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- Author or Editor: Greg J. Holland x
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Abstract
The authors present a comprehensive climatology of heavy rain and east coast cyclones from January 1958 to September 1992. A total of 80 cyclones, including nondeveloping systems, were objectively identified from daily rainfall and surface wind observations at 28 stations along the east coast of Australia. The method used first identifies heavy-rain days, then uses the wind observations to differentiate east coast cyclones from other rain-producing systems. This method is found to be reliable and with modifications may be used to identify other mesoscale systems.
In general, onshore southeasterly to southerly flow is most commonly associated with heavy rain along the east coast of Australia. Local convective heavy-rain events are most common in the Tropics, and the maximum occurrence of heavy-rain days propagates poleward from summer to winter. The latitudinal position and movement of the subtropical anticyclone, and variations in the Southern Oscillation index, have been found to be major factors in the variability of coastal heavy-rain occurrences.
Consistent with previous studies, it is found that east coast cyclones occur primarily in winter and form in regions of warm sea surface temperature anomalies. Intensification of east coast cyclones is associated with strong zonal sea surface temperature gradients, greater than 4°C within 50 km of the coastline.
Significant correlations exist between the occurrence of east coast cyclones, the Southern Oscillation index, and the latitudinal position of the subtropical anticyclone. The strongest correlations, however, suggest a preference for east coast cyclones to form between extreme episodes (negative to positive) of the Southern Oscillation index.
A long-term annual trend toward increased numbers of east coast cyclones has been identified, along with an apparent decrease of local convective heavy-rain events, particularly for coastal stations at higher latitudes. No corresponding trend is found for heavy-rain occurrences, the Southern Oscillation index, or the latitudinal position of the subtropical anticyclone.
Abstract
The authors present a comprehensive climatology of heavy rain and east coast cyclones from January 1958 to September 1992. A total of 80 cyclones, including nondeveloping systems, were objectively identified from daily rainfall and surface wind observations at 28 stations along the east coast of Australia. The method used first identifies heavy-rain days, then uses the wind observations to differentiate east coast cyclones from other rain-producing systems. This method is found to be reliable and with modifications may be used to identify other mesoscale systems.
In general, onshore southeasterly to southerly flow is most commonly associated with heavy rain along the east coast of Australia. Local convective heavy-rain events are most common in the Tropics, and the maximum occurrence of heavy-rain days propagates poleward from summer to winter. The latitudinal position and movement of the subtropical anticyclone, and variations in the Southern Oscillation index, have been found to be major factors in the variability of coastal heavy-rain occurrences.
Consistent with previous studies, it is found that east coast cyclones occur primarily in winter and form in regions of warm sea surface temperature anomalies. Intensification of east coast cyclones is associated with strong zonal sea surface temperature gradients, greater than 4°C within 50 km of the coastline.
Significant correlations exist between the occurrence of east coast cyclones, the Southern Oscillation index, and the latitudinal position of the subtropical anticyclone. The strongest correlations, however, suggest a preference for east coast cyclones to form between extreme episodes (negative to positive) of the Southern Oscillation index.
A long-term annual trend toward increased numbers of east coast cyclones has been identified, along with an apparent decrease of local convective heavy-rain events, particularly for coastal stations at higher latitudes. No corresponding trend is found for heavy-rain occurrences, the Southern Oscillation index, or the latitudinal position of the subtropical anticyclone.
Abstract
Large-scale environmental variables known to be linked to the formation of tropical cyclones have previously been used to develop empirical indices as proxies for assessing cyclone frequency from large-scale analyses or model simulations. Here the authors examine the ability of two recent indices, the genesis potential (GP) and the genesis potential index, to reproduce observed North Atlantic cyclone annual frequency variations and trends. These skillfully estimate the mean seasonal variation of observed cyclones, but they struggle with reproducing interannual frequency variability and change. Examination of the independent contributions by the four terms that make up the indices finds that potential intensity and shear have significant skill, while moisture and vorticity either do not contribute to or degrade the indices’ capacity to reproduce observed interannual variability. It is also found that for assessing basinwide cyclone frequency, averaging indices over the whole basin is less skillful than its application to the general area off the coast of Africa broadly covering the main development region (MDR).
These results point to a revised index, the cyclone genesis index (CGI), which comprises only potential intensity and vertical shear. Application of the CGI averaged over the MDR demonstrates high and significant skill at reproducing interannual variations and trends in all-basin cyclones across both reanalyses. The CGI also provides a more accurate reproduction of seasonal variations than the original GP. Future work applying the CGI to other tropical cyclone basins and to the downscaling of relatively course climate simulations is briefly addressed.
Abstract
Large-scale environmental variables known to be linked to the formation of tropical cyclones have previously been used to develop empirical indices as proxies for assessing cyclone frequency from large-scale analyses or model simulations. Here the authors examine the ability of two recent indices, the genesis potential (GP) and the genesis potential index, to reproduce observed North Atlantic cyclone annual frequency variations and trends. These skillfully estimate the mean seasonal variation of observed cyclones, but they struggle with reproducing interannual frequency variability and change. Examination of the independent contributions by the four terms that make up the indices finds that potential intensity and shear have significant skill, while moisture and vorticity either do not contribute to or degrade the indices’ capacity to reproduce observed interannual variability. It is also found that for assessing basinwide cyclone frequency, averaging indices over the whole basin is less skillful than its application to the general area off the coast of Africa broadly covering the main development region (MDR).
These results point to a revised index, the cyclone genesis index (CGI), which comprises only potential intensity and vertical shear. Application of the CGI averaged over the MDR demonstrates high and significant skill at reproducing interannual variations and trends in all-basin cyclones across both reanalyses. The CGI also provides a more accurate reproduction of seasonal variations than the original GP. Future work applying the CGI to other tropical cyclone basins and to the downscaling of relatively course climate simulations is briefly addressed.
