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Abstract
A mosaic-type parameterization of subgrid-scale topography and land use () is applied for a high-resolution regional climate simulation over the Alpine region with a regional climate model (RegCM3). The model coarse-gridcell size in the control simulation is 15 km while the subgridcell size is 3 km. The parameterization requires disaggregation of atmospheric variables from the coarse grid to the subgrid and aggregation of surface fluxes from the subgrid to the coarse grid. Two 10-yr simulations (1983–92) are intercompared, one without (CONT) and one with (SUB) the subgrid scheme. The authors first validate the CONT simulation, showing that it produces good quality temperature and precipitation statistics, showing in particular a good performance compared to previous runs of this region. The subgrid scheme produces much finer detail of temperature and snow distribution following the topographic disaggregation. It also tends to form and melt snow more accurately in response to the heterogeneous characteristics of topography. In particular, validation against station observations shows that the SUB simulation improves the model simulation of the surface hydrologic cycle, in particular snow and runoff, especially at high-elevation sites. Finally, two experiments explore the model sensitivity to different subgrid disaggregation assumptions, namely, the temperature lapse rate and an empirical elevation-based disaggregation of precipitation.
Abstract
A mosaic-type parameterization of subgrid-scale topography and land use () is applied for a high-resolution regional climate simulation over the Alpine region with a regional climate model (RegCM3). The model coarse-gridcell size in the control simulation is 15 km while the subgridcell size is 3 km. The parameterization requires disaggregation of atmospheric variables from the coarse grid to the subgrid and aggregation of surface fluxes from the subgrid to the coarse grid. Two 10-yr simulations (1983–92) are intercompared, one without (CONT) and one with (SUB) the subgrid scheme. The authors first validate the CONT simulation, showing that it produces good quality temperature and precipitation statistics, showing in particular a good performance compared to previous runs of this region. The subgrid scheme produces much finer detail of temperature and snow distribution following the topographic disaggregation. It also tends to form and melt snow more accurately in response to the heterogeneous characteristics of topography. In particular, validation against station observations shows that the SUB simulation improves the model simulation of the surface hydrologic cycle, in particular snow and runoff, especially at high-elevation sites. Finally, two experiments explore the model sensitivity to different subgrid disaggregation assumptions, namely, the temperature lapse rate and an empirical elevation-based disaggregation of precipitation.
Abstract
The operational algorithm for rainfall retrieval from the Tropical Rainfall Measuring Mission (TRMM) precipitation radar data requires a measurement of the path-integrated attenuation (PIA) as a constraint. This constraint is derived via the surface reference technique, whereby a measurement of the ocean surface in a raining area is compared with the ocean surface backscatter in a neighboring clear area. This method assumes that the surface backscatter difference is due only to the presence of rain, although variation in surface winds could also cause differences in the reference and rain measurements. An alternative surface reference method is to use a measurement of the surface winds and a backscatter model to predict the rain-free, or reference, cross section. Such an approach is developed here for airborne Doppler radar measurements in hurricanes. This approach provides an independent measurement of the reference backscatter, which is compared with the standard clear-air reference. The mean difference between the standard and Doppler-derived PIA is less than or equal to 1 dB; the rms difference is in the range 0.9–2.6 dB. In deriving the model function for backscatter estimation from wind measurements, the authors also find that the dependence of ocean backscatter on wind appears to saturate at high wind speeds at 25° incidence.
Abstract
The operational algorithm for rainfall retrieval from the Tropical Rainfall Measuring Mission (TRMM) precipitation radar data requires a measurement of the path-integrated attenuation (PIA) as a constraint. This constraint is derived via the surface reference technique, whereby a measurement of the ocean surface in a raining area is compared with the ocean surface backscatter in a neighboring clear area. This method assumes that the surface backscatter difference is due only to the presence of rain, although variation in surface winds could also cause differences in the reference and rain measurements. An alternative surface reference method is to use a measurement of the surface winds and a backscatter model to predict the rain-free, or reference, cross section. Such an approach is developed here for airborne Doppler radar measurements in hurricanes. This approach provides an independent measurement of the reference backscatter, which is compared with the standard clear-air reference. The mean difference between the standard and Doppler-derived PIA is less than or equal to 1 dB; the rms difference is in the range 0.9–2.6 dB. In deriving the model function for backscatter estimation from wind measurements, the authors also find that the dependence of ocean backscatter on wind appears to saturate at high wind speeds at 25° incidence.
