Episodes of dry‐air intrusion over northern India have been observed during break phases of the Indian summer monsoon (ISM). Previous investigations have provided observational evidence of a significant reservoir of unsaturated air over the northern Arabian Sea, serving as the source of this dry‐air intrusion. It was also suggested that the monsoon low‐level jet, which typically transports moisture to continental India during the active phase, instead transports dry air during the break phase of the ISM. While the existence of dry‐air intrusion is well‐documented through observations, its representation in climate models remains uncertain. It is important to enhance our understanding of the process of dry‐air advection in climate models to assess their fidelity in simulating the climate over the region. In this study, we quantify the extent of dry‐air intrusion and examine its mechanisms in simulations from the sixth phase of the Coupled Model Intercomparison Project (CMIP6). Most CMIP6 models analysed in this study simulate the observed pattern of dry‐air advection over continental India realistically during the summer monsoon‐break phase. Some models also simulate dry‐air transport from West Asia, possibly due to an overly smoothed representation of orography. Furthermore, the majority of CMIP6 models successfully capture the intrinsic modes associated with the dry monsoon phase, as demonstrated by empirical orthogonal function analysis of low‐level zonal winds. Our analyses indicate that global climate models exhibit better skill in simulating dry processes of the monsoon compared with moist processes. These findings uncover previously underexplored aspects of the monsoon, which are essential for assessing future regional climate changes accurately.
在印度夏季季风（ISM）的间歇期，印度北部曾出现过干燥空气入侵现象。以前的调查提供了观测证据，证明阿拉伯海北部有大量不饱和空气，是这种干燥空气入侵的来源。还有人认为，季风低空喷流通常在季风活跃期向印度大陆输送水汽，而在 ISM 的间歇期则输送干燥空气。虽然干空气入侵的存在已通过观测得到充分证明，但其在气候模式中的表现仍不确定。加强对气候模式中干燥空气平流过程的了解，对评估气候模式模拟该地区气候的真实性非常重要。在本研究中，我们对耦合模式相互比较项目（CMIP6）第六阶段模拟中的干燥空气入侵程度进行了量化，并研究了其机制。本研究分析的大多数 CMIP6 模式都真实地模拟了夏季季风爆发阶段印度大陆上空观测到的干燥空气对流模式。一些模式还模拟了来自西亚的干燥空气输送，这可能是由于对地形的描述过于平滑所致。此外，大多数 CMIP6 模式成功地捕捉到了与干旱季风阶段相关的固有模式，这一点通过对低层带状风的经验正交函数分析得到了证明。我们的分析表明，与湿润过程相比，全球气候模式在模拟季风的干燥过程方面表现出更好的技能。这些发现揭示了季风以前未被充分探索的方面，这对于准确评估未来区域气候变化至关重要。
{"title":"Dry‐air intrusion over India during break phases of the Indian summer monsoon in CMIP6 models","authors":"Rahul Singh, S. Sandeep","doi":"10.1002/qj.4788","DOIUrl":"https://doi.org/10.1002/qj.4788","url":null,"abstract":"Episodes of dry‐air intrusion over northern India have been observed during break phases of the Indian summer monsoon (ISM). Previous investigations have provided observational evidence of a significant reservoir of unsaturated air over the northern Arabian Sea, serving as the source of this dry‐air intrusion. It was also suggested that the monsoon low‐level jet, which typically transports moisture to continental India during the active phase, instead transports dry air during the break phase of the ISM. While the existence of dry‐air intrusion is well‐documented through observations, its representation in climate models remains uncertain. It is important to enhance our understanding of the process of dry‐air advection in climate models to assess their fidelity in simulating the climate over the region. In this study, we quantify the extent of dry‐air intrusion and examine its mechanisms in simulations from the sixth phase of the Coupled Model Intercomparison Project (CMIP6). Most CMIP6 models analysed in this study simulate the observed pattern of dry‐air advection over continental India realistically during the summer monsoon‐break phase. Some models also simulate dry‐air transport from West Asia, possibly due to an overly smoothed representation of orography. Furthermore, the majority of CMIP6 models successfully capture the intrinsic modes associated with the dry monsoon phase, as demonstrated by empirical orthogonal function analysis of low‐level zonal winds. Our analyses indicate that global climate models exhibit better skill in simulating dry processes of the monsoon compared with moist processes. These findings uncover previously underexplored aspects of the monsoon, which are essential for assessing future regional climate changes accurately.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":"56 1 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2024-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141526699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mireia Udina, Eric Peinó, Francesc Polls, Jordi Mercader, Iciar Guerrero, Arianna Valmassoi, Alexandre Paci, Joan Bech
The Land Surface Interactions with the Atmosphere over the Iberian Semi‐arid Environment (LIAISE) campaign examined the impact of anthropization on the water cycle in terms of land–atmosphere–hydrology interactions. The objective of this study is to assess the effects of irrigation on the atmosphere and on precipitation in Weather Research and Forecasting model simulations during the LIAISE special observation period in July 2021. Comparisons between simulations and observations show better verification scores for air temperature, humidity, and wind speed and direction when the model included the irrigation parametrization, improving the model warm and dry bias at 2 m over irrigated areas. Other changes found are the weakening of the sea breeze circulation and a more realistic surface energy partitioning representation. The boundary‐layer height is lowered in the vicinity of irrigated areas, causing a decrease in the lifting condensation level and the level of free convection, which