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- Author or Editor: E. J. Walsh x
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Abstract
A regional climate model (DARLAM) is implemented over the Australian region and a 20-yr seasonally varying simulation is examined for the presence of tropical cyclone–like vortices (TCLVs). The horizontal resolution of the model is 125 km with nine vertical levels and is forced at its boundaries by the output of the Commonwealth Scientific and Industrial Research Organisation GCM using a mixed layer (or “slab”) ocean. Additional simulations are performed with a horizontal resolution of 30 km and with 18 vertical levels to examine the impact of increasing resolution on storm intensity. A sample of TCLVs from the 125-km resolution simulation is simulated at 30-km resolution to determine whether they reach observed tropical storm intensity at the finer resolution. It is found that stronger vortices in the 125-km resolution simulation are more likely to intensify when simulated at finer resolution than weaker vortices. In this way, a detection threshold for vortices generated in the 125-km resolution simulation is established and then used to detect TCLVs in that simulation. The regional climate model DARLAM provides a good simulation of both cyclogenesis and its seasonal variation under the current climate. The response of the model under enhanced greenhouse conditions is studied. Under 2 × CO2 conditions, there is no statistically significant change in regions of formation of TCLVs, with only a slight southward shift simulated. Nevertheless, there are statistically significant effects on the poleward movement of TCLVs, with storms generally tending to travel farther poleward in a warmer climate once they have formed. An analysis is undertaken to determine the reasons for this behavior. While the dynamical constraints on the maintenance of TCLV intensity under 2 × CO2 conditions (e.g., vertical wind shear) are similar to those in the current climate, thermodynamic conditions (e.g., sea surface temperatures) are quite different and are likely to be at least partly the cause of this effect. Other causes include the combination of the slight southward shift in formation and a tendency for TCLV tracks to be more southward in enhanced greenhouse conditions, a consequence of more southward steering winds.
Abstract
A regional climate model (DARLAM) is implemented over the Australian region and a 20-yr seasonally varying simulation is examined for the presence of tropical cyclone–like vortices (TCLVs). The horizontal resolution of the model is 125 km with nine vertical levels and is forced at its boundaries by the output of the Commonwealth Scientific and Industrial Research Organisation GCM using a mixed layer (or “slab”) ocean. Additional simulations are performed with a horizontal resolution of 30 km and with 18 vertical levels to examine the impact of increasing resolution on storm intensity. A sample of TCLVs from the 125-km resolution simulation is simulated at 30-km resolution to determine whether they reach observed tropical storm intensity at the finer resolution. It is found that stronger vortices in the 125-km resolution simulation are more likely to intensify when simulated at finer resolution than weaker vortices. In this way, a detection threshold for vortices generated in the 125-km resolution simulation is established and then used to detect TCLVs in that simulation. The regional climate model DARLAM provides a good simulation of both cyclogenesis and its seasonal variation under the current climate. The response of the model under enhanced greenhouse conditions is studied. Under 2 × CO2 conditions, there is no statistically significant change in regions of formation of TCLVs, with only a slight southward shift simulated. Nevertheless, there are statistically significant effects on the poleward movement of TCLVs, with storms generally tending to travel farther poleward in a warmer climate once they have formed. An analysis is undertaken to determine the reasons for this behavior. While the dynamical constraints on the maintenance of TCLV intensity under 2 × CO2 conditions (e.g., vertical wind shear) are similar to those in the current climate, thermodynamic conditions (e.g., sea surface temperatures) are quite different and are likely to be at least partly the cause of this effect. Other causes include the combination of the slight southward shift in formation and a tendency for TCLV tracks to be more southward in enhanced greenhouse conditions, a consequence of more southward steering winds.
Abstract
Idealized tropical cyclones are inserted into a regional climate model and the resulting intensity evolution of the storms is examined under current and enhanced greenhouse climates. The regional climate model is implemented over a model domain near Australia. In general, storm intensities increase under enhanced greenhouse conditions, although these increases are mostly not statistically significant. The simulated intensities are compared to theoretically derived estimates of maximum potential intensity. The theoretical estimates are mostly larger than the simulated intensities, suggesting that other factors may be limiting the intensification of the storms. Two such factors are suggested: the limited horizontal resolution of the storm simulations and the presence of vertical wind shear. Significant regression relations are demonstrated between maximum intensity of the simulated storms as predicted by sea surface temperature and vertical wind shear variations, while much weaker relationships are shown between maximum intensity and sea surface temperature alone. This suggests that dynamical influences such as vertical wind shear, which are not included in theoretical estimates of maximum potential intensity, act to restrict the development of the storm and thereby its maximum intensity.
