Rebecca Lynn Beal, Zhaoxia Pu, Eric Pardyjak, Sebastian Hoch, Ismail Gultepe
Cold fog refers to a type of fog that forms when the temperature is below 0°C. It can be composed of liquid, ice, and mixed‐phase fog particles. Cold fog happens frequently over mountainous terrain in the cold season, but it is difficult to predict. Using observations from the Cold Fog Amongst Complex Terrain (CFACT) field campaign conducted in Heber Valley, Utah, in the western United States during January and February of 2022, this study investigates the meteorological conditions in the surface and boundary layers that support the formation of wintertime ephemeral cold fog in a local area of small‐scale mountain valleys. It is found that fog formation is susceptible to subtleties in forcing conditions and is supported by several factors: (1) established high pressure over the Great Basin with associated local clear skies, calm winds, and a stable boundary layer; (2) near‐surface inversion with saturation near the surface and strong moisture gradient in the boundary layer; (3) warm (above‐freezing) daytime air temperature with a large diurnal range, accompanied with warm soil temperatures during the daytime; (4) a period of increased turbulence kinetic energy (above 0.5 m2·s−2), followed by calm conditions throughout the fog's duration; and (5) supersaturation with respect to ice. Then, the field observations and identified supporting factors for fog formation were utilized to evaluate high‐resolution (˜400 m horizontal grid spacing) Weather Research and Forecasting (WRF) model simulations. Results show that the WRF model accurately simulates the mesoscale conditions facilitating cold‐fog formation but misses some critical surface and atmospheric boundary conditions. The overall results from this paper indicate that these identified factors that support fog formation are vital to accurately forecasting cold‐fog events. At the same time, they are also critical fields for the NWP model validation.
{"title":"Evaluation of near‐surface and boundary‐layer meteorological conditions that support cold‐fog formation using Cold Fog Amongst Complex Terrain field campaign observations","authors":"Rebecca Lynn Beal, Zhaoxia Pu, Eric Pardyjak, Sebastian Hoch, Ismail Gultepe","doi":"10.1002/qj.4818","DOIUrl":"https://doi.org/10.1002/qj.4818","url":null,"abstract":"Cold fog refers to a type of fog that forms when the temperature is below 0°C. It can be composed of liquid, ice, and mixed‐phase fog particles. Cold fog happens frequently over mountainous terrain in the cold season, but it is difficult to predict. Using observations from the Cold Fog Amongst Complex Terrain (CFACT) field campaign conducted in Heber Valley, Utah, in the western United States during January and February of 2022, this study investigates the meteorological conditions in the surface and boundary layers that support the formation of wintertime ephemeral cold fog in a local area of small‐scale mountain valleys. It is found that fog formation is susceptible to subtleties in forcing conditions and is supported by several factors: (1) established high pressure over the Great Basin with associated local clear skies, calm winds, and a stable boundary layer; (2) near‐surface inversion with saturation near the surface and strong moisture gradient in the boundary layer; (3) warm (above‐freezing) daytime air temperature with a large diurnal range, accompanied with warm soil temperatures during the daytime; (4) a period of increased turbulence kinetic energy (above 0.5 m<jats:sup>2</jats:sup>·s<jats:sup>−2</jats:sup>), followed by calm conditions throughout the fog's duration; and (5) supersaturation with respect to ice. Then, the field observations and identified supporting factors for fog formation were utilized to evaluate high‐resolution (˜400 m horizontal grid spacing) Weather Research and Forecasting (WRF) model simulations. Results show that the WRF model accurately simulates the mesoscale conditions facilitating cold‐fog formation but misses some critical surface and atmospheric boundary conditions. The overall results from this paper indicate that these identified factors that support fog formation are vital to accurately forecasting cold‐fog events. At the same time, they are also critical fields for the NWP model validation.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":"8 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2024-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142188930","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}
Jeong‐Gil Lee, Yoo‐Geun Ham, Ji‐Gwang Kim, Pil‐Hun Chang
In this study, we developed a flow‐dependent oceanic initialization system for initializing the oceanic temperature and salinity in the Global Seasonal forecast system version 5 (GloSea5). Our algorithm overcomes the limitation of stationary perturbations for Ensemble Optimal Interpolation (EnOI) by spreading observed information along isopycnal lines to create three‐dimensional snapshot density states. The proposed algorithm, which we call state‐dependent ensemble‐based EnOI (SD‐EnOI), takes into account changes in the background error covariance over time without relying on ensemble model simulations. To evaluate the quality of the oceanic initial conditions (ICs) produced by SD‐EnOI, we compared them with those generated by the Global Ocean Data Assimilation and Prediction System version 1 (GODAPS1) operated by the Korea Meteorological Agency (KMA) throughout January 2017 to December 2017. Our findings show that the thermal construction of the SD‐EnOI ICs is more realistic than that of GODAPS1, particularly in the tropical Pacific region. The strong warm bias in sea surface temperature (SST) and the shallow mixed‐layer depth bias observed in the GODAPS1 ICs are not shown in SD‐EnOI. Due to the more realistic oceanic thermal structure present in the SD‐EnOI ICs, their use in retrospective forecast experiments resulted in a systematic reduction in climatological SST drift in the central‐eastern Pacific for forecasts up to four lead months compared to using GODAPS1 ICs. This demonstrates the significant impact of the initialization process on the quality of dynamical seasonal forecasts.
