The Need for Climate Prediction Information for Agriculture*

AgMRC Renewable Energy & Climate Change Newsletter
August 2011

Don HofstrandDon Hofstrand
Agricultural Economist

The demand for world agriculture output will grow exponentially overcoming decades due to world population growth and expanding world economies.  At the same time, the agriculture sector will be impacted by changes in climate that will challenge the productivity of the world’s agriculture resources.  To meet this expanding world demand, agriculture must become more adept at anticipating climate changes and variations and finding ways of adapting to these changes.  Below is a discussion of the needs of farmers and agribusinesses for quality information relating to climate predictions.

Climate prediction information has the potential to reduce the impact of adverse weather events.  This will occur because the advance notice will allow decision makers the opportunity to implement plans to minimize the impact of adverse events and find opportunities within favorable events.

Climate prediction is in its infancy. However, the payoff from the research and development of reliable climate prediction information can be substantial for the agricultural industry.  This is especially important considering the increased frequency of the extreme weather events that we are experiencing and will experience in the Midwest in coming decades. 

Below is a discussion of the ways in which climate prediction information can be utilized by crop and livestock producers and agribusinesses to adapt to and minimize the impact of changing weather patterns and adverse weather events.  

Climate prediction information for crops

Farmers grow crops on the field scale (individual farm acres impacted by field-scale climate factors) but sell crops into an international market(impacted by global-scale climatic factors).  Local climate predictions improve crop production planning and subsequently impact individual farmer yields.  Global and regional scale climate factors impact the prices farmers receive for their crop as well as their decisions of what crops to grow. 

Climate predictions of monthly, seasonal and yearly weather influence farmer decisions that are important to the individual growing season of a crop.  Multi-year and decadal predictions of weather influence farmer investment decisions that can span several growing seasons. 

To maximize the value of climate prediction information for decision making the information needs to be combined and provided with other environmental information such as ground cover,soil type, soil organic matter, soil radiation, soil temperature, soil moisture and long-term drought conditions.  This integration of environmental information will help farmers and agribusinesses utilize the information more effectively in decision making. 

Improve crop production planning --Climate predictions of seasonal weather patterns (e.g., drought, heatwaves, cool planting season) help farmers decide which crops are most likely to flourish in the predicted growing season.  This will impact their decisions of which crops to grow and how much of each crop to grow on their farms and whether to purchase crop insurance.  This is especially relevant in regions of the country where farmers traditionally grow a variety of crops.  In areas of the country where crop mix does not change, climate predictions help farmers decide on the relative proportions of each crop to grow.

Improve production input planning --Farmers purchase a variety of crop inputs (e.g., fertilizers,pesticides, fungicides) that are utilized during various times of the growing seasons.  Timely climate prediction information can provide useful information for the type, amount, timing and type of application of crop inputs. 

An outline of the various production inputs used in corn production is presented in Figure 1.  The figure designates the general time period during the year when purchase and application decisions are made by farmers.  For example, nitrogen fertilizer can be purchased and applied several times during the year but usually applied in the spring before planting or in the fall after harvest.  Conversely,crop insurance must be purchased in later winter, well before planting. 

Climate prediction information can help farmers choose the proper crop variety for the expected growing season weather conditions.  For example, the maturity of the corn variety may be impacted by the expected length of the growing season.

Climate predictions can help farmers choose the crop insurance policies and products needed to cover the yield and price risk expected during the growing season.  Because the deadline for purchasing insurance occurs before the growing season begins, climate prediction information can be extremely helpful. 

Climate predictions can help farmers prepare a more accurate fertilizer application plan for the growing season.  Nitrogen fertilizer timing of application can be more accurately designed with information about expected temperatures and precipitation during various periods of the growing season. 

Corn Production Seasonal Decisions

Crop pests including weeds, insects, molds, etc. are highly influenced by the precipitation and temperature conditions of the growing season.  A plant that is stressed is more vulnerable to other biotic (living) orabiotic (non-living) stresses. For example, if humidity levels increase,as has occurred and is expected to continue in the Midwest, corn encountering drought during the grain-filling phase may be more vulnerable to mycotoxin or aflatoxin growth. Climate prediction information can help farmers prepare for these pest problems in advance in order to mitigate their negative impact on crop yields. 

Climate predictions of precipitation and temperature during various stages of the growing season can be especially helpful to farmers producing crops under irrigation.  These predictions allow farmers to more efficiently plan the timing of water application and apply the amount of water needed to optimize crop yields.  

Improved crop field operations planning -- Crop yields are sensitive to the timing of field operations. Climate predictions will provide lead time to help farmers mitigate the effects of adverse weather during the planting season. Delayed planting can significantly reduce yields and make crops vulnerable to early frost in the fall.  Climate prediction information on expected “suitable planting field days” based on highly specific timing, amount, duration and special distribution of precipitation and evaporation during the planting season will help farmers prepare for periods of excessive rainfall.  Information on expected soil temperatures and the timing of the last killing frosts can help farmers identify the optimum time for planting.

