ALBERT

Description: WetNet is an interdisciplinary Earth science data analysis and research project with an emphasis on the study of the global hydrological cycle. The project goals are to facilitate scientific discussion, collaboration, and interaction among a selected group of investigators by providing data access and data analysis software on a personal computer. The WetNet system fulfills some of the functionality of a prototype Product Generation System (PGS), Data Archive and Distribution System (DADS), and Information Management System for the Distributed Active Archive Center. The PGS functionality is satisfied in WetNet by processing the Special Sensor Microwave/Imager (SSM/I) data into a standard format (McIDAS) data sets and generating geophysical parameter Level II browse data sets. The DADS functionality is fulfilled when the data sets are archived on magneto optical cartridges and distributed to the WetNet investigators. The WetNet data sets on the magneto optical cartridges contain the complete WetNet processing, catalogue, and menu software in addition to SSM/I orbit data for the respective two week time period.

Description: Consideration is given to the use of the Defense Meteorological Satellite Program's Special Sensor Microwave/Imager (SSM/I) to identify precipitation in warm and cold land and ocean environments. It is shown that the polarization diversity of the SSM/I operating at 85.5 GHz makes it possible to discriminate between low brightness temperatures due to surface water bodies and those due to precipitation. The theoretical sensitivity of SSM/I between 19.35 and 8.5. GHz and the polarization correction for water surfaces and the effects of cloud water are discussed. Examples are presented of observational studies using SSM/I for the delineation of precipitation over land and oceans.

Description: During the period June to July 1986, NASA conducted the Satellite Precipitation and Cloud Experiment (SPACE) in the central Tennessee, northern Alabama, and northeastern Mississippi area. In addition to SPACE, the Microburst and Severe Thunderstorm (MIST) Program, sponsored by the National Science Foundation, and the FAA-Lincoln Laboratory Operational Weather Study (FLOWS) sponsored by the Federal Aviation Administration, operated concurrently under the acronym of COHMEX (Cooperative Huntsville Meteorological Experiment). The COHMEX field program incorporated measurements from remote sensors flown on high altitude aircraft (ER-2 and U-2), Doppler and conventional radars, rawinsondes, satellites, cloud physics research aircraft, and various surface observational systems.

Description: Thermal remote sensing can provide environmental measuring tools with capabilities for measuring ecosystem development and integrity. Recent advances in applying principles of nonequilibrium thermodynamics to ecology provide fundamental insights into energy partitioning in ecosystems. Ecosystems are nonequilibrium systems, open to material and energy flows, which grow and develop structures and processes to increase energy degradation. More developed terrestrial ecosystems will be more effective at dissipating the solar gradient (degrading its energy content). This can be measured by the effective surface temperature of the ecosystem on a landscape scale. A series of airborne thermal infrared multispectral scanner data were collected from several forested ecosystems ranging from a western US douglas-fir forest to a tropical rain forest in Costa Rica. Also measured were agriculture systems. These data were used to develop measures of ecosystem development and integrity based on surface temperature.

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: Between 1973 and 1992, an average of 20 ha of forest was lost each day to urban expansion of Atlanta, Georgia. Urban surfaces have very different thermal properties than natural surfaces-storing solar energy throughout the day and continuing to release it as sensible heat well after sunset. The resulting heat island effect serves as catalysts for chemical reactions from vehicular exhaust and industrialization leading to a deterioration in air quality. In this study, high spatial resolution multispectral remote sensing data has been used to characterize the type, thermal properties, and distribution of land surface materials throughout the Atlanta metropolitan area. Ten-meter data were acquired with the Advanced Thermal and Land Applications Sensor (ATLAS) on May 11 and 12, 1997. ATLAS is a 15-channel multispectral scanner that incorporates the Landsat TM bands with additional bands in the middle reflective infrared and thermal infrared range. The high spatial resolution permitted discrimination of discrete surface types (e.g., concrete, asphalt), individual structures (e.g., buildings, houses) and their associated thermal characteristics. There is a strong temperature contrast between vegetation and anthropomorphic features. Vegetation has a modal temperature at about 20 C, whereas asphalt shingles, pavement, and buildings have a modal temperature of about 39 C. Broad-leaf vegetation classes are indistinguishable on a thermal basis alone. There is slightly more variability (+/-5 C) among the urban surfaces. Grasses, mixed vegetation and mixed urban surfaces are intermediate in temperature and are characterized by broader temperature distributions with modes of about 29 C. Thermal maps serve as a basis for understanding the distribution of "hotspots", i.e., how landscape features and urban fabric contribute the most heat to the lower atmosphere.

Description: We constructed and analyzed wet and dry soil moisture composites for the mid-latitude GCIP region of the central US using long climate model simulations made with the NCAR CCM3 and reanalysis products from NCEP. Using the diagnostic composites as a guide, we have completed a series of predictability experiments in which we imposed soil water initial conditions in CCM3 for the GCIP region for June 1 from anomalously wet and dry years, with atmospheric initial conditions taken from June 1 of a year with 'near-normal' soil water, and initial soil water from the near-normal year and atmospheric initial conditions from the wet and dry years. Preliminary results indicate that the initial state of the atmosphere is more important than the initial state of soil water determining the subsequent late spring and summer evolution of sod water over the GCIP region. Surprisingly, neither the composites or the predictability experiments yielded a strong influence of soil moisture on the atmosphere. To explore this further, we have made runs with extreme dry soil moisture initial anomalies imposed over the GCIP region (the soil close to being completely dry). These runs did yield a very strong effect on the atmosphere that persisted for at least three months. We conclude that the magnitude of the initial soil moisture anomaly is crucial, at least in CCM3, and are currently investigating whether a threshold exists, below which little impact is seen. In a complementary study, we compared the impact of the initial condition of snow cover versus the initial atmospheric state over the western US (corresponding to the westward extension of the GAPP program follow-on to GCIP). In this case, the initial prescription of snow cover is far more important than the initial atmospheric state in determining the subsequent evolution of snow cover. We are currently working to understand the very different soil water and snow cover results.

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 die 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-H effort is also examined. This integration is run with specified SSTs, but with no data assimilation. Our analysis focuses on two aspects of inter-annual variability. 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 beat 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 in precipitation than do the satellite observations.

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 Earth Science and Applications Division of the NASA Marshall Space Flight Center has been chartered to conduct research, and to develop and use space technology to gain a basic understanding of the earth processes with emphasis on atmospheric processes. An integral part of the research and development efforts has been the Man computer Interactive Data Access System (McIDAS). The McIDAS computer system has permitted integration of data from satellites, aircraft remote sensors, ground based meteorological data sources, and modeled atmospheric radiances. The result has been an increase in knowlege of mesoscale atmospheric processes and has enabled researchers to recommend improvements and suggestions for planned future remote sensing instruments.