Frank J. LaFontaine

High-resolution imaging of rain systems with the advanced microwave precipitation radiometer

Abstract An Advanced Microwave Precipitation Radiometer (AMPR) has been developed and flown in the NASA ER-2 high-altitude aircraft for imaging various atmospheric and surface processes, primarily the internal structure of rain clouds. The AMPR is a scanning four-frequency total power microwave radiometer that is externally calibrated with high-emissivity warm and cold loads. Separate antenna systems allow the sampling of the 10.7- and 19.35-GHz channels at the same spatial resolution, while the 37.1- and 85.5-GHz channels utilize the same multifrequency feedhorn as the 19.35-GHz channel. Spatial resolutions from an aircraft altitude of 20-km range from 0.6 km at 85.5 GHz to 2.8 km at 19.35 and 10.7 GHz. All channels are sampled every 0.6 km in both along-track and cross-track directions, leading to a contiguous sampling pattern ofthe 85.5-GHz 3-dB beamwidth footprints, 2.3 × oversampling of the 37.1-GHz data, and 4.4 × oversampling of the 19.35- and 10.7-GHz data. Radiometer temperature sensitivities ran...

Spatial and Temporal Varying Thresholds for Cloud Detection in GOES Imagery

A new cloud detection technique has been developed and applied to GOES-12 Imager data. The bispectral composite threshold (BCT) technique uses only the 11- and 3.9- channels, and composite imagery generated from these channels, in a four-step cloud detection procedure to produce a binary cloud mask at single-pixel resolution. An innovative aspect of this algorithm is the use of 20-day composites of the 11- and the 11-3.9- channel difference imagery to represent spatially and temporally varying clear-sky thresholds for the bispectral cloud tests. The BCT cloud detection technique has been validated against a ldquotruthrdquo data set generated by the manual determination of the sky conditions from available satellite imagery for four seasons during 2003-2004. The day-and-night algorithm has been shown to determine the correct sky conditions 87.6% of the time (on average) over the eastern two-thirds of the U.S. and surroundings oceans. The incorrectly determined conditions arose from missing clouds 8.9% of the time or from overdetermining clouds 3.5% of the time. Nearly 82% of the misses came in the presence of low clouds. Only small variations in algorithm performance occurred between day-night, land-ocean, and between seasons. The algorithm performed best in the warmer seasons (90.9% correct during the summer versus 81.8% correct in the winter season) and during the day, when the solar illumination provides enhanced surface atmospheric cloud contrast in the infrared channels, and least well during the winter season. The algorithm was found to slightly underdetermine clouds at night and during times of low sun angle and tends to be cloud conservative during the day, particularly in the summertime.

An Assessment of the First- and Second-Generation Navy Operational Precipitation Retrieval Algorithms

Rainfall estimates produced from the Special Sensor Microwave/Imager (SSM/I) data have been utilized operationally by the United States Navy since the launch of the first SSM/I sensor in June of 1987. The navy initially contracted Hughes Aircraft Company to develop a rainfall-retrieval algorithm prior to the launch of SSM/I. This first-generation operational navy rainfall retrieval algorithm, referred to as the D-Matrix algorithm, was used until the development of the second-generation algorithm by the SSM/I Calibration/Validation team, which has subsequently been replaced by a third-generation algorithm developed by the National Oceanic and Atmospheric Administration/National Environmental Satellite, Data and Information System. Results from both the D-Matrix and Cal/Val algorithms have been included in a total of five algorithm intercomparison projects conducted through the Global Precipitation Climatology Project and WetNet. A comprehensive summary of both quantitative and qualitative results from these intercomparisons is given detailing many of the strengths and weaknesses of the algorithms. Based on these results, the D-Matrix algorithm was found to produce excessively large estimates over land and to poorly represent the spatial structure of rainfall systems, especially at higher latitudes. The Cal/Val algorithm produces more realistic structure within storm systems but appears to overestimate the region of precipitation for many systems and significantly underestimates regions of intense rainfall. While the Cal/Val algorithm appears to provide better instantaneous rainfall estimates in the Tropics, the D-Matrix algorithm provides reasonable time-averaged results for monthly or longer periods.

Classification of tropical oceanic precipitation using high-altitude aircraft microwave and electric field measurements

Abstract During the 1998 and 2001 hurricane seasons of the western Atlantic Ocean and Gulf of Mexico, the Advanced Microwave Precipitation Radiometer (AMPR), the ER-2 Doppler (EDOP) radar, and the Lightning Instrument Package (LIP) were flown aboard the NASA ER-2 high-altitude aircraft as part of the Third Convection and Moisture Experiment (CAMEX-3) and the Fourth Convection and Moisture Experiment (CAMEX-4). Several hurricanes, tropical storms, and other precipitation systems were sampled during these experiments. An oceanic rainfall screening technique has been developed using AMPR passive microwave observations of these systems collected at frequencies of 10.7, 19.35, 37.1, and 85.5 GHz. This technique combines the information content of the four AMPR frequencies regarding the gross vertical structure of hydrometeors into an intuitive and easily executable precipitation mapping format. The results have been verified using vertical profiles of EDOP reflectivity and lower-altitude horizontal reflectivit...