induce increases in convective available potential energy and convective inhibition. Precipitation differences between simulations become relevant for smaller areas, close to the irrigated land. When convection is parametrized, simulations including irrigation tend to produce a decrease in rainfall (negative feedback), whereas convection‐permitting simulations produce an increase (positive feedback), although the latter underestimates substantially the observed precipitation field. In addition, irrigation activation decreases the areas exceeding moderate hourly precipitation intensities in all simulations. There is a local impact of irrigated land on model‐resolved precipitation accumulations and intensities, although including the irrigation parametrization did not improve the representation of the observed precipitation field, as probably the precipitation systems during the LIAISE special observation period in July 2021 were mostly driven by larger scale perturbations or mesoscale systems, more than by local processes. Results reported here not only contribute to enhance our understanding of irrigation effects upon precipitation but also demonstrate the need to include irrigation parametrizations in numerical forecasts to overcome the biases found.
{"title":"Irrigation impact on boundary layer and precipitation characteristics in Weather Research and Forecasting model simulations during LIAISE‐2021","authors":"Mireia Udina, Eric Peinó, Francesc Polls, Jordi Mercader, Iciar Guerrero, Arianna Valmassoi, Alexandre Paci, Joan Bech","doi":"10.1002/qj.4756","DOIUrl":"https://doi.org/10.1002/qj.4756","url":null,"abstract":"The Land Surface Interactions with the Atmosphere over the Iberian Semi‐arid Environment (LIAISE) campaign examined the impact of anthropization on the water cycle in terms of land–atmosphere–hydrology interactions. The objective of this study is to assess the effects of irrigation on the atmosphere and on precipitation in Weather Research and Forecasting model simulations during the LIAISE special observation period in July 2021. Comparisons between simulations and observations show better verification scores for air temperature, humidity, and wind speed and direction when the model included the irrigation parametrization, improving the model warm and dry bias at 2 m over irrigated areas. Other changes found are the weakening of the sea breeze circulation and a more realistic surface energy partitioning representation. The boundary‐layer height is lowered in the vicinity of irrigated areas, causing a decrease in the lifting condensation level and the level of free convection, which induce increases in convective available potential energy and convective inhibition. Precipitation differences between simulations become relevant for smaller areas, close to the irrigated land. When convection is parametrized, simulations including irrigation tend to produce a decrease in rainfall (negative feedback), whereas convection‐permitting simulations produce an increase (positive feedback), although the latter underestimates substantially the observed precipitation field. In addition, irrigation activation decreases the areas exceeding moderate hourly precipitation intensities in all simulations. There is a local impact of irrigated land on model‐resolved precipitation accumulations and intensities, although including the irrigation parametrization did not improve the representation of the observed precipitation field, as probably the precipitation systems during the LIAISE special observation period in July 2021 were mostly driven by larger scale perturbations or mesoscale systems, more than by local processes. Results reported here not only contribute to enhance our understanding of irrigation effects upon precipitation but also demonstrate the need to include irrigation parametrizations in numerical forecasts to overcome the biases found.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":"22 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141195378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In May 2015, the southeastern coastal states of India encountered one of the deadliest heatwaves in Indian history. Researchers have extensively studied the event to understand the underlying mechanisms and concluded that horizontal warm‐air advection from northwestern parts of India and adiabatic heating were the main attributing factors for the event. However, the large‐scale atmospheric processes that led to these conditions have not been thoroughly explored. In the present study, we show that this event was largely associated with the boreal summer intraseasonal oscillation (BSISO) that is prominent during this season. Our analysis shows that the BSISO dry phase lead to a persistent high‐pressure system, with anomalous subsidence favoring adiabatic heating and anticyclonic circulation anomalies increasing the northwesterly warm‐air advection. It is shown that a 55% to 75% contribution to the maximum surface air temperature (SAT) anomalies during the heatwave period can be attributed to BSISO‐related temperature anomalies. Furthermore, the results show that, in the absence of BSISO, the heat event would have dissipated with 1–2 hot days with much less intensity and the presence of the BSISO dry phase extended the heatwave duration by six days. The impact of BSISO on this heatwave was further substantiated by sensitivity experiments using the Weather Research and Forecasting (WRF) model. This analysis emphasizes that improving the forecasting skills of BSISO may facilitate the subseasonal forecast of local heatwave events.
