Developments in agricultural meteorology as a guide to its potential for the twenty-first century

AGRICULTURAL AND FOREST METEOROLOGY

ELSEVIER

Agricultural and Forest Meteorology69 (1994) 9 -25

Developments in agricultural meteorology as a guide to its potential for the twenty-first century Wayne L. Decker Department of Atmo.~pheric Science. 100 Gentry Hall. University of Missouri-Colurnbia. Columbia, MO 65211. USA

(Received 1 March 1993; revision accepted 29 October 19931

Abstract In this paper the development of agricultural meteorology since 1800 is reviewed. A description of the development of the necessary climatic data bases for the interdisciplinary science is presented. A review is given of the use of statistics to formulate risks analyses for farm and forest management, and in statistical models for crop prediction through regression. The development and use of crop process models are discussed with several practical models listed. Remote sensing is identified as a new tool for appraising the thermal and water stress of a canopy and in assessing the crop and forest conditions of large production areas. The history of the development of service programs in agricultural and forest meteorology is also discussed. The challenges and problems for further development of these services are described.

I. The development of agrometeorology Agriculture is the world's most weather-sensitive industry. The success of nearly every farm operation or farm management strategy depends on the current weather and the weather of the next few hours. On another scale, the risks imposed by climate determine the type of farm enterprise that can be successful at a particular location. Agrometeorology includes aspects of applications of both meteorology and climatology, so within the context of the discussion presented here agroclimatology is considered part of agricultural meteorology. In general, applied meteorology and climatology have as their objective service to the human enterprise. Agricultural meteorology deals with the manner in which the industry, both production and marketing, responds to the current weather, utilizes weather forecasts, takes advantage of climate risk analyses and modifies the environ0168-1923/94/$07.00 :(~. 1994 ElsevierScience B.V. All rights reserved SSDI 0168-1923(93)0500L-9

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14" 1.. Decker. Agricultural and Fore.~t Meteorology 69 11994) 9-. 25

ment to ameliorate or avoid a weather hazard. Each research project and weather service initiative should serve one or more of these needs. As a new century approaches it appears appropriate to look at the manner in which agricultural meteorology has developed and to speculate on new directions which this form of applied meteorology will take. Although the following remarks are biased toward the experiences in the United States. the analysis and projections have application to events occurring in other regions of the world. Space prevents reference t~ all of the laboratories with significant contributions to the development of agricultural meteorology. It is the intent of this paper to present an appraisal of" the manner in which the science developed, rather than a complete bibliography ol significant contributions. A complete survey of methods in agricultural meteorology has been compiled by Grittiths (1994).

2. Agricultural meteorology in the nineteenth century Prior to 1900 agriculturists and physical scientists were beginning to document the variabilities in climate near and beneath the Earth's surface. Seasonal and diurnal variations in temperature, humidity and wind were measured and summarized. Although many of these descriptions were graphic and descriptive, the basic understanding of heat exchange and diffusion were analytically described (Wollny, 1878a,b. 1883). A complete listing of research papers in agricultural meteorology prior to 1960 was provided by Wang and Barger (1962). Agriculture of this period had become adapted to the climate through a long experience with 'trial and error' in farm management. The crops and livestock produced in each region were the result of generations of efforts to discover the most suited crop and practice. In the Americas, the settlement by Europeans offered ~L challenge to conventional farming practices. The settlement of the east coast of North America with the humid climates adapted well to the European style of farming, but the westward migration of people into the subhumid and semiarid regions offered new challenges to the trial-and-error system of adaptation. After the American Civil War (1860--1865), it became public policy to encourage the westward movement of farmers. Policies were developed which granted 160 acres (65 ha) ot" land to 'homesteaders" who would agree to farm the land for 5 years (Gates, 1977). When the weather turned dry, the farmers, after enduring the initial hardship, oftcn abandoned their claims returning to the east or moving on to other areas. Thi~ practice of learning applied climatology through failure was the initial activity in agricultural meteorology in the Americas.

