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CERES ERBE-like Monthly Regional Averages (ES-9) in HDF ( CER_ES9_Terra-FM2_Edition1-CV)

The ERBE-like Monthly Regional Averages (ES-9) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The ES-9 is also produced for combinations of scanner instruments. All instantaneous shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-8 product for a month are sorted by 2.5-degree spatial regions, by day number, and by the local hour of observation. The mean of the instantaneous fluxes for a given region-day-hour bin is determined and recorded on the ES-9 along with other flux statistics and scene information. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is 'like' the algorithm used for the Earth Radiation Budget Experiment (ERBE). The ES-9 also contains hourly average fluxes for the month and an overall monthly average for each region. These average fluxes are given for both clear-sky and total-sky scenes. The following CERES ES9 data sets are currently available: CER_ES9_FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition1 CER_ES9_PFM+FM1+FM2_Edition2 CER_ES9_PFM+FM1_Edition1 CER_ES9_PFM+FM2_Edition1 CER_ES9_PFM+FM1_Edition2 CER_ES9_PFM+FM2_Edition2 CER_ES9_TRMM-PFM_Edition1 CER_ES9_TRMM-PFM_Edition2 CER_ES9_Terra-FM1_Edition1 CER_ES9_Terra-FM2_Edition1 CER_ES9_FM1+FM2_Edition2 CER_ES9_Terra-FM1_Edition2 CER_ES9_Terra-FM2_Edition2 CER_ES9_Aqua-FM3_Edition1 CER_ES9_Aqua-FM4_Edition1 CER_ES9_FM1+FM2+FM3+FM4_Edition1 CER_ES9_Aqua-FM3_Edition2 CER_ES9_Aqua-FM4_Edition2 CER_ES9_FM1+FM3_Edition2 CER_ES9_FM1+FM4_Edition2 CER_ES9_Aqua-FM3_Edition1-CV CER_ES9_Aqua-FM4_Edition1-CV CER_ES9_Terra-FM1_Edition1-CV CER_ES9_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2006-10-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=2.5 degree; Longitude_Resolution=2.5 degree; Horizontal_Resolution_Range=250 km - < 500 km or approximately 2.5 degrees - < 5.0 degrees; Temporal_Resolution=hourly, daily, monthly; Temporal_Resolution_Range=Hourly - < Daily, Daily - < Weekly, Monthly - < Annual].

CLEAR-SKY SHORTWAVE FLUX↗

MISR Level 2 TOA/Cloud Albedo parameters (MIL2TCAL_V1)

The TOA/Cloud Albedo data contain albedo values, including finely-sampled or local (2.2 km) TOA albedos registered to the RLRA, and two coarsely-sampled (35.2 km resolution) TOA albedos projected to 30-km altitude. The local (2.2 km) albedos do not take the obscuration of cloud features into account, so they should only be treated as traditional albedos when the number of obscured pixels is low. The restrictive and expansive albedos are both available at 35.2 km resolution: the restrictive albedos are only calculated using the radiation upwelling from the pixel under consideration, whereas the expansive albedos use all the radiation emanating from the surrounding area. Therefore, the expansive albedo is closer to the traditional definition of top-of-atmosphere albedos. [Location=GLOBAL] [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=35.2 km; Longitude_Resolution=35.2 km; Horizontal_Resolution_Range=10 km - < 50 km or approximately .09 degree - < .5 degree; Temporal_Resolution=about 15 orbits/day].

CLOUD TEXTURE↗

Radiometric Assessment of the First Three Years of the NOAA-20 VIIRS Reflective Solar Bands Calibration

