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Abstract
Hurricane intensity forecasting has lagged far behind the forecasting of hurricane track. In an effort to improve the understanding of the hurricane intensity dilemma, several attempts have been made to compute an upper bound on the intensity of tropical cyclones. This paper investigates the strides made into determining the maximum intensity of hurricanes. Concentrating on the most recent attempts to understand the maximum intensity problem, the theories of Holland and Emanuel are reviewed with the objective of assessing their validity in real tropical cyclones. Each theory is then tested using both observations and the axisymmetric hurricane numerical models of Ooyama and Emanuel.
It is found that ambient convective instability plays a minor role in the determination of the maximum intensity and that the Emanuel model is the closest to providing a useful calculation of maximum intensity. Several shortcomings are revealed in Emanuel's theory, however, showing the need for more basic research on the axisymmetric and asymmetric dynamics of hurricanes. As an illustration of the importance of asymmetric vorticity dynamics in the determination of a hurricane's maximum intensity it is shown, using Ooyama's hurricane model, that the maximum intensity of a tropical cyclone may be diminished by convectively generated vorticity anomolies excited outside the primary eyewall. The vorticity anomolies are parameterized by adding a concentric ring of vorticity outside the primary eyewall that acts to cut off its supply of angular momentum and moist enthalpy. It is suggested that the generation of vorticity rings (or bands) outside the primary eyewall is a major reason why tropical cyclones fail to attain their maximum intensity even in an otherwise favorable environment.
The upshot of this work points to the need for obtaining a more complete understanding of asymmetric vorticity processes in hurricanes and their coupling to the boundary layer and convection.
Abstract
Hurricane intensity forecasting has lagged far behind the forecasting of hurricane track. In an effort to improve the understanding of the hurricane intensity dilemma, several attempts have been made to compute an upper bound on the intensity of tropical cyclones. This paper investigates the strides made into determining the maximum intensity of hurricanes. Concentrating on the most recent attempts to understand the maximum intensity problem, the theories of Holland and Emanuel are reviewed with the objective of assessing their validity in real tropical cyclones. Each theory is then tested using both observations and the axisymmetric hurricane numerical models of Ooyama and Emanuel.
It is found that ambient convective instability plays a minor role in the determination of the maximum intensity and that the Emanuel model is the closest to providing a useful calculation of maximum intensity. Several shortcomings are revealed in Emanuel's theory, however, showing the need for more basic research on the axisymmetric and asymmetric dynamics of hurricanes. As an illustration of the importance of asymmetric vorticity dynamics in the determination of a hurricane's maximum intensity it is shown, using Ooyama's hurricane model, that the maximum intensity of a tropical cyclone may be diminished by convectively generated vorticity anomolies excited outside the primary eyewall. The vorticity anomolies are parameterized by adding a concentric ring of vorticity outside the primary eyewall that acts to cut off its supply of angular momentum and moist enthalpy. It is suggested that the generation of vorticity rings (or bands) outside the primary eyewall is a major reason why tropical cyclones fail to attain their maximum intensity even in an otherwise favorable environment.
The upshot of this work points to the need for obtaining a more complete understanding of asymmetric vorticity processes in hurricanes and their coupling to the boundary layer and convection.
Abstract
Bistatic dual-polarization radar parameters at S- and C-band frequencies are simulated for rain and hail. The goal is to determine their potential for discriminating the two precipitation types and for estimating the parameters of an exponential size distribution for hail. Raindrops and hailstones are modeled as oblate spheroids with canting distributions representing their fall behavior. Three hailstone composition models are used to illustrate the effects of melting. Most of the bistatic radar parameters are significantly affected by the amount of liquid water in the hailstones, which may prove useful in determining the melting level from the vertical profiles of these parameters. For single-polarized transmission, such as vertical (v) or horizontal (h) polarization, the four bistatic radar parameters of interest are effective reflectivity factor (Z v or Z h), bistatic-to-backscattering reflectivity ratio (BBRv or BBRh), linear depolarization ratio (LDRv or LDRh), and magnitude of the correlation coefficient between the co- and cross-polarized signals (ρ v or ρ h). If the transmission is dual polarized, then in addition to these two sets of parameters, the bistatic differential reflectivity (Z DR) and the magnitude of the copolarized correlation coefficient (ρ hv) will be available. For low elevation angles of the transmitter and receiver the parameters resulting from h-polarized transmission may be difficult to measure near the bistatic azimuth angle of 90° due to very low signal levels. This may not be an issue for precipitation involving large hailstones.
