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W. Gao, R. L. Coulter, B. M. Lesht, J. Qiu, and M. L. Wesely


The authors compared methods for estimating surface fluxes under clear-sky conditions over a large heterogeneous area from a limited number of ground measurements and from satellite observations using data obtained from the southern Great Plains Cloud and Radiation Testbed (CART) site, an area of approximately 350 km × 400 km located in Kansas and Oklahoma. In situ measurements from 10 energy balance Bowen ratio (EBBR) stations showed large spatial variations in latent and sensible heat fluxes across the site because of differences in vegetation and soil conditions. This variation was reproduced by a model for parameterization of subgrid- scale (PASS) surface fluxes that was developed previously and extended in the present study to include a distribution of soil moisture inferred from combined visible and thermal infrared remote sensing data. In the framework of the PASS model, the satellite-derived normalized difference vegetation index and surface temperature were used to derive essential surface parameters including surface albedo, surface conductance, soil heat flux ratio, surface roughness length, and soil moisture, which were then used to calculate a surface energy budget at satellite-pixel scales with pixel-specific surface meteorological conditions appropriately distributed from their mean values using a distribution algorithm. Although the derived soil moisture may be influenced by various uncertainty factors involved in the satellite data and the model, spatial variations of soil moisture derived from the multichannel data from the Advanced Very High Resolution Radiometers on the NOAA-14 satellite appeared to have some correlation (the correlation coefficient is as large as 0.6) with the amount of accumulated previous rainfall measured at the 58 Oklahoma Mesonet stations located within the CART area. Surface net radiation, soil heat flux, and latent and sensible heat fluxes calculated at a spatial resolution of 1 km (the size of a satellite pixel) were evaluated directly by comparing with flux measurements from the EBBR stations and indirectly by comparing air temperature and humidity inferred from calculated sensible and latent heat fluxes with corresponding values measured at 1.5 m above the 58 meteorological stations. In calculating regional fluxes, biases caused by the sampling uncertainty associated with point measurements may be corrected by application of the satellite data.

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Edgeworth R. Westwater, B. Boba Stankov, Domenico Cimini, Yong Han, Joseph A. Shaw, Barry M. Lesht, and Carles N. Long


During June–July 1999, the NOAA R/V Ron H. Brown (RHB) sailed from Australia to the Republic of Nauru where the Department of Energy's Atmospheric Radiation Measurement (ARM) Program operates a long-term climate observing station. During July, when the RHB was in close proximity to the island of Nauru, detailed comparisons of ship- and island-based instruments were possible. Essentially identical instruments were operated from the ship and the island's Atmospheric Radiation and Cloud Station (ARCS)-2. These instruments included simultaneously launched Vaisala RS80-H radiosondes, the Environmental Technology Laboratory's (ETL) Fourier transform infrared radiometer (FTIR), and ARM's atmospheric emitted radiance interferometer (AERI), as well as cloud radars/ceilometers to identify clear conditions.

The ARM microwave radiometer (MWR) operating on Nauru provided another excellent dataset for the entire Nauru99 experiment. The calibration accuracy was verified by a liquid nitrogen blackbody target experiment and by consistent high quality tipping calibrations throughout the experiment. Comparisons were made for calculated clear-sky brightness temperature (T b) and for precipitable water vapor (PWV). These results indicate that substantial errors, sometimes of the order of 20% in PWV, occurred with the original radiosondes. When a Vaisala correction algorithm was applied, calculated T bs were in better agreement with the MWR than were the calculations based on the original data. However, the improvement in T b comparisons was noticeably different for different radiosonde lots and was not a monotonic function of radiosonde age. Three different absorption algorithms were compared: Liebe and Layton, Liebe et al., and Rosenkranz. Using AERI spectral radiance observations as a comparison standard, scaling of radiosondes by MWR data was compared with both original and corrected soundings.

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D. D. Turner, B. M. Lesht, S. A. Clough, J. C. Liljegren, H. E. Revercomb, and D. C. Tobin


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.