Delayed harvest can significantly impact both the yield and quality of crops.   Climate prediction information can help farmers decide whether to harvest crops early or wait for further dry-down to minimize crop drying expenses.  Information on expected“suitable harvest field days” can help farmers make plans to minimize the amount of quality damage due to excessive harvest rainfall.  

Improper tillage can influence crop stands.  Delayed pesticide application can negatively impact crop yields.    Climate prediction scan provide lead time to help farmers mitigate the effects of adverse weather during the planting season (e.g., delay planting due to cold soil).

Improve crop field-level investment decisions --In addition to the growing season decisions outlined above, farmers have a variety of longer-term decisions that require multi-year and/or decadal climate predictions. Future precipitation levels and the variability and intensity of precipitation events can significantly impact crop yields.  Both too little soil moisture and too much soil moisture will reduce crop yields.  Climate predictions can provide essential information for decision makers of whether to install irrigation systems or drainage systems to optimize crop yields. 

Climate predictions of the number of suitable field days for planting,harvesting and other field operations will impact the type and size of crop machinery a farmer should purchase.  Predictions of narrow time windows indicate that farmers should considered oversized machinery to minimize the possibility of missing these time windows.  In addition,predictions of narrow time windows for planting increase the need for applying inputs and other field operations.  Also, narrow harvest windows increase the need for moving grain quickly from field to storage.  In addition to combine size, this includes ample grain movement capability from the field to storage and ample grain drying capacity for a wet and/or short harvest window.

Most crops grown in the U.S. are annual crops.  This means they are planted every year.  However, a significant amount of agriculture production comes from perennial plants that, when planted, will produce over a period of years.  This includes forage crop such as alfalfa which may yield output over four or five years and tree crops such as citrus and nuts that may produce output over a decade or more.  These planting decisions are along-term investment that often involves substantial upfront investment and may include a period of no returns for several years.  Multi-year and decadal climate predictions can be an important resource for this decision. 

Mitigate negative soil impact --Productive soils can be severely impacted by extreme weather events. Intense rainfall on saturated soils will result in substantial washing of soils particles into streams and waterways.  Once erosion occurs on soils it is virtually impossible to correct the damage because soils form over hundreds and thousands of years.  Eroding soils also negatively impact water quality in streams and rivers. 

Because the probability of extreme weather events is expected to increase in future years, the amount of soil erosion will increase if corrective actions are not taken.  Climate predictions of extreme weather events can help farmers plan their cropping and cultural programs to minimize the erosive impact of these events.     

Higher temperatures and more soil moisture, expected to occur in Iowa,will accelerate the microbial action in soil. This leads to a faster breakdown of plant materials to form carbon dioxide out of soil carbon,increasing the loss of soil carbon.  Soil carbon is a critical ingredient for the long-term productivity of soils.  Climate prediction information can help farmers better manage soil carbon levels in light of expected weather events.

Improve crop marketing and planning --Global-scale climate predictions help assess national and world crop production levels.  These assessments of production levels are a major driver in determining the price of agricultural crop commodities.  Due to the dwindling inventories of world grains, prices levels are extremely sensitive to small changes in expected production.  This leads to large swings in grain prices and the opportunity for speculative investing to increases price volatility.  Volatile markets increase the financial risk of producers and processors

Climate predictions help anticipate major weather events that impact the production levels of world crops.  This will reduce the uncertainty of grain production which will subsequently reduce the volatility of world grain markets. Less volatility will lead to less risk for participants in the supply chain.  This risk reduction will lead to a more efficient supply chain and lower and more stable grain and food prices.   

Climate predictions of smaller weather events that, due to their timing, have a significant impact on crop yields are also important.  Most crops have stages in their development that are especially sensitive to weather conditions.  Examples include the pollination period for corn and pod filling for soybeans.  The ability to predict climate conditions during these critical development periods can improve the ability to predict crop yields and grain production levels.

Grain prices impact the marketing and production decisions of farmers and agribusinesses. Decreasing the volatility of grain prices will help farmers make more rational grain marketing decisions and better utilize grain marketing tools to increase profit levels. 

Global-scale climate predictions help farmers make decisions of which crops to plant. Expected selling price is important for estimating the profitability of crops.  Climate predictions of world crop growing conditions and the expected crop prices resulting from these conditions provide information for individual farmer decision making on deciding which crops to plant and/or the relative proportion of each crop to plant.

Climate prediction information for livestock

Climate prediction information will have a significant impact on livestock production decisions.  In addition to the direct impact of weather on animals in terms of heat and cold, climate information will have a significant impact on the cost and availability of livestock feed. 

Improved beef production --Climate predictions of pasture and rangeland conditions will benefit farmers and ranchers in managing their breeding herds.  Producers must either supplement feed levels or reduce breeding herd size during periods of drought.  Advance notice of drought will help farmers and ranchers prepare for the drought and minimize its financial impact. This will also minimize the impact on the beef sector as a whole.