When parameter pairs such as (LDRv, ρ v) and (BBRv, Z v) are plotted, it is observed that rain and hail tend to cluster in different regions on these planes. This indicates a potential for using bistatic radar parameters for differentiating rain from hail. Similar pairs are possible for h-polarization. Various other combinations of these parameters lead to similar results. The use of more than one pair of parameters and/or several bistatic receiver locations should enhance the level of confidence in the discrimination process. It should also be noted that in some cases there are regions on these planes where rain and hail overlap and discrimination may not always be possible.
Other than Z v and Z h, all of the bistatic radar parameters mentioned above are in the form of ratios. As a result, given an exponential size distribution, N 0 exp(−3.67D/D 0), they depend only on the median volume diameter D 0 and not on N 0. Assuming that the amount of liquid water and ice in the composition of the hailstones are known, the ratio parameters may be used for estimating D 0. However, among these parameters only BBRv and BBRh are negligibly affected by variations in the axial ratio and the mean orientation of hailstones, making them preferable for D 0 estimation. Once D 0 is obtained, N 0 may be estimated using Z v or Z h.
Abstract
Bistatic dual-polarization radar parameters at S- and C-band frequencies are simulated for rain and hail. The goal is to determine their potential for discriminating the two precipitation types and for estimating the parameters of an exponential size distribution for hail. Raindrops and hailstones are modeled as oblate spheroids with canting distributions representing their fall behavior. Three hailstone composition models are used to illustrate the effects of melting. Most of the bistatic radar parameters are significantly affected by the amount of liquid water in the hailstones, which may prove useful in determining the melting level from the vertical profiles of these parameters. For single-polarized transmission, such as vertical (v) or horizontal (h) polarization, the four bistatic radar parameters of interest are effective reflectivity factor (Z v or Z h), bistatic-to-backscattering reflectivity ratio (BBRv or BBRh), linear depolarization ratio (LDRv or LDRh), and magnitude of the correlation coefficient between the co- and cross-polarized signals (ρ v or ρ h). If the transmission is dual polarized, then in addition to these two sets of parameters, the bistatic differential reflectivity (Z DR) and the magnitude of the copolarized correlation coefficient (ρ hv) will be available. For low elevation angles of the transmitter and receiver the parameters resulting from h-polarized transmission may be difficult to measure near the bistatic azimuth angle of 90° due to very low signal levels. This may not be an issue for precipitation involving large hailstones.
When parameter pairs such as (LDRv, ρ v) and (BBRv, Z v) are plotted, it is observed that rain and hail tend to cluster in different regions on these planes. This indicates a potential for using bistatic radar parameters for differentiating rain from hail. Similar pairs are possible for h-polarization. Various other combinations of these parameters lead to similar results. The use of more than one pair of parameters and/or several bistatic receiver locations should enhance the level of confidence in the discrimination process. It should also be noted that in some cases there are regions on these planes where rain and hail overlap and discrimination may not always be possible.
Other than Z v and Z h, all of the bistatic radar parameters mentioned above are in the form of ratios. As a result, given an exponential size distribution, N 0 exp(−3.67D/D 0), they depend only on the median volume diameter D 0 and not on N 0. Assuming that the amount of liquid water and ice in the composition of the hailstones are known, the ratio parameters may be used for estimating D 0. However, among these parameters only BBRv and BBRh are negligibly affected by variations in the axial ratio and the mean orientation of hailstones, making them preferable for D 0 estimation. Once D 0 is obtained, N 0 may be estimated using Z v or Z h.
Abstract
The presence of low-lying stratocumulus clouds and fog has been known to modify biophysical and ecological properties in coastal California where forests are frequently shaded by low-lying clouds or immersed in fog during otherwise warm and dry summer months. Summer fog and stratus can ameliorate summer drought stress and enhance soil water budgets and often have different spatial and temporal patterns. Here, this study uses remote sensing datasets to characterize the spatial and temporal patterns of cloud cover over California’s northern Channel Islands. The authors found marine stratus to be persistent from May to September across the years 2001–12. Stratus clouds were both most frequent and had the greatest spatial extent in July. Clouds typically formed in the evening and dissipated by the following early afternoon. This study presents a novel method to downscale satellite imagery using atmospheric observations and discriminate patterns of fog from those of stratus and help explain patterns of fog deposition previously studied on the islands. The outcomes of this study contribute significantly to the ability to quantify the occurrence of coastal fog at biologically meaningful spatial and temporal scales that can improve the understanding of cloud–ecosystem interactions, species distributions, and coastal ecohydrology.
