2024-03-29T09:50:20.889Zhttps://cmr.earthdata.nasa.gov/opensearch/collections.atomCMRechodev@echo.nasa.govECHO dataset metadataSearch parameters: satellite => CloudSat boundingBox => startTime => endTime => 181011https://cmr.earthdata.nasa.gov/opensearch/collections.atom?uid=C1214586924-SCIOPSCMRechodev@echo.nasa.govCloudSat ECMWF-AUX product version 008[Source:CloudSat Standard Data Products Handbook, Cooperative Institute for Research in the Atmosphere, Colorado State University]
This product is built from ECMWF global data that are provided to the DPC via ftp transfer, four times per day. The ECMWF-AUX data set is an intermediate product that contains ECMWF state variable data interpolated to each CloudSat vetical bin. These data are required for input to the 2B-GEOPROF, 2B-CLDCLASS, 2B-TAU, and 2B-FLXHR algorithms.
View the complete documentation in the CloudSat Standard Data Products
Handbook: Please see Related URL LinksC1214586924-SCIOPS2006-06-02T00:00:00.000Z/CloudSat ECMWF-AUX product version 008CloudSat_ECMWF-AUX008SCIOPSCOLOSTATE/CIRA/CPCCOLOSTATE/CIRA/CPCCARTESIAN-90 -180 90 180falsefalsefalsefalsefalsefalsefalsefalse3.36336org.geoss.geoss_data-coretruehttps://cmr.earthdata.nasa.gov/opensearch/collections.atom?uid=C1214591609-SCIOPSCMRechodev@echo.nasa.govCloudsat Level 2 Fluxes and Heating Rates Product[Source: "Cloudsat Level 2 Fluxes and Heating Rates Product Process Description and Interface Control Document" ]
This document provides an overview of the 2B-FLXHR flux and heating rate algorithm for CloudSat. The objective of the algorithm is to make use of liquid and ice water content estimates from the CloudSat Profiling Radar (CPR) to produce estimates of broadband fluxes and heating rates for each radar profile. For a particular radar profile, upwelling and down- welling longwave and shortwave flux profiles are calculated at discrete levels of the atmosphere. Corresponding heating rates are inferred from these fluxes. In order to perform these calculations, the algorithm makes use of a combination of atmospheric state variables obtained from ECMWF reanalysis data, profiles of cloud ice and liquid water content obtained from the CloudSat 2B-LWC and 2B-IWC products, and surface albedos obtained from seasonally-varying maps of surface reflectance properties. The remainder of this document describes the algorithm in greater detail. Section 2 provides an overview of the theoretical basis upon which the algorithm is built. Sections 3 and 4 describe inputs to the algorithm and detail its implementation. The output format for the product is summarized in Section 5 while instructions for the operator can be found in Section 6.
View complete document:
http://www.cloudsat.cira.colostate.edu/C1214591609-SCIOPS2006-06-02T00:00:00.000Z/Cloudsat Level 2 Fluxes and Heating Rates ProductCloudsat_2B-FLXHR007SCIOPSCOLOSTATE/CIRA/CPCCOLOSTATE/CIRA/CPCNACARTESIAN-90 -180 90 180falsefalsefalsefalsefalsefalsefalsefalse3.36336org.geoss.geoss_data-coretruehttps://cmr.earthdata.nasa.gov/opensearch/collections.atom?uid=C1214594669-SCIOPSCMRechodev@echo.nasa.govCloudSat Level 2-C Precipitation Column Algorithm[Source: CloudSat Level 2-C Precipitation Column Algorithm Product Process Description and Interface Control Document, http://www.cloudsat.cira.colostate.edu]
The basis of the work is outlined in Haynes et al. [1], and all quantitative and mathematical details may be obtained from this source. An overview of the physical basis of the retrieval follows.
