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NLDAS Forcing Data L4 Monthly 0.125 x 0.125 degree V001
nasa-test-0.demo.socrata.com | Last Updated 2015-07-19T08:29:14.000ZThis data set contains the forcing data for Phase 1 of the North American Land Data Assimilation System (NLDAS-1). The data are in 1/8th degree grid spacing and range from Aug. 1996 to Dec. 2007. The temporal resolution is monthly. The file format is WMO GRIB-1. The NLDAS-1 monthly forcing data, containing 17 variables, are generated from the NLDAS-1 hourly forcing data. Brief description about the NLDAS-1 hourly forcing data can be found from the GCMD DIF for GES_DISC_NLDAS_FOR0125_H_V001 at http://gcmd.gsfc.nasa.gov/getdif.htm?GES_DISC_NLDAS_FOR0125_H_V001. The data set applies a user-defined parameter table to indicate the contents and parameter number. The GRIBTAB file (http://disc.sci.gsfc.nasa.gov/hydrology/grib_tabs/gribtab_NLDAS_FOR_monthly.001.txt) shows a list of parameters for this data set, along with their Product Definition Section (PDS) IDs and units. The variables, DLWRFsfc, DSWRFsfc, PRESsfc, SPFH2m, TMP2m, UGRD10m, and VGRD10m, are the monthly average from 00Z01 of month to 23:59Zlastdayofmonth. The variables, BRTMPsfc and CAPEsfc, are the monthly average from 00Z01 of month to 23:59Zlastdayofmonth, except if any hour has an undefined value of -9999, then do not include the hour in the monthly average. The variables, PARsfc and RGOESsfc, are the monthly average from 00Z01 of month to 23:59Zlastdayofmonth, except if any hour has an undefined value of -9999, then reassign the variable as zero and include the hour in the monthly average. The variables, ACPCPsfc, APCPsfc, PEDASsfc, and PRDARsfc, are the monthly accumulation from 00Z01 of month to 23:59Zlastdayofmonth. However, the ACPCPsfc is actually the sum of the (ACPCPsfc/PEDASsfc)*APCPsfc from each hour, where the ratio of (ACPCPsfc/PEDASsfc) is the fraction of convective precipitation from EDAS, and then multiplied by the APCPsfc to get the convective precipitation. For PRDARsfc accumulation, if hourly PRDARsfc is undefined or negative, fill the hour with a zero value. The last variable, RSWRFsfc, is the monthly average from 00Z01 of month to 23:59Zlastdayofmonth, except represents the monthly average of the hourly "blend" of the DSWRFsfc from EDAS and RGOESsfc from GEOS. The blend algorithm is that, for each hour, the RGOESsfc from GEOS is used for all the grid points where it is available, but for where it is not available, the DSWRFsfc from EDAS is used. Because the spatial extent/availability of GEOS varies from hour to hour, this blend is done for hourly data first, and then the monthly average is applied to the hourly blended data. This last variable thus best represents the shortwave radiation flux downwards at the surface that is used in the NLDAS-1 LSMs. More about this blending/supplementation can be found from http://ldas.gsfc.nasa.gov/nldas/NLDAS1forcing.php. For more information, please see the README Document at ftp://hydro1.sci.gsfc.nasa.gov/data/s4pa/NLDAS/README.NLDAS1.pdf.
