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Taiping Zhang

Publications and source records attributed to Taiping Zhang.

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
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An Assessment of and Access to NASA CERES Hourly Solar Irradiance Data Products Using POWER Web Services

The National Aeronautics and Space Administration’s (NASA) Clouds and Earth’s Radiant Energy System (CERES) Mission has been providing surface solar irradiance data products since March 2000. With an emphasis on global climate quality data products, CERES produces a suite of data parameters related to both the inputs and the observed and measured solar irradiance components at the top-of-atmosphere and at the surface. This paper discusses the global CERES SYN1Deg (Synoptic 1x1 degree resolution) solar irradiance data products, shows that the accuracy of the global horizontal irradiance (GHI) at the hourly time scale is <1% for bias and 24% RMS compared to the Baseline Surface Radiation Network (BSRN) measurements. This paper then shows the accuracy of the direct and diffuse components and a proposed “bias” correction based upon the solar zenith angle dependence that provides accuracy useful for solar applications on a global basis for all sunlit conditions. Lastly, a brief description of how to obtain these hourly solar irradiance products based upon SYN1Deg using the NASA’s Prediction of Worldwide Energy Resource (POWER) web services portal is given so users can utilize these estimates for testing and evaluation.

Surface solar irradiance↗
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Advances to a Global Agroclimatology Solar Insolation and Meteorological Parameter Data Base: Improved Solar Irradiance up to Hourly Temporal Resolution

A primary objective of NASA’s Prediction of Worldwide Energy Resource (POWER) project is to facilitate the use of NASA Earth Science data holdings within the energy, agricultural, and architectural industries. To this end daily averaged solar data from several NASA projects and metrological data from a NASA assimilation model have long been reformatted and via a user friendly web based data portal (https://power.larc.nasa.gov) at the native resolution of each data products. Potential users can access solar and metrological data in a column formatted DSSAT ASCII format by entering single site specific coordinates or from an area by entering the appropriate area coordinates. Upgrades to the POWER data portal have been implemented that result in a complete upgrade of the base solar insolation data products. From the years 1984 through 2000, a new version of the NASA/GEWEX Surface Radiation Budget (SRB) and Clouds is utilized that reduces the RMS relative to surface measurements. Additionally, Clouds and the Earth’s Radiant Energy System (CERES) SYNoptic 1x1 Degree (SYN1Deg) data products are utilized starting from January 1, 2001 through 3 months of real-time. The CERES Fast Longwave and SHortwave radiative Fluxes (FLASHFlux) is still used to provided daily data spanning from the end of SYN1Deg to within 7 days of real-time. Meteorological parameters now are taken from the NASA Modern Era Retrospective-analysis for Research and Applications (MERRA-2) data set which provides higher resolution data products (hourly and 0.5 x 625 degree) covering the entire globe. Besides updating the solar and meteorological data products, this new version features new data products such as photosynthetically active radiation (PAR), more cloud information, estimates of soil temperatures and improved options for long-term climatological data requests. More than 36+ years daily time slices are included in the combined solar and meteorological data sets. However, perhaps the most important innovation of the POWER GIS-enabled Web Services is the provision of hourly solar and meteorological data products beginning in Jan 1, 2001. The hourly values will enable more detailed modeling and crop analysis that incorporates the diurnal variability of these parameters. The new capability is made possible by utilizing both the CERES SYN1Deg and MERRA-2 data products that include parameters at these resolutions. An assessment of both the meteorological and the solar irradiance data are based upon comparisons with globally distributed surface observations. The meteorological observations from the National Center for Environmental Information’s “Integrated Surface Database” as well as the “Global Summary of the Day” (GSOD) data files. The estimates of solar insolation are compared to the Baseline Solar Radiation Network (BSRN) and other high quality surface measurement networks. Results from the uncertainty assessments demonstrates that the NASA’s meteorological and solar irradiance data can represent a viable alternative to surface observations, particularly in data sparse regions of the world.

solar irradiance↗
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NASA/GEWEX SRB Surface Radiation Budget Fluxes Through the Prism of Weather States

