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Abstract
Some dynamic and thermodynamic structures of a microburst-producing storm, which occurred on 14 July 1982 in Colorado, were studied in detail during the storm's quasi-steady mature stage. Dual-Doppler data from 1646 to 1648 MDT, collected during the project of Joint Airport Weather Studies (JAWS) at Denver's Stapleton International Airport, were objectively analyzed to produce a three-dimensional wind field. The domain of interest had a horizontal dimension of 10 km by 10 km centered on the microburst. There were 19 analysis levels in the vertical, ranging from 0.25 to 8.5 km AGL. The horizontal grid spacing was 0.5 km, while thevertical grid spacing varied from 0.25 km near the surface to 0.5 km at levels above I kin. Vertical velocities were computed by integrating the anelastic continuity equation downward from the storm's top with variational adjustment. Subsequently, fields of deviation-perturbation pressure and virtual temperature were recovered from a detailed wind field using the three momentum equations. These fields were then subjected to internal consistency checks to determine the level of confidence before interpretation.
Findings demonsUate that the thermodynamic retrieval method is feasible for investigating the structure and internal dynamics of the storm. Variational adjustment substantially reduces errors in vertical velocity fields. Results show that the microburst being investigated is embedded within the high-refiectivity region with heavy precipitation. A strong downfiow impinges upon the surface, producing a stagnation mesohigh inside the microburst. This high is accompanied by low pressure in the strongest outflow regions, forming a pronounced horizontal perturbation pressure gradient outward from the high-pressure center. Such pressure patterns are in good agreement with the surface observations in similar cases for two different storms. The outflow regions extend from the surface to approximately I km height with maximum divergence in excess of lO-: s-L The outflow air is negatively buoyant due to evaporation in the outsldn of the microburst. In the middle troposphere, hish pressure forms on the upshear side of the main ulxlraft with low pressure on the downshear side due to dynamical interactions between the updraft and the sheared environmental wind. The retrieved buoyancy field agrees well with the updraft-downdraft structure with warming in the updraft and cooling in the downdraft. The combined effects of perturbation-pressure gradients, buoyancy and precipitation loading are responsible for maintaining vigorous convection of the downdrafis which produced the strong diverging outflow at low levels.
Abstract
Some dynamic and thermodynamic structures of a microburst-producing storm, which occurred on 14 July 1982 in Colorado, were studied in detail during the storm's quasi-steady mature stage. Dual-Doppler data from 1646 to 1648 MDT, collected during the project of Joint Airport Weather Studies (JAWS) at Denver's Stapleton International Airport, were objectively analyzed to produce a three-dimensional wind field. The domain of interest had a horizontal dimension of 10 km by 10 km centered on the microburst. There were 19 analysis levels in the vertical, ranging from 0.25 to 8.5 km AGL. The horizontal grid spacing was 0.5 km, while thevertical grid spacing varied from 0.25 km near the surface to 0.5 km at levels above I kin. Vertical velocities were computed by integrating the anelastic continuity equation downward from the storm's top with variational adjustment. Subsequently, fields of deviation-perturbation pressure and virtual temperature were recovered from a detailed wind field using the three momentum equations. These fields were then subjected to internal consistency checks to determine the level of confidence before interpretation.
Findings demonsUate that the thermodynamic retrieval method is feasible for investigating the structure and internal dynamics of the storm. Variational adjustment substantially reduces errors in vertical velocity fields. Results show that the microburst being investigated is embedded within the high-refiectivity region with heavy precipitation. A strong downfiow impinges upon the surface, producing a stagnation mesohigh inside the microburst. This high is accompanied by low pressure in the strongest outflow regions, forming a pronounced horizontal perturbation pressure gradient outward from the high-pressure center. Such pressure patterns are in good agreement with the surface observations in similar cases for two different storms. The outflow regions extend from the surface to approximately I km height with maximum divergence in excess of lO-: s-L The outflow air is negatively buoyant due to evaporation in the outsldn of the microburst. In the middle troposphere, hish pressure forms on the upshear side of the main ulxlraft with low pressure on the downshear side due to dynamical interactions between the updraft and the sheared environmental wind. The retrieved buoyancy field agrees well with the updraft-downdraft structure with warming in the updraft and cooling in the downdraft. The combined effects of perturbation-pressure gradients, buoyancy and precipitation loading are responsible for maintaining vigorous convection of the downdrafis which produced the strong diverging outflow at low levels.
