Sam Hardy, J. Methven, J. Schwendike, B. Harvey, M. Cullen
Abstract. Cyclonic vortices that are weaker than tropical storm category can bring heavy precipitation as they propagate across the South China Sea and surrounding countries. Here we investigate the structure and dynamics responsible for the intensification of a Borneo vortex that moved from the north of Borneo across the South China Sea and impacted Vietnam and Thailand in late October 2018. This case study is examined using Met Office Unified Model (MetUM) simulations and a semi-geotriptic (SGT) balance approximation tool. Satellite observations and a MetUM simulation with 4.4 km grid initialised at 12:00 UTC on 21 October 2018 show that the westward-moving vortex is characterised by a coherent maximum in total column water and by a comma-shaped precipitation structure with the heaviest rainfall to the northwest of the circulation centre. The Borneo vortex comprises a low-level cyclonic circulation and a mid-level wave embedded in the background easterly shear flow, which strengthens with height up to around 7 km. Despite being in the tropics at 6∘ N, the low-level vortex and mid-level wave are well represented by SGT balance dynamics. The mid-level wave propagates along a vertical gradient in moist stability, i.e. the product between the specific humidity and the static stability, at 4.5 to 5 km and is characterised by a coherent signature in the potential vorticity, meridional wind, and balanced vertical velocity fields. The vertical motion is dominated by coupling with diabatic heating and is shifted relative to the potential vorticity so that the diabatic wave propagates westwards, relative to the flow, at a rate consistent with prediction from moist semi-geostrophic theory. Initial vortex development at low levels is consistent with baroclinic growth initiated by the mid-level diabatic Rossby wave, which propagates on baroclinic shear flow on the southern flank of a large-scale cold surge.
{"title":"Examining the dynamics of a Borneo vortex using a balance approximation tool","authors":"Sam Hardy, J. Methven, J. Schwendike, B. Harvey, M. Cullen","doi":"10.5194/wcd-4-1019-2023","DOIUrl":"https://doi.org/10.5194/wcd-4-1019-2023","url":null,"abstract":"Abstract. Cyclonic vortices that are weaker than tropical storm category can bring heavy precipitation as they propagate across the South China Sea and surrounding countries. Here we investigate the structure and dynamics responsible for the intensification of a Borneo vortex that moved from the north of Borneo across the South China Sea and impacted Vietnam and Thailand in late October 2018. This case study is examined using Met Office Unified Model (MetUM) simulations and a semi-geotriptic (SGT) balance approximation tool. Satellite observations and a MetUM simulation with 4.4 km grid initialised at 12:00 UTC on 21 October 2018 show that the westward-moving vortex is characterised by a coherent maximum in total column water and by a comma-shaped precipitation structure with the heaviest rainfall to the northwest of the circulation centre. The Borneo vortex comprises a low-level cyclonic circulation and a mid-level wave embedded in the background easterly shear flow, which strengthens with height up to around 7 km. Despite being in the tropics at 6∘ N, the low-level vortex and mid-level wave are well represented by SGT balance dynamics. The mid-level wave propagates along a vertical gradient in moist stability, i.e. the product between the specific humidity and the static stability, at 4.5 to 5 km and is characterised by a coherent signature in the potential vorticity, meridional wind, and balanced vertical velocity fields. The vertical motion is dominated by coupling with diabatic heating and is shifted relative to the potential vorticity so that the diabatic wave propagates westwards, relative to the flow, at a rate consistent with prediction from moist semi-geostrophic theory. Initial vortex development at low levels is consistent with baroclinic growth initiated by the mid-level diabatic Rossby wave, which propagates on baroclinic shear flow on the southern flank of a large-scale cold surge.","PeriodicalId":508985,"journal":{"name":"Weather and Climate Dynamics","volume":"35 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139214444","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
David Martin Straus, Daniella I. V. Domeisen, Sarah-Jane Lock, Franco Molteni, P. Yadav
Abstract. Since the Madden–Julian oscillation (MJO) is a major source for tropical and extratropical variability on weekly to monthly timescales, the intrinsic predictability of its global teleconnections is of great interest. As the tropical diabatic heating associated with the MJO ultimately drives these teleconnections, the variability in heating among ensemble forecasts initialized from the same episode of the MJO will limit this predictability. In order to assess this limitation, a suite of 60 d ensemble reforecasts has been carried out with the ECMWF forecast model, spanning 13 starting dates from 1 November and 1 January for different years. The initial dates were chosen so that phases 2 and 3 of the MJO (with anomalous tropical heating in the Indian Ocean sector) were present in the observed initial conditions. The 51 members of an individual ensemble use identical initial conditions for the atmosphere and ocean. Stochastic perturbations to the tendencies produced by the atmospheric physics parameterizations are applied only over the Indian Ocean region (50–120∘ E). This guarantees that the spread between reforecasts within an ensemble is due to perturbations in heat sources only in the Indian Ocean sector. The point-wise spread in the intra-ensemble (or error) variance of vertically integrated tropical heating Q is larger than the average ensemble mean signal even at early forecast times; however the planetary wave (PW) component of Q (zonal waves 1–3) is predictable for 25 to 45 d, the time taken for the error variance to reach 50 % to 70 % of saturation. These scales never reach 90 % of saturation during the forecasts. The upper-level tropical PW divergence is even more predictable than Q (40 to 50 d). In contrast, the PW component of the 200 hPa Rossby wave source, which is responsible for propagating the influence of tropical heating to the extratropics, is only predictable for 20 to 30 d. A substantial ensemble spread of 300 hPa meridional wind propagates from the tropics to the Northern Hemisphere storm-track regions by days 15–16. Following the growth of upper-tropospheric spread in planetary wave heat flux, the stratosphere provides a feedback in enhancing the error via downward propagation towards the end of the reforecasts.
