The Global Energy and Water Cycle Experiment (GEWEX)
Description:
This special collection of the Journal of Hydrometeorology describes research supporting the Global Energy and Water Cycle Experiment (GEWEX) priorities with a specific focus on the advancement of hydrometeorological sciences. It explores how hydrometeorological research has been used to improve process understanding and forecast models, provide datasets for model validation, and support water resource applications.
The Global Energy and Water Cycle Experiment (GEWEX)
Abstract
To analyze the water budget under human influences in the Huaihe River plain region in China, the authors have developed a numerical modeling system that integrates water flux algorithms into a platform created by coupling a soil moisture model with the modular three-dimensional finite-difference groundwater flow model (MODFLOW). The modeling system is largely based on physical laws and employs a numerical method of the finite difference to simulate water movement and fluxes in a horizontally discretized watershed or field. The majority of model parameters carry physical significance and can be determined by field and laboratory measurements or derived from watershed characteristics contained in GIS and remote sensing data. Several other empirical parameters need to be estimated by model calibration. The numerical modeling system is calibrated in the Linhuanji catchment (2 560 km2) to estimate surface runoff, groundwater recharge, and groundwater loss for evapotranspiration and stream baseflow. Model validation is conducted at a small runoff experimental field (1.36 km2) in the Wuduogou Hydrological Experimental Station to test the model’s capability to simulate hydrological components and estimate water fluxes using observed stream stage and groundwater data, as well as lysimeter-measured precipitation recharge and groundwater loss. As proven by the promising results of model testing, this physically based and distributed-parameter model is a valuable contribution to the ever-advancing technology of hydrological modeling and water resources assessment.
Abstract
To analyze the water budget under human influences in the Huaihe River plain region in China, the authors have developed a numerical modeling system that integrates water flux algorithms into a platform created by coupling a soil moisture model with the modular three-dimensional finite-difference groundwater flow model (MODFLOW). The modeling system is largely based on physical laws and employs a numerical method of the finite difference to simulate water movement and fluxes in a horizontally discretized watershed or field. The majority of model parameters carry physical significance and can be determined by field and laboratory measurements or derived from watershed characteristics contained in GIS and remote sensing data. Several other empirical parameters need to be estimated by model calibration. The numerical modeling system is calibrated in the Linhuanji catchment (2 560 km2) to estimate surface runoff, groundwater recharge, and groundwater loss for evapotranspiration and stream baseflow. Model validation is conducted at a small runoff experimental field (1.36 km2) in the Wuduogou Hydrological Experimental Station to test the model’s capability to simulate hydrological components and estimate water fluxes using observed stream stage and groundwater data, as well as lysimeter-measured precipitation recharge and groundwater loss. As proven by the promising results of model testing, this physically based and distributed-parameter model is a valuable contribution to the ever-advancing technology of hydrological modeling and water resources assessment.
Abstract
Global monthly and daily precipitation extremes are examined in relation to the El Niño–Southern Oscillation phenomenon. For each month around the annual cycle and in each 2.5° grid block, extremes in the Global Precipitation Climatology Project dataset are defined as the top five (wet) and bottom five (dry) mean rain rates from 1979 to 2004. Over the tropical oceans El Niño–Southern Oscillation events result in a spatial redistribution and overall increase in extremes. Restricting the analysis to land shows that El Niño is associated with an increase in frequency of dry extremes and a decrease in wet extremes resulting in no change in net extreme months. During La Niña an increase in frequency of dry extremes and no change in wet extremes are observed. Thus, because of the juxtaposition of tropical land areas with the ascending branches of the global Walker Circulation, El Niño (La Niña) contributes to generally dry (wet) conditions in these land areas.
In addition, daily rain rates computed from the Tropical Rainfall Measuring Mission Multisatellite Precipitation Analysis are used to define extreme precipitation frequency locally as the number of days within a given season that exceeded the 95th percentile of daily rainfall for all seasons (1998–2005). During this period, the significant relationships between extreme daily precipitation frequency and Niño-3.4 in the Tropics are spatially similar to the significant relationships between seasonal mean rainfall and Niño-3.4. However, to address the shortness of the record extreme daily precipitation frequency is also related to seasonal rainfall for the purpose of identifying regions where positive seasonal rainfall anomalies can be used as proxies for extreme events. Finally, the longer (1979–2005) but coarser Global Precipitation Climatology Project analysis is reexamined to pinpoint regions likely to experience an increase in extreme precipitation during El Niño–Southern Oscillation events. Given the significance of El Niño–Southern Oscillation predictions, this information will enable the efficient use of resources in preparing for and mitigating the adverse effects of extreme precipitation.
