Discover the booming market for intelligent SF6 dew point meters. This comprehensive analysis reveals key trends, drivers, and restraints impacting growth through 2033, covering regional market share, leading companies, and technological advancements. Learn about the rising demand for precise SF6 gas monitoring in power substations and other industries.

Yearly effective energy and mass transfer (EEMT) (MJ m−2 yr−1) was calculated for the Catalina Mountains by summing the 12 monthly values. Effective energy and mass flux varies seasonally, especially in the desert southwestern United States where contemporary climate includes a bimodal precipitation distribution that concentrates in winter (rain or snow depending on elevation) and summer monsoon periods. This seasonality of EEMT flux into the upper soil surface can be estimated by calculating EEMT on a monthly basis as constrained by solar radiation (Rs), temperature (T), precipitation (PPT), and the vapor pressure deficit (VPD): EEMT = f(Rs,T,PPT,VPD). Here we used a multiple linear regression model to calculate the monthly EEMT that accounts for VPD, PPT, and locally modified T across the terrain surface. These EEMT calculations were made using data from the PRISM Climate Group at Oregon State University (www.prismclimate.org). Climate data are provided at an 800-m spatial resolution for input precipitation and minimum and maximum temperature normals and at a 4000-m spatial resolution for dew-point temperature (Daly et al., 2002). The PRISM climate data, however, do not account for localized variation in EEMT that results from smaller spatial scale changes in slope and aspect as occurs within catchments. To address this issue, these data were then combined with 10-m digital elevation maps to compute the effects of local slope and aspect on incoming solar radiation and hence locally modified temperature (Yang et al., 2007). Monthly average dew-point temperatures were computed using 10 yr of monthly data (2000–2009) and converted to vapor pressure. Precipitation, temperature, and dew-point data were resampled on a 10-m grid using spline interpolation. Monthly solar radiation data (direct and diffuse) were computed using ArcGIS Solar Analyst extension (ESRI, Redlands, CA) and 10-m elevation data (USGS National Elevation Dataset [NED] 1/3 Arc-Second downloaded from the National Map Seamless Server at seamless.usgs.gov). Locally modified temperature was used to compute the saturated vapor pressure, and the local VPD was estimated as the difference between the saturated and actual vapor pressures. The regression model was derived using the ISOHYS climate data set comprised of approximately 30-yr average monthly means for more than 300 weather stations spanning all latitudes and longitudes (IAEA).

Surface Weather and Ocean Observations Web Service is derived from the latest surface weather and marine weather observations at observing sites using the international station model. This map service provides maps depicting the latest surface weather and marine weather observations at observing sites using the international station model. The station model is a method for representing information collected at an observing station using symbols and numbers. The station model depicts current weather conditions, cloud cover, wind speed, wind direction, visibility, air temperature, dew point temperature, sea surface water temperature, significant wave height, air pressure adjusted to mean sea level, and the change in air pressure over the last 3 hours. The circle in the model is centered over the latitude and longitude coordinates of the station. The total cloud cover is expressed as a fraction of cloud covering the sky and is indicated by the amount of circle filled in; Wind speed and direction are represented by a wind barb whose line extends from the cover cloud circle towards the direction from which the wind is blowing.The observations included in this map service are organized into three separate group layers: 1) Wind velocity (wind barb) observations, 2) Cloud Cover observations, and 3) All other observations, which are displayed as numerical values (e.g. Air Temperature, Wind Gust, Visibility, Sea Surface Temperature, etc.).Additionally, due to the density of weather/ocean observations in this map service, each of these group data layers has been split into ten individual "Scale Band" layers, with each one visible for a certain range of map scales. Thus, to ensure observations are displayed at any scale, users should make sure to always specify all six corresponding scale band layers in every map request. This will result in the scale band most appropriate for your present zoom level being shown, resulting in a clean, uncluttered display. As you zoom in, additional observations will appear.Update Frequency: The observations in this service are updated approximately every 10 minutes. However, since the reporting frequency varies by network or station, the observations for a particular station may update only once per hour.Link to data download: https://madis.ncep.noaa.gov/madis_datasets.shtmlLink to metadata: https://www.weather.gov/gis/IDP-GISRestMetadataQuestions/Concerns about the service, please contact the DISS GIS teamTime Information:This map is not time-enabled.Background Information:The maps of near-real-time surface weather and ocean observations are based on non-restricted data obtained from the NWS Family of Services courtesy of NESDIS/OPSD and also the NWS Meteorological Assimilation Data Ingest System (MADIS). The data includes observations from terrestrial and maritime observing stations from the U.S.A. and other countries.

The global intelligent SF6 dew point meter market is experiencing robust growth, driven by increasing demand for reliable and efficient gas-insulated switchgear (GIS) in the power sector, particularly in substations. The rising adoption of smart grids and the need for preventative maintenance to avoid costly equipment failures are significant contributors to this market expansion. The chemical and scientific research industries also contribute substantially, utilizing these meters for precise gas analysis and process control. Technological advancements, including improved sensor accuracy and connectivity features for remote monitoring and data analysis, are fueling market expansion. The portable segment shows strong growth due to its flexibility and ease of use in diverse settings. While a precise market size is unavailable from the provided data, a reasonable estimate based on industry reports and observed growth in related sectors suggests a 2025 market value of approximately $500 million, growing at a compound annual growth rate (CAGR) of 8% over the forecast period (2025-2033). This growth, however, is tempered somewhat by the high initial investment cost of the equipment and the need for specialized technical expertise for operation and maintenance. Competitive landscape analysis indicates a mix of established players and emerging regional manufacturers, suggesting future market consolidation and innovation through partnerships and technological advancements. The market segmentation reveals significant variations in growth across different applications. Substations represent the largest market share, followed by the chemical industry and scientific research. The desktop segment currently holds a larger market share compared to the portable segment; however, the portable segment is witnessing faster growth due to its increasing popularity in field applications and remote monitoring. Regional analysis highlights North America and Europe as mature markets, while the Asia-Pacific region exhibits significant growth potential driven by rapid infrastructure development and increasing electricity demand. This is further strengthened by the presence of several key manufacturers in China. Future market growth will depend heavily on continued investment in grid modernization, advancements in sensor technology, and the development of cost-effective, user-friendly solutions.

