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- Author or Editor: Michael Manton x
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Abstract
The Snowy Precipitation Enhancement Research Project (SPERP) was undertaken in winters from May 2005 to June 2009 in the Snowy Mountains region of southeastern Australia. Part I of this paper describes the design and implementation of the project, as well as the characteristics of the key datasets collected during the field phase. The primary analysis in this paper (Part II) shows an unequivocal impact on the targeting of seeding material, with the maximum level of silver in snow samples collected from the primary target area found to be significantly greater in seeded than unseeded experimental units (EUs). A positive but not statistically significant impact on precipitation was found. Further analysis shows that a substantial source of uncertainty in the estimation of the impacts of seeding on precipitation is associated with EUs where the seeding generators operated for relatively few hours. When the analysis is repeated using only EUs with more than 45 generator hours, the increase in precipitation in the primary target area is 14% at the 8% significance level. When applying that analysis to the overall target area, the precipitation increase is 14% at the 3% significance level. A secondary analysis of the ratio of silver to indium in snow supports the hypothesis that seeding material affected the cloud microphysics. Other secondary analyses reveal that seeding had an impact on virtually all of the physical variables examined in a manner consistent with the seeding hypothesis.
Abstract
The Snowy Precipitation Enhancement Research Project (SPERP) was undertaken in winters from May 2005 to June 2009 in the Snowy Mountains region of southeastern Australia. Part I of this paper describes the design and implementation of the project, as well as the characteristics of the key datasets collected during the field phase. The primary analysis in this paper (Part II) shows an unequivocal impact on the targeting of seeding material, with the maximum level of silver in snow samples collected from the primary target area found to be significantly greater in seeded than unseeded experimental units (EUs). A positive but not statistically significant impact on precipitation was found. Further analysis shows that a substantial source of uncertainty in the estimation of the impacts of seeding on precipitation is associated with EUs where the seeding generators operated for relatively few hours. When the analysis is repeated using only EUs with more than 45 generator hours, the increase in precipitation in the primary target area is 14% at the 8% significance level. When applying that analysis to the overall target area, the precipitation increase is 14% at the 3% significance level. A secondary analysis of the ratio of silver to indium in snow supports the hypothesis that seeding material affected the cloud microphysics. Other secondary analyses reveal that seeding had an impact on virtually all of the physical variables examined in a manner consistent with the seeding hypothesis.
Abstract
Two anomalies are described which arise in the kernel for stochastic droplet collection when it is specified by the formula of Scott and Chen for the linear collision efficiency y(R,r) and by the formula of Wobus et al. for the droplet terminal velocity V(R). It is pointed out that if accurate values for y(R,r) are to be obtained for a given droplet pair by interpolation using data for specific droplet pairs, then for large droplet radii (R<30 μm) it is desirable that these data he tabulated for 2-μm intervals of R. It is shown that if the difference in terminal velocities of two droplets is computed from a formula approximating V(R) and composed of various functions V*(R) applicable over adjoining domains of R, then it is necessary that these functions be constructed so that the formula and its derivatives, at least up to second order, are everywhere continuous. An improved formula for V(R) satisfying this criterion is described.
Abstract
Two anomalies are described which arise in the kernel for stochastic droplet collection when it is specified by the formula of Scott and Chen for the linear collision efficiency y(R,r) and by the formula of Wobus et al. for the droplet terminal velocity V(R). It is pointed out that if accurate values for y(R,r) are to be obtained for a given droplet pair by interpolation using data for specific droplet pairs, then for large droplet radii (R<30 μm) it is desirable that these data he tabulated for 2-μm intervals of R. It is shown that if the difference in terminal velocities of two droplets is computed from a formula approximating V(R) and composed of various functions V*(R) applicable over adjoining domains of R, then it is necessary that these functions be constructed so that the formula and its derivatives, at least up to second order, are everywhere continuous. An improved formula for V(R) satisfying this criterion is described.
Abstract
Over 50 satellite rainfall algorithms were evaluated for a 5° square region in the equatorial western Pacific Ocean during TOGA COARE, November 1992–February 1993. These satellite algorithms used GMS VIS/IR, AVHRR, and SSM/I data to estimate rainfall on both instantaneous and monthly timescales. Validation data came from two calibrated shipboard Doppler radars measuring rainfall every 10 min.
