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- Author or Editor: Bruno Rudolf x
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Abstract
The “satellite-gauge-model” (SGM) technique is described for combining precipitation estimates from microwave satellite data, infrared satellite data, rain gauge analyses, and numerical weather prediction models into improved estimates of global precipitation. Throughout, monthly estimates on a 2.5° × 2.5° lat-long grid are employed. First, a multisatellite product is developed using a combination of low-orbit microwave and geosynchronous-orbit infrared data in the latitude range 40°N–40–S (the adjusted geosynchronous precipitation index) and low-orbit microwave data alone at higher latitudes. Then the rain gauge analysis is brought in, weighting each field by its inverse relative error variance to produce a nearly global, observationally based precipitation estimate. To produce a complete global estimate, the numerical model results are used to fill data voids in the combined satellite-gauge estimate. Our sequential approach to combining estimates allows a user to select the multisatellite estimate, the satellite-gauge estimate, or the full SGM estimate (observationally based estimates plus the model information). The primary limitation in the method is imperfections in the estimation of relative error for the individual fields.
The SGM results for one year of data (July 1987 to June 1988) show important differences from the individual estimates, including model estimates as well as climatological estimates. In general, the SGM results are drier in the subtropics than the model and climatological results, reflecting the relatively dry microwave estimates that dominate the SGM in oceanic regions
Abstract
The “satellite-gauge-model” (SGM) technique is described for combining precipitation estimates from microwave satellite data, infrared satellite data, rain gauge analyses, and numerical weather prediction models into improved estimates of global precipitation. Throughout, monthly estimates on a 2.5° × 2.5° lat-long grid are employed. First, a multisatellite product is developed using a combination of low-orbit microwave and geosynchronous-orbit infrared data in the latitude range 40°N–40–S (the adjusted geosynchronous precipitation index) and low-orbit microwave data alone at higher latitudes. Then the rain gauge analysis is brought in, weighting each field by its inverse relative error variance to produce a nearly global, observationally based precipitation estimate. To produce a complete global estimate, the numerical model results are used to fill data voids in the combined satellite-gauge estimate. Our sequential approach to combining estimates allows a user to select the multisatellite estimate, the satellite-gauge estimate, or the full SGM estimate (observationally based estimates plus the model information). The primary limitation in the method is imperfections in the estimation of relative error for the individual fields.
The SGM results for one year of data (July 1987 to June 1988) show important differences from the individual estimates, including model estimates as well as climatological estimates. In general, the SGM results are drier in the subtropics than the model and climatological results, reflecting the relatively dry microwave estimates that dominate the SGM in oceanic regions
Abstract
Measurements of the horizontal and vertical wind component by a crosswind scintillometer during foehn, the chinooklike downslope windstorm in the Alps, are presented. Because of the sparsity of vertical velocity measurements in the immediate vicinity, the scintillometer calibration is checked mainly with horizontal wind measurements. Then it is assumed that the calibration is the same for both components. The concept was tested during the Mesoscale Alpine Programme field campaign in the autumn of 1999, during which two scintillometers were deployed. Strong, long-lasting, quasi-stationary downward motions on the order of 5 m s−1 and horizontal wind speeds of over 30 m s−1 were detected during strong foehn phases within the valley. Aircraft measurements of various transects near the light paths are compared with two crosswind evaluation techniques. One of them, the slope method, tends to overestimate the actual wind speed by about 20%, whereas the peak technique gives values that are about 10% too low for high wind speeds. The peak method also fails to measure meaningful vertical crosswind speeds. The scintillometer data of one particular foehn storm are compared with nearby Doppler lidar data. The agreement of the horizontal measurements is reasonable. Discrepancies are attributed to topographic and dynamic effects that cause significant spatial inhomogeneities in the wind field. The applicability of continuous scintillometer vertical crosswind measurements in mountainous terrain is demonstrated.