3. Early developments in agricultural meteorology and climatology At many laboratories and experimental fields in the US, Europe and the Asian subcontinent, measurement of the characteristics of the microclimate continued during the first half of the 1900s (Geiger, 1927; Ramdas et al., 1935). The role of water in the soil climate was recognized and the link between the physical properties

W.I,. Decker : Agricultural and Forest Meteorology 69 t1994) 9 25

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of soil and the heat exchange and water movement was investigated. Attempts were made to relate these characteristics to farm management practices (Russell and Keen, 1938). In North America, the semiarid high plains and the prairie subhumid regions wcre for the most part settled with a stable farm population. It was recognized that the year-to-year variations in yields and regional commodity production were associated with variations in climate. Efforts werc made to analytically describe this relationship through statistical analysis of correlation of yields with monthly rainfall. Smith (1914) purposed, on the basis and analysis of Ohio data, that maize yields werc best related to the rainfall during July, Subsequently, Wallace (1920) raised doubts about the universality of this conclusion with an analysis of data for Iowa. These analyses were a first attempt to use statistics to describe the nature of the relationship between the variabilities in yield and production and climate. In fact a 1920 book authored by J. Warren Smith, an agricultural meteorologist employed by the US Weather Burcau, provides a good description of the status of the study of the relationship between farm production and climate (Smith, 1920a). R.A. Fisher was, perhaps, the first to evaluate the relationship between yields and rainfall using multiple correlation. Using data collected at the Rothamsted Experimental Farm in England, Fisher (1925) developed a multiple regression of 5 day rainfall totals against wheat yields. Since thc 1920s, correlation and regression analyses have remained a tool for describing yield weather relations. Barger and Thorn (1949) refined this techniquc providing a method of estimating the deviations of yield from the average on the basis of the probability of precipitation amounts. These authors were the first to adjust the yield experience to account ibr the introduction of the new technology of hybrid varieties of maize. The development of programs for the international cooperation between nations in meteorology occurred during the early years of this century. Blanc and Smith (1964) provide a description of the early efforts and give the background for the establishment of the Commission for Agricultural Meteorology under the mantle of the International Meteorology Committee. Later, this Commission was continued within the organization of the World Meteorological Organization. One of the many accomplishments of the Commission for Agricultural Meteorology was providing the stimulus for the establishment of the first periodical devoted exclusively to research and development in agricultural meteorology. This periodical was first published in 1964 as a journal with the titlc 'Agricultural Meteorology'. In 1984 the periodical broadened its scope and became identified as 'Agricultural and Forest Meteorology'.

4. The climate data base and agricultural meteorology The early studies dealing with relationships between yields and climate were accomplished using limited climatic data and primitive computational proccdures.

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~lgricultural and k?~rest Meteorology 69

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The climate data consisted of summaries derived from observations 0I" daily maximum and minimum temperatures, and daily precipitation. These data wcrc, tbr the most part, taken from weather stations with temperature screens similar to the "cotton belt" shelters used in the US. In the US the records from these stations were sent monthly to a collection point in each state. The records were given a quick error check, monthly temperature averages and precipitation total were computed by hand, the summaries were hand set on small printing presses and printed as state issues of 'Monthly Climatological Data'. Late in the 1940s the US Weather Bureau (the predecessor organization o1 the National Oceanic and Atmospheric Administration (NOAA)) began a National program of placing on "punched cards" the current weather records. All the records from the various observing networks werc hand punched onto the cards. This data base allowed machine processing of the weather data; when coupled with photo-oil: set reproduction, this allowed an efficient climate data processing system. The systcm began operation in July 1948. As new methods of computer operations were developed, the system was altered to incorporate the new the technologies. In general, the climatic data tbr the US are only available in a machine computational form from the start-up date in 1948. Decker (1994) provides a description ot" the analytical methods for using thesc data in probability and risk analyses. Toda.~ there is available at the national archive (National Climate Data Center. NOAA in Ashville, NC) a complete data set for the US from 1948 and tbr most of agricultural regions data extending from early in the century until the present. In the US, the occurrencc of droughts in the central regions in the early 1950,~ produced a need to understand more fully the risk of dry weather for agriculture. The north-central region of the Agricultural Experiment Stations, an area comprising 12 states extending from Ohio on the east to Kansas on the west, and from Missouri on the south to Minnesota on the north, established a formal "study group" to addres,,, this problem. The objectives of the original project were (1) to place the historical weather records prior to July 1948 onto punched cards and (2) conduct risk analyses of the hazards of climate to the agriculture of the region. This project has continued to operate in the region since 1955 and the procedure was subsequently adopted b2r other regions in the US. Many valuable risk analyses have been performed using the data compiled by the Regional Study Committees. For the north-central region of the US, these include bulletins containing regional studies (Shaw et al., 1960; Decker, 1967: Feyerherm et al., 1994). Other Regional Committees have also produced similar studies (Dethier, 1965). Programs to extend the electronic archive of climatic data are needed to further enhance the evaluations of weather and climate risk for agriculture. In the US a recent program was established in virtually all states to identify the observing points with 100 years of historical data and to place these weather records into computer accessible form. These long-term weather stations have been designated by NOAA and the Association of State Climatologists as 'Centennial Weather Stations'. The World Meteorological Organization (WMO) has supported efforts to computerize the climate data base in all countries of the world. Bosen et al. (1966) presented a survey of the methods available to machine process the archived

