Search Results
You are looking at 1 - 10 of 12 items for
- Author or Editor: Matthew Henry x
- All content x
Abstract
The Stefan–Boltzmann law governs the temperature dependence of the blackbody emission of radiation:
Abstract
The Stefan–Boltzmann law governs the temperature dependence of the blackbody emission of radiation:
Abstract
Diffusive energy balance models (EBMs) that use moist static energy, rather than temperature, as the thermodynamic variable to determine the energy transport provide an idealized framework to understand the pattern of radiatively forced surface warming. These models have a polar amplified warming pattern that is quantitatively similar to general circulation model simulations. Even without surface albedo changes or other spatially varying feedbacks, they simulate polar amplification that results from increased poleward energy transport with warming. Here, two estimates for polar amplification are presented that do not require numerical solution of the EBM governing equation. They are evaluated relative to the results of numerical moist EBM solutions. One estimate considers only changes in a moist thermodynamic quantity (assuming that the increase in energy transport results in a spatially uniform change in moist static energy in the warmed climate) and has more polar amplification than the EBM solution. The other estimate uses a new solution of a truncated form of the moist EBM equation, which allows for a temperature change that is consistent with both the dry and latent energy transport changes, as well as radiative changes. The truncated EBM solution provides an estimate for polar amplification that is nearly identical to that of the numerical EBM solution and only depends on the EBM parameters and climatology of temperature. This solution sheds light on the dependence of polar amplification on the climatological temperature distribution and offers an estimate of the residual polar warming in solar radiation management geoengineered climates.
Abstract
Diffusive energy balance models (EBMs) that use moist static energy, rather than temperature, as the thermodynamic variable to determine the energy transport provide an idealized framework to understand the pattern of radiatively forced surface warming. These models have a polar amplified warming pattern that is quantitatively similar to general circulation model simulations. Even without surface albedo changes or other spatially varying feedbacks, they simulate polar amplification that results from increased poleward energy transport with warming. Here, two estimates for polar amplification are presented that do not require numerical solution of the EBM governing equation. They are evaluated relative to the results of numerical moist EBM solutions. One estimate considers only changes in a moist thermodynamic quantity (assuming that the increase in energy transport results in a spatially uniform change in moist static energy in the warmed climate) and has more polar amplification than the EBM solution. The other estimate uses a new solution of a truncated form of the moist EBM equation, which allows for a temperature change that is consistent with both the dry and latent energy transport changes, as well as radiative changes. The truncated EBM solution provides an estimate for polar amplification that is nearly identical to that of the numerical EBM solution and only depends on the EBM parameters and climatology of temperature. This solution sheds light on the dependence of polar amplification on the climatological temperature distribution and offers an estimate of the residual polar warming in solar radiation management geoengineered climates.
Meso β-scale rawinsonde data from the Atmospheric Variability Experiment-Severe Environmental Storms and Mesoscale Experiment (AVE-SESAME) V period (20–21 May 1979) are used to diagnose atmospheric variability in the environment of a convective area. As the storms developed, temperatures increased in the upper stratosphere; however, cooling was observed nearer to the surface and in the lower stratosphere. Height rises above 400 mb produced a mesohigh over the convective area that was most pronounced near 200 mb. Weaker height falls occurred in the lower troposphere.
Wind patterns underwent especially interesting fluctuations. North of the convective area, upper-level winds increased significantly during storm development. Southeast of the convection, however, winds near 200 mb decreased approximately 50% during a 3 h period coinciding with the most active storms. On the other hand, winds at 400 mb almost doubled during the same 3 h period. Strong low-level convergence, upper-level divergence, and ascending motion developed after storm initiation.
Much more detailed study is required to understand this fascinating case. However, many of the current findings about the meso β-scale storm environment are consistent with those previously attributed to feedback mechanisms from severe thunderstorms.
