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- Author or Editor: Ingjerd Haddeland x
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Abstract
Hydrological model predictions are sensitive to model forcings, input parameters, and the parameterizations of physical processes. Analyses performed for the Variable Infiltration Capacity model show that the resulting moisture fluxes are sensitive to the time step and energy balance closure assumptions. In addition, the model results are sensitive to the method of spatial and temporal disaggregation of precipitation. For parameter estimation purposes, it is desirable to do parameter searches in water balance mode (meaning that the effective surface temperature is assumed equal to the surface air temperature; hence no iteration for energy balance closure is performed) at daily time steps. However, transferring these parameters directly to other model modes (e.g., energy balance, in which an iteration for effective surface temperature is performed, and/or different model time steps) results in changes in the simulated moisture fluxes. The simulated differences in moisture fluxes are mainly a result of the parameterization of evapotranspiration at different time steps and model modes. A simple scheme that calculates correction factors for some model parameters is developed. The scheme is used to match simulated moisture fluxes in hourly and 3-hourly energy balance mode to the daily water balance simulation results, and to match hourly energy balance runs using spatially and temporally disaggregated precipitation to 3-hourly energy balance runs using uniformly disaggregated precipitation. For both approaches, the corrected simulations match the baseline simulations quite closely, both over transects across much of the continental United States and for test applications in the Ohio and Arkansas–Red River basins.
Abstract
Hydrological model predictions are sensitive to model forcings, input parameters, and the parameterizations of physical processes. Analyses performed for the Variable Infiltration Capacity model show that the resulting moisture fluxes are sensitive to the time step and energy balance closure assumptions. In addition, the model results are sensitive to the method of spatial and temporal disaggregation of precipitation. For parameter estimation purposes, it is desirable to do parameter searches in water balance mode (meaning that the effective surface temperature is assumed equal to the surface air temperature; hence no iteration for energy balance closure is performed) at daily time steps. However, transferring these parameters directly to other model modes (e.g., energy balance, in which an iteration for effective surface temperature is performed, and/or different model time steps) results in changes in the simulated moisture fluxes. The simulated differences in moisture fluxes are mainly a result of the parameterization of evapotranspiration at different time steps and model modes. A simple scheme that calculates correction factors for some model parameters is developed. The scheme is used to match simulated moisture fluxes in hourly and 3-hourly energy balance mode to the daily water balance simulation results, and to match hourly energy balance runs using spatially and temporally disaggregated precipitation to 3-hourly energy balance runs using uniformly disaggregated precipitation. For both approaches, the corrected simulations match the baseline simulations quite closely, both over transects across much of the continental United States and for test applications in the Ohio and Arkansas–Red River basins.
Abstract
A seasonal snow cover, expansive forests, a long coast line, and a mountainous terrain are features of Norway’s geography. Forests, ground snow, and sea surface temperature (SST) vary on time scales relevant for weather forecasting and climate projections. The mapping and model parameterization of these features vary in novelty, accuracy, and complexity. This paper investigates how increasing the influence of each of these features affects southern Norway’s surface energy and water balance in a regional climate model (WRF). High-resolution (3.7 km) experimental runs have been conducted over two consecutive hydrological years, including 1) heightening the boreal forest line (the Veg experiment), 2) increasing ground snow by altering the snow/rain criterion (the Snow experiment), or 3) increasing the SST (the SST experiment). The Veg experiment led to an increase in annual net radiation 
Abstract
A seasonal snow cover, expansive forests, a long coast line, and a mountainous terrain are features of Norway’s geography. Forests, ground snow, and sea surface temperature (SST) vary on time scales relevant for weather forecasting and climate projections. The mapping and model parameterization of these features vary in novelty, accuracy, and complexity. This paper investigates how increasing the influence of each of these features affects southern Norway’s surface energy and water balance in a regional climate model (WRF). High-resolution (3.7 km) experimental runs have been conducted over two consecutive hydrological years, including 1) heightening the boreal forest line (the Veg experiment), 2) increasing ground snow by altering the snow/rain criterion (the Snow experiment), or 3) increasing the SST (the SST experiment). The Veg experiment led to an increase in annual net radiation
Abstract
This study examines the impact of climate change on droughts in Norway. A spatially distributed (1 × 1 km2) version of the Hydrologiska Byråns Vattenbalansavdelning (HBV) precipitation-runoff model was used to provide hydrological data for the analyses. Downscaled daily temperature and precipitation derived from two atmosphere–ocean general circulation models with two future emission scenarios were applied as input to the HBV model. The differences in hydroclimatological drought characteristics in the summer season between the periods 1961–90 and 2071–2100 were studied. The threshold level method was adopted to select drought events for both present and future climates. Changes in both the duration and spatial extent of precipitation, soil moisture, runoff, and groundwater droughts were identified. Despite small changes in future meteorological drought characteristics, substantial increases in hydrological drought duration and drought affected areas are expected, especially in the southern and northernmost parts of the country. Reduced summer precipitation is a major factor that affects changes in drought characteristics in the south while temperature increases play a more dominant role for the rest of the country.