W.L. Decker .' Agricultural and Forest Meteorology 69 (1994) 9. 25

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climatic data. More recently the National Climate Data Center in the US, with the support of the WMO, has developed a data management system called CLICOM, for use by developing countries using IBM compatible desk-top computers (Helm, 1988).

5. Climate control chambers

The general response of biological organisms to variations in the weather and climate have been understood for a long time. Warm temperatures hasten plant development, water deficiencies cause a loss of turgor, subfreezing temperatures cause the foliage of sensitive plants to die, and dry and windy conditions favor evaporation and transpiration. An example of the effect of temperature on growth was reported by Lehenbauer (1914) when he provided an estimate of the rate of development of maize seedlings under varying temperature conditions. In the late 1940s technology had advanced to the point where it was possible to build facilities to quantitatively document biological response to varying environmental conditions. These facilities allowed the simultaneous study of more than one environmental factor. Perhaps the best known of these facilities was the Erhardt Laboratory established by Fritz Went at the California Institute of Technology (Went, 1950, 1957). This facility provided a way to study the response of plants to diurnal temperature patterns and photoperiodic effects. The Erhardt Laboratory served as a model for the development of growth chambers used today in nearly every biological laboratory and to the establishment of Climatrons at the University of Wisconsin, Duke University and other locations. At about the same time as the Erhardt Laboratory was established, Samuel Brody developed a large animal facility at the University of Missouri-Columbia. This facility, called the Missouri Climatic Laboratory, performed many studies dealing with the physiological response and production of dairy cattle to variations in temperature, humidity, wind and radiation loads (Brody, 1948; Johnson et al., 1962). Subsequently, the facility was used for the study of other animals and was closed after the construction of a more modern laboratory in the Animal Research Center at the University of Missouri. The latter facility is now known as the Brody Climatic Laboratory.

6. Studies dealing with the energy balance of the Earth's surface

The energy balance of the Earth's surface is determined by the balance of incoming and outgoing energy: radiation, sensible heat and latent heat. The quantitative aspects of this balance has been understood for a long time and described by physical meteorologists (Brunt, 1939). The practical aspects of this energy balance, so far as agricultural meteorology, is concerned involves the warming (and cooling) of the soil and vegetation covering the soil, and the vaporization of water by evapo-

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1~.1,. Decker. Agricultural and Fore.~t Meteorology 69 , 1994) 9..25