{"title":"Intrinsic predictability limits arising from Indian Ocean Madden–Julian oscillation (MJO) heating: effects on tropical and extratropical teleconnections","authors":"David Martin Straus, Daniella I. V. Domeisen, Sarah-Jane Lock, Franco Molteni, P. Yadav","doi":"10.5194/wcd-4-1001-2023","DOIUrl":"https://doi.org/10.5194/wcd-4-1001-2023","url":null,"abstract":"Abstract. Since the Madden–Julian oscillation (MJO) is a major source for tropical and extratropical variability on weekly to monthly timescales, the intrinsic predictability of its global teleconnections is of great interest. As the tropical diabatic heating associated with the MJO ultimately drives these teleconnections, the variability in heating among ensemble forecasts initialized from the same episode of the MJO will limit this predictability. In order to assess this limitation, a suite of 60 d ensemble reforecasts has been carried out with the ECMWF forecast model, spanning 13 starting dates from 1 November and 1 January for different years. The initial dates were chosen so that phases 2 and 3 of the MJO (with anomalous tropical heating in the Indian Ocean sector) were present in the observed initial conditions. The 51 members of an individual ensemble use identical initial conditions for the atmosphere and ocean. Stochastic perturbations to the tendencies produced by the atmospheric physics parameterizations are applied only over the Indian Ocean region (50–120∘ E). This guarantees that the spread between reforecasts within an ensemble is due to perturbations in heat sources only in the Indian Ocean sector. The point-wise spread in the intra-ensemble (or error) variance of vertically integrated tropical heating Q is larger than the average ensemble mean signal even at early forecast times; however the planetary wave (PW) component of Q (zonal waves 1–3) is predictable for 25 to 45 d, the time taken for the error variance to reach 50 % to 70 % of saturation. These scales never reach 90 % of saturation during the forecasts. The upper-level tropical PW divergence is even more predictable than Q (40 to 50 d). In contrast, the PW component of the 200 hPa Rossby wave source, which is responsible for propagating the influence of tropical heating to the extratropics, is only predictable for 20 to 30 d. A substantial ensemble spread of 300 hPa meridional wind propagates from the tropics to the Northern Hemisphere storm-track regions by days 15–16. Following the growth of upper-tropospheric spread in planetary wave heat flux, the stratosphere provides a feedback in enhancing the error via downward propagation towards the end of the reforecasts.","PeriodicalId":508985,"journal":{"name":"Weather and Climate Dynamics","volume":"76 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139251566","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Leah Eisenstein, Benedikt Schulz, J. Pinto, P. Knippertz
Abstract. Strong winds associated with extratropical cyclones are one of the most dangerous natural hazards in Europe. These high winds are mostly associated with five mesoscale features: the warm (conveyor belt) jet (WJ); the cold (conveyor belt) jet (CJ); cold frontal convection (CFC); strong cold-sector (CS) winds; and, in some cases, the sting jet (SJ). The timing within the cyclone's life cycle, the location relative to the cyclone core and further characteristics differ between these features and, hence, likely also their associated forecast errors. In Part 