Participants in the workshop concluded that:
1. Over the past decade there were some developments that enhanced our knowledge of climate prediction applications in agriculture. These include the following:
- There has been increasing collaboration between climate and agricultural scientiests towards effective use of climate forecasts.
- There has been quite a significant improvement in climate prediction models at the global level, especially with regard to prediction skill, understanding of processes, assimilation of data and methods to process output. Atlantic and Indian ocean components of the models have become more important.
- Agricultural research has advanced knowledge and methodology, including simulation modeling, required to use climate information effectively.
2. Currently, end users of climate predictions encounter difficulties in understanding the terminology and formats that climate institutions use to delivering forecast and other information, especially the nature of uncertainty. Users are not familiar with the distinction between weather and climate forecasts.
3. Intermediaries (e.g. agricultural extension agents) have limited understanding in using climate forecasts for applications in agricultural decision-making.
4. There are limited curriculum resources and training opportunities on the application of weather and climate (forecast) information at all levels, including applied researchers, extension intermediaries, policy makers, and for training trainers at the university level.
5. Local institutional (e.g. capacity of extension services to use agriculture simulation tools) capacity to support climate applications at the farm level is variable but generally inadequate.
1. Promote collaboration among scientists from the relevant climate and agricultural disciplines.
2. In applications, take advantages of potential cross-sector synergies between climate, agriculture and food security, water and human health.
3. Improve the capacity of agricultural and climate scientists to understand and exploit relevant information available on the World Wide Web. Promote workshops to train people on how to mine and interpret such data.
4. Enhance the ability of the community to integrate the output of Global Circulation Models (GCMs) with environmental monitoring based on remote sensing.
5. Stimulate research on linkages between models:
- How crop models can incorporate GCM outputs and remote sensing information.
- How GCMs can incorporate crop model outputs.
6. Promote greater involvement with all relevant stakeholders to better understand the decision problems and processes, and develop decision tools.
7. Identify "hotspots" for climate applications based on a global assessment of vulnerable regions where forecasts skills are high and capacity exists to use climate information to manage risk.
8. Expand economic analyses of the benefits of climate prediction applications.
9. Include soil moisture (through satellite observations) to improve the predictions of climate forecast models.
10. Develop common measures of forecast skill and quality to allow robust comparisons among different forecast systems.
11. Conduct research to develop user-oriented verification systems of the forecasts (include statistical, mathematical, and economic sciences to address this issue).
12. Since GCM outputs contain more information than is currently being released, assess the potential use of GCM outputs to predict the onset of rainfall season for regions where this subject is an important issue. Climate centers should include experienced evaluators who are familiar with the characteristics of the region targeted to help interpret and evaluate GCM outputs beyond the seasonal climatic means that are routinely released.
13. Address the issues of downscaling, GCM uncertainty and available observations, especially in developing countries.
14. Enhance capacity building on operational meteorology in different regions of the world.
15. Expand the scope of the seasonal climate prediction and incorporate the whole spectrum of climate variability (from intra-seasonal to climate change issues).
16.Promote linkages between climate modelers and local meteorologists to develop sound empirical forecast models.
17. Develop specific modeling tools for analyses at different spatial scales.
18. Improve the current crop simulation models and incorporate more physiologically based processes in order to make them more robust.
19. Develop procedures for updating crop model parameters on a regular basis (especially genetic coefficients).
20. Promote establishment of regional networks for standardized crop observations.
21. Move economic analyses beyond a focus on single crops toward modeling cropping systems, integrated crop-livestock systems and whole farm modeling.
22. Through the International Consortium for Agricultural Systems Applications (ICASA), promote a globally-coordinated initiative in crop modeling and systems analyses for model improvement, model comparison and capacity building.
Capacity Building, Network Development and Institutional Partnership
Increasing farmers prosperity through better use of climate science and associated applications must consider the following aspects:
- Capacity building for climate producers, intermediaries and users (farmers).
- Development of networking among stakeholders.
- Strengthening the institutional partnerships.
23. Given that the science of climate forecasting and applications is relatively recent, it is important to undertake capacity building activities at all levels from climate forecasting to national agricultural research systems to intermediaries to the farm level, especially in developing countries.
24. The focus of capacity building activities for different levels of stakeholders should be formulated according to their needs through an end-to-end capacity building approach involving all stakeholders in the process in order to ensure effective feed back from users to climate producers. Hence training should be organized for:
- Producers of climate information - to produce climate information products in a form that is simple and easy to understand.
- Agriculture scientists in research agencies and universities - to support climate forecast applications and develop recommendations for effective farm-level adaptation strategies to climate risk.
- Communication agencies (e.g. media) - in broadcasting climate forecast information in such a way as to assist the user communities in formulating appropriate actions.
- Extension workers and community-based organizations - to deliver climate forecast application technologies to end-users (e.g. farmers) and assist them in using the technologies.
25. Given that climate application is generally not included in the curricula of agricultural universities, the Agricultural Meteorology Division and the Education and Training Department of WMO should review this issue and work with agricultural universities to include climate forecast modules in their academic curriculum.
26. There is a need to train national agencies in climate prediction applications in agriculture, so they can share the knowledge with extension agents or other intermediaries, and with for policy makers to increase their awareness of climate applications in agriculture.
Networking and Institutional Partnership
27. Strengthen networking and institutional partnership through:
- Linking all relevant national organizations to form strong partnerships with each other and with the global programs initiated by United Nations Agencies, such as WMO and FAO; and International Organizations such as CGIAR, IRI, START; and Regional Organizations such as ACMAD and AGRHYMET.
- Establishing a web-based network among national, regional and international organizations and agencies that can facilitate development of end-to-end systems for applying climate forecasts in the agriculture sector and, policies to address current and future climate risks.
- Linking individuals who work actively in the area of climate forecast application in agriculture through an informal web-based network and other means that will help them further develop their capacity to support climate applications in agriculture in the broadest sense (including technical, socio-economic and institutional aspects), and access information on advancing of climate application technologies, funding sources, data, tools, and periodical meeting/conferences on climate applications.
- Including representatives from the scientific community who work in the concerned area on a Steering Committee for the proposed networks.
28. Document success stories, failures and lessons through case studies to demonstrate the real value of climate information to agricultural communities and scale up from case studies to regional and global scales.
Climate Outlook Forums (COFs)
29. Adopt a holistic approach to COFs including different sectors such as agriculture, hydrology, health as well as media.
30. Explore alternative ways of conducting regional COFs with more active participation of stakeholders.
31. Improve COF systems (terms, applications) by establishing a consortium (farmers, researchers, etc.), to seek funds to conduct future regional COFs.
32. Develop a common language for the dialogue between climate information producers and end-users.
33. Streamline communication systems for delivery of climate information to end-users.
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