transpiration. The latter effect has great importance Ibr defining water stress and the design and scheduling of irrigation. The period from 1948 to 1950 contains "red-letter' years for the quantitative definition of the role of the environment in defining water use. It was in this period that H.L. Penman published a rational method for using meteorological observations to estimate evaporation from a free water surface. In subsequent papers Pcnmat~ demonstrated that the free water evaporation could be adjusted to estimatc vaporization from a plant canopy (Penman, 1949, 1956). The Penman method for estimating evapotranspiration has been much studied in the past 40 years (Gerber and I)eckcr. 1961; Thom and Oliver, 1977) and has become the standard for estimating the nced for irrigation water by agricultural engineers, agronomists and meteorologists throughout the world. It was in 1948 that the Thornthwaite method for estimating potential evapotranspiration was published (Thornthwaite, 1948). This method, which is based on temperature, time of the year and geographic location, has been much discussed and criticized by physical scientists and biologists, Its utility is that estimates of the potential water demand can be made using only temperature data. Unfortunatcl~ the estimates are probably much lower than the actual maximum evaporation and transpiration as shown in Table 1 from a simulation preformed by Savadel (1992). In 1949, the consumptive use principle for irrigation scheduling was published b> Blaney and Criddle (1950). This method also required temperature data and the hours of possible sunshine at each location. The technique has been widely used in semiarid regions of the world by agriculturists. Further research in documenting the energy balance of the Earth and vegetative surfaces has continued over the past 40 years. These have included the development of the Bowen Ratio and eddy correlation methods for estimating latent and sensible heat transfer (Fritschen, 1966; Denmead and Mcllroy, 1970; Goltz et al., 1970). There have been several attempts to quantitatively estimate the components of the total surface energy balance. Shaw and Decker (1979) have discussed the significance of these efforts. In experiments conducted in Europe, America and Australia summaries of detailed measurements of the radiation components, sensible heat and latent heat have been published. It is very difficult for laboratories in agricultural meteorology to obtain the resources necessary to maintain continuous records of thc Table 1 Comparison of the estimated potential evapotranspiration (PET) by the Thornthwaite and Penman moth. ods at Columbia, Missouri, USA for the 10 year period 1966 • 1975 (Savadel. 1992) Percentage of days with higher PET (%1

Daily PET in m m day Fhornthwaite

I0 25 50 75 90

64 5.6 4.3 3.0 2.0

............ Penman 8.4 7.4 5.,~ 4.3 23

W . L Decker / Agricultural and Forest Meteorology 69 11994) 9- 25

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components of the energy balance, so most instrumental summaries extend for limited periods of time. In the 10 year period from 1965 to 1974 a series of observations were taken in central Missouri (Decker, 1975) and there are other data series that were taken at laboratories throughout the world.

7. Modeling biological response to environmental conditions The use of growth chambers, biotrons and careful field observations provided quantitative estimates of how plant processes responded to variations in temperature, available water and other environmental conditions. At the same time, instrumentation development and field observations using these instruments of the energy balance within and above plant canopies provided an understanding of the microclimatic characteristics of biological systems. In the late 1960s and early 1970s reports began to appear in the literature documenting the response of plant growth and development to the environmental conditions (Lemon, 1963; De Wit, 1965; Passioura, 1973). These developments paved the way in the 1980s and 1990s for work on mathematical models of plant response and yields to varying environmental conditions. There are at least four reasons why the agricultural meteorologist needs analytical plant models: (1) to understand how plant canopies respond to variations in the environment; (2) to have an expression which simulates the response of plants to varying soil and climatic conditions; (31) to have a tool for use in the development of superior genetic materials; (4) to estimate the production of a commodity prior to harvest. The tools to answer some of the needs for mathematical expressions to simulate production were accomplished through the early statistical analyses referred to earlier in this paper. The first effort had been accomplished in the 1920s when correlation analyses between yields and rainfall amounts were completed. It was a natural step to use these same tools using more refined statistical techniques and modern computer technologies. Perhaps the best known of these statistical models were published by Louis M. Thompson in the late 1960s and 1970s (Thompson, 1969a,b. 1970). In the mid-1970s the NOAA established a center to study the impacts of climatic variabilities on man. One of the areas of concern was the supply of food and feed grains. Statistical modelling was the tool of choice for their analyses. The results of one such analysis are shown in Fig. 1 for wheat yields in Kansas as presented by McQuigg (1975). In general, statistical models explain about 50% of the variability in yields after the effects of improved agricultural technology is removed. Although this may not be an exciting result, the statistical model is able to recognize the years that bumper crops and crop failures can be expected several weeks prior to harvest. It is a technique well worth retaining in the arsenal of tools available to the agricultural climatologist. As the understanding of biological processes increased and the improvement of computer capability occurred, it was logical that attempts to model the biological processes would follow. The result was in the development of mathematical models

