In 2024, Louisiana recorded 71.25 inches of precipitation. This was the highest precipitation within the 48 contiguous U.S. states that year. On the other hand, Nevada was the driest state, with only 9.53 inches of precipitation recorded. Precipitation across the United States Not only did Louisiana record the largest precipitation volume in 2024, but it also registered the highest precipitation anomaly that year, around 14.36 inches above the 1901-2000 annual average. In fact, over the last decade, rainfall across the United States was generally higher than the average recorded for the 20th century. Meanwhile, the driest states were located in the country's southwestern region, an area which – according to experts – will become even drier and warmer in the future. How does global warming affect precipitation patterns? Rising temperatures on Earth lead to increased evaporation which – ultimately – results in more precipitation. Since 1900, the volume of precipitation in the United States has increased at an average rate of 0.20 inches per decade. Nevertheless, the effects of climate change on precipitation can vary depending on the location. For instance, climate change can alter wind patterns and ocean currents, causing certain areas to experience reduced precipitation. Furthermore, even if precipitation increases, it does not necessarily increase the water availability for human consumption, which might eventually lead to drought conditions.

In 2024, the United States saw some 31.6 inches of precipitation. The main forms of precipitation include hail, drizzle, rain, sleet, and snow. Since the turn of the century, 2012 was the driest year on record with an annual precipitation of 27.5 inches. Regional disparities in rainfall Louisiana emerged as the wettest state in the U.S. in 2024, recording a staggering 71.25 inches (1.8 meters) of precipitation—nearly 14.4 inches (ca. 37 centimeters) above its historical average. In stark contrast, Nevada received only 9.53 inches (ca. 24 centimeters), underscoring the vast differences in rainfall across the nation. These extremes illustrate the uneven distribution of precipitation, with the southwestern states experiencing increasingly dry conditions that experts predict will worsen in the coming years. Drought concerns persist Drought remains a significant concern in many parts of the country. The Palmer Drought Severity Index (PDSI) for the contiguous United States stood at -3.39 in December 2024, indicating moderate to severe drought conditions. This reading follows three years of generally negative PDSI values, with the most extreme drought recorded in December 2023 at -3.93.

Hourly Precipitation Data (HPD) is digital data set DSI-3240, archived at the National Climatic Data Center (NCDC). The primary source of data for this file is approximately 5,500 US National Weather Service (NWS), Federal Aviation Administration (FAA), and cooperative observer stations in the United States of America, Puerto Rico, the US Virgin Islands, and various Pacific Islands. The earliest data dates vary considerably by state and region: Maine, Pennsylvania, and Texas have data since 1900. The western Pacific region that includes Guam, American Samoa, Marshall Islands, Micronesia, and Palau have data since 1978. Other states and regions have earliest dates between those extremes. The latest data in all states and regions is from the present day. The major parameter in DSI-3240 is precipitation amounts, which are measurements of hourly or daily precipitation accumulation. Accumulation was for longer periods of time if for any reason the rain gauge was out of service or no observer was present. DSI 3240_01 contains data grouped by state; DSI 3240_02 contains data grouped by year.

U.S. 15 Minute Precipitation Data is digital data set DSI-3260, archived at the National Climatic Data Center (NCDC). This is precipitation data. The primary source of data for this file is approximately 2,000 mostly U.S. weather stations operated or managed by the U.S. National Weather Service. Stations are primary, secondary, or cooperative observer sites that have the capability to measure precipitation at 15 minute intervals. This dataset contains 15-minute precipitation data (reported 4 times per hour, if precip occurs) for U.S. stations along with selected non-U.S. stations in U.S. territories and associated nations. It includes major city locations and many small town locations. Daily total precipitation is also included as part of the data record. NCDC has in archive data from most states as far back as 1970 or 1971, and continuing to the present day. The major parameter is precipitation amounts at 15 minute intervals, when precipitation actually occurs.

