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NASA NTRS2020

Radiative Transfer Models for Deriving Geostationary Broadband Shortwave Radiances Directly from Visible Channels for the Ceres SYN1DEG Product

The Clouds and the Earth's Radiant Energy System(CERES)project was designed to observe the Earth’s radiation budget at the 1° regional and global scale. The CERES instruments on the Terra (10:30 AM local equator crossing time) and Aqua (1:30 PM) satellite may not accurately capture the 24-hour mean flux over regions with systematic diurnal cycles. The Terra-only and Aqua-only derived regional monthly mean SW flux can differ by 25 Wm-2 over maritime stratus and land afternoon convective regions. The CERES project utilizes hourly Geostationary imager (GEO) derived broadband fluxes to more accurately estimate the regional diurnal flux in between CERES measurements. We propose an approach that converts the GEO visible radiance to broadband radiance using RTM radiances that are specific to the individual GEO visible channel spectral response functions. The RTM is first validated using the very spectrally narrow MODIS visible channel and CERES broadband radiances.

geostationary derived broadband radiances↗
NASA NTRS2020

Uncertainties in CERES Top-of-Atmosphere Fluxes Caused by Changes in Accompanying Imager

The Clouds and the Earth’s Radiant Energy System (CERES) project provides observations of Earth’s radiation budget using measurements from CERES instruments on board the Terra, Aqua, Suomi National Polar-orbiting Partnership (S-NPP), and NOAA-20 satellites. The CERES top-of-atmosphere (TOA) fluxes are produced by converting radiance measurements using empirical angular distribution models, which are functions of cloud properties that are retrieved from imagers flying with the CERES instruments. As the objective is to create a long-term climate data record, not only calibration consistency of the six CERES instruments needs to be maintained for the entire time period, it is also important to maintain the consistency of other input data sets used to produce this climate data record. In this paper, we address aspects that could potentially affect the CERES TOA flux data quality. Discontinuities in imager calibration can affect cloud retrieval which can lead to erroneous flux trends. When imposing an artificial 0.6 per decade decreasing trend to cloud optical depth, which is similar to the trend difference between CERES Edition 2 and Edition 4 cloud retrievals, the decadal SW flux trend changed from −0.3 5 ± 0.18 Wm −2 to 0.61 ± 0.18 Wm −2 . This indicates that a 13% change in cloud optical depth results in about 1% change in the SW flux. Furthermore, different CERES instruments provide valid fluxes at different viewing zenith angle ranges, and including fluxes derived at the most oblique angels unique to S-NPP (>66 ∘ ) can lead to differences of 0.8 Wm −2 and 0.3 Wm −2 in global monthly mean instantaneous SW flux and LW flux. To ensure continuity, the viewing zenith angle ranges common to all CERES instruments (<66 ∘ ) are used to produce the long-term Earth’s radiation budget climate data record. The consistency of cloud properties retrieved from different imagers also needs to be maintained to ensure the TOA flux consistency.

Wenying Su↗
NASA NTRSDate not supplied

Assessing the Radiative Impact of the 2019 – 2020 Australian Bushfires using Trajectory-Mapped CALIPSO Observations.

During the 2019/2020 fire season, Australian bushfires burned 46 million acres, killed 39 people and billions of animals, and became the costlier fire season in Australian history. Between the end of December and early January, a series of pyrocumulonimbus injected thick smoke layers in the upper troposphere and lower stratosphere which were observed over the Tasmanian Sea and New Zealand by the Ozone Mapping and Profiler Suite (OMPS) and the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO). The smoke plume crossed the tropopause and was further dispersed across the Eastern Pacific Ocean rising up to 30 km height after two weeks. . In this study, we use CALIPSO and the NASA Langley Trajectory Model (LaTM), driven by Modern-Era Retrospective analysis for Research and Application, Version 2 (MERRA-2) meteorological data, to track the dispersion of Australian fire smoke plumes in both the troposphere and the stratosphere. Trajectory mapping is used to re-construct the 3-dimension structure of the smoke plumes. Results are compared with independent observations from the Stratospheric Aerosol and Gas Experiment (SAGE) III on the International Space Station (ISS) to understand the complex transport of the plume into the stratosphere and its lifetime. Using trajectory maps, the impact of the Australian bushfires on the Earth’s radiative energy budget is assessed with the Clouds and the Earth’s Radiant Energy System (CERES).