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which were driven by the environmental variables defined by weather and soil conditions. Perhaps the best known and most widely used of these models is the GOSSYM model for cotton production (Baker et al., 1983). Lemmon i19861 reported on the adaptation of GOSSYM to simulate the need for irrigation and the timing of nitrogen applications on farms. McKinion et al. (1989) report that the method is being used on farms throughout the cotton producing states o1"southeast US. The physiology of other crops are also being studied for the development of crop models. For example, Curry et al. (1980) developed a physiological based model for the development and yields of soybeans. There is also a group of models which lie somewhere in between the statistical model and the physiological model. These models use empirical relationships between the biological processes and environmental condition to simulate the development and yields of economically important crops. Perhaps the best known of these models are the CERES group of models for maize, wheat and sorghum (Ritchie et al., 1985; Jones and Kiniry, 1986; Alagarsamy and Ritchie, 1990). Similar models have been developed for soybeans (Curry et al., 1975; Wilkerson et al., 1985). The problem with using the process based models for estimating production is that the required soil and atmospheric variables which drive the models are not generally available for entire production areas. All of these models require data of solar radiation, wind and humidity which are available at only a few observational points. It is necessary to develop surrogate relationships between observed variables

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W.L. Decker ,' Agricuhural and Forest Meteorolo~b. 69 (1994) 9-25 5

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and the missing required observations. For example, Hodges et al. (1985) developed a technique for using temperature and precipitation data for estimating daily solar radiation totals. Another attempt at estimating solar radiation using cloud conditions was developed by Meyers and Dale (1983). This empiricism results in estimates from the process models that are only questionably better than those developed by straight statistical techniques. One of the major advantages of the process based models is the ability ol simulating the impacts of the environment on management options. The GOSSYM model tells the producer when to irrigate and apply nitrogen. The CERES Maize model has been widely used to simulate the effects of weather and soil conditions ou irrigation timing and yields. Figure 2 shows the simulated irrigation requirement m central Missouri for the drought year of 1983. Turgu (1987) reported that the simulated yield of maize was increased by 68% for the period 1966 1983 through an irrigation strategy. Crop models, both statistical and process, have been used to simulate the impacts of climate change on production. Decker and Achutuni (1988) used a statistical model for estimating the effects of climate change owing to global warming on maize production in northwest Missouri. Dhakhwa et al. (1990) and Dhakhwa (1991J reported an analysis using the CERES Maize model for estimating the impacts or global climate change due to greenhouse warming on maize production in two midwest regions in the US. The simulated yields for climate change were obtained b~ adjusting the historical climate by an amount indicated by general circulation models. The effect of the increased carbon dioxide concentration on yields was estimated b} percentage changes in evapotranspiration and photosynthesis within the CERES model. The results of these analyses for the Central Crop Reporting District m Iowa are shown in Table 2. The simulation indicated that climate change projected by global warming will decrease corn yields, but the increased concentration of CO, iexpected to counterbalance somc of the adverse effect.

8. Remote sensing as a tool in agricultural meteorology

To understand the thermal and water balance of growing systems it is necessar~ t~ Fable 2 Simulated maize yields from (£02 fertilization and climate change using the Geophysical Fluid l)ynam~c~ Laboratory scenario for Central Iowa (Dhakhwa. 1991) Carbon dioxide change

('limate change scenario

Simulated yield (bushel per acre)"

