Chapter 4 Weather and Climate Forecasts for Agriculture This chapter was written by H. P. Das, F. J. Doblas-Reyes, Anice Garcia, James Hansen, Luigi Mariani, Ajit Nain, K. Ramesh, L. S. Rathore and R. Venkataraman Sections of this chapter were internally reviewed by facilitators Andrew Challinor, Luigi Mariani, Kees Stigter, Natraj Subhas and R. Venkataraman This chapter was externally reviewed by B. Alaba, B. Chipindu, Ajit Govind and Samsul Huda The chapter was co-ordinated and edited by H. P. Das and Kees Stigter 1 4.1Need for and Requirements of Weather Forecasts for Agriculture 4.1.1. Climate-Based Strategic Agronomic-Planning Weather plays an important role in agricultural production. It has a profound influence on the growth, development and yields of a crop, incidence of pests and diseases, water needs and fertilizer requirements in terms of differences in nutrient mobilization due to water stresses and timeliness and effectiveness of prophylactic and cultural operations on crops. Weather aberrations may cause (i) physical damage to crops and (ii) soil erosion. The quality of crop produce during movement from field to storage and transport to market depends on weather. Bad weather may affect the quality of produce during transport and viability and vigor of seeds and planting material during storage. Thus, there is no aspect of crop culture that is devoid of the impact of weather. However, (a) the weather requirements for optimal growth, development and yield of crops, incidence, multiplication and spread of pests and diseases and susceptibility to weather-induced stresses and affliction by pests and diseases vary amongst crops, with the same crop with the varieties and with the same crop variety with its growth stages. Even on a climatological basis weather factors show spatial variations in an area at a given time, temporal variations at a given place and year to year variations for a given place and time. For cropping purposes weather over short time periods and year-to-year fluctuations at a place over the selected interval have to be considered. For any given time-unit the percentage departures of extreme values from a mean or median value, called the coefficient of variability, is a measure of variability of the parameter The shorter the time-unit, the greater is the degree of variability of a weather parameter. Again, intensity of the above three variations differ amongst weather factors. Over short periods of time, rainfall is the most variable of all parameters, both in time and space. In fact for rainfall the short-period inter-year variability is large, which necessitates expressing variability in terms of percentage probability of realizing a given amount of rain or specify the minimum assured rainfall amounts at a given level of probability. For optimal productivity at a given location crops and cropping practices must be such that while their cardinal phased weather requirements match the temporal march of the concerned weather element(s), endemic periods of pests, diseases and hazardous weather are avoided. In such 2 strategic planning of crops and cropping practices, short-period climatic data, both routine and processed (like initial and conditional probabilities), have a vital role to play. 4.1.2. Weather Vagaries Despite careful agronomic planning on a micro scale to suit local climate crops experience various types of weather vagaries on a year-to year-basis. The effects of weather anomalies are not spectacular. Deviations from normal weather occur with higher frequencies in almost all years, areas and seasons. The most common one is delay in start of the crop season due to rainfall vagaries in case of rainfed crops (as observed in semi arid tropics) and temperature vagaries (as observed in tropics, temperate zones and subtropics) or persistence of end of the season rains in case of irrigated crops. The other important one is the deviations from the normal features in the temporal march of various weather elements. The effects of weather vagaries on crops build up slowly but are often widespread enough destabilize the national agricultural. 4.1.3. Usefulness of Weather Forecasts. Occurrences of erratic weather are beyond human control. However, it is possible to adapt to or mitigate the effects of adverse weather if a forecast of the expected weather can be had in time. Rural proverbs abound in giving thumb rules for anticipation of local weather and timing of agricultural operations in light of expected weather. Basu (1953) found no scientific basis for anticipation of weather in many proverbs/folk lore in vogue. In a recent study Banerjee et al. (2003) have arrived at conclusions similar to that of Basu (1953). However the proverbs/folklore show that the keenness of farmers to know in advance the likely weather situations for crop operations is time immemorial. Agronomic strategies to cope with changing weather are