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GPM Level 3 IMERG Monthly 0.1 x 0.1 degree V03
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T05:01:54.000ZThis Directory Interchange Format (DIF) describes a collection of fields for the GPM Level 3 IMERG *Final* Monthly 0.1 x 0.1 degree V03 (GPM_3IMERGM) at the NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC). The Integrated Multi-satelliE Retrievals for GPM (*IMERG*) is the unified U.S. algorithm that provides the Day-1 multi-satellite precipitation product for the U.S. GPM team. The precipitation estimates from the various precipitation-relevant satellite passive microwave (PMW) sensors comprising the GPM constellation are computed using the 2014 version of the Goddard Profiling Algorithm (GPROF2014), then gridded, intercalibrated to the GPM Combined Instrument product, and combined into half-hourly 0.1°x0.1° fields. These are provided to both the Climate Prediction Center (CPC) Morphing-Kalman Filter (CMORPH-KF) Lagrangian time interpolation scheme and the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks – Cloud Classification System (PERSIANN-CCS) re-calibration scheme. In parallel, CPC assembles the zenith-angle-corrected, intercalibrated “even-odd” geo- IR fields and forward them to PPS for use in the CMORPH-KF Lagrangian time interpolation scheme and the PERSIANN-CCS computation routines. The PERSIANN-CCS estimates are computed (supported by an asynchronous re-calibration cycle) and sent to the CMORPH-KF Lagrangian time interpolation scheme. The CMORPH-KF Lagrangian time interpolation (supported by an asynchronous KF weights updating cycle) uses the PMW and IR estimates to create half-hourly estimates. The IMERG system is run twice in near-real time • “Early” multi-satellite product ~4 hr after observation time and • “Late” multi-satellite product ~12 hr after observation time, and once after the monthly gauge analysis is received • “Final” satellite-gauge product ~2 months after the observation month. The baseline is for the (near-)real-time Early and Late half-hour estimates to be calibrated with climatological coefficients that vary by month and location, while in the Final post-real-time run the multi-satellite half-hour estimates are adjusted so that they sum to a monthly satellite-gauge combination. In all cases the output contains multiple fields that provide information on the input data, selected intermediate fields, and estimation quality. Release document: http://pmm.nasa.gov/sites/default/files/document_files/IMERG_FinalRun_Day1_release_notes.pdf Other key documents: Technical document and acronyms: http://pmm.nasa.gov/sites/default/files/document_files/IMERG_doc.pdf Algorithm Theoretical Basis Document (ATBD): http://pmm.nasa.gov/sites/default/files/document_files/IMERG_ATBD_V4.4.pdf In brief, the input precipitation estimates computed from the various satellite passive microwave sensors are intercalibrated to the GPM Combined Instrument product (because it is presumed to be the best snapshot GPM estimate), then “morphed” and combined with microwave precipitation-calibrated geo-IR fields, and adjusted with monthly surface precipitation gauge analysis data (where available) to provide half-hourly and monthly precipitation estimates on a 0.1° lat./long. grid over the domain 60°N-S. Precipitation phase is diagnosed using analyses of surface temperature, humidity, and pressure. The current period of record is mid-March 2014 to the present (delayed by about 2 months).The Integrated Multi-Satellite Retrievals for GPM (IMERG) algorithm is designed to leverage the international constellation of precipitation-relevant satellites to create a long record of uniformly time/space gridded precipitation estimates for the globe. The algorithm is focused on creating the best estimate at each time step, meaning that it is not a Climate Data Record, although the ideal is as homogenous a record as possible.
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GPM, DPR, GMI Level 3 Combined Precipitation V03
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T05:03:54.000ZThere are uncertainties in the interpretation of data from any one of the instruments (KuPR, KaPR, and GMI). By using data from multiple instruments, further constraints on the solution of precipitation structure improve the final product.The purpose of 3CMB is to give a daily and monthly accumulation of the 2BCMB precipitation product. The 3CMB product is a daily and monthly accumulation of the 2BCMB orbital combined product at two grid sizes, 5 x 5 degrees (G1) and 0.25 x 0.25 degrees (G2). Grid G1 contains the following physical measurements of general interest, among others. Grid G2 contains the same groups, but it is on the ltH x lnH grid and does not have the surface type (st) dimension or the histograms (see dimension definitions below). Below, conditional products represent