Earlier papers have addressed floods from warm-air advection (WAA) in southeast Australia and around the globe, and extreme rainfall in US hurricanes and Australian tropical cyclones (TCs). This is the first paper to address the WAA phenomena in causing monsoon and TC floods and in TC-like systems which develop over the interior of northern Australia. The inland events help explain Australia’s worst tropical flooding disaster in 1916. A disastrous series of floods during late January and early February 2019 caused widespread damage in tropical north Queensland both in inland regions and along the coast. This occurred when some large-scale climate influences, including the sea surface temperatures suggested conditions would not lead to major flooding. Therefore, it is important to focus on the weather systems to understand the processes that resulted in the extreme rainfall responsible for the flooding. The structure of weather systems in most areas involved a pattern in which the winds turned in an anticyclonic sense as they ascended from the low to middle levels of the atmosphere (often referred to as WAA) which was maintained over large areas for 11 days. HYSPLIT air parcel trajectory observations were employed to confirm these ascent analyses. Examination of a period during which the heaviest rain was reported and compared with climatology showed a much stronger monsoon circulation, widespread WAA through tropical Queensland where normally its descending equivalent of cold-air advection is found, and higher mean sea level pressures along the south Queensland coast. The monsoon low was located between strong deep monsoon westerlies to the north and strong deep easterlies to the south which ensured its slow movement. This non-TC event produced heavy inland rainfall. Extreme inland rainfall is rare in this region. Dare et al. (2012), using data from 1969/70 to 2009/10, showed that over north Queensland non-TC events produced a large percentage of the total rainfall. The vertical structure associated with one of the earlier events that occurred in 2008 had sufficient data to detect strong and widespread WAA overlying an onshore moist tropical airstream. This appears to have played a crucial role in such extreme rainfall extending well inland and perhaps gives insight to the cause of a 1916 flooding disaster at Clermont which claimed around 70 lives. Several other events over the inland Tropics with strong WAA also help explain the 1916 disaster.
{"title":"Weather systems and extreme rainfall generation in the 2019 north Queensland floods compared with historical north Queensland record floods","authors":"J. Callaghan","doi":"10.1071/ES20005","DOIUrl":"https://doi.org/10.1071/ES20005","url":null,"abstract":"\u0000Earlier papers have addressed floods from warm-air advection (WAA) in southeast Australia and around the globe, and extreme rainfall in US hurricanes and Australian tropical cyclones (TCs). This is the first paper to address the WAA phenomena in causing monsoon and TC floods and in TC-like systems which develop over the interior of northern Australia. The inland events help explain Australia’s worst tropical flooding disaster in 1916. A disastrous series of floods during late January and early February 2019 caused widespread damage in tropical north Queensland both in inland regions and along the coast. This occurred when some large-scale climate influences, including the sea surface temperatures suggested conditions would not lead to major flooding. Therefore, it is important to focus on the weather systems to understand the processes that resulted in the extreme rainfall responsible for the flooding. The structure of weather systems in most areas involved a pattern in which the winds turned in an anticyclonic sense as they ascended from the low to middle levels of the atmosphere (often referred to as WAA) which was maintained over large areas for 11 days. HYSPLIT air parcel trajectory observations were employed to confirm these ascent analyses. Examination of a period during which the heaviest rain was reported and compared with climatology showed a much stronger monsoon circulation, widespread WAA through tropical Queensland where normally its descending equivalent of cold-air advection is found, and higher mean sea level pressures along the south Queensland coast. The monsoon low was located between strong deep monsoon westerlies to the north and strong deep easterlies to the south which ensured its slow movement. This non-TC event produced heavy inland rainfall. Extreme inland rainfall is rare in this region. Dare et al. (2012), using data from 1969/70 to 2009/10, showed that over north Queensland non-TC events produced a large percentage of the total rainfall. The vertical structure associated with one of the earlier events that occurred in 2008 had sufficient data to detect strong and widespread WAA overlying an onshore moist tropical airstream. This appears to have played a crucial role in such extreme rainfall extending well inland and perhaps gives insight to the cause of a 1916 flooding disaster at Clermont which claimed around 70 lives. Several other events over the inland Tropics with strong WAA also help explain the 1916 disaster.\u0000","PeriodicalId":55419,"journal":{"name":"Journal of Southern Hemisphere Earth Systems Science","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2021-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75204885","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
