E S Takle, Iowa State University, Ames, IA, USA
Copyright 2003 Elsevier Science Ltd. All Rights Reserved.
Introduction
Agricultural meteorology is an interdisciplinary science concerned with discovering, defining, and applying knowledge of the interactions between me-teorological and hydrological factors and biological systems to practical use in agriculture. An ultimate goal of agricultural meteorology is to extend and fully deploy knowledge of atmospheric and related pro-cesses to optimize agricultural production, and hence to increase profitability, decrease risk, and feed an expanding global population. A second goal that is taking on increased importance is to help conserve natural resources and protect our soil, plant, and water resources.
Environmental interactions of a wide range of agriculturally related organisms are of interest to agricultural meteorologists. Although most attention has been focused on agricultural and horticul-tural crops and forests, this segment of atmospheric science also includes environmental interactions with animals grown to provide food and fiber, insects, plant and animal pathogens, and aquaculture species.
Agricultural meteorology, like the entire field of meteorology, has its roots in the study of temperate (mid-latitude) regions of the Northern Hemisphere.
In parallel with its parent discipline, agricul-tural meteorology has more recently intensified its focus on tropical agriculture, with some of the same difficulties of paucity of data faced by tropical meteorology.
The vagaries of weather always have been a leading cause of variability in agricultural production, but the technological era has increased this vulnera-bility even as it has provided some means of insulating agriculture from adverse conditions. So, for instance, disease-resistant crops, wide availability of soil amendments and chemicals for pest control, and efficient tillage, planting, and harvesting equipment have reduced agricultural vulnerability and increased yields; however, larger fields and wide use of mono-cultures have exposed crops to vector-borne diseases and insects, and exposed soil to erosion by wind and water. The use of chemicals, new varieties, and genetically modified organisms has brought new weather dependencies.
Agriculture is arguably the most weather-sensitive sector of society. Forty percent of the land surface of the Earth is classed as arid, semi-arid, and dry subhumid but is home to millions of people, particu-larly in developing countries. For some of these areas, frequent crop failure due to adverse weather must be a part of interannual planning by farmers and regional and state policy makers. International agricultural meteorologists, therefore, have significant concern for famine and food security because of their close link to interannual variability of weather and climate.
Even in areas having what are considered ideal climates for crops, water management is a major concern, particularly in regions where competing uses of fresh water put increased pressure on agricultural uses of water.
The historical focus of agriculture to produce food and fiber for an expanding global population has been supplemented by a new thrust at the beginning of the twenty-first century. Agriculturists now also have roles in managing soil and landscapes to regulate flows of carbon, nutrients, soil amendments, and pesticides.
Atmospheric transport of pesticides, spores, and pollens (particularly those originating from genetical-ly modified plant materials) must be quantified with increased accuracy. Although uncertainty remains large, consensus estimates of sources and sinks of greenhouse gases such as carbon dioxide, methane, and nitrous oxide reveal that agriculture has a signif-icant role. For instance, agricultural sources of meth-ane from ruminant animals, rice production, and biomass burning are comparable to, or may exceed, natural emissions on a global scale. Agriculture may play a significant role in moving society from its fossil-fuel base for energy and materials to one that relies more heavily on bio-energy and bio-based materials.
Tillage practices on natural prairie lands have reduced soil carbon by up to 50% in the US Midwest.
Opportunities for agricultural recapture of soil carbon by use of high-yield plant varieties, reduced tillage, and improved management of crop residues, fertiliza-tion, and irrigation are under consideration.
Most biological and chemical processes in the biosphere are highly temperature- and moisture-dependent, and meteorology is the study of underlying physics and chemistry that governs these processes.
Emerging recognition of the importance of bio-com-plexity and ecosystem services and the need for sustainable methods of agriculture and economic development are creating new roles for agricultural 54 AGRICULTURAL METEOROLOGY AND CLIMATOLOGY
meteorology. Agricultural meteorologists, therefore, can be expected to play an increasingly larger role in working with scientists from many disciplines to meet the challenges of these new environmental concerns.