Australian Bushfires↗
NASA NTRSDate not supplied

A User-Focused Renovation of CERES Metadata

Production software and public data products for Clouds and the Earth’s Radiant Energy System (CERES) continue to evolve as the project extends its climate data record. The data management team for CERES is currently undertaking major renovations of both code and data products, the latter of which is, of course, in service of improving user experience. A major mode of CERES’ data product improvement is in renovating products’ metadata. Metadata standards have evolved since CERES began producing its data products in 2000. In its twentieth year, CERES essentially asked the question: how would the project design its data products if it could start all over again? With forthcoming editions, this rebirth will be realized. CERES has redesigned its metadata standards to best position itself for data discoverability. The project has used the latest standards being developed in NASA’s Earth Science Data and Information Systems (ESDIS) Project’s Unified Metadata Model (UMM) documentation; collaborated with the Atmospheric Science Data Center (ASDC) to ensure compliance with Common Metadata Repository compatibility, and continued compliance with Climate and Forecast (CF) Conventions. In doing so, the team created its own, internal document for proper metadata creation and metadata verification software that is deployed prior to all code deliveries. This presentation will discuss this redesign process, as well as needs met and those that are still outstanding in the search for an improved user experience with CERES data products.

Kathleen Dejwakh↗
NASA NTRSDate not supplied

Studying the 2019 Australian Bushfires Disaster using NASA Data: A Data-Driven Storytelling Approach

The 2019-2020 Australian fire season was particularly devastating, with millions of acres of land burned and impacts affecting Australian ecology, local populations and air quality, and the atmosphere. Australia saw unprecedented heat waves, with temperatures reaching 120 F (49.1 C) in January across central and eastern Australia. The fires gave rise to a host of atmospheric phenomenon, including smoke transport and lofting generated by storm-induced by fires, known as pyrocumulonimbus, reaching the stratosphere. NASA’s satellites not only tracked the event in real time, but also gathered data to further inform forecasting and response methods in the future. To better assist the public in understanding the lead up, impacts, and aftermath effects of these fires, the Science Outreach Team at NASA Langley Research Center’s Atmospheric Science Data Center (ASDC) Distributed Active Archive Center (DAAC) used Esri’s storymap tool to guide users through understanding relevant phenomenon, contributing factors, the effects this event has had on global atmospheric composition, and the science behind researching the tie between disasters and public health. The storymap uses data from the ASDC-supported NASA missions Measurements Of Pollution In The Troposphere (MOPITT), Cloud-Aerosol and Infrared Pathfinder Satellite Observation (CALIPSO), Clouds and the Earth’s Radiant Energy System (CERES), the Stratospheric Aerosol and Gas Experiment (SAGE III), and Multi-angle Imaging SpectroRadiometer (MISR). By using data-driven storytelling to communicate impacts of a large fire event, we hope to provide an accessible, engaging science outreach tool format.

Sanjana Paul↗
NASA NTRSDate not supplied

Understanding The Top-Of-Atmosphere Fluxes Difference Between Aerocom Phase III Models And The CERES Product: Clear-Sky Perspective