NASA’s Clouds and the Earth’s Radiant Energy System (CERES) SYN1deg Ed4.1 product utilizes geostationary (GEO) satellite measured radiances and retrieved cloud properties to account for the regional diurnal fluctuations in the Earth’s radiant broadband fluxes for times between the CERES measurements gathered from the Aqua (1:30 PM) and Terra (10:30 AM) sun-synchronous satellites. In CERES Edition 4 products, a global uniformity in the cloud properties and computed surface fluxes across the GEO satellite domains is maintained by scaling the radiance observations from more than twenty GEO visible imagers in the CERES record to a common radiometric reference scale, i.e., Aqua-MODIS. With the new-generation GEO (Himawari-8/9 and GOES-16/17) imagers having multiple reflective solar bands (RSB) that are spectrally similar to those of VIIRS, the CERES Imager and Geostationary Calibration Group (IGCG) is preparing to use NOAA-20 VIIRS as the reference imager for maintaining the radiometric uniformity across the GEO imager constellation. Given the recent Aqua satellite anomaly, this transition may happen sooner than the projected date of Aqua’s de-orbit. This paper presents an independent performance evaluation of the first three years of the NOAA-20 VIIRS RSB calibration in the NASA VIIRS Land Science Investigator-led Processing System (Land SIPS) L1b Collection 2 dataset. The temporal radiometric stability is assessed using multiple invariant Earth targets, including tropical deep convective clouds and the Saharan desert. The invariant target anisotropic reflectance at the top of the atmosphere was modeled using five years of stable satellite observations acquired from the previous VIIRS instrument onboard the Suomi National Polar-orbiting Partnership (S-NPP) satellite. The anisotropic corrections are essential for detecting temporal trends with high statistical confidence. In addition, the radiometric consistency between the RSB of the two VIIRS instruments will be evaluated.

Rajendra Bhatt↗

Recent Theoretical Advances in Analysis of AIRS/AMSU Sounding Data

AIRS was launched on EOS Aqua on May 4,2002, together with AMSU-A and HSB, to form a next generation polar orbiting infrared and microwave atmospheric sounding system. This paper describes the AIRS Science Team Version 5.0 retrieval algorithm. Starting in early 2007, the Goddard DAAC will use this algorithm to analyze near real time AIRS/AMSU observations. These products are then made available to the scientific community for research purposes. The products include twice daily measurements of the Earth's three dimensional global temperature, water vapor, and ozone distribution as well as cloud cover. In addition, accurate twice daily measurements of the earth's land and ocean temperatures are derived and reported. Scientists use this important set of observations for two major applications. They provide important information for climate studies of global and regional variability and trends of different aspects of the earth's atmosphere. They also provide information for researchers to improve the skill of weather forecasting. A very important new product of the AIRS Version 5 algorithm is accurate case-by-case error estimates of the retrieved products. This heightens their utility for use in both weather and climate applications. These error estimates are also used directly for quality control of the retrieved products. Version 5 also allows for accurate quality controlled AIRS only retrievals, called "Version 5 AO retrievals" which can be used as a backup methodology if AMSU fails. Examples of the accuracy of error estimates and quality controlled retrieval products of the AIRS/AMSU Version 5 and Version 5 AO algorithms are given, and shown to be significantly better than the previously used Version 4 algorithm. Assimilation of Version 5 retrievals are also shown to significantly improve forecast skill, especially when the case-by-case error estimates are utilized in the data assimilation process.

Susskind, Joel↗

Satellite Data Simulator Unit: A Multisensor, Multispectral Satellite Simulator Package

Several multisensor simulator packages are being developed by different research groups across the world. Such simulator packages [e.g., COSP , CRTM, ECSIM, RTTO, ISSARS (under development), and SDSU (this article), among others] share overall aims, although some are targeted more on particular satellite programs or specific applications (for research purposes or for operational use) than others. The SDSU or Satellite Data Simulator Unit is a general-purpose simulator composed of Fortran 90 codes and applicable to spaceborne microwave radiometer, radar, and visible/infrared imagers including, but not limited to, the sensors listed in a table. That shows satellite programs particularly suitable for multisensor data analysis: some are single satellite missions carrying two or more instruments, while others are constellations of satellites flying in formation. The TRMM and A-Train are ongoing satellite missions carrying diverse sensors that observe clouds and precipitation, and will be continued or augmented within the decade to come by future multisensor missions such as the GPM and Earth-CARE. The ultimate goals of these present and proposed satellite programs are not restricted to clouds and precipitation but are to better understand their interactions with atmospheric dynamics/chemistry and feedback to climate. The SDSU's applicability is not technically limited to hydrometeor measurements either, but may be extended to air temperature and humidity observations by tuning the SDSU to sounding channels. As such, the SDSU and other multisensor simulators would potentially contribute to a broad area of climate and atmospheric sciences. The SDSU is not optimized to any particular orbital geometry of satellites. The SDSU is applicable not only to low-Earth orbiting platforms as listed in Table 1, but also to geostationary meteorological satellites. Although no geosynchronous satellite carries microwave instruments at present or in the near future, the SDSU would be useful for future geostationary satellites with a microwave radiometer and/or a radar aboard, which could become more feasible as engineering challenges are met. In this short article, the SDSU algorithm architecture and potential applications are reviewed in brief.