These daily weather records were compiled from a subset of stations in the Global Historical Climatological Network (GHCN)-Daily dataset. A weather record is considered broken if the value exceeds the maximum (or minimum) value recorded for an eligible station. A weather record is considered tied if the value is the same as the maximum (or minimum) value recorded for an eligible station. Daily weather parameters include Highest Min/Max Temperature, Lowest Min/Max Temperature, Highest Precipitation, Highest Snowfall and Highest Snow Depth. All stations meet defined eligibility criteria. For this application, a station is defined as the complete daily weather records at a particular location, having a unique identifier in the GHCN-Daily dataset. For a station to be considered for any weather parameter, it must have a minimum of 30 years of data with more than 182 days complete in each year. This is effectively a 30-year record of service requirement, but allows for inclusion of some stations which routinely shut down during certain seasons. Small station moves, such as a move from one property to an adjacent property, may occur within a station history. However, larger moves, such as a station moving from downtown to the city airport, generally result in the commissioning of a new station identifier. This tool treats each of these histories as a different station. In this way, it does not thread the separate histories into one record for a city. Records Timescales are characterized in three ways. In order of increasing noteworthiness, they are Daily Records, Monthly Records and All Time Records. For a given station, Daily Records refers to the specific calendar day: (e.g., the value recorded on March 7th compared to every other March 7th). Monthly Records exceed all values observed within the specified month (e.g., the value recorded on March 7th compared to all values recorded in every March). All-Time Records exceed the record of all observations, for any date, in a station's period of record. The Date Range and Location features are used to define the time and location ranges which are of interest to the user. For example, selecting a date range of March 1, 2012 through March 15, 2012 will return a list of records broken or tied on those 15 days. The Location Category and Country menus allow the user to define the geographic extent of the records of interest. For example, selecting Oklahoma will narrow the returned list of records to those that occurred in the state of Oklahoma, USA. The number of records broken for several recent periods is summarized in the table and updated daily. Due to late-arriving data, the number of recent records is likely underrepresented in all categories, but the ratio of records (warm to cold, for example) should be a fairly strong estimate of a final outcome. There are many more precipitation stations than temperature stations, so the raw number of precipitation records will likely exceed the number of temperature records in most climatic situations.

Hawaii has an incredible diversity of climate zones packed into a small collection of Islands. Understanding climate and climate change over Hawaii therefore requires accounting for the topographic complexity ... behind these climate zones. Meanwhile, Alaska is one of the coldest regions in the world inhabited by humans, and has experienced the largest temperature increase in the United States, with temperatures that are projected to rise during this century. However, despite being a hotspot for climate change, little is known about future changes in natural hazards across this region. We have created an ensemble downscaled climate product for both these states. The dataset includes daily temperature and daily precipitation over the period 1981-2100, sampling from 22 global climate models, using 8 statistical downscaling techniques, and a future climate forcing scenarios represented by 4 Shared Socioeconomic Pathways (SSPs). This community dataset will permit investigations into the sources of climate uncertainty and climate change uncertainty at the local scale. They may also be used for climate risk assessment across a range of societal sectors. A primary reason for their development by the authors is to drive hydrologic models and explore questions of hydrologic change in these underexplored regions. These data will be described in a paper to be submitted to the journal Scientific Data.

The average temperature in the contiguous United States reached 55.5 degrees Fahrenheit (13 degrees Celsius) in 2024, approximately 3.5 degrees Fahrenheit higher than the 20th-century average. These levels represented a record since measurements started in 1895. Monthly average temperatures in the U.S. were also indicative of this trend. Temperatures and emissions are on the rise The rise in temperatures since 1975 is similar to the increase in carbon dioxide emissions in the U.S. Although CO₂ emissions in recent years were lower than when they peaked in 2007, they were still generally higher than levels recorded before 1990. Carbon dioxide is a greenhouse gas and is the main driver of climate change. Extreme weather Scientists worldwide have found links between the rise in temperatures and changing weather patterns. Extreme weather in the U.S. has resulted in natural disasters such as hurricanes and extreme heat waves becoming more likely. Economic damage caused by extreme temperatures in the U.S. has amounted to hundreds of billions of U.S. dollars over the past few decades.

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.

ERA5 is the fifth generation ECMWF reanalysis for the global climate and weather for the past 8 decades. Data is available from 1940 onwards. ERA5 replaces the ERA-Interim reanalysis. Reanalysis combines model data with observations from across the world into a globally complete and consistent dataset using the laws of physics. This principle, called data assimilation, is based on the method used by numerical weather prediction centres, where every so many hours (12 hours at ECMWF) a previous forecast is combined with newly available observations in an optimal way to produce a new best estimate of the state of the atmosphere, called analysis, from which an updated, improved forecast is issued. Reanalysis works in the same way, but at reduced resolution to allow for the provision of a dataset spanning back several decades. Reanalysis does not have the constraint of issuing timely forecasts, so there is more time to collect observations, and when going further back in time, to allow for the ingestion of improved versions of the original observations, which all benefit the quality of the reanalysis product. ERA5 provides hourly estimates for a large number of atmospheric, ocean-wave and land-surface quantities. An uncertainty estimate is sampled by an underlying 10-member ensemble at three-hourly intervals. Ensemble mean and spread have been pre-computed for convenience. Such uncertainty estimates are closely related to the information content of the available observing system which has evolved considerably over time. They also indicate flow-dependent sensitive areas. To facilitate many climate applications, monthly-mean averages have been pre-calculated too, though monthly means are not available for the ensemble mean and spread. ERA5 is updated daily with a latency of about 5 days. In case that serious flaws are detected in this early release (called ERA5T), this data could be different from the final release 2 to 3 months later. In case that this occurs users are notified. The data set presented here is a regridded subset of the full ERA5 data set on native resolution. It is online on spinning disk, which should ensure fast and easy access. It should satisfy the requirements for most common applications. An overview of all ERA5 datasets can be found in this article. Information on access to ERA5 data on native resolution is provided in these guidelines. Data has been regridded to a regular lat-lon grid of 0.25 degrees for the reanalysis and 0.5 degrees for the uncertainty estimate (0.5 and 1 degree respectively for ocean waves). There are four main sub sets: hourly and monthly products, both on pressure levels (upper air fields) and single levels (atmospheric, ocean-wave and land surface quantities). The present entry is "ERA5 hourly data on single levels from 1940 to present".

