All currently available climate models predict a near-surface warming trend under the influence of rising levels of greenhouse gases in the atmosphere. In addition to the direct effects on climate--for example, on the frequency of heatwaves--this increase in surface temperatures has important consequences for the hydrological cycle, particularly in regions where water supply is currently dominated by melting snow or ice. In a warmer world, less winter precipitation falls as snow and the melting of winter snow occurs earlier in spring. Even without any changes in precipitation intensity, both of these effects lead to a shift in peak river runoff to winter and early spring, away from summer and autumn when demand is highest. Where storage capacities are not sufficient, much of the winter runoff will immediately be lost to the oceans. With more than one-sixth of the Earth's population relying on glaciers and seasonal snow packs for their water supply, the consequences of these hydrological changes for future water availability--predicted with high confidence and already diagnosed in some regions--are likely to be severe.

A frequently encountered difficulty in assessing model-predicted land-atmosphere exchanges of moisture and energy is the absence of comprehensive observations to which model predictions can be compared at the spatial and temporal resolutions at which the models operate. Various methods have been used to evaluate the land surface schemes in coupled models, including comparisons of model-predicted evapotranspiration with values derived from atmospheric water balances, comparison of model-predicted energy and radiative fluxes with tower measurements during periods of intensive observations, comparison of model-predicted runoff with observed streamflow, and comparison of model predictions of soil moisture with spatial averages of point observations. While these approaches have provided useful model diagnostic information, the observation-based products used in the comparisons typically are inconsistent with the model variables with which they are compared-for example, observations are for points or areas much smaller than the model spatial resolution, comparisons are restricted to temporal averages, or the spatial scale is large compared to that resolved by the model. Furthermore, none of the datasets available at present allow an evaluation of the interaction of the water balance components over large regions for long periods. In this study, a model-derived dataset of land surface states and fluxes is presented for the conterminous United States and portions of Canada and Mexico. The dataset spans the period 1950-2000, and is at a 3-h time step with a spatial resolution of ⅛ degree. The data are distinct from reanalysis products in that precipitation is a gridded product derived directly from observations, and both the land surface water and energy budgets balance at every time step. The surface forcings include precipitation and air temperature (both gridded from observations), and derived downward solar and longwave radiation, vapor pressure deficit, and wind. Simulated runoff is shown to match observations quite well over large river basins. On this basis, and given the physically based model parameterizations, it is argued that other terms in the surface water balance (e.g., soil moisture and evapotranspiration) are well represented, at least for the purposes of diagnostic studies such as those in which atmospheric model reanalysis products have been widely used. These characteristics make this dataset useful for a variety of studies, especially where ground observations are lacking.

The Water and Global Change (WATCH) project evaluation of the terrestrial water cycle involves using land surface models and general hydrological models to assess hydrologically important variables including evaporation, soil moisture, and runoff. Such models require meteorological forcing data, and this paper describes the creation of the WATCH Forcing Data for 1958–2001 based on the 40-yr ECMWF Re-Analysis (ERA-40) and for 1901–57 based on reordered reanalysis data. It also discusses and analyses model-independent estimates of reference crop evaporation. Global average annual cumulative reference crop evaporation was selected as a widely adopted measure of potential evapotranspiration. It exhibits no significant trend from 1979 to 2001 although there are significant long-term increases in global average vapor pressure deficit and concurrent significant decreases in global average net radiation and wind speed. The near-constant global average of annual reference crop evaporation in the late twentieth century masks significant decreases in some regions (e.g., the Murray–Darling basin) with significant increases in others.