Masunaga, Hirohiko↗

Rocket Lab Venus - Enabling Low-Cost Interplanetary Missions

Rocket Lab’s mission to Venus [1], launching in January 2025, aims to demonstrate that small launch vehicles, such as Electron, and high-energy small spacecraft, such as Photon, can enable a new paradigm of regular, low-cost interplanetary missions. The Electron launch vehicle will deliver the Photon spacecraft carrying the entry probe into low earth orbit, at which point Photon will take over and put both itself and the attached probe on an Earth-Venus transfer trajectory, with assistance from a Lunar flyby. The primary science objective of the mission is to sample the Venusian cloud layers between atitudes of 45 and 60 km above the surface with an autofluorescing nephelometer. The ~1kg scientific instrument will be carried by a small ~17 kg direct entry probe which will separate from the Photon spacecraft approximately 30 minutes prior to atmospheric entry. The probe outer mould line is a scaled down version of the Deep Space 2 probes [2]. NASA’s newly developed 3D Woven Carbon Phenolic, a derivative of the Heatshield for Extreme Entry Environment Technology (HEEET) material [3], is an enabling technology for this mission, and it will comprise the probe forebody heat shield.The probe will communicate directly back to the Earth during its descent via a small on-board radio frequency (RF) antenna. The hyperbolic Venus encounter will see the probe enter the Venusia atmosphere at approximately 11 km/s with an entry flight path angle (EFPA) of about 10°. This relatively low entry angle was selected to increase the duration of the descent phase, reduce the peak deceleration, and reduce the sensitivity of the nominal entry environments to navigational errors. For reference, the Pioneer Venus probes entered at EFPAs varying from about 25° to 70°, resulting in peak decelerations between around 220 and 450 g’s and peak stagnation point heat fluxes ranging from about 40 to 75 MW/m2 [4]. In comparison, the Rocket Lab Venus probe will experience a lower preak deceleration of around 60 g’s and a lower peak stagnation point heat flux of about 15 MW/m2, at the cost of a greater total heat load and correspondingly higher thermal protection system (TPS) mass fraction. This paper recounts the development history of the TPS for the Rocket Lab Venus probe, with a focus on the unique requirements of the mission. In particular, the effect on the TPS design of the mission’s tight budget, short development timeline, slim mass and RF link margins, and mild but long duration entry heating. Rocket Lab’s initial investigations into a ‘hybrid’ TPS [5] based on a scaled version of the Pioneer Venus full-density carbon phenolic forebody shield, and the abandonment of this approach in favour of NASA’s 3D Woven Carbon Phenolic is presented. Additionally, the leveraging of previous testing under the HEEET project at higher conditions and the associated TPS margining strategy that was adopted to avoid the need for extensive mission-specific arc jet testing is discussed. Finally, this paper concludes with a brief consideration of the feasibility of a future low-cost aerocapture technology demonstrator mission based on the 2025 Rocket Lab Venus mission and entry probe.

