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- Author or Editor: Christopher R. Williams x
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Abstract
Cumulus parameterizations in general circulation models (GCMs) frequently apply mass-flux schemes in their description of tropical convection. Mass flux constitutes the product of the fractional area covered by cumulus clouds in a model grid box and the vertical velocity within the cumulus clouds. The cumulus area fraction profiles can be derived from precipitating radar reflectivity volumes. However, the vertical velocities are difficult to observe, making the evaluation of mass-flux schemes difficult. In this paper, the authors develop and evaluate a parameterization of vertical velocity in convective (cumulus) clouds using only radar reflectivities collected by a C-band polarimetric research radar (CPOL), operating at Darwin, Australia. The parameterization is trained using vertical velocity retrievals from a dual-frequency wind profiler pair located within the field of view of CPOL. The parametric model uses two inputs derived from CPOL reflectivities: the 0-dBZ echo-top height (0-dBZ ETH) and a height-weighted column reflectivity index (Z HWT). The 0-dBZ ETH determines the shape of the vertical velocity profile, while Z HWT determines its strength. The evaluation of these parameterized vertical velocities using (i) the training dataset, (ii) an independent wind-profiler-based dataset, and (iii) 1 month of dual-Doppler vertical velocity retrievals indicates that the statistical representation of vertical velocity is reasonably accurate up to the 75th percentile. However, the parametric model underestimates the extreme velocities. The method allows for the derivation of cumulus mass flux and its variability on current GCM scales based only on reflectivities from precipitating radar, which could be valuable to modelers.
Abstract
Cumulus parameterizations in general circulation models (GCMs) frequently apply mass-flux schemes in their description of tropical convection. Mass flux constitutes the product of the fractional area covered by cumulus clouds in a model grid box and the vertical velocity within the cumulus clouds. The cumulus area fraction profiles can be derived from precipitating radar reflectivity volumes. However, the vertical velocities are difficult to observe, making the evaluation of mass-flux schemes difficult. In this paper, the authors develop and evaluate a parameterization of vertical velocity in convective (cumulus) clouds using only radar reflectivities collected by a C-band polarimetric research radar (CPOL), operating at Darwin, Australia. The parameterization is trained using vertical velocity retrievals from a dual-frequency wind profiler pair located within the field of view of CPOL. The parametric model uses two inputs derived from CPOL reflectivities: the 0-dBZ echo-top height (0-dBZ ETH) and a height-weighted column reflectivity index (Z HWT). The 0-dBZ ETH determines the shape of the vertical velocity profile, while Z HWT determines its strength. The evaluation of these parameterized vertical velocities using (i) the training dataset, (ii) an independent wind-profiler-based dataset, and (iii) 1 month of dual-Doppler vertical velocity retrievals indicates that the statistical representation of vertical velocity is reasonably accurate up to the 75th percentile. However, the parametric model underestimates the extreme velocities. The method allows for the derivation of cumulus mass flux and its variability on current GCM scales based only on reflectivities from precipitating radar, which could be valuable to modelers.
Abstract
Drop-size distribution characteristics were retrieved in eight tropical mesoscale convective systems (MCS) using a dual-frequency (UHF and VHF) wind profiler technique. The MCSs occurred near Darwin, Australia, during the 1993/94 wet season and were representative of the monsoon (oceanic) regime. The retrieved drop-size parameters were compared with corresponding rain gauge and disdrometer data, and it was found that there was good agreement between the measurements, lending credence to the profiler retrievals of drop-size distribution parameters. The profiler data for each MCS were partitioned into a three-tier classification scheme (i.e., convective, mixed convective–stratiform, and stratiform) based on a modified version of to isolate the salient microphysical characteristics in different precipitation types. The resulting analysis allowed for an examination of the drop-size distribution parameters in each category for a height range of about 2.1 km in each MCS.
In general, the distributions of all of the retrieved parameters showed the most variability in convection and the least in stratiform, with the mixed convective–stratiform category usually displaying intermediate characteristics. Although there was significant overlap in the range of many of the parameter distributions, the mean profiles were distinct. In the stratiform region, there was minimal vertical structure for all of the drop-size distribution parameters. This result suggests an equilibrium between depletion (e.g., evaporation) and growth (e.g., coalescence) over the height range examined. In contrast, the convective parameter distributions showed a more complicated structure, probably as a consequence of the complex microphysical processes occurring in the convective precipitation category.
