A Simple Surface Temperature Assimilation Scheme for Use in Land Surface Models

This paper examines the utilization of surface temperature as a variable which can be assimilated in off-line land surface hydrological models. The connection between the surface temperature and evapotranspiration is utilized in making adjustments to the model-computed surface soil moisture. This adjustment is a function of the difference between the model-computed and the observed surface temperature. Comparisons between the model-computed and satellite-observed surface temperatures have been carried out. The assimilation of surface temperature is carried out twice a day (corresponding to the A.M. and P.M. overpass of the NOAA 10) over the Red-Arkansas basin in the southwestern United States (31°50′N-36°N, 94°30′W-104°30′W) for a period of 1 year (August 1987 to July 1988). The soil moisture estimates resulting from the assimilation of surface temperature have a closer agreement with the values derived from the special sensor microwave imager than those from simulations without surface temperature assimilation. Assimilation reduces the effect of errors in precipitation and/or shortwave radiation on simulated soil moistures

Surface Temperature Assimilation in Land Surface Models

This paper examines the utilization of surface temperature as a variable to be assimilated in offline land surface hydrological models. Comparisons between the model computed and satellite observed surface temperatures have been carried out. The assimilation of surface temperature is carried out twice a day (corresponding to the AM and PM overpass of the NOAA10) over the Red- Arkansas basin in the Southwestern United States (31 deg 50 min N - 36 deg N, 94 deg 30 min W - 104 deg 30 min W) for a period of one year (August 1987 to July 1988). The effect of assimilation is to reduce the difference between the surface soil moisture computed for the precipitation and/or shortwave radiation perturbed case and the unperturbed case compared to no assimilation

Comparison of TOVS-derived Land Surface Variables with Ground Observations

The Tiros Operational Vertical Sounder (TOVS) Pathfinder Path A retrieved surface skin temperature, surface air temperatures, and surface specific humidity are compared with data obtained from three large-scale field campaigns: the First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment (FIFE), the Hydrologic Atmospheric Pilot Experiment (HAPEX) in the Sahel, and the Boreal Ecosystem-Atmosphere Study (BOREAS). The long-term estimates of surface skin temperatures, surface air temperatures, and surface vapor pressure were unbiased, and the standard deviations of the errors were about 4°C, 3.5°C, and 3.5 mbar, respectively. The monthly mean variables obtained from the TOVS data at four times of the day (corresponding to the AM and PM overpass for each of two satellites) exhibited realistic diurnal and seasonal cycles when compared with corresponding ground observations

Validation of Satellite Retrieved Land Surface Variables

The effective use of satellite observations of the land surface is limited by the lack of high spatial resolution ground data sets for validation of satellite products. Recent large scale field experiments include FIFE, HAPEX-Sahel and BOREAS which provide us with data sets that have large spatial coverage and long time coverage. It is the objective of this paper to characterize the difference between the satellite estimates and the ground observations. This study and others along similar lines will help us in utilization of satellite retrieved data in large scale modeling studies

Characterizing Subpixel Variability of Low Resolution Radiometer Derived Soil Moisture Using High Resolution Radar Data

Soil moisture estimates obtained using passive remote sensing from satellite platforms often suffer from the drawback of coarse spatial resolution. In this current work, low resolution soil moisture estimates from passive remote sensing are fused with high resolution radar backscatter data to produce soil moisture change estimates at the spatial resolution of radar. More specifically, soil moisture estimated from AMSR-E and TMI (separate cases) for a single 50 km × 50 km pixel has been fused with TRMM-PR backscatter data at 5 km resolution to produce soil moisture change estimates at 5 km resolution. A brief sensitivity analysis has been presented as a baseline study for soil moisture sensitivity of TRMM-PR backscatter. Soil moisture change estimates have been computed using a simple methodology and validated using in situ measurements from the Little Washita Micronet. It is seen that fusing radar data with radiometer soil moisture estimates leads to a better representation of the soil moisture variability within the radiometer pixel as compared to the baseline (radiometer estimate only) case where uniform subpixel distribution of soil moisture is assumed. The TMI/PR case performs better than the AMSR-E/PR case indicating the need for temporally coincident radar radiometer observations for producing high resolution soil moisture change estimates

