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- Author or Editor: L. A. Walter x
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Abstract
A new growth equation for pure water and solution droplets with radii≳1µm has been developed which features discrete vapor and temperature fields at the surface of growing droplets. The discrete fields are created by the condensation and thermal accommodation coefficients in order to maintain steady state in the vapor and heat transfers. The newly derived equation is compared with previous theories, and their differences and ranges of applicability are clarified. It is shown that the newly derived equation includes some of the previous equations as special cases. The new equation is numerically evaluated and graphically examined for the case of pure water droplets. The results show a spreading tendency in size distribution of formed droplets at the start of their growth.
The present theory and equations may also be applied to the evaporation of a droplet and the growth of an ice particle where the shape can he assumed to he spherical.
Abstract
A new growth equation for pure water and solution droplets with radii≳1µm has been developed which features discrete vapor and temperature fields at the surface of growing droplets. The discrete fields are created by the condensation and thermal accommodation coefficients in order to maintain steady state in the vapor and heat transfers. The newly derived equation is compared with previous theories, and their differences and ranges of applicability are clarified. It is shown that the newly derived equation includes some of the previous equations as special cases. The new equation is numerically evaluated and graphically examined for the case of pure water droplets. The results show a spreading tendency in size distribution of formed droplets at the start of their growth.
The present theory and equations may also be applied to the evaporation of a droplet and the growth of an ice particle where the shape can he assumed to he spherical.
Abstract
The Canadian CloudSat/Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) Validation Project (C3VP) was designed to acquire aircraft, surface, and satellite observations of particle size distributions during cold season precipitation events for the purposes of validating and improving upon satellite-based retrievals of precipitation and the representation of cloud and precipitation processes within numerical weather prediction schemes. During an intensive observation period on 22 January 2007, an instrumented aircraft measured ice crystal size distributions, ice and liquid water contents, and atmospheric state parameters within a broad shield of precipitation generated by a passing midlatitude cyclone. The 94-GHz CloudSat radar acquired vertical profiles of radar reflectivity within light to moderate snowfall, coincident with C3VP surface and aircraft instrumentation. Satellite-based retrievals of cold season precipitation require relationships between remotely sensed quantities, such as radar reflectivity or brightness temperature, and the ice water content present within the sampled profile.
In this study, three methods for simulating CloudSat radar reflectivity are investigated by comparing Mie spheres, single dendrites, and fractal aggregates represented within scattering databases or parameterizations. It is demonstrated that calculations of radar backscatter from nonspherical crystal shapes are required to represent the vertical trend in CloudSat radar reflectivity for this particular event, as Mie resonance effects reduce the radar backscatter from precipitation-sized particles larger than 1 mm. Remaining differences between reflectivity from nonspherical shapes and observations are attributed to uncertainty in the mass–diameter relationships for observed crystals and disparities between naturally occurring crystals and shapes assumed in the development of ice crystal scattering databases and parameterizations.
Abstract
The Canadian CloudSat/Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) Validation Project (C3VP) was designed to acquire aircraft, surface, and satellite observations of particle size distributions during cold season precipitation events for the purposes of validating and improving upon satellite-based retrievals of precipitation and the representation of cloud and precipitation processes within numerical weather prediction schemes. During an intensive observation period on 22 January 2007, an instrumented aircraft measured ice crystal size distributions, ice and liquid water contents, and atmospheric state parameters within a broad shield of precipitation generated by a passing midlatitude cyclone. The 94-GHz CloudSat radar acquired vertical profiles of radar reflectivity within light to moderate snowfall, coincident with C3VP surface and aircraft instrumentation. Satellite-based retrievals of cold season precipitation require relationships between remotely sensed quantities, such as radar reflectivity or brightness temperature, and the ice water content present within the sampled profile.