Abstract
This study examines the impact of climate change on droughts in Norway. A spatially distributed (1 × 1 km2) version of the Hydrologiska Byråns Vattenbalansavdelning (HBV) precipitation-runoff model was used to provide hydrological data for the analyses. Downscaled daily temperature and precipitation derived from two atmosphere–ocean general circulation models with two future emission scenarios were applied as input to the HBV model. The differences in hydroclimatological drought characteristics in the summer season between the periods 1961–90 and 2071–2100 were studied. The threshold level method was adopted to select drought events for both present and future climates. Changes in both the duration and spatial extent of precipitation, soil moisture, runoff, and groundwater droughts were identified. Despite small changes in future meteorological drought characteristics, substantial increases in hydrological drought duration and drought affected areas are expected, especially in the southern and northernmost parts of the country. Reduced summer precipitation is a major factor that affects changes in drought characteristics in the south while temperature increases play a more dominant role for the rest of the country.
Abstract
Water-related impacts are among the most important consequences of increasing greenhouse gas concentrations. Changes in the global water cycle will also impact the carbon and nutrient cycles and vegetation patterns. There is already some evidence of increasing severity of floods and droughts and increasing water scarcity linked to increasing greenhouse gases. So far, however, the most important impacts on water resources are the direct interventions by humans, such as dams, water extractions, and river channel modifications. The Water and Global Change (WATCH) project is a major international initiative to bring together climate and water scientists to better understand the current and future water cycle. This paper summarizes the underlying motivation for the WATCH project and the major results from a series of papers published or soon to be published in the Journal of Hydrometeorology WATCH special collection. At its core is the Water Model Intercomparison Project (WaterMIP), which brings together a wide range of global hydrological and land surface models run with consistent driving data. It is clear that we still have considerable uncertainties in the future climate drivers and in how the river systems will respond to these changes. There is a grand challenge to the hydrological and climate communities to both reduce these uncertainties and communicate them to a wider society.
Abstract
Water-related impacts are among the most important consequences of increasing greenhouse gas concentrations. Changes in the global water cycle will also impact the carbon and nutrient cycles and vegetation patterns. There is already some evidence of increasing severity of floods and droughts and increasing water scarcity linked to increasing greenhouse gases. So far, however, the most important impacts on water resources are the direct interventions by humans, such as dams, water extractions, and river channel modifications. The Water and Global Change (WATCH) project is a major international initiative to bring together climate and water scientists to better understand the current and future water cycle. This paper summarizes the underlying motivation for the WATCH project and the major results from a series of papers published or soon to be published in the Journal of Hydrometeorology WATCH special collection. At its core is the Water Model Intercomparison Project (WaterMIP), which brings together a wide range of global hydrological and land surface models run with consistent driving data. It is clear that we still have considerable uncertainties in the future climate drivers and in how the river systems will respond to these changes. There is a grand challenge to the hydrological and climate communities to both reduce these uncertainties and communicate them to a wider society.
Abstract
Six land surface models and five global hydrological models participate in a model intercomparison project [Water Model Intercomparison Project (WaterMIP)], which for the first time compares simulation results of these different classes of models in a consistent way. In this paper, the simulation setup is described and aspects of the multimodel global terrestrial water balance are presented. All models were run at 0.5° spatial resolution for the global land areas for a 15-yr period (1985–99) using a newly developed global meteorological dataset. Simulated global terrestrial evapotranspiration, excluding Greenland and Antarctica, ranges from 415 to 586 mm yr−1 (from 60 000 to 85 000 km3 yr−1), and simulated runoff ranges from 290 to 457 mm yr−1 (from 42 000 to 66 000 km3 yr−1). Both the mean and median runoff fractions for the land surface models are lower than those of the global hydrological models, although the range is wider. Significant simulation differences between land surface and global hydrological models are found to be caused by the snow scheme employed. The physically based energy balance approach used by land surface models generally results in lower snow water equivalent values than the conceptual degree-day approach used by global hydrological models. Some differences in simulated runoff and evapotranspiration are explained by model parameterizations, although the processes included and parameterizations used are not distinct to either land surface models or global hydrological models. The results show that differences between models are a major source of uncertainty. Climate change impact studies thus need to use not only multiple climate models but also some other measure of uncertainty (e.g., multiple impact models).
Abstract
Six land surface models and five global hydrological models participate in a model intercomparison project [Water Model Intercomparison Project (WaterMIP)], which for the first time compares simulation results of these different classes of models in a consistent way. In this paper, the simulation setup is described and aspects of the multimodel global terrestrial water balance are presented. All models were run at 0.5° spatial resolution for the global land areas for a 15-yr period (1985–99) using a newly developed global meteorological dataset. Simulated global terrestrial evapotranspiration, excluding Greenland and Antarctica, ranges from 415 to 586 mm yr−1 (from 60 000 to 85 000 km3 yr−1), and simulated runoff ranges from 290 to 457 mm yr−1 (from 42 000 to 66 000 km3 yr−1). Both the mean and median runoff fractions for the land surface models are lower than those of the global hydrological models, although the range is wider. Significant simulation differences between land surface and global hydrological models are found to be caused by the snow scheme employed. The physically based energy balance approach used by land surface models generally results in lower snow water equivalent values than the conceptual degree-day approach used by global hydrological models. Some differences in simulated runoff and evapotranspiration are explained by model parameterizations, although the processes included and parameterizations used are not distinct to either land surface models or global hydrological models. The results show that differences between models are a major source of uncertainty. Climate change impact studies thus need to use not only multiple climate models but also some other measure of uncertainty (e.g., multiple impact models).
