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JAMSTEC 2002 Annual Report Frontier Research System for Global Change our understanding of the effects of solar radiation on the terrestrial carbon cycle, and provides a critical foundation for satellite-based monitoring of PAR and modeling of the global carbon cycle. d. Marine Biological Process Model Group We have evaluated the effects of global climatic and environmental changes on biological process such as productivity in the ocean. We also have examined that possible feedback to the global environments through changes in the ocean carbon cycles resulted from the ecosystem changes. Especially, we aim at discovering the functional relationship of the lower trophic level ecosystem change in the North Pacific to the recent global climate variation. During FY , we observed signals of alteration of physical, chemical, and biological environments of the water column in one of the world's most productive regions, the Oyashio Water in the western subarctic North Pacific from s to s. We found increased a) conventional view wind stress solar radiation month Jan. Feb. Mar. Apr. May. Jun. Jul. fresh water inflow Phytoplankton bloom 50m 100m 150m b) novel view wind stress solar radiation month Jan. Feb. Mar. Apr. May. Jun. Jul. fresh water inflow 50m 100m 150m Critical Depth Mixed Layer Depth Critical Depth Mixed Layer Depth Nutrient concentration Fig.17 Physical/chemical/biological processes from winter to spring in the Oyashio Water: comparison of the conventional view a) and novel view b). density gradient between surface and subsurface waters that curbed the vertical mixing of seawater during this period. Consequently, not enough nutrients from the deeper ocean were supplied to diatoms. The biomass of spring zooplankton, as an indicator of the secondary production, was also decreased (Figure ). On the other hand, looking only at wintertime, production of diatoms was enhanced due to a stable, shallow mixed layer with sufficient nutrients, which may be the result of an increased wintertime food availability to Neocalanu spp and that caused earlier maturity of these species. 6. Integrated Modeling Research Program The mission of the Program is to develop "new" climate models, global environmental models and ocean data assimilation systems to be run on the world's fastest "Earth Simulator" which was completed in March . The following are the current targets of development : (i) Spectral atmosphere model with a horizontal resolution T and layers in the vertical, world ocean model with . horizontal resolution and layers in the vertical, and a coupled A-O GCM consisting of the two. An objective is to carry out long-term global warming experiments for oceans that contain eddies. (ii) Atmosphere model with a horizontal mesh size of km or less by which tropical cloud clusters and other meso-scale atmospheric systems can be represented explicitly. Similarly, eddy resolving world ocean models are being developed as the coordinate system to cover the globe cubic-grid and incosahedral-grid (quasi-uniform grids) are adopted. (iii) Development of models to include new elements such as aerosols' effects on clouds, or the global carbon cycle, on the basis of currently existing climate models cooperating with other research programs. (iv) In addition to the above described model development, ocean data assimilation systems are also being developed in this program. Four-dimensional variational data assimilation systems, which incorporate satellite and in-situ observational data into numerical models, are the target of development. These can 134
Japan Marine Science and Technology Center Frontier Research System for Global Change provide realistic initial conditions for adequate prediction and also useful re-analysis datasets for accurate estimation of ocean circulation processes. a. Coupled Model Development a-. Future Climate Change Projection Using a High- Resolution Coupled Ocean-Atmosphere Climate Model The aim of this project is to conduct a series of future climate change projection experiments using a high-resolution coupled ocean-atmosphere climate model on the Earth Simulator. The project team consists of members of Center for Climate System Research of the University of Tokyo (CCSR), National Institute for Environmental Studies (NIES), and Frontier Research System for Global Change (FRSGC). For the high-resolution future climate change projection, we have targeted the following spatial resolution of the model: T spectral truncation (approximately .˚) in horizontal and levels in vertical for the atmospheric part .˚ .˚ in horizontal and levels in vertical for the oceanic and sea-ice part With this atmospheric resolution, regional-scale climatic features such as Baiu front and tropical cyclones can be represented. The oceanic resolution should be higher so that the model can reproduce realistic temporal variation of sea-surface height and the complex ocean current system in the northern North Atlantic and the Arctic Oceans, which is critically important to reproduce the North Atlantic Deep Water (NADW) realistically. Further details are referred to the report of the project in this volume. a-. Improvement of Physical Processes in Climate Models (i) Development of new radiation scheme So far there has been no unique method applicable to treat any overlapping of bands on radiative transfer calculation when we require both high accuracy and computational efficiency. After examining several possible schemes, it is found that only one scheme is not sufficient to treat all overlapping bands with the same accuracy. Therefore we develop an optimized scheme to obtain k-distribution parameters for overlapping bands by combining completely uncorrelated, perfectly correlated and partly correlated schemes. By use of this newly developed scheme, calculations of radiative flux and atmospheric heating/cooling rate were performed and the results were compared with corresponding results of the LBL calculations for six model atmospheres (Tropical, Midlatitude summer and winter, Subarctic summer and winter and the US Standard Atmosphere). The results are shown in Fig. P (mb) 0.1 1 10 1E+2 a TRO CKD LBL Error 1E+3 -12.0 -8.0 -4.0 0.0 4.0 Heating Rate (K/d) P (mb) 0.1 1 10 1E+2 c CKD LBL Error CKD LBL Error -0.2 0.2 -0.4 0.0 0.4 Error (K/d) 1E+3 -12.0 -8.0 -4.0 0.0 Heating Rate (K/d) P (mb) 0.1 1 10 1E+2 e MLW SAW 1E+3 -12.0 -8.0 -4.0 0.0 Heating Rate (K/d) P (mb) 0.1 1 10 1E+2 1E+3 b P (mb) 0.1 1 10 1E+2 d MLS CKD LBL Error -12.0 -8.0 -4.0 0.0 Heating Rate (K/d) CKD LBL Error CKD LBL Error -0.2 0.2 -0.4 0.0 0.4 Error (K/d) 1E+3 -12.0 -8.0 -4.0 0.0 Heating Rate (K/d) -0.2 0.2 -0.4 0.0 0.4 -0.2 0.2 -0.4 0.0 0.4 Error (K/d) Error (K/d) -0.2 0.2 -0.4 0.0 0.4 Error (K/d) P (mb) 0.1 1 10 1E+2 1E+3 f SAS USS -12.0 -8.0 -4.0 0.0 Heating Rate (K/d) -0.2 0.2 -0.4 0.0 0.4 Error (K/d) Fig.18 The comparison of heating rates for four transmission schemes to those of LBL model. Black solid line represents LBL results; the dashed lines with different colors represent errors of the four schemes to LBL results. (a) H 2 O, CO 2 and O 3 (630-700cm -1 ); (b) H 2 O, N 2 O and CH 4 (1200-1350cm -1 ); (c) H 2 O, CO 2 and O 3 (940-1200cm -1 ); (d) H 2 O and CH 4 (3900-4540cm -1 ). 135
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