Toshiyuki Nakaegawa

Coupled Climate Simulation by Constraining Ocean Fields in a Coupled Model with Ocean Data

Abstract The authors developed a system for simulating climate variation by constraining the ocean component of a coupled atmosphere–ocean general circulation model (CGCM) through ocean data assimilation and conducted a climate simulation [Multivariate Ocean Variational Estimation System–Coupled Version Reanalysis (MOVE-C RA)]. The monthly variation of sea surface temperature (SST) is reasonably recovered in MOVE-C RA. Furthermore, MOVE-C RA has improved precipitation fields over the Atmospheric Model Intercomparison Project (AMIP) run (a simulation of the atmosphere model forced by observed daily SST) and the CGCM free simulation run. In particular, precipitation in the Philippine Sea in summer is improved over the AMIP run. This improvement is assumed to stem from the reproduction of the interaction between SST and precipitation, indicated by the lag of the precipitation change behind SST. Enhanced (suppressed) convection tends to induce an SST drop (rise) because of cloud cover and ocean mixing in the ...

Landwater variation in four major river basins of the Indochina peninsula as revealed by GRACE

We estimated mass variations in four major river basins—the Mekong, Irrawaddy, Salween and Chao Phraya river basins—of the Indochina Peninsula using the newly released GRACE (Gravity Recovery and Climate Experiment) monthly gravity field solutions of UTCSR RL02 (University of Texas at Austin, Center for Space Research Release 02), JPL RL02 (Jet Propulsion Laboratory Release 02) and GFZ RL03 (GeoForschungsZentrum Potsdam Release 03). The estimated variations were compared with that calculated from a numerical model. The results show that there is a good agreement between the GRACE estimations and the model calculation for the Mekong and Irrawaddy basins, while the aggreement for the Salween and Chao Phraya basins is poor, mainly due to the spatial scale of the areas concerned. The comparison over the combined area of the four river basins shows fairly good agreement, although there are small quantitative discrepancies. The amplitudes of the annual signals of the GRACE solutions are 0.9- to 1.4-fold larger than that of the hydrological model, and the phases are delayed about 1 month compared with the model signal. The phase differences are probably due to improper treatments of the groundwater storage process in the hydrological model, suggesting that the GRACE data possibly provide constraints to the model parameters.

GPS observations in Thailand for hydrological applications

We report the delineation of the onset of the Asian Monsoon based on GPS sensing of water vapor in Thailand. We conducted GPS observations at five sites in Thailand since March 1998 under the hydrological project called GAME-T. The objective of the project is to clarify the water and energy cycle system in the Asian Monsoon area. As a preliminary analysis, we used data from March to June 1998 and estimated the water vapor content in the zenith direction (PWV) every 30 minutes using GIPSY software (GPS-PWV). A comparison of the resultant PWV with those estimated from rawinsonde data (Sonde-PWV) suggested that, generally, the long term trends of both GPS-PWV and Sonde-PWV are consistent and a rapid increase of water vapor content is visible in May, which corresponds to the onset of the Monsoon. However, systematic differences between GPS-PWV and Sonde-PWV are eminent. The RMS of the difference (RMSD) between Sonde-PWV and GPS-PWV reaches about 8.7 mm. This large RMSD can be reduced to about 5 mm by removing some unreliable sonde data and making a linear correction to Sonde-PWV. In addition, a comparison of GPS-PWV with other meteorological data (temperature, humidity, and rainfall) showed that there is a strong correlation between a rapid increase of GPS-PWV and heavy rainfall in Bangkok and in Chiang Mai, which may be used to judge the onset of the Monsoon in the area accurately.

Volcanic influence on centennial to millennial Holocene Greenland temperature change

Solar variability has been hypothesized to be a major driver of North Atlantic millennial-scale climate variations through the Holocene along with orbitally induced insolation change. However, another important climate driver, volcanic forcing has generally been underestimated prior to the past 2,500 years partly owing to the lack of proper proxy temperature records. Here, we reconstruct seasonally unbiased and physically constrained Greenland Summit temperatures over the Holocene using argon and nitrogen isotopes within trapped air in a Greenland ice core (GISP2). We show that a series of volcanic eruptions through the Holocene played an important role in driving centennial to millennial-scale temperature changes in Greenland. The reconstructed Greenland temperature exhibits significant millennial correlations with K+ and Na+ ions in the GISP2 ice core (proxies for atmospheric circulation patterns), and δ18O of Oman and Chinese Dongge cave stalagmites (proxies for monsoon activity), indicating that the reconstructed temperature contains hemispheric signals. Climate model simulations forced with the volcanic forcing further suggest that a series of large volcanic eruptions induced hemispheric-wide centennial to millennial-scale variability through ocean/sea-ice feedbacks. Therefore, we conclude that volcanic activity played a critical role in driving centennial to millennial-scale Holocene temperature variability in Greenland and likely beyond.

