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Extremely high levels of column-averaged dry-air mole fractions of atmospheric methane (XCH4) were detected in August and September 2013 over northeast Asia (∼ 20 ppb above the averaged summertime XCH4 over 2009–2012, after removing a long-term trend), as being retrieved from the Short-Wavelength InfraRed (SWIR) spectral data observed with the Thermal And Near-infrared Sensor for carbon Observation – Fourier Transform Spectrometer (TANSO-FTS) onboard Greenhouse Gases Observing Satellite (GOSAT). Similar enhancements of XCH4 were also observed by the ground-based measurements at two Total Carbon Column Observing Network (TCCON) sites in Japan. The analysis of surface CH4 concentrations observed at three monitoring sites around the Japan archipelago suggest that the extreme increase of XCH4 has occurred in a limited area. The model analysis was conducted to investigate this anomalously high XCH4 event, using an atmospheric transport model. The results indicate that the extreme increase of XCH4 is attributed to the anomalous atmospheric pressure pattern over East Asia during the summer of 2013, which effectively transported the CH4-rich air to Japan from the strong CH4 source areas in east China. The two Japanese TCCON sites, ∼ 1000 km east–west apart each other, coincidentally located along the substantially CH4-rich air flow from east China. This analysis demonstrates the capability of GOSAT to monitor an XCH4 event on a synoptic scale. We anticipate that the synoptic information of XCH4 from GOSAT data contributes to improve our understanding of regional carbon cycle and the regional flux estimation.

Temporal progress of forest reduction by deforestation in the Asian tropical region was simulated using a global climate model that included a new land-surface ecosystem model. The horizontal resolution of the model was 1.875°. Two experimental areas were defined: the Indochina peninsula (ICP) area, and the Maritime Continent (MTC) area. With a control simulation under the actual vegetation condition, a grassland experiment (C4 experiment) and a bare-soil experiment (BS experiment) were carried out. Forest vegetation in the experimental areas was gradually changed (at the latest actual rate) to non-forest type vegetation. The natural growth of C4 grass was reproduced in the C4 experiment, and the plant growth was deterred in the BS experiment. Each experiment was run for 100 model years. Temporal changes of the energy and the carbon cycle balances under the vegetation transition were examined. Compared with the control, the net radiation (RNE) decreased because of the increase in the land surface albedo. The sensible heat flux decreased because of the decreases in RNE and other particular reasons. The results for latent heat flux (E) in this study differed from those in our previous study. In the C4 experiment, E increased, especially in the ICP area; in the BS experiment, E decreased in both experimental areas. In the MTC area, the surface temperature in the C4 experiment increased because of the large influence of decreased precipitation. Decreases of the soil wetness in the C4 experiment were more significant in the MTC area, due to increased transpiration and the decreased precipitation. The change from forest vegetation to C4 grass vegetation induced the reduction of carbon absorption by the land surface. Continuous deforestation in the Asian tropical region certainly induces the elevations of the global atmospheric carbon dioxide concentrations, even if the deforested area is not replaced by bare soil surface condition.

A number of uncertainties exist in climate simulation because the results of climate models are influenced by factors such as their dynamic framework, physical processes, initial and driving fields, and horizontal and vertical resolution. The uncertainties of the model results may be reduced, and the credibility can be improved by employing multi-model ensembles. In this paper, multi-model ensemble results using 10-year simulations of five regional climate models (RCMs) from December 1988 to November 1998 over Asia are presented and compared. The simulation results are derived from phase II of the Regional Climate Model Inter-comparison Project (RMIP) for Asia. Using the methods of the arithmetic mean, the weighted mean, multivariate linear regression, and singular value decomposition, the ensembles for temperature, precipitation, and sea level pressure are carried out. The results show that the multi-RCM ensembles outperform the single RCMs in many aspects. Among the four ensemble methods used, the multivariate linear regression, based on the minimization of the root mean square errors, significantly improved the ensemble results. With regard to the spatial distribution of the mean climate, the ensemble result for temperature was better than that for precipitation. With an increasing number of models used in the ensembles, the ensemble results were more accurate. Therefore, a multi-model ensemble is an efficient approach to improve the results of regional climate simulations.

