We examined natural and anthropogenic controls on terrestrial evapotranspiration (ET) changes from 1982 to 2010 using multiple estimates from remote sensing-based datasets and process-oriented land surface models. A significant increasing trend of ET in each hemisphere was consistently revealed by observationally-constrained data and multi-model ensembles that considered historic natural and anthropogenic drivers. The climate impacts were simulated to determine the spatiotemporal variations in ET. Globally, rising CO2 ranked second in these models after the predominant climatic influences, and yielded decreasing trends in canopy transpiration and ET, especially for tropical forests and high-latitude shrub land. Increasing nitrogen deposition slightly amplified global ET via enhanced plant growth. Land-use-induced ET responses, albeit with substantial uncertainties across the factorial analysis, were minor globally, but pronounced locally, particularly over regions with intensive land-cover changes. Our study highlights the importance of employing multi-stream ET and ET-component estimates to quantify the strengthening anthropogenic fingerprint in the global hydrologic cycle.

Validation of North American Regional Climate Change Assessment Program (NARCCAP) climate simulations is conducted for selected US Forest Service sites in the southeastern United States. Results focus on qualitative and quantitative comparisons of seasonal and monthly temperature data from NARCCAP simulations to the surface air temperature data sets developed at the University of Delaware. The Regional Climate Model, RCM3, driven by the Geophysical Fluid Dynamics Laboratory Global Climate Model underestimates average surface temperature for some areas of the southeast United States by about 4 °C for the daily average during the winter of the selected period. Copyright © 2012 Royal Meteorological Society

A validation study of North American Regional Climate Change Assessment Program (NARCCARP) climate simulations is conducted for selected Unites States Forest Service (USFS) sites in the southeastern USA. Preliminary results focus on qualitative comparisons of seasonal and monthly data from NARCCAP simulations and the NCEP North American Regional Reanalysis (NARR). Additional analyses extend current validation efforts to more quantitative methods incorporating seasonal and monthly time-series plots of variables (e.g., low-level humidity, temperature, precipitation) applicable to forest resource diagnostics and prediction. The validation studies are precursors to current research to assess the vulnerability of southeastern forest cover and fire loads to climate change. Anticipated outcomes from this research will be useful for decision support and policy development by national, state, and local stakeholders.

Precipitation is an important component of the global water cycle and a proxy for changing climate. Proper understanding and quantification of spatio-temporal precipitation variability is critical for a range of meteorological, hydrological, and climate processes. Past and current literature has presented theories and observational studies on how urbanization affects precipitation. Assessment of the urban environment's (land use, aerosols, thermal properties) impact on precipitation will be increasingly important in ongoing climate diagnostics and prediction, global water and energy cycle (GWEC) analysis and modeling, weather forecasting, freshwater resource management, urban planning-design, and land-atmosphere-ocean interface processes. This chapter presents a review of findings and methods related to "urban rainfall effect" studies with an emphasis on numerical modeling strategies. Numerical modeling of atmosphere-land interactions enables controlled experimentation to address fundamental research questions.

There is increasing observational evidence that urban land cover can have a significant effect on precipitation variability. Atlanta, because of its rapid urbanization, has been a focus for several observational studies on urbanization and rainfall. Yet. there is a lack of numerical model studies in the literature to examine physical processes linked to the Atlanta "urban rainfall effect" or URE. This study employs the Weather Research and Forecast (WRF) model to simulate convective precipitation for two cases: 17 August 2002 ("an urban interaction case") and 26th July 1996 (an urban "initiation" case). Case I was chosen based on analysis of radar composites and surface maps which identified it as an event likely to have some urban forcing with minimal large scale forcing; while Case 2 was based on a previous observational study indicating that the storm was initiated by urban heat island induced convergence zone.The control (URBAN) simulations begin 3 h prior to the observed storm initiations and reveal that the model captures the convective evolution of the cases. The alternative (NOURBAN) simulations indicate that removing the city of Atlanta causes distinct differences in the temporal and spatial evolution of the explicitly resolved precipitation. However these differences point more to the likelihood of modification rather than initiation of the convective systems.Time series of cumulative rainfall totals indicate that the explicitly resolved rainfall is initiated at the same time in both the URBAN and NOURBAN simulations. The rainfall initiation time even within sub-sections of the domain is the same for the URBAN and NOURBAN scenario. Rainfall amounts downwind of the city are higher by 10% to 13% within a strip 20-50 km east of the city, for the URBAN schemes in comparison to NOURBAN. (C) 2008 Elsevier B.V. All rights reserved.