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- Author or Editor: Christopher P. Albrecht x
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Abstract
Innovative technologies that support implementation of automated vehicles continue to develop at a rapid pace. These advances strive to increase efficiency and safety throughout the global transportation network. One important challenge to these emergent technologies that remains underappreciated is how the vehicles will perform in adverse weather. Each year, weather-related vehicular crashes account for approximately 21% of all highway crashes in the United States. These crashes result in over 5,300 fatalities, injure over 418,000 people, and cost billions of dollars in insurance claims, liability, emergency services, congestion delays, rehabilitation, and environmental damage annually. Automated vehicles have the potential to significantly mitigate these statistics; however, public, private, and academic partnerships between the meteorological and transportation communities must be established to develop solutions to weather impacts now. To date, such interactions have been sparse and largely contribute to a lack of awareness in how these two communities may collaborate together. The purpose of this manuscript is to call the meteorological community to action and proactive engagement with the transportation community. A secondary goal is to make the transportation community aware of the advantages of teaming with the weather enterprise. Automated vehicles will not only increase travel safety, but also have benefits to the meteorological community through increasing availability of high-resolution surface data observations. The future challenges of these emergent technologies in the context of road weather implications focus on vehicle situational awareness and technological sensing capability in all weather conditions, and transforming how drivers and vehicles are informed of weather threats beyond sensing capabilities.
Abstract
Innovative technologies that support implementation of automated vehicles continue to develop at a rapid pace. These advances strive to increase efficiency and safety throughout the global transportation network. One important challenge to these emergent technologies that remains underappreciated is how the vehicles will perform in adverse weather. Each year, weather-related vehicular crashes account for approximately 21% of all highway crashes in the United States. These crashes result in over 5,300 fatalities, injure over 418,000 people, and cost billions of dollars in insurance claims, liability, emergency services, congestion delays, rehabilitation, and environmental damage annually. Automated vehicles have the potential to significantly mitigate these statistics; however, public, private, and academic partnerships between the meteorological and transportation communities must be established to develop solutions to weather impacts now. To date, such interactions have been sparse and largely contribute to a lack of awareness in how these two communities may collaborate together. The purpose of this manuscript is to call the meteorological community to action and proactive engagement with the transportation community. A secondary goal is to make the transportation community aware of the advantages of teaming with the weather enterprise. Automated vehicles will not only increase travel safety, but also have benefits to the meteorological community through increasing availability of high-resolution surface data observations. The future challenges of these emergent technologies in the context of road weather implications focus on vehicle situational awareness and technological sensing capability in all weather conditions, and transforming how drivers and vehicles are informed of weather threats beyond sensing capabilities.
Abstract
Observations made during a 24-h period as part of the Variability of the American Monsoon Systems (VAMOS) Ocean–Cloud–Atmosphere–Land Study Regional Experiment (VOCALS-REx) are analyzed to study the radiation and turbulence associated with the stratocumulus-topped marine boundary layer (BL). The first 14 h exhibited a well-mixed (coupled) BL with an average cloud-top radiative flux divergence of ~130 W m−2; the BL was decoupled during the last 10 h with negligible radiative flux divergence. The averaged radiative cooling very close to the cloud top was −9.04 K h−1 in coupled conditions and −3.85 K h−1 in decoupled conditions. This is the first study that combined data from a vertically pointing Doppler cloud radar and a Doppler lidar to yield the vertical velocity structure of the entire BL. The averaged vertical velocity variance and updraft mass flux during coupled conditions were higher than those during decoupled conditions at all levels by a factor of 2 or more. The vertical velocity skewness was negative in the entire BL during coupled conditions, whereas it was weakly positive in the lower third of the BL and negative above during decoupled conditions. A formulation of velocity scale is proposed that includes the effect of cloud-top radiative cooling in addition to the surface buoyancy flux. When scaled by the velocity scale, the vertical velocity variance and coherent downdrafts had similar magnitude during the coupled and decoupled conditions. The coherent updrafts that exhibited a constant profile in the entire BL during both the coupled and decoupled conditions scaled well with the convective velocity scale to a value of ~0.5.