The NASA/GEWEX Surface Radiation Budget Version 4 (SRB Rel4) product is now publicly available, covering the period from July 1983 through June 2017. This supersedes the SRB Rel3 (Stackhouse et al., 2011) product which has been used in the community for a wide variety of applications, including climate model validation, agriculture, solar energy, and architecture. SRB Rel4 uses the newly recalibrated and processed ISCCP HXS product as its primary input for cloud and radiance data, replacing ISCCP DX with a ninefold increase in pixel count (10km instead of 30km). This version retains a 1°x1° resolution but benefits from a much larger number of samples per grid box than the SRB Rel3. ISCCP also provides an atmospheric temperature and moisture dataset known as nnHIRS which we use here, along with Seaflux and Landflux surface and near-surface meteorological parameters. Rel4 incorporates several important algorithm improvements. These include recalculated shortwave (SW) atmospheric transmissivities and reflectivities yielding a somewhat less transmissive atmosphere. Both shortwave and longwave (LW) now also include variable aerosol composition and radiative properties, allowing for the use of a detailed aerosol history from the Max Planck Institute Aerosol Climatology (MACv1). LW and SW algorithms now produce pristine sky fluxes, allowing the aerosol flux effects to be quantified. For SW, ocean albedo and snow/ice albedo are improved from Release 3. Total solar irradiance is now variable, and reduced to an average of 1361 Wm-2. The radiative treatment of ice cloud is improved. For the LW, a climatological monthly varying spectral surface emissivity is added. Here we evaluate the SRB Rel4 top of atmosphere (TOA) and surface fluxes in the context of weather states and oceanic regions. Weather states (Tselioudis et al., 2013, Tselioudis et al., 2021) are defined by K-means clustering 2-D histograms of satellite-retrieved cloud optical depths and cloud top pressures. The most recent (Tselioudis et al., 2021) weather states derived from the International Satellite Cloud Climatology Project (ISCCP) H-series data results in eight cloud weather states and one clear sky weather state, for a total of nine weather states. We examine the statistics of SRB Rel4 fluxes for each weather state and a variety of relevant land and ocean regions. We compare to similar analyses performed on CERES EBAF and SYN1Deg flux products, and validate against Baseline Surface Radiometer Network (BSRN) land stations and Pacific Marine Environmental Laboratory (PMEL) ocean buoy data. It is demonstrated that the weather state concept is valuable when examining the comparative strengths and weaknesses of satellite radiative flux algorithms.

Atmospheric Radiation↗
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Assessing Uncertainties and Variability 34 Years of Surface Radiative Fluxes Using GEWEX SRB Release4-IP

The NASA/GEWEX Surface Radiation Budget (SRB) project produces 3-hrly shortwave and longwave surface and top of atmosphere radiative fluxes for the 1983-near present time period. The new Release 4 Integrated Product (IP) uses the newly recalibrated and processed ISCCP HXS product as its primary input for cloud and radiance data, replacing ISCCP DX with a ninefold increase in pixel count (10 km instead of 30 km). This first version retains a 1°x1° resolution enabling intercomparison against previous versions and other data sets such as CERES, but spans 34 years from July 1983 through June 2017 and was announced by Kummerow et al. 2019 (GEWEX News). This new IP product also uses an atmospheric temperature and moisture dataset known as nnHIRS and other parameters such as near surface and skin temperatures from SeaFlux and LandFlux data sets. In addition to the input data improvements, several important algorithm improvements have been made since Release 3. These include recalculated SW atmospheric transmissivities and reflectivities, updated ocean and snow/ice albedos, and variable total solar irradiance consistent with SORCE measurements. The LW code has been updated to improve the optical property treatment for clouds and aerosols are included in this version. Radiative treatment of ice clouds is also improved in the LW. The variable aerosol optical properties for the SW and LW are specified using a detailed aerosol history from the Max Planck Institute Aerosol Climatology (MAC). Here we present an assessment of the LW radiative fluxes and the uncertainty of those fluxes relative to the various inputs to surface SW/LW flux measurements from BSRN and PMEL buoys measurements. We review the validation of the SW and LW fluxes and then in terms of time series and then assess the products in terms of their long-term variability of the surface SW and LW net fluxes compared to multiple other data products including atmospheric reanalysis products. The comparisons of radiative estimates to observations are performed at various temporal scales and aimed at investigation of agreement at longer time averages but accessing potential change in diurnal magnitude and daily variability. Utilizing this uncertainty information, to access long-term variability of surface radiation components at selected region and global scales, considering satellite sampling/calibration “artifacts” as necessary. At the longer time scales, the net SW and net LW the TOA and surface have implications toward closure of the energy budgets at the surface, we assess these compared to other studies on energy budget closure for the same selected global and regional scales.