Yearly effective energy and mass transfer (EEMT) (MJ m−2 yr−1) was calculated for the Valles Calders, upper part of the Jemez River basin by summing the 12 monthly values. Effective energy and mass flux varies seasonally, especially in the desert southwestern United States where contemporary climate includes a bimodal precipitation distribution that concentrates in winter (rain or snow depending on elevation) and summer monsoon periods. This seasonality of EEMT flux into the upper soil surface can be estimated by calculating EEMT on a monthly basis as constrained by solar radiation (Rs), temperature (T), precipitation (PPT), and the vapor pressure deficit (VPD): EEMT = f(Rs,T,PPT,VPD). Here we used a multiple linear regression model to calculate the monthly EEMT that accounts for VPD, PPT, and locally modified T across the terrain surface. These EEMT calculations were made using data from the PRISM Climate Group at Oregon State University (www.prismclimate.org). Climate data are provided at an 800-m spatial resolution for input precipitation and minimum and maximum temperature normals and at a 4000-m spatial resolution for dew-point temperature (Daly et al., 2002). The PRISM climate data, however, do not account for localized variation in EEMT that results from smaller spatial scale changes in slope and aspect as occurs within catchments. To address this issue, these data were then combined with 10-m digital elevation maps to compute the effects of local slope and aspect on incoming solar radiation and hence locally modified temperature (Yang et al., 2007). Monthly average dew-point temperatures were computed using 10 yr of monthly data (2000–2009) and converted to vapor pressure. Precipitation, temperature, and dew-point data were resampled on a 10-m grid using spline interpolation. Monthly solar radiation data (direct and diffuse) were computed using ArcGIS Solar Analyst extension (ESRI, Redlands, CA) and 10-m elevation data (USGS National Elevation Dataset [NED] 1/3 Arc-Second downloaded from the National Map Seamless Server at seamless.usgs.gov). Locally modified temperature was used to compute the saturated vapor pressure, and the local VPD was estimated as the difference between the saturated and actual vapor pressures. The regression model was derived using the ISOHYS climate data set comprised of approximately 30-yr average monthly means for more than 300 weather stations spanning all latitudes and longitudes (IAEA).

National Digital Forecast Database (NDFD) Metadata

The National Digital Forecast Database (NDFD) Web Services provide a set of gridded weather forecasts for various sensible weather elements in near real-time. These forecasts are generated by a collaboration between the National Weather Service (NWS) field offices and the National Centers for Environmental Prediction (NCEP). The NDFD Web Services offer a seamless, digital mosaic of weather forecasts that can be accessed by users to obtain up-to-date information on a variety of weather conditions.

The NDFD's forecasts are gridded, meaning they cover large geographic areas with weather data at specific intervals, providing high-resolution, geographically distributed forecasts. These forecasts can include temperature, precipitation, wind speed and direction, cloud cover, and other meteorological parameters.

These web services are hosted by the Office of Dissemination’s CloudGIS team, which ensures the forecasts are readily accessible and deliverable over the internet. Users, including meteorologists, developers, and anyone interested in weather data, can query these web services for up-to-date forecasts in a digital format, enabling integration into applications, websites, and other platforms.

NDFD’s Web Services Descriptions:

12-Hour Probability of Precipitation Web Service's data layer is the likelihood, expressed as a percent, of a measurable precipitation event (1/100th of an inch or more) at a grid point during the 12-hour valid period. The 12-hour valid periods begin and end at 0000 and 1200 Coordinated Universal Time (UTC).

Apparent Temperature Web Service: contains data that is the perceived temperature derived from either a combination of temperature and wind (Wind Chill) or temperature and humidity (Heat Index) for the indicated hour. When the temperature at a particular grid point falls to 50 F or less, wind chill will be used for that point for the Apparent Temperature. When the temperature at a grid point rises above 80 F, the heat index will be used for Apparent Temperature. Between 51 and 80 F, the Apparent Temperature will be the ambient air temperature.

Dew Point Temperature Web Service's data is the expected dew point temperature for the indicated hour. Dew point temperature is a measure of atmospheric moisture. It is the temperature to which air must be cooled in order to reach saturation (assuming air pressure and moisture content are constant).

Maximum Temperature Web Service's data is the daytime maximum temperature observed from 7 AM to 7PM LST.

Minimum Temperature Web Service's data is predicted minimum temperature for a specific location at a given time, allowing users to visualize the lowest expected temperatures across a geographical area.

Precipitation Amount Web Service's data is the expected quantity of liquid precipitation accumulated over a six-hourly period. A quantitative precipitation forecast (QPF) will be specified when a measurable (1/100th of an inch or more) precipitation type is forecast for any hour during a QPF valid period. NDFD valid periods for QPF are 6 hours long beginning and ending at 0000, 0600, 1200 and 1800 UTC. QPF includes the liquid equivalent amount for snow and ice.

Relative Humidity Web Service's data is a ratio, expressed as a percent, of the amount of atmospheric moisture present relative to the amount that would be present if the air were saturated. Since the latter amount is dependent on temperature, relative humidity is a function of both moisture content and temperature.

Sky Cover Web Service’s data is the predicted percentage of the sky that will be covered by opaque clouds at a given time, provided by the National Digital Forecast Database (NDFD). It is a forecast of how much of the sky will be obscured by clouds, expressed as a percentage value.

Snow Amount Web Service's data is the expected total accumulation of new snow during a 6-hour period. A snow accumulation grid will be specified whenever a measurable snowfall is forecast for any hour during a valid period. Valid periods for the NDFD begin and end at 0600, 1200, 1800, and 0000 UTC.

Temperature Web Service: contains data that is the expected temperature in degrees Fahrenheit valid for the indicated hour.

Wave Height Web Service's data is the average height (from trough to crest) of the one-third highest waves valid for the top of the designated hour. Wave Height is a combination of wind waves and swell.

Wind Direction Web Service's data is the expected sustained 10-meter wind direction for the indicated hour, using 36 points of a compass.

Wind Gust Web Service's data is the maximum 3-second wind speed forecast to occur within a 2-minute interval at a height of 10 meters. Wind gust forecasts are valid at the top of the indicated hour.

Wind Speed Web Service's data is the expected sustained 10-meter sustained wind speed for the indicated hour.

Wind Speed and Direction Web Service's data is the expected sustained 10-meter wind direction for the indicated hour, using 36 points of a compass. Wind Speed is the expected sustained 10-meter sustained wind speed for the indicated hour. Wind barbs (shown below) are used to denote wind speed and direction.

Update Frequency: The data in these service updates hourly. (Click here to see specific Valid Times for update Frequency)

Link to graphical web page: https://digital.weather.gov

Link to data download (grib2): https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/

Link to metadata

Questions/Concerns about the service, please contact the DISS GIS team

Time Information:

These web services are time-enabled, meaning that each individual layer contains time-varying data and can be utilized by clients capable of making map requests that include a time component.

These particular services can be queried with or without the use of a time component. If the time parameter is specified in a request, the data or imagery most relevant to the provided time value, if any, will be returned. If the time parameter is not specified in a request, the latest data or imagery valid for the present system time will be returned to the client. If the time parameter is not specified and no data or imagery is available for the present time, no data will be returned.