The algorithm makes use of path integrated attenuation (PIA) due to hydrometeors as a geophysical measurement. The method depends on the well-behaved relationship between the backscatter cross section of the ocean surface, σ0 , and the wind speed, V at the ocean surface. Higher wind speeds cause greater roughening of the ocean surface, resulting in increased scattering of microwave radiation away from the radar receiver and a lower resulting surface backscatter cross section. The sea surface temperature (SST) of the ocean surface also influences the backscatter cross section through variation of the index of refraction. A database of observations of the surface backscatter cross section under clear-sky conditions, σclr , provides a background reference for the state of the surface when hydrometeors are absent. When cloud or rain is present, the observed backscatter cross section is reduced by hydrometeor attenuation. This reduction allows calculation of PIA given knowledge of the wind speed at the ocean surface (derived from a numerical model) and, to a lesser extent, the SST [2].
The unattenuated radar reflectivity, Zu , near the surface is closely related to the presence of rain; the higher Zu the more likely precipitation is occurring. Zu is the sum of the measured reflectivity, the PIA, and a component due to gaseous attenuation, G (determined from the ECMWF-AUX temperature and moisture profile).
Multiple scattering within the precipitating column can be significant for rainfall exceeding a few millimeter per hour [3], so Monte Carlo modeling is used to simulate the relationship between rainfall and observed PIA for various vertical profiles of precipitation. A model of the melting layer is also incorporated into the Monte Carlo calculations to better represent the transition from snow to rain. This melting layer model aims to treat the attenuating characteristics of melting snowflakes. The model follows snow (modeled through the discrete dipole approximation) falling through a melting layer and melting into rain, assuming a constant lapse rate, Γe , of 6 ◦ C km−1 .
Liquid or mixed precipitation layers are considered to extend to the height of the lowest continuous cloud layer, HCT L , as determined from the 2B-GEOPROF cloud mask, capped by the height of the freezing level, Hf , from ECMWF-AUX. The effects of purely frozen precipitation on PIA are only considered when a core of 10 dBZ of greater reflectivity extends through the freezing level, Hsig . When such a core is absent, melting is considered to start at the freezing level itself. The combination of HCT L , Hf , and Hsig allow determination of the total depth of all precipitation, Dtot , and liquid precipitation, Dliq .C1214594669-SCIOPS1970-01-01T00:00:00.000Z/CloudSat Level 2-C Precipitation Column AlgorithmCloudsat_2C-PRECIP-COLUMNNot providedSCIOPSCOLOSTATE/CIRA/CPCCOLOSTATE/CIRA/CPCCARTESIAN-90 -180 90 180falsefalsefalsefalsefalsefalsefalsefalse3.36336org.geoss.geoss_data-coretruehttps://cmr.earthdata.nasa.gov/opensearch/collections.atom?uid=C1214586890-SCIOPSCMRechodev@echo.nasa.govCloudSat MODIS-AUX product version 007The MODIS-AUX data set is an intermediate product that contains a subset of ancillary MODIS radiance and cloud mask data that overlaps and surrounds each CloudSat cloud profiling radar (CPR) footprint. The MODIS-AUX footprint will be a 3-km (along-track) by 5-km (across-track) box of MODIS data centered on each CloudSat profile location. Input data are obtained from the 1B-CPR and AN-MODIS products, and the MODIS-AUX data are used as input to the 2B-GEOPROF, 2B-CLDCLASS, 2B-TAU, and 2B-FLXHR algorithms in the CloudSat data processing system.
View the complete documentation in the CloudSat Standard Data Products
Handbook: Please see Related URL Links
[Source:CloudSat Standard Data Products Handbook, Cooperative
Institute for Research in the Atmosphere, Colorado State
University]C1214586890-SCIOPS2006-06-02T00:00:00.000Z/CloudSat MODIS-AUX product version 007CloudSat_MODIS_AUXVersion 007SCIOPSCOLOSTATE/CIRA/CPCCOLOSTATE/CIRA/CPCCARTESIAN-90 -180 90 180falsefalsefalsefalsefalsefalsefalsefalse3.36336org.geoss.geoss_data-coretruehttps://cmr.earthdata.nasa.gov/opensearch/collections.atom?uid=C1214586907-SCIOPSCMRechodev@echo.nasa.govCloudSat Radar-Online Combined Water Content (2B-CWC-RO product version 008)[Source:CloudSat Standard Data Products Handbook, Cooperative
Institute for Research in the Atmosphere, Colorado State
University]
This product is calculated using data from the CloudSat Profiling Radar and other sources, including radiance measurements from the MODIS instrument on the Aqua platform, with which CloudSat will orbit in close formation. In practice, 2B-CWC simply obtains visible optical depth from the 2B-TAU product. A radar-only version of the retrieval has been implemented for use during the nighttime half of CloudSat's orbit when visible optical depth information will not be available. For continuity, the radar-only retrieval will also be run during the daytime half of the orbit.