{"title":"Assessing the role of boreal summer intraseasonal oscillation on the severe heatwave of May 2015 over India","authors":"Tukaram Zore, Kiranmayi Landu","doi":"10.1002/qj.4765","DOIUrl":"https://doi.org/10.1002/qj.4765","url":null,"abstract":"In May 2015, the southeastern coastal states of India encountered one of the deadliest heatwaves in Indian history. Researchers have extensively studied the event to understand the underlying mechanisms and concluded that horizontal warm‐air advection from northwestern parts of India and adiabatic heating were the main attributing factors for the event. However, the large‐scale atmospheric processes that led to these conditions have not been thoroughly explored. In the present study, we show that this event was largely associated with the boreal summer intraseasonal oscillation (BSISO) that is prominent during this season. Our analysis shows that the BSISO dry phase lead to a persistent high‐pressure system, with anomalous subsidence favoring adiabatic heating and anticyclonic circulation anomalies increasing the northwesterly warm‐air advection. It is shown that a 55% to 75% contribution to the maximum surface air temperature (SAT) anomalies during the heatwave period can be attributed to BSISO‐related temperature anomalies. Furthermore, the results show that, in the absence of BSISO, the heat event would have dissipated with 1–2 hot days with much less intensity and the presence of the BSISO dry phase extended the heatwave duration by six days. The impact of BSISO on this heatwave was further substantiated by sensitivity experiments using the Weather Research and Forecasting (WRF) model. This analysis emphasizes that improving the forecasting skills of BSISO may facilitate the subseasonal forecast of local heatwave events.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":"5 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141195308","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
K. Van Weverberg, N. Ghilain, E. Goudenhoofdt, M. Barbier, E. Koistinen, S. Doutreloup, B. Van Schaeybroeck, A. Frankl, P. Field
This article presents an evaluation and sensitivity analysis of km‐scale simulations of an unprecedented extreme rainfall event over Europe, with a specific focus on sub‐hourly extremes, size distributions, and kinetic energy (KE) of rain. These variables are critical for hydrological applications, such as flood forecasting or soil‐loss monitoring, but are rarely directly obtained from numerical weather prediction (NWP) models. The simulations presented here reproduce the overall characteristics of the event, but overestimate the extreme rain rates. The rain rate–KE relation was well‐captured, despite too large volume‐mean drop diameters. Amongst the sensitivities investigated, the representation of the raindrop self‐collection–breakup equilibrium and the raindrop size‐distribution shape were found to have the most profound impact on the rainfall characteristics. While extreme rain rates varied within 30%, the rain KE varied by a factor of four between the realistic perturbations to the microphysical assumptions. Changes to the aerosol concentration and rain terminal velocity relations were found to have a relatively smaller impact. Given the large uncertainties, a continued effort to improve the model physics will be indispensable to estimate rain intensities and KE reliably for direct hydrological applications.
