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At least 811 records · Page 45

Breaking Barriers: Integrating Geo-Leo Aerosol Data with an Open-Source Approach

The scientific community is still examining the novel data from geostationary satellite observations and evaluating methods for effectively fusing the polar observations with various spatial and temporal resolutions. However, the merged data will present a significant ""Big Data"" challenge, including processing, storage, data discoverability, accessibility, and migration within cloud computing environments. We have developed an open-source package to fuse aerosol optical depths (AOD) products from six satellite sensors in the past four years (2019~2023), and this presentation will update our recent progress. Using this Python-based package, we produced a level 3 global (AOD) product in a quarter-degree spatial resolution every half-hour, fusing the Level 2 AOD data with the Dark Target aerosol retrieval algorithm from six satellites: three geostationary (GOES-16/17 and Himawari-8) with high temporal resolution, and three polar orbiting (TERRA/MODIS, AQUA/MODIS, and SNPP-VIIRS) with global coverage. By integrating these observations, the diurnal cycle of global AOD in this fused product can be characterized at local, regional, and global scales. Furthermore, we are committed to openness and transparency by providing our package and its associated functionalities as open-source. Our dedication to adhering to the FAIR, CARE, and TRUST principles ensures that our users can rely on the integrity and ethical standards of our work. For instance of Interoperability, this package fuses remote sensing products on demand into desired temporal and spatial domains. It can be run in a central processing unit (CPU) or a Graphics processing unit (GPU) mode. This package will empower researchers and practitioners to use satellite and sensor data efficiently in various applications and research.

Xiaohua Pan↗

The Prospect for Remote Sensing of Cirrus Clouds with a Submillimeter-Wave Spectrometer

Given the substantial radiative effects of cirrus clouds and the need to validate cirrus cloud mass in climate models, it is important to measure the global distribution of cirrus properties with satellite remote sensing. Existing cirrus remote sensing techniques, such as solar reflectance methods, measure cirrus ice water path (IWP) rather indirectly and with limited accuracy. Submillimeter/wave radiometry is an independent method of cirrus remote sensing based on ice particles scattering the upwelling radiance emitted by the lower atmosphere. A new aircraft instrument, the Far Infrared Sensor for Cirrus (FIRSC), is described. The FIRSC employs a Fourier Transform Spectrometer (FTS). which measures the upwelling radiance across the whole submillimeter region (0.1 1.0-mm wavelength). This wide spectral coverage gives high sensitivity to most cirrus particle sizes and allows accurate determination of the characteristic particle size. Radiative transfer modeling is performed to analyze the capabilities of the submillimeter FTS technique. A linear inversion analysis is done to show that cirrus IWP, particle size, and upper-tropospheric temperature and water vapor may be accurately measured, A nonlinear statistical algorithm is developed using a database of 20000 spectra simulated by randomly varying most relevant cirrus and atmospheric parameters. An empirical orthogonal function analysis reduces the 500-point spectrum (20 - 70/cm) to 15 "pseudo-channels" that are then input to a neural network to retrieve cirrus IWP and median particle diameter. A Monte Carlo accuracy study is performed with simulated spectra having realistic noise. The retrieval errors are low for IWP (rms less than a factor of 1.5) and for particle sizes (rins less than 30%) for IWP greater than 5 g/sq m and a wide range of median particle sizes. This detailed modeling indicates that there is good potential to accurately measure cirrus properties with a submillimeter FTS.

Evans, K. Franklin↗

Archetypal TRMM Radar Profiles Identified Through Cluster Analysis

It is widely held that identifiable 'convective regimes' exist in nature, although precise definitions of these are elusive. Examples include land / Ocean distinctions, break / monsoon beahvior, seasonal differences in the Amazon (SON vs DJF), etc. These regimes are often described by differences in the realized local convective spectra, and measured by various metrics of convective intensity, depth, areal coverage and rainfall amount. Objective regime identification may be valuable in several ways: regimes may serve as natural 'branch points' in satellite retrieval algorithms or data assimilation efforts; one example might be objective identification of regions that 'should' share a similar 2-R relationship. Similarly, objectively defined regimes may provide guidance on optimal siting of ground validation efforts. Objectively defined regimes could also serve as natural (rather than arbitrary geographic) domain 'controls' in studies of convective response to environmental forcing. Quantification of convective vertical structure has traditionally involved parametric study of prescribed quantities thought to be important to convective dynamics: maximum radar reflectivity, cloud top height, 30-35 dBZ echo top height, rain rate, etc. Individually, these parameters are somewhat deficient as their interpretation is often nonunique (the same metric value may signify different physics in different storm realizations). Individual metrics also fail to capture the coherence and interrelationships between vertical levels available in full 3-D radar datasets. An alternative approach is discovery of natural partitions of vertical structure in a globally representative dataset, or 'archetypal' reflectivity profiles. In this study, this is accomplished through cluster analysis of a very large sample (0[107) of TRMM-PR reflectivity columns. Once achieved, the rainconditional and unconditional 'mix' of archetypal profile types in a given location and/or season provides a description of the local convective spectrum which retains vertical structure information. A further cluster analysis of these 'mixes' can identify recurrent convective spectra. These are a first step towards objective identification of convective regimes, and towards answering the question: 'What are the most convectively similar locations in the world?'

Boccippio, Dennis J.↗

Model-Based Estimation of Sampling-Caused Uncertainty in Aerosol Remote Sensing for Climate Research Applications

To evaluate the effect of sampling frequency on the global monthly mean aerosol optical thickness (AOT), we use 6 years of geographical coordinates of Moderate Resolution Imaging Spectroradiometer (MODIS) L2 aerosol data, daily global aerosol fields generated by the Goddard Institute for Space Studies General Circulation Model and the chemical transport models Global Ozone Chemistry Aerosol Radiation and Transport, Spectral Radiationtransport Model for Aerosol Species and Transport Model 5, at a spatial resolution between 1.125 deg × 1.125 deg and 2 deg × 3◦: the analysis is restricted to 60 deg S-60 deg N geographical latitude. We found that, in general, the MODIS coverage causes an underestimate of the global mean AOT over the ocean. The long-term mean absolute monthly difference between all and dark target (DT) pixels was 0.01-0.02 over the ocean and 0.03-0.09 over the land, depending on the model dataset. Negative DT biases peak during boreal summers, reaching 0.07-0.12 (30-45% of the global long-term mean AOT). Addition of the Deep Blue pixels tempers the seasonal dependence of the DT biases and reduces the mean AOT difference over land by 0.01-0.02. These results provide a quantitative measure of the effect the pixel exclusion due to cloud contamination, ocean sun-glint and land type has on the MODIS estimates of the global monthly mean AOT. We also simulate global monthly mean AOT estimates from measurements provided by pixel-wide along-track instruments such as the Aerosol Polarimetry Sensor and the Cloud-Aerosol LiDAR with Orthogonal Polarization. We estimate the probable range of the global AOT standard error for an along-track sensor to be 0.0005-0.0015 (ocean) and 0.0029-0.01 (land) or 0.5-1.2% and 1.1-4% of the corresponding global means. These estimates represent errors due to sampling only and do not include potential retrieval errors. They are smaller than or comparable to the published estimate of 0.01 as being a climatologically significant change in the global mean AOT, suggesting that sampling density is unlikely to limit the use of such instruments for climate applications at least on a global, monthly scale.

long-term variability↗

CERES ERBE-like Instantaneous TOA Estimates (ES-8) in HDF (CER_ES8_Aqua-FM3_Edition1-CV)

