Agrometeorological Database

Crop-weather as well as animal-weather relationships are derived from historical records of both climate and agriculture. Such records are also used in deriving the basic statistics and risks that may be associated with any climate-based planning and operational decisions (Doraiswamy et al., 2000). Availability of long-period, high-quality climate and agricultural records are therefore crucial for maximum application of climate information and prediction services in agricultural planning and operations. For some agro-ecological regions, such records are not available.

The length and quality of the climate and agricultural records are key issues that should be addressed, as they provide the information base in any efforts to optimize applications of climate prediction products in agricul tural planning and management. User-specific computerized databases in acceptable formats need to be generated.

Real-Time Climate Information

Many agricultural operations, services, and research studies require realtime weather information on a daily, weekly, or ten-day basis. This information can be generated through an efficient network of agrometeorological stations, which at this time is very poor in most countries (Gommes, Snijders, and Rijks, 1996). Wherever the weather stations are available, most of them do not follow the pattern of agroecological zones. Weather stations installed and maintained by the meteorological departments in various countries are usually located near towns and at airports, where recorded observations are not representative of the agricultural landscape (Ogallo, Boulahyab, and Keane, 2000).


Optimum utilization of any climate prediction product in agriculture requires applied agrometeorological research with two basic components: interdisciplinary research and multiscale research (Hatfield, 1994). The topics include understanding of the local climate/agricultural systems and the associated linkages, especially with respect to extreme events, climate, and pest/disease linkages, and adaptation of agricultural systems to local climate variability. Improved and integrated data sources and interpolation methods, locally validated crop models, and regional numerical forecast models are realistic and attainable goals for the near future.

Enhanced research efforts are required on the determination of the scale and time at which seasonal predictions are suitable for application to agriculture and the environment and on the connection between the past and present weather and the upcoming predicted season.

Downscaling Short- and Medium-Range Weather Forecasts

The science and technology of short- and medium-range weather forecasting with computer models are now quite advanced. Availability of operational short- to medium-range weather forecast products is increasing day by day. For such products to be more useful and effective in agricultural applications, they must be downscaled to the regional, local, and ultimately individual-farm levels. However, most regional/local downscaling techniques require a good knowledge of regional/local climate processes. This knowl edge is highly inadequate due to serious limitations of basic local meteorological data and research.

Downscaling forecasts to a local level is one of the most difficult tasks ahead. Several downscaling techniques have been developed in recent years (Von Storch, Zorita, and Cubasch, 1993; Hughes and Guttorp, 1994; Zorita et al., 1995; Kidson and Thomson, 1998). However, much more effort is needed to achieve the desired goals.

Seasonal Climate Prediction

Improvement in seasonal climate prediction is one crucial factor that could reduce the vulnerability of agricultural systems to severe impacts of extreme interannual climate anomalies. The science and technology of climate prediction within monthly, seasonal, to interannual time scales is still young and is currently under intensive investigation worldwide. The last decade of the twentieth century, however, witnessed a major advance in understanding the predictability of the atmosphere at seasonal to interannual time scales (Palmer and Anderson, 1993; National Research Council, 1996; Carlson, 1998). El Niño and Southern Oscillation are some of the known key drivers to interannual variability and have been associated with worldwide extreme climate anomalies, including changes in the space-time patterns of floods, droughts, cyclone/severe storm activity, and cold and heat waves. For some of these, agricultural application models have been developed which transfer projected ENSO signals directly into agricultural stress indices (Nicholls, 1985; Cane, Eshel, and Buckland, 1994; Glantz, 1994; Keplinger and Mjelde, 1995; Hammer, Holzworth, and Stone, 1996; Mjelde and Keplinger, 1998).

Fast development in computer software, communication technology, and advances in climate science during the past few decades suggest that useful model-based seasonal forecasts are possible in the near future (Serafin, Macdonald, and Gall, 2002). Results from computer models have demonstrated that it is possible to predict sea-surface temperatures and El Niño over time scales extending from a few months to over one year.

At present, numerous impediments are obstructing the optimal use of seasonal forecasts. Nicholls (2000) has reviewed these impediments and has suggested strategies to overcome these problems so as to improve the use of seasonal forecasts. The challenge to improve climate predictions for seasonal to interannual scales has been taken in the WMO program known as the Study of Climate Variability and Predicability (WMO, 1997a,b). It needs to be addressed at national levels as well.

Skilled Multidisciplinary Human Resources

The interdisciplinary nature of agrometeorological services is a weakness that has to be addressed (Hollinger, 1994). At present, skilled multi-disciplinary human resources for integrated agrometeorological applications are relatively limited. If an agricultural meteorology scientist alone has to deliver the most effective products to users, then he or she must be fluent in both biological and physical sciences, so as to look at the world from a different perspective than the physical or biological scientist. There is a great need to strengthen and equip national and regional climate and agrometeorological institutions/units with human resources with multi-disciplinary training.