The Clouds and the Earth’s Radiant Energy System (CERES) project produces a long-term global climate data record (CDR) that can be used to detect decadal changes in the Earth’s radiation budget (ERB) from the surface to the top-of-atmosphere (TOA). The CERES Energy Balanced and Filled (EBAF) product includes monthly mean shortwave (SW), longwave (LW), and net TOA all-sky and clear-sky radiative fluxes over 1-degree latitude by 1-degree longitude regions. The EBAF SW and LW fluxes are adjusted within their uncertainties to be consistent with the heat storage in the Earth-atmosphere system (Johnson et al. 2016). EBAF also provides a gap-free monthly mean clear-sky flux map by inferring clear-sky fluxes from both CERES and MODIS measurements (Loeb et al. 2018). In this study, we compare the TOA clear-sky fluxes from Aerocom phase III output with those from the CERES EBAF products. Flux differences over the ocean are generally smaller than over the land, and the magnitude of the differences shows seasonal and regional dependency. To understand the flux differences, aerosol optical depths (AOD) from the Aerocom models are compared with the satellite retrievals from MODIS and MISR. Over the ocean, the AOD differences and the flux differences show consistent regional features, indicating that the differences between models and observations are robust as the CERES EBAF clear-sky SW fluxes and MODIS/MISR AODs are determined independently. However, very little resemblance is found between the AOD and flux differences over the land. To further understand the cause of the flux differences over the land, we compare the land surface albedo from MODIS with the albedo from the models and find consistency in regional albedo differences and flux differences. Monthly regional radiative kernels of AOD and surface albedo derived using the MERRA-2 reanalysis data (Thorsen et al. 2020) are applied to AOD and surface albedo differences between models and observations. For most of the models, the AOD and surface albedo differences can explain most of the flux differences between models and CERES EBAF. The EOS era satellites have provided 20 years of carefully calibrated and validated observations that are suitable for trend analysis. Both the MODIS AOD and CERES EBAF clear-sky SW flux show decreasing trends over the coastal regions of eastern China and the eastern United States due to the emission control policies enforced in both countries, and an increasing trend off the coast of India. The AOD and clear-sky SW flux trends are less consistent over land, as the surface albedo changes complicate the clear-sky SW flux trend. The AOD and clear-sky SW flux trends from the Oslo model HIST run are also examined. However, none of the aforementioned regional trends are found in the model results.

Wenying Su↗
NASA NTRS2020

Studying the 2019-2020 Australian Bushfires Using NASA Data

The 2019-2020 season has been one of the worst fire seasons on record. Australia has seen unprecedented heat waves, with temperatures reaching 120 F (49.1 C) in January across central and eastern Australia. NASA's satellites not only tracked the event in real time, using resources such as the Global Actives Fires and Hotspots Dashboard you see below, but also collected large volumes of rich data that scientists and researchers can use to study the event and the regional and global effects of the disaster. In this Esri StoryMap, we will guide you through the factors leading up to the 2019-2020 Australian bushfires disaster, the effect this event has had on air quality and global atmospheric composition, and the science behind researching the tie between disasters and public health. This story map will use data from ASDC-supported NASA missions such as the Measurements Of Pollution In The Troposphere (MOPITT), Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), Clouds and the Earth’s Radiant Energy System (CERES), Stratospheric Aerosol and Gas Experiment (SAGE III) on the International Space Station (ISS), and Multi-angle Imaging SpectroRadiometer (MISR).

Sanjana Paul↗
NASA NTRSDate not supplied

CERES Fast Longwave And SHortwave Radiative Flux (FLASHFlux): Research to Operation

The Clouds and Earth’s Radiant Energy System (CERES) project provides satellite-based observations of how Earth’s energy flows are varying in time and space and how clouds and aerosols are affecting the Earth’s radiation budget. Nominally, CERES data products require months of validation and calibration before releasing a climate quality data. The Fast Longwave and Shortwave Radiative Flux (FLASHFlux) data product was developed as to provide key radiative flux data products within a week of observations for scientific, applied science research and educational usage. FLASHFlux achieves this by using simplified calibration process and optimized CERES data fusion production system, an operation meteorology product from Global Modeling and Assimilation Office(GMAO), and surface parameterized radiative flux models. The CERES FLASHFlux provides two data products: 1) an hourly Level 2 Single Scanner Footprint (SSF) data separately for Aqua and Terra observations, and 2) a daily Level 3 Time Interpolated and Spatially Averaged (TISA) 1ox1o gridded data that combines Aqua and Terra observations.The current operational Version 3C is being transitioned to Version4A. We compare the FLASHFlux Version4A fluxes using the specialized calibration to Version3C and to the climate quality CERES Edition4A TOA and surface fluxes over time for Terra and Aqua to determine the uncertainties of the calibration process. In addition, we also compare the impact of the fluxes by using the near real-time GMAO GEOS FP-IT instead of GMAO G5-CERES meteorology data.We also compare both SSF overpass products (for Terra and Aqua) and TISA radiative flux products to a set of surface measurement sites that are globally distributed and assess agreement.Lastly, we introduce the first CERES FF SSF data products from the CERES instrument on board NOAA-20.