Abstract
Using a 6-km-resolution regional climate simulation of Southern California, the effect of orographic blocking on the precipitation climatology is examined. To diagnose whether blocking occurs, precipitating hours are categorized by a bulk Froude number. The precipitation distribution becomes much more spatially homogeneous as the Froude number decreases, and an inspection of winds confirms that this results from the increasing prevalence of orographic blocking. Low Froude (Froude approximately less than 1), blocked cases account for a large fraction of climatological precipitation, particularly at the coastline where more than half is attributable to blocked cases. Thus, the climatological precipitation–slope relationship seen in observations and in the simulation is a hybrid of blocked and unblocked cases.
Simulated precipitation distributions are compared to those predicted by a simple linear model that includes only rainfall arising from direct forced topographic ascent. The agreement is nearly perfect for high Froude (Froude substantially larger than 1) cases but degrades dramatically as the index decreases; as blocking becomes more prevalent, the precipitation–slope relationship becomes continuously weaker than that predicted by the linear model. Because of its high fidelity during unblocked cases, it is surmised that blocking effects are the primary limitation preventing the linear model from accurately representing precipitation climatology and that the representation would be significantly improved during low Froude hours by the addition of a term to reduce the effective slope of the topography. These results suggest orographic blocking may substantially affect climatological precipitation distributions in similarly configured coastal areas.
Abstract
Using a 6-km-resolution regional climate simulation of Southern California, the effect of orographic blocking on the precipitation climatology is examined. To diagnose whether blocking occurs, precipitating hours are categorized by a bulk Froude number. The precipitation distribution becomes much more spatially homogeneous as the Froude number decreases, and an inspection of winds confirms that this results from the increasing prevalence of orographic blocking. Low Froude (Froude approximately less than 1), blocked cases account for a large fraction of climatological precipitation, particularly at the coastline where more than half is attributable to blocked cases. Thus, the climatological precipitation–slope relationship seen in observations and in the simulation is a hybrid of blocked and unblocked cases.
Simulated precipitation distributions are compared to those predicted by a simple linear model that includes only rainfall arising from direct forced topographic ascent. The agreement is nearly perfect for high Froude (Froude substantially larger than 1) cases but degrades dramatically as the index decreases; as blocking becomes more prevalent, the precipitation–slope relationship becomes continuously weaker than that predicted by the linear model. Because of its high fidelity during unblocked cases, it is surmised that blocking effects are the primary limitation preventing the linear model from accurately representing precipitation climatology and that the representation would be significantly improved during low Froude hours by the addition of a term to reduce the effective slope of the topography. These results suggest orographic blocking may substantially affect climatological precipitation distributions in similarly configured coastal areas.
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Abstract
The Russian River in northern California is an important hydrological resource that typically depends on a few significant precipitation events per year, often associated with atmospheric rivers (ARs), to maintain its annual water supply. Because of the highly variable nature of annual precipitation in the region, accurate quantitative precipitation estimates (QPEs) are necessary to drive hydrologic models and inform water management decisions. The basin’s location and complex terrain present a unique challenge to QPEs, with sparse in situ observations and mountains that inhibit remote sensing by ground radars. Gridded multisensor QPE datasets can fill in the gaps but are susceptible to both the errors and uncertainties from the ingested datasets and uncertainties due to interpolation methods. In this study a dense network of independently operated rain gauges is used to evaluate gridded QPE from the Multi-Radar Multi-Sensor (MRMS) during 44 precipitation events occurring during the 2015/16 and 2016/17 wet seasons (October–March). The MRMS QPE products matched the gauge estimates of precipitation reasonably well in approximately half the cases but failed to capture the spatial distribution and intensity of the rainfall in the remaining cases. ERA-Interim reanalysis data suggest that the differences in performance are related to synoptic-scale patterns and AR landfall location. These synoptic-scale differences produce different rainfall distributions and influence basin-scale winds, potentially creating regions of small-scale precipitation enhancement or suppression. Data from four profiling radars indicated that a larger fraction of the precipitation in poorly captured events occurred as shallow stratiform rain unobserved by radar.