means based upon precipitating areas only; unconditional products represent means for raining and non-raining areas combined. Probabilities represent the number of raining observations divided by the total number of raining and non-raining observations. precipTotRate (Group in G1)- Conditional mean rate for all precipitation phases (ice, liquid, mixed-phase). * count (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st): Count. * mean (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Mean, mm/h. * stdev (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Standard deviation for the monthly product. Mean of squares for the daily product, mm/h. * hist (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st x bin): Histogram. precipLiqRate (Group in G1) - Conditional mean rate for liquid precipitation. * count (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st): Count. * mean (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Mean, mm/h. * stdev (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Standard deviation for the monthly product. Mean of squares for the daily product, mm/h. * hist (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st x bin): Histogram. precipTotWaterContent (Group in G1) - Conditional mean water content for all precipitation phases. * count (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st): Count. * mean (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Mean, g/m3. * stdev (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Standard deviation for the monthly product. Mean of squares for the daily product, g/m3. * hist (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st x bin): Histogram. precipLiqWaterContent (Group in G1) - Conditional mean liquid water content. * count (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st): Count. * mean (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Mean, g/m3. * stdev (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Standard deviation for the monthly product. Mean of squares for the daily product, g/m3. * hist (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st x bin): Histogram. precipTotDm (Group in G1) - Conditional mass-weighted mean particle diameter. * count (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st): Count. * mean (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Mean, mm. * stdev (4-byte float, array size: ltL x lnL x ns x hgt x rt x st): Standard deviation for the monthly product. Mean of squares for the daily product, mm. * hist (4-byte integer, array size: ltL x lnL x ns x hgt x rt x st x bin): Histogram. precipTotRateDiurnal (Group in G1) - Conditional mean total surface precipitation rate indexed by local time. * count (4-byte integer, array size: ltL x lnL x ns x st x tim): Count. * mean (4-byte float, array size: ltL x lnL x ns x st x tim): Mean, mm/h. * stdev (4-byte float, array size: ltL x lnL x ns x st x tim): Standard deviation for the monthly product. Mean of squares for the daily product, mm/h. surfPrecipTotRateDiurnalAllObs (4-byte integer, array size: ltL x lnL x ns x st x tim): Number of total observa...
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NLDAS Mosaic Land Surface Model L4 Monthly Climatology 0.125 x 0.125 degree V002
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T04:56:09.000ZThis monthly climatology data set contains a series of land surface parameters simulated from the Mosaic land-surface model (LSM) for Phase 2 of the North American Land Data Assimilation System (NLDAS-2). The data are in 1/8th degree grid spacing. The temporal resolution is monthly, ranging from January to December. The NLDAS-2 monthly climatology data are the monthly data averaged over the thirty years (1980 - 2009) of the NLDAS-2 monthly data. The file format is WMO GRIB-1. Brief description about the NLDAS-2 hourly and monthly Mosaic LSM data can be found from the GCMD DIFs for GES_DISC_NLDAS_MOS0125_H_V002 and GES_DISC_NLDAS_MOS0125_M_V002 at http://gcmd.gsfc.nasa.gov/getdif.htm?GES_DISC_NLDAS_MOS0125_H_V002 and http://gcmd.gsfc.nasa.gov/getdif.htm?GES_DISC_NLDAS_MOS0125_M_V002. Details about the NLDAS-2 configuration of the Mosaic LSM can be found in Xia et al. (2012). The NLDAS-2 Mosaic model monthly climatology data set contains thirty-seven fields. The data set applies a user-defined parameter table to indicate the contents and parameter number. The GRIBTAB file (http://disc.sci.gsfc.nasa.gov/hydrology/grib_tabs/gribtab_NLDAS_MOS.002.txt) shows a list of parameters for this data set, along with their Product Definition Section (PDS) IDs and units. There are six vertical levels for the Soil Moisture (PDS 086) in the Mosaic GRIB files. For more information, please see the README Document at ftp://hydro1.sci.gsfc.nasa.gov/data/s4pa/NLDAS/README.NLDAS2.pdf or the GrADS ctl file at ftp://hydro1.sci.gsfc.nasa.gov/data/gds/NLDAS/NLDAS_MOS0125_MC.002.ctl.