Abstract
Global monthly and daily precipitation extremes are examined in relation to the El Niño–Southern Oscillation phenomenon. For each month around the annual cycle and in each 2.5° grid block, extremes in the Global Precipitation Climatology Project dataset are defined as the top five (wet) and bottom five (dry) mean rain rates from 1979 to 2004. Over the tropical oceans El Niño–Southern Oscillation events result in a spatial redistribution and overall increase in extremes. Restricting the analysis to land shows that El Niño is associated with an increase in frequency of dry extremes and a decrease in wet extremes resulting in no change in net extreme months. During La Niña an increase in frequency of dry extremes and no change in wet extremes are observed. Thus, because of the juxtaposition of tropical land areas with the ascending branches of the global Walker Circulation, El Niño (La Niña) contributes to generally dry (wet) conditions in these land areas.
In addition, daily rain rates computed from the Tropical Rainfall Measuring Mission Multisatellite Precipitation Analysis are used to define extreme precipitation frequency locally as the number of days within a given season that exceeded the 95th percentile of daily rainfall for all seasons (1998–2005). During this period, the significant relationships between extreme daily precipitation frequency and Niño-3.4 in the Tropics are spatially similar to the significant relationships between seasonal mean rainfall and Niño-3.4. However, to address the shortness of the record extreme daily precipitation frequency is also related to seasonal rainfall for the purpose of identifying regions where positive seasonal rainfall anomalies can be used as proxies for extreme events. Finally, the longer (1979–2005) but coarser Global Precipitation Climatology Project analysis is reexamined to pinpoint regions likely to experience an increase in extreme precipitation during El Niño–Southern Oscillation events. Given the significance of El Niño–Southern Oscillation predictions, this information will enable the efficient use of resources in preparing for and mitigating the adverse effects of extreme precipitation.
Abstract
This study employs the NCEP Eta Regional Climate Model to investigate the response of the model’s seasonal simulations of summer precipitation to high-frequency variability of soil moisture. Specifically, it focuses on the response of model precipitation and temperature over the U.S. Midwest and Southeast to imposed changes in the diurnal and synoptic variability of soil moisture in 1988 and 1993.
High-frequency variability of soil moisture increases (decreases) precipitation in the 1988 drought (1993 flood) year in the central and southern-tier states, except along the Gulf Coast, but causes smaller changes in precipitation along the northern-tier states. The diurnal variability and synoptic variability of soil moisture produce similar patterns of precipitation change, indicating the importance of the diurnal cycle of land surface process. The increase (decrease) in precipitation is generally accompanied by a decrease (increase) in surface and lower-tropospheric temperatures, and the changes in precipitation and temperature are attributed to both the local effect of evaporation feedback and the remote influence of large-scale water vapor transport. The precipitation increase and temperature decrease in 1988 are accompanied by an increase in local evaporation and, more importantly, by an increase in the large-scale water vapor convergence into the Midwest and Southeast. Analogous but opposite-sign behavior occurs in 1993 (compared to 1988) in changes in precipitation, temperature, soil moisture, evaporation, and large-scale water vapor transport.
Results also indicate that, in regions where the model simulates the diurnal cycle of soil moisture reasonably well, including this diurnal cycle in the simulations improves model performance. However, no notable improvement in model precipitation can be found in regions where the model fails to realistically simulate the diurnal variability of soil moisture.
Abstract
This study employs the NCEP Eta Regional Climate Model to investigate the response of the model’s seasonal simulations of summer precipitation to high-frequency variability of soil moisture. Specifically, it focuses on the response of model precipitation and temperature over the U.S. Midwest and Southeast to imposed changes in the diurnal and synoptic variability of soil moisture in 1988 and 1993.
High-frequency variability of soil moisture increases (decreases) precipitation in the 1988 drought (1993 flood) year in the central and southern-tier states, except along the Gulf Coast, but causes smaller changes in precipitation along the northern-tier states. The diurnal variability and synoptic variability of soil moisture produce similar patterns of precipitation change, indicating the importance of the diurnal cycle of land surface process. The increase (decrease) in precipitation is generally accompanied by a decrease (increase) in surface and lower-tropospheric temperatures, and the changes in precipitation and temperature are attributed to both the local effect of evaporation feedback and the remote influence of large-scale water vapor transport. The precipitation increase and temperature decrease in 1988 are accompanied by an increase in local evaporation and, more importantly, by an increase in the large-scale water vapor convergence into the Midwest and Southeast. Analogous but opposite-sign behavior occurs in 1993 (compared to 1988) in changes in precipitation, temperature, soil moisture, evaporation, and large-scale water vapor transport.
Results also indicate that, in regions where the model simulates the diurnal cycle of soil moisture reasonably well, including this diurnal cycle in the simulations improves model performance. However, no notable improvement in model precipitation can be found in regions where the model fails to realistically simulate the diurnal variability of soil moisture.