available. For example delay in start of crop season can be countered by using short duration varieties or crops and thicker sowings. However, once the crop season starts the resources and technology get committed and the only option then left is to adopt crop-cultural practices to minimize the effects of mid-seasonal hazardous weather phenomena on the basis of advanced intimation of their occurrences. For example, effects of frosts can be prevented by resorting to irrigation or lighting up of trash fires. Thus, the usefulness of medium range weather forecasts with a validity period that enables farmers to organize and carry out appropriate cultural operations to cope with or take advantage of the forecasted weather is warranted. With the rapid advances in Information 3 Technology and its spread to rural areas, the demand for provision of timely and accurate weather forecasts for farmers is on the increase. 4.1.4. Essential requirements of Weather Forecasts for Agriculture. Receipt of forecasts of late start of the crop season necessitates agronomic changes from the normal at the field level. Organization and execution of such a strategy comes under the category of high cost decisions and will take quite sometime. Therefore, pre-seasonal forecasts must have a validity period of at least 10 days and not less than a week. Field-measures to counter the effects of forecasted hazardous weather, pests, diseases etc take time and hence mid-seasonal forecasts must preferably be communicated 5 days and not less than 3 days in advance. Dissemination of weather forecasts after their formulation to agricultural users should be quick with minimum possible temporal lag. Some of the measures like pre-seasonal agronomic corrections, control operations against pests and diseases, supplementary irrigation and pre-poning of crop harvests will be high cost decisions. Therefore, the weather forecasts must not only be timely but must also be very accurate. Weather forecasts must ideally be issued for small areas. In the case of well-organized weather systems the desired areal delineation of forecasts can be realized. In other cases the area(s) to which the weather forecasts will be applicable must be unambiguously stated. 4.1.5. Some Unique Aspects of Agricultural Weather Forecasts. There are some aspects of weather forecasts for agriculture that are quite distinct from synoptic weather forecasts. In synoptic meteorology the onset and withdrawal of the monsoon is related to changes in wind circulation patterns in the upper atmosphere and associated changes in precipitable water content of air in the lower layers. Preparation of field for sowing and sowing of crop with adequate availability of seed zone soil moisture requires copious rains. Rains that do not contribute to root zone soil moisture of standing crops are ineffective. Agriculturally Significant Rains, ASRs (Venkataraman, 2001) are those that enable commencement of cropping season and that contribute to crop water needs. For agricultural purposes it is the start and end of ASRs that are important. ASRs may be received early as thundershowers or may be delayed. Venkataraman and Krishnan (private communication) have drawn attention to the feasibility of commencement of cropping season much ahead of the monsoon season in Karnataka, Kerala, West Bengal and 4 Assam in India with the help of pre-monsoon thunderstorm rains. The climatological dates of withdrawal of monsoon and end of ARS in a region can also differ significantly. Both start and end of ASRs in a province may show intra-regional variations. Use of Dependable Precipitation, DP at various probability percentage levels and Potential Evapotranspiration have been suggested for delineation of start and end of crop growth period on a climatological basis (Cocheme and Franquin, 1967; Brown and Cocheme, 1973; Venkataraman, 2002) and have been used in many regions. The methods however differ in time-units employed, probability level chosen for DP and fraction of PET used as a measure of adequacy of crop- rainfall. Based on considerations of level of Evaporative Power of AIR, EPA, rainfall amount required to overcome the evaporative barrier and phased moisture needs of crops demands Venkataraman (2001) had suggested (a) use of weekly or decadal periods and (b) that commencement and end of ASR be taken as the one when DP at 50% probability level begins to exceed PET and become less than 50% of PET respectively. Monthly values of PET can be interpolated to derive short period values. So when rainfall probability data for weeks or dekades and monthly values of PET are available the commencement and end of ASRs can be easily delineated. While clear weather is required for sowing operations it must be preceded by antecedent seed zone soil moisture storage. Thus, forecasts of clear weather following a wet spell are crucial. Such forecasts of dry spells following