Meso β-scale rawinsonde data from the Atmospheric Variability Experiment-Severe Environmental Storms and Mesoscale Experiment (AVE-SESAME) V period (20–21 May 1979) are used to diagnose atmospheric variability in the environment of a convective area. As the storms developed, temperatures increased in the upper stratosphere; however, cooling was observed nearer to the surface and in the lower stratosphere. Height rises above 400 mb produced a mesohigh over the convective area that was most pronounced near 200 mb. Weaker height falls occurred in the lower troposphere.
Wind patterns underwent especially interesting fluctuations. North of the convective area, upper-level winds increased significantly during storm development. Southeast of the convection, however, winds near 200 mb decreased approximately 50% during a 3 h period coinciding with the most active storms. On the other hand, winds at 400 mb almost doubled during the same 3 h period. Strong low-level convergence, upper-level divergence, and ascending motion developed after storm initiation.
Much more detailed study is required to understand this fascinating case. However, many of the current findings about the meso β-scale storm environment are consistent with those previously attributed to feedback mechanisms from severe thunderstorms.
Abstract
The authors develop a statistical guidance product, the tropical cyclone tornado parameter (TCTP), for forecasting the probability of one or more tornadoes during a 6-h period that are associated with landfalling tropical cyclones affecting the coastal Gulf of Mexico and the southern Atlantic coast. TCTP is designed to aid forecasters in a time-limited environment. TCTP provides a “quick look” at regions where forecasters can then conduct detailed analyses. The pool of potential predictors included tornado reports and tropical cyclone data between 2000 and 2008, as well as storm environmental parameters. The original pool of 28 potential predictors is reduced to six using stepwise regression and logistic regression. These six predictors are 0–3-km wind shear, 0–3-km storm relative helicity, azimuth angle of the tornado report from the tropical cyclone, distance from the cyclone’s center, time of day, and 950–1000-hPa convective available potential energy. Mean Brier scores and Brier skill scores are computed for the entire TCTP-dependent dataset and for corresponding forecasts produced by the Storm Prediction Center (SPC). TCTP then is applied to four individual cyclone cases to qualitatively and quantitatively assess the parameter and compare its performance with SPC forecasts. Results show that TCTP has skill at identifying regions of tornado potential. However, tornadoes in some tropical systems are overpredicted, but underpredicted in others. TCTP 6-h forecast periods provide slightly poorer statistical performance than the 1-day tornado probability forecasts from SPC, probably because the SPC product includes forecaster guidance and because their forecasts are valid for longer periods (24 h).
Abstract
The authors develop a statistical guidance product, the tropical cyclone tornado parameter (TCTP), for forecasting the probability of one or more tornadoes during a 6-h period that are associated with landfalling tropical cyclones affecting the coastal Gulf of Mexico and the southern Atlantic coast. TCTP is designed to aid forecasters in a time-limited environment. TCTP provides a “quick look” at regions where forecasters can then conduct detailed analyses. The pool of potential predictors included tornado reports and tropical cyclone data between 2000 and 2008, as well as storm environmental parameters. The original pool of 28 potential predictors is reduced to six using stepwise regression and logistic regression. These six predictors are 0–3-km wind shear, 0–3-km storm relative helicity, azimuth angle of the tornado report from the tropical cyclone, distance from the cyclone’s center, time of day, and 950–1000-hPa convective available potential energy. Mean Brier scores and Brier skill scores are computed for the entire TCTP-dependent dataset and for corresponding forecasts produced by the Storm Prediction Center (SPC). TCTP then is applied to four individual cyclone cases to qualitatively and quantitatively assess the parameter and compare its performance with SPC forecasts. Results show that TCTP has skill at identifying regions of tornado potential. However, tornadoes in some tropical systems are overpredicted, but underpredicted in others. TCTP 6-h forecast periods provide slightly poorer statistical performance than the 1-day tornado probability forecasts from SPC, probably because the SPC product includes forecaster guidance and because their forecasts are valid for longer periods (24 h).