None Double None Double

None None (;FD[, (iFDL

129 150

~A bushel per acre of corn is equivalent to 304 kg ha

I01 1i 7

W.L. Decker / Agricultural and bbrest Meteorology 69 (1994) 9.. 25

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know the surface temperature and plant turgor. Although there are many systems available for directly measuring these conditions, most of the instruments require physical contact with the surface. Obviously this contact interferes with the natural heat and vapor exchange between the surface and its environment. To avoid this problem methods must be used to detect the surface properties without physically touching the surfacc. These measurements are achieved through remote sensing. The temperature of the surface is not only a direct measure of the thermal condition, but also indicates, indirectly, the internal moisture condition of the biological system. This surrogate indication of turgor for plants occurs because of the latent heat release during periods of rapid transpiration. Infra-red thermometry provides a way to determine the surface temperature of plants and animals. Precise infra-red thermometers are commercially available to provide these measurements. It is necessary to know thc exact emissivity of the surfacc for very precise temperature measurements. The technique using hand-held or "cherry picker' held instruments are described in the literature (Fuchs and Tanner, 1966: Choudhury et al., 1986). The technology allows the measurement of the surface thermal condition with a resolution of a few square centimeters. A review of the use of infra-red thermomctry in agricultural research has been presented by Gardner et al. (1992a,b). For larger scale resolution the thermal condition of the surface can be observed from airplanes, balloons or satellites. The spatial resolution depends on the optical system of the instruments on the platform, but the same principle is involved as with the hand-hcld instruments. The primary differcnce is the attenuation introduced by the atmosphere. In satellite observations, where this interfcrence is serious, it can bc minimized by the use of two infra-red sensors sensitivc to different infra-red bands (McMillin and Crosby, 1984). Landsat and Spot satellites have resolutions of only a few square meters, but return to the same observation point with a frequency of about 3 weeks. The polar orbiting NOAA satellites have a resolution of about 1 km, but observe the surface at the samc location twice cach day. Crosier (1987) used thc NOAA satellite to estimate the surface temperatures of crop production areas in the mid-west. Techniques have been developed to estimate the condition of vcgetation from remotely sensed data. The theory behind this technique is based on the selcctivc reflection of green vegetation to the near infra-red (0.7 to 3.0 #m) and the visible radiation. This technique was developed by Deering et al. (1975) and was refined by Van Dijk et al. (1987). Although several vegetative indices have been suggested thc most widely used is the normalized vegetative difference index. This index is thc difference between the reflected visible radiation minus the reflected near infra-red radiation divided by thc sum of the two. Thc grcenness index has been used for many applications where small spatial resolution is not required. An example of the application is the assessment of crop conditions over large production areas. Kogan (1990) used a modification of the index to assess drought conditions. Hayes et al. (1991) and Hayes (1991) showed that the relationship between average yields and the mean vegetative index during critical stages of crop production at county size areas (say 1000 km 2) can be made with about the same precision as the use of statistical crop models.

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{t'.l,. Decker Agricultural and k)~rest Meteorology 69 (1994) 9 25

It appears that remote sensing offers a promise for the future. With the development of new sensors and satellite platforms, the techniques will improve. It offers ,t new way to assess the crop condition in competing agricultural areas and to determine the crop status in less accessible and food sensitive regions of the developing world

9. Weather information and agriculture No one disputes the statement +farming is the most weather-sensitive occupatlot~ and the agricultural industry is the most responsive to variabilities in weather and climate'. It is not surprising that throughout the history of the world's weather services there has been an effort to provide agriculture with a specifically focused weather service. Smith (1920b) describes a method for minimum temperature forecasting and discusses the nature of the specialized service to agriculture in the earlx 1900s. In the US the most significant attempt to develop a service for agriculture was the fruit -frost program. The objective of the program was, and remains, to recognize the weather patterns leading to freezing temperatures and to forecast when and where damage is likely. Georg (1978) reviews the techniques for forecasting freezes ~md frosts, and made this observation: "'The state of the art of predicting minimum temperatures and frost is not sufficiently developed to meet present and future demands, and is generally not much better than many years ago". Probably Georg is indicating that there is always a need to further define the area~ in the landscape where freezes are expected to occur. Certainly the forecasting techniques of the world's meteorological centers do a good job of recognizing patterns ol circulation favorable for frost in subtropical regions. On the basis of the fbrecast, the producer must prepare to protect the fruit and vegetable crop from damage and activate the protection procedure when the occurrence of freezing temperatures is imminent. Your (1956) reported that wood fires wcru used to protect freeze sensitive trees in the first century of the Christian era and the method was used in California prior to the beginning of the century. In Florida, the burning of wood to protect citrus fruit was practiced during the early period of the industry in that state. In recent years there have been attempts to transfer the responsibility tbr the weather warnings to private forecasters, but the profits from such a venture, so far as frost forecasting is concerned, have not been great enough to warrant the transfer. So in the US the fruit-frost warning service continues to be u responsibility of the National Weather Service. There have been few attempts to transfer responsibility for the special services fbr fruit-frost forecasting to private organizations in other countries of the world. Because other farm management decisions are weather sensitive, there have been periodic attempts to establish special weather services tbr agriculture. In the late 1950s the US established a pilot program in the lower Mississippi basin for u specialized program for agriculture. In 1962 this program was expanded to eight other regions of the country: by 1971 a plan was drafted to expand the program to

