William James Shuttleworth

Creation of the WATCH Forcing Data and Its Use to Assess Global and Regional Reference Crop Evaporation over Land during the Twentieth Century

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.

Parameter estimation of a land surface scheme using multicriteria methods

Attempts to create models of surfaceߚ;atmosphere interactions with greater physical realism have resulted in land surface schemes (LSS) with large numbers of parameters. The hope has been that these parameters can be assigned typical values by inspecting the literature. The potential for using the various observational data sets that are now available to extract plot-scale estimates for the parameters of a complex LSS via advanced parameter estimation methods developed for hydrological models is explored in this paper. Results are reported for two case studies using data sets of typical quality but very different location and climatological regime (ARM-CART and Tucson). The traditional single-criterion methods were found to be of limited value. However, a multicriteria approach was found to be effective in constraining the parameter estimates into physically plausible ranges when observations on at least one appropriate heat flux and one properly selected state variable are available.

Sensitivity analysis of a land surface scheme using multicriteria methods

Attempts to model surface-atmosphere interactions with greater physical realism have resulted in complex land surface schemes (LSS) with large numbers of parameters. A companion paper describes a multicriteria calibration procedure for extracting plot-scale estimates of the preferred ranges of these parameters from the various observational data sets that are now available. A complementary procedure is presented in this paper that provides an objective determination of the multicriteria sensitivity of the modeled variables to the parameters, thereby allowing the number of calibration parameters and hence the computational effort to be reduced. Two case studies are reported for the BATS model using data sets of typical quality but very different location and climatological regime (ARM-CART and Tucson). The sensitivity results were found to be consistent with the physical properties of the different environments, thereby supporting the reasonableness of the model formulation. Further, when the insensitive parameters are omitted from the calibration process, there is little degradation in the quality of the model description and little change in the preferred range of the remaining parameters.

Seasonal estimates of riparian evapotranspiration using remote and in situ measurements

In many semi-arid basins during extended periods when surface snowmelt or storm runoff is absent, groundwater constitutes the primary water source for human habitation, agriculture and riparian ecosystems. Utilizing regional groundwater models in the management of these water resources requires accurate estimates of basin boundary conditions. A critical groundwater boundary condition that is closely coupled to atmospheric processes and is typically known with little certainty is seasonal riparian evapotranspiration (ET). This quantity can often be a significant factor in the basin water balance in semi-arid regions yet is very difficult to estimate over a large area. Better understanding and quantification of seasonal, large-area riparian ET is a primary objective of the Semi-Arid Land-Surface-Atmosphere (SALSA) Program. To address this objective, a series of interdisciplinary experimental campaigns were conducted in 1997 in the San Pedro Basin in southeastern Arizona. The riparian system in this basin is primarily made up of three vegetation communities: mesquite (Prosopis velutina), sacaton grasses (Sporobolus wrightii), and a cottonwood (Populus fremontii)/willow (Salix goodingii) forest gallery. Micrometeorological measurement techniques were used to estimate ET from the mesquite and grasses. These techniques could not be utilized to estimate fluxes from the cottonwood/willow (C/W) forest gallery due to the height (20‐30 m) and non-uniform linear nature of the forest gallery. Short-term (2‐4 days) sap flux measurements were made to estimate canopy transpiration over several periods of the riparian growing season. Simultaneous remote sensing measurements were used to spatially extrapolate tree and stand measurements. Scaled C/W stand level sap flux estimates were utilized to calibrate a Penman‐Monteith model to enable temporal extrapolation between synoptic measurement periods. With this model and set of measurements, seasonal riparian vegetation water use estimates for the riparian corridor were obtained. To validate these models, a 90-day pre-monsoon water balance over a 10 km section of the river was carried out. All components of the water balance, including riparian ET, were

Measurement depth of the cosmic ray soil moisture probe affected by hydrogen from various sources

[1] We present here a simple and robust framework for quantifying the effective sensor depth of cosmic ray soil moisture neutron probes such that reliable water fluxes may be computed from a time series of cosmic ray soil moisture. In particular, we describe how the neutron signal depends on three near-surface hydrogen sources: surface water, soil moisture, and lattice water (water in minerals present in soil solids) and also their vertical variations. Through a combined modeling study of one-dimensional water flow in soil and neutron transport in the atmosphere and subsurface, we compare average water content between the simulated soil moisture profiles and the universal calibration equation which is used to estimate water content from neutron counts. By using a linear sensitivity weighting function, we find that during evaporation and drainage periods the RMSE of the two average water contents is 0.0070 m 3 m � 3 with a maximum deviation of 0.010 m 3 m � 3 for a range of soil types. During infiltration, the RMSE is 0.011 m 3 m � 3 with a maximum deviation of 0.020 m 3 m � 3 , where piston like flow conditions exists for the homogeneous isotropic media. Because piston flow is unlikely during natural conditions at the horizontal scale of hundreds of meters that is measured by the cosmic ray probe, this modeled deviation of 0.020 m 3 m � 3 represents the worst case scenario for cosmic ray sensing of soil moisture. Comparison of cosmic ray soil moisture data and a distributed sensor soil moisture network in Southern Arizona indicates an RMSE of 0.011 m 3 m � 3 over a

Preface paper to the Semi-Arid Land-Surface-Atmosphere (SALSA) Program special issue.