Valid Time Table:

Service

Valid Time

12-Hour Probability of Precipitation Web Service

The 12-hour valid periods begin and end at 0000 and 1200 Coordinated Universal Time (UTC).

Apparent Temperature Web Service

CONUS displays every hour OCONUS displays every 3 hours (3z,6z,9z,12z etc.)

Dew Point Temperature Web Service

CONUS displays every hour OCONUS displays every 3 hours (3z,6z,9z,12z etc.)

Maximum Temperature Web Service

Display 0z every day

Minimum Temperature Web Service

Display at 12z every day

Precipitation Amount Web Service

CONUS/OCONUS (forecast is valid at 0z,6z,12z and 18z)

Relative Humidity Web Service

CONUS displays every hour OCONUS displays every 3 hours (3z,6z,9z,12z etc.)

Sky Cover Web Service

CONUS displays every hour OCONUS displays every 3 hours (3z,6z,9z,12z etc.)

Snow Amount Web Service

CONUS/OCONUS (forecast is valid at 0z,6z,12z and 18z)

Temperature Web Service

CONUS displays every hour OCONUS displays every 3 hours (3z,6z,9z,12z etc.)

Wave Height Web Service

CONUS displays every hour OCONUS displays every 3 hours (3z,6z,9z,12z etc.)

Wind Direction Web Service

CONUS displays every hour OCONUS displays every 3 hours (3z,6z,9z,12z etc.)

Wind Gust Web Service

CONUS displays every hour OCONUS displays every 3 hours (3z,6z,9z,12z etc.)

Wind Speed

CONUS displays every hour OCONUS displays every 3 hours (3z,6z,9z,12z etc.)

Wind Speed and Direction Web Service

CONUS displays every hour OCONUS displays every 3 hours (3z,6z,9z,12z etc.)

Road Weather Information Systems, known as RWIS, are used to monitor road conditions and make decisions on how to maintain safe driving conditions. RWIS stations may include atmospheric and pavement sensors that measure temperature, dew point, wind speed and direction, visibility and precipitation information. RWIS data is used by the Department to support decision making. The use of RWIS by road maintenance authorities has been proven to increase the level of service, which in turn means better road conditions and lives saved.

Thirty one years of spatially distributed air temperature, relative humidity, dew point temperature, precipitation amount, and precipitation phase data are presented for the Reynolds Creek Experimental Watershed. The data are spatially distributed over a 10m Lidar-derived digital elevation model at an hourly time step using a detrended kriging algorithm. This dataset covers a wide range of weather extremes in a mesoscale basin (237 km2) that encompasses the rain-snow transition zone and should find widespread application in earth science modeling communities. Spatial data allows for a more holistic analysis of basin means and elevation gradients, compared to point data. Files are stored in the NetCDF file format, which allows for easy spatiotemporal averaging and/or subsetting.

The i12_CalSim_Output dataset is a point feature class containing 44 point locations representing a subset of CalSim II output locations. A related table of timeseries data is provided that corresponds to each of these point locations. Timeseries data reflect a simulation period from 10/31/1921 through 9/30/2003 as simulated by the CalSim II model. Multiple CalSim II model simulations are included to reflect projected changes in climate for early-century (2030) and late-century (2070) model simulations (including 2070 drier extreme warming [DEW] scenario and wetter moderate warming [WMW] scenario). Spatial references were developed during the Water Storage Investment Program (WSIP) climate change study conducted in 2016. The user should use caution and fully understand the limitations of these datasets before applying them in a water budget calculation as these datasets correspond to model simulation outputs that contain their own assumptions and limitations.

A typical METAR contains data for the temperature, dew point, wind speed and direction, precipitation, cloud cover and heights, visibility, and barometric pressure. A METAR may also contain information on precipitation amounts, lightning, and other information that would be of interest to pilots or meteorologists such as a pilot report or PIREP, color states and runway visual range (RVR).

Predicted temperature and precipitation values were generated throughout the state of Massachusetts using a stochastic weather generator (SWG) model to develop various climate change scenarios (Steinschneider and Najibi, 2022a). This data release contains temperature and precipitation statistics (SWG_outputTable.csv) derived from the SWG model under the surface warming derived from the RCP 8.5 climate change emissions scenario at 30-year moving averages centered around 2030, 2050, 2070, 2090. During the climate modeling process, extreme precipitation values were also generated by scaling previously published intensity-duration-frequency (IDF) values from the NOAA Atlas 14 database (Perica and others, 2015) by a factor per degree expected warming produced from the SWG model generator (Najibi and others, 2022; Steinschneider and Najibi, 2022b, c). These newly generated IDF values (IDF_outputTable.csv) account for expected changes in extreme precipitation driven by variations in weather associated with climate change throughout the state of Massachusetts. The data presented here were developed in collaboration with the Massachusetts Executive Office of Energy and Environmental Affairs and housed on the Massachusetts climate change clearinghouse webpage (Massachusetts Executive Office of Energy and Environmental Affairs, 2022). References: Massachusetts Executive Office of Energy and Environmental Affairs, 2022, Resilient MA Maps and Data Center at URL https://resilientma-mapcenter-mass-eoeea.hub.arcgis.com/ Najibi, N., Mukhopadhyay, S., and Steinschneider, S., 2022, Precipitation scaling with temperature in the Northeast US: Variations by weather regime, season, and precipitation intensity: Geophysical Research Letters, v. 49, no. 8, 14 p., https://doi.org/10.1029/2021GL097100. Perica, S., Pavlovic, S., St. Laurent, M., Trypaluk, C., Unruh, D., Martin, D., and Wilhite, O., 2015, NOAA Atlas 14 Volume 10 Version 3, Precipitation-Frequency Atlas of the United States, Northeastern States (revised 2019): NOAA, National Weather Service, https://doi.org/10.25923/99jt-a543. Steinschneider, S., and Najibi, N., 2022a, A weather-regime based stochastic weather generator for climate scenario development across Massachusetts: Technical Documentation, Cornell University, https://eea-nescaum-dataservices-assets-prd.s3.amazonaws.com/cms/GUIDELINES/FinalTechnicalDocumentation_WGEN_20220405.pdf. Steinschneider, S., and Najibi, N., 2022b, Future projections of extreme precipitation across Massachusetts—a theory-based approach: Technical Documentation, Cornell University, https://eea-nescaum-dataservices-assets-prd.s3.amazonaws.com/cms/GUIDELINES/FinalTechnicalDocumentation_IDF_Curves_Dec2021.pdf. Steinschneider, S., and Najibi, N., 2022c, Observed and projected scaling of daily extreme precipitation with dew point temperature at annual and seasonal scales across the northeast United States: Journal of Hydrometeorology, v. 23, no. 3, p. 403-419, https://doi.org/10.1175/JHM-D-21-0183.1.

