PERSIANN Precipitation Climate Data Record (PERSIANN-CDR) is a daily quasi-global precipitation product for the period of 1982 to the present (note that there is a delay in data availability due to processing and data input availability). The data covers from 60 degrees S to 60 degrees N and 0 degrees to 360 degrees longitude at 0.25 degree spatial resolution. The product is developed using Gridded Satellite (GridSat-B1) IR data that are derived from merging ISCCP B1 IR data, along with GPCP version 2.2.

PERSIANN Precipitation Climate Data Record (PERSIANN-CDR) is a daily quasi-global precipitation product for the period of 1982 to the present (note that there is a delay in data availability due to processing and data input availability). The data covers from 60 degrees S to 60 degrees N and 0 degrees to 360 degrees longitude at 0.25 degree spatial resolution. The product is developed using Gridded Satellite (GridSat-B1) IR data that are derived from merging ISCCP B1 IR data, along with GPCP version 2.2.

NOAA NEXRAD Quantitative Precipitation Estimation (QPE) Climate Data Record (CDR) is created from the Radar Multi-Radar/Multi-Sensor (MRMS) Reanalysis to produce severe weather and precipitation products for improved decision-making capability to improve severe weather forecasts and warnings, hydrology, aviation, and numerical weather prediction. The data cover a time period from 2002-01-01 to 2011-12-31. NOAA's NEXRAD reanalysis consists of two primary components; (1) Severe weather and radar-reflectivity data generation, (2) Quantitative Precipitation Estimate (including associated precipitation variables and merged rain gauge and radar estimation). This document focuses on the second component of NOAA's NEXRAD reanalysis - the Quantitative Precipitation Estimate (QPE). The primary files generated within this data set are radar-only and radar- gauge (ROQPE, GCQPE, and MOS2D) merged precipitation products as well as ancillary information on precipitation type (PRATE and PFLAG) and radar quality (RQIND). The initial data set covers the time period from January 2002 - December 2011. Radar-only reflectivity, Gauge, Precipitation Flag, and Radar Quality Index for 5-minute data at 1km regular grid over CONUS. Radar only Radar-Gauge Quantitative Precipitation Estimates at hourly scale at 1km regular grid over CONUS. MRMS Quantitative Precipitation Estimation (QPE) uses the most advanced radar technologies and provides high-resolution information about precipitation types and amounts for the nation. The data are stored in netCDF version 4.0 files that include the necessary metadata and supplementary data fields. Data set provides information that can be useful for identification of various types of precipitation, estimation of radar reflectivity, recognition of storm patterns, forecasting technologies for rainfall estimation, and associating different phases of precipitation such as hail freezing rain and snow with radar observations.

NOAA NEXRAD Quantitative Precipitation Estimation (QPE) Climate Data Record (CDR) is created from the Radar Multi-Radar/Multi-Sensor (MRMS) Reanalysis to produce severe weather and precipitation products for improved decision-making capability to improve severe weather forecasts and warnings, hydrology, aviation, and numerical weather prediction. The data cover a time period from 2002-01-01 to 2011-12-31. NOAA's NEXRAD reanalysis consists of two primary components; (1) Severe weather and radar-reflectivity data generation, (2) Quantitative Precipitation Estimate (including associated precipitation variables and merged rain gauge and radar estimation). This document focuses on the second component of NOAA's NEXRAD reanalysis - the Quantitative Precipitation Estimate (QPE). The primary files generated within this data set are radar-only and radar- gauge (ROQPE, GCQPE, and MOS2D) merged precipitation products as well as ancillary information on precipitation type (PRATE and PFLAG) and radar quality (RQIND). The initial data set covers the time period from January 2002 - December 2011. Radar-only reflectivity, Gauge, Precipitation Flag, and Radar Quality Index for 5-minute data at 1km regular grid over CONUS. Radar only Radar-Gauge Quantitative Precipitation Estimates at hourly scale at 1km regular grid over CONUS. MRMS Quantitative Precipitation Estimation (QPE) uses the most advanced radar technologies and provides high-resolution information about precipitation types and amounts for the nation. The data are stored in netCDF version 4.0 files that include the necessary metadata and supplementary data fields. Data set provides information that can be useful for identification of various types of precipitation, estimation of radar reflectivity, recognition of storm patterns, forecasting technologies for rainfall estimation, and associating different phases of precipitation such as hail freezing rain and snow with radar observations.