View the complete documentation in the CloudSat Standard Data Products
Handbook: Please see Related URL LinksC1214586907-SCIOPS2006-06-02T00:00:00.000Z/CloudSat Radar-Online Combined Water Content (2B-CWC-RO product version 008)CloudSat_2B-CWC-RO8SCIOPSCOLOSTATE/CIRA/CPCCOLOSTATE/CIRA/CPCCARTESIAN-90 -180 90 180falsefalsefalsefalsefalsefalsefalsefalse3.36336org.geoss.geoss_data-coretruehttps://cmr.earthdata.nasa.gov/opensearch/collections.atom?uid=C1979701486-GHRC_DAACCMRechodev@echo.nasa.govGEOSSEOSDISGPM Ground Validation Satellite Overpasses IFloodS V1The GPM Ground Validation Satellite Overpasses IFloodS dataset contains plots of satellite overpass paths centered over eastern Iowa during the Global Precipitation Measurement (GPM) mission Iowa Flood Studies (IFloodS) field campaign. The campaign aimed to collect detailed measurements of precipitation at the Earth’s surface while simultaneously collecting data from satellites passing overhead. This dataset consists of paths for Earth observation satellites operating during the campaign: NASA’s AQUA, TERRA, and CloudSat satellites; NOAA’s NOAA-15, NOAA-16, NOAA-17, NOAA-18, and Suomi NPP satellites; Europe’s MetOp-A and MetOp-B satellites, and DMSP’s F-15, F-16, F-17, and F-18 satellites. The satellite overpasses are provided as PNG plot images and as KML files with which the paths can be imported and viewed in Google Earth.2022-05-09T16:16:02.000ZC1979701486-GHRC_DAAC2013-04-01T00:21:15.000Z/2013-06-30T23:10:41.000ZGPM Ground Validation Satellite Overpasses IFloodS V1gpmsatpaifld1GHRC_DAACNASA/MSFC/GHRCNASA/MSFC/GHRC1ACARTESIAN38.41 -98.12 47.39 -85.86truefalsefalsefalsefalsefalsefalsetrue0.65org.ceos.wgiss.cwic.granules.prodgov.nasa.eosdistruehttps://cmr.earthdata.nasa.gov/opensearch/collections.atom?uid=C1214155395-SCIOPSCMRechodev@echo.nasa.govICARE Cloud-Aerosol-Water-Radiation Interactions Data Products[Source: ICARE Home Page, http://www.icare.univ-lille1.fr/ ]
The ICARE Thematic Center was created in 2003 by CNES, CNRS, the Nord-Pas-De-Calais Regional Council, and the University of Lille, to provide various services to support the research community in fields related to atmospheric research, such as aerosols, clouds, radiation, water cycle, and their interactions. ICARE's initial emphasis is the production and distribution of remote sensing data derived from Earth observation missions from CNES, NASA, and EUMETSAT. One of ICARE's main components is the Data and Services Center, located at the University of Lille, which develops science algorithms and production codes, building on the expertise from various partner Science Computing Facilities, and distributes products to the users community.C1214155395-SCIOPS1970-01-01T00:00:00.000Z/ICARE Cloud-Aerosol-Water-Radiation Interactions Data ProductsICARE_PARENT_DATANot providedSCIOPSICAREICARECARTESIAN-90 -180 90 180falsefalsefalsefalsefalsefalsefalsefalse0.78000005https://cmr.earthdata.nasa.gov/opensearch/collections.atom?uid=C1214591444-SCIOPSCMRechodev@echo.nasa.govLevel 2B Radar-Visible Optical Depth Cloud Water Content (2B-CWC-RVOD)[Source: Algorithm Process Description Document for data product 2B-CWC-RVOD, CloudSat Data Processing Center, https://www.cloudsat.cira.colostate.edu/data-products/2b-cwc-rvod]