Abstract
Idealized tropical cyclones are inserted into a regional climate model and the resulting intensity evolution of the storms is examined under current and enhanced greenhouse climates. The regional climate model is implemented over a model domain near Australia. In general, storm intensities increase under enhanced greenhouse conditions, although these increases are mostly not statistically significant. The simulated intensities are compared to theoretically derived estimates of maximum potential intensity. The theoretical estimates are mostly larger than the simulated intensities, suggesting that other factors may be limiting the intensification of the storms. Two such factors are suggested: the limited horizontal resolution of the storm simulations and the presence of vertical wind shear. Significant regression relations are demonstrated between maximum intensity of the simulated storms as predicted by sea surface temperature and vertical wind shear variations, while much weaker relationships are shown between maximum intensity and sea surface temperature alone. This suggests that dynamical influences such as vertical wind shear, which are not included in theoretical estimates of maximum potential intensity, act to restrict the development of the storm and thereby its maximum intensity.
Abstract
This study examines the influence of ENSO on the diurnal cycle of rainfall during boreal winter for the period 1998–2010 over the Maritime Continent (MC) and Australia using Tropical Rainfall Measuring Mission (TRMM) and reanalysis data. The diurnal cycles are composited for the ENSO cold (La Niña) and warm (El Niño) phases. The k-means clustering technique is then applied to group the TRMM data into six clusters, each with a distinct diurnal cycle. Despite the alternating patterns of widespread large-scale subsidence and ascent associated with the Walker circulation, which dominates the climate over the MC during the opposing phases of ENSO, many of the islands of the MC show localized differences in rainfall anomalies that depend on the local geography and orography. While ocean regions mostly experience positive rainfall anomalies during La Niña, some local regions over the islands have more rainfall during El Niño. These local features are also associated with anomalies in the amplitude and characteristics of the diurnal cycle in these regions. These differences are also well depicted in large-scale dynamical fields derived from the interim ECMWF Re-Analysis (ERA-Interim).
Abstract
This study examines the influence of ENSO on the diurnal cycle of rainfall during boreal winter for the period 1998–2010 over the Maritime Continent (MC) and Australia using Tropical Rainfall Measuring Mission (TRMM) and reanalysis data. The diurnal cycles are composited for the ENSO cold (La Niña) and warm (El Niño) phases. The k-means clustering technique is then applied to group the TRMM data into six clusters, each with a distinct diurnal cycle. Despite the alternating patterns of widespread large-scale subsidence and ascent associated with the Walker circulation, which dominates the climate over the MC during the opposing phases of ENSO, many of the islands of the MC show localized differences in rainfall anomalies that depend on the local geography and orography. While ocean regions mostly experience positive rainfall anomalies during La Niña, some local regions over the islands have more rainfall during El Niño. These local features are also associated with anomalies in the amplitude and characteristics of the diurnal cycle in these regions. These differences are also well depicted in large-scale dynamical fields derived from the interim ECMWF Re-Analysis (ERA-Interim).
Abstract
This study examines the variation in tropical cyclone (TC) intensity for different phases of the El Niño–Southern Oscillation (ENSO) phenomenon in the Fiji, Samoa, and Tonga (FST) region. The variation in TC intensity is inferred from the accumulated cyclone energy (ACE), which is constructed from the 6-hourly Joint Typhoon Warning Center best-track data for the period 1985–2006. Overall, results suggest that ACE in the FST region is considerably influenced by the ENSO signal. A substantial contribution to this ENSO signal in ACE comes from the region equatorward of 15°S where TC numbers, lifetime, and intensity all play a significant role. However, the ACE–ENSO relationship weakens substantially poleward of 15°S where large-scale environmental variables affecting TC intensity are found to be less favorable during El Niño years than during La Niña years; in the region equatorward of 15°S, the reverse is true. Therefore, TCs entering this region poleward of 15°S are able to sustain their intensity for a longer period of time during La Niña years as opposed to TCs entering the region during El Niño years, when they decay more rapidly.
