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Recent Cold Front Brings Snow And Needed Moisture To Kansas

Snow fell for the first time this fall across many parts of Kansas on November 14.  While amounts were not particularly heavy, measurable snow was observed in many parts of the state.  After a warm autumn, this recent cold spell and associated snow was an abrupt change in the weather for most of Kansas. The latest Drought Monitor reports that almost 70% of Kansas is under severe to exceptional drought. In times like this, every precipitation event, rain or snow, is important. In this report, we take a closer look at average snowfall totals across Kansas and what snow means in terms of added moisture to the soil.

Snow amounts for November 14, 2022

For the snow event on November 14, a few locations exceeded their November average.  As much as 5 inches of snow was reported in the southwest part of the state, in Stevens, Gray, Haskell and Grant counties.  Lesser amounts from 2 to 3 inches were reported in parts of central Kansas, and from 0.5 to 2 inches across much of eastern Kansas.  Much of this snow melted the next day, with sunshine and above-freezing temperatures, but it’s a reminder that winter is just around the corner. 

Average snowfall for Kansas

Monthly average snowfall amounts for 45 locations, five within each climate division, are listed in Table 1, along with cumulative totals for those months with non-zero snowfall: September through May, although not all sites average snow in all months.  Divisional averages for each set of five cities appear in Table 2. 

Average snowfall for a “snow year”, defined here as the period from July 1-June 30, ranges from 6 to 30 inches across the state, with a statewide average of 16 inches.  Goodland has the highest amount, 30 inches, helped in part by being one of only four locations that averages a small amount of snow in September.  Goodland averages 3.3 inches in November, second only to Colby for the largest November amount in the state.  All locations average some snow in November, but the statewide average is only 1.2 inches. 

About 70% of the total snow that falls in a snow year typically occurs between December and February.  That’s from 5 to 16 inches of snow depending on your location in the state.  The snowiest month varies around the state.  In Salina, December is the snowiest month on average.  In Garden City, it’s January, and in Goodland, it’s February.  But these numbers are 30-year averages; every year is different.  In 2013-14, Manhattan had 41.1 inches.  Three years later, in 2016-17, there was only 3.2 inches.  One strong winter storm could drop the majority of the accumulation in any given snow year.  In December 2005, Manhattan had 12 inches of snow from a single storm, and only 6.7 inches in the other months of the 2005-2006 snow year.  If you missed out snow this week, there are still plenty of time as we move into meteorological winter in just two weeks, starting on December 1.

Table 1.  Monthly snowfall averages for various locations around KansasThese averages are 30-year normals, based on the period 1991-2020, as calculated by the National Weather Service.

 