The CloudSat Radar-Visible Optical Depth Cloud Water Content Product (2B-CWC-RVOD) contains retrieved estimates of cloud liquid and ice water content, effective radius, and related quantities for each radar profile measured by the Cloud Profiling Radar on CloudSat. Retrievals are performed separately for the liquid and ice phases; the two sets of results are then combined in a simple way to obtain a composite profile that is consistent with the input measurements. This radar-visible optical depth product uses a combination of measured radar reflectivity factor (from the CloudSat 2B-GEOPROF product) together with estimates of visible optical dpeth (from the CloudSat 2B-TAU product) to constrain the cloud retrievals more tightly than in the radar-only product (2B-CWC-RO) and presumably yielding more accurate results. However, retrievals of visible optical depth are difficult or impossible in many cases, due to the complexity of the targets and the simplifying assumptions made necessary by the data volumes associated with an operational satellite. Rather than leaving a number of gaps in the RVOD product, a radar-onlly (RO) retrieval is performed for those profiles where visible optical depth information is not available (as indicated by status flags in 2B-TAU). (Retrieved profiles based on an RO retrieval are indicated by a non-zero value of bit 7 in RVOD_CWC_status: “Bad TAU input”.) The RVOD product is therefore a composite of RVOD and RO retrieval solutions in which each retrieved profile uses the maximum information available through the CloudSat data system. For users wanting a more homogenous product, the 2B-CWC-RO product (using radar only) continues to be available.
The CWC algorithm creates a composite profile from separate ice and liquid water retrievals. Both of these retrievals assume that the radar profile is due to a single phase of water, that is, that the entire profile consists of either liquid or ice, but not both. The resulting separate liquid and ice profiles are then combined using a simple scheme based on temperature as reported by an ECMWF model. While the combination algorithm results in a mixture of ice and liquid phases over that part of the vertical profile that has the proper temperature range, the user should be aware that the retrieval does not attempt to retrieve mixed-phase cloud properties directly. Improvements are in the planning stages to better handle the retrieval of mixed-phase cloud.
This document describes the algorithms that have been implemented in Release 4 (R04) of the
2B-CWC-RVOD product (algorithm version 5.1). For each radar profile, the algorithms will
- Examine the cloud mask in 2B-GEOPROF to determine which bins in the column contain cloud,
- Examine the 2B-CLDCLASS product to determine if any cloudy bins have an undetermined or invalid cloud type (indicating a problematic profile),
- Examine the 2B-TAU product to determine if the visible optical depth retrieval is bad, missing, or failed to converge,
- Assign a priori values to the liquid and ice particle size distribution parameters in each cloudy bin based on climatology, temperature, or other criteria,
- Using the a priori values and radar measurements from 2B-GEOPROF (and visible optical depth from 2B-TAU, if available), retrieve liquid and ice particle size distribution parameters for each
cloudy bin. Derive effective radius, water content, and related quantities from the retrieved size
distributions for both liquid and ice phases, together with associated uncertainties,
- Create a composite profile by using the retrieved ice properties at temperatures colder than
−20◦ C, the retrieved liquid properties at temperatures warmer than 0◦ C, and a linear combination of the two in intermediate temperatures,C1214591444-SCIOPS2006-06-02T00:00:00.000Z/Level 2B Radar-Visible Optical Depth Cloud Water Content (2B-CWC-RVOD)Cloudsat_2B-CWC-RVOD008SCIOPSCOLOSTATE/CIRA/CPCCOLOSTATE/CIRA/CPCNot ProvidedCARTESIAN-90 -180 90 180falsefalsefalsefalsefalsefalsefalsefalse1.5288org.geoss.geoss_data-coretrue