{"title":"Generation of state‐dependent ensemble perturbations based on time‐varying seawater density for GloSea5 initialization","authors":"Jeong‐Gil Lee, Yoo‐Geun Ham, Ji‐Gwang Kim, Pil‐Hun Chang","doi":"10.1002/qj.4833","DOIUrl":"https://doi.org/10.1002/qj.4833","url":null,"abstract":"In this study, we developed a flow‐dependent oceanic initialization system for initializing the oceanic temperature and salinity in the Global Seasonal forecast system version 5 (GloSea5). Our algorithm overcomes the limitation of stationary perturbations for Ensemble Optimal Interpolation (EnOI) by spreading observed information along isopycnal lines to create three‐dimensional snapshot density states. The proposed algorithm, which we call state‐dependent ensemble‐based EnOI (SD‐EnOI), takes into account changes in the background error covariance over time without relying on ensemble model simulations. To evaluate the quality of the oceanic initial conditions (ICs) produced by SD‐EnOI, we compared them with those generated by the Global Ocean Data Assimilation and Prediction System version 1 (GODAPS1) operated by the Korea Meteorological Agency (KMA) throughout January 2017 to December 2017. Our findings show that the thermal construction of the SD‐EnOI ICs is more realistic than that of GODAPS1, particularly in the tropical Pacific region. The strong warm bias in sea surface temperature (SST) and the shallow mixed‐layer depth bias observed in the GODAPS1 ICs are not shown in SD‐EnOI. Due to the more realistic oceanic thermal structure present in the SD‐EnOI ICs, their use in retrospective forecast experiments resulted in a systematic reduction in climatological SST drift in the central‐eastern Pacific for forecasts up to four lead months compared to using GODAPS1 ICs. This demonstrates the significant impact of the initialization process on the quality of dynamical seasonal forecasts.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":"13 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2024-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142188931","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}
Seasonal‐range predictability of summer climate in northwestern Europe is generally considered to be low. This is an increasing issue given the worsening impact of summer heatwaves, droughts and intense convective rainfall in a rapidly changing climate. In wintertime, predictive skill in the region is derived from a variety of sources, not least teleconnections with the El Niño‐Southern Oscillation (ENSO). Summer ENSO teleconnections, however, are often considered to be negligible. In this paper, we revisit the topic of summer teleconnections between ENSO and the North Atlantic‐European region. We build on previous work identifying upper tropospheric responses to tropical forcing, since dynamical teleconnections are most apparent at this level. Our results confirm that significantly increased geopotential heights are found stretching over the North‐Atlantic region and into western Europe when La Niña conditions are prevalent during summer. This pattern is part of the previously identified ‘circumglobal’ pattern of wider northern‐hemisphere height changes. We then look for these responses in a range of climate models used in operational seasonal prediction. While parts of the circumglobal pattern are weakly present, none of them produce the response seen over the North Atlantic, even when the effect of sampling on the observed teleconnection is accounted for. We additionally estimate the contribution of the previous (wintertime) phase of ENSO on the following summer. We find a significant delayed response, particularly in heights, to the earlier phase. The combination of the delayed and current responses gives height anomalies that are larger, on average, when ENSO changes phase from winter to summer. Finally, we show that a modest level of regional prediction skill from ENSO does exist. There is a contribution to skill in heights from the previous ENSO phase, but the equivalent contribution to the skill of zonal winds is smaller.