Abstract
Observations made during a 24-h period as part of the Variability of the American Monsoon Systems (VAMOS) Ocean–Cloud–Atmosphere–Land Study Regional Experiment (VOCALS-REx) are analyzed to study the radiation and turbulence associated with the stratocumulus-topped marine boundary layer (BL). The first 14 h exhibited a well-mixed (coupled) BL with an average cloud-top radiative flux divergence of ~130 W m−2; the BL was decoupled during the last 10 h with negligible radiative flux divergence. The averaged radiative cooling very close to the cloud top was −9.04 K h−1 in coupled conditions and −3.85 K h−1 in decoupled conditions. This is the first study that combined data from a vertically pointing Doppler cloud radar and a Doppler lidar to yield the vertical velocity structure of the entire BL. The averaged vertical velocity variance and updraft mass flux during coupled conditions were higher than those during decoupled conditions at all levels by a factor of 2 or more. The vertical velocity skewness was negative in the entire BL during coupled conditions, whereas it was weakly positive in the lower third of the BL and negative above during decoupled conditions. A formulation of velocity scale is proposed that includes the effect of cloud-top radiative cooling in addition to the surface buoyancy flux. When scaled by the velocity scale, the vertical velocity variance and coherent downdrafts had similar magnitude during the coupled and decoupled conditions. The coherent updrafts that exhibited a constant profile in the entire BL during both the coupled and decoupled conditions scaled well with the convective velocity scale to a value of ~0.5.
Abstract
Stratocumulus-topped boundary layers (STBLs) observed in three different regions are described in the context of their thermodynamic and radiative properties. The primary dataset consists of 131 soundings from the southeastern Pacific (SEP), 90 soundings from the island of Graciosa (GRW) in the North Atlantic, and 83 soundings from the U.S. Southern Great Plains (SGP). A new technique that makes an attempt to preserve the depths of the sublayers within an STBL is proposed for averaging the profiles of thermodynamic and radiative variables. A one-dimensional radiative transfer model known as the Rapid Radiative Transfer Model was used to compute the radiative fluxes within the STBL. The SEP STBLs were characterized by a stronger and deeper inversion, together with thicker clouds, lower free-tropospheric moisture, and higher radiative flux divergence across the cloud layer, as compared to the GRW STBLs. Compared to the STBLs over the marine locations, the STBLs over SGP had higher wind shear and a negligible (−0.41 g kg−1) jump in mixing ratio across the inversion. Despite the differences in many of the STBL thermodynamic parameters, the differences in liquid water path at the three locations were statistically insignificant. The soundings were further classified as well mixed or decoupled based on the difference between the surface and cloud-base virtual potential temperature. The decoupled STBLs were deeper than the well-mixed STBLs at all three locations. Statistically insignificant differences in surface latent heat flux (LHF) between well-mixed and decoupled STBLs suggest that parameters other than LHF are responsible for producing decoupling.
Abstract
Stratocumulus-topped boundary layers (STBLs) observed in three different regions are described in the context of their thermodynamic and radiative properties. The primary dataset consists of 131 soundings from the southeastern Pacific (SEP), 90 soundings from the island of Graciosa (GRW) in the North Atlantic, and 83 soundings from the U.S. Southern Great Plains (SGP). A new technique that makes an attempt to preserve the depths of the sublayers within an STBL is proposed for averaging the profiles of thermodynamic and radiative variables. A one-dimensional radiative transfer model known as the Rapid Radiative Transfer Model was used to compute the radiative fluxes within the STBL. The SEP STBLs were characterized by a stronger and deeper inversion, together with thicker clouds, lower free-tropospheric moisture, and higher radiative flux divergence across the cloud layer, as compared to the GRW STBLs. Compared to the STBLs over the marine locations, the STBLs over SGP had higher wind shear and a negligible (−0.41 g kg−1) jump in mixing ratio across the inversion. Despite the differences in many of the STBL thermodynamic parameters, the differences in liquid water path at the three locations were statistically insignificant. The soundings were further classified as well mixed or decoupled based on the difference between the surface and cloud-base virtual potential temperature. The decoupled STBLs were deeper than the well-mixed STBLs at all three locations. Statistically insignificant differences in surface latent heat flux (LHF) between well-mixed and decoupled STBLs suggest that parameters other than LHF are responsible for producing decoupling.