This dataset contains quasi-dynamically downscaled climate data from 8 global climate models from the CMIP5 archive. The data were downscaled using the Intermediate Complexity Atmospheric Research (ICAR Gutmann et al., ... 2016) model after bias correcting the GCM three dimensional atmospheric data to match the ERA-interim reanalysis climatology (Dee et al., 2011). ICAR was configured with the Thompson microphysics, a simple PBL parameterization based on YSU, the RRTMG longwave radiation and an empirical shortwave radiation scheme, the Noah-MP land surface model, the WRF-Lake model, the BMJ cumulus parameterization, and used linear mountain wave theory for upper level wind structures combined with an iterative scheme to remove vertical motion at the model top. The output from ICAR was adjusted to match the climatological statistics of the Livneh et al. (2015) observational dataset.

Soils vary widely in their ability to retain or drain water. The rate at which water drains into the soil has a direct effect on the amount and timing of runoff, what crops can be grown, and where wetlands form. In soils with low drainage rates water will pond on the soil's surface.This layer summarizes soil drainage rates in eight classes:Excessively drained: Water is removed very rapidly. The occurrence of internal free water commonly is very rare or very deep. The soils are commonly coarse-textured and have very high hydraulic conductivity or are very shallow.Somewhat excessively drained: Water is removed from the soil rapidly. Internal free water occurrence commonly is very rare or very deep. The soils are commonly coarse-textured and have high saturated hydraulic conductivity or are very shallow.Well drained: Water is removed from the soil readily but not rapidly. Internal free water occurrence commonly is deep or very deep; annual duration is not specified. Water is available to plants throughout most of the growing season in humid regions. Wetness does not inhibit growth of roots for significant periods during most growing seasons. The soils are mainly free of the deep to redoximorphic features that are related to wetness.Moderately well drained: Water is removed from the soil somewhat slowly during some periods of the year. Internal free water occurrence commonly is moderately deep and transitory through permanent. The soils are wet for only a short time within the rooting depth during the growing season, but long enough that most mesophytic crops are affected. They commonly have a moderately low or lower saturated hydraulic conductivity in a layer within the upper 1 m, periodically receive high rainfall, or both.Somewhat poorly drained: Water is removed slowly so that the soil is wet at a shallow depth for significant periods during the growing season. The occurrence of internal free water commonly is shallow to moderately deep and transitory to permanent. Wetness markedly restricts the growth of mesophytic crops, unless artificial drainage is provided. The soils commonly have one or more of the following characteristics: low or very low saturated hydraulic conductivity, a high water table, additional water from seepage, or nearly continuous rainfall.Poorly drained: Water is removed so slowly that the soil is wet at shallow depths periodically during the growing season or remains wet for long periods. The occurrence of internal free water is shallow or very shallow and common or persistent. Free water is commonly at or near the surface long enough during the growing season so that most mesophytic crops cannot be grown, unless the soil is artificially drained. The soil, however, is not continuously wet directly below plow-depth. Free water at shallow depth is usually present. This water table is commonly the result of low or very low saturated hydraulic conductivity of nearly continuous rainfall, or of a combination of these.Very poorly drained: Water is removed from the soil so slowly that free water remains at or very near the ground surface during much of the growing season. The occurrence of internal free water is very shallow and persistent or permanent. Unless the soil is artificially drained, most mesophytic crops cannot be grown. The soils are commonly level or depressed and frequently ponded. If rainfall is high or nearly continuous, slope gradients may be greater.Subaqueous Soils: Free water is above the soil surface. Internal free water occurrence is permanent, and there is a positive water potential at the soil surface for more than 21 hours of each day. The soils have a peraquic soil moisture regime.For more information on the classifications see the Soil Survey Manual section on Soil Water.Dataset SummaryPhenomenon Mapped: Drainage Class of SoilsGeographic Extent: Contiguous United States, Alaska, Hawaii, Puerto Rico, Guam, US Virgin Islands, Northern Mariana Islands, Republic of Palau, Republic of the Marshall Islands, Federated States of Micronesia, and American Samoa.Projection: Web Mercator Auxiliary SphereData Coordinate System: WKID 5070 USA Contiguous Albers Equal Area Conic USGS version (contiguous US, Puerto Rico, US Virgin Islands), WKID 3338 WGS 1984 Albers (Alaska), WKID 4326 WGS 1984 Decimal Degrees (Guam, Republic of the Marshall Islands, Northern Mariana Islands, Republic of Palau, Federated States of Micronesia, American Samoa, and Hawaii).Units: ClassesCell Size: 30 metersSource Type: DiscretePixel Type: Unsigned integerSource: Natural Resources Conservation ServiceUpdate Frequency: AnnualPublication Date: December 2024Data from the gNATSGO database was used to create the layer for the for the contiguous United States and Alaska. The remaining areas were created with the gSSURGO database (Hawaii, Guam, Puerto Rico, the U.S. Virgin Islands, Northern Marianas Islands, Palau, Federated States of Micronesia, Republic of the Marshall Islands, and American Samoa).This layer is derived from the 30m (contiguous U.S.) and 10m rasters (all other regions) produced by the Natural Resources Conservation Service (NRCS). The value for drainage class is derived from the gSSURGO map unit aggregated attribute table field Drainage Class - Dominant Condition (drclassdcd).What can you do with this layer?This layer is suitable for both visualization and analysis across the ArcGIS system. This layer can be combined with your data and other layers from the ArcGIS Living Atlas of the World in ArcGIS Online and ArcGIS Pro to create powerful web maps that can be used alone or in a story map or other application.Because this layer is part of the ArcGIS Living Atlas of the World it is easy to add to your map:In ArcGIS Online, you can add this layer to a map by selecting Add then Browse Living Atlas Layers. A window will open. Type "drainage class" in the search box and browse to the layer. Select the layer then click Add to Map.In ArcGIS Pro, open a map and select Add Data from the Map Tab. Select Data at the top of the drop down menu. The Add Data dialog box will open on the left side of the box, expand Portal if necessary, then select Living Atlas. Type "drainage class" in the search box, browse to the layer then click OK.In ArcGIS Pro you can use the built-in raster functions or create your own to create custom extracts of the data. Imagery layers provide fast, powerful inputs to geoprocessing tools, models, or Python scripts in Pro.The ArcGIS Living Atlas of the World provides an easy way to explore many other beautiful and authoritative maps on hundreds of topics like this one.Questions?Please leave a comment below if you have a question about this layer, and we will get back to you as soon as possible.