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NLDAS VIC Land Surface Model L4 Monthly Climatology 0.125 x 0.125 degree V002
nasa-test-0.demo.socrata.com | Last Updated 2015-07-19T08:29:26.000ZAbstract: This data set contains a series of land surface parameters simulated from the VIC land-surface model (LSM) for Phase 2 of the North American Land Data Assimilation System (NLDAS-2). The data are in 1/8th degree grid spacing. The temporal resolution is monthly, ranging from January to December. The file format is WMO GRIB-1. The NLDAS-2 monthly climatology data are the monthly data averaged over the thirty years (1980-2009) of the NLDAS-2 monthly data. Brief description about the NLDAS-2 hourly and monthly VIC LSM data can be found from the GCMD DIFs for GES_DISC_NLDAS_VIC0125_H_V002 and GES_DISC_NLDAS_VIC0125_M_V002 at http://gcmd.gsfc.nasa.gov/getdif.htm?GES_DISC_NLDAS_VIC0125_H_V002 and http://gcmd.gsfc.nasa.gov/getdif.htm?GES_DISC_NLDAS_VIC0125_M_V002. Details about the NLDAS-2 configuration of the VIC LSM can be found in Xia et al. (2012). The version of the VIC model for the NLDAS-2 VIC data available from the NASA GES DISC is VIC-4.0.3; this version of the VIC model is the same as used in Sheffield et al. (2003). The NLDAS-2 VIC monthly climatology data contain forty-three fields. The data set applies a user-defined parameter table to indicate the contents and parameter number. The GRIBTAB file (http://disc.sci.gsfc.nasa.gov/hydrology/grib_tabs/gribtab_NLDAS_VIC.002.txt) shows a list of parameters for this data set, along with their Product Definition Section (PDS) IDs and units. For information about the vertical layers of the Soil Moisture Content (PDS 086), Soil Temperature (PDS 085), and Liquid Soil Moisture Content (PDS 151), please see the README Document at ftp://hydro1.sci.gsfc.nasa.gov/data/s4pa/NLDAS/README.NLDAS2.pdf or the GrADS ctl file at ftp://hydro1.sci.gsfc.nasa.gov/data/gds/NLDAS/NLDAS_VIC0125_MC.002.ctl.
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BUV/Nimbus-04 Ozone (O3) Profile and Total Column Ozone Monthly L3 Global 5.0deg Lat Zones V1
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T05:06:01.000ZThe Solar Backscattered Ultra Violet (SBUV) from Nimbus-4 Level-3 monthly zonal mean (MZM) product (BUVN04L3zm) is derived from the Level-2 retrieved ozone profiles. Ozone retrievals are generated from the v8.6 SBUV algorithm. A Level-3 MZM file computes zonal means covering 5 degree latitude bands for each calendar month. For this product there are 72 months of data from May 1970 through April 1976. There are a total of 36 latitudinal bands, 18 in each hemisphere. Profile data are provided at 21 layers from 1013.25, 639.318, 403.382,254.517, 160.589, 101.325,63.9317, 40.3382, 25.4517, 16.0589, 10.1325, 6.39317,4.03382, 2.54517, 1.60589, 1.01325,0.639317, 0.403382, 0.254517, 0.160589 and 0.101325 hPa (measured at bottom of layer). NOTE: Some profiles have 20 layers and do not report the top most layer. Mixing ratios are reported at 15 layers from 0.5, 0.7, 1.0, 1.5, 2.0, 3.0, 4.0, 5.0, 7.0, 10.0, 15.0, 20.0, 30.0, 40.0 and 50.0 hPa (measured at middle of layer). The MZM product averages retrievals that meet the criteria for a good retrieval as determined by error flags in the Level 2 data. A good retrieval is defined as satisfying the following conditions: 1) Profile Error Flag = 0 or 1 (0 = good retrieval; 1 = solar zenith angle > 84 deg.) 2) Total Error Flags = 0, 1, 2 or 5 (0 = good retrieval; 1 = not used; 2 = solar zenith angle > 84 deg; large discrepancy between profile total and best total ozone) NOTE - Total error flag = 5 is anomalously applied at high latitudes and high solar zenith angle where B-Pair total ozone estimate is not as reliable as profile under these conditions. This error flag may be removed in future version of algorithm. The zonal means computed for each month are screened according to the following statistical criteria: 1) number of good retrievals for the month greater than or equal to 2/3 of the samples for a nominal month. 2) mean latitude of good retrievals less than or equal to 1 degree from center of latitude band. 3) mean time of good retrievals less than or equal to 4 days from center of month (i.e., day = 15)
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SAFARI 2000 Surface Atmospheric Radiative Transfer (SMART), Dry Season 2000
nasa-test-0.demo.socrata.com | Last Updated 2015-07-19T08:43:42.000ZSurface-sensing Measurements for Radiative Transfer (SMART) and Chemical, Optical, and Microphysical Measurements of In-situ Troposphere (COMMIT) consist of a suite of instruments that measure (both in-situ and by remote sensing) parameters that help to characterize, as completely as possible, constituents of the atmosphere at a given location. SMART and COMMIT are mobile systems that can be deployed to locations that exhibit interesting atmospheric phenomena. This allows investigators to participate in coordinated measurement campaigns, such as SAFARI 2000.The SMART instruments were deployed to the Skukuza Airport from August 15 to September 17, 2000 to take part in the SAFARI 2000 Dry Season Aircraft Campaign. The SMART-COMMIT mission is designed to pursue the following goals: Earth Observing System (EOS) validation; innovative investigations; and long-term atmospheric monitoring. The results reported in this data set are for the following instruments deployed and measurements recorded at the Skukuza Airport site within the Kruger National Park: several broadband radiometers, for global, diffuse, direct downward solar irradiance and global infrared downward irradiance; meteorological sensors, for surface air temperature, pressure, relative humidity, and wind; and a Solar Spectral Flux Radiometer (NASA Ames) for spectral solar downward irradiance.
