Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.
Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.
OCR for page 61
GOALS Global Ocean-Atmosphere-Land System for Predicting Seasonal-to-Interannual Climate: A Program of Observation, Modeling, and Analysis 6 Relationship of GOALS to Other Programs There are strong scientific linkages among research problems on time scales both shorter and longer than those to be considered by GOALS. These scientific linkages inevitably lead to programmatic linkages; both the scientific and programmatic linkages are described in this chapter. Ongoing efforts in dynamic extended range forecasting (DERF), which nominally covers 7-14 days in advance, would complement the modeling component of GOALS extremely well. This is especially the case for the dynamical prediction of seasonal averages using uncoupled and coupled ocean–land–atmosphere models. Although the role of the ocean in DERF is minimal, modeling and prediction of seasonal-to-interannual variations involving SST changes on these time scales would help to define more precisely the ranges at which SST changes begin to exert an influence on DERF. The GOALS prediction research strategy should include the predicting of SST and DERF to see if more detailed seasonal predictions can be made. Because the overlap between DERF and GOALS predictions is centered on predictions one season in advance, the seasonal prediction is expected to produce fruitful interactions between members of the DERF and GOALS research communities. Observations and predictive capabilities for seasonal-to-interannual time scales will aid in understanding and predicting decadal variations, as well as the effects of radiatively active (greenhouse) gases on time scales of 100 years or more. The tools of prediction on decadal
OCR for page 62
GOALS Global Ocean-Atmosphere-Land System for Predicting Seasonal-to-Interannual Climate: A Program of Observation, Modeling, and Analysis and longer time scales are similar to those used for prediction on time scales of interest to the GOALS program. A major difference is that GOALS can confine its interest to the upper ocean and to the atmosphere's current composition of gases and aerosols, whereas deeper parts of the ocean and changing chemical composition of the atmosphere must be considered as the time scale of interest increases. Simulating an accurate climatological mean state is a crucial part of longer-term climate modeling. Interannual variability is an important part of that climatological mean state. In particular, a world without interannual variability would have a different mean surface temperature from that of the actual world. Figure 6-1, a product of the Zebiak-Cane model, shows the long-term average of SST-anomaly fields from ENSO. Clearly, the ENSO itself warms the eastern Pacific by about 1K relative to the western Pacific and it warms the tropical Pacific as a whole relative to climatology. It is therefore clear that a climate model that did not simulate ENSO correctly, including its mean intensity and frequency distribution, would not be able to simulate the global surface temperature correctly. Climate models must get seasonal-to-interannual variability correct to model the current climate correctly. They must also model changes in interannual variability correctly to model climate change correctly. It has often been pointed out that a change in the intensity and regularity of ENSO would have an effect on the mean climate and that greenhouse warming may express itself partially through such changes (Zebiak and Cane, 1991; Meehl et al., 1993; Trenberth and Hurrell, 1994). Since the coupled ocean–atmosphere—land models developed for prediction of seasonal-to-interannual variations in climate bear a close relationship to the models used for prediction of decadal and longer climate variations, it is clear that advances in modeling short-term climate variability will assist in modeling longer-term climate variability. Finally, it is important to note that the World Weather Watch is a measurement system designed for weather prediction but, when extended over long periods of time, it is also useful for climate measurements. So too, an upper-ocean measurement system for climate prediction of seasonal-to-interannual time scales, if extended over long periods of time, will be useful for climate assessment and prediction for much longer time scales. ENSO is known to affect the carbon dioxide (CO2) content of the atmosphere. When an El Niño event occurs, atmospheric CO2 usually increases above its usual level. This has been attributed to reduced uptake of CO2 by terrestrial vegetation suffering from the decreased rainfall in Southeast Asia. In the equatorial Pacific, however,
OCR for page 63
GOALS Global Ocean-Atmosphere-Land System for Predicting Seasonal-to-Interannual Climate: A Program of Observation, Modeling, and Analysis Figure 6-1 1000-year mean SST-anomaly fields (K) for ENSO conditions from the Zebiak-Cane coupled model.