本文对欧洲上空前所未有的极端降雨事件的千米尺度模拟进行了评估和敏感性分析，重点关注每小时以下的极端降雨量、雨量大小分布和雨的动能（KE）。这些变量对水文应用（如洪水预报或土壤流失监测）至关重要，但很少能从数值天气预报（NWP）模式中直接获取。本文介绍的模拟再现了事件的总体特征，但高估了极端降雨率。尽管雨滴的体积-平均直径过大，但仍很好地捕捉到了雨率-KE 关系。在所研究的敏感性中，发现雨滴自收集-破裂平衡的表示方法和雨滴大小-分布形状对降雨特征的影响最大。虽然极端降雨率的变化在 30% 以内，但降雨 KE 在微观物理假设的实际扰动之间相差四倍。气溶胶浓度和降雨末端速度关系的变化产生的影响相对较小。鉴于存在很大的不确定性，要可靠地估算出直接用于水文应用的降雨强度和 KE 值，就必须继续努力改进模型物理。
{"title":"Sensitivity of simulated rain intensity and kinetic energy to aerosols and warm‐rain microphysics during the extreme event of July 2021 in Belgium","authors":"K. Van Weverberg, N. Ghilain, E. Goudenhoofdt, M. Barbier, E. Koistinen, S. Doutreloup, B. Van Schaeybroeck, A. Frankl, P. Field","doi":"10.1002/qj.4761","DOIUrl":"https://doi.org/10.1002/qj.4761","url":null,"abstract":"This article presents an evaluation and sensitivity analysis of km‐scale simulations of an unprecedented extreme rainfall event over Europe, with a specific focus on sub‐hourly extremes, size distributions, and kinetic energy (KE) of rain. These variables are critical for hydrological applications, such as flood forecasting or soil‐loss monitoring, but are rarely directly obtained from numerical weather prediction (NWP) models. The simulations presented here reproduce the overall characteristics of the event, but overestimate the extreme rain rates. The rain rate–KE relation was well‐captured, despite too large volume‐mean drop diameters. Amongst the sensitivities investigated, the representation of the raindrop self‐collection–breakup equilibrium and the raindrop size‐distribution shape were found to have the most profound impact on the rainfall characteristics. While extreme rain rates varied within 30%, the rain KE varied by a factor of four between the realistic perturbations to the microphysical assumptions. Changes to the aerosol concentration and rain terminal velocity relations were found to have a relatively smaller impact. Given the large uncertainties, a continued effort to improve the model physics will be indispensable to estimate rain intensities and KE reliably for direct hydrological applications.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":"30 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2024-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141171175","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Martin Ridal, Eric Bazile, Patrick Le Moigne, Roger Randriamampianina, Semjon Schimanke, Ulf Andrae, Lars Berggren, Pierre Brousseau, Per Dahlgren, Lisette Edvinsson, Adam El‐Said, Michael Glinton, Susanna Hagelin, Susanna Hopsch, Ludvig Isaksson, Paulo Medeiros, Esbjörn Olsson, Per Unden, Zheng Qi Wang
A regional reanalysis has been produced for a domain covering entire Europe from 1984 to 2021. The reanalysis is produced as part of the Copernicus Climate Change Service. The Service provides the high‐resolution deterministic Copernicus European Regional Reanalysis (CERRA), run at a horizontal resolution of 5.5 km, a 10‐member ensemble run at 11‐km resolution as well as an offline surface analysis, CERRA‐Land. CERRA‐EDA uses an ensemble data assimilation (EDA) technique to perturb the initial condition of the different members. Apart from the horizontal resolution the CERRA and CERRA‐EDA setups are the same; for example, the same data assimilation scheme, same physics parameterization as well as the same vertical levels. These new systems are built from HARMONIE cy40 version, including some back‐phased physics from a newer model version (cy42). Conventional observations, satellite‐based radiances, atmospheric motion vector winds and bending angle from radio occultation observations are used. In addition, ground‐based zenith total delay (ZTD) from global navigational satellite systems (GNSS) and local surface observations, rescued from historical archives at the local National Meteorological Services, are used. Another new feature is the construction of the background error statistics for the data assimilation. Information from the ensemble run, CERRA‐EDA, is used in the derivation of the background error statistics for the high‐resolution CERRA runs. These background error statistics are updated every second day. By doing so, daily environment variation is taken into account as well as all variations over the 37 years of production. The reanalyses and reforecasts from CERRA show an added value compared to the global ERA5 for almost all variables at the surface level. This becomes particularly clear when selecting smaller areas with complex terrain where the high resolution is beneficial. In the free atmosphere it is primarily the analyses and short forecasts, 3–6 hours, that give an added value.