Abstract
The first spaceborne weather radar is the precipitation radar (PR) on the Tropical Rainfall Measuring Mission (TRMM), which was launched in 1997. As part of the TRMM calibration and validation effort, an airborne rain-mapping radar (ARMAR) was used to make underflights of TRMM during the B portion of the Texas and Florida Underflights (TEFLUN-B) and the third Convection and Moisture Experiment (CAMEX-3) in 1998 and the Kwajalein Experiment (KWAJEX) in 1999. The TRMM PR and ARMAR both operate at 14 GHz, and both instruments use a downward-looking, cross-track scanning geometry, which allows direct comparison of data. Nearly simultaneous PR and ARMAR data were acquired in seven separate cases. These data are compared to examine the effects of larger resolution volume and lower sensitivity in the PR data relative to ARMAR. The PR and ARMAR data show similar structures, although the PR data tend to have lower maximum reflectivities and path attenuations because of nonuniform beam-filling effects. Nonuniform beam filling can also cause a bias in the observed path attenuation relative to that corresponding to the beam-averaged rain rate. The PR rain-type classification is usually consistent with the ARMAR data.
Abstract
The first spaceborne weather radar is the precipitation radar (PR) on the Tropical Rainfall Measuring Mission (TRMM), which was launched in 1997. As part of the TRMM calibration and validation effort, an airborne rain-mapping radar (ARMAR) was used to make underflights of TRMM during the B portion of the Texas and Florida Underflights (TEFLUN-B) and the third Convection and Moisture Experiment (CAMEX-3) in 1998 and the Kwajalein Experiment (KWAJEX) in 1999. The TRMM PR and ARMAR both operate at 14 GHz, and both instruments use a downward-looking, cross-track scanning geometry, which allows direct comparison of data. Nearly simultaneous PR and ARMAR data were acquired in seven separate cases. These data are compared to examine the effects of larger resolution volume and lower sensitivity in the PR data relative to ARMAR. The PR and ARMAR data show similar structures, although the PR data tend to have lower maximum reflectivities and path attenuations because of nonuniform beam-filling effects. Nonuniform beam filling can also cause a bias in the observed path attenuation relative to that corresponding to the beam-averaged rain rate. The PR rain-type classification is usually consistent with the ARMAR data.
Abstract
Localized Aviation MOS Program (LAMP) forecasts of ceiling height, visibility, wind, and other weather elements of interest to the aviation community have been produced and put into the National Digital Guidance Database (NDGD) since 2006. The High Resolution Rapid Refresh (HRRR) model is now producing explicit forecasts of ceiling height and visibility computed by algorithms based on variables directly forecasted by the HRRR. The Meteorological Development Laboratory has improved the LAMP ceiling and visibility forecasts by combining these two sources of information into a LAMP–HRRR MELD. The new forecasts show improvement over the original LAMP and particularly over the HRRR and persistence in terms of bias, threat score, and the Gerrity score. This paper explains how the MELD is produced and shows selected verification and example forecasts. A new guidance product based on this work will be made available to partners and customers.
Abstract
Localized Aviation MOS Program (LAMP) forecasts of ceiling height, visibility, wind, and other weather elements of interest to the aviation community have been produced and put into the National Digital Guidance Database (NDGD) since 2006. The High Resolution Rapid Refresh (HRRR) model is now producing explicit forecasts of ceiling height and visibility computed by algorithms based on variables directly forecasted by the HRRR. The Meteorological Development Laboratory has improved the LAMP ceiling and visibility forecasts by combining these two sources of information into a LAMP–HRRR MELD. The new forecasts show improvement over the original LAMP and particularly over the HRRR and persistence in terms of bias, threat score, and the Gerrity score. This paper explains how the MELD is produced and shows selected verification and example forecasts. A new guidance product based on this work will be made available to partners and customers.
Abstract
The potential usefulness of spaceborne Doppler radar as a tropical cyclone observing tool is assessed by conducting a high-resolution simulation of an intense hurricane and generating synthetic observations of reflectivity and radial velocity. The ground-based velocity track display (GBVTD) technique is used to process the radial velocity observations and generate retrievals of meteorologically relevant metrics such as the maximum wind (MW), radius of maximum wind (RMW), and radius of 64-kt wind (R64). Results indicate that the performance of the retrieved metrics compares favorably with the current state-of-the-art satellite methods for intensity estimation and somewhat better than current methods for structure (i.e., wind radii).
