proposed to take advantage of the high-spectral-resolution instrument. On the basis of the forward model and retrieval method, a case study is presented for the simultaneous retrieval of ice cloud optical thickness τ and effective particle size Deff that includes a cloud-top-altitude self-adjustment approach to improve consistency with simulations.

scholarly journals Aerosol trends as a potential driver of regional climate in the central United States: evidence from observations

2017 ◽  
Vol 17 (22) ◽  
pp. 13559-13572 ◽  
Author(s):  
Daniel H. Cusworth ◽  
Loretta J. Mickley ◽  
Eric M. Leibensperger ◽  
Michael J. Iacono
Keyword(s):  
United States ◽  
Radiative Transfer ◽  
Southeastern United States ◽  
Radiant Energy ◽  
Surface Radiation ◽  
Radiation Budget ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Clear Sky

Abstract. In situ surface observations show that downward surface solar radiation (SWdn) over the central and southeastern United States (US) has increased by 0.58–1.0 Wm−2 a−1 over the 2000–2014 time frame, simultaneously with reductions in US aerosol optical depth (AOD) of 3.3–5.0  ×  10−3 a−1. Establishing a link between these two trends, however, is challenging due to complex interactions between aerosols, clouds, and radiation. Here we investigate the clear-sky aerosol–radiation effects of decreasing US aerosols on SWdn and other surface variables by applying a one-dimensional radiative transfer to 2000–2014 measurements of AOD at two Surface Radiation Budget Network (SURFRAD) sites in the central and southeastern United States. Observations characterized as clear-sky may in fact include the effects of thin cirrus clouds, and we consider these effects by imposing satellite data from the Clouds and Earth's Radiant Energy System (CERES) into the radiative transfer model. The model predicts that 2000–2014 trends in aerosols may have driven clear-sky SWdn trends of +1.35 Wm−2 a−1 at Goodwin Creek, MS, and +0.93 Wm−2 a−1 at Bondville, IL. While these results are consistent in sign with observed trends, a cross-validated multivariate regression analysis shows that AOD reproduces 20–26 % of the seasonal (June–September, JJAS) variability in clear-sky direct and diffuse SWdn at Bondville, IL, but none of the JJAS variability at Goodwin Creek, MS. Using in situ soil and surface flux measurements from the Ameriflux network and Illinois Climate Network (ICN) together with assimilated meteorology from the North American Land Data Assimilation System (NLDAS), we find that sunnier summers tend to coincide with increased surface air temperature and soil moisture deficits in the central US. The 1990–2015 trends in the NLDAS SWdn over the central US are also of a similar magnitude to our modeled 2000–2014 clear-sky trends. Taken together, these results suggest that climate and regional hydrology in the central US are sensitive to the recent reductions in aerosol concentrations. Our work has implications for severely polluted regions outside the US, where improvements in air quality due to reductions in the aerosol burden could inadvertently pose an enhanced climate risk.

scholarly journals Assessment of cloud properties from the reanalysis with satellite observations over East Asia

2019 ◽  
Author(s):  
Bin Yao ◽  
Chao Liu ◽  
Yan Yin ◽  
Zhiquan Liu ◽  
Chunxiang Shi ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
East Asia ◽  
Deep Convection ◽  
Satellite Observation ◽  
Reanalysis Data ◽  
Satellite Observations ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
China Meteorological Administration ◽  
Cloud Properties

Abstract. Extensive observational and numerical investigations have been performed to better characterize cloud properties. However, due to the large variations of cloud spatiotemporal distributions and physical properties, quantitative depictions of clouds in different atmospheric reanalysis datasets are still highly uncertain, and cloud parameters in the models to produce those datasets remain largely unconstrained. A radiance-based evaluation approach is introduced and performed to assess the quality of cloud properties by directly comparing reanalysis-driven forward radiative transfer results with radiances from satellite observation. The newly developed China Meteorological Administration Reanalysis data (CRA), the ECMWF’s Fifth-generation Reanalysis (ERA5), and the Modern-Era Retrospective Analysis for Applications, Version 2 (MERRA-2) are considered in the present study. To avoid the unrealistic assumptions and uncertainties on satellite retrieval algorithms and products, the radiative transfer model (RTM) is used as a bridge to “translate” the reanalysis to corresponding satellite observations. The simulated reflectance and brightness temperatures (BTs) are directly compared with observations from the Advanced Himawari Imager (AHI) onboard the Himawari-8 satellite in the region from 80° E to 160° W between 60° N and 60° S, especially for results over East Asia. Comparisons of the reflectance in the solar and BTs in the infrared (IR) window channels reveal that CRA reanalysis better represents the total cloud cover than the other two reanalysis datasets. The simulated BTs for CRA and ERA5 are close to each other in many pixels, whereas the vertical distributions of cloud properties are significantly different, and ERA5 depicts a better deep convection structure than CRA reanalysis. Comparisons of the BT differences (BTDs) between the simulations and observations suggest that the water clouds are generally overestimated in ERA5 and MERRA-2, whereas the ice cloud is responsible for the overestimation over the center of cyclones in ERA5. Overall, the cloud from CRA, ERA5, and MERRA-2 show their own advantages in different aspects. The ERA5 reanalysis is found the most capability in representing the cloudy atmosphere over East Asia, and the results in CRA are close to those in ERA5.

Inter-Calibrating Satellite Remote Sensors Using High Accuracy NASA CLARREO Pathfinder Instrument

2020 ◽  
Author(s):  
Xu Liu ◽  
Wan Wu ◽  
Qiguang Yang ◽  
Yolanda Shea ◽  
Costy Lukashin ◽  
...  
Keyword(s):  
Infrared Imaging ◽  
Space Station ◽  
Radiant Energy ◽  
Principal Component ◽  
Energy System ◽  
Radiative Transfer Model ◽  
Absolute Calibration ◽  
Transfer Model ◽  
Calibration Uncertainty ◽  
Solar Instruments

<p>NASA is planning to launch a highly accurate hyperspectral sensor to measure Earth-reflected solar radiances from the International Space Station in 2023.  The Climate Absolute Radiance and Refractivity Observatory (CLARREO) Pathfinder (CPF) instrument will have an absolute calibration accuracy of 0.3% (1-sigma), which is about a factor of 5 to 10 more accurate than current satellite reflected solar instruments.  We will describe the CPF approach developed to inter-calibrate the Clouds and Earth’s Radiant Energy System (CERES) and Visible Infrared Imaging Radiometer Suite (VIIRS) instruments.  A Principal Component-based Radiative Transfer Model (PCRTM) is used to perform high fidelity CPF radiance spectra simulation and to extend the spectral range of the CPF to match that of the shortwave CERES reflected solar radiation.  The PCRTM model can also be used to correct small errors due to imperfect angular matching between the CPF/CERES and CPF/VIIRS observation angles.  Examples of inter-calibration uncertainty that is anticipated will be demonstrated using simulated CPF data.</p>

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