The ARS Water Data Base is a collection of precipitation and streamflow data from small agricultural watersheds in the United States. This national archive of variable time-series readings for precipitation and runoff contains sufficient detail to reconstruct storm hydrographs and hyetographs. There are currently about 14,000 station years of data stored in the data base. Watersheds used as study areas range from 0.2 hectare (0.5 acres) to 12,400 square kilometers (4,786 square miles). Raingage networks range from one station per watershed to over 200 stations. The period of record for individual watersheds vary from 1 to 50 years. Some watersheds have been in continuous operation since the mid 1930's. Resources in this dataset:Resource Title: FORMAT INFORMATION FOR VARIOUS RECORD TYPES. File Name: format.txtResource Description: Format information identifying fields and their length will be included in this file for all files except those ending with the extension .txt TYPES OF FILES As indicated in the previous section data has been stored by location number in the form, LXX where XX is the location number. In each subdirectory, there will be various files using the following naming conventions: Runoff data: WSXXX.zip where XXX is the watershed number assigned by the WDC. This number may or may not correspond to a naming convention used in common literature. Rainfall data: RGXXXXXX.zip where XXXXXX is the rain gage station identification. Maximum-minimum daily air temperature: MMTXXXXX.zip where XXXXX is the watershed number assigned by the WDC. Ancillary text files: NOTXXXXX.txt where XXXXX is the watershed number assigned by the WDC. These files will contain textual information including latitude-longitude, name commonly used in literature, acreage, most commonly-associated rain gage(s) (if known by the WDC), a list of all rain gages on or near the watershed. Land use, topography, and soils as known by the WDC. Topographic maps of the watersheds: MAPXXXXX.zip where XXXXX is the location/watershed number assigned by the WDC. Map files are binary TIF files. NOT ALL FILE TYPES MAY BE AVAILABLE FOR SPECIFIC WATERSHEDS. Data files are still being compiled and translated into a form viable for this archive. Please bear with us while we grow.Resource Title: Data Inventory - watersheds. File Name: inventor.txtResource Description: Watersheds at which records of runoff were being collected by the Agricultural Research Service. Variables: Study Location & Number of Rain Gages1; Name; Lat.; Long; Number; Pub. Code; Record Began; Land Use2; Area (Acres); Types of Data3Resource Title: Information about the ARS Water Database. File Name: README.txtResource Title: INDEX TO INFORMATION ON EXPERIMENTAL AGRICULTURAL WATERSHEDS. File Name: INDEX.TXTResource Description: This report includes identification information on all watersheds operated by the ARS. Only some of these are included in the ARS Water Data Base. They are so indicated in the column titled ARS Water Data Base. Other watersheds will not have data available here or through the Water Data Center. This index is particularly important since it relates watershed names with the indexing system used by the Water Data Center. Each location has been assigned a number. The data for that location will be stored in a sub-directory coded as LXX where XX is the location number. The index also indicates the watershed number used by the WDC. Data for a particular watershed will be stored in a compressed file named WSXXXXX.zip where XXXXX is the watershed number assigned by the WDC. Although not included in the index, rain gage information will be stored in compressed files named RGXXXXXX.zip where XXXXXX is a 6-character identification of the rain gage station. The Index also provides information such as latitude-longitude for each of the watersheds, acreage, the period-of-record for each acreage. Multiple entries for a particular watershed will either indicate that the acreage designated for the watershed changed or there was a break in operations of the watershed. Resource Title: ARS Water Database files. File Name: ars_water.zipResource Description: USING THIS SYSTEM Before downloading huge amounts of data from the ARS Water Data Base, you should first review the text files included in this directory. They include: INDEX OF ARS EXPERIMENTAL WATERSHEDS: index.txt This report includes identification information on all watersheds operated by the ARS. Only some of these are included in the ARS Water Data Base. They are so indicated in the column titled ARS Water Data Base. Other watersheds will not have data available here or through the Water Data Center. This index is particularly important since it relates watershed names with the indexing system used by the Water Data Center. Each location has been assigned a number. The data for that location will be stored in a sub-directory coded as LXX where XX is the location number. The index also indicates the watershed number used by the WDC. Data for a particular watershed will be stored in a compressed file named WSXXXXX.zip where XXXXX is the watershed number assigned by the WDC. Although not included in the index, rain gage information will be stored in compressed files named RGXXXXXX.zip where XXXXXX is a 6-character identification of the rain gage station. The Index also provides information such as latitude-longitude for each of the watersheds, acreage, the period-of-record for each acreage. Multiple entries for a particular watershed will either indicate that the acreage designated for the watershed changed or there was a break in operations of the watershed. STATION TABLE FOR THE ARS WATER DATA BASE: station.txt This report indicates the period of record for each recording station represented in the ARS Water Data Base. The data for a particular station will be stored in a single compressed file. FORMAT INFORMATION FOR VARIOUS RECORD TYPES: format.txt Format information identifying fields and their length will be included in this file for all files except those ending with the extension .txt TYPES OF FILES As indicated in the previous section data has been stored by location number in the form, LXX where XX is the location number. In each subdirectory, there will be various files using the following naming conventions: Runoff data: WSXXX.zip where XXX is the watershed number assigned by the WDC. This number may or may not correspond to a naming convention used in common literature. Rainfall data: RGXXXXXX.zip where XXXXXX is the rain gage station identification. Maximum-minimum daily air temperature: MMTXXXXX.zip where XXXXX is the watershed number assigned by the WDC. Ancillary text files: NOTXXXXX.txt where XXXXX is the watershed number assigned by the WDC. These files will contain textual information including latitude-longitude, name commonly used in literature, acreage, most commonly-associated rain gage(s) (if known by the WDC), a list of all rain gages on or near the watershed. Land use, topography, and soils as known by the WDC. Topographic maps of the watersheds: MAPXXXXX.zip where XXXXX is the location/watershed number assigned by the WDC. Map files are binary TIF files. NOT ALL FILE TYPES MAY BE AVAILABLE FOR SPECIFIC WATERSHEDS. Data files are still being compiled and translated into a form viable for this archive. Please bear with us while we grow.