In this study, three methods for simulating CloudSat radar reflectivity are investigated by comparing Mie spheres, single dendrites, and fractal aggregates represented within scattering databases or parameterizations. It is demonstrated that calculations of radar backscatter from nonspherical crystal shapes are required to represent the vertical trend in CloudSat radar reflectivity for this particular event, as Mie resonance effects reduce the radar backscatter from precipitation-sized particles larger than 1 mm. Remaining differences between reflectivity from nonspherical shapes and observations are attributed to uncertainty in the mass–diameter relationships for observed crystals and disparities between naturally occurring crystals and shapes assumed in the development of ice crystal scattering databases and parameterizations.
Abstract
Persistent weather regimes characterized by anomalous temperature or precipitation are often associated with persistent anomalies (PAs) in the tropospheric geopotential height field. To identify PAs throughout the annual cycle, an earlier definition is modified to apply a seasonally varying magnitude threshold, based on a smoothed, daily varying climatological average of daily 500-hPa geopotential height variability. The modified index can be applied to a wide variety of analysis, reanalysis, or model-forecast gridded data. Here, the modified PA index is used to identify positive and negative Northern Hemisphere PAs in all seasons and to compute trends in PA frequency, strength, location, and duration, in the ECMWF ERA-Interim reanalysis dataset (1979–2016). Height data are detrended and anomalies are weighted with an inverse sine-of-latitude function. In addition to maxima in PA frequency identified previously (North Pacific, North Atlantic, and Russia), an additional summertime maximum appears in the Arctic; this feature has not been analyzed extensively. A composite of summertime positive Arctic PA events reveals an equivalent barotropic structure, similar to that documented for midlatitude PAs. Arctic PA frequency is greatest in summer; it exhibits no trend in frequency over the 38-yr ERA-Interim analysis period. In fact, no discernable trends in PA frequency, strength, or duration are evident in the analysis period for the primary PA regions, although there is a suggestion of a northward shift in positive PA activity in the North Pacific.
Abstract
Persistent weather regimes characterized by anomalous temperature or precipitation are often associated with persistent anomalies (PAs) in the tropospheric geopotential height field. To identify PAs throughout the annual cycle, an earlier definition is modified to apply a seasonally varying magnitude threshold, based on a smoothed, daily varying climatological average of daily 500-hPa geopotential height variability. The modified index can be applied to a wide variety of analysis, reanalysis, or model-forecast gridded data. Here, the modified PA index is used to identify positive and negative Northern Hemisphere PAs in all seasons and to compute trends in PA frequency, strength, location, and duration, in the ECMWF ERA-Interim reanalysis dataset (1979–2016). Height data are detrended and anomalies are weighted with an inverse sine-of-latitude function. In addition to maxima in PA frequency identified previously (North Pacific, North Atlantic, and Russia), an additional summertime maximum appears in the Arctic; this feature has not been analyzed extensively. A composite of summertime positive Arctic PA events reveals an equivalent barotropic structure, similar to that documented for midlatitude PAs. Arctic PA frequency is greatest in summer; it exhibits no trend in frequency over the 38-yr ERA-Interim analysis period. In fact, no discernable trends in PA frequency, strength, or duration are evident in the analysis period for the primary PA regions, although there is a suggestion of a northward shift in positive PA activity in the North Pacific.
Abstract
Measurements of the optical refractive index structure coefficient
Abstract
Measurements of the optical refractive index structure coefficient
Assessing Dual-Polarization Radar Estimates of Extreme Rainfall during Hurricane HarveyAbstract
Hurricane Harvey hit the Texas Gulf Coast as a major hurricane on 25 August 2017 before exiting the state as a tropical storm on 29 August 2017. Left in its wake was historic flooding, with some locations measuring more than 60 in. (150 cm) of rain over a 5-day period. The WSR-88D radar (KHGX) maintained operations for the entirety of the event. Rain gauge data from the Harris County Flood Warning System (HCFWS) was used for validation with the full radar dataset to retrieve daily and event-total precipitation estimates for the period 25–29 August 2017. The KHGX precipitation estimates were then compared with the HCFWS gauges. Three different hybrid polarimetric rainfall retrievals were used, along with attenuation-based retrieval that employs the radar-observed differential propagation. An advantage of using a attenuation-based retrieval is its immunity to partial beam blockage and calibration errors in reflectivity and differential reflectivity. All of the retrievals are susceptible to changes in the observed drop size distribution (DSD). No in situ DSD data were available over the study area, so changes in the DSD were interpreted by examining the observed radar data. We examined the parameter space of two key values in the attenuation retrieval to test the sensitivity of the rain retrieval. Selecting a value of α = 0.015 and β = 0.600 provided the best overall results, relative to the gauges, but more work needs to be done to develop an automated technique to account for changes in the ambient DSD.