{"title":"Influences on North‐Atlantic summer climate from the El Niño‐Southern Oscillation","authors":"Jeff R. Knight, Adam A. Scaife","doi":"10.1002/qj.4826","DOIUrl":"https://doi.org/10.1002/qj.4826","url":null,"abstract":"Seasonal‐range predictability of summer climate in northwestern Europe is generally considered to be low. This is an increasing issue given the worsening impact of summer heatwaves, droughts and intense convective rainfall in a rapidly changing climate. In wintertime, predictive skill in the region is derived from a variety of sources, not least teleconnections with the El Niño‐Southern Oscillation (ENSO). Summer ENSO teleconnections, however, are often considered to be negligible. In this paper, we revisit the topic of summer teleconnections between ENSO and the North Atlantic‐European region. We build on previous work identifying upper tropospheric responses to tropical forcing, since dynamical teleconnections are most apparent at this level. Our results confirm that significantly increased geopotential heights are found stretching over the North‐Atlantic region and into western Europe when La Niña conditions are prevalent during summer. This pattern is part of the previously identified ‘circumglobal’ pattern of wider northern‐hemisphere height changes. We then look for these responses in a range of climate models used in operational seasonal prediction. While parts of the circumglobal pattern are weakly present, none of them produce the response seen over the North Atlantic, even when the effect of sampling on the observed teleconnection is accounted for. We additionally estimate the contribution of the previous (wintertime) phase of ENSO on the following summer. We find a significant delayed response, particularly in heights, to the earlier phase. The combination of the delayed and current responses gives height anomalies that are larger, on average, when ENSO changes phase from winter to summer. Finally, we show that a modest level of regional prediction skill from ENSO does exist. There is a contribution to skill in heights from the previous ENSO phase, but the equivalent contribution to the skill of zonal winds is smaller.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":"66 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2024-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141948983","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 Northern Annular Mode (NAM) is traditionally defined as the leading empirical orthogonal function (EOF) of mean sea‐level pressure (MSLP) anomalies during winter. Previous studies have shown that the Pacific centre‐of‐action of the NAM is typically more amplified in models than in reanalysis. Here, we analyse the NAM in hindcasts from nine seasonal prediction models over 1993/1994–2016/2017. In all the models, the Pacific centre‐of‐action is much larger than in reanalysis over that period, during which the NAM and the North Atlantic Oscillation (NAO) are almost indistinguishable. As a result, the NAM in the models is correlated with Aleutian Low variability around four times more strongly than in reanalysis. We show that this discrepancy can be explained primarily by the amplitude of Aleutian Low variability, which is on average 17% higher in models than in reanalysis, with a secondary effect from a stronger correlation between the Aleutian Low and NAO. When the NAM is computed using zonally averaged MSLP, the Aleutian Low amplitude does not influence the pattern directly. Instead, the amplitude of the Pacific centre‐of‐action is governed primarily by the correlation between the Aleutian Low and NAO, reducing the apparent Pacific biases in models. While the two methods yield almost identical results in reanalysis, the large Aleutian Low biases result in differences when applied to model data. Modifying the MSLP statistically to alter the Aleutian Low amplitude reveals that the spatial pattern of the traditionally defined NAM is highly sensitive to Aleutian Low variability, even without modifying the correlation between the Aleutian Low and NAO. Hence, the NAM in models may not be as biased as the traditional method would suggest. We therefore conclude that the traditional EOF method is unsuitable for defining the NAM in the presence of highly amplified Aleutian Low variability, and encourage the use of the zonal‐mean method.
