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Abstract
Applications of Doppler weather radar data to the analysis of wind fields are reviewed. Radial velocity measurements from a single radar are used to estimate horizontal wind vectors within small azimuthal sectors using two different models. One assumes a uniform wind, the other a linear wind within the sector. Errors in wind estimates owing to gradients of wind are derived using harmonic analysis. The radar data analysis techniques are tested on complex wind patterns which were reconstructed from dual-Doppler radar measurements.
Abstract
Applications of Doppler weather radar data to the analysis of wind fields are reviewed. Radial velocity measurements from a single radar are used to estimate horizontal wind vectors within small azimuthal sectors using two different models. One assumes a uniform wind, the other a linear wind within the sector. Errors in wind estimates owing to gradients of wind are derived using harmonic analysis. The radar data analysis techniques are tested on complex wind patterns which were reconstructed from dual-Doppler radar measurements.
Abstract
An analysis technique to derive wind field parameters from single-Doppler velocity measurements, known as Modified Velocity-Volume Processing (MVVP) is examined from both theoretical and operational perspectives. For this technique, radar data within limited spatial volumes are fit to a model which usually assumes linearity of the Cartesian wind components. The accuracies and limitations of this technique are illustrated with examples from a case study of a severe storm outbreak in central Oklahoma on 17 May 1981. Implications for use of the MVVP in convective storm forecasting are considered.
Abstract
An analysis technique to derive wind field parameters from single-Doppler velocity measurements, known as Modified Velocity-Volume Processing (MVVP) is examined from both theoretical and operational perspectives. For this technique, radar data within limited spatial volumes are fit to a model which usually assumes linearity of the Cartesian wind components. The accuracies and limitations of this technique are illustrated with examples from a case study of a severe storm outbreak in central Oklahoma on 17 May 1981. Implications for use of the MVVP in convective storm forecasting are considered.
Abstract
There are numerous challenges with the forecasting and detection of flash floods, one of the deadliest weather phenomena in the United States. Statistical metrics of flash flood warnings over recent years depict a generally stagnant warning performance, while regional flash flood guidance utilized in warning operations was shown to have low skill scores. The Hydrometeorological Testbed—Hydrology (HMT-Hydro) experiment was created to allow operational forecasters to assess emerging products and techniques designed to improve the prediction and warning of flash flooding. Scientific goals of the HMT-Hydro experiment included the evaluation of gridded products from the Multi-Radar Multi-Sensor (MRMS) and Flooded Locations and Simulated Hydrographs (FLASH) product suites, including the experimental Coupled Routing and Excess Storage (CREST) model, the application of user-defined probabilistic forecasts in experimental flash flood watches and warnings, and the utility of the Hazard Services software interface with flash flood recommenders in real-time experimental warning operations. The HMT-Hydro experiment ran in collaboration with the Flash Flood and Intense Rainfall (FFaIR) experiment at the Weather Prediction Center to simulate the real-time workflow between a national center and a local forecast office, as well as to facilitate discussions on the challenges of short-term flash flood forecasting. Results from the HMT-Hydro experiment highlighted the utility of MRMS and FLASH products in identifying the spatial coverage and magnitude of flash flooding, while evaluating the perception and reliability of probabilistic forecasts in flash flood watches and warnings.
NSSL scientists and NWS forecasters evaluate new tools and techniques through real-time test bed operations for the improvement of flash flood detection and warning operations.
Abstract
There are numerous challenges with the forecasting and detection of flash floods, one of the deadliest weather phenomena in the United States. Statistical metrics of flash flood warnings over recent years depict a generally stagnant warning performance, while regional flash flood guidance utilized in warning operations was shown to have low skill scores. The Hydrometeorological Testbed—Hydrology (HMT-Hydro) experiment was created to allow operational forecasters to assess emerging products and techniques designed to improve the prediction and warning of flash flooding. Scientific goals of the HMT-Hydro experiment included the evaluation of gridded products from the Multi-Radar Multi-Sensor (MRMS) and Flooded Locations and Simulated Hydrographs (FLASH) product suites, including the experimental Coupled Routing and Excess Storage (CREST) model, the application of user-defined probabilistic forecasts in experimental flash flood watches and warnings, and the utility of the Hazard Services software interface with flash flood recommenders in real-time experimental warning operations. The HMT-Hydro experiment ran in collaboration with the Flash Flood and Intense Rainfall (FFaIR) experiment at the Weather Prediction Center to simulate the real-time workflow between a national center and a local forecast office, as well as to facilitate discussions on the challenges of short-term flash flood forecasting. Results from the HMT-Hydro experiment highlighted the utility of MRMS and FLASH products in identifying the spatial coverage and magnitude of flash flooding, while evaluating the perception and reliability of probabilistic forecasts in flash flood watches and warnings.