There was large variation among algorithms in the magnitude of the satellite-estimated rainfall, but the patterns of rainfall were similar among algorithm types. Compared to the radar observations, most of the satellite algorithms overestimated the amount of rain falling in the region, typically by about 30%. Patterns of monthly observed rainfall were well represented by the satellite algorithms, with correlation coefficients with the observations ranging from 0.86 to 0.90 for algorithms using geostationary data and 0.69 to 0.86 for AVHRR and SSM/I algorithms when validated on a 0.5° grid. Patterns of instantaneous rain rates were also well analyzed, with correlation coefficients with the radar observations of 0.43–0.58 for the geostationary algorithms and 0.60–0.78 for SSM/I algorithms.
Two case studies are presented to demonstrate the capability of one IR algorithm and three microwave algorithms to estimate instantaneous rainfall rates in the Tropics. The three microwave algorithms differed in their estimates of rain area but all showed greater ability than the IR algorithm to reproduce the spatial pattern of rainfall.
Abstract
Over 50 satellite rainfall algorithms were evaluated for a 5° square region in the equatorial western Pacific Ocean during TOGA COARE, November 1992–February 1993. These satellite algorithms used GMS VIS/IR, AVHRR, and SSM/I data to estimate rainfall on both instantaneous and monthly timescales. Validation data came from two calibrated shipboard Doppler radars measuring rainfall every 10 min.
There was large variation among algorithms in the magnitude of the satellite-estimated rainfall, but the patterns of rainfall were similar among algorithm types. Compared to the radar observations, most of the satellite algorithms overestimated the amount of rain falling in the region, typically by about 30%. Patterns of monthly observed rainfall were well represented by the satellite algorithms, with correlation coefficients with the observations ranging from 0.86 to 0.90 for algorithms using geostationary data and 0.69 to 0.86 for AVHRR and SSM/I algorithms when validated on a 0.5° grid. Patterns of instantaneous rain rates were also well analyzed, with correlation coefficients with the radar observations of 0.43–0.58 for the geostationary algorithms and 0.60–0.78 for SSM/I algorithms.
Two case studies are presented to demonstrate the capability of one IR algorithm and three microwave algorithms to estimate instantaneous rainfall rates in the Tropics. The three microwave algorithms differed in their estimates of rain area but all showed greater ability than the IR algorithm to reproduce the spatial pattern of rainfall.
Abstract
Variability in the wet season of tropical northern Australia is examined over its main months, November–March, with a focus on zonal differences between the western, central, and eastern domains, which encompass the northern parts of Western Australia, Northern Territory, and Queensland, respectively. The seasonal progression of the wet season is similar across the region, with steadily increasing atmospheric moisture and rainfall into the core months of the monsoon, January and February, decreasing into March. This seasonal progression differs in the eastern domain, where there is an extension of premonsoonal conditions into December, and a delay of the onset of the monsoon until January. An analysis of TRMM precipitation features (PFs) reveals more intense convection during the premonsoon, steadily decreasing in intensity to much shallower convection by March, with a steady increase in the overall number of PFs throughout the wet season. Regionally, the intensity of PFs steadily decreases eastward across northern Australia with significantly weaker, shallower PFs over the eastern domain. Intraseasonal variability associated with the Madden–Julian oscillation (MJO) has a consistent impact on the rainfall and the total number of TRMM PFs across northern Australia, with both increasing and decreasing during the active and suppressed phases, respectively. However, regional variations in the effect of the MJO lead to radically different characteristics of PFs during the suppressed phases; intense convection and thunderstorms become more frequent over the western and central domains, while shallow PFs associated with the warm rain precipitation process increase in number over the eastern domain.
Abstract
Variability in the wet season of tropical northern Australia is examined over its main months, November–March, with a focus on zonal differences between the western, central, and eastern domains, which encompass the northern parts of Western Australia, Northern Territory, and Queensland, respectively. The seasonal progression of the wet season is similar across the region, with steadily increasing atmospheric moisture and rainfall into the core months of the monsoon, January and February, decreasing into March. This seasonal progression differs in the eastern domain, where there is an extension of premonsoonal conditions into December, and a delay of the onset of the monsoon until January. An analysis of TRMM precipitation features (PFs) reveals more intense convection during the premonsoon, steadily decreasing in intensity to much shallower convection by March, with a steady increase in the overall number of PFs throughout the wet season. Regionally, the intensity of PFs steadily decreases eastward across northern Australia with significantly weaker, shallower PFs over the eastern domain. Intraseasonal variability associated with the Madden–Julian oscillation (MJO) has a consistent impact on the rainfall and the total number of TRMM PFs across northern Australia, with both increasing and decreasing during the active and suppressed phases, respectively. However, regional variations in the effect of the MJO lead to radically different characteristics of PFs during the suppressed phases; intense convection and thunderstorms become more frequent over the western and central domains, while shallow PFs associated with the warm rain precipitation process increase in number over the eastern domain.