This dataset consists of Level III weather radar products collected from Next-Generation Radar (NEXRAD) stations located in the contiguous United States, Alaska, Hawaii, U.S. territories and at military base sites. NEXRAD is a network of 160 high-resolution Doppler weather radars operated by the NOAA National Weather Service (NWS), the Federal Aviation Administration (FAA), and the U.S. Air Force (USAF). Doppler radars detect atmospheric precipitation and winds, which allow scientists to track and anticipate weather events, such as rain, ice pellets, snow, hail, and tornadoes, as well as some non-weather objects like birds and insects. NEXRAD stations use the Weather Surveillance Radar - 1988, Doppler (WSR-88D) system. This is a 10 cm wavelength (S-Band) radar that operates at a frequency between 2,700 and 3,000 MHz. The radar system operates in two basic modes: a slow-scanning Clear Air Mode (Mode B) for analyzing air movements when there is little or no precipitation activity in the area, and a Precipitation Mode (Mode A) with a faster scan for tracking active weather. The two modes employ nine Volume Coverage Patterns (VCPs) to adequately sample the atmosphere based on weather conditions. A VCP is a series of 360 degree sweeps of the antenna at pre-determined elevation angles and pulse repetition frequencies completed in a specified period of time. The radar scan times 4.5, 5, 6 or 10 minutes depending on the selected VCP. During 2008, the WSR-88D radars were upgraded to produce increased spatial resolution data, called Super Resolution. The earlier Legacy Resolution data provides radar reflectivity at 1.0 degree azimuthal by 1 km range gate resolution to a range of 460 km, and Doppler velocity and spectrum width at 1.0 degree azimuthal by 250 m range gate resolution to a range of 230 km. The upgraded Super Resolution data provides radar reflectivity at 0.5 degree azimuthal by 250 m range gate resolution to a range of 460 km, and Doppler velocity and spectrum width at 0.5 degree azimuthal by 250 m range gate resolution to a range of 300 km. Super resolution makes a compromise of slightly decreased noise reduction for a large gain in resolution. In 2010, the deployment of the Dual Polarization (Dual Pol) capability to NEXRAD sites began with the first operational Dual Pol radar in May 2011. Dual Pol radar capability adds vertical polarization to the previous horizontal radar waves, in order to more accurately discern the return signal. This allows the radar to better distinguish between types of precipitation (e.g., rain, hail and snow), improves rainfall estimates, improves data retrieval in mountainous terrain, and aids in removal of non-weather artifacts. The NEXRAD products are divided in two data processing levels. The lower Level II data are base products at original resolution. Level II data are recorded at all NWS and most USAF and FAA WSR-88D sites. From the Level II quantities, computer processing generates numerous meteorological analysis Level III products. The Level III data consists of reduced resolution, low-bandwidth, base products as well as many derived, post-processed products. Level III products are recorded at most U.S. sites, though non-US sites do not have Level III products. There are over 40 Level III products available from the NCDC. General products for Level III include the base and composite reflectivity, storm relative velocity, vertical integrated liquid, echo tops and VAD wind profile. Precipitation products for Level III include estimated ground accumulated rainfall amounts for one and three hour periods, storm totals, and digital arrays. Estimates are based on reflectivity to rainfall rate (Z-R) relationships. Overlay products for Level III are alphanumeric data that give detailed information on certain parameters for an identified storm cell. These include storm structure, hail index, mesocyclone identification, tornadic vortex signature, and storm tracking information. Radar messages for Level III are sent by the radar site to users in order to know more about the radar status and special product data. NEXRAD data are provided to the NOAA National Climatic Data Center for archiving and dissemination to users. Data coverage varies by station and ranges from May 1992 to 1 day from present. Most stations began observing in the mid-1990s, and most period of records are continuous.