Abstract
A 5-yr climatology of the meteorology, including boundary layer cloudiness, for the southeast Pacific region is presented using observations from a buoy located at 20°S, 85°W. The sea surface temperature and surface air temperature exhibit a sinusoidal seasonal cycle that is negatively correlated with surface pressure. The relative humidity, wind speed, and wind direction show little seasonal variability. But the advection of cold and dry air from the southeast varies seasonally and is highly correlated with the latent heat flux variations. A simple model was used to estimate the monthly cloud fraction using the observed surface downwelling longwave radiative flux and surface meteorological parameters. The annual cycle of cloud fraction is highly correlated to that of S. A. Klein: lower-tropospheric stability parameter (0.87), latent heat flux (−0.59), and temperature and moisture advection (0.60). The derived cloud fraction compares poorly with the International Satellite Cloud Climatology Project (ISCCP)-derived low-cloud cover but compares well (0.86 correlation) with ISCCP low- plus middle-cloud cover. The monthly averaged diurnal variations in cloud fraction show marked seasonal variability in the amplitude and temporal structure. The mean annual cloud fraction is lower than the mean annual nighttime cloud fraction by about 9%. Annual and diurnal cycles of surface longwave and shortwave cloud radiative forcing were also estimated. The longwave cloud radiative forcing is about 45 W m−2 year-round, but, because of highly negative shortwave cloud radiative forcing, the net cloud radiative forcing is always negative with an annual mean of −50 W m−2.
Abstract
A 5-yr climatology of the meteorology, including boundary layer cloudiness, for the southeast Pacific region is presented using observations from a buoy located at 20°S, 85°W. The sea surface temperature and surface air temperature exhibit a sinusoidal seasonal cycle that is negatively correlated with surface pressure. The relative humidity, wind speed, and wind direction show little seasonal variability. But the advection of cold and dry air from the southeast varies seasonally and is highly correlated with the latent heat flux variations. A simple model was used to estimate the monthly cloud fraction using the observed surface downwelling longwave radiative flux and surface meteorological parameters. The annual cycle of cloud fraction is highly correlated to that of S. A. Klein: lower-tropospheric stability parameter (0.87), latent heat flux (−0.59), and temperature and moisture advection (0.60). The derived cloud fraction compares poorly with the International Satellite Cloud Climatology Project (ISCCP)-derived low-cloud cover but compares well (0.86 correlation) with ISCCP low- plus middle-cloud cover. The monthly averaged diurnal variations in cloud fraction show marked seasonal variability in the amplitude and temporal structure. The mean annual cloud fraction is lower than the mean annual nighttime cloud fraction by about 9%. Annual and diurnal cycles of surface longwave and shortwave cloud radiative forcing were also estimated. The longwave cloud radiative forcing is about 45 W m−2 year-round, but, because of highly negative shortwave cloud radiative forcing, the net cloud radiative forcing is always negative with an annual mean of −50 W m−2.
Merged Cloud and Precipitation Dataset from the HIAPER GV for the Cloud System Evolution in the Trades (CSET) CampaignAbstract
The Cloud System Evolution in the Trades (CSET) aircraft campaign was conducted in the summer of 2015 in the northeast Pacific to observe the transition from stratocumulus to cumulus cloud regime. Fourteen transects were made between Sacramento, California, and Kona, Hawaii, using the NCAR’s High-Performance Instrumented Airborne Platform for Environmental Research (HIAPER) Gulfstream V (GV) aircraft. The HIAPER W-band Doppler cloud radar (HCR) and the high-spectral-resolution lidar (HSRL), in their first deployment together on board the GV, provided crucial cloud and precipitation observations. The HCR recorded the raw in-phase (I) and quadrature (Q) components of the digitized signal, from which the Doppler spectra and its first three moments were calculated. HCR/HSRL data were merged to develop a hydrometeor mask on a uniform georeferenced grid of 2-Hz temporal and 20-m vertical resolutions. The hydrometeors are classified as cloud or precipitation using a simple fuzzy logic technique based on the HCR mean Doppler velocity, HSRL backscatter, and the ratio of HCR reflectivity to HSRL backscatter. This is primarily applied during zenith-pointing conditions under which the lidar can detect the cloud base and the radar is more sensitive to clouds. The microphysical properties of below-cloud drizzle and optically thin clouds were retrieved using the HCR reflectivity, HSRL backscatter, and the HCR Doppler spectrum width after it is corrected for the aircraft speed. These indicate that as the boundary layers deepen and cloud-top heights increase toward the equator, both the cloud and rain fractions decrease.