OCR for page 64
GOALS Global Ocean-Atmosphere-Land System for Predicting Seasonal-to-Interannual Climate: A Program of Observation, Modeling, and Analysis the upwelling of carbon-rich waters during ENSO acts to reduce atmospheric CO2 from its usual level (see, for example, Feely et al., 1987). The terrestrial effect is larger than the ocean effect, resulting in a small net increase of atmospheric CO2. However, long-term changes in the intensity and regularity of ENSO due to greenhouse warming could alter the rates of these feedback processes and thus alter the greenhouse warming. COLLABORATIVE EFFORTS Regular and systematic forecasting by coupled numerical models has begun at a number of institutions and is being proposed for the IRICP. It is expected that the GOALS research community would collaborate with systematic forecasting activities so that the problems uncovered in forecasting could become active research areas for GOALS. It is expected that those organizations engaged in systematic forecasting would be cognizant of GOALS research so that advances and improvements made in understanding basic physical processes could be incorporated into forecasting models and procedures. GOALS would organize research in support of international prediction activities as a major contribution to CLIVAR. Within the United States, research organized by GOALS would form one leg of the research-observations-predictions tripod illustrated in Figure 6-2. Note that the relationships between programs implied by Figure 6-2 mirror the structure of the GOALS Program itself, as summarized schematically in Figure 4-1. These three legs must interact with each other strongly and bear equal weight in the prediction enterprise: the entire structure would fall if one leg became out of balance with the others. This relationship has precedent in weather prediction programs and was incipient for TOGA. However, organization for GOALS is complicated by the necessary inclusion of both the oceanographic and land aspects of climate predictions. The collaborative programs that are described briefly below deserve specific mention due to their close scientific linkages to GOALS and their potentially strong contributions to the program. Global Climate Observing System (GCOS) and Global Ocean Observing System (GOOS) GOALS would capitalize on the global observations and data management systems for climate (GCOS, the Global Climate Observing System). It will also foster the development and implementation of new observing technologies that will ultimately become part of both
OCR for page 65
GOALS Global Ocean-Atmosphere-Land System for Predicting Seasonal-to-Interannual Climate: A Program of Observation, Modeling, and Analysis Figure 6-2 Functional relationship between GOALS and the other interannual research components of the U.S. Global Change Research Program. The GOALS program will serve as the principal focus for basic research on seasonal-to-interannual time scales. The proposed Global Climate Observing System (GCOS) and the proposed Global Ocean Observing System (GOOS) would provide observations worldwide, and the proposed International Research Institute for Climate Prediction (IRICP) would provide experimental prediction and assessments of seasonal-to-interannual climate variations. GCOS and GOOS (Global Ocean Observing System). Similarly, GOALS investigators would utilize gridded ocean data sets created as input for numerical prediction models of the coupled atmosphere—ocean system as part of the IRICP. Their research would contribute to improvements in these models. Global Energy and Water Cycle Experiment (GEWEX) The primary objective of GEWEX is to understand, model, and predict the characteristics of the global hydrologic cycle and the related energy fluxes. Currently GEWEX is strongly focused on land—atmosphere processes and analysis of global atmospheric water vapor. The GEWEX process studies in the Mississippi Basin (GEWEX-Continen-
OCR for page 66
GOALS Global Ocean-Atmosphere-Land System for Predicting Seasonal-to-Interannual Climate: A Program of Observation, Modeling, and Analysis tal-scale International Project [GCIP]) will quantify the temporal variability of the water and energy cycle, test and improve land-surface parameterizations, and improve macroscale water-budget models for grid-scale and subgrid-scale GCM applications. By contrast, GOALS seeks to understand, model, and predict climate variability on seasonal-to-interannual time scales. As a natural outgrowth of TOGA, GOALS would initially emphasize ocean—atmosphere interactions. Although there are no plans for GOALS to organize land-process studies, GOALS must include considerations of the land surface (soil moisture, snow cover, and so forth) to understand climate variability. GEWEX focuses on a major element of the climate system, whereas GOALS would consider the variability of the climate system itself. Clearly, GOALS and GEWEX can undertake complementary activities, with little redundancy; GEWEX could gain substantially from the GOALS research on climate system predictability, modeling, and prediction. GOALS would need to benefit from the GEWEX research on the global hydrologic cycle and major regional hydrological processes, as well as exploit GCIP products and parameterizations. The GEWEX Asian Monsoon Experiment (GAME), related to TRMM, would also provide observations and understanding of significance to GOALS. GEWEX may well