The ES-8 archival data product contains a 24-hour, single-satellite, instantaneous view of scanner fluxes at the top-of-atmosphere (TOA) reduced from spacecraft altitude unfiltered radiances using Earth Radiation Budget Experiment (ERBE) scanner Inversion algorithms and the ERBE shortwave (SW) and longwave (LW) Angular Distribution Models (ADMs). The ES-8 also includes the total (TOT), SW, LW, and window (WN) channel radiometric data; SW, LW, and WN unfiltered radiance values; and the ERBE scene identification for each measurement. These data are organized according to the CERES 3.3-second scan into 6.6-second records. As long as there is one valid scanner measurement within a record, the ES-8 record will be generated. The following CERES ES8 data sets are currently available: CER_ES8_TRMM-PFM_Edition1 CER_ES8_TRMM-PFM_Edition2 CER_ES8_TRMM-PFM_Transient-Ops2 CER_ES8_Terra-FM1_Edition1 CER_ES8_Terra-FM2_Edition1 CER_ES8_Terra-FM1_Edition2 CER_ES8_Terra-FM2_Edition2 CER_ES8_Aqua-FM3_Edition1 CER_ES8_Aqua-FM4_Edition1 CER_ES8_Aqua-FM3_Edition2 CER_ES8_Aqua-FM4_Edition2 CER_ES8_Aqua-FM3_Edition1-CV CER_ES8_Aqua-FM4_Edition1-CV CER_ES8_Terra-FM1_Edition1-CV CER_ES8_Terra-FM1_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1997-12-27; Stop_Date=2006-10-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 day; Temporal_Resolution_Range=Daily - < Weekly].

TOTAL FILTERED RADIANCE↗

CERES ERBE-like Monthly Geographical Averages (ES-4) in HDF (CER_ES4_FM1+FM2_Edition2)

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=2002-12-31] [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=1 month; Temporal_Resolution_Range=Monthly - < Annual].

NET FLUX↗

CERES ERBE-like Monthly Geographical Averages (ES-4) in HDF (CER_ES4_FM1+FM3_Edition2)

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=2005-12-31] [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=1 month; Temporal_Resolution_Range=Monthly - < Annual].

CLEAR-SKY ALBEDO↗

CERES ERBE-like Monthly Geographical Averages (ES-4) in HDF (CER_ES4_Terra-FM1_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=2006-09-30] [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].

GEOGRAPHIC SCENE TYPE↗

Seven Years of Observations of Mid-Tropospheric CO2 from the Atmospheric Infrared Sounder

The Atmospheric Infrared Sounder (AIRS) on the EOS Aqua Spacecraft was launched on May 4, 2002. AIRS acquires hyperspectral infrared radiances in the 3.7-15.4 um spectral region with spectral resolution of better than 1200. The AIRS was designed to measure temperature and water vapor profiles and cloud properties for improvement in weather forecast and improved parameterization of climate processes. Currently the AIRS Level 1B Radiance Products are assimilated by NWP centers and have shown considerable forecast improvement. Scientists have also demonstrated accurate retrievals of minor gases from AIRS including Carbon Monoxide, Methane, and Ozone. The excellent sensitivity and stability of the AIRS instrument has recently allowed the AIRS team to successfully retrieve Carbon Dioxide (CO2) concentrations in the mid-troposphere (8-10 km) with a horizontal resolution of 100 km and accuracy of 1-2 ppm. The AIRS retrieves over 15,000 measurements per day and can achieve full global coverage in 30 days. The AIRS CO2 accuracy has been validated against a variety of aircraft measurements in the mid-troposphere and upward looking interferometers. Findings from the AIRS data include higher than expected variability in the mid-troposphere, the presence of a belt of CO2 in the southern hemisphere, and numerous observations of atmospheric circulation including the effects of El Nino/La Nina on the CO2 concentrations in the mid-troposphere. The full mid-tropospheric AIRS CO2 data set is now available at the NASA GES/DISC for almost eight years since AIRS has been operational.

carbon dioxide↗

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↗

Heterodyne Receiver Requirements for the Single Aperture Far-Infrared (SAFIR) Observatory

In the next few years, work will commence in earnest on the development of technology for the next generation large cryogenic far-infrared telescope: the Single Aperture Far- Infrared (SAFIR) Observatory. SAFIR's science goals are driven by the fact that youngest stages of almost all phenomena in the universe are shrouded in absorption by cool dust, resulting in the energy being emitted primarily in the far-infrared. The earliest stages of star formation, when gas and dust clouds are collapsing and planets forming, can only be observed in the far-infrared. Spectral diagnostics in the far-infrared are typically quite narrow (approx. 1 km/s) and require high sensitivity to detect them. SAFIR is a 10 m-class telescope designed for cryogenic operation at L2, removing all sources of thermal emission from the telescope and atmosphere. Despite its limited collecting area and angular resolution as compared to the ALMA interferometer, its potential for covering the entire far-infrared band cannot be matched by any ground-based or airborne observatory. This places a new challenge on heterodyne receivers: broad frequency coverage. The ideal mixer would be able to detect frequencies over several octaves (e.g., 0.6 THz - 12 THz) with near quantum-limited performance at all frequencies. In contrast to ground-based observatories, it may not be necessary to strive for high instantaneous bandwidth, as direct detection spectroscopy is preferable for bandwidths of Delta v/ v greater than or equal to 10(exp -4) (e.g., 1 GHz at 10 THz). We consider likely directions for technology development for heterodyne receivers for SAFIR.

