Future Weather Predictions

Aug 30, 2017

By Jim Noel

During August the weather and climate pattern switched where areas of the western half of the corn and soybean belt that needed rain got it while the eastern half dried out. Rainfall the last 30-days has been 2-6 inches with isolated totals to 10 inches in the western half of the region to 0.50 to 2.00 inch eastern areas including Ohio.

Through Labor Day it does look like some much needed rain for Ohio with some of the moisture of the remnants of Harvey. Rainfall is expected to range from 0.50 to 1.50 inches across Ohio on average with isolated totals higher or lower due to thunderstorms.

The latest 16-day average rainfall outlook from the NOAA/NWS/Ohio River Forecast Center can be seen here in the graphic.

For September, we expect a return to normal or below normal precipitation and near normal temperatures once we get past Labor Day.

The outlook still looks like it will turn wetter starting about October during harvest season and likely continuing into winter.

The outlook for frost in Ohio will likely be normal to a week later than normal as soil moisture is good and increasing chance for rain by late September into October should help delay frost slightly.

You can get the latest rainfall consensus estimates at 10 km resolution from both NOAA/NWS and Environment Canada at:

http://mrcc.isws.illinois.edu/gismaps/naprecip.htm

You can get the latest National Weather Service Estimates of Rainfall from:

http://water.weather.gov/precip/

Source: osu.edu

Video: Seeing the Whole Season: How Continuous Crop Modeling Is Changing Breeding

Plant breeding has long been shaped by snapshots. A walk through a plot. A single set of notes. A yield check at the end of the season. But crops do not grow in moments. They change every day.

In this conversation, Gary Nijak of AerialPLOT explains how continuous crop modeling is changing the way breeders see, measure, and select plants by capturing growth, stress, and recovery across the entire season, not just at isolated points in time.

Nijak breaks down why point-in-time observations can miss critical performance signals, how repeated, season-long data collection removes the human bottleneck in breeding, and what becomes possible when every plot is treated as a living data set. He also explores how continuous modeling allows breeding programs to move beyond vague descriptors and toward measurable, repeatable insights that connect directly to on-farm outcomes.

This conversation explores:

• What continuous crop modeling is and how it works

• Why traditional field observations fall short over a full growing season

• How scale and repeated measurement change breeding decisions

• What “digital twins” of plots mean for selection and performance

• Why data, not hardware, is driving the next shift in breeding innovation As data-driven breeding moves from research into real-world programs, this discussion offers a clear look at how seeing the whole season is reshaping value for breeders, seed companies, and farmers, and why this may be only the beginning.