34 APPENDIX A • design and partial implementation of an end-to-end prediction system that will bring together observations and models for us in regions affected by El Niño; the ability to extend forecasts to a month in advance for excess rainfall and floods in the Mississippi basin by use of high-solution models; identification of the remote effects of ENSO and the local effects of land surface on the U.S. drought of 1988; planning of a multinational study to investigate rainfall patterns and variability and interactions with the land surface in the Mississippi basin; deployment of a major radiation-observing network in Oklahoma and Kansas to calibrate climate models and satellite measurements; initiation of activities to expand both the time range of and the spatial extent of prediction to greater areas of the globe including land processes; demonstration, principally by large-scale field experiments, of the importance of soil and vegetation processes in controlling land surface-atmosphere exchange of energy, water, and carbon, satellite data are now being used to define the continental patterns of these exchanges; initiation of ensemble forecasting to explore the effects of El Niño variability over the U.S., and extension of the predictability of seasonal to interannual variations over U.S. regions known to be affected by El Niño (see Figure A-2). demonstration of the benefits of El Niño forecasting to the countries and regions affected by it. These accomplishments have arisen from focused U.S. contributions to international programs, including TOGA, GOALS, and GEWEX. However, a great deal of activity in USGCRP agencies on seasonal to interannual climate has not been part of these focused efforts and therefore has not been nearly as effective in advancing the highest priorities. OPPORTUNITIES FOR USGCRP IN SEASONAL TO INTERANNUAL Based on the results of the TOGA program, the research community believes that future opportunities for the USGCRP will best be achieved in the context of a demonstration research project for an end-to-end seasonal to interannual prediction capability, initially involving El Niño. 36 APPENDIX A Such a demonstration project is reflected in national and international global change program documents that describe the need for research programs, such as CLIVAR/ GOALS and GEWEX, and call for the establishment of an international research institute (IRI) for seasonal to interannual climate prediction. Planning documents for elements of the World Climate Research Program (WCRP) and the U.S. Seasonal to Interannual Climate Prediction Program (SCPP) point to the establishment of an IRI as an important mechanism to 1. accelerate the application of existing predictive skills; 2. ensure multinational support for a program of seasonal to interannual climate prediction, including critical support for the required observing system; 3. identify scientific priorities associated with extending predictive capabilities; and 4. guide the allocation of resources accordingly. The broad outlines of such a demonstration project can be diagrammed as shown in Figure A-3. Since all useful forecasts are local, a large-scale forecast is, by itself, not sufficient for practical application. Local data (models, statistical data, etc.) must be added to the large-scale forecast to produce a regional forecast. This regional forecast is then used for application to a sector. Different applications may require different types of local forecasts: for example, applications to fisheries may require, among other things, ocean temperature, whereas applications to agriculture and water resources will require, among other things, rainfall amounts. 37 APPENDIX A In this context, an end-to-end prediction system can be defined as consisting of the following steps: • Data must be quality controlled and assimilated into a form the model can accept. Initialization: The data and the model must be combined to provide an optimal estimate of the state of the coupled system. • Large-scale prediction: One, and perhaps an ensemble, of predictions must be made. Evaluation: The data must be used to determine the accuracy of the forecast and provide an objective measure of skills and uncertainties. Assessment: The impacts of seasonal to interannual variability and must be examined, an appropriate regional site and scale must be chosen. • Regionalization: Regional data and models must be combined to provide data products for input to forecasts. • Regional forecasts: Regional data products must be combined with the large-scale forecast to provide a regional forecast. Applications: Regional forecasts can be applied to different sectors. Effectiveness of applications: Appropriate ways must be developed to distribute and communicate information (including uncertainties) about seasonal to interannual variability, prediction, and applications to a broad user community. Evaluation of applications: The impact of the applications and the effectiveness of the actions taken must be evaluated. Implementation Implementation of the concept of end-to-end prediction requires a number of things that can be diagrammed as shown in Figure A-4. |