National Digital Forecast Database (NDFD) MetadataThe National Digital Forecast Database (NDFD) Web Services provide a set of gridded weather forecasts for various sensible weather elements in near real-time. These forecasts are generated by a collaboration between the National Weather Service (NWS) field offices and the National Centers for Environmental Prediction (NCEP). The NDFD Web Services offer a seamless, digital mosaic of weather forecasts that can be accessed by users to obtain up-to-date information on a variety of weather conditions.The NDFD's forecasts are gridded, meaning they cover large geographic areas with weather data at specific intervals, providing high-resolution, geographically distributed forecasts. These forecasts can include temperature, precipitation, wind speed and direction, cloud cover, and other meteorological parameters.These web services are hosted by the Office of Dissemination’s CloudGIS team, which ensures the forecasts are readily accessible and deliverable over the internet. Users, including meteorologists, developers, and anyone interested in weather data, can query these web services for up-to-date forecasts in a digital format, enabling integration into applications, websites, and other platforms.NDFD’s Web Services Descriptions:12-Hour Probability of Precipitation Web Service's data layer is the likelihood, expressed as a percent, of a measurable precipitation event (1/100th of an inch or more) at a grid point during the 12-hour valid period. The 12-hour valid periods begin and end at 0000 and 1200 Coordinated Universal Time (UTC).Apparent Temperature Web Service: contains data that is the perceived temperature derived from either a combination of temperature and wind (Wind Chill) or temperature and humidity (Heat Index) for the indicated hour. When the temperature at a particular grid point falls to 50 F or less, wind chill will be used for that point for the Apparent Temperature. When the temperature at a grid point rises above 80 F, the heat index will be used for Apparent Temperature. Between 51 and 80 F, the Apparent Temperature will be the ambient air temperature.Dew Point Temperature Web Service's data is the expected dew point temperature for the indicated hour. Dew point temperature is a measure of atmospheric moisture. It is the temperature to which air must be cooled in order to reach saturation (assuming air pressure and moisture content are constant).Maximum Temperature Web Service's data is the daytime maximum temperature observed from 7 AM to 7PM LST.Minimum Temperature Web Service's data is predicted minimum temperature for a specific location at a given time, allowing users to visualize the lowest expected temperatures across a geographical area.Precipitation Amount Web Service's data is the expected quantity of liquid precipitation accumulated over a six-hourly period. A quantitative precipitation forecast (QPF) will be specified when a measurable (1/100th of an inch or more) precipitation type is forecast for any hour during a QPF valid period. NDFD valid periods for QPF are 6 hours long beginning and ending at 0000, 0600, 1200 and 1800 UTC. QPF includes the liquid equivalent amount for snow and ice.Relative Humidity Web Service's data is a ratio, expressed as a percent, of the amount of atmospheric moisture present relative to the amount that would be present if the air were saturated. Since the latter amount is dependent on temperature, relative humidity is a function of both moisture content and temperature.Sky Cover Web Service’s data is the predicted percentage of the sky that will be covered by opaque clouds at a given time, provided by the National Digital Forecast Database (NDFD). It is a forecast of how much of the sky will be obscured by clouds, expressed as a percentage value.Snow Amount Web Service's data is the expected total accumulation of new snow during a 6-hour period. A snow accumulation grid will be specified whenever a measurable snowfall is forecast for any hour during a valid period. Valid periods for the NDFD begin and end at 0600, 1200, 1800, and 0000 UTC.Temperature Web Service: contains data that is the expected temperature in degrees Fahrenheit valid for the indicated hour.Wave Height Web Service's data is the average height (from trough to crest) of the one-third highest waves valid for the top of the designated hour. Wave Height is a combination of wind waves and swell.Wind Direction Web Service's data is the expected sustained 10-meter wind direction for the indicated hour, using 36 points of a compass.Wind Gust Web Service's data is the maximum 3-second wind speed forecast to occur within a 2-minute interval at a height of 10 meters. Wind gust forecasts are valid at the top of the indicated hour.Wind Speed Web Service's data is the expected sustained 10-meter sustained wind speed for the indicated hour.Wind Speed and Direction Web Service's data is the expected sustained 10-meter wind direction for the indicated hour, using 36 points of a compass. Wind Speed is the expected sustained 10-meter sustained wind speed for the indicated hour. Wind barbs (shown below) are used to denote wind speed and direction.Update Frequency: The data in these service updates hourly. (Click here to see specific Valid Times for update Frequency)Link to graphical web page: https://digital.weather.govLink to data download (grib2): https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/Link to metadataQuestions/Concerns about the service, please contact the DISS GIS teamTime Information:These web services are time-enabled, meaning that each individual layer contains time-varying data and can be utilized by clients capable of making map requests that include a time component.These particular services can be queried with or without the use of a time component. If the time parameter is specified in a request, the data or imagery most relevant to the provided time value, if any, will be returned. If the time parameter is not specified in a request, the latest data or imagery valid for the present system time will be returned to the client. If the time parameter is not specified and no data or imagery is available for the present time, no data will be returned.Valid Time Table:ServiceValid Time12-Hour Probability of Precipitation Web ServiceThe 12-hour valid periods begin and end at 0000 and 1200 Coordinated Universal Time (UTC).Apparent Temperature Web ServiceCONUS displays every hourOCONUS displays every 3 hours (3z,6z,9z,12z etc.)Dew Point Temperature Web ServiceCONUS displays every hourOCONUS displays every 3 hours (3z,6z,9z,12z etc.)Maximum Temperature Web ServiceDisplay 0z every dayMinimum Temperature Web ServiceDisplay at 12z every dayPrecipitation Amount Web ServiceCONUS/OCONUS (forecast is valid at 0z,6z,12z and 18z)Relative Humidity Web ServiceCONUS displays every hourOCONUS displays every 3 hours (3z,6z,9z,12z etc.)Sky Cover Web ServiceCONUS displays every hourOCONUS displays every 3 hours (3z,6z,9z,12z etc.)Snow Amount Web ServiceCONUS/OCONUS (forecast is valid at 0z,6z,12z and 18z)Temperature Web ServiceCONUS displays every hourOCONUS displays every 3 hours (3z,6z,9z,12z etc.)Wave Height Web ServiceCONUS displays every hourOCONUS displays every 3 hours (3z,6z,9z,12z etc.)Wind Direction Web ServiceCONUS displays every hourOCONUS displays every 3 hours (3z,6z,9z,12z etc.)Wind Gust Web ServiceCONUS displays every hourOCONUS displays every 3 hours (3z,6z,9z,12z etc.)Wind SpeedCONUS displays every hourOCONUS displays every 3 hours (3z,6z,9z,12z etc.)Wind Speed and Direction Web ServiceCONUS displays every hourOCONUS displays every 3 hours (3z,6z,9z,12z etc.)