Reflectivity–rainfall (Z–R) relations of the form Z = AR B were developed for each precipitation category as a function of height using linear regressions to the profiler retrievals of R and Z in log space. Similar to findings from previous studies, the rainfall decreased for a given reflectivity as the precipitation type changed from convective to stratiform. This result primarily was due to the fact that the coefficient A in the best-fit stratiform Z–R was approximately a factor of 2 greater than the convective A at all heights. The coefficient A generally increased downward with height in each category; the exponent B showed a small decrease (stratiform), almost no change (convective), or a slight increase (mixed convective–stratiform). Consequently, the amount by which convective rain rate exceeded stratiform (for a given reflectivity) varied significantly as a function of height, ranging from about 15% to over 80%.
Abstract
Drop-size distribution characteristics were retrieved in eight tropical mesoscale convective systems (MCS) using a dual-frequency (UHF and VHF) wind profiler technique. The MCSs occurred near Darwin, Australia, during the 1993/94 wet season and were representative of the monsoon (oceanic) regime. The retrieved drop-size parameters were compared with corresponding rain gauge and disdrometer data, and it was found that there was good agreement between the measurements, lending credence to the profiler retrievals of drop-size distribution parameters. The profiler data for each MCS were partitioned into a three-tier classification scheme (i.e., convective, mixed convective–stratiform, and stratiform) based on a modified version of to isolate the salient microphysical characteristics in different precipitation types. The resulting analysis allowed for an examination of the drop-size distribution parameters in each category for a height range of about 2.1 km in each MCS.
In general, the distributions of all of the retrieved parameters showed the most variability in convection and the least in stratiform, with the mixed convective–stratiform category usually displaying intermediate characteristics. Although there was significant overlap in the range of many of the parameter distributions, the mean profiles were distinct. In the stratiform region, there was minimal vertical structure for all of the drop-size distribution parameters. This result suggests an equilibrium between depletion (e.g., evaporation) and growth (e.g., coalescence) over the height range examined. In contrast, the convective parameter distributions showed a more complicated structure, probably as a consequence of the complex microphysical processes occurring in the convective precipitation category.
Reflectivity–rainfall (Z–R) relations of the form Z = AR B were developed for each precipitation category as a function of height using linear regressions to the profiler retrievals of R and Z in log space. Similar to findings from previous studies, the rainfall decreased for a given reflectivity as the precipitation type changed from convective to stratiform. This result primarily was due to the fact that the coefficient A in the best-fit stratiform Z–R was approximately a factor of 2 greater than the convective A at all heights. The coefficient A generally increased downward with height in each category; the exponent B showed a small decrease (stratiform), almost no change (convective), or a slight increase (mixed convective–stratiform). Consequently, the amount by which convective rain rate exceeded stratiform (for a given reflectivity) varied significantly as a function of height, ranging from about 15% to over 80%.
Abstract
Observational studies have shown the link between convectively coupled Kelvin waves (CCKWs) and eastward-propagating rainfall anomalies. We explore the mechanisms in which CCKWs modulate the propagation of precipitation from west to east over equatorial Africa. We examine a multiyear state-of-the-art Africa-wide climate simulation from a convection-permitting model (CP4A) along with a parameterized global driving-model simulation (G25) and evaluate both against observations (TRMM) and ERA-Interim (ERA-I), with a focus on precipitation and Kelvin wave activity. We show that the two important related processes through which CCKWs influence the propagation of convection and precipitation from west to east across equatorial Africa are 1) low-level westerly wind anomalies that lead to increased low-level convergence, and 2) westerly moisture flux anomalies that amplify the lower- to midtropospheric specific humidity. We identify Kelvin wave activity using zonal wind and geopotential height. Using lagged composite analysis, we show that modeled precipitation over equatorial Africa can capture the eastward-propagating precipitation signal that is associated with CCKWs. Composite analysis on strong (high-amplitude) CCKWs shows that both CP4A and G25 capture the connection between the eastward-propagating precipitation anomalies and CCKWs. In comparison to TRMM, however, the precipitation signal is weaker in G25, while CP4A has a more realistic signal. Results show that both CP4A and G25 generally simulate the key horizontal structure of CCKWs, with anomalous low-level westerlies in phase with positive precipitation anomalies. These findings suggest that for operational forecasting, it is important to monitor the day-to-day Kelvin wave activity across equatorial Africa.
