The NOAA Monthly U.S. Climate Gridded Dataset (NClimGrid) consists of four climate variables derived from the GHCN-D dataset: maximum temperature, minimum temperature, average temperature and precipitation. Each file provides monthly values in a 5x5 lat/lon grid for the Continental United States. Data is available from 1895 to the present. On an annual basis, approximately one year of "final" nClimGrid will be submitted to replace the initially supplied "preliminary" data for the same time period. Users should be sure to ascertain which level of data is required for their research.

This dataset replaces the previous Time Bias Corrected Divisional Temperature-Precipitation Drought Index. The new divisional data set (NClimDiv) is based on the Global Historical Climatological Network-Daily (GHCN-D) and makes use of several improvements to the previous data set. For the input data, improvements include additional station networks, quality assurance reviews and temperature bias adjustments. Perhaps the most extensive improvement is to the computational approach, which now employs climatologically aided interpolation. This 5km grid based calculation nCLIMGRID helps to address topographic and network variability. This data set is primarily used by the National Oceanic and Atmospheric Administration (NOAA) National Climatic Data Center (NCDC) to issue State of the Climate Reports on a monthly basis. These reports summarize recent temperature and precipitation conditions and long-term trends at a variety of spatial scales, the smallest being the climate division level. Data at the climate division level are aggregated to compute statewide, regional and national snapshots of climate conditions. For CONUS, the period of record is from 1895-present. Derived quantities such as Standardized precipitation Index (SPI), Palmer Drought Indices (PDSI, PHDI, PMDI, and ZNDX) and degree days are also available for the CONUS sites. In March 2015, data for thirteen Alaskan climate divisions were added to the NClimDiv data set. Data for the new Alaskan climate divisions begin in 1925 through the present and are included in all monthly updates. Alaskan climate data include the following elements for divisional and statewide coverage: average temperature, maximum temperature (highs), minimum temperature (lows), and precipitation. The Alaska NClimDiv data were created and updated using similar methodology as that for the CONUS, but with a different approach to establishing the underlying climatology. The Alaska data are built upon the 1971-2000 PRISM averages whereas the CONUS values utilize a base climatology derived from the NClimGrid data set. As of November 2018, NClimDiv includes county data and additional inventory files.

In March 2015, data for thirteen Alaskan climate divisions were added to the NClimDiv data set. Data for the new Alaskan climate divisions begin in 1925 through the present and are included in all monthly updates. Alaskan climate data include the following elements for divisional and statewide coverage: average temperature, maximum temperature (highs), minimum temperature (lows), and precipitation. The Alaska NClimDiv data were created and updated using similar methodology as that for the CONUS, but with a different approach to establishing the underlying climatology. The Alaska data are built upon the 1971-2000 PRISM averages whereas the CONUS values utilize a base climatology derived from the NClimGrid data set. In January 2025, the National Centers for Environmental Information (NCEI) began summarizing the State of the Climate for Hawaii. This was made possible through a collaboration between NCEI and the University of Hawaii/Hawaii Climate Data Portal and completes a long-standing gap in NCEI's ability to characterize the State of the Climate for all 50 states. NCEI maintains monthly statewide, divisional, and gridded average temperature, maximum temperatures (highs), minimum temperature (lows) and precipitation data for Hawaii over the period 1991-2025. As of November 2018, NClimDiv includes county data and additional inventory files In March 2015, data for thirteen Alaskan climate divisions were added to the NClimDiv data set. Data for the new Alaskan climate divisions begin in 1925 through the present and are included in all monthly updates. Alaskan climate data include the following elements for divisional and statewide coverage: average temperature, maximum temperature (highs), minimum temperature (lows), and precipitation. The Alaska NClimDiv data were created and updated using similar methodology as that for the CONUS, but with a different approach to establishing the underlying climatology. The Alaska data are built upon the 1971-2000 PRISM averages whereas the CONUS values utilize a base climatology derived from the NClimGrid data set. As of November 2018, NClimDiv includes county data and additional inventory files.

The U.S. Daily Gridded Climate Normals Datasets are derived from the nClimGrid-Daily Dataset newly produced by the NOAA National Centers for Environmental Information (NOAA NCEI). Climatologically aided interpolation was used to transform an extensive set of station temperature and precipitation values into grids at a high spatial resolution of 1/24° latitude/longitude, or approximately 5 km. The values for each individual grid cell change smoothly from day-to-day through the application of the same methods used to generate daily normals for observation stations. The averages of all daily gridded temperature normals are constrained by a harmonic fit to equal the monthly gridded. A moving window averaging technique is used to generate smooth daily gridded precipitation normals which are then also adjusted by month so that the sum of the days would equal the monthly gridded normals. Daily gridded climate normals are calculated for total precipitation, and maximum, minimum and average temperature for the conterminous U.S

The U.S. Daily Gridded Climate Normals Datasets are derived from the nClimGrid-Daily Dataset newly produced by the NOAA National Centers for Environmental Information (NOAA NCEI). Climatologically aided interpolation was used to transform an extensive set of station temperature and precipitation values into grids at a high spatial resolution of 1/24° latitude/longitude, or approximately 5 km. The values for each individual grid cell change smoothly from day-to-day through the application of the same methods used to generate daily normals for observation stations. The averages of all daily gridded temperature normals are constrained by a harmonic fit to equal the monthly gridded. A moving window averaging technique is used to generate smooth daily gridded precipitation normals which are then also adjusted by month so that the sum of the days would equal the monthly gridded normals. Daily gridded climate normals are calculated for total precipitation, and maximum, minimum and average temperature for the conterminous U.S

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.