Abstract
The presence of low-lying stratocumulus clouds and fog has been known to modify biophysical and ecological properties in coastal California where forests are frequently shaded by low-lying clouds or immersed in fog during otherwise warm and dry summer months. Summer fog and stratus can ameliorate summer drought stress and enhance soil water budgets and often have different spatial and temporal patterns. Here, this study uses remote sensing datasets to characterize the spatial and temporal patterns of cloud cover over California’s northern Channel Islands. The authors found marine stratus to be persistent from May to September across the years 2001–12. Stratus clouds were both most frequent and had the greatest spatial extent in July. Clouds typically formed in the evening and dissipated by the following early afternoon. This study presents a novel method to downscale satellite imagery using atmospheric observations and discriminate patterns of fog from those of stratus and help explain patterns of fog deposition previously studied on the islands. The outcomes of this study contribute significantly to the ability to quantify the occurrence of coastal fog at biologically meaningful spatial and temporal scales that can improve the understanding of cloud–ecosystem interactions, species distributions, and coastal ecohydrology.
Abstract
The low-resolution version of the Community Climate System Model, version 4 (CCSM4) is a computationally efficient alternative to the intermediate and standard resolution versions of this fully coupled climate system model. It employs an atmospheric horizontal grid of 3.75° × 3.75° and 26 levels in the vertical with a spectral dynamical core (T31) and an oceanic horizontal grid that consists of a nominal 3° resolution with 60 levels in the vertical. This low-resolution version (T31x3) can be used for a variety of applications including long equilibrium simulations, development work, and sensitivity studies. The T31x3 model is validated for modern conditions by comparing to available observations. Significant problems exist for Northern Hemisphere Arctic locales where sea ice extent and thickness are excessive. This is partially due to low heat transport in T31x3, which translates into a globally averaged sea surface temperature (SST) bias of −1.54°C compared to observational estimates from the 1870–99 historical record and a bias of −1.26°C compared to observations from the 1986–2005 historical record. Maximum zonal wind stress magnitude in the Southern Hemisphere matches observational estimates over the ocean, although its placement is incorrectly displaced equatorward. Aspects of climate variability in T31x3 compare to observed variability, especially so for ENSO where the amplitude and period approximate observations. T31x3 surface temperature anomaly trends for the twentieth century also follow observations. An examination of the T31x3 model relative to the intermediate CCSM4 resolution (finite volume dynamical core 1.9° × 2.5°) for preindustrial conditions shows the T31x3 model approximates this solution for climate state and variability metrics examined here.
Abstract
The low-resolution version of the Community Climate System Model, version 4 (CCSM4) is a computationally efficient alternative to the intermediate and standard resolution versions of this fully coupled climate system model. It employs an atmospheric horizontal grid of 3.75° × 3.75° and 26 levels in the vertical with a spectral dynamical core (T31) and an oceanic horizontal grid that consists of a nominal 3° resolution with 60 levels in the vertical. This low-resolution version (T31x3) can be used for a variety of applications including long equilibrium simulations, development work, and sensitivity studies. The T31x3 model is validated for modern conditions by comparing to available observations. Significant problems exist for Northern Hemisphere Arctic locales where sea ice extent and thickness are excessive. This is partially due to low heat transport in T31x3, which translates into a globally averaged sea surface temperature (SST) bias of −1.54°C compared to observational estimates from the 1870–99 historical record and a bias of −1.26°C compared to observations from the 1986–2005 historical record. Maximum zonal wind stress magnitude in the Southern Hemisphere matches observational estimates over the ocean, although its placement is incorrectly displaced equatorward. Aspects of climate variability in T31x3 compare to observed variability, especially so for ENSO where the amplitude and period approximate observations. T31x3 surface temperature anomaly trends for the twentieth century also follow observations. An examination of the T31x3 model relative to the intermediate CCSM4 resolution (finite volume dynamical core 1.9° × 2.5°) for preindustrial conditions shows the T31x3 model approximates this solution for climate state and variability metrics examined here.