Abstract
Cloud and precipitation properties of the midlatitude storm-track regions over the Southern Ocean (SO) and North Atlantic (NA) are explored using reanalysis datasets and A-Train observations from 2007 to 2011. In addition to the high-level retrieval products, lower-level observed variables—CloudSat radar reflectivity and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) lidar attenuated backscatter—are directly examined using both contoured frequency by altitude diagrams (CFADs) and contoured frequency by temperature diagrams (CFTDs) to provide direct insight into thermodynamic phase properties. While the wintertime temperature profiles are similar over the two regions, the summertime environment is warmer over the NA. The NA atmosphere is generally moister than the SO, while the SO boundary layer is moister during winter. The results herein suggest that although the two regions exhibit many similarities in the prevalence of boundary layer clouds (BLCs) and frontal systems, notable differences exist. The NA environment exhibits stronger seasonality in thermodynamic structure, cloud, and precipitation properties than the SO. The regional differences of cloud properties are dominated by microphysics in winter and thermodynamics in summer. Glaciated clouds with higher reflectivities are found at warmer temperatures over the NA. BLCs (primarily below 1.5 km) are a predominant component over the SO. The wintertime boundary layer is shallower over the SO. Midlevel clouds consisting of smaller hydrometeors in higher concentration (potentially supercooled liquid water) are more frequently observed over the SO. Cirrus clouds are more prevalent over the NA. Notable differences exist in both the frequencies of thermodynamic phases of precipitation and intensity of warm rain over the two regions.
Abstract
Cloud and precipitation properties of the midlatitude storm-track regions over the Southern Ocean (SO) and North Atlantic (NA) are explored using reanalysis datasets and A-Train observations from 2007 to 2011. In addition to the high-level retrieval products, lower-level observed variables—CloudSat radar reflectivity and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) lidar attenuated backscatter—are directly examined using both contoured frequency by altitude diagrams (CFADs) and contoured frequency by temperature diagrams (CFTDs) to provide direct insight into thermodynamic phase properties. While the wintertime temperature profiles are similar over the two regions, the summertime environment is warmer over the NA. The NA atmosphere is generally moister than the SO, while the SO boundary layer is moister during winter. The results herein suggest that although the two regions exhibit many similarities in the prevalence of boundary layer clouds (BLCs) and frontal systems, notable differences exist. The NA environment exhibits stronger seasonality in thermodynamic structure, cloud, and precipitation properties than the SO. The regional differences of cloud properties are dominated by microphysics in winter and thermodynamics in summer. Glaciated clouds with higher reflectivities are found at warmer temperatures over the NA. BLCs (primarily below 1.5 km) are a predominant component over the SO. The wintertime boundary layer is shallower over the SO. Midlevel clouds consisting of smaller hydrometeors in higher concentration (potentially supercooled liquid water) are more frequently observed over the SO. Cirrus clouds are more prevalent over the NA. Notable differences exist in both the frequencies of thermodynamic phases of precipitation and intensity of warm rain over the two regions.
Abstract
Moderate Resolution Imaging Spectroradiometer (MODIS) Level 2 observations from the Terra satellite are used to create a 3-yr climatology of cloud-top phase over a section of the Southern Ocean (south of Australia) and the North Pacific Ocean. The intent is to highlight the extensive presence of supercooled liquid water over the Southern Ocean region, particularly during summer. The phase of such clouds directly affects the absorbed shortwave radiation, which has recently been found to be “poorly simulated in both state-of-the-art reanalysis and coupled global climate models” (Trenberth and Fasullo).
The climatology finds that supercooled liquid water is present year-round in the low-altitude clouds across this section of the Southern Ocean. Further, the MODIS cloud phase algorithm identifies very few glaciated cloud tops at temperatures above −20°C, rather inferring a large portion of “uncertain” cloud tops. Between 50° and 60°S during the summer, the albedo effect is compounded by a seasonal reduction in high-level cirrus. This is in direct contrast to the Bering Sea and Gulf of Alaska. Here MODIS finds a higher likelihood of observing warm liquid water clouds during summer and a reduction in the relative frequency of cloud tops within the 0° to −20°C temperature range.
As the MODIS cloud phase product has limited ability to confidently identify cloud-top phase between −5° and −25°C, future research should include observations from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and other space-based sensors to help with the classification within this temperature range. Further, multiregion in situ verification of any remotely sensed observations is vital to further understanding the cloud phase processes.