北部环流模式（NAM）传统上被定义为冬季平均海平面气压（MSLP）异常的领先经验正交函数（EOF）。以往的研究表明，与再分析相比，模式中的 NAM 太平洋作用中心通常会被放大。在此，我们分析了 1993/1994-2016/2017 年期间九个季节预测模式的后报中的 NAM。在所有模式中，这一时期的太平洋影响中心比再分析中的影响中心要大得多，在这一时期，NAM 和北大西洋涛动（NAO）几乎没有区别。因此，模式中的 NAM 与阿留申低纬度变率的相关性是再分析的四倍。我们的研究表明，造成这种差异的主要原因是阿留申低纬度变率的振幅，它在模式中比在再分析中平均高出 17%，其次是阿留申低纬度与西北气旋之间更强的相关性。当使用分区平均 MSLP 计算 NAM 时，阿留申低纬度振幅不会直接影响模式。相反，太平洋作用中心的振幅主要受阿留申低压和西北大西洋环流之间的相关性影响，从而减少了模式中明显的太平洋偏差。虽然这两种方法在再分析中得出的结果几乎相同，但在应用于模式数据时，阿留申低纬度的巨大偏差导致了差异。从统计角度修改 MSLP 以改变阿留申低纬度振幅，可以发现传统定义的 NAM 空间模式对阿留申低纬度变率非常敏感，即使不修改阿留申低纬度与 NAO 之间的相关性也是如此。因此，模式中的 NAM 可能并不像传统方法认为的那样有偏差。因此，我们得出结论，在阿留申低纬度变率被高度放大的情况下，传统的 EOF 方法不适合定义 NAM，并鼓励使用 zonal-mean 方法。
{"title":"Large model biases in the Pacific centre of the Northern Annular Mode due to exaggerated variability of the Aleutian Low","authors":"Simon H. Lee, Lorenzo M. Polvani","doi":"10.1002/qj.4825","DOIUrl":"https://doi.org/10.1002/qj.4825","url":null,"abstract":"The Northern Annular Mode (NAM) is traditionally defined as the leading empirical orthogonal function (EOF) of mean sea‐level pressure (MSLP) anomalies during winter. Previous studies have shown that the Pacific centre‐of‐action of the NAM is typically more amplified in models than in reanalysis. Here, we analyse the NAM in hindcasts from nine seasonal prediction models over 1993/1994–2016/2017. In all the models, the Pacific centre‐of‐action is much larger than in reanalysis over that period, during which the NAM and the North Atlantic Oscillation (NAO) are almost indistinguishable. As a result, the NAM in the models is correlated with Aleutian Low variability around four times more strongly than in reanalysis. We show that this discrepancy can be explained primarily by the amplitude of Aleutian Low variability, which is on average 17% higher in models than in reanalysis, with a secondary effect from a stronger correlation between the Aleutian Low and NAO. When the NAM is computed using zonally averaged MSLP, the Aleutian Low amplitude does not influence the pattern directly. Instead, the amplitude of the Pacific centre‐of‐action is governed primarily by the correlation between the Aleutian Low and NAO, reducing the apparent Pacific biases in models. While the two methods yield almost identical results in reanalysis, the large Aleutian Low biases result in differences when applied to model data. Modifying the MSLP statistically to alter the Aleutian Low amplitude reveals that the spatial pattern of the traditionally defined NAM is highly sensitive to Aleutian Low variability, even without modifying the correlation between the Aleutian Low and NAO. Hence, the NAM in models may not be as biased as the traditional method would suggest. We therefore conclude that the traditional EOF method is unsuitable for defining the NAM in the presence of highly amplified Aleutian Low variability, and encourage the use of the zonal‐mean method.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":"20 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2024-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141948991","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}
Unstable surface‐layer velocity and temperature spectra, scaled using inertial subrange properties and Monin–Obukhov similarity theory, have been known to show a notable spread in low frequencies. Here, a large ensemble of 14 datasets, over relatively simple (from flat and homogeneous terrain to gentle slopes or valley floor) and very complex mountainous terrain (steep slopes, crater rim, mountain tops), is used to assess the reasons for this low‐frequency behaviour. Turbulence anisotropy is shown to be the primary factor accounting for the spread in the spectral density at the largest scales and the spectral peak position of streamwise and spanwise velocity spectra. On the other hand, the low‐frequency behaviour of surface‐normal spectra is dominated by stability effects, whereas for temperature spectra turbulence anisotropy and stability play a similar role. Using a combination of scaling relations for temperature and velocity variances as well as dissipation of turbulence kinetic energy and half the temperature variance, and of a semi‐empirical model provided in the literature, we are able to describe the behaviour of the velocity and temperature spectra with only turbulence anisotropy and stability as input parameters. These observations are valid over both simple and complex mountainous terrain, although variability of the largest scales of complex‐terrain datasets highlights the effect of processes other than turbulence anisotropy or stability. Finally, we provide some insights into the scalewise nature of anisotropic eddies under different stabilities.