a wet spell are also required for the initiation of disease control measures. There are areas where frequent thunderstorm activity precedes the arrival of rains associated with well-defined weather systems and the rains once started persist without any let up. In such cases the agronomic strategy should be to utilize pre-seasonal rains for land preparation and resort to dry sowings in anticipation of rain in the next few days. Land preparation can be done on post-facto receipt of thundershowers. However, dry-sown seeds will get baked out in absence of rains. It is prudent to sow on receipt of forecast of impending rains. So forecasts of rainy season become crucial in such areas. In temperate regions frost can cause severe menace to agricultural productivity. Frosts normally occur when the screen temperatures reach zero degrees centigrade. The depression of radiation minimum temperature of crops below the screen minimum will vary with places and seasons. The radiative cooling will be maximal under cold nights with clear skies and minimal with warm night temperatures with cloudy skies. Thus due to nighttime radiative cooling of crop canopies, crop-frosts can occur even when screen temperatures are above 5 zero degrees centigrade. Similarly Dew, which influences the crop water needs and the incidence of diseases, can get deposited over crops at lower relative humidities than what is deducible from a thermohygrograph. The Frictional layer near the ground is ignored by the synoptic meteorologist but low level winds in this layer influence the long-distance dispersal of insects (like desert locusts) and disease spores (wheat rusts). It is hence clear that the types of forecast for critical farming operations would have some unique features that would require further processing of some elements of synoptic weather forecasts. The above aspect is dealt with in a detailed manner and on a weather element-wise basis in a subsequent chapter. 4.2 Characters of present weather forecasts A deterministic definition states that “weather forecast describes the anticipated meteorological conditions for a specified place (or area) and period of time”; an alternative and more probabilistic definition states that “weather forecast is an expression of probability of a particular future state of the atmospheric system in a given point or territory”. In view of the above a Weather forecast may be defined as a declaration in advance of the likelihood of occurrence of future weather event(s) or condition(s) in a specified area(s) at given time-period(s) on the basis of (i) a rational study of synoptic, three-dimensional and time-series data of sufficient spatial coverage of weather parameters and (ii) analyses of correlated meteorological conditions. The positive effect of weather forecasts in agriculture is maximized if weather forecasters are aware of the farmer’s requirements and farmers know how to make the most use of the forecasts that are available. Response amongst varieties of a crop to weather phenomenon is one of degree rather than of type. However, the type and intensity of weather phenomenon that cause setbacks to crops vary amongst crops and with the same crop with its growth stages. Because of crop-weather reasons, crops and cropping practices vary across areas even in the same season. In the provision of weather forecasts for agriculture the emphasis should be on the look out for incidence of abnormal weather and prevalence of aberrant crop situations. Now, one cannot determine abnormality unless one knows what the normal picture is, both with reference to crops and weather. Thus, the first step in familiarizing the weather forecasters with the weather warning requirements of farmers is the preparation of “Crop Guides to Forecasters” (i) giving the times of occurrence and duration of developmental phases from sowing to harvest of major crops in the 6 regions of their forecast interest and (ii) specifying the types of weather phenomenon for which weather warnings and forecasts are to be issued in the different crop Phases. Such guides can be used by the forecasters to prepare period-wise, region-wise calendars of agricultural weather warnings. In the crop guide to forecasters normal values of important weather elements in the crop season, for the national short-time period adopted for agrometeorological work, should also be given and such guides made available to the farming community so that any farmer will know immediately the normal features of weather for a given crop and season in his place. The week is the accepted time-unit for agrometeorological work in India. The Crop-weather calendars in use in India, using the week as the time-unit, vide a sample depicted in Figure 4.2.1, are excellent examples of the type of compiled information that would assist forecasters in framing weather warnings and forecasts for use of farmers. In weather forecasting we now have a very wide range of operational products that traditionally are classified in the following groups: 1. Now-casting (NC) 2. Very Short Range Forecast (VSRF) 3. Short Range Forecast (SRF) 4. Medium Range Forecast (MRF) 5. Long Range Forecast (LRF) Each weather forecast can be defined on the basis of the following criteria: 1. dominant technology 2. temporal range of validity after emission 3. characters of input and output time and space resolution 4. broadcasting needs 5. accuracy 6. usefulness Table 1 shows a general description of different types of weather forecasts founded on criteria from 1 to 5; Table 2 presents an almost qualitative description founded on criteria 5 and 6. 