Paul W Stackhouse↗
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Application of the BSRN Data in Validating the GEWEX SRB Data: Quality-Control and Resulting Available Monthly Means

The BSRN data have been used in validation of the satellite-based GEWEX SRB data, and the recent Release 4.0-IP data cover the 34-year period from July 1983 to June 2017. Here we focus on the validation of the shortwave monthly means from 1992 to 2017 against the BSRN Global 1. We first perform the BSRN-recommended quality-control on the original data. We then calculate the monthly-hourly means from which we calculate the monthly means. Twenty-four (24) monthly-hourly means are required to calculate a monthly mean. To guarantee the quality of the monthly mean, we also require that 95% or more hourly means be available in order for a monthly-hourly mean to be calculated. Since the above quality-control significantly reduces the number of available monthly means, we are curious how many monthly means we would get if we relax the quality-control, and how the resulting monthly means would compare with the GEWEX SRB data. In a version we experimented, only constant upper and lower bounds are imposed on various fluxes, and the original data are largely retained. We found that many more monthly means would be available, and the overall bias and RMS would not be significantly different from that of the strict quality-control. With the strict quality-control, if we let Avail (minimum percentage of available hourly means required for a monthly-hourly mean to be computed) change from 3.2% to 95%, the Bias/RMS/N change from -2.77/20.56/9756 to -0.35/13.41/4581, where N is the number of available monthly means, and Bias and RMS are in the unit of W/sq. m. On the other hand, with the lax quality-control, when Avail changes from 3.2% to 95%, the Bias/RMS/N change from -0.82/19.53/9819 to -0.21/14.41/5875. South Pole (SPO) is one of the sites we are particularly interested in. With the strict quality-control, and when Avail changes from 3.2% to 95%, the Bias/RMS/N change from 5.89/15.85/283 to 1.23/5.52/133; with the lax quality-control, the Bias/RMS/N change from 1.17/11.21/284 to 1.88/7.9/177.

Taiping Zhang↗
NASA NTRSDate not supplied

Surface and Atmospheric Shortwave Radiative Fluxes From ISCCP Data and Fu-Liou Algorithm at Higher Spatial and Vertical Resolution

NASA/GEWEX Surface Radiation Budget (SRB) has provided surface and TOA shortwave and longwave radiative fluxes using International Satellite Cloud Climatology data as the primary input. Release 4.0 came out in 2019, with data from July 1983 through June 2017, and improved validation stats relative to Release 3.0 (Stackhouse et al., 2012). Release 4.0 used the newly reprocessed ISCCP H data set. The shortwave algorithm for versions 3 and 4 has been based on the Pinker and Laszlo (1992) algorithm, which relies on the satellite-measured shortwave radiance to produce a TOA albedo. This background TOA albedo is made utilizing the background clear-sky visible radiance (called clear-sky composite radiance in the ISCCP data) and applying narrowband-to-broadband angular distribution models. Using a climatological aerosol assumption, the surface albedo is estimated using radiative transfer based (i.e., Fu/Liou radiative transfer model; Fu and Liou, 1993) look-up tables. Using this surface albedo and an instantaneous TOA albedo, the look-up tables are used to adjust both the aerosol optical depth (for clear sky) and cloud optical depth (for cloudy sky) for each scene. These properties and look up tables are then used to generate surface fluxes. While this has worked well to provide useful fluxes, it has occasionally resulted in inaccurate direct and diffuse surface SW fluxes due to the overreliance on aerosol optical depth. With increased computational power and storage now available, a more direct approach is now possible. Here we present a different approach for a future high resolution SRB Release 5.0. We replace the Pinker-Laszlo lookup table approach with a forward call to the Fu-Liou radiative transfer model as modified by the CERES team (Rose et al., 2006). In addition to being a proven radiation code, Fu-Liou allows the calculation of fluxes at different atmospheric levels and spectral bands, which will provide more insight into the surface radiation budget, its variability and attribution. It is expected that horizontal resolution will increase to at least 0.5°x0.5° from the current 1°x1°. Here we demonstrate a preliminary look at the next SRB, and show comparisons with the current release.