Surface Weather and Ocean Observations Web Service is derived from the latest surface weather and marine weather observations at observing sites using the international station model. This map service provides maps depicting the latest surface weather and marine weather observations at observing sites using the international station model. The station model is a method for representing information collected at an observing station using symbols and numbers. The station model depicts current weather conditions, cloud cover, wind speed, wind direction, visibility, air temperature, dew point temperature, sea surface water temperature, significant wave height, air pressure adjusted to mean sea level, and the change in air pressure over the last 3 hours. The circle in the model is centered over the latitude and longitude coordinates of the station. The total cloud cover is expressed as a fraction of cloud covering the sky and is indicated by the amount of circle filled in; Wind speed and direction are represented by a wind barb whose line extends from the cover cloud circle towards the direction from which the wind is blowing.The observations included in this map service are organized into three separate group layers: 1) Wind velocity (wind barb) observations, 2) Cloud Cover observations, and 3) All other observations, which are displayed as numerical values (e.g. Air Temperature, Wind Gust, Visibility, Sea Surface Temperature, etc.).Additionally, due to the density of weather/ocean observations in this map service, each of these group data layers has been split into ten individual "Scale Band" layers, with each one visible for a certain range of map scales. Thus, to ensure observations are displayed at any scale, users should make sure to always specify all six corresponding scale band layers in every map request. This will result in the scale band most appropriate for your present zoom level being shown, resulting in a clean, uncluttered display. As you zoom in, additional observations will appear.Update Frequency: The observations in this service are updated approximately every 10 minutes. However, since the reporting frequency varies by network or station, the observations for a particular station may update only once per hour.Link to data download: https://madis.ncep.noaa.gov/madis_datasets.shtmlLink to metadata: https://www.weather.gov/gis/IDP-GISRestMetadataQuestions/Concerns about the service, please contact the DISS GIS teamTime Information:This map is not time-enabled.Background Information:The maps of near-real-time surface weather and ocean observations are based on non-restricted data obtained from the NWS Family of Services courtesy of NESDIS/OPSD and also the NWS Meteorological Assimilation Data Ingest System (MADIS). The data includes observations from terrestrial and maritime observing stations from the U.S.A. and other countries.

Last Updated: January 2015

Map Information

This nowCOAST time-enabled map service provides maps depicting the past four hours of surface meteorological analyses of air temperature, dew point temperature, visibility, wind velocity, wind speed, wind gust, and 1-hr accumulated precipitation from the NWS/NCEP Real-Time Mesoscale Analysis (RTMA) system. The horizontal spatial resolution depends on geographic region: 2.5 km (1.6 miles) horizontal resolution for CONUS, Hawaii, Puerto Rico and Guam and 3 km (1.86 miles) for Alaska region.

The air and dew point temperatures are indicated on the map by different colors at 2 degree Fahrenheit increments from -30 to 130 degrees F in order to use same color legend throughout the year for the United States. The same color scale is used for displaying the NDFD maximum and minimum air temperature forecasts.

The visibility is indicated on the map by different colors for the following ranges: 0 - 0.24, 0.25 - 0.49, 0.5 - 0.74, 0.75 - 0.99, 1.0 - 2.9, 3.0 - 4.9, 5.0 - 6.9, and 7.0 + miles in order to correspond with thresholds important to mariners and aviators as well as thresholds associated with visibility-related watches, warnings and advisories issued by the National Weather Service.

The total precipitation amount is indicated by different colors at 0.01, 0.10, 0.25 and then at 1/4 inch intervals up to 4.0 (e.g. 0.50, 0.75, 1.00, 1.25, etc.), at 1-inch intervals from 4 to 10 inches and then at 2-inch intervals up to 14 inches. The increments from 0.01 to 1.00 or 2.00 inches are similar to what are used on the NCEP Weather Prediction Center QPF products and the NWS River Forecast Center (RFC) daily precipitation analysis.

Wind speed and wind gust are indicated on the map by different colors for 5 knots increments up to 115 knots. The legend includes tick marks for both knots and miles per hour. The same color scale is used for displaying the NDFD wind speed/gust forecasts. The wind velocity is depicted by curved wind barbs along streamlines. The direction of the wind barb is indicated with an arrowhead. The flags on the wind barb are the standard meteorological convention in units of knots.

The analyses are updated in the nowCOAST map service every hour. For more detailed information about the update schedule, see: http://new.nowcoast.noaa.gov/help/#section=updateschedule

Background Information The NCEP RTMA system is an hourly, high-resolution, objective analysis/assimilation system for near-real surface weather conditions. RTMA system uses the Two-Dimensional Variational Analysis mode of NCEP's Gridpoint Statistical Interpolation (GSI). The first guess for the RTMA analyses for Alaska, Puerto Rico, Guam, and HI domains are provided by downscaled forecasts from NCEP's North American Mesoscale (NAM) Model. The first guess for OCONUS domain analyses are from the 1-hour forecasts of the NCEP Rapid Refresh system. The RTMA system was developed by NCEP/Environmental Modeling Center/Mesoscale Modeling Branch in cooperation with NOAA/Office of Oceanic and Atmospheric Research/Environmental Research Laboratory.

Time Information

This map is time-enabled, meaning that each individual layer contains time-varying data and can be utilized by clients capable of making map requests that include a time component.

This particular service can be queried with or without the use of a time component. If the time parameter is specified in a request, the data or imagery most relevant to the provided time value, if any, will be returned. If the time parameter is not specified in a request, the latest data or imagery valid for the present system time will be returned to the client. If the time parameter is not specified and no data or imagery is available for the present time, no data will be returned.

In addition to ArcGIS Server REST access, time-enabled OGC WMS 1.3.0 access is also provided by this service.

Due to software limitations, the time extent of the service and map layers displayed below does not provide the most up-to-date start and end times of available data. Instead, users have three options for determining the latest time information about the service:

Issue a returnUpdates=true request for an individual layer or for
the service itself, which will return the current start and end times of
available data, in epoch time format (milliseconds since 00:00 January 1,
1970). To see an example, click on the "Return Updates" link at the bottom of
this page under "Supported Operations". Refer to the
ArcGIS REST API Map Service Documentation
for more information.


  Issue an Identify (ArcGIS REST) or GetFeatureInfo (WMS) request against
  the proper layer corresponding with the target dataset. For raster
  data, this would be the "Image Footprints with Time Attributes" layer
  in the same group as the target "Image" layer being displayed. For
  vector (point, line, or polygon) data, the target layer can be queried
  directly. In either case, the attributes returned for the matching
  raster(s) or vector feature(s) will include the following:


      validtime: Valid timestamp.


      starttime: Display start time.


      endtime: Display end time.


      reftime: Reference time (sometimes reffered to as
      issuance time, cycle time, or initialization time).


      projmins: Number of minutes from reference time to valid
      time.


      desigreftime: Designated reference time; used as a
      common reference time for all items when individual reference
      times do not match.


      desigprojmins: Number of minutes from designated
      reference time to valid time.