{"title":"Spectral scaling of unstably stratified atmospheric flows: Turbulence anisotropy and the low‐frequency spread","authors":"Claudine Charrondière, Ivana Stiperski","doi":"10.1002/qj.4811","DOIUrl":"https://doi.org/10.1002/qj.4811","url":null,"abstract":"Unstable surface‐layer velocity and temperature spectra, scaled using inertial subrange properties and Monin–Obukhov similarity theory, have been known to show a notable spread in low frequencies. Here, a large ensemble of 14 datasets, over relatively simple (from flat and homogeneous terrain to gentle slopes or valley floor) and very complex mountainous terrain (steep slopes, crater rim, mountain tops), is used to assess the reasons for this low‐frequency behaviour. Turbulence anisotropy is shown to be the primary factor accounting for the spread in the spectral density at the largest scales and the spectral peak position of streamwise and spanwise velocity spectra. On the other hand, the low‐frequency behaviour of surface‐normal spectra is dominated by stability effects, whereas for temperature spectra turbulence anisotropy and stability play a similar role. Using a combination of scaling relations for temperature and velocity variances as well as dissipation of turbulence kinetic energy and half the temperature variance, and of a semi‐empirical model provided in the literature, we are able to describe the behaviour of the velocity and temperature spectra with only turbulence anisotropy and stability as input parameters. These observations are valid over both simple and complex mountainous terrain, although variability of the largest scales of complex‐terrain datasets highlights the effect of processes other than turbulence anisotropy or stability. Finally, we provide some insights into the scalewise nature of anisotropic eddies under different stabilities.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":"1 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2024-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141948984","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}
Amethyst A. Johnson, Juliane Schwendike, Andrew N. Ross, Adrian Lock, John M. Edwards, Jeffrey D. Kepert
The turbulent transport of momentum, heat, and moisture can impact tropical cyclone intensity. However, representing subgrid‐scale turbulence accurately in numerical weather prediction models is challenging due to a lack of observational data. To address this issue, a case study of Hurricane Maria was conducted to analyse the influence of different free tropospheric turbulence parametrisations on sheared tropical cyclones. The study used the current Met Office Unified Model (MetUM) parametrisation, as well as a parametrisation scheme with significantly reduced free tropospheric mixing length. Convection‐permitting ensemble simulations were performed for both mixing schemes at two initialisation times (four 18‐member ensembles in total), revealing an improvement in the intensity forecasts of Hurricane Maria when the mixing length was decreased in the free troposphere. By implementing this change, the less diffuse simulations presented a drier mid‐level. The resolved downward transport of drier air from the mid‐levels into the inflow layer (so‐called “downdraft ventilation”) was thus more effective in reducing the storm's intensity. In contrast to earlier studies, where decreasing the diffusivity in the boundary layer intensified the storm, we show that decreasing the free tropospheric diffusivity can weaken the storm by enhancing shear‐related weakening processes. While this study was performed using the MetUM, the findings highlight the general importance of considering turbulence parametrisation, and show that changes in diffusivity can have different impacts on storm intensity depending on the environment and where the changes are applied.
{"title":"Impacts of free tropospheric turbulence parametrisation on a sheared tropical cyclone","authors":"Amethyst A. Johnson, Juliane Schwendike, Andrew N. Ross, Adrian Lock, John M. Edwards, Jeffrey D. Kepert","doi":"10.1002/qj.4823","DOIUrl":"https://doi.org/10.1002/qj.4823","url":null,"abstract":"The turbulent transport of momentum, heat, and moisture can impact tropical cyclone intensity. However, representing subgrid‐scale turbulence accurately in numerical weather prediction models is challenging due to a lack of observational data. To address this issue, a case study of Hurricane <jats:italic>Maria</jats:italic> was conducted to analyse the influence of different free tropospheric turbulence parametrisations on sheared tropical cyclones. The study used the current Met Office Unified Model (MetUM) parametrisation, as well as a parametrisation scheme with significantly reduced free tropospheric mixing length. Convection‐permitting ensemble simulations were performed for both mixing schemes at two initialisation times (four 18‐member ensembles in total), revealing an improvement in the intensity forecasts of Hurricane <jats:italic>Maria</jats:italic> when the mixing length was decreased in the free troposphere. By implementing this change, the less diffuse simulations presented a drier mid‐level. The resolved downward transport of drier air from the mid‐levels into the inflow layer (so‐called “downdraft ventilation”) was thus more effective in reducing the storm's intensity. In contrast to earlier studies, where decreasing the diffusivity in the boundary layer intensified the storm, we show that decreasing the free tropospheric diffusivity can weaken the storm by enhancing shear‐related weakening processes. While this study was performed using the MetUM, the findings highlight the general importance of considering turbulence parametrisation, and show that changes in diffusivity can have different impacts on storm intensity depending on the environment and where the changes are applied.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":"1 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2024-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141948982","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}
Yimin Ma, Greg L. Roff, Susan J. Rennie, Peter J. Steinle, Hua Ye, Milton J. Woods
The new scheme for deriving the near‐surface wind profiles discussed in Ma (in review) is applied to an Australian Bureau of Meteorology operational convective scale model over various domains. Both the new and conventional schemes' diagnostic 10‐m winds are then verified against Australia‐wide automatic weather station observations. Analyses of bulk statistics reveal that the new scheme's 10‐m wind forecasts have generally better accuracy than the current conventional scheme with a consistent reduction of biases over all domains. A widely recognised diurnal bias pattern of surface wind speed over the land is substantially reduced, and the inclusion of Ekman spiral effect on the 10‐m wind marginally improves statistics of the wind direction during the nighttime. The new scheme introduces no systemic bias, given the histogram of a bulk mean bias is analogiased to a Gaussian distribution, and moves the distribution of diagnostic wind speed closer to that observed.
