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Using the Connecticut River basin as an example, this study assesses the extent to which remote sensing data can help improve hydrological modeling and how it may influence projected future hydrological trends. The dynamic leaf area index (LAI) derived from satellite remote sensing was incorporated into the Variable Infiltration Capacity model (VIC) to enable an interannually varying seasonal cycle of vegetation (VICVEG); the evapotranspiration (ET) data based on remote sensing were combined with ET from a default VIC simulation to develop a simple bias-correction algorithm, and the simulation was then repeated with the bias-corrected ET replacing the simulated ET in the model (VICET). VICET performs significantly better in simulating the temporal variability of river discharge at daily, biweekly, monthly, and seasonal time scales, while VICVEG better captures the interannual variability of discharge, particularly in the winter and spring, and shows slight improvements to soil moisture estimates. The methodology of incorporating ET data into VIC as a bias-correction tool also influences the modeled future hydrological trends. Compared to the default VIC, VICET portrays a future characterized by greater drought risk and a stronger decreasing trend of minimum river flows. Integrating remote sensing data with hydrological modeling helps characterize the range of model-related uncertainties and more accurately reconstruct historic river flow estimates, leading to a better understanding and prediction of hydrological response to future climate changes.

Future changes of terrestrial ecosystems due to changes in atmospheric CO 2 concentration and climate are subject to a large degree of uncertainty, especially for vegetation in the Tropics. Here, we evaluate the natural vegetation response to projected future changes using an improved version of a dynamic vegetation model (CLM-CN-DV) driven with climate change projections from 19 global climate models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5). The simulated equilibrium vegetation distribution under historical climate (1981)(1982)(1983)(1984)(1985)(1986)(1987)(1988)(1989)(1990)(1991)(1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000) has been compared with that under the projected future climate (2081-2100) scenario for Representative Concentration Pathway 8.5 (RCP8.5) to qualitatively assess how natural potential vegetation might change in the future. With one outlier excluded, the ensemble average of vegetation changes corresponding to climates of 18 GCMs shows a poleward shift of forests in northern Eurasia and North America, which is consistent with findings from previous studies. It also shows a general "upgrade" of vegetation type in the Tropics and most of the temperate zones, in the form of deciduous trees and shrubs taking over C3 grass in Europe and broadleaf deciduous trees taking over C4 grasses in Central Africa and the Amazon. LAI and NPP are projected to increase in the high latitudes, southeastern Asia, southeastern North America, and Central Africa. This results from CO 2 fertilization, enhanced water use efficiency, and in the extra-tropics warming. However, both LAI and NPP are projected to decrease in the Amazon due to drought. The competing impacts of climate change and CO 2 fertilization lead to large uncertainties in the projection of future vegetation changes in the Tropics.Climatic Change

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Previous studies documented a recent decline of the global terrestrial evapotranspiration (ET) trend, of which the underlying mechanisms are not well understood. Based on experiments using the Community Land Model version 4.5 driven with the North American Land Data Assimilation System phase‐2 (NLDAS‐2) forcing data, this study investigates the variation and changes of ET trends at the continental scale and the mechanisms underlying these changes. Simulations are conducted over the NLDAS domain including the contiguous U.S. and part of Mexico for the period of 1980–2014. Changes of ET trend are derived based on the two subperiods 1982–1997 and 1998–2008. The strongest signals of trend change, of either sign, are primarily located in dry regimes, where ET is limited by water rather than energy. Sensitivity experiments were performed to isolate the impact of some of the most influential factors on the changing ET trends. Results indicate that trends in wind speed and surface air temperature had negligible impact on the ET trend and its changes within the study domain, and the ET trend and its changes are dominated by changes in precipitation amount. Changes in precipitation characteristics including the frequency and intensity are suggested to have a secondary effect on the ET trend changes through modifying the partitioning of water between infiltration and runoff. These findings are further supported by correlation coefficients between ET and various driving factors. Results from this study may be region specific and therefore may not hold for ET trend changes over the rest of the globe.