Fundamental Principles
Radiation
Agricultural meteorology is built on a foundation of fundamental physical laws with applications to the plant, animal, and soil environments. The principles of radiation describe how radiant energy received direct-ly from the sun and in diffuse form from the atmos-phere is made available to plants for photosynthesis and converted by solid and liquid surfaces into other forms of energy. Approximately 40% of the radiation emitted by the Sun is in the visible wavelength band from 0.4 to 0.7mm, sometimes referred to as the short-wave band or, for biological applications, as the band of photosynthetically active radiation (PAR). Radia-tion with wavelengths just shorter than those in the PAR zone is called ultraviolet radiation (UV-A from 0.32 to 0.40mm, and UV-B from 0.28 to 0.32mm).
Ultraviolet radiation is not used by plants for photo-synthesis but it can damage living tissue of plants and animals, particularly simple organisms.
Visible radiation may arrive at a leaf surface either directly from the Sun or indirectly by reflection from atmospheric molecules, clouds, or solid or liquid surfaces (including other plant leaves). Leaf orienta-tions and solar zenith angle cause the amount of radiation received to vary over the course of the day.
The fraction of plan area of leaves to ground area covered by the plant (including only one side of the leaf) is called the leaf area index (LAI) and is used to describe the area of the plant available for photosyn-thesis.
Radiation of wavelengths just larger than visible light is called long-wave or infrared radiation, with the band from about 0.7 to 1.5mm being referred to as the near-infrared region, which accounts for about 40%
of the solar spectrum. Wien’s displacement law (eqn [1]) relates the wavelength of radiated energy to temperature.
l¼2897
T ½1#
In eqn [1],l is the wavelength (in mm) andT is the temperature in K. Wien’s law can be used to show that most terrestrial surfaces emit radiation of 8–12mm, with most growing plants radiating at about 10mm.
The amount of dry matter produced by a plant per unit absorbed PAR is a measure of its light-use efficiency (LUE), with typical values being from 1.5 to 4.5 g dry
matter per megajoule. Chlorophyll in leaves makes plants much less reflective in the PAR region than in the near-infrared (by a factor of 4 for corn and soybeans), a fact that allows remote assessment of photosynthesis by use of the normalized differ-ence vegetation index (NDVI) derived from satellite observations.
Heat Balance
Thermodynamic principles provide the basis for rela-tions among atmospheric pressure, temperature, and density (ideal gas law), as well as the transfer and conversion of energy (first law of thermodynamics). A primary focus of agricultural meteorology is the balance of energy (conservation of energy) for the system being studied, such as a metabolizing organism or a plant-covered or soil surface. For an organism we can describe the steady state heat balance by eqn [2].
RnþM¼CþLEþG ½2#
In eqn [2],Rnis the net gain of heat from radiation;M is the net gain of heat from metabolism;Cis the loss of sensible heat to air by convection;LEis the loss of latent heat by evaporation of water;G is the loss of heat to ground and vegetation by conduction.Eis the evaporation rate (flux of water vapor per unit area), andLis the latent heat of vaporization. All quantities are considered to be averaged values per unit area. For applications to animal agriculture,Mis likely to be a significant factor, but for a soil or vegetated surface, the metabolism contribution is negligible. The radiant component of energy consists of absorbed incoming short-wave energy less net emitted long-wave energy.
A plant canopy uses a portion of the short-wave component of this net incoming radiant energy for photosynthesis. In a balanced condition, the plant uses its evapotranspiration capacity to regulate its temper-ature by converting excess sensible heat to latent heat.
Most agricultural animals, like humans, also have the capacity to rid themselves of excess heat by means of evaporation.
Surface Aerodynamics
The aerodynamics of plant interactions with the atmosphere provides a basis for understanding how plants exchange moisture, trace gases, and heat energy with and extract momentum from the free atmosphere through turbulent processes. Descriptions of the movement of pollen, spores, insects, and chemical sprays also require information about mean and turbulent flow processes on scales of centimeters to hundreds of kilometers.
Simple representations of atmosphere–surface in-teractions are given by drag coefficient formulations of AGRICULTURAL METEOROLOGY AND CLIMATOLOGY 55
vertical fluxes of quantitySfrom a surface as given in eqn [3].