Using a regional climate model that includes a terrestrial biosphere model, numerical simulations were performed to clarify the mechanism of the carbon cycle between the terrestrial ecosystem and the atmosphere and to investigate the climate factors impact on the carbon cycle in the East Asian terrestrial ecosystem.Model verifications were performed with regard to the principal elements: precipitation and vegetation phenology. The variations of the atmospheric carbon dioxide concentration simulated by the model were validated using the data at six in situ observatories.After the confirmations of the model performance, regional features of the impact of climate factors on the gross primary production (GPP) were analyzed. The downward short-wave radiation (DSW), the soil wetness (SW), and the surface temperature (TA) were chosen as the effective climate factors. In the NE-Asia region, a positive anomaly of DSW in warm season induces a positive anomaly of GPP. High anomalous TA in the cold season also induces a large value of GPP. In the China region, similarly to that in NE-Asia, DSW is important for GPP. The effect of SW is also important in the spring. While the correlation between the variation of TA and that of GPP is positive and high in winter, the positive anomaly of TA in the warm season induces negative anomaly of GPP. In the Indochina region, DSW is important throughout the year. In contrast, the correlations between the variations of SW and those of GPP are negative in all seasons, indicating that GPP becomes a negative anomaly when the precipitation is a positive anomaly. In the India region, DSW in the warm season and SW in the cold season are important for increasing GPP. In the Mongolia and Inland regions, SW is a more important climate factor than DSW for GPP. High temperature in the cold season is also important. In summer, unusually high temperature and dry climate conditions reduce GPP. In the Philippines region, main factor affecting GPP is DSW.

Several numerical simulations were performed, using a global climate model that includes a realistic land surface model, to investigate the impact of Asian tropical vegetation changes on the climate. The control simulation, under conditions of the actual vegetation, and three vegetation-change impact experiments were performed. The results of the impact experiments were compared with those of the control simulation. The horizontal resolution of the model used in these simulations was 1.875°, being finer than that of the models used in previous vegetation-change impact studies. As a result, it was determined that the effects of vegetation changes in the Asian tropical region had spatially different features. The morphological, physiological, and physical changes of the land surface vegetation in the Asian tropical region certainly induce statistically significant climate changes in these and the surrounding areas. That is, from the results of the bare soil and C4 grass experiments, the decrease in the roughness length, and from the results of the green-less experiment, the decrease of the latent heat flux, exert strong influences on the horizontal and convective circulations of the atmosphere. Consequently, the distribution of precipitation will undergo a change. Other energy and water balances at the land surface are also influenced by the vegetation changes, and the induced changes are generally statistically significant. The influences of vegetation changes in the Asian tropical region were more complicated than those in the Amazon. One reason for this was that the Asian tropical region is strongly influenced by the Asian monsoon circulation; another reason is that the land–sea distribution and the distribution of vegetation in the Asian tropical region are not as simple as in a tropical rain forest like the Amazon.

Verification of local climatic features produced by a regional climate model (JSM-BAIM) that includesa Biosphere-Atmosphere Interaction Model (BAIM) in the Japan Spectral Model (JSM) was performed.The data used in the verification were the results of a six-year integration calculated by the JSM-BAIM.In the time integration of the JSM-BAIM, the spectral boundary coupling (SBC) method was used. Thereproducibility of horizontally distributed features, and local and seasonal changes in the principal climaticelements of the model, were investigated in finer detail than that of our previous study.Comparisons of the model results with JMA objective analysis data were performed with respect togeopotential heights, temperatures, and winds at the 850-hPa and 500-hPa levels. Statistically signifi-cant differences appeared, mainly in the summer temperature field, and in the summer and the winterwind fields. It was considered that the statistically significant differences in the summer temperaturefield were due to the effects of land surface processes, and the summer convection process over thesouthern ocean area. The statistically significant differences in the wind field were mainly due to theinfluence of differences in topography between the regional model field and the analysis field, especiallywhen interacting with the strong wind flow during the winter season.Comparisons of the model results with the data of dense surface meteorological observation network(AMeDAS) were performed with respect to precipitation, surface air temperature, and radiation at theland surface over four typical climate areas in the Japanese Islands. The model reproduced reasonablywell the features of the seasonal and interannual variations of each variable, in each area. There were,however, some seasonal and regional features in the differences between the model results and theAMeDAS data.The JSM-BAIM, with the use of the spectral boundary coupling (SBC) method in a long period timeintegration, had sufficient accuracy for use in investigations of the interaction mechanisms between theterrestrial ecosystems and climate; temporally at least on the level of the seasonal and interannual variations,and spatially at least on the level of the climatic classification of the Japanese Islands. There is, however,the necessity for further verification using observed data, especially with respect to the near landsurface air temperature in a natural vegetation environment, and the atmospheric variables over the ocean.