Abstract
The potential usefulness of spaceborne Doppler radar as a tropical cyclone observing tool is assessed by conducting a high-resolution simulation of an intense hurricane and generating synthetic observations of reflectivity and radial velocity. The ground-based velocity track display (GBVTD) technique is used to process the radial velocity observations and generate retrievals of meteorologically relevant metrics such as the maximum wind (MW), radius of maximum wind (RMW), and radius of 64-kt wind (R64). Results indicate that the performance of the retrieved metrics compares favorably with the current state-of-the-art satellite methods for intensity estimation and somewhat better than current methods for structure (i.e., wind radii).
Abstract
A new airborne rain-mapping radar (ARMAR) has been developed by NASA and the Jet Propulsion Laboratory for operation on the NASA Ames DC-8 aircraft. The radar operates at 13.8 GHz, the frequency to be used by the radar on the Tropical Rainfall Measuring Mission (TRMM). ARMAR simulates the TRMM radar geometry by looking downward and scanning its antenna in the cross-track direction. This basic compatibility between ARMAR and TRMM allows ARMAR to provide information useful for the TRMM radar design, for rain retrieval algorithm development, and for postlaunch calibration. ARMAR has additional capabilities, including multiple polarization, Doppler velocity measurement, and a radiometer channel for brightness temperature measurement. The system has been tested in both ground-based and airborne configurations. This paper describes the design of the system and shows results of field tests.
Abstract
A new airborne rain-mapping radar (ARMAR) has been developed by NASA and the Jet Propulsion Laboratory for operation on the NASA Ames DC-8 aircraft. The radar operates at 13.8 GHz, the frequency to be used by the radar on the Tropical Rainfall Measuring Mission (TRMM). ARMAR simulates the TRMM radar geometry by looking downward and scanning its antenna in the cross-track direction. This basic compatibility between ARMAR and TRMM allows ARMAR to provide information useful for the TRMM radar design, for rain retrieval algorithm development, and for postlaunch calibration. ARMAR has additional capabilities, including multiple polarization, Doppler velocity measurement, and a radiometer channel for brightness temperature measurement. The system has been tested in both ground-based and airborne configurations. This paper describes the design of the system and shows results of field tests.
Abstract
Several algorithms to calculate a rain-rate profile from a single-frequency air- or spaceborne radar backscatter profile and a given path-integrated attenuation have been proposed. The accuracy of any such algorithm is limited by the ambiguities between the (multiple) exact solutions, which depend on the variability of the parameters in the Z–R and k–R relations used. In this study, coupled Z–R and k–R relations are derived based on the drop size distribution. It is then shown that, because of the coupling, the relative difference between the multiple mutually ambiguous rain-rate profiles solving the problem must remain acceptably low, provided the available path-integrated attenuation value is known to within 0.5 dB.
Abstract
Several algorithms to calculate a rain-rate profile from a single-frequency air- or spaceborne radar backscatter profile and a given path-integrated attenuation have been proposed. The accuracy of any such algorithm is limited by the ambiguities between the (multiple) exact solutions, which depend on the variability of the parameters in the Z–R and k–R relations used. In this study, coupled Z–R and k–R relations are derived based on the drop size distribution. It is then shown that, because of the coupling, the relative difference between the multiple mutually ambiguous rain-rate profiles solving the problem must remain acceptably low, provided the available path-integrated attenuation value is known to within 0.5 dB.
Abstract
Because of their dependence on water, natural and human systems are highly sensitive to changes in the hydrologic cycle. The authors introduce a new measure of hydroclimatic intensity (HY-INT), which integrates metrics of precipitation intensity and dry spell length, viewing the response of these two metrics to global warming as deeply interconnected. Using a suite of global and regional climate model experiments, it is found that increasing HY-INT is a consistent and ubiquitous signature of twenty-first-century, greenhouse gas–induced global warming. Depending on the region, the increase in HY-INT is due to an increase in precipitation intensity, dry spell length, or both. Late twentieth-century observations also exhibit dominant positive HY-INT trends, providing a hydroclimatic signature of late twentieth-century warming. The authors find that increasing HY-INT is physically consistent with the response of both precipitation intensity and dry spell length to global warming. Precipitation intensity increases because of increased atmospheric water holding capacity. However, increases in mean precipitation are tied to increases in surface evaporation rates, which are lower than for atmospheric moisture. This leads to a reduction in the number of wet days and an increase in dry spell length. This analysis identifies increasing hydroclimatic intensity as a robust integrated response to global warming, implying increasing risks for systems that are sensitive to wet and dry extremes and providing a potential target for detection and attribution of hydroclimatic changes.