Abstract
This study examines the variation in tropical cyclone (TC) intensity for different phases of the El Niño–Southern Oscillation (ENSO) phenomenon in the Fiji, Samoa, and Tonga (FST) region. The variation in TC intensity is inferred from the accumulated cyclone energy (ACE), which is constructed from the 6-hourly Joint Typhoon Warning Center best-track data for the period 1985–2006. Overall, results suggest that ACE in the FST region is considerably influenced by the ENSO signal. A substantial contribution to this ENSO signal in ACE comes from the region equatorward of 15°S where TC numbers, lifetime, and intensity all play a significant role. However, the ACE–ENSO relationship weakens substantially poleward of 15°S where large-scale environmental variables affecting TC intensity are found to be less favorable during El Niño years than during La Niña years; in the region equatorward of 15°S, the reverse is true. Therefore, TCs entering this region poleward of 15°S are able to sustain their intensity for a longer period of time during La Niña years as opposed to TCs entering the region during El Niño years, when they decay more rapidly.
Abstract
This study presents a binary classification model for the prediction of tropical cyclone (TC) activity in the Fiji, Samoa, and Tonga regions (the FST region) using the accumulated cyclone energy (ACE) as a proxy of TC activity. A probit regression model, which is a suitable probability model for describing binary response data, is developed to determine at least a few months in advance (by July in this case) the probability that an upcoming TC season may have for high or low TC activity. Years of “high TC activity” are defined as those years when ACE values exceeded the sample climatology (i.e., the 1985–2008 mean value). Model parameters are determined using the Bayesian method. Various combinations of the El Niño–Southern Oscillation (ENSO) indices and large-scale environmental conditions that are known to affect TCs in the FST region are examined as potential predictors. It was found that a set of predictors comprising low-level relative vorticity, upper-level divergence, and midtropspheric relative humidity provided the best skill in terms of minimum hindcast error. Results based on hindcast verification clearly suggest that the model predicts TC activity in the FST region with substantial skill up to the May–July preseason for all years considered in the analysis, in particular for ENSO-neutral years when TC activity is known to show large variations.
Abstract
This study presents a binary classification model for the prediction of tropical cyclone (TC) activity in the Fiji, Samoa, and Tonga regions (the FST region) using the accumulated cyclone energy (ACE) as a proxy of TC activity. A probit regression model, which is a suitable probability model for describing binary response data, is developed to determine at least a few months in advance (by July in this case) the probability that an upcoming TC season may have for high or low TC activity. Years of “high TC activity” are defined as those years when ACE values exceeded the sample climatology (i.e., the 1985–2008 mean value). Model parameters are determined using the Bayesian method. Various combinations of the El Niño–Southern Oscillation (ENSO) indices and large-scale environmental conditions that are known to affect TCs in the FST region are examined as potential predictors. It was found that a set of predictors comprising low-level relative vorticity, upper-level divergence, and midtropspheric relative humidity provided the best skill in terms of minimum hindcast error. Results based on hindcast verification clearly suggest that the model predicts TC activity in the FST region with substantial skill up to the May–July preseason for all years considered in the analysis, in particular for ENSO-neutral years when TC activity is known to show large variations.
Abstract
An objective methodology for forecasting the probability of tropical cyclone (TC) formation in the Fiji, Samoa, and Tonga regions (collectively the FST region) using antecedent large-scale environmental conditions is investigated. Three separate probabilistic forecast schemes are developed using a probit regression approach where model parameters are determined via Bayesian fitting. These schemes provide forecasts of TC formation from an existing system (i) within the next 24 h (W24h), (ii) within the next 48 h (W48h), and (iii) within the next 72 h (W72h). To assess the performance of the three forecast schemes in practice, verification methods such as the posterior expected error, Brier skill scores, and relative operating characteristic skill scores are applied. Results suggest that the W24h scheme, which is formulated using large-scale environmental parameters, on average, performs better than that formulated using climatology and persistence (CLIPER) variables. In contrast, the W48h (W72h) scheme formulated using large-scale environmental parameters performs similar to (poorer than) that formulated using CLIPER variables. Therefore, large-scale environmental parameters (CLIPER variables) are preferred as predictors when forecasting TC formation in the FST region within 24 h (at least 48 h) using models formulated in the present investigation.