Ma 所讨论的用于推导近地表风廓线的新方案（综述中）被应用于澳大利亚气象局在不同领域的对流尺度运行模型。然后，根据澳大利亚全境自动气象站的观测结果，对新方案和传统方案的 10 米诊断风进行了验证。对大量统计数据的分析表明，新方案的 10 米风速预报精度普遍高于当前的传统方案，并且在所有域中都持续减少了偏差。人们普遍认为的陆地表面风速昼夜偏差模式已大大减少，而将埃克曼螺旋效应纳入 10 米风速预报可略微改善夜间风向的统计数据。新方案没有引入系统偏差，因为大体平均偏差的直方图类似于高斯分布，并使诊断风速的分布更接近观测到的风速。
{"title":"Near‐surface wind profiles from numerical model predictions. Part II: Verifications against Australia‐wide surface wind observations","authors":"Yimin Ma, Greg L. Roff, Susan J. Rennie, Peter J. Steinle, Hua Ye, Milton J. Woods","doi":"10.1002/qj.4780","DOIUrl":"https://doi.org/10.1002/qj.4780","url":null,"abstract":"The new scheme for deriving the near‐surface wind profiles discussed in Ma (in review) is applied to an Australian Bureau of Meteorology operational convective scale model over various domains. Both the new and conventional schemes' diagnostic 10‐m winds are then verified against Australia‐wide automatic weather station observations. Analyses of bulk statistics reveal that the new scheme's 10‐m wind forecasts have generally better accuracy than the current conventional scheme with a consistent reduction of biases over all domains. A widely recognised diurnal bias pattern of surface wind speed over the land is substantially reduced, and the inclusion of Ekman spiral effect on the 10‐m wind marginally improves statistics of the wind direction during the nighttime. The new scheme introduces no systemic bias, given the histogram of a bulk mean bias is analogiased to a Gaussian distribution, and moves the distribution of diagnostic wind speed closer to that observed.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":"13 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2024-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141948990","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}
A limited‐area model (LAM) is established based on a global model (Global–Regional Integrated Forecast System; GRIST). GRIST–LAM inherits all the technical features of its global counterpart, enabling independent regional weather and climate modeling. The key advancement involves extending the original dynamical core to integrate it under the lateral boundary conditions (LBCs). As an initial development and evaluation study, this paper focuses on the consistency issue between the LAM and the global model. Three perfect‐model tests, using global solutions as LBCs and background truths, were performed to evaluate the LAM behaviors. In the pure dynamical core test, the LBC errors do not compromise the solutions within the interior domain. However, certain configurations can lead to more discontinuous solutions at the domain boundary. The solution error for a specified region decreases as the domain size increases when all other factors are equal. A small error pulse is generated during the initial stage of integration due to the presence of artificial transient waves induced by the LBCs. The model generates fine‐scale details and smaller errors based on coarser‐resolution LBCs. The consistency between LAM and LBC also influences the errors. The climate simulations demonstrate that both hydrostatic and non‐hydrostatic LAMs can reach statistical equilibrium. Regional model climates in the interior domain have higher quality but are sensitive to domain size and LBC configuration. Using a variable LBC coefficient is helpful to alleviate the artificial precipitation at the boundary. In the kilometer‐scale test, the global variable‐resolution model and its LAM counterpart show comparable results. Their performance is competitive with that of a uniform‐resolution global storm‐resolving simulation. Global variable‐resolution and LAM generate higher magnitudes in the tail part of the kinetic energy spectra due to higher local resolution and produce a consistent time evolution of precipitation. The broad implication of this study is also discussed.