Abstract
The Russian River in northern California is an important hydrological resource that typically depends on a few significant precipitation events per year, often associated with atmospheric rivers (ARs), to maintain its annual water supply. Because of the highly variable nature of annual precipitation in the region, accurate quantitative precipitation estimates (QPEs) are necessary to drive hydrologic models and inform water management decisions. The basin’s location and complex terrain present a unique challenge to QPEs, with sparse in situ observations and mountains that inhibit remote sensing by ground radars. Gridded multisensor QPE datasets can fill in the gaps but are susceptible to both the errors and uncertainties from the ingested datasets and uncertainties due to interpolation methods. In this study a dense network of independently operated rain gauges is used to evaluate gridded QPE from the Multi-Radar Multi-Sensor (MRMS) during 44 precipitation events occurring during the 2015/16 and 2016/17 wet seasons (October–March). The MRMS QPE products matched the gauge estimates of precipitation reasonably well in approximately half the cases but failed to capture the spatial distribution and intensity of the rainfall in the remaining cases. ERA-Interim reanalysis data suggest that the differences in performance are related to synoptic-scale patterns and AR landfall location. These synoptic-scale differences produce different rainfall distributions and influence basin-scale winds, potentially creating regions of small-scale precipitation enhancement or suppression. Data from four profiling radars indicated that a larger fraction of the precipitation in poorly captured events occurred as shallow stratiform rain unobserved by radar.
During the past five years, the National Weather Service (NWS) has replaced over half of its liquid-in-glass maximum and minimum thermometers in wooden Cotton Region Shelters (CRSs) with thermistor-based Maximum–Minimum Temperature Systems (MMTSs) housed in smaller plastic shelters. Analyses of data from 424 (of the 3300) MMTS stations and 675 CRS stations show that a mean daily minimum temperature change of roughly +0.3°C, a mean daily maximum temperature change of−0.4°C, and a change in average temperature of −0.1 °C were introduced as a result of the new instrumentation. The change of −0.7°C in daily temperature range is particularly significant for climate change studies that use this element as an independent variable. Although troublesome for climatologists, there is reason to believe that this change (relative to older records) represents an improvement in absolute accuracy. The bias appears to be rather sharp and well defined. Since the National Climatic Data Center (NCDC) station history database contains records of instrumentation, adjustments for this bias can be readily applied, and we are reasonably confident that the corrections we have developed can be used to produce homogeneous time series of area-average temperature.
During the past five years, the National Weather Service (NWS) has replaced over half of its liquid-in-glass maximum and minimum thermometers in wooden Cotton Region Shelters (CRSs) with thermistor-based Maximum–Minimum Temperature Systems (MMTSs) housed in smaller plastic shelters. Analyses of data from 424 (of the 3300) MMTS stations and 675 CRS stations show that a mean daily minimum temperature change of roughly +0.3°C, a mean daily maximum temperature change of−0.4°C, and a change in average temperature of −0.1 °C were introduced as a result of the new instrumentation. The change of −0.7°C in daily temperature range is particularly significant for climate change studies that use this element as an independent variable. Although troublesome for climatologists, there is reason to believe that this change (relative to older records) represents an improvement in absolute accuracy. The bias appears to be rather sharp and well defined. Since the National Climatic Data Center (NCDC) station history database contains records of instrumentation, adjustments for this bias can be readily applied, and we are reasonably confident that the corrections we have developed can be used to produce homogeneous time series of area-average temperature.
It is believed that the severity of the storm hitting Canada on October 15, 1954 was due to the addition of an independent development to the dying hurricane Hazel. The problem of forecasting this event is discussed in the light of forecasts made at the time. The presence of a secondary development is verified.
It is believed that the severity of the storm hitting Canada on October 15, 1954 was due to the addition of an independent development to the dying hurricane Hazel. The problem of forecasting this event is discussed in the light of forecasts made at the time. The presence of a secondary development is verified.