This dataset consists of Level II weather radar data collected from Next-Generation Radar (NEXRAD) stations located in the contiguous United States, Alaska, Hawaii, U.S. territories and at military base sites. NEXRAD is a network of 160 high-resolution Doppler weather radars operated by the NOAA National Weather Service (NWS), the Federal Aviation Administration (FAA), and the U.S. Air Force (USAF). Doppler radars detect atmospheric precipitation and winds, which allow scientists to track and anticipate weather events, such as rain, ice pellets, snow, hail, and tornadoes, as well as some non-weather objects like birds and insects. NEXRAD stations use the Weather Surveillance Radar - 1988, Doppler (WSR-88D) system. This is a 10 cm wavelength (S-Band) radar that operates at a frequency between 2,700 and 3,000 MHz. The radar system operates in two basic modes: a slow-scanning Clear Air Mode (Mode B) for analyzing air movements when there is little or no precipitation activity in the area, and a Precipitation Mode (Mode A) with a faster scan for tracking active weather. The two modes employ nine Volume Coverage Patterns (VCPs) to adequately sample the atmosphere based on weather conditions. A VCP is a series of 360 degree sweeps of the antenna at pre-determined elevation angles and pulse repetition frequencies completed in a specified period of time. The radar scan times 4.5, 5, 6 or 10 minutes depending on the selected VCP. The NEXRAD products are divided into multiple data processing levels. The lower Level II data contain the three meteorological base data quantities at original resolution: reflectivity, mean radial velocity, and spectrum width. With the advent of dual polarization beginning in 2011, additional base products of differential reflectivity, correlation coefficient and differential phase are available. Level II data are recorded at all NWS and most USAF and FAA WSR-88D sites. From the Level II quantities, computer processing generates numerous meteorological analysis Level 3 products. NEXRAD data are acquired by the NOAA National Centers for Environmental Information (NCEI) for archiving and dissemination to users. Data coverage varies by station and ranges from June 1991 to 1 day from present. Most stations began observing in the mid-1990s, and most period of records are continuous.

This service is available to all ArcGIS Online users with organizational accounts. For more information on this service, including the terms of use, visit us online at https://goto.arcgisonline.com/landscape11/USA_Soils_Drainage_Class.Soils vary widely in their ability to retain or drain water. The rate at which water drains into the soil has a direct effect on the amount and timing of runoff, what crops can be grown, and where wetlands form. In soils with low drainage rates water will pond on the soil's surface. Poorly drained soils are desirable when growing crops like rice where the fields are flooded for cultivation but other crops need better drained soils.Dataset SummaryPhenomenon Mapped: Drainage Class of SoilsUnits: ClassesCell Size: 30 metersSource Type: DiscretePixel Type: Unsigned integerData Coordinate System: USA Contiguous Albers Equal Area Conic USGS version (contiguous US, Puerto Rico, US Virgin Islands), WGS 1984 Albers (Alaska), Hawaii Albers Equal Area Conic (Hawaii), Western Pacific Albers Equal Area Conic (Guam, Marshall Islands, Northern Marianas Islands, Palau, Federated States of Micronesia, and American Samoa)Mosaic Projection: Web Mercator Auxiliary SphereExtent: Contiguous United States, Alaska, Hawaii, Puerto Rico, Guam, US Virgin Islands, Marshall Islands, Northern Marianas Islands, Palau, Federated States of Micronesia, and American SamoaSource: Natural Resources Conservation ServicePublication Date: July 2020ArcGIS Server URL: https://landscape11.arcgis.com/arcgis/Data from the gNATSGO database was used to create the layer for the contiguous United States, Alaska, Puerto Rico, and the U.S. Virgin Islands. The remaining areas were created with the gSSURGO database (Hawaii, Guam, Marshall Islands, Northern Marianas Islands, Palau, Federated States of Micronesia, and American Samoa).This layer is derived from the 30m (contiguous U.S.) and 10m rasters (all other regions) produced by the Natural Resources Conservation Service (NRCS). The value for drainage class is derived from the gSSURGO map unit aggregated attribute table field Drainage Class - Dominant Condition (drclassdcd).The layer has an attribute field for Drainage Class and a description field for use in pop-ups. The eight values of drainage class with corresponding attribute table index value are defined by the NRCS Soil Survey Manual