Abstract
Observational studies have shown the link between convectively coupled Kelvin waves (CCKWs) and eastward-propagating rainfall anomalies. We explore the mechanisms in which CCKWs modulate the propagation of precipitation from west to east over equatorial Africa. We examine a multiyear state-of-the-art Africa-wide climate simulation from a convection-permitting model (CP4A) along with a parameterized global driving-model simulation (G25) and evaluate both against observations (TRMM) and ERA-Interim (ERA-I), with a focus on precipitation and Kelvin wave activity. We show that the two important related processes through which CCKWs influence the propagation of convection and precipitation from west to east across equatorial Africa are 1) low-level westerly wind anomalies that lead to increased low-level convergence, and 2) westerly moisture flux anomalies that amplify the lower- to midtropospheric specific humidity. We identify Kelvin wave activity using zonal wind and geopotential height. Using lagged composite analysis, we show that modeled precipitation over equatorial Africa can capture the eastward-propagating precipitation signal that is associated with CCKWs. Composite analysis on strong (high-amplitude) CCKWs shows that both CP4A and G25 capture the connection between the eastward-propagating precipitation anomalies and CCKWs. In comparison to TRMM, however, the precipitation signal is weaker in G25, while CP4A has a more realistic signal. Results show that both CP4A and G25 generally simulate the key horizontal structure of CCKWs, with anomalous low-level westerlies in phase with positive precipitation anomalies. These findings suggest that for operational forecasting, it is important to monitor the day-to-day Kelvin wave activity across equatorial Africa.
Abstract
Rainfall retrieval algorithms often assume a gamma-shaped raindrop size distribution (DSD) with three mathematical parameters N
w
, D
m
, and μ. If only two independent measurements are available, as with the dual-frequency precipitation radar on the Global Precipitation Measurement (GPM) mission core satellite, then retrieval algorithms are underconstrained and require assumptions about DSD parameters. To reduce the number of free parameters, algorithms can assume that μ is either a constant or a function of D
m
. Previous studies have suggested μ–Λ constraints [where Λ = (4 + μ)/D
m
], but controversies exist over whether μ–Λ constraints result from physical processes or mathematical artifacts due to high correlations between gamma DSD parameters. This study avoids mathematical artifacts by developing joint probability distribution functions (joint PDFs) of statistically independent DSD attributes derived from the raindrop mass spectrum. These joint PDFs are then mapped into gamma-shaped DSD parameter joint PDFs that can be used in probabilistic rainfall retrieval algorithms as proposed for the GPM satellite program. Surface disdrometer data show a high correlation coefficient between the mass spectrum mean diameter D
m
and mass spectrum standard deviation σ
m
. To remove correlations between DSD attributes, a normalized mass spectrum standard deviation 
Abstract
Rainfall retrieval algorithms often assume a gamma-shaped raindrop size distribution (DSD) with three mathematical parameters N
w
, D
m
, and μ. If only two independent measurements are available, as with the dual-frequency precipitation radar on the Global Precipitation Measurement (GPM) mission core satellite, then retrieval algorithms are underconstrained and require assumptions about DSD parameters. To reduce the number of free parameters, algorithms can assume that μ is either a constant or a function of D
m
. Previous studies have suggested μ–Λ constraints [where Λ = (4 + μ)/D
m
], but controversies exist over whether μ–Λ constraints result from physical processes or mathematical artifacts due to high correlations between gamma DSD parameters. This study avoids mathematical artifacts by developing joint probability distribution functions (joint PDFs) of statistically independent DSD attributes derived from the raindrop mass spectrum. These joint PDFs are then mapped into gamma-shaped DSD parameter joint PDFs that can be used in probabilistic rainfall retrieval algorithms as proposed for the GPM satellite program. Surface disdrometer data show a high correlation coefficient between the mass spectrum mean diameter D
m
and mass spectrum standard deviation σ
m
. To remove correlations between DSD attributes, a normalized mass spectrum standard deviation
Abstract
The Atmospheric Carbon and Transport (ACT)-America NASA Earth Venture Suborbital Mission set out to improve regional atmospheric greenhouse gas (GHG) inversions by exploring the intersection of the strong GHG fluxes and vigorous atmospheric transport that occurs within the midlatitudes. Two research aircraft instrumented with remote and in situ sensors to measure GHG mole fractions, associated trace gases, and atmospheric state variables collected 1,140.7 flight hours of research data, distributed across 305 individual aircraft sorties, coordinated within 121 research flight days, and spanning five 6-week seasonal flight campaigns in the central and eastern United States. Flights sampled 31 synoptic sequences, including fair-weather and frontal conditions, at altitudes ranging from the atmospheric boundary layer to the upper free troposphere. The observations were complemented with global and regional GHG flux and transport model ensembles. We found that midlatitude weather systems contain large spatial gradients in GHG mole fractions, in patterns that were consistent as a function of season and altitude. We attribute these patterns to a combination of regional terrestrial fluxes and inflow from the continental boundaries. These observations, when segregated according to altitude and air mass, provide a variety of quantitative insights into the realism of regional CO2 and CH4 fluxes and atmospheric GHG transport realizations. The ACT-America dataset and ensemble modeling methods provide benchmarks for the development of atmospheric inversion systems. As global and regional atmospheric inversions incorporate ACT-America’s findings and methods, we anticipate these systems will produce increasingly accurate and precise subcontinental GHG flux estimates.
