No abstract

The U.S. Army has a need for continuous, accurate estimates of the wet bulb globe temperature to protect soldiers and civilian workers from heat-related injuries, including those involved in the storage and destruction of aging chemical munitions at depots across the United States. At these depots, workers must don protective clothing that increases their risk of heat-related injury. Because of the difficulty in making continuous, accurate measurements of wet bulb globe temperature outdoors, the authors have developed a model of the wet bulb globe temperature that relies only on standard meteorological data available at each storage depot for input. The model is composed of separate submodels of the natural wet bulb and globe temperatures that are based on fundamental principles of heat and mass transfer, has no site-dependent parameters, and achieves an accuracy of better than 1 degree C based on comparisons with wet bulb globe temperature measurements at all depots.

Thousands of comparisons between total precipitable water vapor (PWV) obtained from radiosonde (Vaisala RS80-H) profiles and PWV retrieved from a collocated microwave radiometer (MWR) were made at the Atmospheric Radiation Measurement (ARM) Program's Southern Great Plains Cloud and Radiation Testbed (SGP CART) site in northern Oklahoma from 1994 to 2000. These comparisons show that the RS80-H radiosonde has an approximate 5% dry bias compared to the MWR. This observation is consistent with interpretations of Vaisala RS80 radiosonde data obtained during the Tropical Ocean Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA COARE). In addition to the dry bias, analysis of the PWV comparisons as well as of data obtained from dual-sonde soundings done at the SGP show that the calibration of the radiosonde humidity measurements varies considerably both when the radiosondes come from different calibration batches and when the radiosondes come from the same calibration batch. This variability can result in peak-to-peak differences between radiosondes of greater than 25% in PWV. Because accurate representation of the vertical profile of water vapor is critical for ARM's science objectives, an empirical method for correcting the radiosonde humidity profiles is developed based on a constant scaling factor. By using an independent set of observations and radiative transfer models to test the correction, it is shown that the constant humidity scaling method appears both to improve the accuracy and reduce the uncertainty of the radiosonde data. The ARM data are also used to examine a different, physically based, correction scheme that was developed recently by scientists from Vaisala and the National Center for Atmospheric Research (NCAR). This scheme, which addresses the dry bias problem as well as other calibration-related problems with the RS80-H sensor, results in excellent agreement between the PWV retrieved from the MWR and integrated from the corrected radiosonde. However, because the physically based correction scheme does not address the apparently random calibration variations observed, it does not reduce the variability either between radiosonde calibration batches or within individual calibration batches.

Many clouds important to the Earth's energy balance contain small amounts of liquid water, yet despite many improvements, large differences in retrievals of their liquid water amount and particle size still must be resolved.

[1] A microwave radiometer is described that provides continuous thermodynamic (temperature, water vapor, and moisture) soundings during clear and cloudy conditions. The radiometric profiler observes radiation intensity at 12 microwave frequencies, along with zenith infrared and surface meteorological measurements. Historical radiosonde and neural network or regression methods are used for profile retrieval. We compare radiometric, radiosonde, and forecast soundings and evaluate the accuracy of radiometric temperature and water vapor soundings on the basis of statistical comparison with radiosonde soundings. We find that radiometric soundings are equivalent in accuracy to radiosonde soundings when used in numerical weather forecasting. A case study is described that demonstrates improved fog forecasting on the basis of variational assimilation of radiometric soundings. The accuracy of radiometric cloud liquid soundings is evaluated by comparison with cloud liquid sensors carried by radiosondes. Accurate high-resolution three-dimensional water vapor and wind analysis is described on the basis of assimilation of simulated thermodynamic and wind soundings along with GPS slant delays. Examples of mobile thermodynamic and wind profilers are shown. Thermodynamic profiling, particularly when combined with wind profiling and slant GPS, provides continuous atmospheric soundings for improved weather and dispersion forecasting.