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SBUV2/NOAA-18 Ozone (O3) Profile and Total Column Ozone Monthly L3 Global 5.0deg Lat Zones V1
nasa-test-0.demo.socrata.com | Last Updated 2015-07-19T08:44:52.000ZThe Solar Backscattered Ultra Violet (SBUV) from NOAA-18 Level-3 monthly zonal mean (MZM) product (SBUV2N18L3zm) is derived from the Level-2 retrieved ozone profiles. Ozone retrievals are generated from the v8.6 SBUV algorithm. A Level-3 MZM file computes zonal means covering 5 degree latitude bands for each calendar month. For this product there are 78 months of data from July 2005 through December 2011. There are a total of 36 latitudinal bands, 18 in each hemisphere. Profile data are provided at 21 layers from 1013.25, 639.318, 403.382,254.517, 160.589, 101.325,63.9317, 40.3382, 25.4517, 16.0589, 10.1325, 6.39317,4.03382, 2.54517, 1.60589, 1.01325,0.639317, 0.403382, 0.254517, 0.160589 and 0.101325 hPa (measured at bottom of layer). NOTE: Some profiles have 20 layers and do not report the top most layer. Mixing ratios are reported at 15 layers from 0.5, 0.7, 1.0, 1.5, 2.0, 3.0, 4.0, 5.0, 7.0, 10.0, 15.0, 20.0, 30.0, 40.0 and 50.0 hPa (measured at middle of layer). The MZM product averages retrievals that meet the criteria for a good retrieval as determined by error flags in the Level 2 data. A good retrieval is defined as satisfying the following conditions: 1) Profile Error Flag = 0 or 1 (0 = good retrieval; 1 = solar zenith angle > 84 deg.) 2) Total Error Flags = 0, 1, 2 or 5 (0 = good retrieval; 1 = not used; 2 = solar zenith angle > 84 deg; large discrepancy between profile total and best total ozone) NOTE - Total error flag = 5 is anomalously applied at high latitudes and high solar zenith angle where B-Pair total ozone estimate is not as reliable as profile under these conditions. This error flag may be removed in future version of algorithm. The zonal means computed for each month are screened according to the following statistical criteria: 1) number of good retrievals for the month greater than or equal to 2/3 of the samples for a nominal month. 2) mean latitude of good retrievals less than or equal to 1 degree from center of latitude band. 3) mean time of good retrievals less than or equal to 4 days from center of month (i.e., day = 15)
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TRMM Precipitation Radar (PR) Level 2 Rainfall Rate and Profile Product (TRMM Product 2A25) V7
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T04:52:32.000ZThe TRMM Precipitation Radar (PR), the first of its kind in space, is an electronically scanning radar, operating at 13.8 GHz that measures the 3-D rainfall distribution over both land and ocean, and defines the layer depth of the precipitation. The objectives of 2A25 is to correct for the rain attenuation in measured radar reflectivity and to estimate the instantaneous three-dimensional distribution of rain from the TRMM Precipitation Radar (PR) data. The estimates of attenuation-corrected radar reflectivity factor and rainfall rate are given at each resolution cell of the PR. The estimated near-surface rainfall rate and average rainfall rate between the two pre-defined altitudes (2 and 4 km) are also calculated for each beam position. 2A25 basically uses a hybrid of the Hitschfeld-Bordan method and the surface reference method to estimate the vertical true radar reflectivity (Z) profile. (The hybrid method is described in Iguchi and Meneghini (1994)). The vertical rain profile is then calculated from the estimated true Z profile by using an appropriate Z-R relationship. The attenuation correction is, in principle, based on the surface reference method. This method assumes that the decrease in the apparent surface cross section (delta sigma-zero) is caused by the propagation loss in rain. The coefficient a in the k-Z relationship, k=a Z**b, is adjusted in such a way that the path-integrated attenuation (PIA) estimated from the measured Zm-profile will match the delta sigma-zero. The attenuation correction of Z is carried out by the Hitschfeld-Bordan method with the modified