Earth Radiation Budget↗
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The Surface Longwave Downward Fluxes of the NASA GEWEX SRB Release 4.0 IP Products: Validation Against the Surface-Based BSRN and PMEL Observed Data

Since the NASA Global Energy Water Exchanges (GEWEX) Surface Radiation Budget (SRB) project released its 3rd version of products in 2010, the GEWEX Data Assessments Panel (GDAP) has been working on integrating various data products to address issues in the closing of the global energy and water cycles. The 4th version of the SRB products, Rel. 4.0-IP, has integrated data products from the cloud, aerosol, atmosphere, ocean surface, and land surface projects, coordinating within GDAP, to produce a long-term time series of TOA and surface radiative estimates. The Rel. 4-IP shortwave products span 34 years continuously from July 1983 to June 2017 on a quasi-equal-area 1degree longitude by 1degree latitude grid system. The longwave products are for land only from 1983-07 to 1987-12; for both land and ocean from 1988-01 to 2009-12; and ocean only from 2010-01 to 2017-06. The data are provided at 3 hourly, 3-hourly-monthly, daily and monthly means. The ISCCP HXS clouds and radiances are the key cloud input of the current GEWEX SRB algorithms. In addition, the longwave algorithm has also made changes in cloud microphysical property, surface skin temperature input, surface emissivity, atmospheric profile, adding longwave aerosol optical properties, revising cloud overlap procedure, and so on. Details of changes in both inputs and algorithms are documented in a NASA Algorithm Theoretical Basis Document (ATBD). We have validated the surface longwave downward fluxes against the surface-based Baseline Surface Radiation Network (BSRN) and the Pacific Marine Environmental Laboratory (PMEL) buoy data. As of 2020, the BSRN archive has 12,116 site-months of observed records from 73 stations on all seven continents, and as of 2017, PMEL archive has 4389 buoy months of observed records from 64 buoys deployed in the tropics of Pacific, Atlantic and Indian Oceans. This paper presents how the SRB Rel. 4.0-IP surface longwave downward fluxes compare with these surface-based measurements and how the comparison statistics differ from that of Rel. 3.0.

GEWEX SRB↗
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Using Time Series Data Products to Support ASHRAE’s Historic and Future Climate Data Needs through NASA’s POWER Web Services

To address the data needs for resilience and sustainability of building systems within ASHRAE, the NASA Prediction of Worldwide Energy Resource (POWER) project facilitates the use of NASA Earth Science data on a long-term, global scale. Solar data from several NASA projects and meteorological data from NASA assimilation models have been reformatted and disseminated to the public via a user friendly web GIS-enabled based data portal (https://power.larc.nasa.gov) in selectable data formats, immediately amenable to key industry wide decision support tools such as EnergyPlus. Time series of potential climate conditions from downscaled climate simulations are being made available for similar statistics and formats. An emphasis is placed upon obtaining and utilizing time series data to conduct analysis of building system performance for current and planning building systems for energy savings and greenhouse gas emissions. This presentation has the learning following learning objectives for the ASHRAE community: 1) Learn how NASA POWER’s web service suite can provide supplementary solar and surface meteorological data parameters, including a discussion of uncertainty. 2) Learn how downscaled climate scenario information can be provided to evaluate potential future requirements. The presentation is part of a forum entitled, "Weather Data for Large-Scale Building Energy Modeling".

time series↗
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Monthly Mean DNI and GTI Derived from Monthly Mean GHI and DHI Using Two Methods: Comparisons with the BSRN Data and the Results Derived from the CERES Hourly Data