Abstract
Regional climate simulations are conducted using the Polar fifth-generation Pennsylvania State University (PSU)–NCAR Mesoscale Model (MM5) with a 60-km horizontal resolution domain over North America to explore the summer climate of the Last Glacial Maximum (LGM: 21 000 calendar years ago), when much of the continent was covered by the Laurentide Ice Sheet (LIS). Output from a tailored NCAR Community Climate Model version 3 (CCM3) simulation of the LGM climate is used to provide the initial and lateral boundary conditions for Polar MM5. LGM boundary conditions include continental ice sheets, appropriate orbital forcing, reduced CO2 concentration, paleovegetation, modified sea surface temperatures, and lowered sea level.
The simulated LGM summer climate is characterized by a pronounced low-level thermal gradient along the southern margin of the LIS resulting from the juxtaposition of the cold ice sheet and adjacent warm ice-free land surface. This sharp thermal gradient anchors the midtropospheric jet stream and facilitates the development of synoptic cyclones that track over the ice sheet, some of which produce copious liquid precipitation along and south of the LIS terminus. Precipitation on the southern margin is orographically enhanced as moist southerly low-level flow (resembling a contemporary Great Plains low-level jet configuration) in advance of the cyclone is drawn up the ice sheet slope. Composites of wet and dry periods on the LIS southern margin illustrate two distinctly different atmospheric flow regimes. Given the episodic nature of the summer rain events, it may be possible to reconcile the model depiction of wet conditions on the LIS southern margin during the LGM summer with the widely accepted interpretation of aridity across the Great Plains based on geological proxy evidence.
Abstract
Regional climate simulations are conducted using the Polar fifth-generation Pennsylvania State University (PSU)–NCAR Mesoscale Model (MM5) with a 60-km horizontal resolution domain over North America to explore the summer climate of the Last Glacial Maximum (LGM: 21 000 calendar years ago), when much of the continent was covered by the Laurentide Ice Sheet (LIS). Output from a tailored NCAR Community Climate Model version 3 (CCM3) simulation of the LGM climate is used to provide the initial and lateral boundary conditions for Polar MM5. LGM boundary conditions include continental ice sheets, appropriate orbital forcing, reduced CO2 concentration, paleovegetation, modified sea surface temperatures, and lowered sea level.
The simulated LGM summer climate is characterized by a pronounced low-level thermal gradient along the southern margin of the LIS resulting from the juxtaposition of the cold ice sheet and adjacent warm ice-free land surface. This sharp thermal gradient anchors the midtropospheric jet stream and facilitates the development of synoptic cyclones that track over the ice sheet, some of which produce copious liquid precipitation along and south of the LIS terminus. Precipitation on the southern margin is orographically enhanced as moist southerly low-level flow (resembling a contemporary Great Plains low-level jet configuration) in advance of the cyclone is drawn up the ice sheet slope. Composites of wet and dry periods on the LIS southern margin illustrate two distinctly different atmospheric flow regimes. Given the episodic nature of the summer rain events, it may be possible to reconcile the model depiction of wet conditions on the LIS southern margin during the LGM summer with the widely accepted interpretation of aridity across the Great Plains based on geological proxy evidence.
Abstract
Optimized regional climate simulations are conducted using the Polar MM5, a version of the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5), with a 60-km horizontal resolution domain over North America during the Last Glacial Maximum (LGM, 21 000 calendar years ago), when much of the continent was covered by the Laurentide Ice Sheet (LIS). The objective is to describe the LGM annual cycle at high spatial resolution with an emphasis on the winter atmospheric circulation. Output from a tailored NCAR Community Climate Model version 3 (CCM3) simulation of the LGM climate is used to provide the initial and lateral boundary conditions for Polar MM5. LGM boundary conditions include continental ice sheets, appropriate orbital forcing, reduced CO2 concentration, paleovegetation, modified sea surface temperatures, and lowered sea level.
Polar MM5 produces a substantially different atmospheric response to the LGM boundary conditions than CCM3 and other recent GCM simulations. In particular, from November to April the upper-level flow is split around a blocking anticyclone over the LIS, with a northern branch over the Canadian Arctic and a southern branch impacting southern North America. The split flow pattern is most pronounced in January and transitions into a single, consolidated jet stream that migrates northward over the LIS during summer. Sensitivity experiments indicate that the winter split flow in Polar MM5 is primarily due to mechanical forcing by LIS, although model physics and resolution also contribute to the simulated flow configuration.