Tailored Products

The perspectives of many meteorologists are based on long-standing traditions about the type of information expected by their agricultural clients (Seeley, 1994). There is a need to address the climate information requirements of specific sectoral agricultural users so that climate prediction centers can produce custom-tailored products. Information has value when it is tailored and disseminated in such a way that end users get maximum benefit from applying its content (Weiss, Van Crowder, and Bernardi, 2000). Areas of agricultural expertise that have prospered throughout the years are those with a product that is wanted and used in agricultural production. The future will see increased availability of real-time, high-resolution weather data. Opportunities for agricultural meteorology services will grow dramatically if agricultural meteorologists meet the challenge of making custom-tailored products, defined and presented in their clients' language, to meet their precise needs, and educate agricultural producers in using weather data in a variety of management decisions (Perry, 1994). Rijks and Baradas (2000) suggested that the identification of clients' needs could be made through a process of listening to people in the industry and through dialogue about the issues that could make their work safer, easier, and more reliable.

Forecast Services and Users' Interface

There is an overexpectation of forecast accuracy among users. The common perception is that both long- and short-range forecasts are not reliable enough to use in decision making (Crichton et al., 1999). The difficulty is to convince the users what forecast accuracy is attainable with the current state of the art. It is crucial that farmers have good knowledge of the skill and lim itations of any climate prediction products. To achieve this, agroclima-tologists have to take a more proactive role than they have at present (Blad, 1994). Extension education programs are needed to educate agricultural producers about agrometeorological products and the skill and limitations of any climate prediction product (Stigter, Sivakumar, and Rijks, 2000).

To conclude, reducing the risk associated with increased climate variability has a high potential for increasing productivity and quality while protecting the environment. Agroclimatological services generate the possibility of tailoring crop and animal management to anticipated weather conditions either to take advantage of favorable conditions or to reduce the effects of adverse conditions.

TABLE 9.1. Role of weather/climate forecast information in key decisions in farm industries

Industry Key decision

Why weather and climate information is important

Climate/weather information required

Strategies to reduce losses/enhance profits

Management Buying new property

Debt taken in unfavorable weather Historical records of rainfall, wind, conditions can make repayment temperature, and frosts difficult.

Investment in new machinery Purchase/hire of high-cost ma- Seasonal climate outlook chinery requires good weather for maximum income to ensure easy repayments.

Seasonal planning Warmer weather conditions may Seasonal climate outlook cause crops to mature early. Excessively wet season requires planning for control of weeds, insect pests, and diseases.

Managing labor and equipment Labor and machinery will not be Short-range weather forecast efficiently deployed under an extreme combination of high temperature and high humidity or low temperature and strong winds. A combination of temperatures of 30°C and above, coupled with 70 percent or higher relative humidity, causes discomfort for humans. Wind chill: Wind chill stress on the human body occurs when temperatures are very low and strong winds are blowing. The convective heat loss from the body becomes painfully extreme. Exposure to wind chill in wet clothing is most dangerous.

Buy only if climate is favorable for the enterprise. Avoid areas that have high recurrence of drought, floods, and frost.

Make large purchases in seasons when the outlook is normal or better than normal.

Book labor and contractors earlier to harvest crops.

A forecast of mild and fair weather indicates that the entire period offers excellent conditions and maximum hours for field operation. Utilize such days for operations in which long ninterrupted working hours are required. Avoid deploying labor for a field operation in a period of extremely hot humid weather in summer and wind chill periods in winter. Choose an alternative operation for which a minimum of human labor is required. Make the best use of machinery and labor in mild and dry weather.

Industry Key decision

Why weather and climate information is important

Climate/weather information required

Strategies to reduce losses/enhance profits

Marketing produce

Cropping What crop(s) to plant

Variety of crop to plant

Potential profit changes with production and quality estimates/information.

State, national, and worldwide weather forecasts

Select a crop that makes the best Probabilities of rainfall and abnor-use of the climate. malities in temperature

Most crop species have a number Seasonal climate outlook of varieties available that vary in their length of growing season or resistance to heat, cold, frost, waterlogging, or disease.

When to plant a crop Most crop seeds cannot germin- Extended weather forecast;

ate below 4.5°C during the winter probability of follow-up rainfall in season and below 10°C during short term the summer season. Follow-up rainfall may make the paddock too wet to plant or more rainfall may be needed to allow the crop to establish. Even a light rainfall after the crop has been sown adversely affects the germination rate through crust formation.

Optimum depth at which seed Under extremely dry weather, soil Extended weather forecast should be sown to achieve an moisture will deplete at a fast rate optimal rate of seed emergence because of high evaporation.

Hence, upper soil profiles will dry _rapidly, resulting in inadequate_

Monitoring weather conditions in countries that are major producers of the same crop/commodity can give an estimate of the right time to market the produce.