Abstract
This study uses a nonhierarchical cluster analysis to identify the major environmental circulation patterns associated with tropical cloud cluster (TCC) formation in the western North Pacific. All TCCs that formed in July–October 1981–2009 are examined based on their 850-hPa wind field around TCC centers. Eight types of environmental circulation patterns are identified. Of these, four are related to monsoon systems (trough, confluence, north of trough, and south of trough), three are related to easterly systems (low-latitude zone, west of subtropical high, and southwest of subtropical high), and one is associated with low-latitude cross-equatorial flow. The genesis potential index (GPI) is analyzed to compare how favorable the environmental conditions are for tropical cyclone (TC) formation when TCCs form. Excluding three cluster types with the GPI lower than the climatology of all samples, TCCs formed in monsoon environments have larger sizes, lower brightness temperatures, longer lifetimes, and higher GPIs than those of TCCs formed in easterly environments. However, for TCCs formed in easterly environments, the average GPI for those TCCs that later develop into TCs (developing TCCs) is higher than that for other TCCs (nondeveloping TCCs). This difference is nonsignificant for TCCs formed in monsoon environments. Conversely, the average magnitudes of GPI are similar for developing TCCs, regardless of whether TCCs form in easterly or monsoon environments. In summary, the probability of a TCC to develop into a TC is more sensitive to the environmental conditions for TCCs formed in easterly environments than those formed in monsoon environments.
Abstract
This study uses a nonhierarchical cluster analysis to identify the major environmental circulation patterns associated with tropical cloud cluster (TCC) formation in the western North Pacific. All TCCs that formed in July–October 1981–2009 are examined based on their 850-hPa wind field around TCC centers. Eight types of environmental circulation patterns are identified. Of these, four are related to monsoon systems (trough, confluence, north of trough, and south of trough), three are related to easterly systems (low-latitude zone, west of subtropical high, and southwest of subtropical high), and one is associated with low-latitude cross-equatorial flow. The genesis potential index (GPI) is analyzed to compare how favorable the environmental conditions are for tropical cyclone (TC) formation when TCCs form. Excluding three cluster types with the GPI lower than the climatology of all samples, TCCs formed in monsoon environments have larger sizes, lower brightness temperatures, longer lifetimes, and higher GPIs than those of TCCs formed in easterly environments. However, for TCCs formed in easterly environments, the average GPI for those TCCs that later develop into TCs (developing TCCs) is higher than that for other TCCs (nondeveloping TCCs). This difference is nonsignificant for TCCs formed in monsoon environments. Conversely, the average magnitudes of GPI are similar for developing TCCs, regardless of whether TCCs form in easterly or monsoon environments. In summary, the probability of a TCC to develop into a TC is more sensitive to the environmental conditions for TCCs formed in easterly environments than those formed in monsoon environments.
Abstract
Reliable estimates of future changes in extreme weather phenomena, such as tropical cyclone maximum wind speeds, are critical for climate change impact assessments and the development of appropriate adaptation strategies. However, global and regional climate model outputs are often too coarse for direct use in these applications, with variables such as wind speed having truncated probability distributions compared to those of observations. This poses two problems: How can model-simulated variables best be adjusted to make them more realistic? And how can such adjustments be used to make more reliable predictions of future changes in their distribution?
This study investigates North Atlantic tropical cyclone maximum wind speeds from observations (1950–2010) and regional climate model simulations (1995–2005 and 2045–55 at 12- and 36-km spatial resolutions). The wind speed distributions in these datasets are well represented by the Weibull distribution, albeit with different scale and shape parameters.
A power-law transfer function is used to recalibrate the Weibull variables and obtain future projections of wind speeds. Two different strategies, bias correction and change factor, are tested by using 36-km model data to predict future 12-km model data (pseudo-observations). The strategies are also applied to the observations to obtain likely predictions of the future distributions of wind speeds. The strategies yield similar predictions of likely changes in the fraction of events within Saffir–Simpson categories—for example, an increase from 21% (1995–2005) to 27%–37% (2045–55) for category 3 or above events and an increase from 1.6% (1995–2005) to 2.8%–9.8% (2045–55) for category 5 events.
Abstract
Reliable estimates of future changes in extreme weather phenomena, such as tropical cyclone maximum wind speeds, are critical for climate change impact assessments and the development of appropriate adaptation strategies. However, global and regional climate model outputs are often too coarse for direct use in these applications, with variables such as wind speed having truncated probability distributions compared to those of observations. This poses two problems: How can model-simulated variables best be adjusted to make them more realistic? And how can such adjustments be used to make more reliable predictions of future changes in their distribution?
This study investigates North Atlantic tropical cyclone maximum wind speeds from observations (1950–2010) and regional climate model simulations (1995–2005 and 2045–55 at 12- and 36-km spatial resolutions). The wind speed distributions in these datasets are well represented by the Weibull distribution, albeit with different scale and shape parameters.
A power-law transfer function is used to recalibrate the Weibull variables and obtain future projections of wind speeds. Two different strategies, bias correction and change factor, are tested by using 36-km model data to predict future 12-km model data (pseudo-observations). The strategies are also applied to the observations to obtain likely predictions of the future distributions of wind speeds. The strategies yield similar predictions of likely changes in the fraction of events within Saffir–Simpson categories—for example, an increase from 21% (1995–2005) to 27%–37% (2045–55) for category 3 or above events and an increase from 1.6% (1995–2005) to 2.8%–9.8% (2045–55) for category 5 events.
