ALBERT

Description: A set of global, monthly rainfall products has been intercompared to understand the quality and utility of the estimates. The products include 25 observational (satellite-based), four model and two climatological products. The results of the intercomparison indicate a very large range (factor of two or three) of values when all products are considered. The range of values is reduced considerably when the set of observational products is limited to those considered quasi-standard. The model products do significantly poorer in the tropics, but are competitive with satellite-based fields in mid-latitudes over land. Over ocean, products are compared to frequency of precipitation from ship observations. The evaluation of the observational products point to merged data products (including rain gauge information) as providing the overall best results.

Description: A technique has been developed for assimilating GOES-derived skin temperature tendencies and insolation into the surface energy budget equation of a mesoscale model so that the simulated rate of temperature change closely agrees with the satellite observations. A critical assumption of the technique is that the availability of moisture (either from the soil or vegetation) is the least known term in the model's surface energy budget. Therefore, the simulated latent heat flux, which is a function of surface moisture availability, is adjusted based upon differences between the modeled and satellite-observed skin temperature tendencies. An advantage of this technique is that satellite temperature tendencies are assimilated in an energetically consistent manner that avoids energy imbalances and surface stability problems that arise from direct assimilation of surface shelter temperatures. The fact that the rate of change of the satellite skin temperature is used rather than the absolute temperature means that sensor calibration is not as critical. The technique has been employed on a semi-operational basis at the GHCC within the PSU/NCAR MM5. Assimilation has been performed on a grid centered over the Southeastern US since November 1998. Results from the past year show that assimilation of the satellite data reduces both the bias and RMSE for simulations of surface air temperature and relative humidity. These findings are based on comparison of assimilation runs with a control using the simple 5-layer soil model available in MM5. A significant development in the past several months was the inclusion of the detailed Oregon State University land surface model (OSU/LSM) as an option within MM5. One of our working hypotheses has been that the assimilation technique, although simple, may provide better short-term forecasts than a detailed LSM that requires significant number initialized parameters. Preliminary results indicate that the assimilation out performs the OSU/LSM as it is incorporated in MM5. Details will be presented at the symposium.

Description: The goals of this study are the evaluation of current fast radiative transfer models (RTMs) and line-by-line (LBL) models. The intercomparison focuses on the modeling of 11 representative sounding channels routinely used at numerical weather prediction centers: 7 HIRS (High-resolution Infrared Sounder) and 4 AMSU (Advanced Microwave Sounding Unit) channels. Interest in this topic was evidenced by the participation of 24 scientists from 16 institutions. An ensemble of 42 diverse atmospheres was used and results compiled for 19 infrared models and 10 microwave models, including several LBL RTMs. For the first time, not only radiances, but also Jacobians (of temperature, water vapor and ozone) were compared to various LBL models for many channels. In the infrared, LBL models typically agree to within 0.05-0.15 K (standard deviation) in terms of top-of-the-atmosphere brightness temperature (BT). Individual differences up to 0.5 K still exist, systematic in some channels, and linked to the type of atmosphere in others. The best fast models emulate LBL BTs to within 0.25 K, but no model achieves this desirable level of success for all channels. The ozone modeling is particularly challenging, In the microwave, fast models generally do quite well against the LBL model to which they were tuned. However significant differences were noted among LBL models, Extending the intercomparison to the Jacobians proved very useful in detecting subtle and more obvious modeling errors. In addition, total and single gas optical depths were calculated, which provided additional insight on the nature of differences. Recommendations for future intercomparisons are suggested.

Description: A set of global, monthly rainfall products has been intercompared to understand the quality and utility of the estimates. The products include 25 observational (satellite-based), four model and two climatological products. The results of the intercomparison indicate a very large range (factor of two or three) of values when all products are considered. The range of values is reduced considerably when the set of observational products is limited to those considered quasi-standard. The model products do significantly poorer in the tropics, but are competitive with satellite-based fields in mid-latitudes over land. Over ocean, products are compared to frequency of precipitation from ship observations. The evaluation of the observational products point to merged data products (including rain gauge information) as providing the overall best results.

