William L. Crosson

Estimation of surface heat and moisture fluxes over a prairie grassland: 3. Design of a hybrid physical/remote sensing biosphere model

This is the third in a series of papers describing a measurement program and modeling approach to the estimation of surface heat and moisture fluxes over a tallgrass prairie. We describe the design and formulation of an experimental biosphere model (Ex-BATS) which follows the development of Dickinsons biosphere-atmosphere transfer scheme (BATS). Ex-BATS has been designed to incorporate in situ measurements and satellite parameterizations of certain canopy variables which are slowly varying in the course of a growing season. All components of a multistage biosphere process model used to simulate the exchange of heat and moisture between the canopy and the atmosphere are presented here. The remote sensing aspects of the model are described in a companion paper. The procedures used to optimize the model and the validation of the model against First ISLSCP Field Experiment (FIFE) observations taken during 1987 are described. Validation was carried out for three of the four intensive field campaigns (IFCs): 1, 2 and 3. The validation intercomparison shows that the Ex-BATS model reproduces the diurnal behavior of the surface fluxes very closely. The rms differences between in situ measurements of sensible and latent heat fluxes and their model counterparts are of the order of 35 W m−2. Biases over the three IFCs, which ranged in duration from 10 to 17 days, are typically less than 20 W m −2. The overall bias for the 44 days within the first three IFCs is less than 10 W m −2. The biases and rms differences are of the same order as the accuracy and precision uncertainties of the measured fluxes, therefore the model provides a useful experimental tool to explain radiative, hydrological, and physiological controls on surface fluxes over vegetated canopies and the explicit sources of water flux to the atmosphere from transpiration, foliage evaporation, and soil evaporation.

Estimation of surface heat and moisture fluxes over a prairie grassland: 1. In situ energy budget measurements incorporating a cooled mirror dew point hygrometer

This paper focuses on in situ measurements obtained during the First ISLSCP Field Experiment (FIFE) needed to support the development and validation of a biosphere model. Seasonal time series of surface flux measurements obtained from two surface radiation and energy budget stations (SREBS) used to support the FIFE surface flux measurement subprogram are analyzed. Data collection and processing procedures are presented along with the measurement analysis for the entire 1987 experimental period. The two Florida State University (FSU) stations, which were part of a 22-station surface flux network, used a cooled mirror dew point hygrometer to measure surface layer moisture gradients. Evapotranspiration was determined using the Bowen ratio method. A case study of FIFE Golden Day 2 illustrates the capabilities of a SREBS system. Sensible and latent heat fluxes are compared among themselves and against the 22-site domain means. The FSU site intercomparison demonstrates clear evidence of site-to-site differences, but a lengthy time series is required to interpret them correctly. Consistent relationships are observed between the SREBS fluxes and the all-site means on the FIFE Golden Days. The 1987 surface flux data show variations on annual, intraseasonal, synoptic, and diurnal time scales. The annual time scale, arising from a continually changing solar declination, is evident in the available heating although cloudiness variability serves to disguise the signal until late summer. The intraseasonal time scale is observed to be a response to the large scale rainfall pattern of 1987 (alternating wet and dry conditions during the summer months resulted in daytime daily mean Bowen ratios ranging from 0.1 to 0.7, with highest values occurring during plant senescence in October). Fluxes are also modulated on a synoptic time scale (5–7 days) resulting mostly from cloudiness perturbations which have a direct impact on surface available heating. The diurnal time scale, which results from the continually changing solar zenith angle, is modulated by a variety of soil moisture and plant physiology factors but is most sensitive to the intermittent behavior of cloudiness. These characteristics of the surface fluxes emphasize the strong feedback cloud and precipitation have on virtually all aspects of the atmospheric and surface energy budgets.