7 Table 1 – Definition of weather forecasts Type of Acronym Definition Characters of output Dominant technology Other aspects Time and space weather resolution forecast of typical products Now- NC A description of A relatively complete set Analysis techniques, extrapolation A fundamental prerequisite Typical time casting current weather of variables can be of trajectories, empirical models, for NC is the operational resolution is variables and 0 - produced (air temperature methods derived from forecaster continuity and the 1 hour; typical 2 hours and relative humidity, experience (rules of thumb). Basic availability an efficient space resolution description of wind speed and direction, information is represented by data broadcasting systems (eg: is of the order of forecasted solar radiation, from networks of Automatic very intense showers gamma mesocale weather precipitation amount and Weather Stations, maps from affecting a given territory (20-2 km). variables type, cloud amount and meteorological radar, images from must be followed with type, etc.) meteorological satellites, local and continuity in provision of regional observations and so on) information for final users. Very VSRF Up to 12 hours A relatively complete Analysis techniques, A fundamental Typical time short- description of set of variables can be extrapolation of trajectories, prerequisite for VSRF is resolution is 1-3 range weather produced (see interpretation of forecast data the availability an efficient hours; typical forecast variables nowcasting) and maps from NWP (LAM and broadcasting systems (eg: space resolution GM), empirical models, methods frost information must be is of the order of derived from forecaster broadcasted to farmers beta mesocale experience (rules of thumb). The that can activate irrigation (200-20 km). basic information is represented facilities or fires or other by data from networks of systems of protection). Automatic Weather Stations, maps from meteorological radar, images from meteorological satellites, NWP models, local and regional observations and so on) 8 Short- SRF Beyond 12 A relatively complete Interpretation of forecast data In SRF the attention is Typical time range hours and up set of variables can be and maps from NWP (LAM and centred on mesoscale resolution is 6 weather to 72 hours produced (see GM), empirical models, methods features of different hours; typical forecast description of nowcasting) derived from forecaster meteorological fields. SRF space resolution (*) weather experience (rules of thumb). The can be broadcasted by a is of the order of variables basic information is represented wide set of media alfa or beta mesocale by data from networks of (newspapers, radio, Tv, (2.000-20 km). Automatic Weather Stations, web, etc.) and can maps from meteorological represent a fundamental radars, images from information for farmers. meteorological satellites, NWP models, local and regional observations and so on) 9 Medium- MRF Beyond 72 hours A relatively complete set Interpretation of forecast data and In MRF the attention is Typical time range and up to 240 of variables can be maps from NWP (GM), empirical centred on synoptic features resolution is weather hours produced (see nowcasting)models derived from forecaster of different meteorological 12-24 hours; forecast (*) description of experience (rules of thumb). The fields. MRF can be typical space weather basic information is represented by broadcasted by a wide set of resolution is of the variables NWP models. Techniques of media (newspapers, radio, order of alfa "ensemble forecasting" are Tv, web, etc.) and can mesocale adopted in order to overcome the represent a fundamental (2.000-200 km). problem of depletion of skill information for farmers. typical of forecasts founded on NWP models. Instead of using just one model run, many runs with slightly different initial conditions are made. An average, or "ensemble mean", of the different forecasts is created. This ensemble mean will likely have more skill because it averages over the many possible initial states and essentially smoothes the chaotic nature of climate. In addition, it is possible to forecast probabilities of different conditions. 10