202624_smap

Dates of Images: September 24, 2026 (0 UTC) to September 25, 2026 (0 UTC) Date of Next Image: Daily accumulation from September 24, updated as frequently as the following day at 1500 UTC. Summary: GPM IMERG Early Precipitation Rate L3 V07(GPM IMERG Early Precipitation L3 Half Hourly 0.1 degree x 0.1 degree V07 (GPM_3IMERGHHE 07))is an image service derived from the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM) Early dataset. The web service shows total precipitation (mm) for the date range outlined by aggregating 30-minute intervals. IMERG is an algorithm that estimates precipitation rate from multiple passive microwave sensors in the GPM constellation, the GPM Dual-Frequency Radar, and infrared (IR) sensors mounted on geostationary satellites. The data is calibrated seasonally and regionally with varying climatological calibration to the Final Run, which adjusts the Early based on the climatological relationship between Early and monthly gauge data. Input precipitation data estimates computed from the various satellite passive microwave sensors are intercalibrated to the Combined Radar-Radiometer Algorithm (CORRA) product (because it is presumed to be the best snapshot Tropical Rainfall Measuring Mission (TRMM)/GPM estimate after adjustment to the monthly Global Precipitation Climatology Project Satellite-Gauge (GPCP SG)), then "forward morphed" and combined with microwave precipitation-calibrated geo-IR fields to provide half-hourly precipitation estimates on a 0.1°x0.1° (roughly 10x10 km) grid over the globe. Precipitation phase is computed using analyses of surface temperature, humidity, and pressure. Credits: Huffman, G.J., E.F. Stocker, D.T. Bolvin, E.J. Nelkin, Jackson Tan (2024), GPM IMERG Early Precipitation L3 Half Hourly 0.1 degree x 0.1 degree V07, Greenbelt, MD, Goddard Earth Sciences Data and Information Services Center (GES DISC), Accessed [Data Access Date], 10.5067/GPM/IMERG/3B-HH-E/07 Data Access: This data was accessed using Giovanni with a sample URL as follows:https://giovanni.gsfc.nasa.gov/giovanni/#service=AcMp&starttime=2026-04-10T00:00:00Z&endtime=2026-04-16T23:59:59Z&bbox=130.0781,-3.3838,163.125,26.8506&data=GPM_3IMERGHHL_07_precipitation Dataset at a Glance: Shortname: GPM_3IMERGHHE DOI:10.5067/GPM/IMERG/3B-HH-E/07 Version: 07 Coverage: -180.0,-90.0,180.0,90.0 Temporal Coverage: 1998-01-01 to Present Data Resolution: Spatial: 0.1 ° x 0.1 ° Temporal: 30 minutes Symbology: The default symbology in the Map Viewer may be changed to accommodate other color schemes using the settings in the Image Display panel from the layer settings menu. NoData values, and values less than 0.03 mm/hr (the current threshold value for the IMERG algorithm) have been removed. Ensure that pop-ups are enabled to view pixel values (select Modify Map first).

Dates Available: April 2021 - Present Update Frequency: Twice a day Summary: Landslides are a widespread and often underestimated natural hazard, causing thousands of deaths and significant economic damage each year. They routinely block roads, destroy infrastructure, and disrupt communities worldwide. While intense or prolonged rainfall is the most common landslide trigger, earthquakes and human activities can also cause them. The global Landslide Hazard Assessment for Situational Awareness (LHASA) model provides users with a comprehensive view of landslide hazard in near real-time. Using machine learning, LHASA combines rainfall data from the Global Precipitation Measurement (GPM) satellite with antecedent soil moisture from the Soil Moisture Active Passive (SMAP) satellite to identify areas currently at risk from landslides. The model shows where and when landslides are most probable, then calculates the exposed population and road length within each administrative district, helping users understand both the hazard and potential impacts on communities and infrastructure. To learn more please visit: https://landslides.nasa.gov/ Suggested Use: LHASA 2.1 was created to enable global monitoring of landslide hazard and is not a substitute for local site investigations. Red indicates high hazard and blue indicates low hazard. LHASA nowcast Hazard: "yesterday", "today", and "tomorrow": This map shows the relative probability of landslide occurrence yesterday, today, and tomorrow; respectively, based on rainfall estimates from GPM and forecasts from GEOS-FP. Satellite/Sensor: GPM, SMAP Resolution: 30 arcseconds (~1 kilometer) Credits: NASA GSFC Users are requested to cite the following paper: Stanley, T. A., D. B. Kirschbaum, G. Benz, et al. 2021. "Data-Driven Landslide Nowcasting at the Global Scale." Frontiers in Earth Science, 9: [10.3389/feart.2021.640043]