Assessment of Rainfall Estimates Using a Standard Z-R Relationship and the Probability Matching Method Applied to Composite Radar Data in Central Florida

Abstract Precipitation estimates from radar systems are a crucial component of many hydrometeorological applications, from dash flood forecasting to regional water budget studies. For analyses on large spatial scales and long timescales, it is frequently necessary to use composite reflectivities from a network of radar systems. Such composite products are useful for regional or national studies, but introduce a set of difficulties not encountered when using single radars. For instance, each contributing radar has its own calibration and scanning characteristics, but radar identification may not be retained in the compositing procedure. As a result, range effects on signal return cannot be taken into account. This paper assesses the accuracy with which composite radar imagery can be used to estimate precipitation in the convective environment of Florida during the summer of 1991. Results using Z = 300 R1.4. (WSR-88D default Z-R relationship) are compared with those obtained using the probability matching m...

Methods for Characterizing Fine Particulate Matter Using Ground Observations and Remotely Sensed Data: Potential Use for Environmental Public Health Surveillance

Abstract This study describes and demonstrates different techniques for surface fitting daily environmental hazards data of particulate matter with aerodynamic diameter less than or equal to 2.5 μm (PM2.5) for the purpose of inte grating respiratory health and environmental data for the Centers for Disease Control and Prevention (CDC) pilot study of Health and Environment Linked for Information Exchange (HELIX)–Atlanta. It presents a methodology for estimating daily spatial surfaces of ground-level PM2.5 concentrations using the B-Spline and inverse distance weighting (IDW) surface-fitting techniques, leveraging National Aeronautics and Space Administration (NASA) Moderate Resolution Imaging Spectrometer (MODIS) data to complement U.S. Environmental Protection Agency (EPA) ground observation data. The study used measurements of ambient PM2.5 from the EPA database for the year 2003 as well as PM2.5 estimates derived from NASA’s satellite data. Hazard data have been processed to derive the surrogate PM2.5 exposure estimates. This paper shows that merging MODIS remote sensing data with surface observations of PM2.5 not only provides a more complete daily representation of PM2.5 than either dataset alone would allow, but it also reduces the errors in the PM2.5- estimated surfaces. The results of this study also show that although the IDW technique can introduce some numerical artifacts that could be due to its interpolating nature, which assumes that the maxima and minima can occur only at the observation points, the daily IDW PM2.5 surfaces had smaller errors in general, with respect to observations, than those of the B-Spline surfaces. Finally, the methods discussed in this paper establish a foundation for environmental public health linkage and association studies for which determining the concentrations of an environmental hazard such as PM2.5 with high accuracy is critical.

Ground-based passive microwave remote sensing observations of soil moisture at S-band and L-band with insight into measurement accuracy

A ground-based experiment in passive microwave remote sensing of soil moisture was conducted in Huntsville, AL, from July 1-14, 1996. The goal of the experiment was to evaluate the overall performance of an empirically-based retrieval algorithm at S-band and L-band under a different set of conditions and to characterize the site-specific accuracy inherent within the technique. With high temporal frequency observations at S-band and L-band, the authors were able to observe large scale moisture changes following irrigation and rainfall events, as well as diurnal behavior of surface moisture among three plots, one bare, one covered with short grass and another covered with alfalfa. The L-band emitting depth was determined to be on the order of 0-3 or 0-5 cm below 0.30 cm/sup 3//cm/sup 3/ with an indication that it is less at higher moisture values. The S-band emitting depth was not readily distinguishable from L-band. The uncertainty in remotely sensed soil moisture observations due to surface heterogeneity and temporal variability in variables and parameters was characterized by imposing random errors on the most sensitive variables and parameters and computing the confidence limits on the observations. Discrepancies between remotely sensed and gravimetric soil moisture estimates appear to be larger than those expected from errors in variable and parameter estimation. This would suggest that a vegetation correction procedure based on more dynamic modeling may be required to improve the accuracy of remotely sensed soil moisture.

Effect of the number of soil layers on a modeled surface water budget

A sensitivity analysis was performed to determine the effects of systematically increasing the number of soil layers in a land surface-atmosphere model on the components of the modeled water budget. The study was done for a forested location in central Oklahoma for a 65-day period in spring 1996 using the model called Simulator for Hydrology and Energy Exchange at the Land Surface (SHEELS). SHEELS is based on the Biosphere-Atmosphere Transfer Scheme (BATS), except that the subsurface hydrology was substantially changed to improve representation of the soil moisture profile. The soil profile was divided into zones of thickness 0.05 m (upper), 1.25 m (root), and 1.20 m (bottom). The two principal conclusions are that (1) the water budget is very sensitive to the number of layers in the soil profile under wet conditions and (2) the water budget is much more sensitive to the number of layers in the profile than to the range of 2 orders of magnitude in saturated hydraulic conductivity considered in this study. A result of the latter conclusion is that larger errors in modeled water fluxes can occur from using an insufficient number of soil layers than from using an incorrect value of saturated hydraulic conductivity.

