The future adequacy of freshwater resources is difficult to assess, owing to a complex and rapidly changing geography of water supply and use. Numerical experiments combining climate model outputs, water budgets, and socioeconomic information along digitized river networks demonstrate that (i) a large proportion of the world's population is currently experiencing water stress and (ii) rising water demands greatly outweigh greenhouse warming in defining the state of global water systems to 2025. Consideration of direct human impacts on global water supply remains a poorly articulated but potentially important facet of the larger global change question.
A number of polar datasets have recently been released involving in situ measurements, satellite retrievals, and reanalysis output that provide new opportunities to evaluate regional climate in the Arctic. These data have been used to assess a 1-yr pan-Arctic simulation (October 1985–September 1986) performed by a version of the fifth-generation Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) Mesoscale Model (MM5) that incorporated the NCAR land surface model (LSM) and a simple thermodynamic sea ice model to investigate interactions between the land surface and atmosphere. The model's standard cloud scheme using relative humidity was replaced by one using simulated cloud liquid water and ice water after a set of short test simulations revealed excessive cloud cover. Model validation concentrates on factors relevant to the water cycle: atmospheric circulation, temperature, surface radiation fluxes, precipitation, and runoff. The model captures general patterns of atmospheric circulation over land. The rms differences from the Historical Arctic Rawinsonde Archive (HARA) rawinsonde winds at 850 hPa are smaller for the simulation (9.8 m s−1) than for the NCEP–NCAR reanalysis (10.5 m s−1) that supplies the model's boundary conditions. For continental watersheds, the model simulates well annual average surface air temperature (bias <2°C) and precipitation (bias <0.5 mm day−1). However, the model has a summer dry bias with monthly precipitation error occasionally exceeding 1 mm day−1. The model simulates the approximate magnitude of spring runoff surge, but annual runoff is less than observed (18%–48% less among the continental watersheds). Analysis of precipitation and surface air temperature errors indicates that further improvements in both evapotranspiration and precipitation are needed to simulate well the full annual water cycle.
Abstract The role of undisturbed tropical land ecosystems in the global carbon budget is not well understood. It has been suggested that interannual climate variability can affect the capacity of these ecosystems to store carbon in the short term. In this paper, we use a transient version of the Terrestrial Ecosystem Model (TEM) to estimate annual carbon storage in undisturbed Amazonian ecosystems during the period 1980–94, and to understand the underlying causes of the year‐to‐year variations in net carbon storage for this region.