Abstract
Hurricane Harvey hit the Texas Gulf Coast as a major hurricane on 25 August 2017 before exiting the state as a tropical storm on 29 August 2017. Left in its wake was historic flooding, with some locations measuring more than 60 in. (150 cm) of rain over a 5-day period. The WSR-88D radar (KHGX) maintained operations for the entirety of the event. Rain gauge data from the Harris County Flood Warning System (HCFWS) was used for validation with the full radar dataset to retrieve daily and event-total precipitation estimates for the period 25–29 August 2017. The KHGX precipitation estimates were then compared with the HCFWS gauges. Three different hybrid polarimetric rainfall retrievals were used, along with attenuation-based retrieval that employs the radar-observed differential propagation. An advantage of using a attenuation-based retrieval is its immunity to partial beam blockage and calibration errors in reflectivity and differential reflectivity. All of the retrievals are susceptible to changes in the observed drop size distribution (DSD). No in situ DSD data were available over the study area, so changes in the DSD were interpreted by examining the observed radar data. We examined the parameter space of two key values in the attenuation retrieval to test the sensitivity of the rain retrieval. Selecting a value of α = 0.015 and β = 0.600 provided the best overall results, relative to the gauges, but more work needs to be done to develop an automated technique to account for changes in the ambient DSD.
Abstract
Selective logging degrades tropical forests. Logging operations vary in timing, location, and intensity. Evidence of this land use is rapidly obscured by forest regeneration and ongoing deforestation. A detailed study of selective logging operations was conducted near Sinop, State of Mato Grosso, Brazil, one of the key Amazonian logging centers. An 11-yr series of annual Lansdat images (1992–2002) was used to detect and track logged forests across the landscape. A semiautomated method was applied and compared to both visual interpretation and field data. Although visual detection provided precise delineation of some logged areas, it missed many areas. The semiautomated technique provided the best estimates of logging extent that are largely independent of potential user bias. Multitemporal analyses allowed the authors to analyze the annual variations in logging and deforestation, as well as the interaction between them. It is shown that, because of both rapid regrowth and deforestation, evidence of logging activities often disappeared within 1–3 yr. During the 1992–2002 interval, a total of 11 449 km2 of forest was selectively logged. Around 17% of these logged forests had been deforested by 2002. An intra-annual analysis was also conducted using four images spread over a single year. Nearly 3% of logged forests were rapidly deforested during the year in which logging occurred, indicating that even annual monitoring will underestimate logging extent. Great care will need to be taken when inferring logging rates from observations greater than a year apart because of the partial detection of previous years of logging activity.
Abstract
Selective logging degrades tropical forests. Logging operations vary in timing, location, and intensity. Evidence of this land use is rapidly obscured by forest regeneration and ongoing deforestation. A detailed study of selective logging operations was conducted near Sinop, State of Mato Grosso, Brazil, one of the key Amazonian logging centers. An 11-yr series of annual Lansdat images (1992–2002) was used to detect and track logged forests across the landscape. A semiautomated method was applied and compared to both visual interpretation and field data. Although visual detection provided precise delineation of some logged areas, it missed many areas. The semiautomated technique provided the best estimates of logging extent that are largely independent of potential user bias. Multitemporal analyses allowed the authors to analyze the annual variations in logging and deforestation, as well as the interaction between them. It is shown that, because of both rapid regrowth and deforestation, evidence of logging activities often disappeared within 1–3 yr. During the 1992–2002 interval, a total of 11 449 km2 of forest was selectively logged. Around 17% of these logged forests had been deforested by 2002. An intra-annual analysis was also conducted using four images spread over a single year. Nearly 3% of logged forests were rapidly deforested during the year in which logging occurred, indicating that even annual monitoring will underestimate logging extent. Great care will need to be taken when inferring logging rates from observations greater than a year apart because of the partial detection of previous years of logging activity.