Abstract
Moderate Resolution Imaging Spectroradiometer (MODIS) Level 2 observations from the Terra satellite are used to create a 3-yr climatology of cloud-top phase over a section of the Southern Ocean (south of Australia) and the North Pacific Ocean. The intent is to highlight the extensive presence of supercooled liquid water over the Southern Ocean region, particularly during summer. The phase of such clouds directly affects the absorbed shortwave radiation, which has recently been found to be “poorly simulated in both state-of-the-art reanalysis and coupled global climate models” (Trenberth and Fasullo).
The climatology finds that supercooled liquid water is present year-round in the low-altitude clouds across this section of the Southern Ocean. Further, the MODIS cloud phase algorithm identifies very few glaciated cloud tops at temperatures above −20°C, rather inferring a large portion of “uncertain” cloud tops. Between 50° and 60°S during the summer, the albedo effect is compounded by a seasonal reduction in high-level cirrus. This is in direct contrast to the Bering Sea and Gulf of Alaska. Here MODIS finds a higher likelihood of observing warm liquid water clouds during summer and a reduction in the relative frequency of cloud tops within the 0° to −20°C temperature range.
As the MODIS cloud phase product has limited ability to confidently identify cloud-top phase between −5° and −25°C, future research should include observations from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and other space-based sensors to help with the classification within this temperature range. Further, multiregion in situ verification of any remotely sensed observations is vital to further understanding the cloud phase processes.
Abstract
The relationship between orographic precipitation, low-level thermodynamic stability, and the synoptic meteorology is explored for the Snowy Mountains of southeast Australia. A 21-yr dataset (May–October, 1995–2015) of upper-air soundings from an upwind site is used to define synoptic indicators and the low-level stability. A K-means clustering algorithm was employed to classify the daily meteorology into four synoptic classes. The initial classification, based only on six synoptic indicators, distinctly defines both the surface precipitation and the low-level stability by class. Consistent with theory, the wet classes are found to have weak low-level stability, and the dry classes have strong low-level stability. By including low-level stability as an additional input variable to the clustering method, statistically significant correlations were found between the precipitation and the low-level stability within each of the four classes. An examination of the joint PDF reveals a highly nonlinear relationship; heavy rain was associated with very weak low-level stability, and conversely, strong low-level stability was associated with very little precipitation. Building on these historical relationships, model output statistics (MOS) from a moderate resolution (12-km spatial resolution) operational forecast were used to develop stepwise regression models designed to improve the 24-h forecast of precipitation over the Snowy Mountains. A single regression model for all days was found to reduce the RMSE by 7% and the bias by 75%. A class-based regression model was found to reduce the overall RMSE by 30% and the bias by 85%.
Abstract
The relationship between orographic precipitation, low-level thermodynamic stability, and the synoptic meteorology is explored for the Snowy Mountains of southeast Australia. A 21-yr dataset (May–October, 1995–2015) of upper-air soundings from an upwind site is used to define synoptic indicators and the low-level stability. A K-means clustering algorithm was employed to classify the daily meteorology into four synoptic classes. The initial classification, based only on six synoptic indicators, distinctly defines both the surface precipitation and the low-level stability by class. Consistent with theory, the wet classes are found to have weak low-level stability, and the dry classes have strong low-level stability. By including low-level stability as an additional input variable to the clustering method, statistically significant correlations were found between the precipitation and the low-level stability within each of the four classes. An examination of the joint PDF reveals a highly nonlinear relationship; heavy rain was associated with very weak low-level stability, and conversely, strong low-level stability was associated with very little precipitation. Building on these historical relationships, model output statistics (MOS) from a moderate resolution (12-km spatial resolution) operational forecast were used to develop stepwise regression models designed to improve the 24-h forecast of precipitation over the Snowy Mountains. A single regression model for all days was found to reduce the RMSE by 7% and the bias by 75%. A class-based regression model was found to reduce the overall RMSE by 30% and the bias by 85%.
Abstract
A “climatology” of supercooled cloud tops is presented for southeastern Australia and the western United States, where historic glaciogenic cloud-seeding trials have been located. The climatology finds that supercooled cloud tops are common over the mountainous region of southeastern Australia and Tasmania (SEAT). Regions where cloud-seeding trials reported positive results coincide with a higher likelihood of observing supercooled cloud tops. Maximum absolute frequencies (AFs) occur ∼40% of the time during winter. There is a relationship between the underlying orography and the likelihood of observing supercooled liquid water (SLW)-topped clouds. Regions of the United States that have been the subject of cloud-seeding trials show lower AFs of SLW-topped clouds. The maximum is located over the Sierra Nevada and occurs ∼20% of the time during winter (Sierra Cooperative Pilot Project). These sites are on mountains with peaks higher than any found in SEAT (>3000 m). For the Sierra Nevada, the AF of SLW-topped clouds decreases as the elevation increases, with glaciation occurring at the higher elevations. The remote sensing of supercooled cloud tops is not proof of a region’s amenability for glaciogenic cloud seeding. This study simply highlights the significant environmental differences between historical cloud-seeding regions in the United States and Australia, suggesting that it is not reasonable to extrapolate results from one region to another. Without in situ cloud microphysical measurements, in-depth knowledge of the timing and duration of potentially seedable events, or knowledge of the synoptic forcing of such events, it is not possible to categorize a region’s potential for precipitation augmentation operations.
