Attempts to relate agricultural production to weather go back at least 2,000 years and are still evolving. The twentieth century can be termed a very progressive and fertile one in respect to meteorology and agrometeo-rology (Fleming, 1996). Qualitative studies in the nineteenth century were followed by statistical analyses, then by microclimatic measurements, and most recently by modeling (Decker, 1994; Monteith, 2000).
Visual observations of the microclimate and its impact on crop plants have been going on for several centuries. However, measurement of the characteristics of the microclimate in laboratory and experimental fields was strengthened during the first half of the twentieth century. The role of water in soil climate was recognized, and the link between the physical properties of soil, heat exchange, and water movement was investigated.
It is well recognized that year-to-year variations in yields and regional commodity production are associated with variations in climate. Efforts were made to describe this relationship through statistical analysis of the correlation of yields with monthly rainfall. These analyses were a first attempt to use statistics to describe the nature of the relationship between variable yields, production, and climate. Later, the relationship between yields and rainfall was studied using multiple correlation methods. Since the 1920s (with some refinements in techniques), correlation and regression analyses have become the favorite tools for describing yield-weather relations.
The first half of the twentieth century saw great contributions toward the quantification of water loss and use by plants. Research studies on the measurement and analysis of energy fluxes above crops and on crop evapotranspiration were stimulated.
It was in this period that Bowen proposed a method (Bowen ratio) of partitioning the energy used in evaporation and heating the air. Penman published a rational method for using meteorological observations to estimate evaporation from a free water surface and vaporization from a plant canopy.
The Penman method for estimating evapotranspiration has become a standard tool for estimating the need for irrigation water by agricultural engineers, agronomists, and meteorologists throughout the world. At the same time, the Thornthwaite method for estimating potential evapotranspiration was published. Further research into the energy balance resulted in the development of the eddy correlation method for estimating latent and sensible heat transfer. Later, Blaney and Criddle developed the consumptive use principle for irrigation scheduling. This technique has been widely used by agriculturists in the semiarid regions of the world.
In more recent years, advanced and reliable instrumentation has made possible continuous measurements of biometeorological exchange processes, such as measurements of mass and energy exchange to assess the plant community's response to atmospheric variables.
By the middle of the twentieth century, technology was available to build facilities in which biological responses to environmental conditions could be measured quantitatively. These facilities provided a way to study the responses of plants and animals to diurnal variations in weather conditions. One such facility was at the California Institute of Technology. At about the same time, a large animal facility at the University of Missouri, called the Missouri Climatic Laboratory, was established for studies dealing with the physiological response and production of dairy cattle to variations in temperature, humidity, wind, and radiation loads. As a result of these facilities, several excellent studies have contributed to a better understanding of climate and weather effects on plants and animals. These two laboratories served as precursors to the development of the growth chambers used today in nearly every part of the world.
By the late 1960s and early 1970s, an extensive literature was available that documented the response of plant growth and development to environmental conditions. This information paved the way for work on mathematical models of plant response and yields to varying environmental conditions. The comprehensive development and use of plant and animal dynamic simulation models started with the availability of computers in the early 1970s. By the close of the twentieth century, several thousand computer-based plant and animal dynamic simulation models had been developed to expand scientific insights into complex biological and environmental systems, and their use has resulted in huge economic benefits.
The application of crop simulation models and simulation-based decision support systems became more acceptable to the agricultural community during the final decade of the twentieth century (Hoogenboom, 2000). Increases in the sophistication of computers and decreased costs are further fueling rapid advances in modeling. Interest has arisen in the topic of scaling from the leaf level to the global scale, to examine the global nature of climate change and its impact (Paw U, 2000).
Remote sensing detects and measures the characteristics of a target without being in physical touch with it. Information about the object is derived through electromagnetic energy. Aircraft and satellites are the main platforms for remote-sensing observations. Aerial photographs are the original form of remote sensing and remain the most widely used method. Infrared thermometry provides a way to determine the surface temperatures of plants and animals. Precise handheld infrared thermometers are commercially available to provide these measurements. The technology allows the measurement of the surface temperature with a resolution of a few square centimeters.
The development and deployment of earth satellites in the 1970s brought a revolution in remote sensing. Remote sensing now provides a sequence of reliable and irreplaceable information for agriculture planning and management (Maracchi, Pérarnaud, and Kleschenko, 2000).
The agriculture industry is the most sensitive to variability in weather and climate. Throughout the world, efforts have been made to provide agriculture with a specifically focused weather service. Most countries of the world have developed programs to provide agroclimatological services.
Unfortunately, in many countries there is a lack of coordination and cooperation to link agencies representing agriculture and meteorology in their efforts to advise farmers of weather-related risk management. This lack of cooperation has adversely affected improvements and further development in agro-advisory services. Furthermore, due to a lack of financial support, the network of meteorological stations does not adequately cover various agrometeorological zones to meet potential needs. Conflicts within and between countries often halt the collection and exchange of weather data. This has a detrimental impact on projects in which analysis of weather and climate data is attempted.
Early studies dealing with relationships between yields and climate were accomplished using limited climatic data and primitive computational procedures. The advent of the computer era saw the development of new methods for storing historical data. Computer programs are now available that can electronically archive huge amounts of climatic data. These archives have further enhanced the evaluations of weather and climate risk for agriculture. The World Meteorological Organization (WMO) supports the sharing of computerized climate data in all countries of the world (Decker, 1994).
Over the past 100 years, human activities have significantly altered the earth's atmosphere. Increases in the concentrations of greenhouse gases have led to warming of the earth's surface. An accumulating body of evidence suggested that by the last decade of the twentieth century global warming had already made significant negative impacts in a large number of regions. The menace of global climate change became a central issue of investigation in the 1990s and beyond. The investigations considered the effects of global warming on individual plants, plant stands, and entire vegetation units from regional to global scales (Overdieck, 1997). The investigations were not confined only to plants; the impact on hydro-resources, livestock, insect pests, and diseases has also been investigated.