W.L. Decker ," Agricultural and Forest Meteorology 69 (1994) 9 25

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all regions in the US (NOAA, 1971). Although the limited program operated within the boundaries of 18 of the 50 US states was demonstrated to be cost effective, the program was never expanded to include all of the areas in the country. In fact, consolidation of service offices effectively reduced the area of service to agriculture. In the 1985 Farm Bill the Congress of the US included a section authorizing the Department of Agriculture to establish a service program in agricultural meteorology. Funds to activate the program have never been appropriated. It is not obvious why the weather service programs for agriculture has never been accepted in the US. Perhaps other more pressing issues have used the required resources. More likely, the failure of this program to receive legislative and executive sanction rests in two facts. First, agriculturists feel the weather is a given which must be accepted as a risk to production and the specialized weather service would be a convenience, but not an essential in management decisions. Second, the structure of the governmental infrastructure in the US places the weather service and agriculture in two divergent branches of the government. The programs of the US Department of Agriculture focus on production and marketing of commodities; while the US weather service, an environmental agency (NOAA) within the Department of Commerce. accepts primary responsibility in the preparation of forecast tools, general forecasting and severe weather warnings. It appears to be doubtful if either department is really interested in developing an effective service program in agricultural meteorology. Most countries of the world with substantial agricultural industries have a structured program in agricultural meteorology services. This effort is supported by considerable support from the WMO. In most cases, as noted in the previous paragraphs concerning the US program, there is a lack of coordination and cooperation between the meteorological service and the ministry of agriculture. This lack of cooperation was apparent from the review of the summary by Petr (1991) for agricultural meteorology in Czechoslovakia and in the report on the Soviet meteorological service by Kogan (1986). In activities conducted in Africa, Asia and Latin America by the Cooperative Institute for Applied Meteorology (a cooperative program between the NOAA and the University of Missouri) the failure of the agencies representing agriculture and meteorology in developing countries to link their efforts in agriculture weather service has been apparent. The opportunity for the development of an effective service program in agricultural meteorology remains a challenge of the 1990s and the twenty-first century. For a model of such a program one needs only to consult the literature. McQuigg (1975) presented a background for what was known about the use of weather information to assess the economic impacts of weather variability. Omar (1980) presented an update of examples of how the use of weather information and advice may be used in pest management tbr agriculture. Robertson (1980) presented a complete blue print for the development of an effective service program in agricultural meteorology. Robertson's recommendations include: (1) climatic risk analysis for long-term planning, (2) monitoring of current crop and forage conditions, (3) farm weather forecasting (short, medium and long range), (4) preparing climate seasonal outlooks, and (5) crop production forecasting.

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W L . Decker

Agricultural and b)~rest Meteorology 69 t 1994) 9.25

I0. Developments in agricultural meteorology for the twenty-first century In the past 150- 200 years agricultural meteorology has advanced from a descriptive science to an interdisciplinary field based on analytical procedures using physical and biological principles. Scientists and professionals should be challenged to build on that experience. The data base for preparing better risk analyses for applications to agriculture are in place. Instrumentation and computer power to further refine crop. animal and vegetative models should be given a high priority for basic research in agricultural and forest meteorology. The twenty-first century offers a challenge tor the development o1" applications t,. risk analysis, crop and forest models, and assessments of production. This effort will require the use of satellite remote sensing and the development ol an effective infrastructure to deliver the products to the farmer, forester and conservationist. The manpower needs of agricultural and forest meteorology are .small whc~ compared with other fields. This size makes the field particularly vulnerable 1,~ budget cuts by administrators of governmental, educational and private organizations. There is a real danger that this interdisciplinary effort will sustain a real reduction through smaller personnel pools in the research and service component,, dedicated to agriculture and forestry.

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