East coast lows (ECLs) are low pressure systems that occur near the east coast of Australia. But not all lows cause the same level of impact, and a small proportion of ECLs are responsible for more than half of all days with widespread rainfall above 50mm in this region. In this study, we combine analyses of cyclones at both the surface and 500hPa levels to assess the locations of cyclones responsible for widespread heavy rainfall on the east coast. We found that the majority of days with widespread totals above 100mm on the east coast occur when a low at 500hPa over inland southeast Australia coincides with a surface low located more directly over the east coast. Such events occur on about 15 days per year but are responsible for more than 50% of days with widespread heavy rainfall on the eastern seaboard of Australia. We also found that extreme rainfall was most likely when both the surface and upper cyclones were very strong, when measured using the maximum Laplacian of pressure/height. The seasonal frequency of cyclones at the surface and 500hPa were found to be only weakly correlated with each other and often had opposing relationships (albeit weak in magnitude) with both global climate drivers and indices of local circulation variability. Trends in cyclone frequency were weak over the period 1979–2019, but there was a small decline in the frequency of deep cyclone days, which was statistically significant in some parts of the southeast. Understanding which ECLs are associated with heavy rainfall will help us to better identify how future climate change will influence ECL impacts.
{"title":"Intense east coast lows and associated rainfall in eastern Australia","authors":"A. Pepler, A. Dowdy","doi":"10.1071/ES20013","DOIUrl":"https://doi.org/10.1071/ES20013","url":null,"abstract":"\u0000East coast lows (ECLs) are low pressure systems that occur near the east coast of Australia. But not all lows cause the same level of impact, and a small proportion of ECLs are responsible for more than half of all days with widespread rainfall above 50mm in this region. In this study, we combine analyses of cyclones at both the surface and 500hPa levels to assess the locations of cyclones responsible for widespread heavy rainfall on the east coast. We found that the majority of days with widespread totals above 100mm on the east coast occur when a low at 500hPa over inland southeast Australia coincides with a surface low located more directly over the east coast. Such events occur on about 15 days per year but are responsible for more than 50% of days with widespread heavy rainfall on the eastern seaboard of Australia. We also found that extreme rainfall was most likely when both the surface and upper cyclones were very strong, when measured using the maximum Laplacian of pressure/height. The seasonal frequency of cyclones at the surface and 500hPa were found to be only weakly correlated with each other and often had opposing relationships (albeit weak in magnitude) with both global climate drivers and indices of local circulation variability. Trends in cyclone frequency were weak over the period 1979–2019, but there was a small decline in the frequency of deep cyclone days, which was statistically significant in some parts of the southeast. Understanding which ECLs are associated with heavy rainfall will help us to better identify how future climate change will influence ECL impacts.\u0000","PeriodicalId":55419,"journal":{"name":"Journal of Southern Hemisphere Earth Systems Science","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2021-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72457919","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Climate scientists routinely rely on averaging over time or space to simplify complex information and to concisely communicate findings. Currently, no consistent definitions of ‘warm’ or ‘cool’ seasons for southern Australia exist, making comparisons across studies difficult. Similarly, numerous climate studies in Australia use either arbitrarily defined areas or the Natural Resource Management (NRM) clusters to perform spatial averaging. While the NRM regions were informed by temperature and rainfall information, they remain somewhat arbitrary. Here we use weather type influence on rainfall and clustering methods to quantitatively define climatic regions and seasons over southern Australia. Three methods are explored: k-means clustering and two agglomerative clustering methods, Ward linkage and average linkage. K-means was found to be preferred in temporal clustering, while the average linkage method was preferred for spatial clustering. For southern Australia as a whole, we define the cool season as April–September and warm season as October–March, though we note that a three-season split may provide more nuanced climate analysis. We also show that different regions across southern Australia experience different seasons and demonstrate the changing spatial influence of weather types with the seasons, which may aid regionally or seasonally specific climate analysis. Division of southern Australia into 15 climatic regions shows localised agreement with the NRM clusters where distinct differences in rainfall amounts exist. However, the climate regions defined here better represent the importance of topographical aspect on weather type influence and the inland extent of particular weather types. We suggest that the use of these regions would provide consistent climate analysis across studies if widely adopted. A key requirement for climate scientists is the simplification of data sets into both seasonally or regionally averaged subsets. This simplification, by grouping like regions or seasons, is done for a number of reasons both scientific and practical, including to help understand patterns of variability, underlying drivers and trends in climate and weather, to communicate large amounts of data concisely, to reduce the amount of data required for processing (which becomes increasingly important with higher resolution climate model output), or to more simply draw a physical boundary between regions for other purposes, such as flora and fauna habitat analysis, appropriate agricultural practices or water management.