Abstract
An objective methodology for forecasting the probability of tropical cyclone (TC) formation in the Fiji, Samoa, and Tonga regions (collectively the FST region) using antecedent large-scale environmental conditions is investigated. Three separate probabilistic forecast schemes are developed using a probit regression approach where model parameters are determined via Bayesian fitting. These schemes provide forecasts of TC formation from an existing system (i) within the next 24 h (W24h), (ii) within the next 48 h (W48h), and (iii) within the next 72 h (W72h). To assess the performance of the three forecast schemes in practice, verification methods such as the posterior expected error, Brier skill scores, and relative operating characteristic skill scores are applied. Results suggest that the W24h scheme, which is formulated using large-scale environmental parameters, on average, performs better than that formulated using climatology and persistence (CLIPER) variables. In contrast, the W48h (W72h) scheme formulated using large-scale environmental parameters performs similar to (poorer than) that formulated using CLIPER variables. Therefore, large-scale environmental parameters (CLIPER variables) are preferred as predictors when forecasting TC formation in the FST region within 24 h (at least 48 h) using models formulated in the present investigation.
Abstract
Significant advances have been made in understanding the key climate factors responsible for tropical cyclone (TC) activity, yet any theory that estimates likelihood of observed TC formation rates from mean climate states remains elusive. The present study investigates how the extremes of observed TC genesis (TCG) frequency during peak TC seasons are interrelated with distinct changes in the large-scale climate conditions over different ocean basins using the global International Best Track Archive for Climate Stewardship (IBTrACS) dataset and ERA-Interim for the period 1979–2014. Peak TC seasons with significantly high and low TCG frequency are identified for five major ocean basins, and their substantial spatial changes in TCG are noted with regionally distinct differences. To explore the possible climate link behind such changes, a suite of potentially relevant dynamic and thermodynamic climate conditions is analyzed. Results indicate that the observed changes in extreme TCG frequency are closely linked with distinct dominance of specific dynamic and thermodynamic climate conditions over different regions. While the combined influences of dynamic and thermodynamic climate conditions are found to be necessary for modulating TC formation rate over the North Atlantic, eastern Pacific, and southern Indian Oceans, significant changes in large-scale dynamic conditions appear to solely control the TCG frequency over the western Pacific and South Pacific basins. Estimation of the fractional changes in genesis-weighted climate conditions also indicates the coherent but distinct competing effects of different climate conditions on TCG frequency. The present study further points out the need for revising the existing genesis indices for estimating TCG frequency over individual basins.
Abstract
Significant advances have been made in understanding the key climate factors responsible for tropical cyclone (TC) activity, yet any theory that estimates likelihood of observed TC formation rates from mean climate states remains elusive. The present study investigates how the extremes of observed TC genesis (TCG) frequency during peak TC seasons are interrelated with distinct changes in the large-scale climate conditions over different ocean basins using the global International Best Track Archive for Climate Stewardship (IBTrACS) dataset and ERA-Interim for the period 1979–2014. Peak TC seasons with significantly high and low TCG frequency are identified for five major ocean basins, and their substantial spatial changes in TCG are noted with regionally distinct differences. To explore the possible climate link behind such changes, a suite of potentially relevant dynamic and thermodynamic climate conditions is analyzed. Results indicate that the observed changes in extreme TCG frequency are closely linked with distinct dominance of specific dynamic and thermodynamic climate conditions over different regions. While the combined influences of dynamic and thermodynamic climate conditions are found to be necessary for modulating TC formation rate over the North Atlantic, eastern Pacific, and southern Indian Oceans, significant changes in large-scale dynamic conditions appear to solely control the TCG frequency over the western Pacific and South Pacific basins. Estimation of the fractional changes in genesis-weighted climate conditions also indicates the coherent but distinct competing effects of different climate conditions on TCG frequency. The present study further points out the need for revising the existing genesis indices for estimating TCG frequency over individual basins.