P Sawaengphokhai↗
NASA NTRS2020

Georgia Energy III Project Summary - Identifying Habitat and Solar Site Conflict in Georgia by Developing an Environmental Sensitivity Public Mapping Too

The rapid expansion of the solar industry across the state of Georgia has a detrimental effect on the habitats of keystone and threatened species, such as the gopher tortoise (Gopherus polyphemus) and the American black bear (Ursus americanus). NASA DEVELOP collaborated with the Georgia Chapter of The Nature Conservancy (TNC) and the Georgia Department of Natural Resources to continue the research from two previous NASA DEVELOP projects in 2017. The team worked to assess the conflict between solar suitability and environmentally sensitive areas with the Land-Use Conflict Identification Strategy (LUCIS) and to determine how conflict has changed since the 2017 analysis. The project utilized Terra/Aqua Clouds and the Earth's Radiant Energy System (CERES) satellite data and other ancillary datasets to conduct and compare a general statewide LUCIS analysis from 2017 to 2019 and to complete an in-depth LUCIS analysis of Georgia’s fastest-growing solar counties—Taylor, Twiggs, Decatur, and Brooks. The analysis indicated that between 2017 and 2019, the entire state saw high conflict areas increase by 38%. Project partners will use these findings to target areas for promotion of conservation policy and education efforts. The team also provided the TNC with a publicly available web application, called the Environmental Sensitivity Mapping Tool (ESMT), that can be updated as new data are released. The ESMT will be used to educate interest groups, such as solar developers and conservationists, to help them recognize and mitigate the negative effects of solar development on the environment.

DEVELOP Project Summary↗
NASA NTRSDate not supplied

Assessing the Radiative Impact of the 2019 – 2020 Australian Bushfires using Trajectory-Mapped CALIPSO and SAGE III/ISS Observations.

During the 2019/2020 fire season, Australian bushfires burned 46 million acres, killed 39 people and billions of animals, and became the costlier fire season in Australian history. Between the end of December and early January, a series of pyrocumulonimbus injected thick smoke layers in the upper troposphere and lower stratosphere which were observed over the Tasmanian Sea and New Zealand by the Ozone Mapping and Profiler Suite (OMPS) and the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO). The smoke plume crossed the tropopause and was further dispersed across the Eastern Pacific Ocean rising up to 30 km height after two weeks. . In this study, we use CALIPSO and the NASA Langley Trajectory Model (LaTM), driven by Modern-Era Retrospective analysis for Research and Application, Version 2 (MERRA-2) meteorological data, to track the dispersion of Australian fire smoke plumes in both the troposphere and the stratosphere. Trajectory mapping is used to re-construct the 3-dimension structure of the smoke plumes. Results are compared with independent observations from the Stratospheric Aerosol and Gas Experiment (SAGE) III on the International Space Station (ISS) to understand the complex transport of the plume into the stratosphere and its lifetime. Using trajectory maps, the impact of the Australian bushfires on the Earth’s radiative energy budget is assessed with the Clouds and the Earth’s Radiant Energy System (CERES).

Australian bushfire↗
NASA NTRSDate not supplied

CERES Fast Longwave And SHortwave Radiative Flux (FLASHFlux): Research to Operation

The Clouds and Earth’s Radiant Energy System (CERES) project provides satellite-based observations of how Earth’s energy flows are varying in time and space and how clouds and aerosols are affecting the Earth’s radiation budget. Nominally, CERES data products require months of validation and calibration before releasing a climate quality data. The Fast Longwave and Shortwave Radiative Flux (FLASHFlux) data product was developed as to provide key data for applied science research involving the renewable energy and agricultural sectors within a week of observations. FLASHFlux achieves this by using simplified calibration, an operation meteorology product from Global Modeling and Assimilation Office (GMAO), and its own surface parameterizations model. The CERES FLASHFlux provides two data products: 1) an hourly Level 2 Single Scanner Footprint (SSF) data separately for Aqua and Terra observations, and 2) a daily Level 3 Time Interpolated and Spatially Averaged (TISA) 1ox 1ogridded data that combines Aqua and Terra observations. We inter-compared of FLASHFlux Version4A calibration to the climate quality CERES Edition4A data product over time. In addition, we also inter-compared the impact of the fluxes by using the near real-time GMAO GEOS FP-IT instead of GMAO G5-CERES meteorology data. We also compare both SSF overpass and TISA radiative flux products to a set of surface measurement sites that are globally distributed and assess agreement.