Abstract
An area of intense thunderstorms occurred within the special rawinsonde network collecting data on 20–21 May 1979, the fifth day of the Atmospheric Variability Experiment-Severe Environmental Storms and Mesoscale Experiment (AVE-SESAME). The data are at the meso β-scale, i.e., 75 km spacing and 3 or 1.5 h intervals. They are used to perform a kinetic energy analysis of the near storm environment. The mesoscale storm environment is characterized by cross-contour generation of kinetic energy, transfers of energy to nonresolvable scales of motion (negative dissipation), horizontal flux divergence and upward transport of energy. These processes are maximized within the upper troposphere and are greatest during times of strongest convection. Current mesoscale values are much larger than previous results based on synoptic-scale data.
Energy budgets are obtained at 3 h intervals from the routine National Weather Service rawinsonde network. A comparison of results from the same analysis region, but derived from the two different resolutions, reveals several common features. Complex vertical variations in winds (energy) over southeastern Oklahoma are also examined in detail. Motions not detected by the meso β-scale input data appera to play an important role in the energy balance of some layers. A sensitivity analysis is presented to quantify uncertainties in the energy budget terms.
Abstract
An area of intense thunderstorms occurred within the special rawinsonde network collecting data on 20–21 May 1979, the fifth day of the Atmospheric Variability Experiment-Severe Environmental Storms and Mesoscale Experiment (AVE-SESAME). The data are at the meso β-scale, i.e., 75 km spacing and 3 or 1.5 h intervals. They are used to perform a kinetic energy analysis of the near storm environment. The mesoscale storm environment is characterized by cross-contour generation of kinetic energy, transfers of energy to nonresolvable scales of motion (negative dissipation), horizontal flux divergence and upward transport of energy. These processes are maximized within the upper troposphere and are greatest during times of strongest convection. Current mesoscale values are much larger than previous results based on synoptic-scale data.
Energy budgets are obtained at 3 h intervals from the routine National Weather Service rawinsonde network. A comparison of results from the same analysis region, but derived from the two different resolutions, reveals several common features. Complex vertical variations in winds (energy) over southeastern Oklahoma are also examined in detail. Motions not detected by the meso β-scale input data appera to play an important role in the energy balance of some layers. A sensitivity analysis is presented to quantify uncertainties in the energy budget terms.
Abstract
The precise mechanisms driving Arctic amplification are still under debate. Previous attribution methods compute the vertically uniform temperature change required to balance the top-of-atmosphere energy imbalance caused by each forcing and feedback, with any departures from vertically uniform warming collected into the lapse-rate feedback. We propose an alternative attribution method using a single-column model that accounts for the forcing dependence of high-latitude lapse-rate changes. We examine this method in an idealized general circulation model (GCM), finding that, even though the column-integrated carbon dioxide (CO2) forcing and water vapor feedback are stronger in the tropics, they contribute to polar-amplified surface warming as they produce bottom-heavy warming in high latitudes. A separation of atmospheric temperature changes into local and remote contributors shows that, in the absence of polar surface forcing (e.g., sea ice retreat), changes in energy transport are primarily responsible for the polar-amplified pattern of warming. The addition of surface forcing substantially increases polar surface warming and reduces the contribution of atmospheric dry static energy transport to the warming. This physically based attribution method can be applied to comprehensive GCMs to provide a clearer view of the mechanisms behind Arctic amplification.
Abstract
The precise mechanisms driving Arctic amplification are still under debate. Previous attribution methods compute the vertically uniform temperature change required to balance the top-of-atmosphere energy imbalance caused by each forcing and feedback, with any departures from vertically uniform warming collected into the lapse-rate feedback. We propose an alternative attribution method using a single-column model that accounts for the forcing dependence of high-latitude lapse-rate changes. We examine this method in an idealized general circulation model (GCM), finding that, even though the column-integrated carbon dioxide (CO2) forcing and water vapor feedback are stronger in the tropics, they contribute to polar-amplified surface warming as they produce bottom-heavy warming in high latitudes. A separation of atmospheric temperature changes into local and remote contributors shows that, in the absence of polar surface forcing (e.g., sea ice retreat), changes in energy transport are primarily responsible for the polar-amplified pattern of warming. The addition of surface forcing substantially increases polar surface warming and reduces the contribution of atmospheric dry static energy transport to the warming. This physically based attribution method can be applied to comprehensive GCMs to provide a clearer view of the mechanisms behind Arctic amplification.