Abstract
A diagonostic analysis is made of a midwinter mesoscale vortex that developed over the Mississippi Valley and produced moderate to heavy snow with gale force winds (>18 m s−1), lightning, and thunder along a narrow track approximately 1500 km in length. The mesoscale vortex resembled the so-called “polar lows” that form over the subpolar seas. The similarities include development on the cyclonic-shear side of a long-wave trough, strong positive vorticity advection associated with a 500 mb short-wave trough, upstream tilt of the geopotential heights, conditional instability in the lower troposphere, a southeastward track, small (∼200 km) diameter, and a 9 mb deepening of the surface mesolow in 12 h. The most intriguing features of the present analysis are the extremely large potential vorticities and horizontal temperature gradients in the midtroposphere, indicating an extrusion of stratospheric air down to levels below 700 mb.
Abstract
A diagonostic analysis is made of a midwinter mesoscale vortex that developed over the Mississippi Valley and produced moderate to heavy snow with gale force winds (>18 m s−1), lightning, and thunder along a narrow track approximately 1500 km in length. The mesoscale vortex resembled the so-called “polar lows” that form over the subpolar seas. The similarities include development on the cyclonic-shear side of a long-wave trough, strong positive vorticity advection associated with a 500 mb short-wave trough, upstream tilt of the geopotential heights, conditional instability in the lower troposphere, a southeastward track, small (∼200 km) diameter, and a 9 mb deepening of the surface mesolow in 12 h. The most intriguing features of the present analysis are the extremely large potential vorticities and horizontal temperature gradients in the midtroposphere, indicating an extrusion of stratospheric air down to levels below 700 mb.
Abstract
This study examines the modulation of tropical cyclone (TC) activity by the Madden–Julian oscillation (MJO) in the Fiji, Samoa, and Tonga regions (FST region), using Joint Typhoon Warning Center best-track cyclone data and the MJO index developed by Wheeler and Hendon. Results suggest strong MJO–TC relationships in the FST region. The TC genesis patterns are significantly altered over the FST region with approximately 5 times more cyclones forming in the active phase than in the inactive phase of the MJO. This modulation is further strengthened during El Niño periods. The large-scale environmental conditions (i.e., low-level relative vorticity, upper-level divergence, and vertical wind shear) associated with TC genesis show a distinct patterns of variability for the active and inactive MJO phases. The MJO also has a significant effect on hurricane category and combined gale and storm category cyclones in the FST region. The occurrences of both these cyclone categories are increased in the active phase of the MJO, which is associated with enhanced convective activity. The TCs in the other MJO phases where convective activity is relatively low, however, show a consistent pattern of increase in hurricane category cyclones and a concomitant decrease in gale and storm category cyclones. Finally, TC tracks in different MJO phases are also objectively described using a cluster analysis technique. Patterns seen in the clustered track regimes are well explained here in terms of 700–500-hPa mean steering flow.
Abstract
This study examines the modulation of tropical cyclone (TC) activity by the Madden–Julian oscillation (MJO) in the Fiji, Samoa, and Tonga regions (FST region), using Joint Typhoon Warning Center best-track cyclone data and the MJO index developed by Wheeler and Hendon. Results suggest strong MJO–TC relationships in the FST region. The TC genesis patterns are significantly altered over the FST region with approximately 5 times more cyclones forming in the active phase than in the inactive phase of the MJO. This modulation is further strengthened during El Niño periods. The large-scale environmental conditions (i.e., low-level relative vorticity, upper-level divergence, and vertical wind shear) associated with TC genesis show a distinct patterns of variability for the active and inactive MJO phases. The MJO also has a significant effect on hurricane category and combined gale and storm category cyclones in the FST region. The occurrences of both these cyclone categories are increased in the active phase of the MJO, which is associated with enhanced convective activity. The TCs in the other MJO phases where convective activity is relatively low, however, show a consistent pattern of increase in hurricane category cyclones and a concomitant decrease in gale and storm category cyclones. Finally, TC tracks in different MJO phases are also objectively described using a cluster analysis technique. Patterns seen in the clustered track regimes are well explained here in terms of 700–500-hPa mean steering flow.
