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Northern Eurasia experienced anomalous weather conditions in the 2003 summer. We examined how forest ecosystems responded to the meteorological anomalies during the period using the dataset collected at flux monitoring sites in Asia, including a boreal forest in Mongolia, temperate forests in China and Japan, and a sub-tropical forest in China, as well as the dataset from satellite remote sensing. From July to August 2003, an active rain band stayed in the mid-latitude in East Asia for an unusually long period. Under the influence of the rain band, the gross primary production (GPP) of temperate forests was 20-30% lower in the 2003 summer than in other years due to significant reduction in the photosynthetic photon flux density (PPFD). The GPP of a cool-temperate forest in the north of the rain band was slightly enhanced by the higher PPFD; however, the GPP of a sub-tropical forest located in the south of the rain band was reduced by drought stress due to extremely hot and dry conditions. The correlation coefficients for the year-to-year changes in the PPFD and GPP during mid-summer were calculated, and the spatial distribution was examined. The spatial pattern of the PPFD was calculated by satellite data, and that of the GPP was estimated by a regression-type model, which was trained and tested by ground observation data. The correlation was positive in the mid- and high-latitudes since light was an essential factor of the summer GPP. On the other hand, a negative correlation appeared in the lower latitudes, suggesting that the water limitation was much more important than the PPFD in the region. Our study illustrated that the integration of flux data from wide areas by combining satellite remote sensing data can help us gain an understanding of the ecosystem responses to large-scale meteorological phenomena. [ABSTRACT FROM AUTHOR]

Larch forests are widely distributed across many cool-temperate and boreal regions, and they are expected to play an important role in global carbon and water cycles. Model parameterizations for larch forests still contain large uncertainties owing to a lack of validation. In this study, a process-based terrestrial biosphere model, BIOMEBGC, was tested for larch forests at six AsiaFlux sites and used to identify important environmental factors that affect the carbon and water cycles at both temporal and spatial scales. The model simulation performed with the default deciduous conifer parameters produced results that had large differences from the observed net ecosystem exchange (NEE), gross primary productivity (GPP), ecosystem respiration (RE), and evapotranspiration (ET). Therefore, we adjusted several model parameters in order to reproduce the observed rates of carbon and water cycle processes. This model calibration, performed using the AsiaFlux data, significantly improved the model performance. The simulated annual GPP, RE, NEE, and ET from the calibrated model were highly consistent with observed values. The observed and simulated GPP and RE across the six sites are positively correlated with the annual mean air temperature and annual total precipitation. On the other hand, the simulated carbon budget is partly explained by the stand disturbance history in addition to the climate. The sensitivity study indicates that spring warming enhances the carbon sink, whereas summer warming decreases it across the larch forests. The summer radiation is the most important factor that controls the carbon fluxes in the temperate site, but the VPD and water conditions are the limiting factors in the boreal sites. One model parameter, the allocation ratio of carbon between aboveground and belowground, is site-specific, and it is negatively correlated with the annual climate of annual mean air temperature and total precipitation. Although this study significantly improves the model performance, the uncertainties that remain in terms of the sensitivity to water conditions should be examined in ongoing and long-term observations. [ABSTRACT FROM AUTHOR]

Aircraft-based remote sensing was carried out over the Lena River region (approximately 100 km horizontal scale) near Yakutsk, in eastern Siberia, on nine days between 24 April and 19 June 2000. A home-use video camera was installed on the aircraft and aerial images of the land surface were recorded. By flying at very low altitudes (100 m and 150 m), we compensated for the low resolution of the camera. In all, 5515 scenes were sampled at 10-s intervals from the video, visually interpreted, and classified. The snow/ice and water cover conditions were also interpreted. The results showed that grassland covers the riverine lowland (RLL) of the Lena River, while the principal form of land cover over the terraces is larch forest (about 61%). There was a remarkable contrast between the left (LBT) and right (RBT) bank terraces of the Lena River, no-forest areas covered 28.8% of the RBT, whereas no-forest areas covered only 13.8% of the LBT. In addition, the LBT had a greater proportion of birch forest than the RBT (15.2% vs 2.5%). The video data over eight days showed that the snow thawed first in the RLL and last in the forested areas of the LBT and RBT. An increase in the area covered by water in the RLL in mid-May was probably due to flooding by the Lena River. Distinguishing insolated from cloud-shadowed scenes of the land surface revealed that the insolation rate was lower over the LBT and RBT than over the RLL. The land-cover database created in this analysis will play an important role as basic, reliable ground-truth information for studies using satellite images. [ABSTRACT FROM AUTHOR]