{"title":"Establishing a limited‐area model based on a global model: A consistency study","authors":"Yi Zhang, Zhuang Liu, Yiming Wang, Siyuan Chen","doi":"10.1002/qj.4804","DOIUrl":"https://doi.org/10.1002/qj.4804","url":null,"abstract":"A limited‐area model (LAM) is established based on a global model (Global–Regional Integrated Forecast System; GRIST). GRIST–LAM inherits all the technical features of its global counterpart, enabling independent regional weather and climate modeling. The key advancement involves extending the original dynamical core to integrate it under the lateral boundary conditions (LBCs). As an initial development and evaluation study, this paper focuses on the consistency issue between the LAM and the global model. Three perfect‐model tests, using global solutions as LBCs and background truths, were performed to evaluate the LAM behaviors. In the pure dynamical core test, the LBC errors do not compromise the solutions within the interior domain. However, certain configurations can lead to more discontinuous solutions at the domain boundary. The solution error for a specified region decreases as the domain size increases when all other factors are equal. A small error pulse is generated during the initial stage of integration due to the presence of artificial transient waves induced by the LBCs. The model generates fine‐scale details and smaller errors based on coarser‐resolution LBCs. The consistency between LAM and LBC also influences the errors. The climate simulations demonstrate that both hydrostatic and non‐hydrostatic LAMs can reach statistical equilibrium. Regional model climates in the interior domain have higher quality but are sensitive to domain size and LBC configuration. Using a variable LBC coefficient is helpful to alleviate the artificial precipitation at the boundary. In the kilometer‐scale test, the global variable‐resolution model and its LAM counterpart show comparable results. Their performance is competitive with that of a uniform‐resolution global storm‐resolving simulation. Global variable‐resolution and LAM generate higher magnitudes in the tail part of the kinetic energy spectra due to higher local resolution and produce a consistent time evolution of precipitation. The broad implication of this study is also discussed.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":"73 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2024-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141948992","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}
Cornel Soci, Hans Hersbach, Adrian Simmons, Paul Poli, Bill Bell, Paul Berrisford, András Horányi, Joaquín Muñoz‐Sabater, Julien Nicolas, Raluca Radu, Dinand Schepers, Sebastien Villaume, Leopold Haimberger, Jack Woollen, Carlo Buontempo, Jean‐Noël Thépaut
We provide a description and concise evaluation of the European Centre of Medium‐range Weather Forecasts Reanalysis v.5 (ERA5) global reanalysis from an additional extension back to 1940 that was released in March 2023, including its timely updates to the end of 2022. The ERA5 product from 1979 to end 2020 and a preliminary back extension from 1950 to 1978 have already been described elsewhere. The new back extension that spans 1940 to 1978 represents the official release and supersedes the preliminary product. Currently, the ERA5 data record extends over more than 83 years of hourly global three‐dimensional fields for many quantities that describe the global atmosphere, land surface, and ocean waves at a horizontal resolution of about 31 km. ERA5 relies on the ingestion of sub‐daily in‐situ and satellite observations, and the number of these increases from 17,000 per day in 1940 to 25 million per day by 2022. Accordingly, the quality of the reanalysis improves throughout the period. Over the Northern Hemisphere ERA5 generally provides a reliable representation of the synoptic situation from the early 1940s and provides long‐term variability that is in line with other datasets. Over the Southern Hemisphere, however, for the early period the description of ERA5 seems mainly statistical. Furthermore, there is a small deviation in surface temperature compared with reconstructions based on monthly aggregations of observations over land before 1946. For this period, the absence of upper air temperature observations reveals a model cold bias in the lower stratosphere. For the period from 1950 to 1978, the final release described here improves on the suboptimal treatment of International Best Track Archive for Climate Stewardship observations in the preliminary release, with, as a result, a much more homogeneous representation of tropical cyclones over the entire ERA5 record. Longer spin‐up periods also have a beneficial impact on soil moisture.
{"title":"The ERA5 global reanalysis from 1940 to 2022","authors":"Cornel Soci, Hans Hersbach, Adrian Simmons, Paul Poli, Bill Bell, Paul Berrisford, András Horányi, Joaquín Muñoz‐Sabater, Julien Nicolas, Raluca Radu, Dinand Schepers, Sebastien Villaume, Leopold Haimberger, Jack Woollen, Carlo Buontempo, Jean‐Noël Thépaut","doi":"10.1002/qj.4803","DOIUrl":"https://doi.org/10.1002/qj.4803","url":null,"abstract":"We provide a description and concise evaluation of the European Centre of Medium‐range Weather Forecasts Reanalysis v.5 (ERA5) global reanalysis from an additional extension back to 1940 that was released in March 2023, including its timely updates to the end of 2022. The ERA5 product from 1979 to end 2020 and a preliminary back extension from 1950 to 1978 have already been described elsewhere. The new back extension that spans 1940 to 1978 represents the official release and supersedes the preliminary product. Currently, the ERA5 data record extends over more than 83 years of hourly global three‐dimensional fields for many quantities that describe the global atmosphere, land surface, and ocean waves at a horizontal resolution of about 31 km. ERA5 relies on the ingestion of sub‐daily in‐situ and satellite observations, and the number of