Lyle Campbell↗

Atmospheric Research 2018 Technical Highlights

Atmospheric research in the Earth Sciences Division (610) consists of research and technology development programs dedicated to advancing knowledge and understanding of the atmosphere and its interaction with the climate of Earth. The Division’s goals are to improve understanding of the dynamics and physical properties of precipitation, clouds, and aerosols; atmospheric chemistry, including the role of natural and anthropogenic trace species on the ozone balance in the stratosphere and the troposphere; and radiative properties of Earth’s atmosphere and the influence of solar variability on the Earth’s climate. Major research activities are carried out in the Mesoscale Atmospheric Processes Laboratory, the Climate and Radiation Laboratory, the Atmospheric Chemistry and Dynamics Laboratory, and the Wallops Field Support Office. The overall scope of the research covers an end-to-end process, starting with the identification of scientific problems, leading to observation requirements for remote sensing platforms, technology and retrieval algorithm development; followed by flight projects and satellite missions; and eventually, resulting in data processing, analyses of measurements, and dissemination from flight projects and missions.

Highlights↗

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↗

The Atmosphere Observing System (AOS): A core component of NASA’s Earth System Observatory (ESO)

This paper describes the Atmosphere Observing System (AOS) mission, formerly called Aerosol, Cloud, Convection and Precipitation (ACCP) and now a component of NASA’s Earth System Observatory (ESO). The AOS mission combines two high-priority missions called for in the 2017–2027 Decadal Survey (DS)1 of Earth Science and Applications from Space by the National Academies of Sciences, Engineering, and Medicine. This paper describes the scientific purpose of the mission and the organization of the mission Study Team, explains the approach to developing mission architectures, and discusses how the Study Team narrowed mission architecture choices from many to one. Finally, the next steps toward mission implementation and the challenges going forward are discussed.

Ivanco, Marie↗

GeoNEX: A Geostationary Earth Observatory

The latest generation of geostationary satellites (Himawari 8/9, GOES-16/17, FY-4, GK-2A) carries sensors that closely mimic the spatial and spectral characteristics of widely used polar-orbiting, global monitoring sensors such as MODIS and VIIRS. When combined, data from various currently operating/planned geostationary platforms provide a geo-ring of hyper-temporal (5-10 minutes), multispectral observations at spatial resolutions as high as 500 m. These high frequency observations offer exciting new possibilities for monitoring our planet, including better retrievals of geophysical variables by overcoming cloud cover, enabling studies of diurnally varying phenomena in the atmosphere, land, and the oceans, and support operational decision-making in agriculture, hydrology and disaster management. The NASA Earth Exchange (NEX) team, in collaboration with scientists from JAXA, KARI, NOAA and other international institutions, created the GeoNEX (www.nasa.gov/geonex) pipeline to integrate data from all available geostationary platforms and produce and distribute spatially, temporally, and radiometrically consistent data for the earth science community. We envision various institutions adapting the Geo component (e.g., GeoNOAA, GeoKARI, GeoChiba, GeoJAXA, GeoCMA) and customizing the pipeline and downstream products to serve the local/regional research and applied science communities. To facilitate collaborative work among the partners, we have established the OpenNEX platform on the public cloud. OpenNEX provides researchers, developers, educators, and ordinary users with easy access to an integrated Earth science computational and data platform, enabling citizen scientists and application developers to realize the full value of GeoNEX data assets and software tools.

GeoNEX↗

2024 Atmospheric Radiation Measurement (ARM) Annual Report

This report provides an overview of the Atmospheric Radiation Measurement (ARM) user facility and a sample of achievements for fiscal year 2024 (FY2024). Strong collaborations between nine DOE national laboratories enable ARM to successfully operate in remote locations around the world. This unique partnership supports the DOE mission to provide for the energy security of the nation. Without the support of the following laboratories, ARM would not be the state-of-the-art facility that it is today. ARM is a multi-laboratory, U.S. Department of Energy (DOE) Office of Science user facility and a key contributor to national and international atmospheric and climate research efforts. ARM offers scientists cutting-edge, ground-based observatories, aerial observation capabilities, and high-performance computing. ARM’s capabilities have enabled more than 30 years of continuous measurements of cloud and aerosol properties and their effects on Earth’s energy balance.

54 ENVIRONMENTAL SCIENCES↗

Surface Meteorology and Solar Energy (SSE) Data Release 5.1

The Surface meteorology and Solar Energy (SSE) data set contains over 200 parameters formulated for assessing and designing renewable energy systems.The SSE data set is formulated from NASA satellite- and reanalysis-derived insolation and meteorological data for the 10-year period July 1983 through June 1993. Results are provided for 1 degree latitude by 1 degree longitude grid cells over the globe. Average daily and monthly measurements for 1195 World Radiation Data Centre ground sites are also available. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1983-07-01; Stop_Date=1993-06-30] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree].