Monthly mean Global Horizontal Irradiances (GHI) and Diffuse Horizontal Irradiances (DHI) are more widely available than monthly mean Direct Normal Irradiances (DNI) and Global Tilted Irradiances (GTI). Empirical methods have been developed to derive monthly mean DNI and GTI from monthly mean GHI or from GHI and DHI. In this paper, we evaluate two such methods. The first one was the Whitlock Method developed by Charles H. Whitlock (2005) for the NASA POWER project by means of regression of the BSRN data. The method expresses the monthly mean DHI-to-GHI ratio as polynomial functions of monthly mean clearness index, sunset hour angle and noon solar elevation angle on the monthly-average-day. The monthly mean DNI is calculated by dividing the monthly mean GHI-DHI difference, or DirHI, by the cosine of the solar zenith angle at the mid-time between sunrise and solar noon on the monthly-average-day. The second method is the LJCR Method developed by Liu and Jorden (1960) and Collares-Pereira and Rabl (1979), and this method empirically splits monthly mean GHI and DHI into hourly means on the monthly-average-day, and the resulting hourly mean GHI and DHI and their difference, DirHI, can then be used to compute the monthly mean DNI, GTI and the global solar tracker irradiance (GTrI). This method is also used by RETScreen. We recently produced a set of hourly DNI and DHI by bias-correcting the CERES hourly DNI and DHI, and computed hourly GTI and GTrI as well. The data span twenty plus years from March 2000 to near present on a 1 by 1 grid system. The monthly mean CERES GHI and the corrected DHI are used as inputs to the above two methods to compute monthly mean DNI, GTI and GTrI. Through comparisons with the BSRN data, it is found that the Whitlock Method, with slight modification, and the LJCR Method can produce results that are nearly as good as the results derived from the CERES hourly data.

Taiping Zhang↗
NASA NTRSDate not supplied

Creating A Consistent Historical NASA POWER Solar Radiation Dataset to Support Renewable Energy, Building Energy Efficiency and Agro-Climatology Decisions

Prediction of Worldwide Energy Resources (POWER) project provides irradiance dataset to support renewable energy, building energy efficiency and agricultural needs. These datasets are derived from Global Energy and Water Cycle Experiment Surface Radiation Budget (GEWEX SRB) and Clouds and the Earth’s Radiant Energy System (CERES SYN1Deg). A systematic bias has been reported between these two datasets for the years with overlapping observations. For obtaining a consistent climate data record spanning the entire time record of observations, it is crucial to understand and remove the bias in the irradiance dataset. Inconsistency in solar radiation data can lead to inaccurate conclusions about solar energy potential and obscure real trends in solar radiation patterns that would impact energy availability assessments. In this study, we adapt quantile mapping approach to remove the systematic bias and to improve reliability of shortwave and longwave irradiance data. We present a validation of the bias corrected data against ground truth. For each 1° latitude and 1° longitude grid box across the globe, we match the CDFs of the reference dataset (CERES SYN1Deg) to that of the SRB dataset, thereby, adjusting the irradiance values to match the empirical distribution of two different measurements. The performance of quantile mapping is evaluated by using the metrics such as Mean Absolute Deviation (MAD). The results indicate that the quantile mapping significantly improves the accuracy and reliability of solar irradiance dataset especially for the weather conditions associated with high cloud cover and extreme irradiance values. The initial range of MAD for the studied sites for daily data was 4 to 19 Wm-2. After correction these reduced to 3 to 7 Wm-2. The findings from this study have important implications for solar energy system design, agricultural planning, and climate modeling community. Reducing the inconsistency and biases in solar irradiance dataset can enable better planning and operation of solar energy systems, leading to increased efficiency and cost-effectiveness. Additionally, this work also contributes to the statistical post-processing techniques in the renewable energy domain and highlights the potential of historical and near-real-time NASA POWER dataset as a valuable resource for solar energy research and applications.

POWER↗
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Assessing the Variability of Radiation, Water and Energy in the Deep Tropics Over the Last 3 Decades

Global surface energy closure and its variability depends heavily upon the surface radiative energy budget in the deep tropics. A key process observed is the change in convection regimes from disorganized convection to organized deep convection. During these periods an imbalance is observed between energy and water fluxes in terms of energy closure in some atmospheric reanalysis systems, implying that processes are not simulated well. A recent paper by Hsaio et al (2023, pre-published version) found that the transition process has wind shear and longwave cloud radiative feedback signatures. In this presentation, we assess the surface radiative budget in the deep tropics by comparing multiple data products (GEWEX SRB Rel4IP, CERES Ed4.1, ISSCP FH, etc.) and describing the variability across the deep tropics for the period from 1988 to near present. We assess this variability of the radiative flux anomalies (including the net TOA, surface and the atmospheric divergence fluxes) against water vapor divergence, cloud properties (include ISCCP “Weather States, Tselioudis et al. 2021) and larger scale wind shear. We include further analysis contrasting 6 key tropical oceanic regions (Indian Ocean east and west, tropical western, central and eastern Pacific Ocean, and Tropical Atlantic Ocean) and the sensitivity of the fluxes as a function of fluctuations in cloud types in response to various larger scale atmospheric processes (e.g. El Niño, Indian Ocean Dipole). These are contrasted against the modeled radiative fluxes from ERA-5 and MERRA-2. Ocean buoy measurements of radiative fluxes are utilized to help assess data radiative flux uncertainty over the nearly 40 year period. In general, the variability for overlap periods of these various data products agrees well, but there are significant differences in the net fluxes that vary according to the rendering of surface, atmospheric, aerosol and cloud properties. We conclude with recommendations for continuing work.