{"title":"Redefining southern Australia’s climatic regions and seasons","authors":"S. Fiddes, A. Pepler, K. Saunders, P. Hope","doi":"10.1071/ES20003","DOIUrl":"https://doi.org/10.1071/ES20003","url":null,"abstract":"\u0000Climate scientists routinely rely on averaging over time or space to simplify complex information and to concisely communicate findings. Currently, no consistent definitions of ‘warm’ or ‘cool’ seasons for southern Australia exist, making comparisons across studies difficult. Similarly, numerous climate studies in Australia use either arbitrarily defined areas or the Natural Resource Management (NRM) clusters to perform spatial averaging. While the NRM regions were informed by temperature and rainfall information, they remain somewhat arbitrary. Here we use weather type influence on rainfall and clustering methods to quantitatively define climatic regions and seasons over southern Australia. Three methods are explored: k-means clustering and two agglomerative clustering methods, Ward linkage and average linkage. K-means was found to be preferred in temporal clustering, while the average linkage method was preferred for spatial clustering. For southern Australia as a whole, we define the cool season as April–September and warm season as October–March, though we note that a three-season split may provide more nuanced climate analysis. We also show that different regions across southern Australia experience different seasons and demonstrate the changing spatial influence of weather types with the seasons, which may aid regionally or seasonally specific climate analysis. Division of southern Australia into 15 climatic regions shows localised agreement with the NRM clusters where distinct differences in rainfall amounts exist. However, the climate regions defined here better represent the importance of topographical aspect on weather type influence and the inland extent of particular weather types. We suggest that the use of these regions would provide consistent climate analysis across studies if widely adopted. A key requirement for climate scientists is the simplification of data sets into both seasonally or regionally averaged subsets. This simplification, by grouping like regions or seasons, is done for a number of reasons both scientific and practical, including to help understand patterns of variability, underlying drivers and trends in climate and weather, to communicate large amounts of data concisely, to reduce the amount of data required for processing (which becomes increasingly important with higher resolution climate model output), or to more simply draw a physical boundary between regions for other purposes, such as flora and fauna habitat analysis, appropriate agricultural practices or water management.\u0000","PeriodicalId":55419,"journal":{"name":"Journal of Southern Hemisphere Earth Systems Science","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2021-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74947835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The El Niño-Southern Oscillation (ENSO) is the dominant driver of interannual variability on rainfall in many Pacific Islands and in countries bordering the tropical Pacific Ocean. From 1916 through to 1975, the correlation coefficient between the Southern Oscillation Index (SOI) and interannual variability in rainfall in eastern Australia was strong in negative phases of the Interdecadal Pacific Oscillation (IPO) but weak in positive phases. By examining records of rainfall over the past hundred years in central Vanuatu and on the ‘dry side’ of Fiji, which both lie near the southern edge of the South Pacific Convergence Zone (SPCZ), we find that such modulation by IPO has been much weaker there than in eastern Australia. This paper examines possible reasons for this difference. We also find that the correlation between rainfall and the SOI remained strong throughout each of the past three phases of the IPO, in all these places, including eastern Australia. However, at Rarotonga in the southern Cook Islands, whose position is also near the southern edge of the SPCZ, but at the southeastern end, the displacement of the SPCZ by ENSO events is greater there than further west. Consequently, the correlation between rainfall and SOI is so strong at Rarotonga in El Niño years with SOI<−5 that SOI alone becomes a good predictor of wet-season rainfall there. The difference in modulation of rainfall in eastern Australia between the two positive phases of IPO (1926–1941 and 1978–1998) may be due to the influence on Australia of other climatic oscillations, such as the Indian Ocean Dipole, though other factors may also have played a role.