Abstract
The Canadian CloudSat/Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) Validation Project (C3VP) was a field campaign designed to obtain aircraft, surface, and radar observations of clouds and precipitation in support of improving the simulation of snowfall and cold season precipitation, their microphysical processes represented within forecast models, and radiative properties relevant to remotely sensed retrievals. During the campaign, a midlatitude cyclone tracked along the U.S.–Canadian border on 22 January 2007, producing an extensive area of snowfall. Observations of ice crystals from this event are used to evaluate the assumptions and physical relationships for the snow category within the Goddard six-class, single-moment microphysics scheme, as implemented within the Weather Research and Forecasting (WRF) model.
The WRF model forecast generally reproduced the precipitation and cloud structures sampled by radars and aircraft, permitting a comparison between C3VP observations and model snowfall characteristics. Key snowfall assumptions in the Goddard scheme are an exponential size distribution with fixed intercept and effective bulk density, and the relationship between crystal diameter and terminal velocity. Fixed values for the size distribution intercept and density did not represent the vertical variability of naturally occurring populations of aggregates, and the current diameter and fall speed relationship underestimated terminal velocities for all sizes of crystals.
Abstract
The Canadian CloudSat/Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) Validation Project (C3VP) was a field campaign designed to obtain aircraft, surface, and radar observations of clouds and precipitation in support of improving the simulation of snowfall and cold season precipitation, their microphysical processes represented within forecast models, and radiative properties relevant to remotely sensed retrievals. During the campaign, a midlatitude cyclone tracked along the U.S.–Canadian border on 22 January 2007, producing an extensive area of snowfall. Observations of ice crystals from this event are used to evaluate the assumptions and physical relationships for the snow category within the Goddard six-class, single-moment microphysics scheme, as implemented within the Weather Research and Forecasting (WRF) model.
The WRF model forecast generally reproduced the precipitation and cloud structures sampled by radars and aircraft, permitting a comparison between C3VP observations and model snowfall characteristics. Key snowfall assumptions in the Goddard scheme are an exponential size distribution with fixed intercept and effective bulk density, and the relationship between crystal diameter and terminal velocity. Fixed values for the size distribution intercept and density did not represent the vertical variability of naturally occurring populations of aggregates, and the current diameter and fall speed relationship underestimated terminal velocities for all sizes of crystals.
Abstract
Persistent anomalies (PAs) are associated with a variety of impactful weather extremes, prompting research into how their characteristics will respond to climate change. Previous studies, however, have not provided conclusive results, owing to the complexity of the phenomenon and to difficulties in general circulation model (GCM) representations of PAs. Here, we diagnose PA activity in 10 years of current and projected future output from global, high-resolution (15-km mesh) time-slice simulations performed with the Model for Prediction Across Scales-Atmosphere (MPAS-A). These time slices span a range of ENSO states. They include high-resolution representations of sea surface temperatures and GCM-based sea ice for present and future climates. Future projections, based on the RCP8.5 scenario, exhibit strong Arctic amplification and tropical upper warming, providing a valuable experiment with which to assess the impact of climate change on PA frequency. The MPAS-A present-climate simulations reproduce the main centers of observed PA activity, but with an eastward shift in the North Pacific and reduced amplitude in the North Atlantic. The overall frequency of positive PAs in the future simulations is similar to that in the present-day simulations, while negative PAs become less frequent. Although some regional changes emerge, the small, generally negative changes in PA frequency and meridional circulation index indicate that climate change does not lead to increased persistence of midlatitude flow anomalies or increased waviness in these simulations.