*This version has been superseded by a newer version. It is highly recommended for users to access the current version. Users should only access this superseded version for special cases, such as reproducing studies. If necessary, this version can be accessed by contacting NCEI.* The NOAA Global Surface Temperature Dataset (NOAAGlobalTemp) is a blended product from two independent analysis products: the Extended Reconstructed Sea Surface Temperature (ERSST) analysis and the land surface temperature (LST) analysis using the Global Historical Climatology Network (GHCN) temperature database. The data is merged into a monthly global surface temperature dataset dating back from 1850 to the present. The monthly product output is in gridded (5 degree x 5 degree) and time series formats. The product is used in climate monitoring assessments of near-surface temperatures on a global scale. Changes to the data in version 5.1 included: removing the EOT filtering; filling in data gaps over the polar regions; and extending the beginning data coverage from 1880 to 1850.

The NOAA Global Surface Temperature Dataset (NOAAGlobalTemp) is a monthly global merged land-ocean surface temperature analysis product that is derived from two independent analyses. The first is the Extended Reconstructed Sea Surface Temperature (ERSST) analysis and the second is a land surface air temperature (LSAT) analysis that uses the Global Historical Climatology Network - Monthly (GHCN-M) temperature database. The NOAAGlobalTemp data set contains global surface temperatures in gridded (5° × 5°) and monthly resolution time series (from 1850 to present time) data files. The product is used in climate monitoring assessments of near-surface temperatures on a global scale. This version, v6.0, an updated version to the current operational release v5.1, is implemented by an Artificial Neural Network method to improve the surface temperature reconstruction over the land.

*This version has been superseded by a newer version. It is highly recommended for users to access the current version. Users should only access this superseded version for special cases, such as reproducing studies. If necessary, this version can be accessed by contacting NCEI.* The NOAA Global Surface Temperature Dataset (NOAAGlobalTemp) is derived from two independent analyses: the Extended Reconstructed Sea Surface Temperature (ERSST) analysis and the land surface temperature (LST) analysis using the Global Historical Climatology Network (GHCN) temperature database. The data is merged into a monthly global surface temperature dataset dating back from 1880 to the present, updated monthly, in gridded (5 degree x 5 degree) and time series formats. This data set is used in climate monitoring assessments of near-surface temperatures on a global scale. The changes from version 3.5.4 to version 4.0.0 include an update to the primary input dataset (ERSST) now at version 4.0.0 and GHCN-Monthly now at version 3.3.0. This dataset is formerly known as Merged Land-Ocean Surface Temperature (MLOST).

The NOAA Global Surface Temperature Dataset (NOAAGlobalTemp) is a blended product from two independent analysis products: the Extended Reconstructed Sea Surface Temperature (ERSST) analysis and the land surface temperature (LST) analysis using the Global Historical Climatology Network (GHCN) temperature database. The data is merged into a monthly global surface temperature dataset dating back from 1880 to the present. The monthly product output is in gridded (5 degree x 5 degree) and time series formats. The product is used in climate monitoring assessments of near-surface temperatures on a global scale. The changes from version 4 to version 5 include an update to the primary input datasets: ERSST version 5 (updated from v4), and GHCN-M version 4 (updated from v3.3.3). Version 5 updates also include a new netCDF file format with CF conventions. This dataset is formerly known as Merged Land-Ocean Surface Temperature (MLOST).

The NOAA Global Surface Temperature Dataset (NOAAGlobalTemp) is a blended product from two independent analysis products: the Extended Reconstructed Sea Surface Temperature (ERSST) analysis and the land surface temperature (LST) analysis using the Global Historical Climatology Network (GHCN) temperature database. The data is merged into a monthly global surface temperature dataset dating back from 1850 to the present. The monthly product output is in gridded (5 degree x 5 degree) and time series formats. The product is used in climate monitoring assessments of near-surface temperatures on a global scale. Changes to the data in version 5.1 included: removing the EOT filtering; filling in data gaps over the polar regions; and extending the beginning data coverage from 1880 to 1850.