Estimation of surface heat and moisture fluxes over a prairie grassland: 4. Impact of satellite remote sensing of slow canopy variables on performance of a hybrid biosphere model

Herein, we present the results of a series of numerical experiments using the Ex-BATS biosphere model, which is an adaptation of Dickinsons biosphere-atmosphere transfer scheme (BATS). These simulations are used to assess how the model performs when remotely sensed data are used to estimate three key canopy variables. These canopy variables, which effectively represent the slowly changing boundary conditions of a vegetated surface, consist of the total surface albedo, leaf area index, and the nondiurnally varying component of stomatal resistance, referred to as stressed stomatal resistance. The surface albedo is retrieved from NOAA-AVHRR (advanced very high resolution radiometer) channel 1 spectral reflectance information in conjunction with a directional reflectance model which accounts for the strong diurnal variations in surface reflectance. A 4-channel vegetation index also retrieved from AVHRR measurements is used to estimate the leaf area index. A similar index derived from high-resolution SPOT visible and near-infrared information has been used to describe the spatial variations in such indices which impact the retrieval of the leaf area index. Satellite retrieval of stomatal resistance is based on split-window skin temperatures from AVHRR channels 4 and 5 from the afternoon overpass (∼1630 LT). Variables derived from the hourly skin temperature observations of GOES-VISSR have also been examined with respect to retrieval of stomatal resistance. It was found that although stomatal resistance has little correlation with the diurnal amplitude of skin temperature, it is closely related to the daily maximum of skin temperature. Numerical experiments have been conducted to examine model sensitivity to each of these canopy variables. Results indicate that Ex-BATS is not sensitive to small variations of surface albedo or leaf area index within the range of estimation uncertainty. The rms measurement-model flux differences in every numerical trial were within 6 W m−2 of the rms differences obtained for the simulations performed using measured albedo and leaf area index. Measured stomatal resistance values were obtained using an inversion form of the model. The resulting stomatal resistances were used to perform a control experiment simulating an ideal satellite retrieval scenario involving one observation per day. The control experiment resulted in improvements of approximately 20 W m−2 in the rms flux differences over the model using a purely hypothetical formulation for stomatal resistance. Simulations using the remotely retrieved stomatal resistances produced significantly reduced rms differences for latent and sensible heat fluxes over the model using the hypothetical formulation. Based on a 55-day composite involving all days from the four FIFE intensive field campaigns, the sensible and latent heat flux improvements are approximately 25 and 20%, respectively (11 and 8 W m−2). The satellite retrievals are only 20 and 30% less accurate (7 and 10 W m−2) than the idealized results of the control experiment.

Comparison of two microwave radiobrightness models and validation with field measurements

This paper compares microwave brightness temperature (T/sub B/) estimated by two radiobrightness models: a multilayer coherent radiative transfer (CRT) model and a single-layer Fresnel reflectance model. Two dielectric mixing schemes were used along with the models to calculate permittivity (real part of the dielectric constant). Model T/sub B/ and permittivity estimates were compared and validated against Huntsville, AL 1998 field experiment measurements. Model differences can be attributed to the mixing scheme, the radiobrightness model, or the vertical profile representation. Two sets of simulations were performed to quantify the sources of variation, one using observed son temperature and moisture profiles as input, and another using uniform profiles. Using uniform profiles, systematic differences in permittivity estimated by the mixing schemes resulted in T/sub B/ differences as large as 15 K. However, for uniform profiles, differences in T/sub B/ estimated by the radiobrightness models for a given permittivity value were less than 2 K. For cases using observed profiles, near-surface drying of the profiles resulted in T/sub B/ values from the CRT model 6-10 K higher than estimates from the Fresnel model, which determines T/sub B/ based on 0-5 cm mean moisture and temperature. Therefore, the major sources of T/sub B/ variations were the dielectric mixing scheme and the shape of the near-surface moisture profile. No radiobrightness/mixing scheme combination exhibited superiority across all plots and times.