1998年の航空機搭載型分光走査放射計 (AMSS) のデータで, (1) 積雪面の可視から近赤外へかけての急激な放射照度の減少, と (2) 植生面 (森林など) の近赤外短波での放射照度の立ち上がり, の両方を考慮できる積雪・植生指標が実際にどのようになるかを評価した.植生+積雪の混在条件下で従来の2波長帯 (NDVIなどと同じ) による指標と比べ, 3波長を使い前述 (1) + (2) の効果を反映した指標のほうが植生密度 (PAI : 樹体面積指数) により敏感であり, 林床の積雪に影響されず植生被覆の状態をとらえることが出来た.また, 0.9μmより短波長側における反射率のスペクトルは, 植生による0.7μm付近の立ち上がりを良く捕らえていることも確かめられた.さらに, 植生+積雪の条件下でPAIを忠実に推定できるS3を使って積雪のみと森林域を分類し, いくつかの波長帯における反射率が観測角度によりどの程度変化するかを見積もったところ, 積雪面は前方散乱が強く森林域では等方的, とセンサ操作角は±35度と小さいにもかかわらずBRDF的特性がかなり現れていることがわかった.ただし, 波長ごとのBRDF特性は相似であり, 指標への影響は小さい.

Northern Eurasia is one of the largest terrestrial carbon reservoirs on the Earth's surface. However, since the coverage of surface CO2 observations is still limited, the response to the climate variability remains uncertain. We estimated monthly CO2 fluxes for three sub-regions in Northern Eurasia (north of ~60?N), Northeastern Europe, Western Siberia and Eastern Siberia, using CO2 retrievals from the Japanese Greenhouse Gases Observing SATellite (GOSAT). The variations of estimated CO2 fluxes were examined in terms of the regional climate variability, for the three consecutive growing seasons of 2009?2011. The CO2 fluxes estimated using GOSAT data are highly correlated with the surface temperature anomalies in July and August (r?>?0.8) while no correlation is found in the CO2 fluxes estimated only using surface observations. The estimated fluxes from GOSAT data exhibit high negative correlations with one-month lagged positive precipitation anomalies in late summer (r?>??0.7) through surface temperature and the Normalized Difference Vegetation Index (NDVI). The results indicate that GOSAT data reflects the changes in terrestrial biospheric processes responding to climate anomalies. In 2010, a large part of Eurasia experienced an extremely hot and dry summer, while cold and wet weather conditions were recorded in Western Siberia. The CO2 fluxes estimated from GOSAT data showed a reduction of net CO2 uptake in Northeastern Europe and Eastern Siberia, but the enhancement of net CO2 uptake in Western Siberia. These opposite sub-regional flux anomalies can be explained by the different climate anomalies on a sub-regional scale in Northern Eurasia. Thus, this study demonstrates that space-based observations by GOSAT compensate for the lack of ground-based observational coverage so as to better capture the inter-annually varying atmosphere-terrestrial biosphere CO2 exchange on a regional scale.

In the Northern hemisphere, the CO 2 concentration in the warm season indicated anomalously high values in 2003, and low values in 2004. To investigate the reasons of the interannual variation, a numerical simulation using a land biosphere – atmosphere full couple GCM was carried out. Relationship between interannual variations of CO 2 and those of the land surface elements was investigated. In 2003, high surface temperature and low soil wetness conditions in the Eurasian Continent and in North America, and low downward short wave radiation condition in East Asia, occurred in the warm season. It is considered that these climate conditions in 2003 induced relatively low GPP and NEP values in the continental scale. Comparison of the simulation results of GCM with satellite data (MODIS and AMSR-E) was performed concerning the remarkable interannual changes from 2003 to 2004. Global distributions of the seasonal changes by the model almost agree with those by the satellite data regarding both the land surface temperature and the soil moisture. The interannual changes of land surface temp erature by the model agree well with those by the MODIS data. As to the soil moisture, the regions exist where the interannual changes by the model disagree with those by the AMSR-E data especially in the warm season. The values of elements calculated by the model are physically and bioecologically consistent each other in the model. Therefore, the model results are useful as the relative information for the validation of the global scale or re gional scale products of satellite data estimated separately by each algorithm. Keywords: climate model, land surface element, satellite product