Fs¼ !UtðSt!SsurfÞ ½3#
Ut is the transport velocity for the interface and the values ofSare taken at heighttand at the surface. The transport velocity at the Earth’s surface is usually parametrized by use of a drag coefficient (CDs) for the quantity S and the mean wind speed at some level (usually taken to be 10 m), i.e.fV10g(eqn [4]).
Ut¼CDsfV10g ½4#
Drag coefficients depend on atmospheric stability but are typically in the range 1&10!3 to 5&10!3 (dimensionless).
Concepts of gradient or Fickian diffusion have been used to describe fluxes by measuring vertical gradients and using assumptions or additional measurements to estimate transfer coefficients. Under this approach, the turbulent flux of a quantity is proportional to the vertical gradient of its mean quantities above the surface, eqn [5].
Fs¼ !Ks
qs
qz ½5#
whereKsis the turbulent diffusion transfer coefficient for variables, usually estimated to bekunz(kbeing von Karman’s constant (0.4) and un being the friction velocity) with an additional stability correction factor and constant for each variables. Equation [5] with an assumed form ofKsis used to derive vertical profiles of temperature and horizontal windspeed over homoge-neous surfaces. Profiles inside crop canopies are more complicated and are usually specified by empirical relations.
Evaporation and Precipitation
Agriculture is practiced over large regions of the Earth where water excess or water deficit is a major limitation for successful crops. Therefore, a major focus of agricultural meteorology and climatology is the study of precipitation and evaporation. The heat balance equation can be used to provide an estimate of the evaporation rate for a surface from knowledge of other components of the heat budget by a type of Penman–Monteith equation (eqn [6]).
LE¼DðRn!HGÞ þFw
Dþg ½6#
In eqn [6] D¼RHsqqs=qT, where RHs is the saturation relative humidity andqs is the saturation specific humidity; HG is the soil heat flux; Fw¼ CEbðRHp!RHaÞ, where CE is the bulk transfer
coefficient for moisture, b¼un=CD, RHp is the relative humidity at the plant or soil surface, RHa is the ambient relative humidity, un is the friction velocity, and CD is the drag coefficient; and g¼cp=L, where cp is the specific heat capacity of air at constant pressure. In some implementations,D and Fw are replaced by factors that include canopy and atmospheric resistances to flow of heat and momentum.
Both amount and timeliness of precipitation and evaporation are of critical importance to agriculture.
Irrigation scheduling requires reliable climate infor-mation as well as good weather forecasts, particularly with increased competition for fresh water due to increased population and expanded uses of water.
Food security exacerbates the vulnerability of many precipitation-deficient developing countries to inter-annual variability of precipitation and raises the urgency of improved seasonal to interannual forecasts of weather and climate.
Instrumentation, Measurements, and Networks
Agricultural climatology relies on records of basic meteorological measurements having been taken over extensive areas and significantly long periods of time.
These records form the basis for understanding climate variability and change and also for extracting statistically significant relationships between meteor-ological variables and soil and plant processes, plant, animal, and pest development, and seasonal yield. In addition to standard atmospheric measurements, agriculturists need measurements of soil temperature and soil moisture. These measurements are less widely recorded although they (especially soil moisture) are being recognized for their role in climate memory and hence seasonal forecasting. More such measurements and networks for measurements are needed, particu-larly in developing countries where use of technology to reduce vulnerability to climate variability is severely limited.
The central role of the surface energy balance in agricultural meteorology calls for accurate methods of evaluating fluxes of heat, momentum, moisture, and trace gases from crop, soil, and forest surfaces.
Unfortunately, this is not an easy task for heterogene-ous surfaces typically encountered in agricultural applications. Estimates of surface fluxes can be made: by drag coefficient formulations and gradient diffusion estimates, or by eddy correlation methods.