A Real-Time MODIS Vegetation Product for Land Surface and Numerical Weather Prediction Models

A technique is presented to produce real-time, daily vegetation composites at 0.01 ° resolution ( ~ 1 km) over the Conterminous United States (CONUS) for use in the NASA Land Information System (LIS) and weather prediction models. Green vegetation fraction (GVF) is derived from direct-broadcast swaths of normalized difference vegetation index from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the NASA Earth Observing System satellites. The real-time data and increased resolution compared to the 0.144 ° ( ~ 16 km) resolution monthly GVF climatology in community models result in an improved representation of vegetation in high-resolution models, especially in complex terrain. The MODIS GVF fields show seasonal variations that are similar to the community model climatology, and respond realistically to temperature and precipitation anomalies. The wet spring and summer 2010 over the U.S. Plains led to higher regional GVF than in the climatology. The GVF substantially decreased over the U.S. Southern Plains from 2010 to 2011, consistent with the transition to extreme drought in summer 2011. LIS simulations depict substantial sensitivity to the MODIS GVF, with regional changes in heat fluxes around 100 Wm-2 over the northern U.S. in June 2010. CONUS LIS simulations during the 2010 warm season indicate that the larger MODIS GVF in the western U.S. led to higher latent heat fluxes and initially lower sensible heat fluxes, with a net drying effect on the soil. With time, the drier soil eventually lead to higher mean sensible heat fluxes such that the total surface energy output increased by late summer 2010 over the western U.S. A sensitivity simulation of a severe weather event using real-time MODIS GVF data results in systematic changes to low-level temperature, moisture, and instability fields, and improves the evolution of simulated precipitation.

Tropical Oceanic Precipitation Changes after the 1991 Pinatubo Eruption

Abstract Passive microwave channels like those flown on the Special Sensor Microwave Imager (SSM/I) contain two primary types of information on oceanic precipitation: condensate below the freezing level and precipitation-size condensate above the freezing level. The authors explore the question of whether these two separate pieces of information might contain insight into climate processes during a perturbation in the climate system. In particular, the relative fluctuations of rain and ice signals could be related to precipitation efficiency, an important determinant of the equilibrium climate, and thus a potential feedback mechanism in climate change. As an example of this potential application, SSM/I-derived liquid and frozen precipitation signals are used to infer changes in tropical oceanic precipitation characteristics during the cool period following the 1991 eruption of Mount Pinatubo. The need for an assessment of the temperature sensitivity of precipitation-retrieval algorithms is also discussed.

Critical Analyses of Data Differences between FNMOC and AFGWC Spawned SSM/I Datasets

Antenna temperatures and the corresponding geolocation data from the five sources of the Special Sensor Microwave/Imager data from the Defense Meteorological Satellite Program F11 satellite have been characterized. Data from the Fleet Numerical Meteorology and Oceanography Center (FNMOC) have been compared with data from other sources to define and document the differences resulting from different processing systems. While all sources used similar methods to calculate antenna temperatures, different calibration averaging techniques and other processing methods yielded temperature differences. Analyses of the geolocation data identified perturbations in the FNMOC and National Environmental Satellite, Data and Information Service data. The effects of the temperature differences were examined by generating rain rates using the Goddard Scattering Algorithm. Differences in the geophysical precipitation products are directly attributable to antenna temperature differences.

Application of Airborne Passive Microwave Observations for Monitoring Inland Flooding Caused by Tropical Cyclones

Abstract Inland flooding from tropical cyclones is a significant factor in storm-related deaths in the United States and other countries, with the majority of tropical cyclone fatalities recorded in the United States resulting from freshwater flooding. Information collected during National Aeronautics and Space Administration (NASA) tropical cyclone field experiments suggests that surface water and flooding can be detected and therefore monitored at a greater spatial resolution by using passive microwave airborne radiometers than by using satellite sensors. The 10.7-GHz frequency of the NASA Advanced Microwave Precipitation Radiometer (AMPR) has demonstrated high-resolution detection of anomalous surface water and flooding in numerous situations. In this study, an analysis of three cases is conducted utilizing satellite and airborne radiometer data. Data from the 1998 Third Convection and Moisture Experiment (CAMEX-3) are utilized to detect surface water during the landfalling Hurricane Georges in both th...