Abstract
The influence of the Laurentian Great Lakes on the climate of surrounding regions is significant, especially in leeward settings where lake-effect snowfall occurs. Heavy lake-effect snow represents a potential natural hazard and plays important roles in winter recreational activities, agriculture, and regional hydrology. Changes in lake-effect snowfall may represent a regional-scale manifestation of hemispheric-scale climate change, such as that associated with global warming. This study examines records of snowfall from several lake-effect and non-lake-effect sites throughout most of the twentieth century in order to 1) determine whether differences in snowfall trends exist between these settings and 2) offer possible linkages between lake-effect snow trends and records of air temperature, water temperature, and ice cover. A new, historic record of oxygen isotope [δ
18O
Abstract
The influence of the Laurentian Great Lakes on the climate of surrounding regions is significant, especially in leeward settings where lake-effect snowfall occurs. Heavy lake-effect snow represents a potential natural hazard and plays important roles in winter recreational activities, agriculture, and regional hydrology. Changes in lake-effect snowfall may represent a regional-scale manifestation of hemispheric-scale climate change, such as that associated with global warming. This study examines records of snowfall from several lake-effect and non-lake-effect sites throughout most of the twentieth century in order to 1) determine whether differences in snowfall trends exist between these settings and 2) offer possible linkages between lake-effect snow trends and records of air temperature, water temperature, and ice cover. A new, historic record of oxygen isotope [δ
18O
Abstract
During April 2007, a coordinated series of snow measurements was made across the Northwest Territories and Nunavut, Canada, during a snowmobile traverse from Fairbanks, Alaska, to Baker Lake, Nunavut. The purpose of the measurements was to document the general nature of the snowpack across this region for the evaluation of satellite- and model-derived estimates of snow water equivalent (SWE). Although detailed, local snow measurements have been made as part of ongoing studies at tundra field sites (e.g., Daring Lake and Trail Valley Creek in the Northwest Territories; Toolik Lake and the Kuparak River basin in Alaska), systematic measurements at the regional scale have not been previously collected across this region of northern Canada. The snow cover consisted of depth hoar and wind slab with small and ephemeral fractions of new, recent, and icy snow. The snow was shallow (<40 cm deep), usually with fewer than six layers. Where snow was deposited on lake and river ice, it was shallower, denser, and more metamorphosed than where it was deposited on tundra. Although highly variable locally, no longitudinal gradients in snow distribution, magnitude, or structure were detected. This regional homogeneity allowed us to identify that the observed spatial variability in passive microwave brightness temperatures was related to subgrid fractional lake cover. Correlation analysis between lake fraction and Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) brightness temperature showed frequency dependent, seasonally evolving relationships consistent with lake ice drivers. Simulations of lake ice thickness and snow depth on lake ice produced from the Canadian Lake Ice Model (CLIMo) indicated that at low frequencies (6.9, 10.7 GHz), correlations with lake fraction were consistent through the winter season, whereas at higher frequencies (18.7, 36.5 GHz), the strength and direction of the correlations evolved consistently with the penetration depth as the influence of the subice water was replaced by emissions from the ice and snowpack. A regional rain-on-snow event created a surface ice lens that was detectable using the AMSR-E 36.5-GHz polarization gradient due to a strong response at the horizontal polarization. The appropriate polarization for remote sensing of the tundra snowpack depends on the application: horizontal measurements are suitable for ice lens detection; vertically polarized measurements are appropriate for deriving SWE estimates.