{"title":"CERRA, the Copernicus European Regional Reanalysis system","authors":"Martin Ridal, Eric Bazile, Patrick Le Moigne, Roger Randriamampianina, Semjon Schimanke, Ulf Andrae, Lars Berggren, Pierre Brousseau, Per Dahlgren, Lisette Edvinsson, Adam El‐Said, Michael Glinton, Susanna Hagelin, Susanna Hopsch, Ludvig Isaksson, Paulo Medeiros, Esbjörn Olsson, Per Unden, Zheng Qi Wang","doi":"10.1002/qj.4764","DOIUrl":"https://doi.org/10.1002/qj.4764","url":null,"abstract":"A regional reanalysis has been produced for a domain covering entire Europe from 1984 to 2021. The reanalysis is produced as part of the Copernicus Climate Change Service. The Service provides the high‐resolution deterministic Copernicus European Regional Reanalysis (CERRA), run at a horizontal resolution of 5.5 km, a 10‐member ensemble run at 11‐km resolution as well as an offline surface analysis, CERRA‐Land. CERRA‐EDA uses an ensemble data assimilation (EDA) technique to perturb the initial condition of the different members. Apart from the horizontal resolution the CERRA and CERRA‐EDA setups are the same; for example, the same data assimilation scheme, same physics parameterization as well as the same vertical levels. These new systems are built from HARMONIE cy40 version, including some back‐phased physics from a newer model version (cy42). Conventional observations, satellite‐based radiances, atmospheric motion vector winds and bending angle from radio occultation observations are used. In addition, ground‐based zenith total delay (ZTD) from global navigational satellite systems (GNSS) and local surface observations, rescued from historical archives at the local National Meteorological Services, are used. Another new feature is the construction of the background error statistics for the data assimilation. Information from the ensemble run, CERRA‐EDA, is used in the derivation of the background error statistics for the high‐resolution CERRA runs. These background error statistics are updated every second day. By doing so, daily environment variation is taken into account as well as all variations over the 37 years of production. The reanalyses and reforecasts from CERRA show an added value compared to the global ERA5 for almost all variables at the surface level. This becomes particularly clear when selecting smaller areas with complex terrain where the high resolution is beneficial. In the free atmosphere it is primarily the analyses and short forecasts, 3–6 hours, that give an added value.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":"234 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2024-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141171502","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Monin–Obukhov similarity theory (MOST) is used in virtually all Earth System Models to parametrize the near‐surface turbulent exchanges and mean variable profiles. Despite its widespread use, there is high uncertainty in the literature about the appropriate parametrizations to use. In addition, MOST has limitations in very stable and unstable regimes, over heterogeneous terrain and complex orography, and has been found to represent the surface fluxes incorrectly. A new approach including turbulence anisotropy as a non‐dimensional scaling parameter has recently been developed and has been shown to overcome these limitations and generalize the flux‐variance relations to complex terrain. In this article, we analyze the flux‐gradient relations for five well‐known datasets, ranging from flat and homogeneous to slightly complex terrain. The scaling relations show substantial scatter and highlight the uncertainty in the choice of parametrization even over canonical conditions. We show that, by including information on turbulence anisotropy as an additional scaling parameter, the original scatter becomes well bounded and new formulations can be developed that drastically improve the accuracy of the flux‐gradient relations for wind shear () in unstable conditions and for temperature gradient () in both unstable and stable regimes. This analysis shows that both and are strongly dependent on turbulence anisotropy and allows us finally to settle the extensively discussed free convection regime for , which clearly exhibits a power law when anisotropy is accounted for. Furthermore, we show that the eddy diffusivities for momentum and heat and the turbulent Prandtl number are strongly dependent on anisotropy and that the latter goes to zero in the free convection limit. These results highlight the necessity to include anisotropy in the study of near‐surface atmospheric turbulence and lead the way for theoretically more robust simulations of the boundary layer over complex terrain.