Select late-maturing crops if planting dates are early, short-maturing crops if season is short. Select crops with higher drought tolerance in dry seasons.

Choose a crop variety that best suits the seasonal conditions. Plant varieties that mature before the possibility of late frost. Plant a long-season variety if rainfall is likely to be evenly spread and a short-duration variety if probability is of less rainfall.

Mild temperatures above 4.5°C in winter and above 10°C in summer are ideal for sowing seed crops provided soil moisture is adequate and sowing dates for the crop are optimal.

Plant early if outlook is for continued rain or plant now if only one or two planting opportunities in the season.

A forecast of dry, hot, and windy weather will suggest sowing the crop at a slightly deeper depth than normal to achieve the desired germination of seed.


Fertilizer application moisture for the seed to germinate. The second limiting factor will be extremely high temperature in the shallower depths of the soil, and the seed planted at shallow depth will be roasted or the emerging seedlings will be burnt.

Fertilizing with nitrogen can increase crop yield potential but only if there is sufficient rainfall.

Temperature, rainfall, and wind speeds determine the efficiency of fertilizer application. Wind speed greater than 15 km/hour does not allow the finely particled fertilizer to hit the ground at the right place. The spread is uneven and a substantial amount is blown away from the target and wasted as drift.

Seasonal climate outlook

Short-range weather forecast of temperature, wind, and rainfall

Fertilize only at the optimum rate if outlook for the season is favorable.

A forecast of mild, dry, and light wind is ideal for fertilizer application.

Apply fertilizer when the forecast is for less than 10oC, with no or insignificant rainfall, and wind speed less than 15 km/hour. Avoid finely particled fertilizer application on days for which the wind speed forecast is above 15 km/hour.

Disease control

Insect control

Many crop diseases are affected Seasonal climate outlook by weather. As an example, yellow spot in wheat can become prevalent in wet years, causing reduced production.

Many insect pests become a problem in only particular seasonal conditions. Heliothis in the caterpillar stage is an example. Heliothis moth can move in on storm fronts.

Seasonal climate outlook; extended and short-range weather forecast of rain, wind, and temperature

Be prepared for disease control if the outlook is for a wet season. Monitor the crop and undertake a spray application when the first symptoms of disease become apparent.

Heliothis have a life cycle of four weeks in heat wave conditions versus ten weeks in cooler condi-tions.Therefore, scouting and spraying of the crop is necessary more often in heat wave conditions.

is od

Industry Key decision

Why weather and climate information is important

Climate/weather information required

Strategies to reduce losses/enhance profits

Weed control


Wetter years or wetter than average seasons may cause an increase in the number of crop weeds.

Sugarcane Replant or retain old ratoon

Determining harvesting and crushing schedules

Trash blanket

When to burn cane prior to harvest

Horticulture Site selection

Crop selection

Seasonal climate outlook and extended weather forecast of rain, wind, and temperature

Rainy spell delays/prevents harvest and creates problems in wind, and temperature transport and storage of harvested grain. Rainfall at crop maturity reduces grain quality and increases grain moisture.

Spray earlier to ensure weeds do not get too large, and if using ground spraying, spray when damage to soil structure by machinery is least.

Extended weather forecast of rain, Harvest early to avoid rains.

If rainfall is anticipated, postpone

New plantings culminate in poor stands and stunted growth in dry seasons.

Rainfall reduces the commercial cane sugar content (CSC) and hinders transport of cane from paddocks.

Trash on ground in dry weather will preserve moisture.

Weather affects the effectiveness and safety of using fire as a tool for cleaning cane.

Climate records can determine if the area is suitable for particular crops.

Most crops have specific climatic and water requirements.

Seasonal climate outlook

Extended and short-range weather forecasts

Seasonal climate outlook

Extended and short-range weather forecasts of temperature, relative humidity, and rain

Historical records of rainfall, wind, humidity, temperature, and frosts

Historical records of rainfall, wind strength, humidity, and frost; num-

the operation until the next clear day, when soil moisture does not interfere with the operation. Budget for the timely use of grain dryers to reduce moisture levels.

New planting should take place only in a favorable season. Maintain old ratoon if conditions are unfavorable.

Harvest highest yielding blocks first or blocks more susceptible to waterlogging if rain is likely.

Do not burn trash in dry years; harvest green.

Fire cane only on days with low fire danger.

Select climatic site that suits the requirements of the crop to be grown.

Select crops that suit the local area and are not subject to ad-

Crop selection (continued)


Site selection

Varietal selection

Disease control

Low temperatures: Number, dura- ber of frosts/year, likely dates of tion, and severity significantly first and last frosts of the season influence plant growth and product quality. For example, lettuce heads are affected by several light frosts in a row.

High temperatures: Heat wave conditions and high night temperatures markedly affect crop quality

Rainfall: In many horticultural areas, if irrigation water is not limiting, rain can cause damage and an increase in disease prevalence for most crops.

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