Radiation budget↗
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The Use of the BSRN Data as A Benchmark for the POWER Hourly DHI and DNI and In Validating Derived Hourly GTI

The satellite-based CERES SYN1deg hourly data is the source data of the POWER GIS solar data that covers 2001 to near present. The SYN1deg(Ed4.1) hourly GHI agrees well with the BSRN data, but the hourly DHI and DirHI (Direct Horizontal Irradiance) are positively and negatively, respectively, biased with appreciable magnitudes. The hourly DNI, derived by dividing the DirHI by cos(SZA), or the cosine of the solar zenith angle, is therefore negatively biased. Based on the statistics of comparisons with the BSRN data, we performed bias corrections on the hourly DHI and DNI. The corrections were executed in the 3-D phase space of latitude, cos(SZA), and cloud fraction (CLFR). The isotropic model is then used to derive the hourly global tilted irradiance (GTI). For validation purpose, we applied the isotropic model to the BSRN data at the original 1-, 2-, 3- or 5-minute interval. The satellite-based hourly GTI shows good agreement with their BSRN counterpart. We also examined two monthly-mean-based methods that empirically derive monthly mean GTI and DNI from monthly mean GHI and from both monthly mean GHI and DHI. The monthly-mean-based results compare favorably with the hourly-mean-based results. The GEWEX SRB (V4-IP) provides POWER with daily mean GHI for the years before the CERES era, and the data were corrected using quantile mapping by referencing the CERES SYN1deg data. We used the Kolmogorov -Smirnov test (K-S test) and Cramer-von Mises test to examine how well the results agree with the BSRN data. We found that if we set the lower limit for the daily mean GHI to 30 W m-2, the data can pass the K-S test at 0.01 significance level and the Cramer-von Mises test at 0.001 significance level. If no lower limit is set on the daily means, the data fail both tests. The satellite-based CERES SYN1deg hourly data is the source data of the POWER GIS solar data that covers 2001 to near present. The SYN1deg(Ed4.1) hourly GHI agrees well with the BSRN data, but the hourly DHI and DirHI (Direct Horizontal Irradiance) are positively and negatively, respectively, biased with appreciable magnitudes. The hourly DNI, derived by dividing the DirHI by cos(SZA), or the cosine of the solar zenith angle, is therefore negatively biased. Based on the statistics of comparisons with the BSRN data, we performed bias corrections on the hourly DHI and DNI. The corrections were executed in the 3-D phase space of latitude, cos(SZA), and cloud fraction (CLFR). The isotropic model is then used to derive the hourly global tilted irradiance (GTI). For validation purpose, we applied the isotropic model to the BSRN data at the original 1-, 2-, 3- or 5-minute interval. The satellite-based hourly GTI shows good agreement with their BSRN counterpart. We also examined two monthly-mean-based methods that empirically derive monthly mean GTI and DNI from monthly mean GHI and from both monthly mean GHI and DHI. The monthly-mean-based results compare favorably with the hourly-mean-based results. The GEWEX SRB (V4-IP) provides POWER with daily mean GHI for the years before the CERES era, and the data were corrected using quantile mapping by referencing the CERES SYN1deg data. We used the Kolmogorov -Smirnov test (K-S test) and Cramer-von Mises test to examine how well the results agree with the BSRN data. We found that if we set the lower limit for the daily mean GHI to 30 W m-2, the data can pass the K-S test at 0.01 significance level and the Cramer-von Mises test at 0.001 significance level. If no lower limit is set on the daily means, the data fail both tests.