{"title":"Flux‐gradient relations and their dependence on turbulence anisotropy","authors":"Samuele Mosso, Marc Calaf, Ivana Stiperski","doi":"10.1002/qj.4762","DOIUrl":"https://doi.org/10.1002/qj.4762","url":null,"abstract":"Monin–Obukhov similarity theory (MOST) is used in virtually all Earth System Models to parametrize the near‐surface turbulent exchanges and mean variable profiles. Despite its widespread use, there is high uncertainty in the literature about the appropriate parametrizations to use. In addition, MOST has limitations in very stable and unstable regimes, over heterogeneous terrain and complex orography, and has been found to represent the surface fluxes incorrectly. A new approach including turbulence anisotropy as a non‐dimensional scaling parameter has recently been developed and has been shown to overcome these limitations and generalize the flux‐variance relations to complex terrain. In this article, we analyze the flux‐gradient relations for five well‐known datasets, ranging from flat and homogeneous to slightly complex terrain. The scaling relations show substantial scatter and highlight the uncertainty in the choice of parametrization even over canonical conditions. We show that, by including information on turbulence anisotropy as an additional scaling parameter, the original scatter becomes well bounded and new formulations can be developed that drastically improve the accuracy of the flux‐gradient relations for wind shear () in unstable conditions and for temperature gradient () in both unstable and stable regimes. This analysis shows that both and are strongly dependent on turbulence anisotropy and allows us finally to settle the extensively discussed free convection regime for , which clearly exhibits a power law when anisotropy is accounted for. Furthermore, we show that the eddy diffusivities for momentum and heat and the turbulent Prandtl number are strongly dependent on anisotropy and that the latter goes to zero in the free convection limit. These results highlight the necessity to include anisotropy in the study of near‐surface atmospheric turbulence and lead the way for theoretically more robust simulations of the boundary layer over complex terrain.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":"72 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2024-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141171250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The purpose of this study is to investigate the influence of the urban environment of the Paris region on an isolated convective cell that formed downwind of the city on May 7, 2022, using the Meso‐NH research atmospheric model at a horizontal scale of 300 m. To account for all sources of forecast uncertainty, the initial and lateral boundary conditions of the simulations are provided by an ensemble prediction system. A multi‐layer urban scheme is used to represent the influence of buildings on the airflow accurately. Two sets of ensemble simulations are performed: the first set (URB) uses a fine‐scale surface description of the city, while the second set (NOURB) replaces urban surfaces with vegetation. This sensitivity test shows that, despite the high variability of simulated precipitation within the ensemble, the city of Paris plays a statistically significant role in the initiation of convection in this case. Convective cells are initiated over the city for several members of the URB ensemble, while almost no precipitation is simulated for the same members of the NOURB ensemble. The mean 6‐h rainfall accumulation of the URB ensemble is increased by 70% over Paris (compared with the NOURB ensemble) and no statistically significant trend is found around the city. The analysis reveals that the capital experiences a higher sensible heat flux due to drier and warmer air, resulting in enhanced vertical velocities and an increase in boundary‐layer height in the URB ensemble. Additionally, the total water content and cloud fraction over Paris are intensified, leading to more precipitation. These findings suggest that urbanisation has a notable impact on convection and precipitation processes in this case.
{"title":"Urban influence on convective precipitation in the Paris region: Hectometric ensemble simulations in a case study","authors":"Arnaud Forster, Clotilde Augros, Valéry Masson","doi":"10.1002/qj.4749","DOIUrl":"https://doi.org/10.1002/qj.4749","url":null,"abstract":"The purpose of this study is to investigate the influence of the urban environment of the Paris region on an isolated convective cell that formed downwind of the city on May 7, 2022, using the Meso‐NH research atmospheric model at a horizontal scale of 300 m. To account for all sources of forecast uncertainty, the initial and lateral boundary conditions of the simulations are provided by an ensemble prediction system. A multi‐layer urban scheme is used to represent the influence of buildings on the airflow accurately. Two sets of ensemble simulations are performed: the first set (URB) uses a fine‐scale surface description of the city, while the second set (NOURB) replaces urban surfaces with vegetation. This sensitivity test shows that, despite the high variability of simulated precipitation within the ensemble, the city of Paris plays a statistically significant role in the initiation of convection in this case. Convective cells are initiated over the city for several members of the URB ensemble, while almost no precipitation is simulated for the same members of the NOURB ensemble. The mean 6‐h rainfall accumulation of the URB ensemble is increased by 70% over Paris (compared with the NOURB ensemble) and no statistically significant trend is found around the city. The analysis reveals that the capital experiences a higher sensible heat flux due to drier and warmer air, resulting in enhanced vertical velocities and an increase in boundary‐layer height in the URB ensemble. Additionally, the total water content and cloud fraction over Paris are intensified, leading to more precipitation. These findings suggest that urbanisation has a notable impact on convection and precipitation processes in this case.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":"244 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2024-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141171320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Peter Schaumann, Martin Rempel, Ulrich Blahak, Volker Schmidt
Many post‐processing methods improve forecasts at individual locations but remove their correlation structure. However, this information is essential for forecasting larger‐scale events, such as the total precipitation amount over areas like river catchments, which are relevant for weather warnings and flood predictions. We propose a method to reintroduce spatial correlation into a post‐processed forecast using an R‐vine copula fitted to historical observations. The method rearranges predictions at individual locations and ensures that they still exhibit the post‐processed marginal distributions. It works similarly to well‐known approaches, like the “Schaake shuffle” and “ensemble copula coupling.” However, compared to these methods, which rely on a ranking with no ties at each considered location in their source for spatial correlation, the copula serves as a measure of how well a given arrangement compares with the observed historical distribution. Therefore, no close relationship is required between the post‐processed marginal distributions and the spatial correlation source. This is advantageous for post‐processed seamless forecasts in two ways. First, meteorological parameters such as the precipitation amount, whose distribution has an atom at zero, have rankings with ties. Second, seamless forecasts represent an optimal combination of their input forecasts and may spatially shifted from them at scales larger than the areas considered herein, leading to non‐reasonable spatial correlation sources for the well‐known methods. Our results indicate that the calibration of the combination model carries over to the output of the proposed model, that is, the evaluation of area predictions shows a similar improvement in forecast quality as the predictions for individual locations. Additionally, the spatial correlation of the forecast is evaluated with the help of object‐based metrics, for which the proposed model also shows an improvement compared to both input forecasts.