Update Frequency: Daily Summary: Land Information System (LIS) 0-200 cm layer Soil Moisture Percentile generated by the NASA SPoRT Center over a Contiguous United States domain. The NASA Land Information System (LIS) is a high-performance land surface modeling and data assimilation system used to characterize land surface states and fluxes by integrating satellite-derived datasets, ground-based observations, and model re-analyses. The NASA SPoRT Center at MSFC developed a real-time configuration of the LIS (“SPoRT-LIS”), which is designed for use in experimental operations by domestic and international users. SPoRT-LIS is an observations-driven, historical and real-time modeling setup that runs the Noah land surface model over a full CONUS domain. It provides soil moisture estimates at approximately 3-km horizontal grid spacing over a 2-meter-deep soil column and has been validated for regional applications and against U.S. Drought Monitor products. SPoRT-LIS consists of a 33-year soil moisture climatology spanning from 1981 to 2013, which is extended to the present time and forced by atmospheric analyses from the operational North American Land Data Assimilation System-Phase 2 through 4 days prior to the current time, and by the National Centers for Environmental Prediction Global Data Assimilation System in combination with hourly Multi-Radar Multi-Sensor precipitation estimates from 4 days ago to the present time. A unique feature of SPoRT-LIS is the incorporation of daily, real-time satellite retrievals of VIIRS Green Vegetation Fraction since 2012, which results in more representative evapotranspiration and ultimately soil moisture estimates than using a fixed seasonal depiction of vegetation in the model. The 33-year soil moisture climatology also provides the database for real-time soil moisture percentiles evaluated for all U.S. counties and at each modeled grid point. The present-day soil moisture analyses are compared to daily historical distributions to determine the soil wet/dry anomalies for the specific day of the year. Soil moisture percentile maps are constructed for the model layers, and these data are frequently referenced by scientists and operational agencies contributing to the weekly U.S. Drought Monitor product. Suggested Use: This product can be used for drought assessment, fire risk assessment, potential for flooding hazards associated with heavy precipitation and high percentiles; contextualizing soil moisture content to historical values. Soil moisture percentiles are shown using a Classified Color Ramp (Multi-Color, 11-classes) that colorize the low percentile categories (≤ 30th) as shown in the U.S. Drought Monitor weekly products, ranging from yellow to dark red. The high percentile categories (≥ 70th) are colorized with increasing blue intensity. Intermediate percentiles in the 30th to 70th range are assigned a nominal gray shade. The 0-200 cm layer combines SPoRT-LIS soil moisture analyses from the top four model layers 0-10 cm, 10-40 cm, 40-100 cm, and 100-200cm. The 0-100 cm cumulative layer adjusts more slowly to precipitation episodes or the lack thereof compared to the 0-10 cm and 0-40 cm percentiles. It takes considerably longer time periods for intercepted rainfall and snowmelt to infiltrate from the upper 0-10 cm and 10-40 cm layers into the next model layer at 40-100 cm, or conversely for the deeper soil layer to dry from evapotranspiration processes. Expect anomalies of soil moisture percentiles in the 0-100 cm cumulative layer to respond on the order of weeks to months (or longer, especially during dry periods), depending on the soil classification and soil responsiveness. Data Caveats: The SPoRT-LIS is as good as the input forcing analyses, so occasional soil moisture artifacts may appear in the horizontal maps related to quality-control issues of the input datasets. These can be manifested with unusually low or high percentiles, especially along international borders, coastlines, and isolated dry “bulls-eyes” at rain gauge with quality issues. Data Visualization: The Soil Moisture Percentile is the histogram rank of the current day’s soil moisture value compared to the 33-year climatology for the present day. The percentile places into historical context the soil moisture to determine how unusually wet or dry, or typical the conditions are. Percentile thresholds as established by the drought community are used to categorize soil moisture dry anomalies as follows: Further Reference: NASA SPoRT project page: https://weather.ndc.nasa.gov/sport/ Real-time SPoRT-LIS viewer: https://weather.ndc.nasa.gov/sport/viewer/?dataset=lis_conus U.S. Drought Monitor page: https://droughtmonitor.unl.edu/ Esri REST Endpoint: See URL Section on right side of page