these increases from 17,000 per day in 1940 to 25 million per day by 2022. Accordingly, the quality of the reanalysis improves throughout the period. Over the Northern Hemisphere ERA5 generally provides a reliable representation of the synoptic situation from the early 1940s and provides long‐term variability that is in line with other datasets. Over the Southern Hemisphere, however, for the early period the description of ERA5 seems mainly statistical. Furthermore, there is a small deviation in surface temperature compared with reconstructions based on monthly aggregations of observations over land before 1946. For this period, the absence of upper air temperature observations reveals a model cold bias in the lower stratosphere. For the period from 1950 to 1978, the final release described here improves on the suboptimal treatment of International Best Track Archive for Climate Stewardship observations in the preliminary release, with, as a result, a much more homogeneous representation of tropical cyclones over the entire ERA5 record. Longer spin‐up periods also have a beneficial impact on soil moisture.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":"21 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141886038","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}
Microwave temperature sounders onboard polar‐orbiting satellites can provide global observation data twice a day, supplying a large amount of temperature information for global data assimilation and serving as a crucial instrument to improve operational numerical forecasts. However, regional numerical forecasts are still subject to a lack of polar‐orbiting satellite data within regional model domains, and even multiple polar‐orbiting satellites may simultaneously miss measurements. Establishing a three‐orbit observation system of polar‐orbiting satellites is crucial to improve the spatiotemporal coverage of polar‐orbiting satellite data. In this study, we investigate the impact of assimilating microwave temperature sounding data from a three‐orbit constellation on precipitation forecasts in inland China based on the data from the US afternoon‐orbit satellite NOAA‐19, the European morning‐orbit satellite Meteorological Operational satellite‐A and the Chinese early‐morning‐orbit satellite Fengyun‐3E (FY‐3E) launched recently. The research results indicate that there are data gaps at 0600 and 1800 UTC in the East Asian region only for the morning‐orbit and afternoon‐orbit satellite observations. The FY‐3E satellite can provide additional microwave temperature sounding observations over the eastern region of China, thus partially compensating for the gap in polar‐orbiting satellite data in China. Moreover, the additional assimilation of the FY‐3E data can further improve numerical forecasts, effectively adjusting the spatial structure and eastward movement of the weather system, thereby considerably increasing the prediction accuracy of rainfall location and intensity. Rolling‐prediction results show that the data from the three‐orbit constellation provide a stable and notable improvement in precipitation forecasts in inland China, especially for forecasts longer than nine hours and amounts of rainfall below 10 mm. These research findings provide valuable insights for optimizing the assimilation application of polar‐orbiting satellite data in regional numerical forecasts.
{"title":"Improving inland precipitation forecast in China through data assimilation of microwave temperature sounding data from a three‐orbit constellation","authors":"Yu Huang, Zhengkun Qin, Juan Li, Jiali Mao","doi":"10.1002/qj.4802","DOIUrl":"https://doi.org/10.1002/qj.4802","url":null,"abstract":"Microwave temperature sounders onboard polar‐orbiting satellites can provide global observation data twice a day, supplying a large amount of temperature information for global data assimilation and serving as a crucial instrument to improve operational numerical forecasts. However, regional numerical forecasts are still subject to a lack of polar‐orbiting satellite data within regional model domains, and even multiple polar‐orbiting satellites may simultaneously miss measurements. Establishing a three‐orbit observation system of polar‐orbiting satellites is crucial to improve the spatiotemporal coverage of polar‐orbiting satellite data. In this study, we investigate the impact of assimilating microwave temperature sounding data from a three‐orbit constellation on precipitation forecasts in inland China based on the data from the US afternoon‐orbit satellite NOAA‐19, the European morning‐orbit satellite Meteorological Operational satellite‐A and the Chinese early‐morning‐orbit satellite Fengyun‐3E (FY‐3E) launched recently. The research results indicate that there are data gaps at 0600 and 1800 UTC in the East Asian region only for the morning‐orbit and afternoon‐orbit satellite observations. The FY‐3E satellite can provide additional microwave temperature sounding observations over the eastern region of China, thus partially compensating for the gap in polar‐orbiting satellite data in China. Moreover, the additional assimilation of the FY‐3E data can further improve numerical forecasts, effectively adjusting the spatial structure and eastward movement of the weather system, thereby considerably increasing the prediction accuracy of rainfall location and intensity. Rolling‐prediction results show that the data from the three‐orbit constellation provide a stable and notable improvement in precipitation forecasts in inland China, especially for forecasts longer than nine hours and amounts of rainfall below 10 mm. These research findings provide valuable insights for optimizing the assimilation application of polar‐orbiting satellite data in regional numerical forecasts.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":"81 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141886040","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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