{"title":"Generating synthetic rainfall fields by R‐vine copulas applied to seamless probabilistic predictions","authors":"Peter Schaumann, Martin Rempel, Ulrich Blahak, Volker Schmidt","doi":"10.1002/qj.4751","DOIUrl":"https://doi.org/10.1002/qj.4751","url":null,"abstract":"Many post‐processing methods improve forecasts at individual locations but remove their correlation structure. However, this information is essential for forecasting larger‐scale events, such as the total precipitation amount over areas like river catchments, which are relevant for weather warnings and flood predictions. We propose a method to reintroduce spatial correlation into a post‐processed forecast using an R‐vine copula fitted to historical observations. The method rearranges predictions at individual locations and ensures that they still exhibit the post‐processed marginal distributions. It works similarly to well‐known approaches, like the “Schaake shuffle” and “ensemble copula coupling.” However, compared to these methods, which rely on a ranking with no ties at each considered location in their source for spatial correlation, the copula serves as a measure of how well a given arrangement compares with the observed historical distribution. Therefore, no close relationship is required between the post‐processed marginal distributions and the spatial correlation source. This is advantageous for post‐processed seamless forecasts in two ways. First, meteorological parameters such as the precipitation amount, whose distribution has an atom at zero, have rankings with ties. Second, seamless forecasts represent an optimal combination of their input forecasts and may spatially shifted from them at scales larger than the areas considered herein, leading to non‐reasonable spatial correlation sources for the well‐known methods. Our results indicate that the calibration of the combination model carries over to the output of the proposed model, that is, the evaluation of area predictions shows a similar improvement in forecast quality as the predictions for individual locations. Additionally, the spatial correlation of the forecast is evaluated with the help of object‐based metrics, for which the proposed model also shows an improvement compared to both input forecasts.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":"26 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2024-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141146397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Flash flooding is a significant societal problem, but related precipitation forecasts are often poor. To address, one can try to use output from convection‐parametrising (global) ensembles, post‐processed to forecast at point‐scale, or convection‐resolving limited area ensembles. The new methodology described here combines both. We apply “ecPoint‐rainfall” post‐processing to the ECMWF global ensemble. Alongside we use 2.2 km COSMO LAM ensemble output (centred on Italy), and also post‐process that, using a scale‐selective neighbourhood approach to compensate for insufficient members and to preserve consistently forecast local details. The two resulting scale‐compatible components then undergo lead‐time‐weighted blending, to create the final probabilistic 6 h rainfall forecasts. Product creation for forecasters, in this way, constituted the “Italy Flash Flood use case” within the EU‐funded MISTRAL project; real‐time delivery of open access products is ongoing. One year of verification shows that, of the five components (2 raw, 2 post‐processed and blended), ecPoint is the most skilful. The post‐processed COSMO ensemble adds most value to summer convective events in the evening, when the global model has an underprediction bias. In two typical heavy rainfall case studies we observed underestimation of the largest point totals in the raw ECMWF ensemble, and overestimation in the raw COSMO ensemble. However, ecPoint elevated the ECMWF maxima and highlighted best the most affected areas and merged products seemed to be the most skilful of all. Even though our LAM post‐processing does not include (or arguably need) bias‐correction, this study still provides a unique blueprint for successfully combining ensemble rainfall forecasts from global and LAM systems around the world. It also has important implications for forecast products as global ensembles move ever closer to having convection‐permitting resolution.