Beef production involves two major types of businesses.  Businesses that produce the calf (or yearling) and those that feed the calf to slaughter weight.  The major costs associated with finishing an animal are the cost of purchasing the animal and feed costs.   By reducing the impact of extreme weather events on beef breeding herd size adjustments,beef feeding enterprises will be faced with a more stable supply and price of feeder animals.  In addition, climate predictions of the future availability and price of feed will reduce financial risk and reduce the overall cost of beef production.

Many beef operations are structured with only partial shelters for the animals.  Their exposure to weather conditions can significantly impact animal health and performance.  This will range from calf death loss to reduced rates of gain for finishing animals.  The ability to anticipate these periods in advance will allow the producer to take corrective action to minimize its impact.

Improved dairy production -- Many modern dairy enterprises are structured with only partial shelters for the animals.  Their exposure to weather conditions can significantly impact their health and performance. Excess cold or heat will negatively impact the level of milk production. The ability to anticipate these periods in advance with climate prediction information will allow the producer to take corrective action to minimize the impact.

Dairy production depends on large quantities of forage production such as alfalfa.  Because forage is a bulky feed to transport, it tends to be produced in a relatively small geographic area in which the feed is consumed.  Climate predictions of local pasture and forage conditions will be valuable for dairy producers. 

Improved swine and poultry production --Although much of modern swine and poultry production occurs in enclosed conditions (confinement), it is still vulnerable to the weather impact on feeds such as corn and soybeans.  Climate prediction information to estimate the amount and price of feed crops can improve the stability,profitability and efficiency of the swine industry. 

Improved investment planning --Modern livestock production requires long-term investments in facilities and breeding herds.  These decisions are influenced by future climate conditions. 

Climate prediction information for agribusiness

Agribusinesses are impacted by both regional and local climate factors.  They provide an array of production inputs and other products and services over a wide geographic region that is influenced by regional climatic factors. However, production input purchase decisions are made by individual farmers based on local climate factors.

Seed and genetics companies --Monthly and seasonal climatic predictions influence decisions of what seed varieties to plant (e.g. wet spring produces demand for shorter season varieties).  So, climate predictions over a geographic region will provide seed companies information on how much and where to distribute seeds varieties.

Multi-year and decadal climate predictions help identify the types and varieties of seed that seed companies will develop for future climate conditions.  Due to increase climate variation, hybrids will need to contain more resistance traits to flourish under these variations.

Crop insurance companies --Monthly and seasonal climate predictions will be useful for farmer decisions of the types and levels of insurance products to purchase. This will also help the insurance companies assess the volume and locations of the various insurance policies that will be purchased. Climate predictions can also provide advance notice of the location of extreme weather events that will help insurance companies determine how and where to deploy their workers and claims adjusters.   Multi-year and decadal climate predictions will be useful to insurance companies to develop the types of insurance products that will be demanded by farmers under future climate conditions. 

Input/supply companies (fertilizers and pesticides) --Monthly and seasonal climate predictions can be used in logistics/transportation decisions to provide inputs where they are demanded by farmers.  Multi-year and decadal climate predictions will be useful in developing and producing the types of fertilizers and pesticides needed under future climatic conditions. For example, many weeds respond more quickly to elevated levels CO2 than crops. Herbicides are, in some cases, less effective on weeds grown under these conditions.

Farm machinery companies/dealerships --Monthly and seasonal climate predictions of extreme weather events that impact machine operations will be used in logistics/transportation decisions to provide machines and machine parts where they will be needed.   Multi-year and decadal climate predictions will be useful in developing machinery modifications needed under future climate conditions.

Feed companies -- Monthly and seasonal climate predictions of the availability and price of various feeds are important for the manufacture of complete feeds.  Multi-year and decadal climate predictions will impact the size and geographic location of livestock production areas which will subsequently impact the location of new feed mills.

Food and biofuel companies --Monthly and seasonal climate predictions of the availability, quality and price of various ingredients and feedstocks are important for the manufacture of food products and biofuels.  Multi-year and decadal climate predictions impact size and geographic location of food ingredient and biofuel feedstock production areas.


Due to the pressure on the agricultural sector to produce food, fuel and fiber for an expanding world, methods of improving agricultural productivity must be identified and exploited.  The situation is exacerbated by the challenges of climate change which will modify temperature and precipitation patterns and increase the frequency of extreme weather events. 

Research to help predict the timing,location and intensity of these changes and events will provide valuable and actionable information to agricultural decision makers to increase production, reduce risk and mitigate the environmental impacts of these events.  As discussed previously, there are numerous ways that farmers and agribusinesses can use this information to achieve these ends.  The payoff from these research investments will be substantial.

* This report is an outgrowth of the focus on the impact of climate change and variability on agriculture at the Ninth Annual Climate Prediction Applications Science Workshop (CPASW) held in Des Moines, Iowa during March 1-4, 2011.