Monitoring groundwater variation by satellite and implications for in-situ gravity measurements

In order to establish a new technique for monitoring groundwater variations in urban areas, the applicability of precise in-situ gravity measurements and extremely high precision satellite gravity data via GRACE (Gravity Recovery and Climate Experiment) was tested. Using the GRACE data, regional scale water mass variations in four major river basins of the Indochina Peninsula were estimated. The estimated variations were compared with Soil-Vegetation-Atmosphere Transfer Scheme (SVATS) models with a river flow model of 1) globally uniform river velocity, 2) river velocity tuned by each river basin, 3) globally uniform river velocity considering groundwater storage, and 4) river velocity tuned by each river basin considering groundwater storage. Model 3) attained the best fit to the GRACE data, and the model 4) yielded almost the same values. This implies that the groundwater plays an important role in estimating the variation of total terrestrial storage. It also indicates that tuning river velocity, which is based on the in-situ measurements, needs further investigations in combination with the GRACE data. The relationships among GRACE data, SVATS models, and in-situ measurements were also discussed briefly.

Validation of precipitation over Japan during 1985–2004 simulated by three regional climate models and two multi-model ensemble means

We dynamically downscaled Japanese reanalysis data (JRA-25) for 60 regions of Japan using three regional climate models (RCMs): the Non-Hydrostatic Regional Climate Model (NHRCM), modified RAMS version 4.3 (NRAMS), and modified Weather Research and Forecasting model (TWRF). We validated their simulations of the precipitation climatology and interannual variations of summer and winter precipitation. We also validated precipitation for two multi-model ensemble means: the arithmetic ensemble mean (AEM) and an ensemble mean weighted according to model reliability. In the 60 regions NRAMS simulated both the winter and summer climatological precipitation better than JRA-25, and NHRCM simulated the wintertime precipitation better than JRA-25. TWRF, however, overestimated precipitation in the 60 regions in both the winter and summer, and NHRCM overestimated precipitation in the summer. The three RCMs simulated interannual variations, particularly summer precipitation, better than JRA-25. AEM simulated both climatological precipitation and interannual variations during the two seasons more realistically than JRA-25 and the three RCMs overall, but the best RCM was often superior to the AEM result. In contrast, the weighted ensemble mean skills were usually superior to those of the best RCM. Thus, both RCMs and multi-model ensemble means, especially multi-model ensemble means weighted according to model reliability, are powerful tools for simulating seasonal and interannual variability of precipitation in Japan under the current climate.

Modern solar maximum forced late twentieth century Greenland cooling

The abrupt Northern Hemispheric warming at the end of the twentieth century has been attributed to an enhanced greenhouse effect. Yet Greenland and surrounding subpolar North Atlantic remained anomalously cold in 1970s to early 1990s. Here we reconstructed robust Greenland temperature records (North Greenland Ice Core Project and Greenland Ice Sheet Project 2) over the past 2100 years using argon and nitrogen isotopes in air trapped within ice cores and show that this cold anomaly was part of a recursive pattern of antiphase Greenland temperature responses to solar variability with a possible multidecadal lag. We hypothesize that high solar activity during the modern solar maximum (approximately 1950s–1980s) resulted in a cooling over Greenland and surrounding subpolar North Atlantic through the slowdown of Atlantic Meridional Overturning Circulation with atmospheric feedback processes.

Validation of a Pattern Scaling Approach for Determining the Maximum Available Renewable Freshwater Resource

AbstractA pattern scaling approach allows projection of regional climate changes under a wide range of emission scenarios. A basic assumption of this approach is that the spatial response pattern to global warming (scaling pattern) is the same for all emission scenarios. Precipitation minus evapotranspiration (PME) over land can be considered to be a measure of the maximum available renewable freshwater resource, and estimation of PME is fundamentally important for the assessment of water resources. The authors assessed the basic assumption of pattern scaling for PME by the use of five global climate models. A significant scenario dependency (SD) of the scaling pattern of PME was found over some regions. This SD of the scaling pattern of PME was mainly due to the SD and the nonlinear response of large-scale atmospheric and oceanic changes. When the SD of the scaling pattern of PME is significant in a target area, projections of the impact of climate change need to carefully take into consideration the SD....