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At least 253 records · Page 14

In-situ Microwave Brightness Temperature Variability from Ground-based Radiometer Measurements at Dome C in Antarctica Induced by Wind-formed Features

Space-borne microwave radiometers are among the most useful tools to study snow and to collect information on the Antarctic climate. They have several advantages over other remote sensing techniques: high sensitivity to snow properties of interest (temperature, grain size, density), subdaily coverage in the polar regions, and their observations are independent of cloud conditions and solar illumination. Thus, microwave radiometers are widely used to retrieve information over snow-covered regions. For the Antarctic Plateau, many studies presenting retrieval algorithms or numerical simulations have assumed, explicitly or not, that the subpixel-scale heterogeneity is negligible and that the retrieved properties were representative of whole pixels. In this presentation, we investigate the spatial variations of brightness temperature over arange of a few kilometers in the Dome C area (Antarctic Plateau).

Antarctica↗

MISR radiometric camera-by-camera Cloud Mask (MIRCCM_V4)

The MISR instrument consists of nine pushbroom cameras which measure radiance in four spectral bands. Global coverage is achieved in nine days. The cameras are arranged with one camera pointing toward the nadir, four cameras pointing forward and four cameras pointing aftward. It takes 7 minutes for all nine cameras to view the same surface location. The view angles relative to the surface reference ellipsoid, are 0, 26.1, 45.6, 60.0, and 70.5 degrees. The spectral band shapes are nominally gaussian, centered at 443, 555, 670, and 865 nm. The RCCM is derived from the radiance values, and is calculated independently for each camera. Therefore, the amount of apparent cloudiness will vary with view angle, with the oblique view angles generally being more cloudy than the near-nadir ones. Since the RCCM is calculated primarily from the radiance values, it does not work well over snow and ice and will usually confuse clear snow/ice with cloud. It works the best over clear-sky ocean, but other surface types are also of quite good quality. The RCCM product also contains a glint mask for each camera, and this mask is set to true whenever the scattering angles indicate that glint could be possible. This glint mask is not masked out over land; users must do this step themselves. [Temporal_Coverage: Start_Date=2000-02-24; Stop_Date=] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180].

SUN GLINT↗

Use of TEMPO as a Proxy for Hyperspectral Geostationary Ocean Color Measurements from the GeoXO OCX Instrument: Harnessing Machine Learning and Principal Component Techniques for Atmospheric and Glint Correction

Retrievals of ocean color from space are important for better understanding the ocean ecosystem. The launch of atmospheric geostationary hyperspectral sensors such as TEMPO, provides a unique opportunity to examine the diurnal variability in ocean ecology. While TEMPO does not have as high spatial resolution or full spectral coverage as planned coastal ocean sensors such as the Geosynchronous Littoral Imaging and Monitoring Radiometer (GLIMR) or GeoXO Ocean Color instrument (OCX), its hourly measurements provide coverage of regions such as Lake Erie and the Gulf of Mexico at spatial scales of approximately 5 km. These data can be useful for testing new algorithms. We will apply our newly developed machine learning based atmospheric correction approach for ocean color retrievals to TEMPO data. Our approach begins by decomposing measured radiances from hyperspectral sensors into spectral features that describe the scattering and absorption of the atmosphere as well as the underlying surface reflectance. The coefficients of the principal components are then used to train a neural network to predict ocean color properties derived from collocated MODIS/VIIRS physically-based retrievals. This machine learning approach does not rely on radiative transfer modeling, and the use of MODIS/VIIRS data for training accounts for possible calibration b in hyperspectral data. Previously, we applied our approach using blue and UV wavelengths with the Ozone Monitoring Instrument (OMI) and TROPOspheric Monitoring Instrument (TROPOMI) to show that it can estimate ocean color properties in less-than-ideal conditions such as lightly to moderately clouded conditions as well as sun glint and thus improve the spatial coverage of ocean color measurements. TEMPO provides an opportunity to improve on this approach since it will provide collocated measurements at green and red wavelengths that were not available from OMI and TROPOMI and are important particularly for coastal waters. Additionally, our technique can be applied early in the mission and has potential to demonstrate the value of near real time ocean color products that are important for monitoring of harmful algae blooms and other oceanic phenomena.