Polar MM5 LGM results are generally consistent with proxy climate estimates in the western United States, Alaska, and the Canadian Arctic and may help resolve some long-standing discrepancies between proxy data and previous simulations of the LGM climate.
Abstract
Optimized regional climate simulations are conducted using the Polar MM5, a version of the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5), with a 60-km horizontal resolution domain over North America during the Last Glacial Maximum (LGM, 21 000 calendar years ago), when much of the continent was covered by the Laurentide Ice Sheet (LIS). The objective is to describe the LGM annual cycle at high spatial resolution with an emphasis on the winter atmospheric circulation. Output from a tailored NCAR Community Climate Model version 3 (CCM3) simulation of the LGM climate is used to provide the initial and lateral boundary conditions for Polar MM5. LGM boundary conditions include continental ice sheets, appropriate orbital forcing, reduced CO2 concentration, paleovegetation, modified sea surface temperatures, and lowered sea level.
Polar MM5 produces a substantially different atmospheric response to the LGM boundary conditions than CCM3 and other recent GCM simulations. In particular, from November to April the upper-level flow is split around a blocking anticyclone over the LIS, with a northern branch over the Canadian Arctic and a southern branch impacting southern North America. The split flow pattern is most pronounced in January and transitions into a single, consolidated jet stream that migrates northward over the LIS during summer. Sensitivity experiments indicate that the winter split flow in Polar MM5 is primarily due to mechanical forcing by LIS, although model physics and resolution also contribute to the simulated flow configuration.
Polar MM5 LGM results are generally consistent with proxy climate estimates in the western United States, Alaska, and the Canadian Arctic and may help resolve some long-standing discrepancies between proxy data and previous simulations of the LGM climate.
Abstract
The Regional Arctic System Model (RASM) is a fully coupled, regional Earth system model applied over the pan-Arctic domain. This paper discusses the implementation of the Variable Infiltration Capacity land surface model (VIC) in RASM and evaluates the ability of RASM, version 1.0, to capture key features of the land surface climate and hydrologic cycle for the period 1979–2014 in comparison with uncoupled VIC simulations, reanalysis datasets, satellite measurements, and in situ observations. RASM reproduces the dominant features of the land surface climatology in the Arctic, such as the amount and regional distribution of precipitation, the partitioning of precipitation between runoff and evapotranspiration, the effects of snow on the water and energy balance, and the differences in turbulent fluxes between the tundra and taiga biomes. Surface air temperature biases in RASM, compared to reanalysis datasets ERA-Interim and MERRA, are generally less than 2°C; however, in the cold seasons there are local biases that exceed 6°C. Compared to satellite observations, RASM captures the annual cycle of snow-covered area well, although melt progresses about two weeks faster than observations in the late spring at high latitudes. With respect to derived fluxes, such as latent heat or runoff, RASM is shown to have similar performance statistics as ERA-Interim while differing substantially from MERRA, which consistently overestimates the evaporative flux across the Arctic region.
Abstract
The Regional Arctic System Model (RASM) is a fully coupled, regional Earth system model applied over the pan-Arctic domain. This paper discusses the implementation of the Variable Infiltration Capacity land surface model (VIC) in RASM and evaluates the ability of RASM, version 1.0, to capture key features of the land surface climate and hydrologic cycle for the period 1979–2014 in comparison with uncoupled VIC simulations, reanalysis datasets, satellite measurements, and in situ observations. RASM reproduces the dominant features of the land surface climatology in the Arctic, such as the amount and regional distribution of precipitation, the partitioning of precipitation between runoff and evapotranspiration, the effects of snow on the water and energy balance, and the differences in turbulent fluxes between the tundra and taiga biomes. Surface air temperature biases in RASM, compared to reanalysis datasets ERA-Interim and MERRA, are generally less than 2°C; however, in the cold seasons there are local biases that exceed 6°C. Compared to satellite observations, RASM captures the annual cycle of snow-covered area well, although melt progresses about two weeks faster than observations in the late spring at high latitudes. With respect to derived fluxes, such as latent heat or runoff, RASM is shown to have similar performance statistics as ERA-Interim while differing substantially from MERRA, which consistently overestimates the evaporative flux across the Arctic region.