{"title":"Post‐processing output from ensembles with and without parametrised convection, to create accurate, blended, high‐fidelity rainfall forecasts","authors":"Estíbaliz Gascón, Andrea Montani, Tim D. Hewson","doi":"10.1002/qj.4753","DOIUrl":"https://doi.org/10.1002/qj.4753","url":null,"abstract":"Flash flooding is a significant societal problem, but related precipitation forecasts are often poor. To address, one can try to use output from convection‐parametrising (global) ensembles, post‐processed to forecast at point‐scale, or convection‐resolving limited area ensembles. The new methodology described here combines both. We apply “ecPoint‐rainfall” post‐processing to the ECMWF global ensemble. Alongside we use 2.2 km COSMO LAM ensemble output (centred on Italy), and also post‐process that, using a scale‐selective neighbourhood approach to compensate for insufficient members and to preserve consistently forecast local details. The two resulting scale‐compatible components then undergo lead‐time‐weighted blending, to create the final probabilistic 6 h rainfall forecasts. Product creation for forecasters, in this way, constituted the “Italy Flash Flood use case” within the EU‐funded MISTRAL project; real‐time delivery of open access products is ongoing. One year of verification shows that, of the five components (2 raw, 2 post‐processed and blended), ecPoint is the most skilful. The post‐processed COSMO ensemble adds most value to summer convective events in the evening, when the global model has an underprediction bias. In two typical heavy rainfall case studies we observed underestimation of the largest point totals in the raw ECMWF ensemble, and overestimation in the raw COSMO ensemble. However, ecPoint elevated the ECMWF maxima and highlighted best the most affected areas and merged products seemed to be the most skilful of all. Even though our LAM post‐processing does not include (or arguably need) bias‐correction, this study still provides a unique blueprint for successfully combining ensemble rainfall forecasts from global and LAM systems around the world. It also has important implications for forecast products as global ensembles move ever closer to having convection‐permitting resolution.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":"172 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2024-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141059874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Specification of the observation‐error covariance matrix for data assimilation systems affects the observation information content retained by the analysis, particularly for observations known to have correlated observation errors (e.g., geostationary satellite and Doppler radar data). A widely adopted approach for estimating observation‐error covariance matrices uses observation‐minus‐background and observation‐minus‐analysis residuals, which are routinely produced by most data assimilation systems. Although this approach is known to produce biased and noisy estimates, due to sampling and misspecification errors, there has been no systematic study of sampling errors with this approach to date. Furthermore, the eigenspectrum of the estimated observation‐error covariance matrix is known to influence the analysis information content and numerical convergence of variational assimilation schemes. In this work, we provide new theorems for the sampling error and eigenvalues of the estimated observation‐error covariance matrices with this approach. We also conduct numerical experiments to illustrate our theoretical results. We find that this method produces large sampling errors if the true observation‐error standard deviation is large, while the other error characteristics, including the true background‐error standard deviation and observation‐ and background‐error correlation length‐scales, have a relatively small effect. We also find that the smallest eigenvalues of the estimated matrices may be smaller or larger than the true eigenvalues, depending on the assumed and true observation‐ and background‐error statistics. These results may provide insights for practical applications: for example, in deciding on appropriate sample sizes and choosing parameters for matrix reconditioning techniques.
{"title":"Sampling and misspecification errors in the estimation of observation‐error covariance matrices using observation‐minus‐background and observation‐minus‐analysis statistics","authors":"Guannan Hu, Sarah L. Dance","doi":"10.1002/qj.4750","DOIUrl":"https://doi.org/10.1002/qj.4750","url":null,"abstract":"Specification of the observation‐error covariance matrix for data assimilation systems affects the observation information content retained by the analysis, particularly for observations known to have correlated observation errors (e.g., geostationary satellite and Doppler radar data). A widely adopted approach for estimating observation‐error covariance matrices uses observation‐minus‐background and observation‐minus‐analysis residuals, which are routinely produced by most data assimilation systems. Although this approach is known to produce biased and noisy estimates, due to sampling and misspecification errors, there has been no systematic study of sampling errors with this approach to date. Furthermore, the eigenspectrum of the estimated observation‐error covariance matrix is known to influence the analysis information content and numerical convergence of variational assimilation schemes. In this work, we provide new theorems for the sampling error and eigenvalues of the estimated observation‐error covariance matrices with this approach. We also conduct numerical experiments to illustrate our theoretical results. We find that this method produces large sampling errors if the true observation‐error standard deviation is large, while the other error characteristics, including the true background‐error standard deviation and observation‐ and background‐error correlation length‐scales, have a relatively small effect. We also find that the smallest eigenvalues of the estimated matrices may be smaller or larger than the true eigenvalues, depending on the assumed and true observation‐ and background‐error statistics. These results may provide insights for practical applications: for example, in deciding on appropriate sample sizes and choosing parameters for matrix reconditioning techniques.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":"49 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2024-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141059644","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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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