Abstract
In 2011, exceptionally low atmospheric moisture content combined with moderately high temperatures to produce a record-high vapor pressure deficit (VPD) in the southwestern United States (SW). These conditions combined with record-low cold-season precipitation to cause widespread drought and extreme wildfires. Although interannual VPD variability is generally dominated by temperature, high VPD in 2011 was also driven by a lack of atmospheric moisture. The May–July 2011 dewpoint in the SW was 4.5 standard deviations below the long-term mean. Lack of atmospheric moisture was promoted by already very dry soils and amplified by a strong ocean-to-continent sea level pressure gradient and upper-level convergence that drove dry northerly winds and subsidence upwind of and over the SW. Subsidence drove divergence of rapid and dry surface winds over the SW, suppressing southerly moisture imports and removing moisture from already dry soils. Model projections developed for the fifth phase of the Coupled Model Intercomparison Project (CMIP5) suggest that by the 2050s warming trends will cause mean warm-season VPD to be comparable to the record-high VPD observed in 2011. CMIP5 projections also suggest increased interannual variability of VPD, independent of trends in background mean levels, as a result of increased variability of dewpoint, temperature, vapor pressure, and saturation vapor pressure. Increased variability in VPD translates to increased probability of 2011-type VPD anomalies, which would be superimposed on ever-greater background VPD levels. Although temperature will continue to be the primary driver of interannual VPD variability, 2011 served as an important reminder that atmospheric moisture content can also drive impactful VPD anomalies.
Abstract
In 2011, exceptionally low atmospheric moisture content combined with moderately high temperatures to produce a record-high vapor pressure deficit (VPD) in the southwestern United States (SW). These conditions combined with record-low cold-season precipitation to cause widespread drought and extreme wildfires. Although interannual VPD variability is generally dominated by temperature, high VPD in 2011 was also driven by a lack of atmospheric moisture. The May–July 2011 dewpoint in the SW was 4.5 standard deviations below the long-term mean. Lack of atmospheric moisture was promoted by already very dry soils and amplified by a strong ocean-to-continent sea level pressure gradient and upper-level convergence that drove dry northerly winds and subsidence upwind of and over the SW. Subsidence drove divergence of rapid and dry surface winds over the SW, suppressing southerly moisture imports and removing moisture from already dry soils. Model projections developed for the fifth phase of the Coupled Model Intercomparison Project (CMIP5) suggest that by the 2050s warming trends will cause mean warm-season VPD to be comparable to the record-high VPD observed in 2011. CMIP5 projections also suggest increased interannual variability of VPD, independent of trends in background mean levels, as a result of increased variability of dewpoint, temperature, vapor pressure, and saturation vapor pressure. Increased variability in VPD translates to increased probability of 2011-type VPD anomalies, which would be superimposed on ever-greater background VPD levels. Although temperature will continue to be the primary driver of interannual VPD variability, 2011 served as an important reminder that atmospheric moisture content can also drive impactful VPD anomalies.
Abstract
Cool- and warm-season precipitation totals have been reconstructed on a gridded basis for North America using 439 tree-ring chronologies correlated with December–April totals and 547 different chronologies correlated with May–July totals. These discrete seasonal chronologies are not significantly correlated with the alternate season; the December–April reconstructions are skillful over most of the southern and western United States and north-central Mexico, and the May–July estimates have skill over most of the United States, southwestern Canada, and northeastern Mexico. Both the strong continent-wide El Niño–Southern Oscillation (ENSO) signal embedded in the cool-season reconstructions and the Arctic Oscillation signal registered by the warm-season estimates faithfully reproduce the sign, intensity, and spatial patterns of these ocean–atmospheric influences on North American precipitation as recorded with instrumental data. The reconstructions are included in the North American Seasonal Precipitation Atlas (NASPA) and provide insight into decadal droughts and pluvials. They indicate that the sixteenth-century megadrought, the most severe and sustained North American drought of the past 500 years, was the combined result of three distinct seasonal droughts, each bearing unique spatial patterns potentially associated with seasonal forcing from ENSO, the Arctic Oscillation, and the Atlantic multidecadal oscillation. Significant 200–500-yr-long trends toward increased precipitation have been detected in the cool- and warm-season reconstructions for eastern North America. These seasonal precipitation changes appear to be part of the positive moisture trend measured in other paleoclimate proxies for the eastern area that began as a result of natural forcing before the industrial revolution and may have recently been enhanced by anthropogenic climate change.