NSSL scientists and NWS forecasters evaluate new tools and techniques through real-time test bed operations for the improvement of flash flood detection and warning operations.
Abstract
The atmospheric response to Arctic and Antarctic sea ice changes typical of the present day and coming decades is investigated using the Hadley Centre global climate model (HadGEM3). The response is diagnosed from ensemble simulations of the period 1979 to 2009 with observed and perturbed sea ice concentrations. The experimental design allows the impacts of ocean–atmosphere coupling and the background atmospheric state to be assessed. The modeled response can be very different to that inferred from statistical relationships, showing that the response cannot be easily diagnosed from observations. Reduced Arctic sea ice drives a local low pressure response in boreal summer and autumn. Increased Antarctic sea ice drives a poleward shift of the Southern Hemisphere midlatitude jet, especially in the cold season. Coupling enables surface temperature responses to spread to the ocean, amplifying the atmospheric response and revealing additional impacts including warming of the North Atlantic in response to reduced Arctic sea ice, with a northward shift of the Atlantic intertropical convergence zone and increased Sahel rainfall. The background state controls the sign of the North Atlantic Oscillation (NAO) response via the refraction of planetary waves. This could help to resolve differences in previous studies, and potentially provides an “emergent constraint” to narrow the uncertainties in the NAO response, highlighting the need for future multimodel coordinated experiments.
Abstract
The atmospheric response to Arctic and Antarctic sea ice changes typical of the present day and coming decades is investigated using the Hadley Centre global climate model (HadGEM3). The response is diagnosed from ensemble simulations of the period 1979 to 2009 with observed and perturbed sea ice concentrations. The experimental design allows the impacts of ocean–atmosphere coupling and the background atmospheric state to be assessed. The modeled response can be very different to that inferred from statistical relationships, showing that the response cannot be easily diagnosed from observations. Reduced Arctic sea ice drives a local low pressure response in boreal summer and autumn. Increased Antarctic sea ice drives a poleward shift of the Southern Hemisphere midlatitude jet, especially in the cold season. Coupling enables surface temperature responses to spread to the ocean, amplifying the atmospheric response and revealing additional impacts including warming of the North Atlantic in response to reduced Arctic sea ice, with a northward shift of the Atlantic intertropical convergence zone and increased Sahel rainfall. The background state controls the sign of the North Atlantic Oscillation (NAO) response via the refraction of planetary waves. This could help to resolve differences in previous studies, and potentially provides an “emergent constraint” to narrow the uncertainties in the NAO response, highlighting the need for future multimodel coordinated experiments.
Abstract
Complete models of the hydrologic cycle have gained recent attention as research has shown interdependence between the coupled land and energy balance of the subsurface, land surface, and lower atmosphere. PF.WRF is a new model that is a combination of the Weather Research and Forecasting (WRF) atmospheric model and a parallel hydrology model (ParFlow) that fully integrates three-dimensional, variably saturated subsurface flow with overland flow. These models are coupled in an explicit, operator-splitting manner via the Noah land surface model (LSM). Here, the coupled model formulation and equations are presented and a balance of water between the subsurface, land surface, and atmosphere is verified. The improvement in important physical processes afforded by the coupled model using a number of semi-idealized simulations over the Little Washita watershed in the southern Great Plains is demonstrated. These simulations are initialized with a set of offline spinups to achieve a balanced state of initial conditions. To quantify the significance of subsurface physics, compared with other physical processes calculated in WRF, these simulations are carried out with two different surface spinups and three different microphysics parameterizations in WRF. These simulations illustrate enhancements to coupled model physics for two applications: water resources and wind-energy forecasting. For the water resources example, it is demonstrated how PF.WRF simulates explicit rainfall and water storage within the basin and runoff. Then the hydrographs predicted by different microphysics schemes within WRF are compared. Because soil moisture is expected to impact boundary layer winds, the applicability of the model to wind-energy applications is demonstrated by using PF.WRF and WRF simulations to provide estimates of wind and wind shear that are useful indicators of wind-power output.