  Query the nowCOAST LayerInfo web service, which has been created to
  provide additional information about each data layer in a service,
  including a list of all available "time stops" (i.e. "valid times"),
  individual timestamps, or the valid time of a layer's latest available
  data (i.e. "Product Time"). For more information about the LayerInfo
  web service, including examples of various types of requests, refer to
  the nowCOAST help documentation at:
  http://new.nowcoast.noaa.gov/help/#section=layerinfo

References

NWS, 2011: Real-Time Mesoscale Analysis (RTMA) Product Description Document, NOAA/NWS Silver Spring, MD (Available at http://products.weather.gov/PDD/RTMA_Operational_2011.pdf). NWS, 2013: Real-Time Mesoscale Analysis (RTMA) Documentation, NWS/NCEP/EMC, College Park, MD (Available at http://nomads.ncep.noaa.gov/txt_descriptions/RTMA_doc.shtml).

ERA5-Land total precipitation monthly time series for Mauritania at 30 arc seconds (ca. 1000 meter) resolution (2019 - 2023)

Source data:
ERA5-Land is a reanalysis dataset providing a consistent view of the evolution of land variables over several decades at an enhanced resolution compared to ERA5. ERA5-Land has been produced by replaying the land component of the ECMWF ERA5 climate reanalysis. Reanalysis combines model data with observations from across the world into a globally complete and consistent dataset using the laws of physics. Reanalysis produces data that goes several decades back in time, providing an accurate description of the climate of the past.

Total precipitation:
Accumulated liquid and frozen water, including rain and snow, that falls to the Earth's surface. It is the sum of large-scale precipitation (that precipitation which is generated by large-scale weather patterns, such as troughs and cold fronts) and convective precipitation (generated by convection which occurs when air at lower levels in the atmosphere is warmer and less dense than the air above, so it rises). Precipitation variables do not include fog, dew or the precipitation that evaporates in the atmosphere before it lands at the surface of the Earth. This variable is accumulated from the beginning of the forecast time to the end of the forecast step. The units of precipitation are depth in metres. It is the depth the water would have if it were spread evenly over the grid box. Care should be taken when comparing model variables with observations, because observations are often local to a particular point in space and time, rather than representing averages over a model grid box and model time step.

Processing steps:
The original hourly ERA5-Land data has been spatially enhanced from 0.1 degree to 30 arc seconds (approx. 1000 m) spatial resolution by image fusion with CHELSA data (V1.2) (https://chelsa-climate.org/). For each day we used the corresponding monthly long-term average of CHELSA. The aim was to use the fine spatial detail of CHELSA and at the same time preserve the general regional pattern and fine temporal detail of ERA5-Land. The steps included aggregation and enhancement, specifically:
1. spatially aggregate CHELSA to the resolution of ERA5-Land
2. calculate proportion of ERA5-Land / aggregated CHELSA
3. interpolate proportion with a Gaussian filter to 30 arc seconds
4. multiply the interpolated proportions with CHELSA
Using proportions ensures that areas without precipitation remain areas without precipitation. Only if there was actual precipitation in a given area, precipitation was redistributed according to the spatial detail of CHELSA.

The spatially enhanced daily ERA5-Land data has been aggregated to monthly resolution, by calculating the sum of the precipitation per pixel over each month.

File naming:
ERA5_land_monthly_prectot_sum_30sec_YYYY_MM_01T00_00_00_int.tif
e.g.:ERA5_land_monthly_prectot_sum_30sec_2023_12_01T00_00_00_int.tif

The date within the filename is year and month of aggregated timestamp.

Pixel values:
mm * 10
Scaled to Integer, example: value 218 = 21.8 mm

Projection + EPSG code:
Latitude-Longitude/WGS84 (EPSG: 4326)

Spatial extent:
north: 28:18N
south: 14:42N
west: 17:05W
east: 4:49W

Temporal extent:
January 2019 - December 2023

Spatial resolution:
30 arc seconds (approx. 1000 m)

Temporal resolution:
monthly

Lineage:
Dataset has been processed from original Copernicus Climate Data Store (ERA5-Land) data sources. As auxiliary data CHELSA climate data has been used.

Software used:
GRASS GIS 8.3.2

Format: GeoTIFF

Original ERA5-Land dataset license:
https://cds.climate.copernicus.eu/api/v2/terms/static/licence-to-use-copernicus-products.pdf

CHELSA climatologies (V1.2): Data used: Karger D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E, Linder, H.P., Kessler, M. (2018): Data from: Climatologies at high resolution for the earth's land surface areas. Dryad digital repository. http://dx.doi.org/doi:10.5061/dryad.kd1d4
Original peer-reviewed publication: Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, P., Kessler, M. (2017): Climatologies at high resolution for the Earth land surface areas. Scientific Data. 4 170122. https://doi.org/10.1038/sdata.2017.122

Representation type: Grid

Processed by:
mundialis GmbH & Co. KG, Germany (https://www.mundialis.de/)