Abstract
Measurements of the horizontal and vertical wind component by a crosswind scintillometer during foehn, the chinooklike downslope windstorm in the Alps, are presented. Because of the sparsity of vertical velocity measurements in the immediate vicinity, the scintillometer calibration is checked mainly with horizontal wind measurements. Then it is assumed that the calibration is the same for both components. The concept was tested during the Mesoscale Alpine Programme field campaign in the autumn of 1999, during which two scintillometers were deployed. Strong, long-lasting, quasi-stationary downward motions on the order of 5 m s−1 and horizontal wind speeds of over 30 m s−1 were detected during strong foehn phases within the valley. Aircraft measurements of various transects near the light paths are compared with two crosswind evaluation techniques. One of them, the slope method, tends to overestimate the actual wind speed by about 20%, whereas the peak technique gives values that are about 10% too low for high wind speeds. The peak method also fails to measure meaningful vertical crosswind speeds. The scintillometer data of one particular foehn storm are compared with nearby Doppler lidar data. The agreement of the horizontal measurements is reasonable. Discrepancies are attributed to topographic and dynamic effects that cause significant spatial inhomogeneities in the wind field. The applicability of continuous scintillometer vertical crosswind measurements in mountainous terrain is demonstrated.
The Global Precipitation Climatology Project (GPCP) has released the GPCP Version 1 Combined Precipitation Data Set, a global, monthly precipitation dataset covering the period July 1987 through December 1995. The primary product in the dataset is a merged analysis incorporating precipitation estimates from low-orbit-satellite microwave data, geosynchronous-orbit-satellite infrared data, and rain gauge observations. The dataset also contains the individual input fields, a combination of the microwave and infrared satellite estimates, and error estimates for each field. The data are provided on 2.5° × 2.5° latitude-longitude global grids. Preliminary analyses show general agreement with prior studies of global precipitation and extends prior studies of El Nino-Southern Oscillation precipitation patterns. At the regional scale there are systematic differences with standard climatologies.
The Global Precipitation Climatology Project (GPCP) has released the GPCP Version 1 Combined Precipitation Data Set, a global, monthly precipitation dataset covering the period July 1987 through December 1995. The primary product in the dataset is a merged analysis incorporating precipitation estimates from low-orbit-satellite microwave data, geosynchronous-orbit-satellite infrared data, and rain gauge observations. The dataset also contains the individual input fields, a combination of the microwave and infrared satellite estimates, and error estimates for each field. The data are provided on 2.5° × 2.5° latitude-longitude global grids. Preliminary analyses show general agreement with prior studies of global precipitation and extends prior studies of El Nino-Southern Oscillation precipitation patterns. At the regional scale there are systematic differences with standard climatologies.
Abstract
The Global Precipitation Climatology Project (GPCP) Version-2 Monthly Precipitation Analysis is described. This globally complete, monthly analysis of surface precipitation at 2.5° latitude × 2.5° longitude resolution is available from January 1979 to the present. It is a merged analysis that incorporates precipitation estimates from low-orbit satellite microwave data, geosynchronous-orbit satellite infrared data, and surface rain gauge observations. The merging approach utilizes the higher accuracy of the low-orbit microwave observations to calibrate, or adjust, the more frequent geosynchronous infrared observations. The dataset is extended back into the premicrowave era (before mid-1987) by using infrared-only observations calibrated to the microwave-based analysis of the later years. The combined satellite-based product is adjusted by the rain gauge analysis. The dataset archive also contains the individual input fields, a combined satellite estimate, and error estimates for each field. This monthly analysis is the foundation for the GPCP suite of products, including those at finer temporal resolution. The 23-yr GPCP climatology is characterized, along with time and space variations of precipitation.
Abstract
The Global Precipitation Climatology Project (GPCP) Version-2 Monthly Precipitation Analysis is described. This globally complete, monthly analysis of surface precipitation at 2.5° latitude × 2.5° longitude resolution is available from January 1979 to the present. It is a merged analysis that incorporates precipitation estimates from low-orbit satellite microwave data, geosynchronous-orbit satellite infrared data, and surface rain gauge observations. The merging approach utilizes the higher accuracy of the low-orbit microwave observations to calibrate, or adjust, the more frequent geosynchronous infrared observations. The dataset is extended back into the premicrowave era (before mid-1987) by using infrared-only observations calibrated to the microwave-based analysis of the later years. The combined satellite-based product is adjusted by the rain gauge analysis. The dataset archive also contains the individual input fields, a combined satellite estimate, and error estimates for each field. This monthly analysis is the foundation for the GPCP suite of products, including those at finer temporal resolution. The 23-yr GPCP climatology is characterized, along with time and space variations of precipitation.