Abstract
The Cloud System Evolution in the Trades (CSET) aircraft campaign was conducted in the summer of 2015 in the northeast Pacific to observe the transition from stratocumulus to cumulus cloud regime. Fourteen transects were made between Sacramento, California, and Kona, Hawaii, using the NCAR’s High-Performance Instrumented Airborne Platform for Environmental Research (HIAPER) Gulfstream V (GV) aircraft. The HIAPER W-band Doppler cloud radar (HCR) and the high-spectral-resolution lidar (HSRL), in their first deployment together on board the GV, provided crucial cloud and precipitation observations. The HCR recorded the raw in-phase (I) and quadrature (Q) components of the digitized signal, from which the Doppler spectra and its first three moments were calculated. HCR/HSRL data were merged to develop a hydrometeor mask on a uniform georeferenced grid of 2-Hz temporal and 20-m vertical resolutions. The hydrometeors are classified as cloud or precipitation using a simple fuzzy logic technique based on the HCR mean Doppler velocity, HSRL backscatter, and the ratio of HCR reflectivity to HSRL backscatter. This is primarily applied during zenith-pointing conditions under which the lidar can detect the cloud base and the radar is more sensitive to clouds. The microphysical properties of below-cloud drizzle and optically thin clouds were retrieved using the HCR reflectivity, HSRL backscatter, and the HCR Doppler spectrum width after it is corrected for the aircraft speed. These indicate that as the boundary layers deepen and cloud-top heights increase toward the equator, both the cloud and rain fractions decrease.
CHUVA, meaning “rain” in Portuguese, is the acronym for the Cloud Processes of the Main Precipitation Systems in Brazil: A Contribution to Cloud-Resolving Modeling and to the Global Precipitation Measurement (GPM). The CHUVA project has conducted five field campaigns; the sixth and last campaign will be held in Manaus in 2014. The primary scientific objective of CHUVA is to contribute to the understanding of cloud processes, which represent one of the least understood components of the weather and climate system. The five CHUVA campaigns were designed to investigate specific tropical weather regimes. The first two experiments, in Alcantara and Fortaleza in northeastern Brazil, focused on warm clouds. The third campaign, which was conducted in Belém, was dedicated to tropical squall lines that often form along the sea-breeze front. The fourth campaign was in the Vale do Paraiba of southeastern Brazil, which is a region with intense lightning activity. In addition to contributing to the understanding of cloud process evolution from storms to thunderstorms, this fourth campaign also provided a high-fidelity total lightning proxy dataset for the NOAA Geostationary Operational Environmental Satellite (GOES)-R program. The fifth campaign was carried out in Santa Maria, in southern Brazil, a region of intense hailstorms associated with frequent mesoscale convective complexes. This campaign employed a multimodel high-resolution ensemble experiment. The data collected from contrasting precipitation regimes in tropical continental regions allow the various cloud processes in diverse environments to be compared. Some examples of these previous experiments are presented to illustrate the variability of convection across the tropics.
CHUVA, meaning “rain” in Portuguese, is the acronym for the Cloud Processes of the Main Precipitation Systems in Brazil: A Contribution to Cloud-Resolving Modeling and to the Global Precipitation Measurement (GPM). The CHUVA project has conducted five field campaigns; the sixth and last campaign will be held in Manaus in 2014. The primary scientific objective of CHUVA is to contribute to the understanding of cloud processes, which represent one of the least understood components of the weather and climate system. The five CHUVA campaigns were designed to investigate specific tropical weather regimes. The first two experiments, in Alcantara and Fortaleza in northeastern Brazil, focused on warm clouds. The third campaign, which was conducted in Belém, was dedicated to tropical squall lines that often form along the sea-breeze front. The fourth campaign was in the Vale do Paraiba of southeastern Brazil, which is a region with intense lightning activity. In addition to contributing to the understanding of cloud process evolution from storms to thunderstorms, this fourth campaign also provided a high-fidelity total lightning proxy dataset for the NOAA Geostationary Operational Environmental Satellite (GOES)-R program. The fifth campaign was carried out in Santa Maria, in southern Brazil, a region of intense hailstorms associated with frequent mesoscale convective complexes. This campaign employed a multimodel high-resolution ensemble experiment. The data collected from contrasting precipitation regimes in tropical continental regions allow the various cloud processes in diverse environments to be compared. Some examples of these previous experiments are presented to illustrate the variability of convection across the tropics.