City

Sep

Oct

Nov

Dec

Jan

Feb

Mar

Apr

May

Total

Northwest

Colby

0.2

1.6

3.5

3.9

5.1

5.8

4.2

2.2

0.7

27.2

Goodland

0.2

2.0

3.3

5.2

4.7

6.3

4.8

3.2

0.3

30.0

Hill City

0.0

0.7

1.5

3.8

3.3

5.5

2.1

0.3

0.2

17.4

Oberlin

0.0

1.3

2.3

4.2

5.7

6.2

3.4

1.9

0.2

25.2

St. Francis

0.3

0.9

2.0

2.9

4.6

4.5

2.9

1.7

0.0

19.8

North Central

Cawker City

0.0

0.3

1.6

3.5

4.5

5.8

1.7

0.5

0.0

17.9

Concordia

0.0

0.3

1.9

4.5

5.4

5.2

1.6

0.4

0.0

19.3

Minneapolis

0.0

0.3

1.6

4.5

4.7

3.4

2.2

0.9

0.0

17.6

Phillipsburg

0.0

0.7

1.1

3.2

3.4

6.6

1.5

0.5

0.0

17.0

Washington

0.0

0.1

1.0

2.4

4.6

4.6

1.4

0.3

0.0

14.4

Northeast

Atchison

0.0

0.3

0.9

3.8

5.0

4.8

1.8

0.4

0.0

17.0

Bonner Springs

0.0

0.3

1.1

4.3

5.0

5.1

1.5

0.1

0.0

17.4

Hiawatha

0.0

0.0

1.2

3.6

4.7

4.1

2.2

1.1

0.0

16.9

Manhattan

0.0

0.0

1.1

4.8

4.8

5.0

1.8

0.1

0.0

17.6

Marysville

0.0

0.1

1.0

3.3

4.9

4.3

1.5

0.7

0.0

15.8

West

Central

Ness City

0.0

0.4

1.3

3.2

3.2

3.5

3.3

0.4

0.1

15.4

Oakley

0.0

1.2

2.5

4.5

4.5

6.6

4.2

1.8

0.4

25.7

Scott City

0.0

1.2

1.1

3.1

4.5

4.0

3.9

1.8

0.0

19.6

Tribune

0.1

1.3

2.1

3.8

4.2

4.2

3.6

2.1

0.3

21.7

WaKeeney

0.0

1.1

1.8

4.3

4.3

4.3

3.2

1.3

0.0

20.3

Central

Abilene

0.0

0.2

1.0

2.2

4.1

2.8

1.7

0.2

0.0

12.2

Great Bend

0.0

0.1

1.7

2.3

2.2

2.6

2.3

0.3

0.0

11.5

Hays

0.0

0.3

1.4

3.3

3.4

4.8

2.1

0.5

0.0

15.8

McPherson

0.0

0.1

0.6

2.9

4.1

3.3

2.6

0.6

0.0

14.2

Salina

0.0

0.5

1.4

4.1

3.8

4.0

1.3

0.4

0.0

15.5

East

Central

Council Grove

0.0

0.4

0.5

2.8

4.0

2.9

1.2

0.2

0.0

12.0

Emporia

0.0

0.1

1.4

3.9

5.5

4.1

1.0

0.3

0.0

16.3

Garnett

0.0

0.5

0.4

3.0

4.8

2.5

1.4

0.2

0.0

12.8

Olathe

0.0

0.3

1.2

3.4

3.9

3.3

1.4

0.3

0.0

13.8

Topeka

0.0

0.4

1.0

4.1

4.6

5.2

1.7

0.1

0.0

17.1

Southwest

Ashland

0.0

0.1

0.5

3.2

2.3

3.6

1.8

0.1

0.0

11.6

Dodge City

0.0

0.6

1.4

4.0

3.9

4.7

3.7

0.8

0.0

19.1

Elkhart

0.0

0.7

1.2

4.7

4.2

2.1

3.5

0.4

0.8

17.6

Garden City

0.0

0.8

1.0

2.7

3.4

3.3

3.2

1.1

0.1

15.6

Liberal

0.0

0.7

1.0

4.6

3.5

1.8

2.3

0.4

0.1

14.4

South

Central

Greensburg

0.0

0.4

1.4

3.6

4.5

2.6

3.8

0.0

0.0

16.3

Hutchinson

0.0

0.0

0.7

3.1

3.5

1.9

2.3

0.3

0.0

11.8

Medicine Lodge

0.0

0.0

0.3

2.1

2.1

4.0

0.8

0.1

0.0

9.4

Pratt

0.0

0.1

0.4

2.6

3.6

3.9

4.1

0.4

0.0

15.1

Wichita

0.0

0.2

0.8

3.1

2.7

3.6

2.1

0.2

0.0

12.7

Southeast

Arkansas City

0.0

0.0

0.2

1.9

1.8

1.1

1.1

0.1

0.0

6.2

Coffeyville

0.0

0.0

0.6

3.2

1.8

1.4

1.3

0.0

0.0

8.3

Eureka

0.0

0.1

0.5

3.0

2.8

1.2

0.9

0.1

0.0

8.6

Fort Scott

0.0

0.0

0.4

2.3

3.9

1.0

0.7

0.1

0.0

8.4

Pittsburg

0.0

0.0

0.6

2.9

3.4

1.0

1.6

0.0

0.0

9.5

Table 2. Monthly snowfall averages by climate division.

Division

Sep

Oct

Nov

Dec

Jan

Feb

Mar

Apr

May

Total

Northwest

0.1

1.3

2.5

4.0

4.7

5.7

3.5

1.9

0.3

23.9

North Central

0.0

0.3

1.4

3.6

4.5

5.1

1.7

0.5

0.0

17.2

Northeast

0.0

0.1

1.1

4.0

4.9

4.7

1.8

0.5

0.0

16.9

West Central

0.0

1.0

1.8

3.8

4.1

4.5

3.6

1.5

0.2

20.5

Central

0.0

0.2

1.2

3.0

3.5

3.5

2.0

0.4

0.0

13.8

East Central

0.0

0.3

0.9

3.4

4.6

3.6

1.3

0.2

0.0

14.4

Southwest

0.0

0.6

1.0

3.8

3.5

3.1

2.9

0.6

0.2

15.7

South Central

0.0

0.1

0.7

2.9

3.3

3.2

2.6

0.2

0.0

13.1

Southeast

0.0

0.0

0.5

2.7

2.7

1.1

1.1

0.1

0.0

8.2

Statewide

0.0

0.5

1.2

3.5

4.0

3.8

2.3

0.6

0.1

16.0

How much moisture is in snow?

