GLDAS Soil Moisture 2000 - Present

<div>Soils and soil moisture greatly influence the water cycle and have impacts on runoff, flooding and agriculture. Soil type and soil particle composition (sand, clay, silt) affect soil moisture and the ability of the soil to retain water. Soil moisture is also affected by levels of evaporation and plant transpiration, potentially leading to near dryness and eventual drought.</div><div><br /></div><div>Measuring and monitoring soil moisture can ensure the fitness of your crops and help predict or prepare for flash floods and drought. The GLDAS soil moisture data is useful for modeling these scenarios and others, but only at global scales. </div><div><br /></div><div><font size='3'>Dataset Summary</font></div><div><font size='3'><br /></font></div><div>The GLDAS Soil Moisture layer is a time-enabled image service that shows average monthly soil moisture from 2000 to the present, measured as the millimeters of water contained within four different depth levels. It is calculated by NASA using the Noah land surface model, run at 0.25 degree spatial resolution using satellite and ground-based observational data from the Global Land Data Assimilation System (GLDAS-2.1). The model is run with 3-hourly time steps and aggregated into monthly averages. Review the complete list of model <a href='https://ldas.gsfc.nasa.gov/gldas/GLDASforcing.php' rel='nofollow ugc' target='_blank'>inputs</a><span>, explore the </span><a href='https://hydro1.gesdisc.eosdis.nasa.gov/data/GLDAS/GLDAS_NOAH025_M.2.1/' rel='nofollow ugc' target='_blank'>output</a> data (in GRIB format), and see the full Hydrology <a href='https://disc.gsfc.nasa.gov/datasets?keywords=Hydrology' rel='nofollow ugc' target='_blank'>Catalog</a> for all related data and information!</div><div><br /></div><div><b>Phenomenon Mapped:</b> Soil Moisture</div><div><b>Units:</b> Millimeters</div><div><b>Time Interval:</b> Monthly</div><div><b>Time Extent:</b> 2000/01/01 to present</div><div><b>Cell Size:</b> 28 km</div><div><b>Source Type</b>: Scientific</div><div><b>Pixel Type</b>: Signed Integer</div><div><b>Data Projection</b>: GCS WGS84</div><div><b>Mosaic Projection: </b>Web Mercator Auxiliary Sphere</div><div><b>Extent:</b> Global Land Surface</div><div><b>Source:</b> NASA</div><div><b>Update Cycle:</b> Sporadic</div><div><br /></div><div><font size='3'>What can you do with this layer?</font></div><div><br /></div><div>This layer is suitable for both visualization and analysis. It can be used in ArcGIS Online in web maps and applications and can be used in ArcGIS Desktop. The GLDAS soil moisture data is useful for modeling, but only at global scales. </div><div><br /></div><div>By applying the &quot;Calculate Anomaly&quot; processing template, it is also possible to view these data in terms of deviation from the mean. Mean soil moisture for a given month is calculated over the entire period of record - 2000 to present.</div><div><br /></div><div><b>Time:</b> This is a time-enabled layer. By default, it will show the first month from the map's time extent. Or, if time animation is disabled, a time range can be set using the layer's multidimensional settings. If you wish to calculate the average, sum, or min/max over the time extent, change the mosaic operator used to resolve overlapping pixels. In ArcGIS Online, you do this in the &quot;Image Display Order&quot; tab. In ArcGIS Pro, use the &quot;Data&quot; ribbon. In ArcMap, it is in the 'Mosaic' tab of the layer properties window. If you do this, make sure to also select a specific variable. The minimum time extent is one month, and the maximum is 8 years. </div><div><br /></div><div><b>Variables:</b> This layer has five variables, corresponding to different depth levels. By default total is shown, but you can view an individual depth level using the multidimensional filter, or by applying the relevant raster function. </div><div><br /></div><div><b>Important:</b> You must switch from the cartographic renderer to the analytic renderer in the processing template tab in the layer properties window before using this layer as an input to geoprocessing tools.</div><div><br /></div>