Abstract
Because of their dependence on water, natural and human systems are highly sensitive to changes in the hydrologic cycle. The authors introduce a new measure of hydroclimatic intensity (HY-INT), which integrates metrics of precipitation intensity and dry spell length, viewing the response of these two metrics to global warming as deeply interconnected. Using a suite of global and regional climate model experiments, it is found that increasing HY-INT is a consistent and ubiquitous signature of twenty-first-century, greenhouse gas–induced global warming. Depending on the region, the increase in HY-INT is due to an increase in precipitation intensity, dry spell length, or both. Late twentieth-century observations also exhibit dominant positive HY-INT trends, providing a hydroclimatic signature of late twentieth-century warming. The authors find that increasing HY-INT is physically consistent with the response of both precipitation intensity and dry spell length to global warming. Precipitation intensity increases because of increased atmospheric water holding capacity. However, increases in mean precipitation are tied to increases in surface evaporation rates, which are lower than for atmospheric moisture. This leads to a reduction in the number of wet days and an increase in dry spell length. This analysis identifies increasing hydroclimatic intensity as a robust integrated response to global warming, implying increasing risks for systems that are sensitive to wet and dry extremes and providing a potential target for detection and attribution of hydroclimatic changes.
Abstract
The Tropical Rainfall Measuring Mission (TRMM) satellite was launched on 27 November 1997, and data from all the instruments first became available approximately 30 days after the launch. Since then, much progress has been made in the calibration of the sensors, the improvement of the rainfall algorithms, and applications of these results to areas such as data assimilation and model initialization. The TRMM Microwave Imager (TMI) calibration has been corrected and verified to account for a small source of radiation leaking into the TMI receiver. The precipitation radar calibration has been adjusted upward slightly (by 0.6 dBZ) to match better the ground reference targets; the visible and infrared sensor calibration remains largely unchanged. Two versions of the TRMM rainfall algorithms are discussed. The at-launch (version 4) algorithms showed differences of 40% when averaged over the global Tropics over 30-day periods. The improvements to the rainfall algorithms that were undertaken after launch are presented, and intercomparisons of these products (version 5) show agreement improving to 24% for global tropical monthly averages. The ground-based radar rainfall product generation is discussed. Quality-control issues have delayed the routine production of these products until the summer of 2000, but comparisons of TRMM products with early versions of the ground validation products as well as with rain gauge network data suggest that uncertainties among the TRMM algorithms are of approximately the same magnitude as differences between TRMM products and ground-based rainfall estimates. The TRMM field experiment program is discussed to describe active areas of measurements and plans to use these data for further algorithm improvements. In addition to the many papers in this special issue, results coming from the analysis of TRMM products to study the diurnal cycle, the climatological description of the vertical profile of precipitation, storm types, and the distribution of shallow convection, as well as advances in data assimilation of moisture and model forecast improvements using TRMM data, are discussed in a companion TRMM special issue in the Journal of Climate (1 December 2000, Vol. 13, No. 23).
Abstract
The Tropical Rainfall Measuring Mission (TRMM) satellite was launched on 27 November 1997, and data from all the instruments first became available approximately 30 days after the launch. Since then, much progress has been made in the calibration of the sensors, the improvement of the rainfall algorithms, and applications of these results to areas such as data assimilation and model initialization. The TRMM Microwave Imager (TMI) calibration has been corrected and verified to account for a small source of radiation leaking into the TMI receiver. The precipitation radar calibration has been adjusted upward slightly (by 0.6 dBZ) to match better the ground reference targets; the visible and infrared sensor calibration remains largely unchanged. Two versions of the TRMM rainfall algorithms are discussed. The at-launch (version 4) algorithms showed differences of 40% when averaged over the global Tropics over 30-day periods. The improvements to the rainfall algorithms that were undertaken after launch are presented, and intercomparisons of these products (version 5) show agreement improving to 24% for global tropical monthly averages. The ground-based radar rainfall product generation is discussed. Quality-control issues have delayed the routine production of these products until the summer of 2000, but comparisons of TRMM products with early versions of the ground validation products as well as with rain gauge network data suggest that uncertainties among the TRMM algorithms are of approximately the same magnitude as differences between TRMM products and ground-based rainfall estimates. The TRMM field experiment program is discussed to describe active areas of measurements and plans to use these data for further algorithm improvements. In addition to the many papers in this special issue, results coming from the analysis of TRMM products to study the diurnal cycle, the climatological description of the vertical profile of precipitation, storm types, and the distribution of shallow convection, as well as advances in data assimilation of moisture and model forecast improvements using TRMM data, are discussed in a companion TRMM special issue in the Journal of Climate (1 December 2000, Vol. 13, No. 23).