benefit from the GOALS estimates, in space and time, of the atmospheric water vapor moving over the continents and its variability. GOALS is proposed as a phased project, starting from the global tropics, then considering the influence of the tropics on higher latitudes, and finally incorporating higher-latitude regions in the examination of climate variability. This phased structure maximizes the opportunity to develop collaboration between GOALS and GEWEX, and to gain optimum benefit from the successes of the two programs. World Ocean Circulation Experiment (WOCE) The World Ocean Circulation Experiment (WOCE) was established by the WCRP to address the questions of ocean heat transport and the role of the ocean in climate change on decades-to-centuries time scales. WOCE emphasizes study of the transfer of heat, momentum, and greenhouse gases between the atmosphere and the ocean. The primary goal of WOCE is to model the ocean's present state, to predict its future state, and to predict feedbacks between climate change and the ocean circulation. WOCE includes plans to study the surface and subsurface circulation of the global ocean, with an 8-year field program that ends in 1997. Synthesis and modeling efforts will con-
OCR for page 67
GOALS Global Ocean-Atmosphere-Land System for Predicting Seasonal-to-Interannual Climate: A Program of Observation, Modeling, and Analysis tinue well into the next century. As was noted with respect to GEWEX and GOALS, the WOCE and GOALS objectives are complementary, with little redundancy. Of direct relevance to GOALS are the description of the ocean's present circulation and its variability, air-sea boundary-layer processes, the role of exchange among different ocean basins, and the effect of the oceanic heat storage and transport on the global heat balance. WOCE's monitoring of the upper ocean would certainly contribute to GOALS and, in turn, GOALS would eventually support and augment WOCE upper-ocean observations through the extension in time and space of the TOGA TAO array. Atmospheric Radiation Measurement (ARM) The goal of the U.S. Department of Energy's Atmospheric Radiation Measurement (ARM) program is to improve the treatment of cloud-radiative forcing and feedbacks in GCMs. The ARM program is providing an experimental testbed for the study of important atmospheric processes, particularly cloud-radiative forcing and feedback. There is a particular emphasis on testing parameterizations for use in atmospheric models. Five primary Cloud and Radiation Testbed (CART) sites1 will be established during the next 5 to 10 years and will be operated for at least 10 years. Their five primary locales, in the proposed order of implementation are the: Southern Great Plains, United States (now operational); Tropical Western Pacific; North Slope of Alaska; Eastern Ocean Margins; and Gulf Stream, off the U.S. east coast. The first stage of the project at the Tropical Western Pacific site, will be the phased deployment of three to five Atmospheric Radiation and Cloud Stations (ARCS) in the region beginning in 1994. An ARCS will measure solar and terrestrial radiation components, cloud properties, and meteorological variables. The data will be transmitted back to a data center in the United States and will be available to any interested party. The Tropical Western Pacific site will be of particular interest for ENSO studies and improved parameterizations 1 This number may be reduced due to budget constraints.
OCR for page 68
GOALS Global Ocean-Atmosphere-Land System for Predicting Seasonal-to-Interannual Climate: A Program of Observation, Modeling, and Analysis of radiative forcing from the ARM program will be of great value in modeling seasonal-to-interannual variations. Atlantic Climate Change Program (ACCP) The Atlantic Climate Change Program (ACCP) has focused primarily on decadal time scales of climate variability. However, program objectives also explicitly include study of the variability that is associated with interannual and seasonal time scales. Therefore, there is a direct intersection of program objectives with those of GOALS. The goals of the ACCP and GOALS are clearly complementary, with the Atlantic Ocean forming a common geographic focus. The ACCP and GOALS should have common observational components. These observational studies would be designed to examine specific processes that are thought important in the exchange of energy and mass between the atmosphere and ocean, and between the atmosphere and land. They would support evaluation of subgrid-scale parameterizations in the numerical climate models to be used in both programs. Other Programs The potential interaction of GOALS with national and international programs is not limited to the major programs described above. The Surface Heat and Energy Budget of the Arctic (SHEBA) program, which will provide critical observations at high latitudes, would be of value to GOALS in meeting its long-term objectives. Atmospheric chemistry programs are expected to be the source of information on chemistry and radiation data and models, as well as information on the role of volcanic aerosols. GOALS program management and science teams would also examine possible interactions with the Joint Global Ocean Flux Study (JGOFS), the primary focus of which is understanding the carbon cycle, but which may develop data sets complementary to GOALS activities.
Representative terms from entire chapter: