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Decision and Policy Analysis Research Area – DAPA

Seasonal climate and crop forecasts for agricultural risk management

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Workshop on Numerical Modeling in Mesoscale Weather and Climate using the Eta Model: Physical and Numerical Aspects

Written by Diana Giraldo and Carlos Navarro

A major problem for agricultural production in the Andes constitutes the very oscillating and irregular climatic variations. Knowledge on weather condition allows for the development of seasonal management strategies for producers who depend on rainfed agriculture mainly.

Currently, the global climate models (GCMs) are the best available scientific tool to simulate the response of the global climate system to a change in atmospheric composition. However, the PROBLEM for local agricultural applications is that these are in a resolution of 100 to 300 km. From there, the NECESSITY to use dynamic Regional Climate Models (RCM) whose resolution can go up to 10 km resolution and which can depict regional effects and teleconnection patterns (processes that take place over long distances). Therefore, the OPTION for seasonal climate forecasting in agriculture is to combine different dynamic and statistical regionalization techniques to build common frameworks in processes of inter-comparison and combined use of models and methods.

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CIAT-INPE project presentation

Remember that in order to predict the weather for the next months (90, 120 days), the main focus should be based on the existing possibilities that the atmosphere is affected by external influence mechanisms (TSM) and predictable to an interval of several months. The idea is not to predict the specific weather conditions on a given day (absolute values), but to determine the average conditions over several days (trend), taking into account the associated uncertainty. When reliable climate forecasts are available, farmers can decide when, how and what to plant and can also decide on the type of management practices they will apply to a given cropping system, and this in turn results in increased agricultural output.

One of the most important activities carried out under the project was the participation of CIAT and CIP in WorkEta IV – “Workshop on Numerical Modeling in Mesoscale Weather and Climate using the Eta Model: Physical and Numerical Aspects”, held from March 3-8 in Cachoeira Paulista (SP, Brazil), at the Center for Weather Forecast and Climate Studies (CPTEC) del INPE. The main objective of the Workshop was to contribute to the improvement and updating of professionals from different countries in Latin America, through knowledge-sharing of new developments and trends of high-resolution numerical modeling, via:

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Participants of Worketa IV

• Conferences addressing the numerical aspects of dynamics, physics and recent research in mesoscale models.

• Projects departing from theoretical and practical training, which involve installing and running different modes of Eta regional model: (1) weather, (2) seasonal climate forecast and (3) climate change.

• Presentations of participants involved in research activities.

Among the most representative conference were: (1) Land Surface in Weather and Climate Models de by M. Ek – NOAA Federal (2) Prevision Metrics by J. Rozante (3) Forecast ensemble / seasonal climate forecast by J.Bustamante – CPTEC (4) Change projections by A. Lyra – CPTEC (5) Application in agricultural sector – CCST. These presentations are available at the DAPA-Slideshare (see below). For more information about the course programming please see http://cursos.cptec.inpe.br/iv-worketa .

After introducing the Eta regional dynamic model by CPTEC, the next activity within the project’s main objective is a comprehensive introduction to statistical seasonal forecast model (CPT-IRI). In a following blog-post we will report the discussions on using the CPT tool to implement the crop yield forecasts.

 


 

 


 

 


 

 


 

 


 

 


 

For more info, please contact us:

Diana Giraldo d.giraldo@cgiar.org

Carlos Navarro c.e.navarro@cgiar.org

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