{"title":"Interdecadal modulation of the effect of ENSO on rainfall in the southwestern Pacific","authors":"T. Weir, R. Kumar, Arona Ngari","doi":"10.1071/ES19053","DOIUrl":"https://doi.org/10.1071/ES19053","url":null,"abstract":"\u0000The El Niño-Southern Oscillation (ENSO) is the dominant driver of interannual variability on rainfall in many Pacific Islands and in countries bordering the tropical Pacific Ocean. From 1916 through to 1975, the correlation coefficient between the Southern Oscillation Index (SOI) and interannual variability in rainfall in eastern Australia was strong in negative phases of the Interdecadal Pacific Oscillation (IPO) but weak in positive phases. By examining records of rainfall over the past hundred years in central Vanuatu and on the ‘dry side’ of Fiji, which both lie near the southern edge of the South Pacific Convergence Zone (SPCZ), we find that such modulation by IPO has been much weaker there than in eastern Australia. This paper examines possible reasons for this difference. We also find that the correlation between rainfall and the SOI remained strong throughout each of the past three phases of the IPO, in all these places, including eastern Australia. However, at Rarotonga in the southern Cook Islands, whose position is also near the southern edge of the SPCZ, but at the southeastern end, the displacement of the SPCZ by ENSO events is greater there than further west. Consequently, the correlation between rainfall and SOI is so strong at Rarotonga in El Niño years with SOI<−5 that SOI alone becomes a good predictor of wet-season rainfall there. The difference in modulation of rainfall in eastern Australia between the two positive phases of IPO (1926–1941 and 1978–1998) may be due to the influence on Australia of other climatic oscillations, such as the Indian Ocean Dipole, though other factors may also have played a role.\u0000","PeriodicalId":55419,"journal":{"name":"Journal of Southern Hemisphere Earth Systems Science","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2021-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87663235","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper presents the tracking and short-term forecasting of mesoscale convective cloud clusters (CCs) that occurred over southeast Brazil and the adjacent Atlantic Ocean during 2009–17. These events produce intense rainfall and severe storms that impact agriculture, defence, hydroelectricity and offshore oil production. To identify, track and forecast CCs, the Geostationary Operational Environmental Satellite infrared imagery and the Forecasting and Tracking the Evolution of Cloud Clusters method are used. The forecast performance is investigated by applying statistical analyses between the observed and forecasted CCs’ physical properties. A total of 7139 mesoscale convective CCs were identified, tracked and selected for the short-term forecasting at their maturation phases. The CC tracking showed a high frequency of CCs over the Atlantic Ocean and mainly over continental and coastal southeast Brazil during the wet season. This indicates an important role played by the cold fronts and convective diurnal forcing on the organisation of convective cloudiness over that region. The majority of the CCs reached their maturation phases within the first 2h of life cycle, which occurred mostly between the late afternoon and evening. The CCs had short lifetimes and were predominantly in meso-β scales, followed by meso-α convective CCs. The CCs showed cloud-top temperatures typical of clouds with strong vertical development and potential to produce rainfall. The short-term forecasting of CCs at their maturation phases revealed different behaviours of the statistical indices with forecast range. For the 30–60-min timeframe, the forecasts performed relatively well. For longer forecast lead times (90–120min), the forecasts overestimated the occurrences, intensities and growth of the CCs and forecasted the CCs to be further north and east of their actual observed locations. Overall, our results may contribute to improving the forecast quality of these intense weather events.