Taiping Zhang↗
NASA NTRSDate not supplied

NASA Surface Radiation Budget Project: A Look Back and A Look Forward

The NASA Langley Surface Radiation Budget (SRB) project, historically associated with GEWEX, has provided estimates of surface and TOA shortwave and longwave radiative fluxes using International Satellite Cloud Climatology Project (ISCCP) cloud properties and radiances as primary input. The first release was in 1995 (Whitlock et al., 1995) at daily 2.5° resolution. Subsequent releases have improved physics, temporal and spatial resolution, as well as increasing the total length of the time series. Release 4 in 2019 (Kummerow et al., 2019) is on a 1° nested grid, with temporal resolutions from 3-hourly to daily and monthly. It originally spanned from July 1983 to December 2017 and has since been extended through 2019. Release 4 uses the ISCCP H series of data, a complete reprocessing which retains more pixels than the previous D series, used in prior SRB versions. SRB data has been used extensively by a wide range of customers, including but not limited to the solar energy community, climate modelers, architects, oceanographers, and the agricultural community. It is an especial feature of SRB that global radiation budget data are available from the 1983 through 2000 period, which is prior to CERES providing alternate data, and then 2000 through near present to provide overlap coverage. Here we use the 36.5 year record of SRB Release 4 to examine the changes in shortwave and longwave fluxes over the period, including the changes in different regions of the globe. We examine energy budget features such as hemispheric symmetry and implied meridional transport of energy. We look at the variability of these features prior to and during the CERES period and compare to later products. We also look at Release 5, currently under development. This version will provide 0.5° resolution. In addition to surface and TOA radiative fluxes it will include fluxes at several atmospheric layers, and some spectral features beyond the broadband shortwave and longwave fluxes in Release 4 and prior. The shortwave algorithm is undergoing a complete change from the Pinker-Laszlo algorithm. Shortwave fluxes will now be calculated from a forward call to the Fu-Liou radiative transfer model as modified by the CERES team (Rose et al., 2006). Input datasets are being improved, including surface properties, atmospheric profiles of temperature and humidity, aerosols, and total solar irradiance. Preliminary results from Release 5 and comparisons to Release 4 will be shown.

Earth Radiation Budget↗
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Exploring Radiation, Water and Energy Closure in Key Deep Tropical Regions Over the Last 3 Decades

The closure of global energy and water budgets at various time scales depends heavily upon the on the processes of water and energy exchange in the deep tropics. A key process observed is the change in convection regimes from disorganized convection to organized deep convection. During these periods an imbalance in key tropical regions is observed of water budget terms between observations and atmospheric reanalysis systems, implying that processes are not simulated well. For instance, periods of imbalance in the water budget may be at least partly attributed to precipitation estimates due to the transition between cloud and precipitation systems in which ice cloud affects microwave radar estimates (Lietmann-Niimi et al. 2024, submitted). A recent paper by Hsaio et al (2023, pre-published version) found that the transition process is characterized by wind shear and longwave cloud radiative feedback signatures as well. This is just one example how these processes also affect the radiative fluxes and thus the energy budget at the TOA. In this presentation, we assess the net radiative budget and components in the deep tropics by comparing multiple data products (GEWEX SRB Rel4IP, CERES EBAF/SYN1deg Ed4.2, ISSCP FH, etc.) and describing the temporal variability of energy balance terms across the deep tropics for the period from 1988 to near present in six key oceanic regions. These six key tropical oceanic regions are West Indian Ocean, the south Indian Ocean east, tropical western, central and eastern Pacific Ocean, and Tropical Atlantic Ocean. In these regions we assess the sensitivity of the fluxes as a function of fluctuations in cloud types in response to various larger scale atmospheric processes (e.g. El Niño, Indian Ocean Dipole). We assess this variability of the radiative flux anomalies (including the net TOA, surface and the atmospheric divergence fluxes) against water vapor divergence, cloud properties (include ISCCP “Weather States, Tselioudis et al. 2021) and larger scale wind shear to assess the uncertainties of energy closure in these regions. These are contrasted against the modeled radiative fluxes from ERA-5 and MERRA-2. Ocean buoy measurements of radiative fluxes are utilized to help assess data radiative flux uncertainty over the nearly 40 year period. In general, the variability for overlap periods of these various data products agrees well, but there are significant differences in the net fluxes that vary according to the rendering of surface, atmospheric, aerosol and cloud properties. These differences also affect closure terms and inferences on systematic uncertainties within the observational estimates. We conclude with recommendations for continuing work

Radiation budget↗