Utilization of Satellite Data in Land Surface Hydrology: Sensitivity and Assimilation

This paper investigates the sensitivity of potential evapotranspiration to input meteorological variables, viz- surface air temperature and surface vapor pressure. The sensitivity studies have been carried out for a wide range of land surface variables such as wind speed, leaf area index and surface temperatures. Errors in the surface air temperature and surface vapor pressure result in errors of different signs in the computed potential evapotranspiration. This result has implications for use of estimated values from satellite data or analysis of surface air temperature and surface vapor pressure in large scale hydrological modeling. The comparison of cumulative potential evapotranspiration estimates using ground observations and satellite observations over Manhattan, Kansas for a period of several months shows very little difference between the two. The cumulative differences between the ground based and satellite based estimates of potential evapotranspiration amounted to less that 20mm over a 18 month period and a percentage difference of 15%. The use of satellite estimates of surface skin temperature in hydrological modeling to update the soil moisture using a physical adjustment concept is studied in detail including the extent of changes in soil moisture resulting from the assimilation of surface skin temperature. The soil moisture of the surface layer is adjusted by 0.9mm over a 10 day period as a result of a 3K difference between the predicted and the observed surface temperature. This is a considerable amount given the fact that the top layer can hold only 5mm of water

Scaling Water and Energy Fluxes in Climate Systems: Three Land-Atmospheric Modeling Experiments

The effects of small-scale heterogeneity in land-surface characteristics on the large-scale fluxes of water and energy in the land-atmosphere system have become a central focus of many of the climatology research experiments. The acquisition of high-resolution land-surface data through remote sensing and intensive land-climatology field experiments(like HAPEX and EIFE) has provided data to investigate the interactions between microscale land-atmosphere interactions and macroscale models. One essential research question is how to account for the small-scale heterogeneities and whether `effective\u27 parameters can be used in the macroscale models. To address this question ofscaling, three modeling experiments were performed and are reviewed in the paper. The first is concerned with the land-surface hydrology during rain events and between rain events. The second experiment applies the Simple Biosphere Model (SiB) to a heterogeneous domain and the spatial and temporal latent beat flux is analyzed. The third experiment uses thermatic mapper (TM) data to look at the scaling of the normalized vegetation index (NDVI), latent heat flux, and sensible heat flux through either scaling of the TM-derived fields using the TM data or the fields derived from aggregated TM data.In all three experiments it was found that the surface fluxes and land characteristics can be sealed, and that macroscale models based on elective parameters are sufficient to account for the small-scale heterogeneities investigated. The paper also suggests that the scale at which a macroscale model becomes valid, the representative elementary scale (REA), is on the order 1.5-3 correlation lengths, which for land processes investigated appears to be about 1000-1500 m. At scales less than the REA scale, exact patterns of subgrid heterogeneities are needed for accurate small-scale modeling

Links Between Snow Cover, Surface Skin Temperature, and Rainfall Variability in the North American Monsoon System

The influence of land–atmosphere interactions on the variability of the North American monsoon system(NAMS) is investigated using the Television Infrared Observation Satellite (TIROS) Operational Vertical Sounder(TOVS) Pathfinder, the Climate Prediction Center (CPC) gauge precipitation, and observed snow water equivalent(SWE). Three hypotheses are tested regarding the connection between land surface variables and precipitationin the NAMS region. First, there is a weak negative correlation between 1 April SWE and subsequent surfacetemperature in the southern Rocky Mountains (SRM) region. However, this connection persists only until Juneand, therefore, cannot directly influence monsoon rainfall in July and August. Second, there is a negativecorrelation between SRM surface temperature and NAMS precipitation during the monsoon season, rather thanthe positive correlation previously proposed. Third, there is a highly significant negative correlation betweenrainfall and surface temperature within the NAMS region. On the monthly timescale, surface temperature decreasesby ~4 K per 1 mm day21 increase in rainfall, consistent with a positive soil moisture–rainfall feedback.The substantial variability of SRM skin temperature (~10 K) may modulate the temperature gradient betweenland and ocean. However, these skin temperature anomalies persist only for ~1 month, so their effects arevariable throughout the monsoon season