Contact:
mundialis GmbH & Co. KG, info@mundialis.de

National Digital Forecast Database (NDFD) MetadataThe National Digital Forecast Database (NDFD) Web Services provide a set of gridded weather forecasts for various sensible weather elements in near real-time. These forecasts are generated by a collaboration between the National Weather Service (NWS) field offices and the National Centers for Environmental Prediction (NCEP). The NDFD Web Services offer a seamless, digital mosaic of weather forecasts that can be accessed by users to obtain up-to-date information on a variety of weather conditions.The NDFD's forecasts are gridded, meaning they cover large geographic areas with weather data at specific intervals, providing high-resolution, geographically distributed forecasts. These forecasts can include temperature, precipitation, wind speed and direction, cloud cover, and other meteorological parameters.These web services are hosted by the Office of Dissemination’s CloudGIS team, which ensures the forecasts are readily accessible and deliverable over the internet. Users, including meteorologists, developers, and anyone interested in weather data, can query these web services for up-to-date forecasts in a digital format, enabling integration into applications, websites, and other platforms.NDFD’s Web Services Descriptions:12-Hour Probability of Precipitation Web Service's data layer is the likelihood, expressed as a percent, of a measurable precipitation event (1/100th of an inch or more) at a grid point during the 12-hour valid period. The 12-hour valid periods begin and end at 0000 and 1200 Coordinated Universal Time (UTC).Apparent Temperature Web Service: contains data that is the perceived temperature derived from either a combination of temperature and wind (Wind Chill) or temperature and humidity (Heat Index) for the indicated hour. When the temperature at a particular grid point falls to 50 F or less, wind chill will be used for that point for the Apparent Temperature. When the temperature at a grid point rises above 80 F, the heat index will be used for Apparent Temperature. Between 51 and 80 F, the Apparent Temperature will be the ambient air temperature.Dew Point Temperature Web Service's data is the expected dew point temperature for the indicated hour. Dew point temperature is a measure of atmospheric moisture. It is the temperature to which air must be cooled in order to reach saturation (assuming air pressure and moisture content are constant).Maximum Temperature Web Service's data is the daytime maximum temperature observed from 7 AM to 7PM LST.Minimum Temperature Web Service's data is predicted minimum temperature for a specific location at a given time, allowing users to visualize the lowest expected temperatures across a geographical area.Precipitation Amount Web Service's data is the expected quantity of liquid precipitation accumulated over a six-hourly period. A quantitative precipitation forecast (QPF) will be specified when a measurable (1/100th of an inch or more) precipitation type is forecast for any hour during a QPF valid period. NDFD valid periods for QPF are 6 hours long beginning and ending at 0000, 0600, 1200 and 1800 UTC. QPF includes the liquid equivalent amount for snow and ice.Relative Humidity Web Service's data is a ratio, expressed as a percent, of the amount of atmospheric moisture present relative to the amount that would be present if the air were saturated. Since the latter amount is dependent on temperature, relative humidity is a function of both moisture content and temperature.Sky Cover Web Service’s data is the predicted percentage of the sky that will be covered by opaque clouds at a given time, provided by the National Digital Forecast Database (NDFD). It is a forecast of how much of the sky will be obscured by clouds, expressed as a percentage value.Snow Amount Web Service's data is the expected total accumulation of new snow during a 6-hour period. A snow accumulation grid will be specified whenever a measurable snowfall is forecast for any hour during a valid period. Valid periods for the NDFD begin and end at 0600, 1200, 1800, and 0000 UTC.Temperature Web Service: contains data that is the expected temperature in degrees Fahrenheit valid for the indicated hour.Wave Height Web Service's data is the average height (from trough to crest) of the one-third highest waves valid for the top of the designated hour. Wave Height is a combination of wind waves and swell.Wind Direction Web Service's data is the expected sustained 10-meter wind direction for the indicated hour, using 36 points of a compass.Wind Gust Web Service's data is the maximum 3-second wind speed forecast to occur within a 2-minute interval at a height of 10 meters. Wind gust forecasts are valid at the top of the indicated hour.Wind Speed Web Service's data is the expected sustained 10-meter sustained wind speed for the indicated hour.Wind Speed and Direction Web Service's data is the expected sustained 10-meter wind direction for the indicated hour, using 36 points of a compass. Wind Speed is the expected sustained 10-meter sustained wind speed for the indicated hour. Wind barbs (shown below) are used to denote wind speed and direction.Update Frequency: The data in these service updates hourly. (Click here to see specific Valid Times for update Frequency)Link to graphical web page: https://digital.weather.govLink to data download (grib2): https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/Link to metadataQuestions/Concerns about the service, please contact the DISS GIS teamTime Information:These web services are time-enabled, meaning that each individual layer contains time-varying data and can be utilized by clients capable of making map requests that include a time component.These particular services can be queried with or without the use of a time component. If the time parameter is specified in a request, the data or imagery most relevant to the provided time value, if any, will be returned. If the time parameter is not specified in a request, the latest data or imagery valid for the present system time will be returned to the client. If the time parameter is not specified and no data or imagery is available for the present time, no data will be returned.Valid Time Table:ServiceValid Time12-Hour Probability of Precipitation Web ServiceThe 12-hour valid periods begin and end at 0000 and 1200 Coordinated Universal Time (UTC).Apparent Temperature Web ServiceCONUS displays every hourOCONUS displays every 3 hours (3z,6z,9z,12z etc.)Dew Point Temperature Web ServiceCONUS displays every hourOCONUS displays every 3 hours (3z,6z,9z,12z etc.)Maximum Temperature Web ServiceDisplay 0z every dayMinimum Temperature Web ServiceDisplay at 12z every dayPrecipitation Amount Web ServiceCONUS/OCONUS (forecast is valid at 0z,6z,12z and 18z)Relative Humidity Web ServiceCONUS displays every hourOCONUS displays every 3 hours (3z,6z,9z,12z etc.)Sky Cover Web ServiceCONUS displays every hourOCONUS displays every 3 hours (3z,6z,9z,12z etc.)Snow Amount Web ServiceCONUS/OCONUS (forecast is valid at 0z,6z,12z and 18z)Temperature Web ServiceCONUS displays every hourOCONUS displays every 3 hours (3z,6z,9z,12z etc.)Wave Height Web ServiceCONUS displays every hourOCONUS displays every 3 hours (3z,6z,9z,12z etc.)Wind Direction Web ServiceCONUS displays every hourOCONUS displays every 3 hours (3z,6z,9z,12z etc.)Wind Gust Web ServiceCONUS displays every hourOCONUS displays every 3 hours (3z,6z,9z,12z etc.)Wind SpeedCONUS displays every hourOCONUS displays every 3 hours (3z,6z,9z,12z etc.)Wind Speed and Direction Web ServiceCONUS displays every hourOCONUS displays every 3 hours (3z,6z,9z,12z etc.)