{"title":"Tracking and short-term forecasting of mesoscale convective cloud clusters over southeast Brazil using satellite infrared imagery","authors":"J. Siqueira, V. D. S. Marques","doi":"10.1071/ES19050","DOIUrl":"https://doi.org/10.1071/ES19050","url":null,"abstract":"\u0000This paper presents the tracking and short-term forecasting of mesoscale convective cloud clusters (CCs) that occurred over southeast Brazil and the adjacent Atlantic Ocean during 2009–17. These events produce intense rainfall and severe storms that impact agriculture, defence, hydroelectricity and offshore oil production. To identify, track and forecast CCs, the Geostationary Operational Environmental Satellite infrared imagery and the Forecasting and Tracking the Evolution of Cloud Clusters method are used. The forecast performance is investigated by applying statistical analyses between the observed and forecasted CCs’ physical properties. A total of 7139 mesoscale convective CCs were identified, tracked and selected for the short-term forecasting at their maturation phases. The CC tracking showed a high frequency of CCs over the Atlantic Ocean and mainly over continental and coastal southeast Brazil during the wet season. This indicates an important role played by the cold fronts and convective diurnal forcing on the organisation of convective cloudiness over that region. The majority of the CCs reached their maturation phases within the first 2h of life cycle, which occurred mostly between the late afternoon and evening. The CCs had short lifetimes and were predominantly in meso-β scales, followed by meso-α convective CCs. The CCs showed cloud-top temperatures typical of clouds with strong vertical development and potential to produce rainfall. The short-term forecasting of CCs at their maturation phases revealed different behaviours of the statistical indices with forecast range. For the 30–60-min timeframe, the forecasts performed relatively well. For longer forecast lead times (90–120min), the forecasts overestimated the occurrences, intensities and growth of the CCs and forecasted the CCs to be further north and east of their actual observed locations. Overall, our results may contribute to improving the forecast quality of these intense weather events.\u0000","PeriodicalId":55419,"journal":{"name":"Journal of Southern Hemisphere Earth Systems Science","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2021-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86328266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This is a summary of the southern hemisphere atmospheric circulation patterns and meteorological indices for summer 2018–19; an account of seasonal rainfall and temperature for the Australian region is also provided. January 2019 was Australia’s hottest month on record, nearly 1°C warmer than any previous month. Impacts of heavy rain and floods were reported in Australia, New Zealand and South American nations. Extreme terrestrial and maritime heatwaves occurred in and around Australia and New Zealand. Case studies of the Australian heatwave, Queensland floods in January and February, and a tide-driven coastal inundation event are considered.
{"title":"Seasonal climate summary for Australia and the southern hemisphere (summer 2018–19): extreme heat and flooding prominent","authors":"B. Hague","doi":"10.1071/ES20009","DOIUrl":"https://doi.org/10.1071/ES20009","url":null,"abstract":"\u0000This is a summary of the southern hemisphere atmospheric circulation patterns and meteorological indices for summer 2018–19; an account of seasonal rainfall and temperature for the Australian region is also provided. January 2019 was Australia’s hottest month on record, nearly 1°C warmer than any previous month. Impacts of heavy rain and floods were reported in Australia, New Zealand and South American nations. Extreme terrestrial and maritime heatwaves occurred in and around Australia and New Zealand. Case studies of the Australian heatwave, Queensland floods in January and February, and a tide-driven coastal inundation event are considered.\u0000","PeriodicalId":55419,"journal":{"name":"Journal of Southern Hemisphere Earth Systems Science","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2021-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73119466","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Severe surface wind gusts produced by thunderstorms have the potential to damage infrastructure and are a major hazard for society. Wind gust data are examined from 35 observing stations around Australia, with lightning observations used to indicate the occurrence of deep convective processes in the vicinity of the observed wind gusts. A collation of severe thunderstorm reports is also used to complement the station wind gust data. Atmospheric reanalysis data are used to systematically examine large-scale environmental measures associated with severe convective winds. We find that methods based on environmental measures provide a better indication of the observed severe convective winds than the simulated model wind gusts from the reanalysis data, noting that the spatial scales on which these events occur are typically smaller than the reanalysis grid cells. Consistent with previous studies in other regions and idealised modelling, the majority of severe convective wind events are found to occur in environments with steep mid-level tropospheric lapse rates, moderate convective instability and strong background wind speeds. A large proportion of events from measured station data occur with relatively dry environmental air at low levels, although it is unknown to what extent this type of environment is representative of other severe wind-producing convective modes in Australia. The occurrence of severe convective winds is found to be well represented by a number of indices used previously for forecasting applications, such as the weighted product of convective available potential energy (CAPE) and vertical wind shear, the derecho composite parameter and the total totals index, as well as by logistic regression methods applied to environmental variables. Based on the systematic approach used in this study, our findings provide new insight on spatio-temporal variations in the risk of damaging winds occurring, including the environmental factors associated with their occurrence.