Arctic heating↗

NASA's mission to planet Earth: Earth observing system

The topics covered include the following: global climate change; radiation, clouds, and atmospheric water; the ocean; the troposphere - greenhouse gases; land cover and the water cycle; polar ice sheets and sea level; the stratosphere - ozone chemistry; volcanoes; the Earth Observing System (EOS) - how NASA will support studies of global climate change?; research and assessment - EOS Science Investigations; EOS Data and Information System (EOSDIS); EOS observations - instruments and spacecraft; a national international effort; and understanding the Earth System.

Source record↗

The Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2): Science Requirements, Concept, and Implementation

The Ice, Cloud, and land Elevation Satellite (ICESat) mission used laser altimetry measurements to determine changes in elevations of glaciers and ice sheets, as well as sea ice thickness distribution. These measurements have provided important information on the response of the cryosphere (Earths frozen surfaces) to changes in atmosphere and ocean condition. ICESat operated from 2003-2009 and provided repeat altimetry measurements not only to the cryosphere scientific community but also to the ocean, terrestrial and atmospheric scientific communities. The conclusive assessment of significant ongoing rapid changes in the Earths ice cover, in part supported by ICESat observations, has strengthened the need for sustained, high accuracy, repeat observations similar to what was provided by the ICESat mission. Following recommendations from the National Research Council for an ICESat follow-on mission, the ICESat-2 mission is now under development for planned launch in 2018. The primary scientific aims of the ICESat-2 mission are to continue measurements of sea ice freeboard and ice sheet elevation to determine their changes at scales from outlet glaciers to the entire ice sheet, and from 10s of meters to the entire polar oceans for sea ice freeboard. ICESat carried a single beam profiling laser altimeter that produced approximately 70 m diameter footprints on the surface of the Earth at approximately 150 m along-track intervals. In contrast, ICESat-2 will operate with three pairs of beams, each pair separated by about 3 km across-track with a pair spacing of 90 m. Each of the beams will have a nominal 17 m diameter footprint with an along-track sampling interval of 0.7 m. The differences in the ICESat-2 measurement concept are a result of overcoming some limitations associated with the approach used in the ICESat mission. The beam pair configuration of ICESat-2 allows for the determination of local cross-track slope, a significant factor in measuring elevation change for the outlet glaciers surrounding the Greenland and Antarctica coasts. The multiple beam pairs also provide improved spatial coverage. The dense spatial sampling eliminates along-track measurement gaps, and the small footprint diameter is especially useful for sea surface height measurements in the often narrow leads needed for sea ice freeboard and ice thickness retrievals. The ICESat-2 instrumentation concept uses a low energy 532 nm (green) laser in conjunction with single-photon sensitive detectors to measure range. Combining ICESat-2 data with altimetry data collected since the start of the ICESat mission in 2003, such as Operation IceBridge and ESAs CryoSat-2, will yield a 15+ year record of changes in ice sheet elevation and sea ice thickness. ICESat-2 will also provide information of mountain glacier and ice cap elevations changes, land and vegetation heights, inland water elevations, sea surface heights, and cloud layering and optical thickness.

ICESat-2↗

Customizing NASA's Earth Science Research Products for addressing MENA Water Challenges