P. C. Sawaengphokhai↗
NASA NTRS2021

Improving the CERES SYN Cloud and Flux Products by Identifying GOES-17 Scan Anomalies Using a Convolutional Neural Network

The NASA Clouds and the Earth’s Radiant Energy System (CERES) project relies on top-of-atmosphere (TOA) broadband fluxes derived from geostationary (GEO) satellite imagery to account for the diurnal flux variations between the CERES observation intervals, and thereby produce a synoptic gridded (SYN1deg) product based on continuous temporal observations. Consistent broadband flux derivation depends on accurate radiative property measurements and cloud retrievals, which largely determine the radiance-to-flux conversion process. Therefore, it is important to ensure a high quality of cloud property input in order to maintain a reliable broadband flux record. In Edition 4 of the CERES SYN1deg product, a robust automated image anomaly detection algorithm based on inter-line and inter-pixel differences, spatial variance, and 2-D Fourier analysis has been successful in identifying imagery with linear artifacts, but the line-by-line inspection and cleaning process must still be performed by a human. Therefore, further automation of this quality assurance process is warranted, especially considering the excessive amount of additional cleaning necessitated by the GOES-17 Advance Baseline Imager (ABI) cooling system anomaly. As such, this article highlights advancement of the CERES GEO image artifact cleaning approach based on a convolutional neural network (CNN) for classification of bad scanlines. Once trained, the CNN approach is a computationally inexpensive means to ensure greater consistency in cloud retrievals, and therefore broadband flux derivation, based on GOES-17 measurements.

Benjamin Scarino↗
NASA NTRS2021

Optimized MODIS Channel Selection to Improve the NASA CERES FluxByCloudType Product Fluxes

The NASA Clouds and the Earth’s Radiant Energy System (CERES) project has provided the climate community more than a 20-year record of top of the atmosphere (TOA) reflected shortwave (SW) and emitted longwave (LW) fluxes. The fluxes used to monitor the Earth’s energy balance as well as for climate model validation and cloud feedback studies. One of the largest uncertainties in climate models is the response of clouds in feedback studies. To reduce this uncertainty requires more stringently validation of model generated fluxes by cloud-type. Rather than relying on radiative transfer model generated fluxes from observed cloud-type retrievals, the CERES FluxByCloudType (FBCT) product, relies on MODIS empirical narrowband to broadband relationships to convert the cloudy portions of the CERES footprints into fluxes. The overcast footprint and sub-footprint cloud layer fluxes are then stratified by 7 pressure layers and 6 optical depth bins and temporally averaged into daily and monthly regional cloud-type fluxes. The CERES project analyzed a total of 19 MODIS channels for use in the next generation FBCT product narrowband to broadband conversion. This was accomplished by comparing the narrowband to broadband RMS errors from all possible 5-channel combinations. The SW and LW optimized channels were selected by also considering analogous geostationary, MODIS and VIIRS imager channels as well as channel combinations that provided the lowest RMS errors across all surface types. The optimized channel combinations will be tested in the FBCT algorithm to investigate any cloud fraction, effective pressure, optical depth, PW, solar and view angle, surface type and regional narrowband to broadband dependencies.