Abstract
Complete models of the hydrologic cycle have gained recent attention as research has shown interdependence between the coupled land and energy balance of the subsurface, land surface, and lower atmosphere. PF.WRF is a new model that is a combination of the Weather Research and Forecasting (WRF) atmospheric model and a parallel hydrology model (ParFlow) that fully integrates three-dimensional, variably saturated subsurface flow with overland flow. These models are coupled in an explicit, operator-splitting manner via the Noah land surface model (LSM). Here, the coupled model formulation and equations are presented and a balance of water between the subsurface, land surface, and atmosphere is verified. The improvement in important physical processes afforded by the coupled model using a number of semi-idealized simulations over the Little Washita watershed in the southern Great Plains is demonstrated. These simulations are initialized with a set of offline spinups to achieve a balanced state of initial conditions. To quantify the significance of subsurface physics, compared with other physical processes calculated in WRF, these simulations are carried out with two different surface spinups and three different microphysics parameterizations in WRF. These simulations illustrate enhancements to coupled model physics for two applications: water resources and wind-energy forecasting. For the water resources example, it is demonstrated how PF.WRF simulates explicit rainfall and water storage within the basin and runoff. Then the hydrographs predicted by different microphysics schemes within WRF are compared. Because soil moisture is expected to impact boundary layer winds, the applicability of the model to wind-energy applications is demonstrated by using PF.WRF and WRF simulations to provide estimates of wind and wind shear that are useful indicators of wind-power output.
Abstract
No Abstract available.
Abstract
No Abstract available.
Abstract
During the Deep Propagating Gravity Wave Experiment (DEEPWAVE) project in June and July 2014, the Gulfstream V research aircraft flew 97 legs over the Southern Alps of New Zealand and 150 legs over the Tasman Sea and Southern Ocean, mostly in the low stratosphere at 12.1-km altitude. Improved instrument calibration, redundant sensors, longer flight legs, energy flux estimation, and scale analysis revealed several new gravity wave properties. Over the sea, flight-level wave fluxes mostly fell below the detection threshold. Over terrain, disturbances had characteristic mountain wave attributes of positive vertical energy flux (EF z ), negative zonal momentum flux, and upwind horizontal energy flux. In some cases, the fluxes changed rapidly within an 8-h flight, even though environmental conditions were nearly unchanged. The largest observed zonal momentum and vertical energy fluxes were MF x = −550 mPa and EF z = 22 W m−2, respectively.
A wide variety of disturbance scales were found at flight level over New Zealand. The vertical wind variance at flight level was dominated by short “fluxless” waves with wavelengths in the 6–15-km range. Even shorter scales, down to 500 m, were found in wave breaking regions. The wavelength of the flux-carrying mountain waves was much longer—mostly between 60 and 150 km. In the strong cases, however, with EF z > 4 W m−2, the dominant flux wavelength decreased (i.e., “downshifted”) to an intermediate wavelength between 20 and 60 km. A potential explanation for the rapid flux changes and the scale “downshifting” is that low-level flow can shift between “terrain following” and “envelope following” associated with trapped air in steep New Zealand valleys.
Abstract
During the Deep Propagating Gravity Wave Experiment (DEEPWAVE) project in June and July 2014, the Gulfstream V research aircraft flew 97 legs over the Southern Alps of New Zealand and 150 legs over the Tasman Sea and Southern Ocean, mostly in the low stratosphere at 12.1-km altitude. Improved instrument calibration, redundant sensors, longer flight legs, energy flux estimation, and scale analysis revealed several new gravity wave properties. Over the sea, flight-level wave fluxes mostly fell below the detection threshold. Over terrain, disturbances had characteristic mountain wave attributes of positive vertical energy flux (EF z ), negative zonal momentum flux, and upwind horizontal energy flux. In some cases, the fluxes changed rapidly within an 8-h flight, even though environmental conditions were nearly unchanged. The largest observed zonal momentum and vertical energy fluxes were MF x = −550 mPa and EF z = 22 W m−2, respectively.
A wide variety of disturbance scales were found at flight level over New Zealand. The vertical wind variance at flight level was dominated by short “fluxless” waves with wavelengths in the 6–15-km range. Even shorter scales, down to 500 m, were found in wave breaking regions. The wavelength of the flux-carrying mountain waves was much longer—mostly between 60 and 150 km. In the strong cases, however, with EF z > 4 W m−2, the dominant flux wavelength decreased (i.e., “downshifted”) to an intermediate wavelength between 20 and 60 km. A potential explanation for the rapid flux changes and the scale “downshifting” is that low-level flow can shift between “terrain following” and “envelope following” associated with trapped air in steep New Zealand valleys.