as:0. Excessively drained: Water is removed very rapidly. The occurrence of internal free water commonly is very rare or very deep. The soils are commonly coarse-textured and have very high hydraulic conductivity or are very shallow.1. Somewhat excessively drained: Water is removed from the soil rapidly. Internal free water occurrence commonly is very rare or very deep. The soils are commonly coarse-textured and have high saturated hydraulic conductivity or are very shallow.2. Well drained: Water is removed from the soil readily but not rapidly. Internal free water occurrence commonly is deep or very deep; annual duration is not specified. Water is available to plants throughout most of the growing season in humid regions. Wetness does not inhibit growth of roots for significant periods during most growing seasons. The soils are mainly free of the deep to redoximorphic features that are related to wetness.3. Moderately well drained: Water is removed from the soil somewhat slowly during some periods of the year. Internal free water occurrence commonly is moderately deep and transitory through permanent. The soils are wet for only a short time within the rooting depth during the growing season, but long enough that most mesophytic crops are affected. They commonly have a moderately low or lower saturated hydraulic conductivity in a layer within the upper 1 m, periodically receive high rainfall, or both.4. Somewhat poorly drained: Water is removed slowly so that the soil is wet at a shallow depth for significant periods during the growing season. The occurrence of internal free water commonly is shallow to moderately deep and transitory to permanent. Wetness markedly restricts the growth of mesophytic crops, unless artificial drainage is provided. The soils commonly have one or more of the following characteristics: low or very low saturated hydraulic conductivity, a high water table, additional water from seepage, or nearly continuous rainfall.5. Poorly drained: Water is removed so slowly that the soil is wet at shallow depths periodically during the growing season or remains wet for long periods. The occurrence of internal free water is shallow or very shallow and common or persistent. Free water is commonly at or near the surface long enough during the growing season so that most mesophytic crops cannot be grown, unless the soil is artificially drained. The soil, however, is not continuously wet directly below plow-depth. Free water at shallow depth is usually present. This water table is commonly the result of low or very low saturated hydraulic conductivity of nearly continuous rainfall, or of a combination of these.6. Very poorly drained: Water is removed from the soil so slowly that free water remains at or very near the ground surface during much of the growing season. The occurrence of internal free water is very shallow and persistent or permanent. Unless the soil is artificially drained, most mesophytic crops cannot be grown. The soils are commonly level or depressed and frequently ponded. If rainfall is high or nearly continuous, slope gradients may be greater.7. Subaqueous Soils: These soils are under the surface of a body of water. (There are only a few of these in the entire dataset.)What can you do with this Layer? This layer is suitable for both visualization and analysis across the ArcGIS system. This layer can be combined with your data and other layers from the ArcGIS Living Atlas of the World in ArcGIS Online and ArcGIS Pro to create powerful web maps that can be used alone or in a story map or other application.Because this layer is part of the ArcGIS Living Atlas of the World it is easy to add to your map:In ArcGIS Online, you can add this layer to a map by selecting Add then Browse Living Atlas Layers. A window will open. Type "drainage class" in the search box and browse to the layer. Select the layer then click Add to Map.In ArcGIS Pro, open a map and select Add Data from the Map Tab. Select Data at the top of the drop down menu. The Add Data dialog box will open on the left side of the box, expand Portal if necessary, then select Living Atlas. Type "drainage class" in the search box, browse to the layer then click OK.In ArcGIS Pro you can use the built-in raster functions or create your own to create custom extracts of the data. Imagery layers provide fast, powerful inputs to geoprocessing tools, models, or Python scripts in Pro.Online you can filter the layer to show subsets of the data using the filter button and the layer's built-in raster functions.The ArcGIS Living Atlas of the World provides an easy way to explore many other beautiful and authoritative maps on hundreds of topics like this one.

