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Decision and Policy Analysis Research Area – DAPA

What’s new in DAPA’s crop and climate modeling team

The research carried out by DAPA’s Crop and Climate modelling team seeks to develop and apply vanguard methodologies to explain the response of agro-ecosystems to environmental conditions and quantify the impact of changes in these conditions.

The research carried out by DAPA’s Crop and Climate modelling team seeks to develop and apply vanguard methodologies to explain the response of agro-ecosystems to environmental conditions and quantify the impact of changes in these conditions. Photo: N. Palmer

The Crop and Climate modeling team serves as a source of expertise in DAPA for best modeling practices.  We work on diverse projects with both internal and external clients that require modeling outputs. Here are some examples of activities that the group is currently developing.

One primary activity of our group is the generation of high resolution climate projections from downscaled and bias-corrected global climate model outputs. This data are being published through the CCAFS Climate Portal (ccafs-climate.org), has been used by more than 2000 institutions worldwide, including non-climatic scientists and next-users, arriving to more than 300 publications, on themes especially related to vulnerability assessments and increasing adaptive capacity in developing countries.

Seasonal climate forecasts are also being developed using the Climate Predictability Tool from Columbia IRI for several CCAFS projects and in the CIAT-MADR (Ministry of Agriculture and Rural Development in Colombia) agreement to help recommend optimal sowing dates and crop varieties. The RClimTool platform (a free application created by us) is used to organize and clean the weather station data that is a primary input of the forecast models.

We are also working on the development of a process-based cassava crop model, and working with CIAT’s cassava program to run nutrient trials in Asia to supply experimental data for model development. In addition, we are simulating climate change impacts on major crops across Latin America for a project with the Inter-American Development Bank (IDB), with these results feeding into economic modeling analyses using IMPACT by the Global Futures team.

Going forward, we see ongoing opportunities to collaborate with other modelling teams in DAPA and with physiologists and agronomists in CIAT’s Agrobiodiversity Research Program, which focuses on crop breeding. In addition, we work with networks of scientists dedicated to improving crop models, mainly AgMIP (The Agricultural Model Intercomparison and Improvement Project). Our results feed into decision and policy-making processes at institutions like the Colombian MADR and IDB.

The following Prezi presentation shown CIAT’s Annual Program Review recently, includes research questions and preliminary results from some of the following ongoing projects:

  • Downscaling and bias correction of GCMs (Global Climate Models) to provide future climate projections for impact studies in agriculture and adaptation to progressive climate change (Contact c.e.navarro@cgiar.org)
  • A new version of an innovative tool used for quality control and meteorological data gap-filling (RClimTool v.2.0; contact l.llanos@cgiar.org).
  • The development of a process-based cassava model in DSSAT (Contact l.p.moreno@cgiar.org).
  • The generation of seasonal climate forecasts for Colombia & Guatemala and agro-climatic forecasts in Colombia to optimize sowing date decisions and varieties (Contact d.giraldo@cgiar.org).
  • TPE identification (Target Population Environments) in Colombia to inform crop breeding efforts (Contact c.barrios@cgiar.org).
  • A study about impact of climate change in main Latin-American crops using DSSAT and the development of a mechanistic model for cassava (Contact d.obando@cgiar.org).

For more information please contact us: Sharon Gourdji (s.m.gourdji@cgiar.org) and Carlos Navarro (c.e.navarro@cgiar.org).

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