Abstract
The Deep Propagating Gravity Wave Experiment (DEEPWAVE) was designed to quantify gravity wave (GW) dynamics and effects from orographic and other sources to regions of dissipation at high altitudes. The core DEEPWAVE field phase took place from May through July 2014 using a comprehensive suite of airborne and ground-based instruments providing measurements from Earth’s surface to ∼100 km. Austral winter was chosen to observe deep GW propagation to high altitudes. DEEPWAVE was based on South Island, New Zealand, to provide access to the New Zealand and Tasmanian “hotspots” of GW activity and additional GW sources over the Southern Ocean and Tasman Sea. To observe GWs up to ∼100 km, DEEPWAVE utilized three new instruments built specifically for the National Science Foundation (NSF)/National Center for Atmospheric Research (NCAR) Gulfstream V (GV): a Rayleigh lidar, a sodium resonance lidar, and an advanced mesosphere temperature mapper. These measurements were supplemented by in situ probes, dropsondes, and a microwave temperature profiler on the GV and by in situ probes and a Doppler lidar aboard the German DLR Falcon. Extensive ground-based instrumentation and radiosondes were deployed on South Island, Tasmania, and Southern Ocean islands. Deep orographic GWs were a primary target but multiple flights also observed deep GWs arising from deep convection, jet streams, and frontal systems. Highlights include the following: 1) strong orographic GW forcing accompanying strong cross-mountain flows, 2) strong high-altitude responses even when orographic forcing was weak, 3) large-scale GWs at high altitudes arising from jet stream sources, and 4) significant flight-level energy fluxes and often very large momentum fluxes at high altitudes.
Abstract
The Deep Propagating Gravity Wave Experiment (DEEPWAVE) was designed to quantify gravity wave (GW) dynamics and effects from orographic and other sources to regions of dissipation at high altitudes. The core DEEPWAVE field phase took place from May through July 2014 using a comprehensive suite of airborne and ground-based instruments providing measurements from Earth’s surface to ∼100 km. Austral winter was chosen to observe deep GW propagation to high altitudes. DEEPWAVE was based on South Island, New Zealand, to provide access to the New Zealand and Tasmanian “hotspots” of GW activity and additional GW sources over the Southern Ocean and Tasman Sea. To observe GWs up to ∼100 km, DEEPWAVE utilized three new instruments built specifically for the National Science Foundation (NSF)/National Center for Atmospheric Research (NCAR) Gulfstream V (GV): a Rayleigh lidar, a sodium resonance lidar, and an advanced mesosphere temperature mapper. These measurements were supplemented by in situ probes, dropsondes, and a microwave temperature profiler on the GV and by in situ probes and a Doppler lidar aboard the German DLR Falcon. Extensive ground-based instrumentation and radiosondes were deployed on South Island, Tasmania, and Southern Ocean islands. Deep orographic GWs were a primary target but multiple flights also observed deep GWs arising from deep convection, jet streams, and frontal systems. Highlights include the following: 1) strong orographic GW forcing accompanying strong cross-mountain flows, 2) strong high-altitude responses even when orographic forcing was weak, 3) large-scale GWs at high altitudes arising from jet stream sources, and 4) significant flight-level energy fluxes and often very large momentum fluxes at high altitudes.
Abstract
A warm bias in tropical tropopause temperature is found in the Met Office Unified Model (MetUM), in common with most models from phase 5 of CMIP (CMIP5). Key dynamical, microphysical, and radiative processes influencing the tropical tropopause temperature and lower-stratospheric water vapor concentrations in climate models are investigated using the MetUM. A series of sensitivity experiments are run to separate the effects of vertical advection, ice optical and microphysical properties, convection, cirrus clouds, and atmospheric composition on simulated tropopause temperature and lower-stratospheric water vapor concentrations in the tropics. The numerical accuracy of the vertical advection, determined in the MetUM by the choice of interpolation and conservation schemes used, is found to be particularly important. Microphysical and radiative processes are found to influence stratospheric water vapor both through modifying the tropical tropopause temperature and through modifying upper-tropospheric water vapor concentrations, allowing more water vapor to be advected into the stratosphere. The representation of any of the processes discussed can act to significantly reduce biases in tropical tropopause temperature and stratospheric water vapor in a physical way, thereby improving climate simulations.
Abstract
A warm bias in tropical tropopause temperature is found in the Met Office Unified Model (MetUM), in common with most models from phase 5 of CMIP (CMIP5). Key dynamical, microphysical, and radiative processes influencing the tropical tropopause temperature and lower-stratospheric water vapor concentrations in climate models are investigated using the MetUM. A series of sensitivity experiments are run to separate the effects of vertical advection, ice optical and microphysical properties, convection, cirrus clouds, and atmospheric composition on simulated tropopause temperature and lower-stratospheric water vapor concentrations in the tropics. The numerical accuracy of the vertical advection, determined in the MetUM by the choice of interpolation and conservation schemes used, is found to be particularly important. Microphysical and radiative processes are found to influence stratospheric water vapor both through modifying the tropical tropopause temperature and through modifying upper-tropospheric water vapor concentrations, allowing more water vapor to be advected into the stratosphere. The representation of any of the processes discussed can act to significantly reduce biases in tropical tropopause temperature and stratospheric water vapor in a physical way, thereby improving climate simulations.