The most direct measurement of vertical fluxes is accomplished by using eddy correlation methods, which have seen increased use due to wider availability 56 AGRICULTURAL METEOROLOGY AND CLIMATOLOGY
of improvements in sensors and recording and in data archiving equipment and methods. Eddy correlation methods are based on the principle that turbulent flow near the Earth’s surface can lead to vertical fluxes of heat, moisture, momentum or trace gases in the absence of a mean vertical flux of dry air. We express the vertical flux of quantitysasFs¼csrwðtÞsðtÞ, with a time-averaged value given byfFsg ¼csrfwðtÞsðtÞg, wherecsis a constant for the particular quantity being transported, r is the dry air density, and w is the vertical wind speed. We can expresswas a sum of a time-independent mean and a time-dependent turbu-lent component,wðtÞ ¼w0þw0ðtÞ, and similarly for s,sðtÞ ¼s0þs0ðtÞ. We can then write eqn [7].
Fs¼csrðw0þw0ðtÞÞðs0þs0ðtÞÞ
¼csr½w0s0þw0s0ðtÞ þw0ðtÞs0þw0ðtÞs0ðtÞ# ½7#
After time averaging, this becomes eqn [8].
fFsg ¼csrfw0s0g þcsrfw0s0ðtÞg
þcsrfw0ðtÞs0g þcsrfw0ðtÞs0ðtÞg ½8#
The first two terms on the right-hand side of eqn [8] are zero because the mean vertical wind speed is zero. The third term vanishes because, by definition, the mean fluctuation of the vertical wind is zero. The last term can be nonzero, however, if the fluctuation of the vertical wind has correlation other than zero with the fluctuating part ofs. The time-averaged turbulent flux ofsthen reduces tofFsggiven by eqn [9], which can be computed by combining measured w0 and s0 taken from simultaneous recordings of fast response meas-urements ofwðtÞandsðtÞ.
fFsg ¼csrfw0ðtÞs0ðtÞg ½9#
The Bowen ratio is defined as the ratio of heat flux to moisture flux near the surface (eqn [10]).
B¼ C
LE¼cpfw0T0g
Lfw0q0sg ½10#
From eqn [2], ignoring metabolic contributions, we can express the sensible heat flux and latent heat flux, respectively, from the surface as in eqns [11] and [12].
C¼BðRn!GÞ
1þB ½11#
LE¼Rn!G
1þB ½12#
Flux measurements by the eddy correlation method present challenges that can lead to uncertainty of 5–30%. For a particular situation being sampled, an
appropriate averaging time must be selected to be long enough to ensure a sufficiently large sample but not so long as to mix turbulent processes with phenomena of longer time scales. Perhaps a more serious problem is the ‘representativeness’ issue: Fluxes at a point over an agricultural field are not completely vertical, particu-larly where inhomogeneities exist in the field. It can be difficult to specify the ‘surface footprint’ from which the surface flux emerged for situations having chang-ing wind directions, terrain irregularities, changchang-ing levels of atmospheric stability, or inhomogeneities of surface vegetation, soil moisture, or soil type. Year-long measurements of CO2flux over a mixed-species forest in irregular terrain, for instance, would require considerably more care in interpretation than daytime measurements over a flat field of corn. Despite the additional expense and care needed in conducting measurements and additional effort for analysis, eddy correlation measurements are increasingly being used for evaluating surface fluxes of CO2and other trace gases and moisture.
Measurement networks have been established by some local, state, federal, and international agencies to provide both an expanding climate database and a basis for near-term and seasonal agricultural decision making. There is an urgent need to expand these networks to meet the increasing food needs, particu-larly in developing countries. Remote sensing by satellite is finding expanded use in providing large-scale data of relevance to agriculture, but its use for individual farmers is limited.
Modeling and Theory
Modeling of plant interactions with the atmosphere has emerged from at least two directions: global climate modelers seeking more accurate representa-tion of energy, momentum, and moisture budgets at the Earth’s surface, and crop modelers seeking ways of understanding plant responses to climate and of projecting yields of agricultural crops. Climate scien-tists use the so-called soil–vegetation–atmosphere transfer (SVAT) models as ‘surface packages’ to which they supply meteorological data at each surface grid point at each model time step (a few minutes to hours).
The SVAT model then calculates the response of the soil and plants (e.g., evaporation or transpiration, temperature change, soil moisture content, moisture uptake by roots, rain or dew held on leaves, precip-itation runoff, momentum extracted) and returns to the climate model the surface fluxes of heat, moisture, and momentum consistent with these soil- and plant-based changes. Computational constraints limit the detail to which plant processes can be described, but, AGRICULTURAL METEOROLOGY AND CLIMATOLOGY 57
simplistic as they are, the models provide a conceptual framework for eventual coupling of more detailed crop, forest, and ecosystem models.