The NCEP Climate Forecast System Reanalysis (CFSR) was initially completed for the 31-year period from 1979 to 2009, in January 2010. The CFSR was designed and executed as a global, high resolution, coupled atmosphere-ocean-land surface-sea ice system to provide the best estimate of the state of these coupled domains over this 31-year period. The CFSR has also been extended as an operational, real time product into the future. New features of the CFSR include: (1) coupling of atmosphere and ocean during the generation of the 6 hour guess field; (2) an interactive sea-ice model; and (3) assimilation of satellite radiances by the Grid-point Statistical Interpolation (GSI) scheme over the entire period. The CFSR global atmosphere resolution is approximately 38 km (T382) with 64 levels extending from the surface to 0.26 hPa. The global ocean's latitudinal spacing is 0.25 deg at the equator, extending to a global 0.5 deg beyond the tropics, with 40 levels to a depth of 4737m. The global land surface model has four4 soil levels and the global sea ice model has 3 layers. The CFSR atmospheric model has observed variations in carbon dioxide (CO2) over the 1979-2009 period, together with changes in aerosols and other trace gases and solar variations. Most available in-situ and satellite observation data were included in the CFSR. Satellite-based radiance observations were bias corrected with spin-up runs at full resolution, taking into account variable CO2 concentrations. This procedure enabled smooth transitions of the observation record due to evolutionary changes in satellite observing systems. The CFSR atmospheric, oceanic and land surface output products are available at an hourly time resolution and at a 0.5 deg x 0.5 deg latitude and longitude resolution. In total, there are 10 data products available from the National Climatic Data Center that make up the CFS Reanalysis collection: MON - Monthly Means; TIME - Parameter Timeseries; PGB - 3-D Pressure Level Data; FLX - Surface and Radiative Fluxes; OCN - 3-D Ocean Data; IPV - 3-D Isentropic Level Data; DIAB - 3-D Diabatic Heating Data; GRBLOW - Low-Resolution Data; HIC - High-Res Initial Conditions; LIC - Low-Res Initial Conditions. All data are in GRIB-2 format, except for the initial condition data which are in native binary formats. Total CFSR data volume is approximately 200 TB.