1 of this study (Eisenstein et al., 2022a), we introduced the objective and flexible identification tool RAMEFI (RAndom-forest-based MEsoscale wind Feature Identification), which distinguishes between the WJ, CFC and CS as well as CJ and SJ combined. RAMEFI is based on a probabilistic random forest trained on station observations of 12 storm cases over Europe. Being independent of spatial distribution, RAMEFI can also be applied to gridded data. Here, we use RAMEFI to compile a climatology over 19 extended winter seasons (October–March 2000–2019) based on high-resolution regional reanalyses of the German Consortium for Small-scale Modelling (COSMO) model over Europe. This allows the first ever long-term objective statistical analysis of the mesoscale wind features, including their occurrence frequency, geographical distribution and characteristics. For western and central Europe, we demonstrate that the CS is prominent in most winter storms, while CFC is the least common cause of high winds, both in terms of frequency and affected area. However, probably due to convective momentum transport, CFC is on average the cause of the highest gusts after the CJ and has the highest gust factor. As expected, CFC high-wind areas show high levels of humidity and overcast conditions. In contrast, the CS is characterised by sunnier conditions interspersed by patchy cumulus clouds, leading to a broader cloud cover distribution than for other features. The WJ produces the weakest winds on average but affects a larger area than CJ. Central Europe is more strongly affected by WJ and CFC winds, while the CJ usually occurs farther north over the North and Baltic seas, northern Germany, Denmark and southern Scandinavia. System-relative composites show that the WJ and CFC tend to occur earlier in the cyclone life cycle than the CJ and CS. Consistently, the CS is the most common cause of high winds over eastern Europe, where cyclones tend to occlude, represented by a narrowing warm sector and weakening cold front. The WJ mostly occurs within the south-eastern quadrant of a cyclone bordered by the narrow CFC in the west. However, the location of CFC varies greatly between cases. The CS occurs in the south-western quadrant, while the CJ appears closer to the cyclone centre, sometimes stretching into the south-eastern quadrant. This objective climatology largely confirms previous, more subjective investigations bu
摘要与外热带气旋相关的强风是欧洲最危险的自然灾害之一。这些强风主要与五个中尺度特征有关：暖（传送带）喷流（WJ）；冷（传送带）喷流（CJ）；冷锋对流（CFC）；强冷空气（CS）；以及在某些情况下的刺喷流（SJ）。这些特征在气旋生命周期中的时间、相对于气旋核心的位置和其他特征各不相同，因此也可能存在相关的预报误差。在本研究的第一部分（Eisenstein 等人，2022a）中，我们介绍了客观灵活的识别工具 RAMEFI（基于森林的中尺度风特征识别），它可以区分 WJ、CFC 和 CS 以及 CJ 和 SJ。RAMEFI 基于对欧洲 12 个风暴观测站观测数据进行训练的概率随机森林。RAMEFI 与空间分布无关，因此也可应用于网格数据。在此，我们利用 RAMEFI，基于德国小尺度模拟联合会（COSMO）模型在欧洲的高分辨率区域再分析，编制了 19 个冬季延长季节（2000 年 10 月至 2019 年 3 月）的气候学数据。这首次对中尺度风特征进行了长期客观的统计分析，包括其出现频率、地理分布和特征。对于欧洲西部和中部，我们证明 CS 在大多数冬季风暴中都很突出，而 CFC 在频率和受影响面积方面都是最不常见的大风原因。然而，可能是由于对流动量传输的原因，CFC 平均是继 CJ 之后导致最高阵风的原因，并且具有最高的阵风系数。不出所料，CFC 高风速地区的湿度和阴雨条件都很高。相比之下，CS 的特点是阳光充足，夹杂着零星积云，导致云层分布比其他特征更广。WJ 产生的平均风力最弱，但影响的区域比 CJ 大。中欧受 WJ 和 CFC 风的影响更大，而 CJ 通常出现在更北边的北海和波罗的海、德国北部、丹麦和斯堪的纳维亚半岛南部。系统相关合成显示，WJ 和 CFC 在气旋生命周期中出现的时间往往早于 CJ 和 CS。一直以来，CS 是造成东欧上空大风的最常见原因，气旋往往会在那里闭塞，表现为暖扇缩小和冷锋减弱。WJ 大多发生在气旋的东南象限内，与西部狭窄的 CFC 相邻。然而，不同情况下 CFC 的位置差异很大。CS 出现在西南象限，而 CJ 出现在离气旋中心更近的地方，有时会延伸到东南象限。这种客观的气候学研究在很大程度上证实了之前更为主观的调查，但也将这些调查纳入了气候学背景中。它允许对特征特性进行更详细的分析，并为未来研究中的模式评估和预报评价奠定了坚实的基础。
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