Abstract
During April 2007, a coordinated series of snow measurements was made across the Northwest Territories and Nunavut, Canada, during a snowmobile traverse from Fairbanks, Alaska, to Baker Lake, Nunavut. The purpose of the measurements was to document the general nature of the snowpack across this region for the evaluation of satellite- and model-derived estimates of snow water equivalent (SWE). Although detailed, local snow measurements have been made as part of ongoing studies at tundra field sites (e.g., Daring Lake and Trail Valley Creek in the Northwest Territories; Toolik Lake and the Kuparak River basin in Alaska), systematic measurements at the regional scale have not been previously collected across this region of northern Canada. The snow cover consisted of depth hoar and wind slab with small and ephemeral fractions of new, recent, and icy snow. The snow was shallow (<40 cm deep), usually with fewer than six layers. Where snow was deposited on lake and river ice, it was shallower, denser, and more metamorphosed than where it was deposited on tundra. Although highly variable locally, no longitudinal gradients in snow distribution, magnitude, or structure were detected. This regional homogeneity allowed us to identify that the observed spatial variability in passive microwave brightness temperatures was related to subgrid fractional lake cover. Correlation analysis between lake fraction and Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) brightness temperature showed frequency dependent, seasonally evolving relationships consistent with lake ice drivers. Simulations of lake ice thickness and snow depth on lake ice produced from the Canadian Lake Ice Model (CLIMo) indicated that at low frequencies (6.9, 10.7 GHz), correlations with lake fraction were consistent through the winter season, whereas at higher frequencies (18.7, 36.5 GHz), the strength and direction of the correlations evolved consistently with the penetration depth as the influence of the subice water was replaced by emissions from the ice and snowpack. A regional rain-on-snow event created a surface ice lens that was detectable using the AMSR-E 36.5-GHz polarization gradient due to a strong response at the horizontal polarization. The appropriate polarization for remote sensing of the tundra snowpack depends on the application: horizontal measurements are suitable for ice lens detection; vertically polarized measurements are appropriate for deriving SWE estimates.
Abstract
Hurricane Lane (2018) was an impactful event for the Hawaiian Islands and provided a textbook example of the compounding hazards that can be produced from a single storm. Over a 4-day period, the island of Hawaiʻi received an island-wide average of 424 mm (17 in.) of rainfall, with a 4-day single-station maximum of 1,444 mm (57 in.), making Hurricane Lane the wettest tropical cyclone ever recorded in Hawaiʻi (based on all available quantitative records). Simultaneously, fires on the islands of nearby Maui and Oʻahu burned 1,043 ha (2,577 ac) and 162 ha (400 ac), respectively. Land-use characteristics and antecedent moisture conditions exacerbated fire hazard, and both fire and rain severity were influenced by the storm environment and local topographical features. Broadscale subsidence around the storm periphery and downslope winds resulted in dry and windy conditions conducive to fire, while in a different region of the same storm, preexisting convection, incredibly moist atmospheric conditions, and upslope flow brought intense, long-duration rainfall. The simultaneous occurrence of rain-driven flooding and landslides, high-intensity winds, and multiple fires complicated emergency response. The compounding nature of the hazards produced during the Hurricane Lane event highlights the need to improve anticipation of complex feedback mechanisms among climate- and weather-related phenomena.
Abstract
Hurricane Lane (2018) was an impactful event for the Hawaiian Islands and provided a textbook example of the compounding hazards that can be produced from a single storm. Over a 4-day period, the island of Hawaiʻi received an island-wide average of 424 mm (17 in.) of rainfall, with a 4-day single-station maximum of 1,444 mm (57 in.), making Hurricane Lane the wettest tropical cyclone ever recorded in Hawaiʻi (based on all available quantitative records). Simultaneously, fires on the islands of nearby Maui and Oʻahu burned 1,043 ha (2,577 ac) and 162 ha (400 ac), respectively. Land-use characteristics and antecedent moisture conditions exacerbated fire hazard, and both fire and rain severity were influenced by the storm environment and local topographical features. Broadscale subsidence around the storm periphery and downslope winds resulted in dry and windy conditions conducive to fire, while in a different region of the same storm, preexisting convection, incredibly moist atmospheric conditions, and upslope flow brought intense, long-duration rainfall. The simultaneous occurrence of rain-driven flooding and landslides, high-intensity winds, and multiple fires complicated emergency response. The compounding nature of the hazards produced during the Hurricane Lane event highlights the need to improve anticipation of complex feedback mechanisms among climate- and weather-related phenomena.