Abstract
Seasonal climate prediction offers the potential to anticipate variations in crop production early enough to adjust critical decisions. Until recently, interest in exploiting seasonal forecasts from dynamic climate models (e.g. general circulation models, GCMs) for applications that involve crop simulation models has been hampered by the difference in spatial and temporal scale of GCMs and crop models, and by the dynamic, nonlinear relationship between meteorological variables and crop response. Although GCMs simulate the atmosphere on a sub-daily time step, their coarse spatial resolution and resulting distortion of day-to-day variability limits the use of their daily output. Crop models have used daily GCM output with some success by either calibrating simulated yields or correcting the daily rainfall output of the GCM to approximate the statistical properties of historic observations. Stochastic weather generators are used to disaggregate seasonal forecasts either by adjusting input parameters in a manner that captures the predictable components of climate, or by constraining synthetic weather sequences to match predicted values. Predicting crop yields, simulated with historic weather data, as a statistical function of seasonal climatic predictors, eliminates the need for daily weather data conditioned on the forecast, but must often address poor statistical properties of the crop-climate relationship. Most of the work on using crop simulation with seasonal climate fore- casts has employed historic analogs based on categorical ENSO indices. Other methods based on clas- sification of predictors or weather types can provide daily weather inputs to crop models conditioned on forecasts. Advances in climate-based crop forecasting in the coming decade are likely to include more robust evaluation of the methods reviewed here, dynamically embedding crop models within cli- mate models to account for crop influence on regional climate, enhanced use of remote sensing, and research in the emerging area of 'weather within climate.'
Highlights
Forecasts of climate fluctuations with a seasonal lead-time are possible because the atmosphere responds to the more slowly varying ocean and land surfaces, an example being climate fluctuations associated with the El Niño-Southern Oscillation (ENSO) in the tropical Pacific
If farmers are to benefit from seasonal climate forecasts, the information must be presented in terms of production outcomes at a scale relevant to their decisions, with uncertainties expressed in transparent, probabilistic terms
(2) Because crop yield is not a simple function of seasonal total rainfall, the accumulation of errors going from seasonal climatic predictors (e.g. sea surface temperatures (SSTs)), to local seasonal means, to crop response, implies that predictions of effects such as crop response will be less accurate than predictions of climatic means
Summary
Forecasts of climate fluctuations with a seasonal (i.e. several months) lead-time are possible because the atmosphere responds to the more slowly varying ocean and land surfaces, an example being climate fluctuations associated with the El Niño-Southern Oscillation (ENSO) in the tropical Pacific. (2) Because crop yield is not a simple function of seasonal total rainfall, the accumulation of errors going from seasonal climatic predictors (e.g. SSTs), to local seasonal means, to crop response, implies that predictions of effects such as crop response will be less accurate than predictions of climatic means Recent research challenges these assumptions (Hansen 2005). Advances in the use of seasonal climate forecasts with agricultural simulation models contribute to (1) translating climate forecasts into more relevant information about impacts within the system being managed; (2) ex-ante assessment of benefit to motivate support and insights to target interventions; and (3) guiding management responses through the use of model-based systems that support discussion and decision-making (Hansen 2005)
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