Impacts of Spatial Scaling Errors on Soil Moisture Retrieval Accuracy at L-Band

In the near future, data from two microwave remote sensors at L-band will enable estimation of near-surface soil moisture. The European Space Agencys Soil Moisture and Salinity Mission (SMOS) launched in November 2009, and NASA is developing a new L-band soil moisture mission named Soil Moisture Active/Passive (SMAP). Soil moisture retrieval theory is well-established, but many details of its application, including the effects of spatial scale, are still being studied. To support these two L-band missions, studies are needed to improve our understanding of the various error sources associated with retrieval of soil moisture from satellite sensors. The purpose of this study is to quantify the magnitude of the scaling error created by the existence of sub-footprint scale variability in soil and vegetation properties, which have nonlinear relationships with emitted microwave energy. The scaling error is related to different functional relationships between surface microwave emissivity and soil moisture that exist for different soils and land cover types within a satellite footprint. We address this problem using single-frequency, single-polarization passive L-band microwave simulations for an Upper Midwest agricultural region in the United States. Making several simplifying assumptions, the analysis performed here helps provide guidance and define limits for future mission requirements by indicating hydrological and landscape conditions under which large errors are expected, and other conditions that are more conducive to accurate soil moisture estimates. Errors associated with spatial aggregation of highly variable land surface characteristics within 40 km satellite ?footprints? were found to be larger than the baseline mission requirements of 0.04-0.06 Volumetric Soil Moisture (VSM) over much of the study area. Soil moisture estimation errors were especially large and positive over portions of the domain characterized by mixtures of forests, wetlands, and open water or mixtures of forest and pasture. However, by eliminating from the analysis areas with high vegetation water content or substantial surface water fractions, conditions that have well-documented adverse effects on soil moisture retrieval, we obtained errors that are in line with these mission requirements. We developed a parameterization for effective optical depth (?eff) based on the standard deviation of optical depth (??) within a footprint in order to improve soil moisture retrieval in the presence of highly variable vegetation density. Use of the resulting parameterized optical depth in retrievals eliminated almost all of the soil moisture biases in our simulated setting. Operationally, the empirical relationship between ?eff and ?? would need to be determined a priori based on intensive measurements from ground-based instrumentation networks or via tuning of the algorithm. Due to this issue and other confounding factors, results are not expected to be as good as in the simulated cases presented here. However, the relationship found in this study is likely to be consistent across landscapes, so any correction following this functional form would very likely lead to large improvements over retrievals based simply on weighted mean properties.

Estimation of surface heat and moisture fluxes over a prairie grassland: 2. Two-dimensional time filtering and site variability

The behavior of in situ measurements of surface fluxes obtained during FIFE 1987 is examined by using correlative and spectral techniques in order to assess the significance of fluctuations on various time scales, from subdiurnal up to synoptic, intraseasonal, and annual scales. The objectives of this analysis are (1) to determine which temporal scales have a significant impact on areal averaged fluxes and (2) to design a procedure for filtering an extended flux time series that preserves the basic diurnal features and longer time scales while removing high frequency noise that cannot be attributed to site-induced variation. These objectives are accomplished through the use of a two-dimensional cross-time Fourier transform, which serves to separate processes inherently related to diurnal and subdiurnal variability from those which impact flux variations on the longer time scales. A filtering procedure is desirable before the measurements are utilized as input with an experimental biosphere model, to insure that model based intercomparisons at multiple sites are uncontaminated by input variance not related to true site behavior. Analysis of the spectral decomposition indicates that subdiurnal time scales having periods shorter than 6 hours have little site-to-site consistency and therefore little impact on areal integrated fluxes. The spectral filter has thus been designed to remove these modes. Application of the filter to the 143-day FIFE 1987 flux records results in time series that retain at least 90% of the original variance and preserve the slower diurnal and longer time scales.