As projected by IPCC 2007 report, by the end of this century the Middle East North Mrica (MENA) region is projected to experience an increase of 3 C to 5 C rise in mean temperatures and a 20% decline in precipitation. This poses a serious problem for this geographic zone especially when majority of the hydrological consumption is for the agriculture sector and the remaining amount is for domestic consumption. In late 2011, the World Bank, USAID and NASA have joined hands to establishing integrated, modem, up to date NASA developed capabilities for various countries in the MENA region for addressing water resource issues and adapting to climate change impacts for improved decision making for societal benefits. The main focus of this undertaking is to address the most pressing societal issues which can be modeled and solved by utilizing NASA Earth Science remote sensing data products and hydrological models. The remote sensing data from space is one of the best ways to study such complex issues and further feed into the decision support systems. NASA's fleet of Earth Observing satellites offer a great vantage point from space to look at the globe and provide vital signs necessary to maintain healthy and sustainable ecosystem. NASA has over fifteen satellites and thirty instruments operating on these space borne platforms and generating over 2000 different science products on a daily basis. Some of these products are soil moisture, global precipitation, aerosols, cloud cover, normalized difference vegetation index, land cover/use, ocean altimetry, ocean salinity, sea surface winds, sea surface temperature, ozone and atmospheric gasses, ice and snow measurements, and many more. All of the data products, models and research results are distributed via the Internet freely through out the world. This project will utilize several NASA models such as global Land Data Assimilation System (LDAS) to generate hydrological states and fluxes in near real time. These LDAS products will then be further compared with other NASA satellite observations (MODIS, VIIRS, TRMM, etc.) and other discrete models to compare and optimize evapotranspiration, soil moisture and crop irrigation, drought assessment and water balance. The floods being a critical disaster in many of the MENA countries, NASA's global flood mapping and modeling framework (CREST) will be customized for country specific needs and delivered to the remote sensing organizations for their future use. Training is an important component under this activity and adequate level of training will be offered to build basic capacity to work with NASA provided data products, models for their future use. This paper provides a comprehensive introduction to NASA's Earth Science mission for understanding the behavior of our home Planet, projecting its health for future generations and applying research results solving societal issues.

Habib, Shahid↗

CERES ERBE-like Monthly Geographical Averages (ES-4) in HDF (CER_ES4_Aqua-FM4_Edition1)

The ERBE-like Monthly Geographical Averages (ES-4) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The ES-4 is also produced for combinations of scanner instruments. For each observed 2.5-degree spatial region, the daily average, the hourly average over the month, and the overall monthly average of shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-9 product are spatially nested up from 2.5-degree regions to 5- and 10-degree regions, to 2.5-, 5-, and 10-degree zonal averages, and to global monthly averages. For each nested area, the albedo and net flux are given. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is 'like' the algorithm used for the Earth Radiation Budget Experiment (ERBE). The following CERES ES4 data sets are currently available: CER_ES4_FM1+FM2_Edition1 CER_ES4_PFM+FM1+FM2_Edition1 CER_ES4_PFM+FM1+FM2_Edition2 CER_ES4_PFM+FM1_Edition1 CER_ES4_PFM+FM2_Edition1 CER_ES4_TRMM-PFM_Edition1 CER_ES4_TRMM-PFM_Edition2 CER_ES4_Terra-FM1_Edition1 CER_ES4_Terra-FM2_Edition1 CER_ES4_FM1+FM2_Edition2 CER_ES4_Terra-FM1_Edition2 CER_ES4_Terra-FM2_Edition2 CER_ES4_Aqua-FM3_Edition1 CER_ES4_Aqua-FM4_Edition1 CER_ES4_FM1+FM2+FM3+FM4_Edition1 CER_ES4_Aqua-FM3_Edition2 CER_ES4_Aqua-FM4_Edition2 CER_ES4_FM1+FM3_Edition2 CER_ES4_FM1+FM4_Edition2 CER_ES4_PFM+FM1_Edition2 CER_ES4_PFM+FM2_Edition2 CER_ES4_Aqua-FM3_Edition1-CV CER_ES4_Aqua-FM4_Edition1-CV CER_ES4_Terra-FM1_Edition1-CV CER_ES4_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-03-29] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=2.5 degree; Longitude_Resolution=2.5 degree; Horizontal_Resolution_Range=250 km - < 500 km or approximately 2.5 degrees - < 5.0 degrees; Temporal_Resolution=1 month; Temporal_Resolution_Range=Monthly - < Annual].