a. Since a is adjusted, this type of surface reference method is called the a-adjustment method. The a-adjustment method assumes that the discrepancy between the PIA estimate from delta sigma-zero and that from the measured Zm-profile can be attributed to the inappropriate choice of a values, which may vary depending on the raindrop size distribution and other conditions. It assumes that the radar is properly calibrated and that the measured Zm has no error. In order to avoid inaccuracies in the attenuation correction when rain is weak, a hybrid of the surface reference method and the Hitschfeld-Bordan method is used (Iguchi and Meneghini, 1994). The PIA is first estimated from the precipitation echo alone. The weight given by the hybrid method to the PIA estimate from the surface reference increases as the attenuation estimate increases. When rain is very weak and the attenuation estimate is small, the PIA estimate from the surface reference is effectively neglected. With the introduction of the hybrid method, the divergence associated with the Hitschfeld-Bordan method is also prevented. One major difference from the method described in the above reference is that, in order to deal with the beam-filling problem, a non-uniformity parameter is introduced and is used to correct the bias in the surface reference arising from the horizontal non-uniformity of rain field within the beam. Since radar echoes from near the surface are contaminated by the mainlobe clutter, the rain estimate at the lowest point in the clutter-free region is given as the near-surface rainfall rate for each angle bin. Spatial coverage is between 38 degrees North and 38 degrees South, owing to the 35 degree inclination of the TRMM satellite. This orbit provides extensive coverage in the tropics and allows each location to be covered at a different local time each day, enabling the analysis of the diurnal cycle of precipitation. There are, in general, 9150 scans along the orbit, with each scan consisting of 49 rays. The scan width is about 220 km. The data are stored in the Hierarchical Data Format (HDF), which includes both core and product specific metadata applicable to the PR measurements. A fi...
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NLDAS Secondary Forcing Data L4 Monthly 0.125 x 0.125 degree V002
nasa-test-0.demo.socrata.com | Last Updated 2015-07-20T04:55:51.000ZThis data set contains the monthly secondary forcing data "File B" for Phase 2 of the North American Land Data Assimilation System (NLDAS-2). The data are in 1/8th degree grid spacing and range from Jan 1979 to the present. The temporal resolution is monthly. The file format is WMO GRIB-1. The NLDAS-2 monthly secondary forcing data were generated from the NLDAS-2 hourly secondary forcing data, as monthly accumulation for precipitation and convective precipitation and monthly average for other variables. Monthly period of each month is from 00Z at start of the month to 23:59Z at end of the month. The one exception to this is the first month (Jan. 1979) that starts from 00Z 02 Jan 1979, except for the monthly accumulated precipitation and convective precipitation that both start from 12Z 01 Jan 1979. Brief description about the NLDAS-2 hourly secondary forcing data can be found from the GCMD DIF for GES_DISC_NLDAS_FORB0125_H_V002 at http://gcmd.gsfc.nasa.gov/getdif.htm?GES_DISC_NLDAS_FORB0125_H_V002. Details about the generation of the NLDAS-2 forcing datasets can be found in Xia et al. (2012). The NLDAS-2 monthly land surface forcing fields are grouped into two GRIB files, "File A" and "File B". "File B" is the secondary (optional) forcing file and contains ten fields. The data set applies a user-defined parameter table to indicate the contents and parameter number. The GRIBTAB file (http://disc.sci.gsfc.nasa.gov/hydrology/grib_tabs/gribtab_NLDAS_FORB_monthly.002.txt) shows a list of parameters for this data set, along with their Product Definition Section (PDS) IDs and units. For more information, please see the README Document at ftp://hydro1.sci.gsfc.nasa.gov/data/s4pa/NLDAS/README.NLDAS2.pdf.