Abstract
Cool- and warm-season precipitation totals have been reconstructed on a gridded basis for North America using 439 tree-ring chronologies correlated with December–April totals and 547 different chronologies correlated with May–July totals. These discrete seasonal chronologies are not significantly correlated with the alternate season; the December–April reconstructions are skillful over most of the southern and western United States and north-central Mexico, and the May–July estimates have skill over most of the United States, southwestern Canada, and northeastern Mexico. Both the strong continent-wide El Niño–Southern Oscillation (ENSO) signal embedded in the cool-season reconstructions and the Arctic Oscillation signal registered by the warm-season estimates faithfully reproduce the sign, intensity, and spatial patterns of these ocean–atmospheric influences on North American precipitation as recorded with instrumental data. The reconstructions are included in the North American Seasonal Precipitation Atlas (NASPA) and provide insight into decadal droughts and pluvials. They indicate that the sixteenth-century megadrought, the most severe and sustained North American drought of the past 500 years, was the combined result of three distinct seasonal droughts, each bearing unique spatial patterns potentially associated with seasonal forcing from ENSO, the Arctic Oscillation, and the Atlantic multidecadal oscillation. Significant 200–500-yr-long trends toward increased precipitation have been detected in the cool- and warm-season reconstructions for eastern North America. These seasonal precipitation changes appear to be part of the positive moisture trend measured in other paleoclimate proxies for the eastern area that began as a result of natural forcing before the industrial revolution and may have recently been enhanced by anthropogenic climate change.
Abstract
The Arctic is warming at more than twice the rate of the global average. This warming is influenced by clouds, which modulate the solar and terrestrial radiative fluxes and, thus, determine the surface energy budget. However, the interactions among clouds, aerosols, and radiative fluxes in the Arctic are still poorly understood. To address these uncertainties, the Ny-Ålesund Aerosol Cloud Experiment (NASCENT) study was conducted from September 2019 to August 2020 in Ny-Ålesund, Svalbard. The campaign’s primary goal was to elucidate the life cycle of aerosols in the Arctic and to determine how they modulate cloud properties throughout the year. In situ and remote sensing observations were taken on the ground at sea level, at a mountaintop station, and with a tethered balloon system. An overview of the meteorological and the main aerosol seasonality encountered during the NASCENT year is introduced, followed by a presentation of first scientific highlights. In particular, we present new findings on aerosol physicochemical and molecular properties. Further, the role of cloud droplet activation and ice crystal nucleation in the formation and persistence of mixed-phase clouds, and the occurrence of secondary ice processes, are discussed and compared to the representation of cloud processes within the regional Weather Research and Forecasting Model. The paper concludes with research questions that are to be addressed in upcoming NASCENT publications.
Abstract
The Arctic is warming at more than twice the rate of the global average. This warming is influenced by clouds, which modulate the solar and terrestrial radiative fluxes and, thus, determine the surface energy budget. However, the interactions among clouds, aerosols, and radiative fluxes in the Arctic are still poorly understood. To address these uncertainties, the Ny-Ålesund Aerosol Cloud Experiment (NASCENT) study was conducted from September 2019 to August 2020 in Ny-Ålesund, Svalbard. The campaign’s primary goal was to elucidate the life cycle of aerosols in the Arctic and to determine how they modulate cloud properties throughout the year. In situ and remote sensing observations were taken on the ground at sea level, at a mountaintop station, and with a tethered balloon system. An overview of the meteorological and the main aerosol seasonality encountered during the NASCENT year is introduced, followed by a presentation of first scientific highlights. In particular, we present new findings on aerosol physicochemical and molecular properties. Further, the role of cloud droplet activation and ice crystal nucleation in the formation and persistence of mixed-phase clouds, and the occurrence of secondary ice processes, are discussed and compared to the representation of cloud processes within the regional Weather Research and Forecasting Model. The paper concludes with research questions that are to be addressed in upcoming NASCENT publications.