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The Arm Program's Water Vapor Intensive Observation Periods

Overview, Initial Accomplishments, and Future Challenges

H. E. Revercomb, D. D. Turner, D. C. Tobin, R. O. Knuteson, W. F. Feltz, J. Barnard, J. Bösenberg, S. Clough, D. Cook, R. Ferrare, J. Goldsmith, S. Gutman, R. Halthore, B. Lesht, J. Liljegren, H. Linné, J. Michalsky, V. Morris, W. Porch, S. Richardson, B. Schmid, M. Splitt, T. Van Hove, E. Westwater, and D. Whiteman

A series of water vapor intensive observation periods (WVIOPs) were conducted at the Atmospheric Radiation Measurement (ARM) site in Oklahoma between 1996 and 2000. The goals of these WVIOPs are to characterize the accuracy of the operational water vapor observations and to develop techniques to improve the accuracy of these measurements.

The initial focus of these experiments was on the lower atmosphere, for which the goal is an absolute accuracy of better than 2% in total column water vapor, corresponding to ~1 W m−2 of infrared radiation at the surface. To complement the operational water vapor instruments during the WVIOPs, additional instrumentation including a scanning Raman lidar, microwave radiometers, chilled-mirror hygrometers, a differential absorption lidar, and ground-based solar radiometers were deployed at the ARM site. The unique datasets from the 1996, 1997, and 1999 experiments have led to many results, including the discovery and characterization of a large (> 25%) sonde-to-sonde variability in the water vapor profiles from Vaisala RS-80H radiosondes that acts like a height-independent calibration factor error. However, the microwave observations provide a stable reference that can be used to remove a large part of the sonde-to-sonde calibration variability. In situ capacitive water vapor sensors demonstrated agreement within 2% of chilled-mirror hygrometers at the surface and on an instrumented tower. Water vapor profiles retrieved from two Raman lidars, which have both been calibrated to the ARM microwave radiometer, showed agreement to within 5% for all altitudes below 8 km during two WVIOPs. The mean agreement of the total precipitable water vapor from different techniques has converged significantly from early analysis that originally showed differences up to 15%. Retrievals of total precipitable water vapor (PWV) from the ARM microwave radiometer are now found to be only 3% moister than PWV derived from new GPS results, and about 2% drier than the mean of radiosonde data after a recently defined sonde dry-bias correction is applied. Raman lidar profiles calibrated using tower-mounted chilled-mirror hygrometers confirm the expected sensitivity of microwave radiometer data to water vapor changes, but it is drier than the microwave radiometer (MWR) by 0.95 mm for all PWV amounts. However, observations from different collocated microwave radiometers have shown larger differences than expected and attempts to resolve the remaining inconsistencies (in both calibration and forward modeling) are continuing.

The paper concludes by outlining the objectives of the recent 2000 WVIOP and the ARM–First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment (FIRE) Water Vapor Experiment (AFWEX), the latter of which switched the focus to characterizing upper-tropospheric humidity measurements.

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N. L. Miller, A. W. King, M. A. Miller, E. P. Springer, M. L. Wesely, K. E. Bashford, M. E. Conrad, K. Costigan, P. N. Foster, H. K. Gibbs, J. Jin, J. Klazura, B. M. Lesht, M. V. Machavaram, F. Pan, J. Song, D. Troyan, and R. A. Washington-Allen

A Department of Energy (DOE) multilaboratory Water Cycle Pilot Study (WCPS) investigated components of the local water budget at the Walnut River watershed in Kansas to study the relative importance of various processes and to determine the feasibility of observational water budget closure. An extensive database of local meteorological time series and land surface characteristics was compiled. Numerical simulations of water budget components were generated and, to the extent possible, validated for three nested domains within the Southern Great Plains—the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Cloud Atmospheric Radiation Testbed (CART), the Walnut River watershed (WRW), and the Whitewater watershed (WW), in Kansas.

A 2-month intensive observation period (IOP) was conducted to gather extensive observations relevant to specific details of the water budget, including finescale precipitation, streamflow, and soil moisture measurements that were not made routinely by other programs. Event and seasonal water isotope (d18O, dD) sampling in rainwater, streams, soils, lakes, and wells provided a means of tracing sources and sinks within and external to the WW, WRW, and the ARM CART domains. The WCPS measured changes in the leaf area index for several vegetation types, deep groundwater variations at two wells, and meteorological variables at a number of sites in the WRW. Additional activities of the WCPS include code development toward a regional climate model that includes water isotope processes, soil moisture transect measurements, and water-level measurements in groundwater wells.

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