{"title":"Severe convection-related winds in Australia and their associated environments","authors":"Andrew Brown, A. Dowdy","doi":"10.1071/ES19052","DOIUrl":"https://doi.org/10.1071/ES19052","url":null,"abstract":"\u0000Severe surface wind gusts produced by thunderstorms have the potential to damage infrastructure and are a major hazard for society. Wind gust data are examined from 35 observing stations around Australia, with lightning observations used to indicate the occurrence of deep convective processes in the vicinity of the observed wind gusts. A collation of severe thunderstorm reports is also used to complement the station wind gust data. Atmospheric reanalysis data are used to systematically examine large-scale environmental measures associated with severe convective winds. We find that methods based on environmental measures provide a better indication of the observed severe convective winds than the simulated model wind gusts from the reanalysis data, noting that the spatial scales on which these events occur are typically smaller than the reanalysis grid cells. Consistent with previous studies in other regions and idealised modelling, the majority of severe convective wind events are found to occur in environments with steep mid-level tropospheric lapse rates, moderate convective instability and strong background wind speeds. A large proportion of events from measured station data occur with relatively dry environmental air at low levels, although it is unknown to what extent this type of environment is representative of other severe wind-producing convective modes in Australia. The occurrence of severe convective winds is found to be well represented by a number of indices used previously for forecasting applications, such as the weighted product of convective available potential energy (CAPE) and vertical wind shear, the derecho composite parameter and the total totals index, as well as by logistic regression methods applied to environmental variables. Based on the systematic approach used in this study, our findings provide new insight on spatio-temporal variations in the risk of damaging winds occurring, including the environmental factors associated with their occurrence.\u0000","PeriodicalId":55419,"journal":{"name":"Journal of Southern Hemisphere Earth Systems Science","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2021-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84233389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Deryn Griffiths, N. Loveday, Benjamin Price, Michael Foley, Alistair McKelvie
The Flip-Flop Index, designed to quantify the extent to which a forecast changes from one issue time to the next, is extended to a Circular Flip-Flop Index for use with forecasts of wind direction, swell direction or similar. The index was devised so we could understand the degree of stability in wind direction forecasts. The Circular Flip Flop Index is independent of observations, has a relatively simple definition and does not penalise a sequence of forecasts that show a trend as long as the forecasts stay within a 180° sector. The Circular Flip-Flop Index is interpreted in terms of the impact of changing forecasts on decisions made by users of the forecast. The Circular Flip-Flop Index has been used to compare the stability of sequences of automated forecast guidance to the official Australian Bureau of Meteorology forecasts, which are prepared manually. It is the first objective assessment of the stability of forecasts of direction. The results show that the forecasts of wind direction from the automated forecast guidance, itself a consensus of many numerical weather models, are more stable than the official, manual forecasts. The Circular Flip-Flop Index does not measure skill but can play a complementary role in characterising and evaluating a forecasting system.