Abstract
The Atmospheric Carbon and Transport (ACT)-America NASA Earth Venture Suborbital Mission set out to improve regional atmospheric greenhouse gas (GHG) inversions by exploring the intersection of the strong GHG fluxes and vigorous atmospheric transport that occurs within the midlatitudes. Two research aircraft instrumented with remote and in situ sensors to measure GHG mole fractions, associated trace gases, and atmospheric state variables collected 1,140.7 flight hours of research data, distributed across 305 individual aircraft sorties, coordinated within 121 research flight days, and spanning five 6-week seasonal flight campaigns in the central and eastern United States. Flights sampled 31 synoptic sequences, including fair-weather and frontal conditions, at altitudes ranging from the atmospheric boundary layer to the upper free troposphere. The observations were complemented with global and regional GHG flux and transport model ensembles. We found that midlatitude weather systems contain large spatial gradients in GHG mole fractions, in patterns that were consistent as a function of season and altitude. We attribute these patterns to a combination of regional terrestrial fluxes and inflow from the continental boundaries. These observations, when segregated according to altitude and air mass, provide a variety of quantitative insights into the realism of regional CO2 and CH4 fluxes and atmospheric GHG transport realizations. The ACT-America dataset and ensemble modeling methods provide benchmarks for the development of atmospheric inversion systems. As global and regional atmospheric inversions incorporate ACT-America’s findings and methods, we anticipate these systems will produce increasingly accurate and precise subcontinental GHG flux estimates.
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 Deep Propagating Gravity Wave Experiment (DEEPWAVE) was designed to quantify gravity wave (GW) dynamics and effects from orographic and other sources to regions of dissipation at high altitudes. The core DEEPWAVE field phase took place from May through July 2014 using a comprehensive suite of airborne and ground-based instruments providing measurements from Earth’s surface to ∼100 km. Austral winter was chosen to observe deep GW propagation to high altitudes. DEEPWAVE was based on South Island, New Zealand, to provide access to the New Zealand and Tasmanian “hotspots” of GW activity and additional GW sources over the Southern Ocean and Tasman Sea. To observe GWs up to ∼100 km, DEEPWAVE utilized three new instruments built specifically for the National Science Foundation (NSF)/National Center for Atmospheric Research (NCAR) Gulfstream V (GV): a Rayleigh lidar, a sodium resonance lidar, and an advanced mesosphere temperature mapper. These measurements were supplemented by in situ probes, dropsondes, and a microwave temperature profiler on the GV and by in situ probes and a Doppler lidar aboard the German DLR Falcon. Extensive ground-based instrumentation and radiosondes were deployed on South Island, Tasmania, and Southern Ocean islands. Deep orographic GWs were a primary target but multiple flights also observed deep GWs arising from deep convection, jet streams, and frontal systems. Highlights include the following: 1) strong orographic GW forcing accompanying strong cross-mountain flows, 2) strong high-altitude responses even when orographic forcing was weak, 3) large-scale GWs at high altitudes arising from jet stream sources, and 4) significant flight-level energy fluxes and often very large momentum fluxes at high altitudes.
Abstract
The Deep Propagating Gravity Wave Experiment (DEEPWAVE) was designed to quantify gravity wave (GW) dynamics and effects from orographic and other sources to regions of dissipation at high altitudes. The core DEEPWAVE field phase took place from May through July 2014 using a comprehensive suite of airborne and ground-based instruments providing measurements from Earth’s surface to ∼100 km. Austral winter was chosen to observe deep GW propagation to high altitudes. DEEPWAVE was based on South Island, New Zealand, to provide access to the New Zealand and Tasmanian “hotspots” of GW activity and additional GW sources over the Southern Ocean and Tasman Sea. To observe GWs up to ∼100 km, DEEPWAVE utilized three new instruments built specifically for the National Science Foundation (NSF)/National Center for Atmospheric Research (NCAR) Gulfstream V (GV): a Rayleigh lidar, a sodium resonance lidar, and an advanced mesosphere temperature mapper. These measurements were supplemented by in situ probes, dropsondes, and a microwave temperature profiler on the GV and by in situ probes and a Doppler lidar aboard the German DLR Falcon. Extensive ground-based instrumentation and radiosondes were deployed on South Island, Tasmania, and Southern Ocean islands. Deep orographic GWs were a primary target but multiple flights also observed deep GWs arising from deep convection, jet streams, and frontal systems. Highlights include the following: 1) strong orographic GW forcing accompanying strong cross-mountain flows, 2) strong high-altitude responses even when orographic forcing was weak, 3) large-scale GWs at high altitudes arising from jet stream sources, and 4) significant flight-level energy fluxes and often very large momentum fluxes at high altitudes.
