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 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.

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>

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.

Using deep learning to emulate and accelerate a radiative-transfer model

2021 ◽  
Author(s):  
Ryan Lagerquist ◽  
David Turner ◽  
Imme Ebert-Uphoff ◽  
Jebb Stewart ◽  
Venita Hagerty
Keyword(s):  
Deep Learning ◽  
Radiative Transfer ◽  
Heating Rate ◽  
Weather Prediction ◽  
Computing Time ◽  
Single Layer ◽  
Radiative Heating ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Heating Rates

AbstractThis paper describes the development of U-net++ models, a type of neural network that performs deep learning, to emulate the shortwave Rapid Radiative-transfer Model (RRTM). The goal is to emulate the RRTM accurately in a small fraction of the computing time, creating a U-net++ that could be used as a parameterization in numerical weather prediction (NWP). Target variables are surface downwelling flux, top-of-atmosphere upwelling flux (), net flux, and a profile of radiative-heating rates. We have devised several ways to make the U-net++ models knowledge-guided, recently identified as a key priority in machine learning (ML) applications to the geosciences. We conduct two experiments to find the best U-net++ configurations. In Experiment 1, we train on non-tropical sites and test on tropical sites, to assess extreme spatial generalization. In Experiment 2, we train on sites from all regions and test on different sites from all regions, with the goal of creating the best possible model for use in NWP. The selected model from Experiment 1 shows impressive skill on the tropical testing sites, except four notable deficiencies: large bias and error for heating rate in the upper stratosphere, unreliable for profiles with single-layer liquid cloud, large heating-rate bias in the mid-troposphere for profiles with multi-layer liquid cloud, and negative bias at lowzenith angles for all flux components and tropospheric heating rates. The selected model from Experiment 2 corrects all but the first deficiency, and both models run ~104 times faster than the RRTM. Our code is available publicly.

scholarly journals Using the Himawari-8 AHI Multi-Channel to Improve the Calculation Accuracy of Outgoing Longwave Radiation at the Top of the Atmosphere

2019 ◽  
Vol 11 (5) ◽  
pp. 589 ◽  
Author(s):  
Bu-Yo Kim ◽  
Kyu-Tae Lee
Keyword(s):  
Water Vapor ◽  
Optical Thickness ◽  
Outgoing Longwave Radiation ◽  
Radiant Energy ◽  
Longwave Radiation ◽  
Energy System ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Atmospheric Conditions ◽  
Calculation Algorithm

In this study, Himawari-8 Advanced Himawari Imager (AHI) longwave channel data that is sensitive to clouds and absorption gas were used to improve the accuracy of the algorithm used to calculate outgoing longwave radiation (OLR) at the top of the atmosphere. A radiative transfer model with a variety of atmospheric conditions was run using Garand vertical profile data as input data. The results of the simulation showed that changes in AHI channels 8, 12, 15, and 16, which were used to calculate OLR, were sensitive to changes in cloud characteristics (cloud optical thickness and cloud height) and absorption gases (water vapor, O3, CO2, aerosol optical thickness) in the atmosphere. When compared to long-term analysis OLR data from 2017, as recorded by the Cloud and Earth’s Radiant Energy System (CERES), the OLR calculated in this study had an annual mean bias of 2.28 Wm−2 and a root mean square error (RMSE) of 11.03 Wm−2. The new calculation method mitigated the problem of overestimations in OLR in mostly cloudy and overcast regions and underestimated OLR in cloud-free desert regions. It is also an improvement over the result from the existing OLR calculation algorithm, which uses window and water vapor channels.

scholarly journals Characteristic Atmospheric Radiative Heating Rate Profiles in Arctic Clouds as Observed at Barrow, Alaska

2018 ◽  
Vol 57 (4) ◽  
pp. 953-968 ◽  
Author(s):  
D. D. Turner ◽  
M. D. Shupe ◽  
A. B. Zwink
Keyword(s):  
Heating Rate ◽  
Liquid Water ◽  
Single Layer ◽  
Radiative Heating ◽  
Radiative Transfer Model ◽  
Radiative Cooling ◽  
Transfer Model ◽  
Liquid Water Path ◽  
Water Path ◽  
Order Of Magnitude

AbstractA 2-yr cloud microphysical property dataset derived from ground-based remote sensors at the Atmospheric Radiation Measurement site near Barrow, Alaska, was used as input into a radiative transfer model to compute radiative heating rate (RHR) profiles in the atmosphere. Both the longwave (LW; 5–100 μm) and shortwave (SW; 0.2–5 μm) RHR profiles show significant month-to-month variability because of seasonal dependence in the vertical profiles of cloud liquid and ice water contents, with additional contributions from the seasonal dependencies of solar zenith angle, water vapor amount, and temperature. The LW and SW RHR profiles were binned to provide characteristic profiles as a function of cloud type and liquid water path (LWP). Single-layer liquid-only clouds are shown to have larger (10–30 K day−1) LW radiative cooling rates at the top of the cloud layer than single-layer mixed-phase clouds; this is due primarily to differences in the vertical distribution of liquid water between the two classes. However, differences in SW RHR profiles at the top of these two classes of clouds are less than 3 K day−1. The absolute value of the RHR in single-layer ice-only clouds is an order of magnitude smaller than in liquid-bearing clouds. Furthermore, for double-layer cloud systems, the phase and condensed water path of the upper cloud strongly modulate the radiative cooling both at the top and within the lower-level cloud. While sensitivity to cloud overlap and phase has been shown previously, the characteristic RHR profiles are markedly different between the different cloud classifications.

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.

Sign in / Sign up

Export Citation Format

Share Document