{"title":"Circular Flip-Flop Index: quantifying revision stability of forecasts of direction","authors":"Deryn Griffiths, N. Loveday, Benjamin Price, Michael Foley, Alistair McKelvie","doi":"10.1071/es21010","DOIUrl":"https://doi.org/10.1071/es21010","url":null,"abstract":"The Flip-Flop Index, designed to quantify the extent to which a forecast changes from one issue time to the next, is extended to a Circular Flip-Flop Index for use with forecasts of wind direction, swell direction or similar. The index was devised so we could understand the degree of stability in wind direction forecasts. The Circular Flip Flop Index is independent of observations, has a relatively simple definition and does not penalise a sequence of forecasts that show a trend as long as the forecasts stay within a 180° sector. The Circular Flip-Flop Index is interpreted in terms of the impact of changing forecasts on decisions made by users of the forecast. The Circular Flip-Flop Index has been used to compare the stability of sequences of automated forecast guidance to the official Australian Bureau of Meteorology forecasts, which are prepared manually. It is the first objective assessment of the stability of forecasts of direction. The results show that the forecasts of wind direction from the automated forecast guidance, itself a consensus of many numerical weather models, are more stable than the official, manual forecasts. The Circular Flip-Flop Index does not measure skill but can play a complementary role in characterising and evaluating a forecasting system.","PeriodicalId":55419,"journal":{"name":"Journal of Southern Hemisphere Earth Systems Science","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82906543","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Variability and trend of sea level in southern waters of Java, Indonesia","authors":"A. Nurlatifah, Martono, I. Susanti, M. Suhermat","doi":"10.1071/es21004","DOIUrl":"https://doi.org/10.1071/es21004","url":null,"abstract":"","PeriodicalId":55419,"journal":{"name":"Journal of Southern Hemisphere Earth Systems Science","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81480363","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Examination of events occurring over the last 53 years in the Australian Region have revealed in the minds of forecasters a common pattern in the development of severe extratropical cyclones which have affected the sub-tropical and temperate East Coast. To evaluate this theory 20 years of data were systematically examined and showed that this was true. To represent these many cases nine such events which delivered the largest impacts over the 53 years were chosen for study. These extratropical cyclones formed downstream of a tropopause undulation which can be easily identified as a warm region at the 200 hPa-level and the formation zone was in a region of heavy rain embedded in a region of warm air advection at 700 hPa. There were hardly any exceptions to this general rule, and one that occurred is presented and was also one of the most rapidly developing systems. This pattern is then evaluated against tropical cyclone events which move in the Australasian sub tropics and three different scenarios are described and compared with a mature severe tropical cyclone which intensified as it moved into the Australia sub tropics. Hurricane Sandy due to its devastating effect on the US sub-tropics in 2012 is examined as a benchmark case whose impact could affect the Australasian sub tropics in the future as sea levels rise with higher density populations.
{"title":"East coast lows and extratropical transition of tropical cyclones, structures producing severe events and their comparison with mature tropical cyclones","authors":"J. Callaghan","doi":"10.1071/es21003","DOIUrl":"https://doi.org/10.1071/es21003","url":null,"abstract":"Examination of events occurring over the last 53 years in the Australian Region have revealed in the minds of forecasters a common pattern in the development of severe extratropical cyclones which have affected the sub-tropical and temperate East Coast. To evaluate this theory 20 years of data were systematically examined and showed that this was true. To represent these many cases nine such events which delivered the largest impacts over the 53 years were chosen for study. These extratropical cyclones formed downstream of a tropopause undulation which can be easily identified as a warm region at the 200 hPa-level and the formation zone was in a region of heavy rain embedded in a region of warm air advection at 700 hPa. There were hardly any exceptions to this general rule, and one that occurred is presented and was also one of the most rapidly developing systems. This pattern is then evaluated against tropical cyclone events which move in the Australasian sub tropics and three different scenarios are described and compared with a mature severe tropical cyclone which intensified as it moved into the Australia sub tropics. Hurricane Sandy due to its devastating effect on the US sub-tropics in 2012 is examined as a benchmark case whose impact could affect the Australasian sub tropics in the future as sea levels rise with higher density populations.","PeriodicalId":55419,"journal":{"name":"Journal of Southern Hemisphere Earth Systems Science","volume":null,"pages":null},"PeriodicalIF":3.6,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81760495","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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