Update Frequency: Daily Summary: Land Information System (LIS) 0-200 cm layer Soil Moisture Percentile generated by the NASA SPoRT Center over a Contiguous United States domain. The NASA Land Information System (LIS) is a high-performance land surface modeling and data assimilation system used to characterize land surface states and fluxes by integrating satellite-derived datasets, ground-based observations, and model re-analyses. The NASA SPoRT Center at MSFC developed a real-time configuration of the LIS (“SPoRT-LIS”), which is designed for use in experimental operations by domestic and international users. SPoRT-LIS is an observations-driven, historical and real-time modeling setup that runs the Noah land surface model over a full CONUS domain. It provides soil moisture estimates at approximately 3-km horizontal grid spacing over a 2-meter-deep soil column and has been validated for regional applications and against U.S. Drought Monitor products. SPoRT-LIS consists of a 33-year soil moisture climatology spanning from 1981 to 2013, which is extended to the present time and forced by atmospheric analyses from the operational North American Land Data Assimilation System-Phase 2 through 4 days prior to the current time, and by the National Centers for Environmental Prediction Global Data Assimilation System in combination with hourly Multi-Radar Multi-Sensor precipitation estimates from 4 days ago to the present time. A unique feature of SPoRT-LIS is the incorporation of daily, real-time satellite retrievals of VIIRS Green Vegetation Fraction since 2012, which results in more representative evapotranspiration and ultimately soil moisture estimates than using a fixed seasonal depiction of vegetation in the model. The 33-year soil moisture climatology also provides the database for real-time soil moisture percentiles evaluated for all U.S. counties and at each modeled grid point. The present-day soil moisture analyses are compared to daily historical distributions to determine the soil wet/dry anomalies for the specific day of the year. Soil moisture percentile maps are constructed for the model layers, and these data are frequently referenced by scientists and operational agencies contributing to the weekly U.S. Drought Monitor product. Suggested Use: This product can be used for drought assessment, fire risk assessment, potential for flooding hazards associated with heavy precipitation and high percentiles; contextualizing soil moisture content to historical values. Soil moisture percentiles are shown using a Classified Color Ramp (Multi-Color, 11-classes) that colorize the low percentile categories (≤ 30th) as shown in the U.S. Drought Monitor weekly products, ranging from yellow to dark red. The high percentile categories (≥ 70th) are colorized with increasing blue intensity. Intermediate percentiles in the 30th to 70th range are assigned a nominal gray shade. The 0-200 cm layer combines SPoRT-LIS soil moisture analyses from the top four model layers 0-10 cm, 10-40 cm, 40-100 cm, and 100-200cm. The 0-100 cm cumulative layer adjusts more slowly to precipitation episodes or the lack thereof compared to the 0-10 cm and 0-40 cm percentiles. It takes considerably longer time periods for intercepted rainfall and snowmelt to infiltrate from the upper 0-10 cm and 10-40 cm layers into the next model layer at 40-100 cm, or conversely for the deeper soil layer to dry from evapotranspiration processes. Expect anomalies of soil moisture percentiles in the 0-100 cm cumulative layer to respond on the order of weeks to months (or longer, especially during dry periods), depending on the soil classification and soil responsiveness. Data Caveats: The SPoRT-LIS is as good as the input forcing analyses, so occasional soil moisture artifacts may appear in the horizontal maps related to quality-control issues of the input datasets. These can be manifested with unusually low or high percentiles, especially along international borders, coastlines, and isolated dry “bulls-eyes” at rain gauge with quality issues. Data Visualization: The Soil Moisture Percentile is the histogram rank of the current day’s soil moisture value compared to the 33-year climatology for the present day. The percentile places into historical context the soil moisture to determine how unusually wet or dry, or typical the conditions are. Percentile thresholds as established by the drought community are used to categorize soil moisture dry anomalies as follows: Further Reference: NASA SPoRT project page: https://weather.ndc.nasa.gov/sport/ Real-time SPoRT-LIS viewer: https://weather.ndc.nasa.gov/sport/viewer/?dataset=lis_conus Daily animations of experimental 2-week forecasts of SPoRT-LIS soil moisture percentiles: https://geo.nsstc.nasa.gov/SPoRT/modeling/lis/conus3km/forecasts/ NASA Land Information System project page: https://lis.gsfc.nasa.gov/ U.S. Drought Monitor page: https://droughtmonitor.unl.edu/ Esri REST Endpoint: See URL Section on right side of page

GLOBCOMP01A_HOURLY_FULL

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