CERES↗
NASA NTRSDate not supplied

Towards a More Realistic Representation of Surface Albedo in NASA CERES Satellite Products: A Comparison with MOSAiC Field Campaign

Observing the Arctic from space is one of the most challenging tasks in climate science. Uncertainty in the NASA Clouds and the Earth’s Radiant Energy System (CERES)-derived irradiances is larger over sea ice than any other scene type and comes from several sources. The one-year long MOSAiC expedition in the central Arctic provides a rare opportunity to explore uncertainty in CERES-derived radiative fluxes. First, a systematic and statistically robust assessment of surface shortwave and longwave fluxes has been conducted using in-situ measurements from MOSAiC flux stations. The CERES SYN1deg product overestimates the SW_down flux by 11.40 Wm-2 and underestimates the SW_up flux by −15.70 Wm-2 and LW_down fluxes by −13.30 Wm-2 at the surface during summertime. In addition, large differences are found in the LW_up flux (~320 Wm-2) when the surface reaches melting point (~0℃). The large negative bias in upwelling shortwave flux can be attributed to the underestimation of surface albedo (−0.15) in SYN1deg. In addition to direct comparison, a series of perturbation experiments with a radiative transfer model are performed to estimate the contributions to the differences. By correcting both cloud and albedo inputs, the biases in SW_net flux and LW_net flux can be reduced to less than half of the control run biases to +19.90% and −10.53%, respectively. Furthermore, a compensating effect between underestimation of broadband albedo and overestimation of spectral albedo in visible and mid-infrared bands in SYN1deg datasets is found and contributes to the shortwave flux differences. The difference in CERES broadband albedo (~20 Wm 2) contributes to larger uncertainty in SW_up flux than spectral albedo shape (~3 Wm 2). The results of this study inform the future development of CERES products and will ultimately reduce uncertainties in Arctic surface radiation budget derived from satellite measurements.

Yiyi Huang↗
NASA NTRSDate not supplied

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↗
NASA NTRSDate not supplied

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↗
NASA NTRSDate not supplied

Evaluating Twenty-Year Trends in Earth’s Energy Flows from Observations

Recent satellite and ocean in-situ observations indicate a doubling of Earth’s Energy Imbalance (EEI) since 2005 that is a consequence of anthropogenic forcing, internal variability, and climate feedbacks. In this study, we follow-up with an assessment of how other components of Earth’s energy budget have changed since 2000 and how well these can be tracked. Specifically, we use top-of-atmosphere and surface observations from the Clouds and the Earth’s Radiant Energy System (CERES) and calculations of atmospheric divergence of energy transport from ERA-5 to determine the change in total surface flux along with its radiative and turbulent heat flux components. We also assess trends in ocean heat uptake for different ocean layers using various ocean reanalysis datasets. We compare trends derived using various observational and modeling approaches to assess how robust the derived trends are. Our analysis is restricted to global, hemispheric and regional spatial scales and annual mean and seasonal timescales.

CERES↗
NASA NTRSDate not supplied

Evaluating CERES TOA Fluxes using ARISE aircraft observations

Uncertainty in observations of top-of-atmosphere (TOA) radiation fluxes are larger in the Arctic than in other regions. The magnitude of these uncertainties limit our understanding of the Arctic surface energy budget and its variability. The significant uncertainties are due to the low sun angles and wide range of highly reflecting, anisotropic, and highly heterogeneous surface conditions. Therefore, quantifying, attributing, and reducing Arctic TOA radiative flux uncertainty enables a better understanding of the rapidly changing Arctic. To advance this goal, we compare the Cloud and Earth’s Radiant Energy System (CERES) TOA radiative fluxes with measurements from the Arctic Radiation-IceBridge Sea and Ice Experiment (ARISE) flow in September 2014. A key objective of ARISE was to evaluate and attribute uncertainty in CERES footprint and gridded TOA radiative fluxes. In this study, we first compare the CERES TOA flux with those obtained from the broadband radiometer measurements from the aircraft using instantaneously matched footprint with the flight track and as the hourly gridded fluxes. This comparison indicates an agreement within uncertainty in the longwave (2 Wm-2 ) for all five grid boxes and agreement in the shortwave (10 Wm-2) for four-out-of-five grid boxes. While not a statistically significant results given the small sample size, the hourly, gridded and the instantaneously matched footprint comparison suggest a -10 Wm-2 bias for CERES in the shortwave. To explore whether this is a robust feature or a statistical artifact, we quantify the individual sources of uncertainty in the differences (temporal and spatial sampling differences, scene evolution, accuracy, angular distribution models, and scene id) to see if any of these differences account for the shortwave bias.

CERES↗