Description: The germination of this special Computers & Geosciences (C&G) issue began at the Royal Geographical Society (with the Institute of British Geographers) (RGS-IBG) annual meeting in January 1997 held at the University of Exeter, UK. The snow and cold of the English winter were tempered greatly by warm and cordial discussion of how to stimulate and enhance cooperation on geostatistical and geospatial research in remote sensing 'across the big pond' between UK and US researchers. It was decided that one way forward would be to hold parallel sessions in 1998 on geostatistical and geospatial research in remote sensing at appropriate venues in both the UK and the US. Selected papers given at these sessions would be published as special issues of C&G on the UK side and Photogrammetric Engineering and Remote Sensing (PE&RS) on the US side. These issues would highlight the commonality in research on geostatistical and geospatial research in remote sensing on both sides of the Atlantic Ocean. As a consequence, a session on "Geostatistics and Geospatial Techniques for Remote Sensing of Land Surface Processes" was held at the RGS-IBG annual meeting in Guildford, Surrey, UK in January 1998, organized by the Modeling and Advanced Techniques Special Interest Group (MAT SIG) of the Remote Sensing Society (RSS). A similar session was held at the Association of American Geographers (AAG) annual meeting in Boston, Massachusetts in March 1998, sponsored by the AAG's Remote Sensing Specialty Group (RSSG). The 10 papers that make up this issue of C&G, comprise 7 papers from the UK and 3 papers from the LIS. We are both co-editors of each of the journal special issues, with the lead editor of each journal issue being from their respective side of the Atlantic. The special issue of PE&RS (vol. 65) that constitutes the other half of this co-edited journal series was published in early 1999, comprising 6 papers by US authors. We are indebted to the International Association for Mathematical Geology for allowing us to use C&G as a vehicle to convey how geostatistics and geospatial techniques can be used to analyze remote sensing and other types of spatial data. We see this special issue of C&G. and its complementary issue of PE&RS. as a testament to the vitality and interest in the application of geostatistical and geospatial techniques in remote sensing. We also see these special journal issues as the beginning of a fruitful. and hopefully long-term relationship, between American and British geographers and other researchers interested in geostatistical and geospatial techniques applied to remote sensing and other spatial data.

Description: The coherent Doppler lidar, when operated from an airborne platform, offers a unique measurement capability for study of atmospheric and surface processes and feature. This is especially true for scientific objectives requiring measurements in optically-clear air, where other remote sensing technologies such as Doppler radar are at a disadvantage in terms of spatial resolution and coverage. The atmospheric lidar remote sensing groups of several US institutions, led by Marshall Space Flight Center, have developed an airborne coherent Doppler lidar capable of mapping the wind field and aerosol structure in three dimensions. The instrument consists of about a 1 Joule/pulse (eyesafe) lidar transceiver, telescope, scanner, inertial measurement unit, and operations control system to orchestrate all subsystem functions and tasks. The scanner is capable of directing the expanded lidar beam in a variety of ways, in order to extract vertically resolved wind fields. Horizontal resolution is about 1 km; vertical resolution is even finer. Winds are obtained by measuring backscattered, Doppler-shifted laser radiation from naturally-occurring aerosol particles (on an order of 1 micron in diameter). Measurement coverage depends on aerosol spatial distribution and concentration. Velocity accuracy has been verified to be about 1 m/s. A variety of applications has been demonstrated during the three flight campaigns conducted during 1995-1998. Examples will be shown during the presentation. In 1995, boundary layer winds over the ocean were mapped with unprecedented resolution. In 1996, unique measurements were made of flow over the complex terrain of the Aleutian Islands; interaction of the marine boundary layer jet with the California coastal mountain range; a weak dry line in Texas - New Mexico; an upper tropospheric jet stream; the angular dependence of sea surface scattering; and in-flight radiometric calibration using the surface of White Sands National Monument. In 1998, the first measurements of eyewall and boundary layer winds within a hurricane were made with the airborne Doppler lidar. Potential future applications, and plans for improvements, will also be identified.

Description: Since the beginning of the World Climate Research Program's Global Precipitation Climatology Project (GPCP) satellite remote sensing of precipitation has made dramatic improvements, particularly for tropical regions. Data from microwave and infrared sensors now form the most critical input to precipitation data sets and can be calibrated with surface gauges to so that the strengths of each data source can be maximized in some statistically optimal sense. Recent availability of the TRMM (Tropical Rainfall Measuring Mission) has further aided in narrowing uncertainties in rainfall over the tropics and subtropics. Although climate modeling efforts have long relied on space-based precipitation estimates for validation, we now are in a position to make more quantitative assessments of model performance, particularly in tropical regions. An integration of the CCM3 using observed SSTs as a lower boundary condition is used to examine how well this model responds to ENSO forcing in terms of anomalous precipitation. An integration of the NCEP spectral model used for the Reanalysis-11 effort is also examined. This integration is run with specified SSTs, but no data assimilation. Our analysis focuses on two aspects. First are the spatial anomalies that are indicative of dislocations in Hadley and Walker circulations. Second, we consider the ability of models to replicate observed increases in oceanic precipitation that are noted in satellite observations for large ENSO events. Finally, we consider a slab ocean version of the CCM3 model with prescribed ocean heat transports that mimic upwelling anomalies, but which still allows the surface energy balance to be predicted. This less restrictive experiment is used to understand why model experiments with specified SSTs seem to have noticeably less interannual variability than do the satellite precipitation observations.