Benford, Dominic J.↗

Biomass Estimation from Simulated GEDI, ICESat-2 and NISAR Across Environmental Gradients in Sonoma County, California

Estimates of the magnitude and distribution of aboveground carbon in Earth’s forests remain uncertain, yet knowledge of forest carbon content at a global scale is critical for forest management in support of climate mitigation. In light of this knowledge gap, several upcoming spaceborne missions aim to map forest aboveground biomass, and many new biomass products are expected from these datasets. As these new missions host different technologies, each with relative strengths and weaknesses for biomass retrieval, as well as different spatial resolutions, consistently comparing or combining biomass estimates from these new datasets will be challenging. This paper presents a demonstration of an inter-comparison of biomass estimates from simulations of three NASA missions (GEDI, ICESat-2 and NISAR) over Sonoma county in California, USA. We use a high resolution, locally calibrated airborne lidar map as our reference dataset, and emphasize the importance of considering uncertainties in both reference maps and spaceborne estimates when conducting biomass product validation. GEDI and ICESat-2 were simulated from airborne lidar point clouds, while UAVSAR’s L-band backscatter was used as a proxy for NISAR. To estimate biomass for the lidar missions we used GEDI’s footprint-level biomass algorithms, and also adapted these for application to ICESat-2. For UAVSAR, we developed a locally trained biomass model, calibrated against the ALS reference map. Each mission simulation was evaluated in comparison to the local reference map at its native product resolution (25 m, 100m transect, and 1 ha) yielding RMSEs of 57%, 75%, and 89% for GEDI, NISAR, and ICESat-2 respectively. RMSE values increased for GEDI’s power beam during simulated daytime conditions (64%), coverage beam during nighttime conditions (72%), and coverage beam daytime conditions (87%). We also test the application of GEDI’s biomass modeling framework for estimation of biomass from ICESat-2, and fine that ICESat-2 yields reasonable biomass estimates, particularly in relatively short, open canopies. Results suggest that while all three missions will produce datasets useful for biomass mapping, tall, dense canopies such as those found in Sonoma County present the greatest challenges for all three missions, while steep slopes also prove challenging for single-date SAR based biomass retrieval. Our methods provide guidance for the inter-comparison and validation of spaceborne biomass estimates through the use of airborne lidar reference maps, and could be repeated with on-orbit estimates in any area with high quality field plot and ALS data. These methods allow for regional interpretations and filtering of multi-mission biomass estimates toward improved wall-to-wall biomass maps through data fusion.

GEDI↗

CERES ERBE-like Monthly Geographical Averages (ES-4) in HDF (CER_ES4_PFM+FM1_Edition2)

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=2000-03-31] [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=1 month; Temporal_Resolution_Range=Monthly - < Annual].

CLEAR-SKY ALBEDO↗

CERES ERBE-like Monthly Regional Averages (ES-9) in HDF (CER_ES9_TRMM-PFM_Edition1)

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=1998-08-31] [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 ALBEDO↗

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

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=2005-10-31] [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 SOLAR INCIDENCE↗

CERES ERBE-like Monthly Regional Averages (ES-9) in HDF (CER_ES9_FM1+FM2_Edition1)

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=2003-12-31] [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 SOLAR INCIDENCE↗

CERES ERBE-like Monthly Regional Averages (ES-9) in HDF (CER_ES9_PFM+FM1+FM2_Edition1)

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=2000-03-31] [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].

EOSDIS↗

CERES ERBE-like Monthly Regional Averages (ES-9) in HDF (CER_ES9_PFM+FM1+FM2_Edition2)

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=2000-03-31] [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].

NET FLUX↗