Zachary Fasnacht↗

Observations of Cirrus Clouds over the Pacific Region by the NASA Multiwavelength Lidar System

As part of the Pacific Exploratory Mission-West Campaign that took place during 16 Sep. - 21 Oct. 1991, lidar measurements were made from the ARC DC-8 aircraft at an altitude of approximately 9 km. This mission provided a unique opportunity to make cirrus cloud observations around the Pacific region covering the latitude range from 5 to 55 deg N and the longitude range from -114 to 120 deg E. Cirrus clouds were observed on most of these flights providing a unique data base. The latitudinal coverage of cirrus observations was further extended to -5 deg S from observations on 30 Jan. 1992 as part of the Airborne Arctic Stratospheric Expedition 2. During this latter mission, aerosol depolarizations at 622 and 1064 nm were also measured. The optical characteristics and statistics related to these cirrus cloud observations are summarized.

Ismail, Syed↗

Advancing Technologies for Climate Observation

Climate research needs Accurate global cloud ice measurements Cloud ice properties are fundamental controlling variables of radiative transfer and precipitation Cost-effective, sensitive instruments for diurnal and wide-swath coverage Mature technology for space remote sensing IceCube objectivesDevelop and validate a flight-qualified 883 GHz receiver for future use in ice cloud radiometer missions Raise TRL (57) of 883 GHz receiver technology Reduce instrument cost and risk by developing path to space for COTS sub-mm-wave receiver systems Enable remote sensing of global cloud ice with advanced technologies and techniques

radiative transfer↗

Large Aperture Scanning Lidar Based on Holographic Optical Elements

Lidar remote sensing instruments can make a significant contribution to satisfying many of the required measurements of atmospheric and surface parameters for future spaceborne platforms, including topographic altimeters, atmospheric profiles of, wind, humidity, temperature, trace molecules, aerosols, and clouds. It is highly desirable to have wide measurement swaths for rapid coverage rather than just the narrow ribbon of data that is obtained with a nadir only observation. For most applications global coverage is required, and for wind measurements scanning or pointing is required in order to retrieve the full 3-D wind vector from multiple line-of-sight Doppler measurements. Conventional lidar receivers make up a substantial portion of the instrument's size and weight. Wide angle scanning typically requires a large scanning mirror in front of the receiver telescope, or pointing the entire telescope and aft optics assembly, Either of these methods entails the use of large bearings, motors, gearing and their associated electronics. Spaceborne instruments also need reaction wheels to counter the torque applied to the spacecraft by these motions. NASA has developed simplified conical scanning telescopes using Holographic Optical Elements (HOEs) to reduce the size, mass, angular momentum, and cost of scanning lidar systems. NASA has developed two operating lidar systems based on 40 cm diameter HOEs. The first such system, named Prototype Holographic Atmospheric Scanner for Environmental Remote Sensing (PHASERS) was a joint development between NASA Goddard Space Flight Center (GSFC) and the University of Maryland College Park. PHASERS is based on a reflection HOE for use at the doubled Nd:YAG laser wavelength of 532 nm and has recently undergone a number of design changes in a collaborative effort between GSFC and Saint Anselm College in New Hampshire. The next step was to develop IR transmission HOEs for use with the Nd:YAG fundamental in the Holographic Airborne Rotating Lidar Instrument Experiment (HARLIE). The HOE spins like a compact disk in a large ring ball bearing. In an aircraft the HOE faces down, looking out through a window at an angle of 45 degrees off-nadir. The HOE diffracts 85% of the incident 532 nm light into a 160 micron spot at a focal length of 1 meter. HARLIE is a field deployable lidar measuring aerosol, cloud, and boundary layer backscatter for atmospheric research. It has flown several times and is also used from a ground-based trailer in an upward-looking mode. The HOE generates a 45 degree conical scan pattern by rotating at speeds up to 30 rpm. Like PHASERS, the HOE in HARLIE serves both as the laser collimating lens as well as the receiver telescope primary optic. The telescope is coupled to the receiver package via fiber optic. The transmitter is a diode pumped Nd:YAG laser operating at 1064 nm, delivering 1 mJ pulses at a 5 KHz rep-rate. The receiver has a 200 microradian field-of-view and a 0.5 nm optical bandpass. The photon counting data system utilizes a single Geiger-mode silicon avalanche photodiode detector, This new technology has also presented us with new data visualization challenges as well as new measurement techniques. The backscatter data obtained from a stationary (i.e. ground-based) scanning HOE lidar is on the surface of a cone, which when viewed over many consecutive scans can reveal atmospheric motions on this surface over time as the atmosphere advects over the site. In a moving platform such as an airplane or satellite, the data from consecutive scans cover different areas under the flight path, revealing atmospheric structure in 3-dimensions. An example of a visualization of HARLIE ground-based data is presented, showing aerosol backscatter on a 90 degree conical surface generated from one 360 degree scan of the lidar during the HOLO-1 field campaign on the afternoon of 10 March 1999. Higher backscatter levels are rendered as lighter signal against a dark background. Breaking Kelvin-Helmholtz waves are evident on the north side of the scan at an altitude of 10-11 km. Time series of successive scans made at regular intervals render unique views of atmospheric motions, from which vertical profiles of atmospheric wind vectors can be obtained using a unique data analysis approach. Wind vectors obtained from the lidar were compared with co-located radiosonde wind profiles during an intensive operating period in September-October 2000 at the Atmospheric Radiation Measurement Program's Southern Great Plains Central Facility.

Schwemmer, Geary K.↗

Application of physical adsorption thermodynamics to heterogeneous chemistry on polar stratospheric clouds

Laboratory isotherms for the binding of several nonheterogeneously active atmospheric gases and for HCl to water ice are translated into adsorptive equilibrium constants and surface enthalpies. Extrapolation to polar conditions through the Clausius Clapeyron relation yields coverage estimates below the percent level for N2, Ar, CO2, and CO, suggesting that the crystal faces of type II stratospheric cloud particles may be regarded as clean with respect to these species. For HCl, and perhaps HF and HNO3, estimates rise to several percent, and the adsorbed layer may offer acid or proton sources alternate to the bulk solid for heterogeneous reactions with stratospheric nitrates. Measurements are lacking for many key atmospheric molecules on water ice, and almost entirely for nitric acid trihydrate as substrate. Adsorptive equilibria enter into gas to particle mass flux descriptions, and the binding energy determines rates for desorption of, and encounter between, potential surface reactants.

Elliott, Scott↗

Archive Management of NASA Earth Observation Data to Support Cloud Analysis

NASA collects, processes and distributes petabytes of Earth Observation (EO) data from satellites, aircraft, in situ instruments and model output, with an order of magnitude increase expected by 2024. Cloud-based web object storage (WOS) of these data can simplify the execution of such an increase. More importantly, it can also facilitate user analysis of those volumes by making the data available to the massively parallel computing power in the cloud. However, storing EO data in cloud WOS has a ripple effect throughout the NASA archive system with unexpected challenges and opportunities. One challenge is modifying data servicing software (such as Web Coverage Service servers) to access and subset data that are no longer on a directly accessible file system, but rather in cloud WOS. Opportunities include refactoring of the archive software to a cloud-native architecture; virtualizing data products by computing on demand; and reorganizing data to be more analysis-friendly.

Lynnes, Christopher↗

Archive Management of NASA Earth Observation Data to Support Cloud Analysis

NASA collects, processes and distributes petabytes of Earth Observation (EO) data from satellites, aircraft, in situ instruments and model output, with an order of magnitude increase expected by 2024. Cloud-based web object storage (WOS) of these data can simplify the execution of such an increase. More importantly, it can also facilitate user analysis of those volumes by making the data available to the massively parallel computing power in the cloud. However, storing EO data in cloud WOS has a ripple effect throughout the NASA archive system with unexpected challenges and opportunities. One challenge is modifying data servicing software (such as Web Coverage Service servers) to access and subset data that are no longer on a directly accessible file system, but rather in cloud WOS. Opportunities include refactoring of the archive software to a cloud-native architecture; virtualizing data products by computing on demand; and reorganizing data to be more analysis-friendly. Reviewed by Mark McInerney ESDIS Deputy Project Manager.

Lynnes, Christopher↗

Changes in Cirrus Cloudiness and their Relationship to Contrails

Condensation trails, or contrails, formed in the wake of high-altitude aircraft have long been suspected of causing the formation of additional cirrus cloud cover. More cirrus is possible because 10 - 20% of the atmosphere at typical commercial flight altitudes is clear but ice-saturated. Since they can affect the radiation budget like natural cirrus clouds of equivalent optical depth and microphysical properties, contrail -generated cirrus clouds are another potential source of anthropogenic influence on climate. Initial estimates of contrail radiative forcing (CRF) were based on linear contrail coverage and optical depths derived from a limited number of satellite observations. Assuming that such estimates are accurate, they can be considered as the minimum possible CRF because contrails often develop into cirrus clouds unrecognizable as contrails. These anthropogenic cirrus are not likely to be identified as contrails from satellites and would, therefore, not contribute to estimates of contrail coverage. The mean lifetime and coverage of spreading contrails relative to linear contrails are needed to fully assess the climatic effect of contrails, but are difficult to measure directly. However, the maximum possible impact can be estimated using the relative trends in cirrus coverage over regions with and without air traffic. In this paper, the upper bound of CRF is derived by first computing the change in cirrus coverage over areas with heavy air traffic relative to that over the remainder of the globe assuming that the difference between the two trends is due solely to contrails. This difference is normalized to the corresponding linear contrail coverage for the same regions to obtain an average spreading factor. The maximum contrail-cirrus coverage, estimated as the product of the spreading factor and the linear contrail coverage, is then used in the radiative model to estimate the maximum potential CRF for current air traffic.

Minnis, Patrick↗

CERES Monthly Gridded Single Satellite TOA and Surfaces/Clouds (SFC) data in HDF (CER_SFC_Terra-FM2-MODIS_Edition2B)

The Monthly Gridded TOA/Surface Fluxes and Clouds (SFC) 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 SFC is also produced for combinations of scanner instruments. All instantaneous shortwave, longwave, and window fluxes at the Top-of-the-Atmosphere (TOA) and surface from the CERES SSF product for a month are sorted by 1-degree spatial regions and by the local hour of observation. The mean of the instantaneous fluxes for a given region-hour bin is determined and recorded on the SFC along with other flux statistics and scene information. These average fluxes are given for both clear-sky and total-sky scenes. The regional cloud properties are column averaged and are included on the SFC. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2003-10-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=100] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

CLOUD INFRARED EMISSIVITY↗

CERES Monthly Gridded Single Satellite TOA and Surfaces/Clouds (SFC) data in HDF (CER_SFC_Aqua-FM3-MODIS_Edition2A)

The Monthly Gridded TOA/Surface Fluxes and Clouds (SFC) 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 SFC is also produced for combinations of scanner instruments. All instantaneous shortwave, longwave, and window fluxes at the Top-of-the-Atmosphere (TOA) and surface from the CERES SSF product for a month are sorted by 1-degree spatial regions and by the local hour of observation. The mean of the instantaneous fluxes for a given region-hour bin is determined and recorded on the SFC along with other flux statistics and scene information. These average fluxes are given for both clear-sky and total-sky scenes. The regional cloud properties are column averaged and are included on the SFC. [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=100] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