Description: The NASA Tropical Rainfall Measuring Mission (TRMM) Observatory made an overpass during the Central Oklahoma tornado outbreak at approximately 04:00 LTC on 4 May, 1999 (23:00 CDT on 3 May). At the time of the TRMM snapshot there were 25 individual storms in Oklahoma that could be identified and cross-correlated between the TRMM measurements and the Twin Lakes (KTLX) NEXRAD radar. Of these, six were significant supercells that could be trended for 30-min prior and subsequent to (1 hr total) the TRMM overpass. Thus, we are able to provide a context for the TRMM snapshot with respect to each individual supercell's recent growth, decay, and severe weather producing history. The most vigorous and electrically active storm at the time of the overpass is the Stroud, OK supercell whose F3 tornado ended only about 10 minutes earlier. Another F3 tornado north of Crescent, OK (- 150 km west of Stroud) is on the ground and a supercell with a developing, yet still weak mesocyclone is just south of the Stroud storm. This latter storm produces an F1 tornado an hour later near Sapulpa, OK. The objective of this study is to provide additional insight into the characteristics of the supercell storms through the unique capabilities and vantagepoint of the TRMM science instruments.

Description: This study compares the lightning locations reported by the National Lightning Detection Network (NLDN) with the lightning locations determined by the Lightning Imaging Sensor (LIS). The NLDN system identifies the rf signature of cloud-to-ground lightning. The LIS data is the top level of a hierarchy of optical data objects. The centroid and timing of each LIS lightning activity center are compared with each flash in a subset of the NLDN long range lightning location data in a portion of the Atlantic Ocean and the Caribbean Sea consisting of those locations more than 625 km from any sensor. This subset is produced by analyzing each reported NLDN location to determine if that location is within the LIS field of view at the time of the reported flash. The Tropical Rainfall Measuring Mission Satellite (TRMM) orbit limits the cross-sensor comparison to tropical and sub-tropical regions. Because the rf-detection system depends on ionospheric propagation conditions, a separate analysis was made for daylight conditions at both source and sensor as well as nighttime at both places. A full year of data is compared to provide an adequate sample of each data set. Confirmation of lightning in the general location of the NLDN report is established when LIS detected one or more centers of lightning activity within a 2 degree radius from the NLDN location.

Description: Airborne lidar systems are used to determine wind velocity and to measure aerosol or cloud backscatter variability. Atmospheric aerosols, being affected by local and regional sources, show tremendous variability. Continuous wave (cw) lidar can obtain detailed aerosol loading with unprecedented high resolution (3 sec) and sensitivity (1 mg/cubic meter) as was done during the 1995 NASA Multi-center Airborne Coherent Atmospheric Wind Sensor (MACAWS) mission over western North America and the Pacific Ocean. Backscatter variability was measured at a 9.1 micron wavelength cw focused CO2 Doppler lidar for approximately 52 flight hours, covering an equivalent horizontal distance of approximately 30,000 km in the troposphere. Some quasi-vertical backscatter profiles were also obtained during various ascents and descents at altitudes that ranged from approximately 0.1 to 12 km. Similarities and differences for aerosol loading over land and ocean were observed. Mid-tropospheric aerosol backscatter background mode was approximately 6 x 10(exp -11)/ms/r, consistent with previous lidar datasets. While these atmospheric measurements were made, the lidar also retrieved a distinct backscatter signal from the Earth's surface from the unfocused part of the focused cw lidar beam during aircraft rolls. Atmospheric backscatter can be highly variable both spatially and temporally, whereas, Earth-surface backscatter is relatively much less variant and can be quite predictable. Therefore, routine atmospheric backscatter measurements by an airborne lidar also give Earth surface backscatter which can allow for investigating the Earth terrain. In the case where the Earth's surface backscatter is coming from a well-known and fairly uniform region, then it can potentially offer lidar calibration opportunities during flight. These Earth surface measurements over varying Californian terrain during the mission were compared with laboratory backscatter measurements using the same lidar of various Earth surfaces giving good agreement, suggesting that the lidar efficiency, and thus a lidar calibration factor for detection, can be estimated fairly well using Earth's surface signal.