The Semi-Arid Land-Surface-Atmosphere Program (SALSA) is a multi-agency, multi-national research effort that seeks to evaluate the consequences of natural and human-induced environmental change in semi-arid regions. The ultimate goal of SALSA is to advance scientific understanding of the semi-arid portion of the hydrosphere-biosphere interface in order to provide reliable information for environmental decision making. SALSA approaches this goal through a program of long-term, integrated observations, process research, modeling, assessment, and information management that is sustained by cooperation among scientists and information users. In this preface to the SALSA special issue, general program background information and the critical nature of semi-arid regions is presented. A brief description of the Upper San Pedro River Basin, the initial location for focused SALSA research follows. Several overarching research objectives under which much of the interdisciplinary research contained in the special issue was undertaken are discussed. Principal methods, primary research sites and data collection used by numerous investigators during 1997-1999 are then presented. Scientists from about 20 US, five European (four French and one Dutch), and three Mexican agencies and institutions have collaborated closely to make the research leading to this special issue a reality. The SALSA Program has served as a model of interagency cooperation by breaking new ground in the approach to large scale interdisciplinary science with relatively limited resources.

The Effect of Atmospheric Water Vapor on Neutron Count in the Cosmic-Ray Soil Moisture Observing System

The cosmic-ray method for measuring soil moisture, used in the Cosmic-Ray Soil Moisture Observing System (COSMOS), relies on the exceptional ability of hydrogen to moderate fast neutrons. Sources of hydrogen near the ground, other than soil moisture, affect the neutron measurement and therefore must be quantified. This study investigates the effect of atmospheric water vapor on the cosmic-ray probe signal and evaluates the fast neutron response in realistic atmospheric conditions using the neutron transport code Monte Carlo N-Particle eXtended (MCNPX). The vertical height of influence of the sensor in the atmosphere varies between 412 and 265m in dry and wet atmospheres, respectively. Model results show that atmospheric water vapor near the surface affects the neutron intensity signal by up to 12%, corresponding to soil moisture differences on the order of 0.10m 3 m 23 . A simple correction is defined to identify the true signal associated with integrated soil moisture that rescales the measured neutron intensity to that which would have been observed in the atmospheric conditions prevailing on the day of sensor calibration. Use of this approach is investigated with in situ observations at two sites characterized by strong seasonality in water vapor where standard meteorological measurements are readily available.

Constraining Land Surface and Atmospheric Parameters of a Locally Coupled Model Using Observational Data

Abstract In coupled land surface–atmosphere modeling, the possibility and benefits of constraining model parameters using observational data bear investigation. Using the locally coupled NCAR Single-column Community Climate Model (NCAR SCCM), this study demonstrates some feasible, effective approaches to constrain parameter estimates for coupled land–atmosphere models and explores the effects of including both land surface and atmospheric parameters and fluxes/variables in the parameter estimation process, as well as the value of conducting the process in a stepwise manner. The results indicate that the use of both land surface and atmospheric flux variables to construct error criteria can lead to better-constrained parameter sets. The model with “optimal” parameters generally performs better than when a priori parameters are used, especially when some atmospheric parameters are included in the parameter estimation process. The overall conclusion is that, to achieve balanced, reasonable model performance ...

Estimation of area-average sensible heat flux using a large-aperture scintillometer during the Semi-Arid Land-Surface-Atmosphere (SALSA) Experiment

The use of a large-aperture scintillometer to estimate sensible heat flux has been successfully tested by several investigators. Most of these investigations, however, have been confined to homogeneous or to sparse with single vegetation-type surfaces. The use of the scintillometer over surfaces made up of contrasting vegetation types is problematic because it requires estimates of effective roughness length and effective displacement height in order to derive area-average sensible heat from measurements of the refractive index. In this study an approach based on a combination of scintillometer measurements and an aggregation scheme has been used to derive area-average sensible heat flux over a transect spanning two adjacent and contrasting vegetation patches: grass and mesquite. The performance of this approach has been assessed using data collected during the 1997 Semi-Arid Land-Surface-Atmosphere field campaign. The results show that the combined approach performed remarkably well, and the correlation coefficient between measured and simulated area-average sensible heat flux was ∼0.95. This is of interest because this approach offers a reliable means for validating remotely sensed estimates of surface fluxes at comparable spatial scales.

Sensitivity of ground heat flux to vegetation cover fraction and leaf area index

Two land-surface models that participated in the recent Project for Intercomparison of Land-Surface Parameterization Schemes (PILPS, phase 2c) are used to investigate the sensitivity of the ground heat flux to the vegetation cover fraction and leaf area index (LAI). The two models are the Biosphere-Atmosphere Transfer Scheme (BATS) and the model developed at the Institute of Atmospheric Physics, Chinese Academy of Sciences (IAP94). The impacts of including transmission of solar radiation through the canopy in the BATS model are also assessed. The ground heat flux is the energy residual of net radiation minus latent plus sensible heat fluxes at the soil surface (also referred to as the soil heat flux). However, the energy residual above the canopy was used as a surrogate for the ground heat flux by the two models in the PILPS 2c study. The two energy residuals (i.e., above the canopy and at the soil surface) can differ depending on the modeled time step, the order in which the canopy and soil temperatures are computed, and whether canopy heat storage is included or neglected. As expected, reducing the areal coverage of vegetation results in an increased daytime soil heat flux, and increasing LAI leads to decreased soil heat flux and greater above-canopy latent heat flux. Both models show a strong sensitivity to LAI when LAI is small and little sensitivity when LAI is large. Allowing transmission of solar radiation through the canopy in BATS reduces the sensible heat flux above the canopy and enhances all the flux terms at the soil surface, especially when LAI is low. This model behavior is similar to that from IAP94, which uses a two-stream radiation scheme. This modification to BATS also results in a soil heat flux that lies within estimated bounds for a wide range of LAI (0.5–5.5).