[1] Systematic biases in gauge-based measurement of precipitation can be substantial. Of the sources of bias, wind-induced undercatch of solid precipitation is by far the largest. A methodology for producing gridded mean monthly catch ratios (CRs) for the adjustment of wind-induced undercatch and wetting losses is developed, which is suitable for application to continental or global gridded precipitation products. The adjustments for wind-induced solid precipitation were estimated using gauge type-specific regression equations from the recent World Meteorological Organization Solid Precipitation Measurement Intercomparison. Wind-induced undercatch of liquid precipitation and wetting losses were estimated using methods employed in previous global bias adjustment efforts. Due to the unique nature of Canada's precipitation measurement network, the Canadian adjustments were determined using more detailed information than for the rest of the domain, and are therefore expected to be more reliable. The gridded gauge adjustment products are designed to be applicable both to climatological estimates and to individual years during the 1979 through 1998 reference period. Application of the CRs to an existing precipitation product yielded an increase in mean annual global terrestrial precipitation of 11.7%. As compared with recent (but more localized) studies that used a similar method to account for wind-induced catch deficiencies, our estimates of wind-induced undercatch are 1.6-7.9% higher on a mean annual basis. Compared to a previous global precipitation bias adjustment effort, our adjusted data set results on average in slightly greater warm season and lower cold season precipitation increases, greater precipitation increases over North America, and lower precipitation increases over Eurasia.

Many of the scientific and societal challenges in understanding and preparing for global environmental change rest upon our ability to understand and predict the water cycle change at large river basin, continent, and global scales. However, current large-scale land models (as a component of Earth System Models, or ESMs) do not yet reflect the best hydrologic process understanding or utilize the large amount of hydrologic observations for model testing. This paper discusses the opportunities and key challenges to improve hydrologic process representations and benchmarking in ESM land models, suggesting that (1) land model development can benefit from recent advances in hydrology, both through incorporating key processes (e.g., groundwater-surface water interactions) and new approaches to describe multiscale spatial variability and hydrologic connectivity; (2) accelerating model advances requires comprehensive hydrologic benchmarking in order to systematically evaluate competing alternatives, understand model weaknesses, and prioritize model development needs, and (3) stronger collaboration is needed between the hydrology and ESM modeling communities, both through greater engagement of hydrologists in ESM land model development, and through rigorous evaluation of ESM hydrology performance in research watersheds or Critical Zone Observatories. Such coordinated efforts in advancing hydrology in ESMs have the potential to substantially impact energy, carbon, and nutrient cycle prediction capabilities through the fundamental role hydrologic processes play in regulating these cycles.

Abstract:For most of the global land area poleward of about 40°latitude, snow plays an important role in the water cycle. The (seasonal) timing of runoff in these areas is especially sensitive to projected losses of snowpack associated with warming trends, whereas projected (annual) runoff volume changes are primarily associated with precipitation changes, and to a lesser extent, with changes in evapotranspiration (ET). Regional studies in the USA (and especially the western USA) suggest that hydrologic adjustments to a warming climate have been ongoing since the mid-twentieth century. We extend the insights extracted from the western USA to the global scale using a physically based hydrologic model to assess the effects of systematic changes in precipitation and temperature on snow-affected portions of the global land area as projected by a suite of global climate models. While annual (and in some cases seasonal) changes in precipitation are a key driver of projected changes in annual runoff, we find, as in the western USA, that projected warming produces strong decreases in winter snow accumulation and spring snowmelt over much of the affected area regardless of precipitation change. Decreased snowpack produces decreases in warmseason runoff in many mid-to high-latitude areas where precipitation changes are either moderately positive or negative in the future projections. Exceptions, however, occur in some high-latitude areas, particular in Eurasia, where changes in projected precipitation are large enough to result in increased, rather than decreased, snow accumulation. Overall, projected changes in snowpack and the timing of snowmelt-derived runoff are largest near the boundaries of the areas that currently experience substantial snowfall, and at least qualitatively, they mirror the character of observed changes in the western USA.

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In the western United States, the seasonal phase of snow storage bridges between winter‐dominant precipitation and summer‐dominant water demand. The critical role of snow in water supply has been frequently quantified using the ratio of snowmelt‐derived runoff to total runoff. However, current estimates of the fraction of annual runoff generated by snowmelt are not based on systematic analyses. Here based on hydrological model simulations and a new snowmelt tracking algorithm, we show that 53% of the total runoff in the western United States originates as snowmelt, despite only 37% of the precipitation falling as snow. In mountainous areas, snowmelt is responsible for 70% of the total runoff. By 2100, the contribution of snowmelt to runoff will decrease by one third for the western U.S. in the Intergovernmental Panel on Climate Change Representative Concentration Pathway 8.5 scenario. Snowmelt‐derived runoff currently makes up two thirds of the inflow to the region's major reservoirs. We argue that substantial impacts on water supply are likely in a warmer climate.