National Digital Forecast Database (NDFD) MetadataThe National Digital Forecast Database (NDFD) Web Services provide a set of gridded weather forecasts for various sensible weather elements in near real-time. These forecasts are generated by a collaboration between the National Weather Service (NWS) field offices and the National Centers for Environmental Prediction (NCEP). The NDFD Web Services offer a seamless, digital mosaic of weather forecasts that can be accessed by users to obtain up-to-date information on a variety of weather conditions.The NDFD's forecasts are gridded, meaning they cover large geographic areas with weather data at specific intervals, providing high-resolution, geographically distributed forecasts. These forecasts can include temperature, precipitation, wind speed and direction, cloud cover, and other meteorological parameters.These web services are hosted by the Office of Dissemination’s CloudGIS team, which ensures the forecasts are readily accessible and deliverable over the internet. Users, including meteorologists, developers, and anyone interested in weather data, can query these web services for up-to-date forecasts in a digital format, enabling integration into applications, websites, and other platforms.NDFD’s Web Services Descriptions:12-Hour Probability of Precipitation Web Service's data layer is the likelihood, expressed as a percent, of a measurable precipitation event (1/100th of an inch or more) at a grid point during the 12-hour valid period. The 12-hour valid periods begin and end at 0000 and 1200 Coordinated Universal Time (UTC).Apparent Temperature Web Service: contains data that is the perceived temperature derived from either a combination of temperature and wind (Wind Chill) or temperature and humidity (Heat Index) for the indicated hour. When the temperature at a particular grid point falls to 50 F or less, wind chill will be used for that point for the Apparent Temperature. When the temperature at a grid point rises above 80 F, the heat index will be used for Apparent Temperature. Between 51 and 80 F, the Apparent Temperature will be the ambient air temperature.Dew Point Temperature Web Service's data is the expected dew point temperature for the indicated hour. Dew point temperature is a measure of atmospheric moisture. It is the temperature to which air must be cooled in order to reach saturation (assuming air pressure and moisture content are constant).Maximum Temperature Web Service's data is the daytime maximum temperature observed from 7 AM to 7PM LST.Minimum Temperature Web Service's data is predicted minimum temperature for a specific location at a given time, allowing users to visualize the lowest expected temperatures across a geographical area.Precipitation Amount Web Service's data is the expected quantity of liquid precipitation accumulated over a six-hourly period. A quantitative precipitation forecast (QPF) will be specified when a measurable (1/100th of an inch or more) precipitation type is forecast for any hour during a QPF valid period. NDFD valid periods for QPF are 6 hours long beginning and ending at 0000, 0600, 1200 and 1800 UTC. QPF includes the liquid equivalent amount for snow and ice.Relative Humidity Web Service's data is a ratio, expressed as a percent, of the amount of atmospheric moisture present relative to the amount that would be present if the air were saturated. Since the latter amount is dependent on temperature, relative humidity is a function of both moisture content and temperature.Sky Cover Web Service’s data is the predicted percentage of the sky that will be covered by opaque clouds at a given time, provided by the National Digital Forecast Database (NDFD). It is a forecast of how much of the sky will be obscured by clouds, expressed as a percentage value.Snow Amount Web Service's data is the expected total accumulation of new snow during a 6-hour period. A snow accumulation grid will be specified whenever a measurable snowfall is forecast for any hour during a valid period. Valid periods for the NDFD begin and end at 0600, 1200, 1800, and 0000 UTC.Temperature Web Service: contains data that is the expected temperature in degrees Fahrenheit valid for the indicated hour.Wave Height Web Service's data is the average height (from trough to crest) of the one-third highest waves valid for the top of the designated hour. Wave Height is a combination of wind waves and swell.Wind Direction Web Service's data is the expected sustained 10-meter wind direction for the indicated hour, using 36 points of a compass.Wind Gust Web Service's data is the maximum 3-second wind speed forecast to occur within a 2-minute interval at a height of 10 meters. Wind gust forecasts are valid at the top of the indicated hour.Wind Speed Web Service's data is the expected sustained 10-meter sustained wind speed for the indicated hour.Wind Speed and Direction Web Service's data is the expected sustained 10-meter wind direction for the indicated hour, using 36 points of a compass. Wind Speed is the expected sustained 10-meter sustained wind speed for the indicated hour. Wind barbs (shown below) are used to denote wind speed and direction.Update Frequency: The data in these service updates hourly. (Click here to see specific Valid Times for update Frequency)Link to graphical web page: https://digital.weather.govLink to data download (grib2): https://tgftp.nws.noaa.gov/SL.us008001/ST.opnl/DF.gr2/DC.ndfd/Link to metadataQuestions/Concerns about the service, please contact the DISS GIS teamTime Information:These web services are time-enabled, meaning that each individual layer contains time-varying data and can be utilized by clients capable of making map requests that include a time component.These particular services can be queried with or without the use of a time component. If the time parameter is specified in a request, the data or imagery most relevant to the provided time value, if any, will be returned. If the time parameter is not specified in a request, the latest data or imagery valid for the present system time will be returned to the client. If the time parameter is not specified and no data or imagery is available for the present time, no data will be returned.Valid Time Table:ServiceValid Time12-Hour Probability of Precipitation Web ServiceThe 12-hour valid periods begin and end at 0000 and 1200 Coordinated Universal Time (UTC).Apparent Temperature Web ServiceCONUS displays every hourOCONUS displays every 3 hours (3z,6z,9z,12z etc.)Dew Point Temperature Web ServiceCONUS displays every hourOCONUS displays every 3 hours (3z,6z,9z,12z etc.)Maximum Temperature Web ServiceDisplay 0z every dayMinimum Temperature Web ServiceDisplay at 12z every dayPrecipitation Amount Web ServiceCONUS/OCONUS (forecast is valid at 0z,6z,12z and 18z)Relative Humidity Web ServiceCONUS displays every hourOCONUS displays every 3 hours (3z,6z,9z,12z etc.)Sky Cover Web ServiceCONUS displays every hourOCONUS displays every 3 hours (3z,6z,9z,12z etc.)Snow Amount Web ServiceCONUS/OCONUS (forecast is valid at 0z,6z,12z and 18z)Temperature Web ServiceCONUS displays every hourOCONUS displays every 3 hours (3z,6z,9z,12z etc.)Wave Height Web ServiceCONUS displays every hourOCONUS displays every 3 hours (3z,6z,9z,12z etc.)Wind Direction Web ServiceCONUS displays every hourOCONUS displays every 3 hours (3z,6z,9z,12z etc.)Wind Gust Web ServiceCONUS displays every hourOCONUS displays every 3 hours (3z,6z,9z,12z etc.)Wind SpeedCONUS displays every hourOCONUS displays every 3 hours (3z,6z,9z,12z etc.)Wind Speed and Direction Web ServiceCONUS displays every hourOCONUS displays every 3 hours (3z,6z,9z,12z etc.)

A typical BUOY reading contains data for the current air and water temperatures, dew point, both wind and wave speed and direction, visibility, tide height, and barometric pressure.

This map contains live feed sources for US current wildfire locations and perimeters, VIIRS and MODIS hot spots, wildfire conditions / red flag warnings, and wildfire potential. Each of these layers provides insight into where a fire is located, its intensity and the surrounding areas susceptibility to wildfire. Find out more about the Esri Disaster Response Program: www.esri.com/disaster About the Data: Click on the links in the LAYERS section for details about each layer Wildfire: This displays large active fire incidents and situation reports that have been entered into the National Interagency Fire Center (NIFC) database by local emergency response teams. The final official perimeter should be obtained from the host unit, which can be determined by looking at the Unit Id for any specific fire. The host unit is responsible for producing official and final perimeters for all incidents in their jurisdiction.Hot Spot: The MODIS and VIIRS thermal layers are created from the MODIS satellite detection system and represents hot spots that could be potential fire locations in the last 24 hour period at a horizontal resolution of 1 km and temporal resolution of 1 to 2 days. Wind Data (NOAA METAR): Typical METAR contains data for the temperature, dew point, wind speed and direction, precipitation, cloud cover and heights, visibility, and barometric pressure. A METAR may also contain information on precipitation amounts, lightning, and other information. Red Flag Warnings: Filtered from the Weather Watches and Warnings layer.