Abstract
A “climatology” of supercooled cloud tops is presented for southeastern Australia and the western United States, where historic glaciogenic cloud-seeding trials have been located. The climatology finds that supercooled cloud tops are common over the mountainous region of southeastern Australia and Tasmania (SEAT). Regions where cloud-seeding trials reported positive results coincide with a higher likelihood of observing supercooled cloud tops. Maximum absolute frequencies (AFs) occur ∼40% of the time during winter. There is a relationship between the underlying orography and the likelihood of observing supercooled liquid water (SLW)-topped clouds. Regions of the United States that have been the subject of cloud-seeding trials show lower AFs of SLW-topped clouds. The maximum is located over the Sierra Nevada and occurs ∼20% of the time during winter (Sierra Cooperative Pilot Project). These sites are on mountains with peaks higher than any found in SEAT (>3000 m). For the Sierra Nevada, the AF of SLW-topped clouds decreases as the elevation increases, with glaciation occurring at the higher elevations. The remote sensing of supercooled cloud tops is not proof of a region’s amenability for glaciogenic cloud seeding. This study simply highlights the significant environmental differences between historical cloud-seeding regions in the United States and Australia, suggesting that it is not reasonable to extrapolate results from one region to another. Without in situ cloud microphysical measurements, in-depth knowledge of the timing and duration of potentially seedable events, or knowledge of the synoptic forcing of such events, it is not possible to categorize a region’s potential for precipitation augmentation operations.
Abstract
The case study of a heavy precipitation event associated with the passage of cold front over the Australian Snowy Mountains (ASM) on 3 August 2018 has been examined using the observational data from an intensive field campaign and high-resolution (1 km) Weather Research and Forecasting (WRF) simulation. We divided this event into prefrontal, cold front, and postfrontal periods. The cold front and postfrontal periods were characterized by higher production of graupel, while relatively low graupel was produced in the prefrontal period. Overall, aggregation along with deposition are likely the main growth mechanisms of snow in the prefrontal clouds, while heavy rain was produced below the melting level over windward slopes of the ASM. The simulated melting level is lower compared to the observations, which is consistent with model cold bias. Stronger orographic uplift and frontal forcing were mainly responsible for the enhanced supercooled liquid water (SLW) production over the ASM in the cold front period. A drop in elevation of the freezing level and increase in low-level relative humidity further enhanced the SLW production. The production of graupel through riming processes was highly efficient in the cold front period given the high concentration of ice-phase hydrometeors in the frontal clouds and the development of clouds comprising supercooled liquid water. The orographic updrafts and embedded convection were the main dynamical processes generating postfrontal SLW clouds and graupel. Ice initiation processes were activated once SLW cloud tops reached −15°C level followed by graupel production through riming processes.
Abstract
The case study of a heavy precipitation event associated with the passage of cold front over the Australian Snowy Mountains (ASM) on 3 August 2018 has been examined using the observational data from an intensive field campaign and high-resolution (1 km) Weather Research and Forecasting (WRF) simulation. We divided this event into prefrontal, cold front, and postfrontal periods. The cold front and postfrontal periods were characterized by higher production of graupel, while relatively low graupel was produced in the prefrontal period. Overall, aggregation along with deposition are likely the main growth mechanisms of snow in the prefrontal clouds, while heavy rain was produced below the melting level over windward slopes of the ASM. The simulated melting level is lower compared to the observations, which is consistent with model cold bias. Stronger orographic uplift and frontal forcing were mainly responsible for the enhanced supercooled liquid water (SLW) production over the ASM in the cold front period. A drop in elevation of the freezing level and increase in low-level relative humidity further enhanced the SLW production. The production of graupel through riming processes was highly efficient in the cold front period given the high concentration of ice-phase hydrometeors in the frontal clouds and the development of clouds comprising supercooled liquid water. The orographic updrafts and embedded convection were the main dynamical processes generating postfrontal SLW clouds and graupel. Ice initiation processes were activated once SLW cloud tops reached −15°C level followed by graupel production through riming processes.