CLOUD INFRARED EMISSIVITY↗

CERES Monthly Gridded Single Satellite TOA and Surfaces/Clouds (SFC) data in HDF (CER_SFC_Aqua-FM4-MODIS_Edition2A)

The Monthly Gridded TOA/Surface Fluxes and Clouds (SFC) 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 SFC is also produced for combinations of scanner instruments. All instantaneous shortwave, longwave, and window fluxes at the Top-of-the-Atmosphere (TOA) and surface from the CERES SSF product for a month are sorted by 1-degree spatial regions and by the local hour of observation. The mean of the instantaneous fluxes for a given region-hour bin is determined and recorded on the SFC along with other flux statistics and scene information. These average fluxes are given for both clear-sky and total-sky scenes. The regional cloud properties are column averaged and are included on the SFC. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-03-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=100] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

CLOUD INFRARED EMISSIVITY↗

In Situ and Lidar Observations of Tropopause Subvisible Cirrus Clouds During TC4

During the Tropical Composition, Clouds, and Climate Coupling (TC4) experiment in July-August 2007, the NASA WB-57F and ER-2 aircraft made coordinated flights through a tropopause subvisible cirrus (SVC) layer off the Pacific Coast of Central America. The ER-2 aircraft was equipped with a remote sensing payload that included the cloud physics lidar (CPL). The WB-57F payload included cloud microphysical and trace gas measurements, and the aircraft made four vertical profiles through the SVC layer shortly after the ER-2 flew over. The in situ and remotely sensed data are used to quantify the meteorological and microphysical properties of the SVC layer, and these data are compared to the limited set of SVC measurements that have previously been made. It is found that the layer encountered was particularly tenuous, with optical depths (tau) between about 10(exp -4) and 10(exp -3). From the in situ and other meteorological data, radiative heating rate perturbations of approx.0.05-0.1 K/day are calculated. These heating rates are smaller than previous estimates for tropopause SVC, consistent with the smaller tau in the present study. Coverage statistics based on CPL data from other TC4 flights indicate that this cloud was not an outlier among the sampled population. SVC with properties similar to the one presented here are below the detection limit of space \based lidars such as CALIPSO, and a comparison with the TC4 statistics suggests that a majority (>50%) of tropopause SVC (with tau < 0.01) could be unaccounted for in studies using CALIPSO data.

Davis, Sean↗

CERES Monthly Gridded Single Satellite Fluxes and Clouds (FSW) in HDF (CER_FSW_TRMM-PFM-VIRS_Beta1)

The Monthly Gridded Radiative Fluxes and Clouds (FSW) 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 FSW is also produced for combinations of scanner instruments. All instantaneous fluxes from the CERES CRS product for a month are sorted by 1-degree spatial regions and by the Universal Time (UT) hour of observation. The mean of the instantaneous fluxes for a given region-hour bin is determined and recorded on the FSW along with other flux statistics and scene information. The mean adjusted fluxes at the four atmospheric levels defined by CRS are also included for both clear-sky and total-sky scenes. In addition, four cloud height categories are defined by dividing the atmosphere into four intervals with boundaries at the surface, 700-, 500-, 300-hPa, and the Top-of-the-Atmosphere (TOA). The cloud layers from CRS are put into one of the cloud height categories and averaged over the region. The cloud properties are also column averaged and included on the FSW. [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=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 month; Temporal_Resolution_Range=Monthly - < Annual].