NET FLUX↗

CERES ERBE-like Monthly Geographical Averages (ES-4) in HDF (CER_ES4_Aqua-FM4_Edition1-CV)

The ERBE-like Monthly Geographical Averages (ES-4) product contains a month of space and time averaged Clouds and the Earth's Radiant Energy System (CERES) data for a single scanner instrument. The ES-4 is also produced for combinations of scanner instruments. For each observed 2.5-degree spatial region, the daily average, the hourly average over the month, and the overall monthly average of shortwave and longwave fluxes at the Top-of-the-Atmosphere (TOA) from the CERES ES-9 product are spatially nested up from 2.5-degree regions to 5- and 10-degree regions, to 2.5-, 5-, and 10-degree zonal averages, and to global monthly averages. For each nested area, the albedo and net flux are given. For each region, the daily average flux is estimated from an algorithm that uses the available hourly data, scene identification data, and diurnal models. This algorithm is 'like' the algorithm used for the Earth Radiation Budget Experiment (ERBE). The following CERES ES4 data sets are currently available: CER_ES4_FM1+FM2_Edition1 CER_ES4_PFM+FM1+FM2_Edition1 CER_ES4_PFM+FM1+FM2_Edition2 CER_ES4_PFM+FM1_Edition1 CER_ES4_PFM+FM2_Edition1 CER_ES4_TRMM-PFM_Edition1 CER_ES4_TRMM-PFM_Edition2 CER_ES4_Terra-FM1_Edition1 CER_ES4_Terra-FM2_Edition1 CER_ES4_FM1+FM2_Edition2 CER_ES4_Terra-FM1_Edition2 CER_ES4_Terra-FM2_Edition2 CER_ES4_Aqua-FM3_Edition1 CER_ES4_Aqua-FM4_Edition1 CER_ES4_FM1+FM2+FM3+FM4_Edition1 CER_ES4_Aqua-FM3_Edition2 CER_ES4_Aqua-FM4_Edition2 CER_ES4_FM1+FM3_Edition2 CER_ES4_FM1+FM4_Edition2 CER_ES4_PFM+FM1_Edition2 CER_ES4_PFM+FM2_Edition2 CER_ES4_Aqua-FM3_Edition1-CV CER_ES4_Aqua-FM4_Edition1-CV CER_ES4_Terra-FM1_Edition1-CV CER_ES4_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-03-29] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=2.5 degree; Longitude_Resolution=2.5 degree; Horizontal_Resolution_Range=250 km - < 500 km or approximately 2.5 degrees - < 5.0 degrees; Temporal_Resolution=1 month; Temporal_Resolution_Range=Monthly - < Annual].

CLEAR-SKY SHORTWAVE FLUX↗

Forward and Inverse Models for Satellite Remote Sensors using Principal Component Analysis

Satellite remote sensors such as AIRS on Aqua, CrIS on S-NPP, NOAA20 and JPSS-2, IASI on Metop A, B, and C make millions of observations each day with thousands of spectral channels for each observation; this poses challenges for efficiently inversion of the inherently large dataset as needed to retrieve atmospheric and surface properties. This presentation will illustrate the use of Principal Component Analysis (PCA) to speed up radiative transfer forward model calculations and to stabilize the inversion algorithms. A Principal Component-based radiative transfer model (PCRTM) developed at NASA Langley Research Center can simulate top of atmosphere (TOA) radiance or reflectance spectra from 50 cm-1 to 50000 cm-1 (200 m to 0.20 m quickly and accurately. PCRTM demonstrated very high accuracy relative to reference line-by-line radiative transfer models and it saves orders of magnitude computational time. Examples of the PCRTM model developed for hyperspectral sensors such as AIRS, CrIS, IASI, NAST-I, SHIS, CPF, TEMPO, SBG, OMI, and SCIAMACHY will be presented. In addition to using the PCRTM as forward model, the NASA Langley developed inversion algorithm also uses PCA to compress the state vector into a compressed dimension to speed up and stabilize the inversion process. Examples of retrieved atmospheric temperature, water vapor, CO2, CO, CH4, N2O, and O3 profiles, cloud properties (optical depth, size, phase, and height), and surface properties (surface emissivity spectra and skin temperatures) will be presented. This algorithm is being transitioned to the NASA Sounder SIPS and NASA's Goddard Earth Sciences Data and Information Services Center (GES DISC).

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