Several terms are used when talking about how much moisture is contained in a certain amount of snow. In Kansas, the most frequently used term is often liquid equivalent. This is the depth of water that would result from melting a sample of snow. Liquid equivalent is the amount of measurable moisture if the snow were to have fallen as rain. This is where the infamous “10-to-1” ratio has its roots. The “10-to-1” ratio is the assumption that for every 10 inches of snow that falls, there is roughly 1 inch of actual moisture. This ratio is actually only an estimate and is based on snow forming in the 28-34 degrees F range. If temperatures are colder, say in the 10 to 15 degree F range, estimates can be as high as 30-to-1 (30 inches of snow equal to 1 inch of moisture/precipitation). This is a simplified estimation because snow liquid equivalent is also subject to temperature and humidity above the surface as well. Historically, average Kansas snow ranges from 12-14 inches per 1 inch of moisture (Figure 1).

For the recent snow event on November 14, the Dodge City National Weather Service office measured 1.9 inches of snow. The liquid amount of the melted snow reported was 0.11 inches. This results in a snow-to-liquid ratio of 17.3. During the snowfall, surface temperatures ranged from 23 to 26 degrees F, so ratios higher than 10-to-1 are expected. Other ratios from this event include 14.5 at Larned (3.2 inches snow, 0.22 inches liquid), 14.0 at Hugoton (2.8 inches snow, 0.20 inches liquid) and 12.5 at Minneapolis (2.5 inches snow, 0.20 inches liquid).

Source : ksu.edu

Trending Video

Turning Plant Defense Into a Management Strategy

Video: Turning Plant Defense Into a Management Strategy

Turning Plant Defense Into a Management Strategy

Understanding how a plant responds to stress is one thing.

Using that knowledge to make better management decisions is another.

Systemic acquired resistance, or SAR, is the plant's more direct defense response. When stress or infection occurs, the plant begins signaling throughout its system and preparing defensive compounds.

But if we know that response exists, can we help prepare the plant before the stress arrives?

The answer starts with understanding what triggers the response and what the plant needs to carry it out.

The Trigger and the Fuel

Salicylic acid plays an important role in triggering the SAR pathway.

Think of it as turning the truck on.

The engine may be running, but it still needs fuel to do the work.

In this case, manganese plays an important role in supporting the enzyme systems involved in the plant's defensive response.

This makes manganese status an important part of the conversation. Whether a producer is using tissue testing, sap analysis, or simply scouting for visible deficiency symptoms, the goal is to make sure the plant has adequate manganese available.

Manganese is required in relatively small amounts, but that does not make its role small.

If the plant receives a signal to defend itself but lacks the nutrition needed to support that response, it may struggle to carry out the process efficiently.

The trigger matters.

The fuel matters too.

Prepare Before the Stress Arrives

The best time to think about stress management is before the plant is overwhelmed.

Once a crop is already struggling, management can quickly turn into a game of catch-up.

This is similar to nitrogen management. Once a plant becomes severely deficient, correcting the problem does not necessarily erase the time and yield potential already lost.

Plant defense can work the same way.

Low-rate, targeted approaches designed to support the SAR pathway may fit best ahead of an expected stress event rather than after significant damage has already occurred.

That requires producers to think about predictable stress.

We may not know exactly what the weather will do tomorrow, but we generally know summer heat is coming. We know certain field conditions increase disease pressure. We know a herbicide application can temporarily stress a crop as the plant processes the chemistry.

Even a properly timed and labeled herbicide application can create a temporary response in the plant.

That does not mean the herbicide is bad.

Weeds can create significantly more yield loss than the temporary stress caused by controlling them.

The question is not whether we should eliminate every stressor.

The question is whether we can better prepare the plant to manage necessary and predictable stress.

Not All Stress Is Bad

Stress is a normal part of plant growth.

A perfectly stress-free environment does not exist in the field.

In fact, some stress is necessary for normal plant development. A plant responds to wind, temperature, moisture, sunlight, and countless other environmental signals throughout the season.

The environment is stress.

The plant's job is to manage it.

Problems begin when the stress load becomes greater than the plant's ability to respond.

Extreme heat, drought, high salt concentrations, disease pressure, and even certain management practices can add to that load.

This is where understanding SAR becomes useful.

Instead of waiting until the plant is visibly struggling, producers can begin identifying periods when stress is likely and make management decisions around those windows.

ISR Starts With the Soil

While SAR is a more direct defense response, induced systemic resistance, or ISR, brings the conversation back to soil health.

The longevity of a farm is closely connected to the health of its soil.

Carbon plays a major role because it supports biological life within the soil. Bacteria, fungi, and other organisms interact with plant roots and influence how the plant grows, accesses nutrients, and prepares for stress.

This is why soil health cannot be reduced to one product or one application.

It is a system.

Keeping living plants in the field longer can support biological activity. Cover crops may fit some operations. Better water management can improve soil conditions.