Ag Blog Update 20 Oct

Ag Blog Update 20 Oct

During the 2020 growing season, Eric Hunt of Atmospheric and Environmental Research, Inc. will be providing weekly updates of the soil moisture index (SMI) from the Noah-MP land surface model in the NASA LIS framework for the entire U.S. and regional analysis of the SMI over the four regions of U.S. where the majority of corn, soybean, wheat, and cotton production occurs. The analysis is intended to provide the larger agricultural and meteorological communities insight as to areas where soil moisture is excessive or deficient compared to average for that location and what that may mean for impacts. It is my goal that these maps can be an early warning signal for flash drought development or where flash flooding could be likely in the coming week if heavy precipitation materializes. Please be advised that the SMI should be viewed as complementary, not a substitute, to the U.S. Drought Monitor (USDM) and that declarations of drought or flash flood potential for a particular location should never be based on the SMI alone. Remote sensing based products such as The Evaporative Stress Index (ESI) are also included in our analysis (when available) as are various other maps that help give insight into current conditions across the U.S.

This blog post was partially supported by NASA grant 80NSSC19K1266.

Order of Maps and Tables in today’s Ag Blog

  1. Figure 1. Soil Moisture Index map
  2. Figure 2. Driest Soils
  3. Figure 3. SMI change map
  4. Figure 4. 30-day percent of normal precipitation


The latest soil moisture index map (SMI; Figure 1) shows moist soils over Southeast and the far northwest corner of the Pacific Northwest and a lot of dry to very dry soils elsewhere. One bright spot on the current map is significant improvement in parts of New England, though the improvements was less pronounced or non-existent in parts of southern New England which are in extreme drought on the latest map of the U.S. Drought Monitor. Figure 2 also shows that the eastern Great Lakes, western Corn Belt, High Plains, southern Rockies, and northern California are all very dry. These areas are all in some level of abnormal dryness or drought on the USDM as well. As of last Thursday, over 26% of the continental United States (CONUS) has an SMI below -3.0, with higher percentages in the Great Plains and Corn Belt regions (Table 1).

This may be especially problematic in the southern Rockies and High Plains region, which traditionally does not receive significant precipitation during La Nina winter. That of course is not a guarantee that relief won’t come this winter, just that past history does not favor such an outcome. This region is also very important for grazing and winter wheat, the latter of which is likely to be adversely affected by the drought. Further to the north across the Corn Belt, Figure 3 shows that the “gains” from beneficial rain received the week of Labor Day have been mostly exhausted by a return to dry weather over the last month (Figure 4).

The beneficial aspect of the dry weather across the Corn Belt is it has helped expedite harvest, with 60 percent of corn harvested and 75 percent of soybean harvested according to the latest U.S. Crop Progress Report. Neither are on record pace, but both are above average for this week of the year. The upcoming forecast is less favorable for continued accelerated progress however, especially in the northern and western sections of the Corn Belt. The moisture would definitely be welcome across much Iowa and eastern Nebraska, which have been quite dry the past several weeks to months.

No Ag Blog next week but I’ll likely still post a few maps on Twitter next Monday.

Figure 1. Soil moisture index (SMI) map) for the 7-day period ending 15 October 2020. Results are based on output from the 0-1 m (surface to 3.23 feet) layers in the Noah-Multiparameterization (Noah-MP) land surface model. Noah-MP is run in the NASA Land Information System (LIS) framework with the North American Land Data Assimilation Version 2 (NLDAS-2) forcing dataset. The SMI calculation is based on the soil moisture index created in Hunt et al. (2009) such that ‘5’(dark green) is the wettest and ‘-5’ (dark red) the driest for the period of record.  The period of record used calculate the SMI for the current map is 1979-present.





Corn Belt




Great Plains North




Great Plains South













Table 1. The regional median SMI value from the current map and the percentage of grid points in the four regions with SMI values greater than 3.0 and less than -3.0. Regions are indicated by the boxes in Figure 2.

Figure 2. The grid points from figure 1 with an SMI at or below -3.0 on 15 October.

Figure 3. The 30-day change in the SMI between 16 September and 15 October 2020. Scale shows the color that corresponds to the direction (positive or negative) and the magnitude of the change.


Figure 4. Percent of normal precipitation over the past 30 days (through Sunday 18 October).  Map courtesy of the High Plains Regional Climate Center.

About the author:


Eric Hunt is an agricultural climatologist from Lincoln, NE and has several members of his extended family actively farming in Illinois and Nebraska. Eric has been with AER since 2012 and received his Ph.D. from the University of Nebraska. Among other activities, he is currently working on NASA funded projects to study the evolution of flash drought. He routinely blogs about agriculture and weather on the AER website. He can be reached via email at and @DroughtLIS on Twitter.

About AER:

Founded in 1977, Atmospheric and Environmental Research is an award-winning environmental research, consulting and weather information services company with demonstrated expertise in numerical weather prediction, climate dynamics and radiation, circulation diagnostics, atmospheric chemistry, air quality and risk assessment, planetary sciences, remote sensing, satellite meteorology, and systems engineering. Consulting services are available. AER is a business unit of Verisk Analytics (VRSK). For more information, please visit our web site at

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