Crop models may be physiologically based or statistically based. Crop growth models are built on plant biophysical processes of agricultural crops and their relationship to environmental factors. They predict growth, development, and yield based on complex interactions between weather, soil character-istics, nutrients, and plants. A practical application of crop growth models is to estimate agricultural pro-duction as a function of weather and soil conditions under alternative management conditions. Basic me-teorological information needed to drive these models includes air temperature, precipitation, and solar radiation (or sunshine hours). More advanced models might additionally use dew-point temperature, wind speed, and soil temperature. Statistically-based crop models provide large-area yield predictions based on correlations of past yields with regional average weather conditions. These models tend to be much less computationally intensive, but also more location-specific and hence less transferable to other regions.
The fate of fugitive agricultural chemicals and movement of insects and pollen are addressed by models of atmospheric flow on scales of turbulent eddies to mesoscale meteorology. Large-eddy simula-tion (LES) models and models developed for use in air pollution regulation are sometimes adapted for sim-ulating transport of agriculturally related materials.
Recent advances in numerical simulation of turbulent flow through vegetation have been used to understand the aerodynamic functioning of agricultural shelter-belts. Extensions of these models to simulate the complete microclimate provide opportunities for exploring, by use of first principles, complex phy-sical relationships in heterogeneous ecosystems and landscapes.
Concern for national and international food security has prompted the need for models of seasonal yield of various food crops. Private organizations as well as governmental agencies have developed yield models based on long-range weather conditions. The Food and Agriculture Organization of the United Nations has developed agrometeorological models that forecast yield on the basis of cumulative weekly or ten-day crop water balances for providing early warning of poten-tial food security problems in developing countries.
Manipulating Microclimates to
Enhance Productivity and Reduce Risk
Agriculturists have a long history of enhancing crop growth by manipulating soil and plant microclimates
through use of irrigation, glass-houses, shelterbelts and windbreaks, snow fences, wind machines, surface mulches, certain tillage practices, alley-cropping, and agroforestry. The design and operation of such mod-ifications require considerable information on the mean, extremes, and interannual variability of climate at the specific location where the practice is imple-mented.
Horticulture crops, which typically have a higher value per unit area than grain crops, are sensitive to small changes in microclimate. Also in contrast to grains, horticulture crops are more sensitive to weath-er-induced reduction in product quality or market value. For instance, the desirable red coloration on some fruits is sensitive to optimal amounts of solar radiation at a critical stage. Manipulation of micro-climates for horticultural crops is more cost-effective than for cereals because of both their high value and their sensitivity of quality to microclimate. Weather extremes may have multiyear impacts on agricultural crops grown as perennials (e.g., fruits, nuts, grapes), which raises the cost-effectiveness of microclimate modifications for reducing such extremes.
Agriculture Meteorology Forecasts
Agriculturists can use weather forecasts with valid times of a few minutes to several months. Weather forecasts are used for planning tillage and planting operations, seed purchase, chemical application, frost suppression, grain harvesting, transport and storage, pest and disease management, and marketing, as well as crop growth calculations and long-range planning.
Major improvements over the past 10 years in our understanding of the El Nin˜o/Southern Oscillation (ENSO)-related phenomena have enhanced prospects for seasonal to interannual forecasts of agriculture-sensitive climate information. Such information now is being used in early warning systems for planning, management, and operations in some tropical areas. In regions where the climate correlation with ENSO is strong, projected ENSO factors have been used to create projections of stress indices. Other than in the Tropics and a few extratropical locations, the ENSO signal in climate is muted or absent. However, current research on this and related areas may offer future progress in seasonal to interannual forecasts.
Climate Data
Agricultural climatologists use long-term records of standard meteorological data to compute derived agriculturally related variables such as growing degree days, heat stress units, frost-free days, Palmer drought 58 AGRICULTURAL METEOROLOGY AND CLIMATOLOGY