Global-scale surface soil moisture products are currently available from multiple remote sensing platforms. Footprint-scale assessments of these products are generally restricted to limited number of densely-instrumented validation sites. However, by taking active and passive soil moisture products together with a third independent soil moisture estimates via land surface modeling, triple collocation (TC) can be applied to estimate the correlation metric of satellite soil moisture products (versus an unknown ground truth) over a quasi-global domain. Here, an assessment of Soil Moisture Active Passive (SMAP), Soil Moisture Ocean Salinity (SMOS) and Advanced SCATterometer (ASCAT) surface soil moisture retrievals via TC is presented. Considering the potential violation of TC error assumptions, the impact of active-passive and satellite-model error cross correlations on the TC-derived inter-comparison results is examined at in situ sites using quadruple collocation analysis. In addition, confidence intervals for the TC-estimated correlation metric are constructed from moving-block bootstrap sampling designed to preserve the temporal persistence of the original (unevenly-sampled) soil moisture time-series. This study is the first to apply TC to obtain a robust global-scale cross-assessment of SMAP, SMOS and ASCAT soil moisture retrieval accuracy in terms of anomaly temporal correlation. Our results confirm the overall advantage of SMAP (with a global average anomaly correlation of 0.76) over SMOS (0.66) and ASCAT (0.63) that has been established in several recent regional, ground-based studies. SMAP is also the best-performing product over the majority of applicable land pixels (52%), although SMOS and ASCAT each shows advantage in distinct geographic regions.

The regression tree method is used to upscale evapotranspiration (ET) measurements at eddy-covariance (EC) towers to the grassland ecosystems over the Dryland East Asia (DEA). The regression tree model was driven by satellite and meteorology datasets, and explained 82% and 76% of the variations of ET observations in the calibration and validation datasets, respectively. The annual ET estimates ranged from 222.6 to 269.1 mm yr(-1) over the DEA region with an average of 245.8 mm yr(-1) from 1982 through 2009. Ecosystem ET showed decreased trends over 61% of the DEA region during this period, especially in most regions of Mongolia and eastern Inner Mongolia due to decreased precipitation. The increased ET occurred primarily in the western and southern DEA region. Over the entire study area, water balance (the difference between precipitation and ecosystem ET) decreased substantially during the summer and growing season. Precipitation reduction was an important cause for the severe water deficits. The drying trend occurring in the grassland ecosystems of the DEA region can exert profound impacts on a variety of terrestrial ecosystem processes and functions.

Intensive observations, analysis and modeling within the framework of the rangelands atmosphere-hydrosphere-biosphere interaction study experiment in northeastern Asia (RAISE) project, have allowed investigations into the hydrologic cycle in the ecotone of forest-steppe, and its relation to atmosphere and ecosystem in the eastern part of Mongolia. In this region, changes in the climate have been reported and a market oriented economy was introduced recently, but their impact on the natural environment is still not well understood. In this RAISE special issue, the outcome is presented of the studies carried out by six groups within RAISE, namely: (1) Land-atmosphere interaction analysis, (2) ecosystem analysis and modeling, (3) hydrologic cycle analysis, (4) climatic modeling, (5) hydrologic modeling, and (6) integration. The results are organized in five relevant categories comprising (i) hydrologic cycle including precipitation, groundwater, and surface water, (ii) hydrologic cycle and ecosystem, (iii) surface-atmosphere interaction, (iv) effect of grazing activities on soils, plant ecosystem and surface fluxes, and (v) future prediction. Comparison with studies on rangelands in other parts of the world, and some future directions of studies still needed in this region are also summarized., (Copyright © 2006 Elsevier B.V. All rights reserved.)