Abstract
Persistent anomalies (PAs) are associated with a variety of impactful weather extremes, prompting research into how their characteristics will respond to climate change. Previous studies, however, have not provided conclusive results, owing to the complexity of the phenomenon and to difficulties in general circulation model (GCM) representations of PAs. Here, we diagnose PA activity in 10 years of current and projected future output from global, high-resolution (15-km mesh) time-slice simulations performed with the Model for Prediction Across Scales-Atmosphere (MPAS-A). These time slices span a range of ENSO states. They include high-resolution representations of sea surface temperatures and GCM-based sea ice for present and future climates. Future projections, based on the RCP8.5 scenario, exhibit strong Arctic amplification and tropical upper warming, providing a valuable experiment with which to assess the impact of climate change on PA frequency. The MPAS-A present-climate simulations reproduce the main centers of observed PA activity, but with an eastward shift in the North Pacific and reduced amplitude in the North Atlantic. The overall frequency of positive PAs in the future simulations is similar to that in the present-day simulations, while negative PAs become less frequent. Although some regional changes emerge, the small, generally negative changes in PA frequency and meridional circulation index indicate that climate change does not lead to increased persistence of midlatitude flow anomalies or increased waviness in these simulations.
Abstract
The North American Regional Reanalysis (NARR) was used to develop an expanded, long-term (1979–2009) climatology of meridional (southerly and northerly) low-level jets over North America and surrounding coastal environs. NARR has greater spatial coverage and finer temporal (3 hourly) and horizontal (32 km) resolutions than do routine rawinsonde wind measurements. The NARR climatology focuses on jet frequency and average speed and elevation by month and 3-hourly time step. To evaluate the plausibility of the climatology, jet characteristics were compared with those obtained from prior climatological analyses, case studies, field campaigns, and numerical simulations. Strong agreement was found with many of the previously documented characteristics of well-known jets, including the northerly Pacific coast jet and southerly Great Plains jet. The NARR climatology provides additional insights into the spatial extent and seasonal shifts of large jet frequencies and into diurnal fluctuations in frequency, speed, and elevation. Weaker and/or less spatially extensive jets are also well depicted in the NARR climatology, including the southerly Gulf of California jet, summertime southerly jets and autumn northerly jets off the mid-Atlantic coast, and northerly jets in the high plains. Furthermore, several new areas of relatively frequent jet occurrence, most of which align with shallow thermal gradients, are seen in the NARR climatology. The NARR climatology supplements and enhances our understanding of North American low-level jets and points to the need for additional research on both the climatological characteristics of these jets and on the processes contributing to their formation.
Abstract
The North American Regional Reanalysis (NARR) was used to develop an expanded, long-term (1979–2009) climatology of meridional (southerly and northerly) low-level jets over North America and surrounding coastal environs. NARR has greater spatial coverage and finer temporal (3 hourly) and horizontal (32 km) resolutions than do routine rawinsonde wind measurements. The NARR climatology focuses on jet frequency and average speed and elevation by month and 3-hourly time step. To evaluate the plausibility of the climatology, jet characteristics were compared with those obtained from prior climatological analyses, case studies, field campaigns, and numerical simulations. Strong agreement was found with many of the previously documented characteristics of well-known jets, including the northerly Pacific coast jet and southerly Great Plains jet. The NARR climatology provides additional insights into the spatial extent and seasonal shifts of large jet frequencies and into diurnal fluctuations in frequency, speed, and elevation. Weaker and/or less spatially extensive jets are also well depicted in the NARR climatology, including the southerly Gulf of California jet, summertime southerly jets and autumn northerly jets off the mid-Atlantic coast, and northerly jets in the high plains. Furthermore, several new areas of relatively frequent jet occurrence, most of which align with shallow thermal gradients, are seen in the NARR climatology. The NARR climatology supplements and enhances our understanding of North American low-level jets and points to the need for additional research on both the climatological characteristics of these jets and on the processes contributing to their formation.