CLOUD OVERLAP↗

CERES) Monthly Gridded Single Satellite Fluxes and Clouds (FSW) in HDF (CER_FSW_Terra-FM2-MODIS_Edition2C)

The Monthly Gridded Radiative Fluxes and Clouds (FSW) 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 FSW is also produced for combinations of scanner instruments. All instantaneous fluxes from the CERES CRS product for a month are sorted by 1-degree spatial regions and by the Universal Time (UT) hour of observation. The mean of the instantaneous fluxes for a given region-hour bin is determined and recorded on the FSW along with other flux statistics and scene information. The mean adjusted fluxes at the four atmospheric levels defined by CRS are also included for both clear-sky and total-sky scenes. In addition, four cloud height categories are defined by dividing the atmosphere into four intervals with boundaries at the surface, 700-, 500-, 300-hPa, and the Top-of-the-Atmosphere (TOA). The cloud layers from CRS are put into one of the cloud height categories and averaged over the region. The cloud properties are also column averaged and included on the FSW. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2001-10-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 month; Temporal_Resolution_Range=Monthly - < Annual].

CLOUD OVERLAP↗

Assessment of Cloud Fraction Derived from a New Geostationary Satellite Cloud Retrieval Algorithm for CERES and Progress Towards Cross-platform Continuity

For over two decades The Clouds and the Earth’s Radiant Energy System (CERES) project has produced long-term records of top-of-atmosphere (TOA) and surface irradiances for detecting changes in the Earth’s radiation budget and advancing understanding of how clouds contribute to those changes. Accurate characterization of the spatial and temporal distributions of clouds are a critical component for producing CERES datasets. The CERES Cloud Working Group (CWG) derives cloud properties from both geostationary (GEO) and low-Earth orbit (LEO) satellite sensors in order to provide complete global coverage at hourly temporal resolution. However, the use of multiple sensors to provide this spatiotemporal coverage throughout a long-term record presents some challenges, because the various sensors generally have different spectral band characteristics (e.g., spectral band width and response) and spatial resolution. These differences can result in spatial artifacts at the coverage boundary between two sensors or temporal artifacts when one sensor replaces another in the record. For the upcoming Edition 5 release of CERES products, the CWG is developing cloud retrieval algorithms which utilize only spectral bands common to most modern passive satellite radiometers and account for differences in spectral width and response. The goal with this approach is to provide global cloud properties for CERES with greater cross-platform consistency than the previous Edition 4 products and thus mitigate artifacts which are evident at the interface of two sensors. This study focuses on retrieval of total cloud fraction from various GEO sensors, and we use Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) observations to assess the accuracy of total cloud fraction derived from the various sensors. The Edition 5 cloud mask algorithm depends on estimates of cloud-free TOA spectral radiances to differentiate clear and cloudy conditions, and CALIOP is used to assess the accuracy of those estimates when cloud-free conditions are indeed observed.

CALIOP↗

CERES Monthly Gridded Single Satellite TOA and Surfaces/Clouds(SFC) data in HDF (CER_SFC_Aqua-FM3-MODIS_Edition1B)

The Monthly Gridded TOA/Surface Fluxes and Clouds (SFC) 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 SFC is also produced for combinations of scanner instruments. All instantaneous shortwave, longwave, and window fluxes at the Top-of-the-Atmosphere (TOA) and surface from the CERES SSF product for a month are sorted by 1-degree spatial regions and by the local hour of observation. The mean of the instantaneous fluxes for a given region-hour bin is determined and recorded on the SFC along with other flux statistics and scene information. These average fluxes are given for both clear-sky and total-sky scenes. The regional cloud properties are column averaged and are included on the SFC. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1998-01-01; Stop_Date=2005-03-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=100] [Data_Resolution: Latitude_Resolution=1 degree; Longitude_Resolution=1 degree; Horizontal_Resolution_Range=100 km - < 250 km or approximately 1 degree - < 2.5 degrees; Temporal_Resolution=1 hour; Temporal_Resolution_Range=Hourly - < Daily].

CLEAR-SKY ALBEDO↗