The availability of a proper meteorological and agrometeorological database is a major prerequisite for studying and managing the processes of agricultural and forest production. Historical data and observations during the current growing season will play a critical role in increased applications of crop models and model-generated output by farmers, consultants, and other policy- and decision makers. A major and inevitable priority is to build a database of meteorological, phenological, soil, and agronomic information. The acquisition of pertinent climate and agrometeorological data, their pro cessing, quality control, and archiving, and timely access and database management are important components that will make the information valuable to agrometeorological research and operational programs. The major concerns for the availability of climate and agrometeorological data will continue to be in the areas of data collection and database management (Siva-kumar, Stigter, and Rijks, 2000; Stigter, Sivakumar, and Rijks, 2000).
The most important development for science in general and for agro-meteorology in particular is the rapid advances in electronics and their impact on computer, communication, and measurement technologies. The potential to handle data by computers and exchange them globally via the Internet is growing daily. Computers have opened the gates to the ability to store huge amounts of data and to process them through more computationally intensive statistical techniques (Serafin, Macdonald, and Gall, 2002). In agrometeorology, in which a vast amount of atmospheric data must be linked with complex sets of biological data, the availability of data in a uniform file format and the vanishing of data processing limitations result in a strong momentum for research.
Agrometeorological models have many potential uses for answering questions in research, crop management, and policy. As society becomes more computerized and technology oriented, there will be a greater possibility for the application of crop simulation models and decision support systems to help provide guidance in solving real-world problems related to agricultural sustainability, food security, the use of natural resources, and protection of the environment.
A major area for future research is the response of environmentally sensitive agricultural practices to weather events (De Pauw, Gobel, and Adam, 2000). As the public becomes more concerned about the environment, greater pressure will be put on the agricultural community to document and prove that chemical applications are not harming the environment. This will require a better understanding of the role weather plays in the fate of agricultural chemicals during application, their persistence and movement after application, and their effect on natural organisms. To gain this understand ing, research will require a more extensive interdisciplinary approach than is employed today. Adaptive research is required under on-farm or at least close to on-farm conditions, ideally with farmers participating (Olufayo, Stigter, and Baldy, 1998).
One of the most prominent current problems of humankind is global warming and its impact on the environment, water resources, agriculture, and human health. Agrometeorology has to play a leading role in the assessment of climate change, its impact on the biosphere, and adaptation strategies to increasing climate variability and climate change.
Investigation of the effects of global warming on animals will be another challenge. Future animal agrometeorologists have to search deeper into animal responses to specifically defined factors of the environment. These findings will permit the development of more adaptive, more tolerant, and more productive animals in stressful environments (Salinger, Stigter, and Das, 2000).
Increasing environmental, population, and economic pressures are creating difficulties in solving agricultural pest and disease management problems. Future climate change and increased variability will further complicate pest and disease management problems. This will require improved analyses of the weather to develop new pest management techniques and strategies. Agrometeorologists trained in weather-pest and weather-disease relationships and in the basics of pest management disciplines need to play a key role in developing pest and disease management strategies (Strand, 2000).
Neither education nor training is a one-time effort. The acquisition of knowledge and skills should be viewed as a continuous process throughout one's career (Lomas, Milford, and Mukhala, 2000). The need for continued training in agrometeorology was demonstrated by a survey on education and training requirements by the WMO (Olufayo, Stigter, and Baldy, 1998). The study revealed that the national meteorological and hydrological services in many countries do not have adequately trained personnel. Further more, in many countries there are neither facilities nor sufficient national resources available to train personnel in the home country or abroad.
In the academic setting, there is a need for creative educational programs in schools. These programs will educate younger generations on the importance of agriculture and how weather affects the food supply (Blad, 1994). Development of such programs requires professionals with an understanding of the interactions of weather and climate with agriculture. Unfortunately, fewer professionals are being trained in this discipline because of limited independent programs or departments in universities. Future training of agricultural meteorologists at the university level will require cooperative efforts between the WMO and member countries.
A second area of education that has been lacking is that of the public and agricultural producers. Perry (1994) points out that agricultural producers need to learn how to better use weather-driven models in their daily decision making. More important, they need to be taught how weather affects the various decisions they make and how their productivity or profit can be improved by using this information. The perception is that both long- and short-range forecasts are not sufficiently reliable to use in decision making (Jagtap and Chan, 2000). Research programs are needed to improve and quantify the reliability of forecasts and show how these forecasts can be used to improve decision making. Subsequently, extension programs are needed to transfer these findings to agricultural producers.
Information has value when it is disseminated in such a way that end users receive the maximum benefit from applying it (Weiss, Van Crowder, and Bernardi, 2000). Areas of agricultural expertise that have prospered throughout the years are those with a product that is appreciated and used by farmers. Plant breeding, soil science, entomology, and plant pathology are areas that have been particularly successful. Each has some specific products that attract agricultural producers. The opportunity for agrometeoro-logical services will grow dramatically if the importance and economic benefits of agrometeorological services are demonstrated. A major challenge to agricultural meteorologists is to educate agricultural producers to use weather data in various management decisions (Seeley, 1994). Demonstration of successful uses of the climate and weather through case studies is a useful example to begin discussion and to transfer potential applications to adopters of new technology.
Agrometeorology has a broad number of perspectives and applications. Computer usage has brought rapid advances in this science and has opened new doors in perspectives and applications that were not available before. The twenty-first century offers a challenge for the development of applications, risk analysis, crop and forest models, and assessments of production under global warming.
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