Quarterly Journal of the Royal Meteorological Society最新文献_第9页

Improvements in the spread–skill relationship of precipitation in a convective‐scale ensemble through blending 通过混合改善对流尺度集合中降水的传播-技能关系

IF 8.9 3区地球科学

Quarterly Journal of the Royal Meteorological Society Pub Date : 2024-05-24 DOI: 10.1002/qj.4754

Adam Gainford, Suzanne L. Gray, T.H.A. Frame, A. Porson, Marco Milan

{"title":"Improvements in the spread–skill relationship of precipitation in a convective‐scale ensemble through blending","authors":"Adam Gainford, Suzanne L. Gray, T.H.A. Frame, A. Porson, Marco Milan","doi":"10.1002/qj.4754","DOIUrl":"https://doi.org/10.1002/qj.4754","url":null,"abstract":"Convective‐scale ensembles are used routinely in operational centres around the world to produce probabilistic precipitation forecasts, but a lack of spread between members is providing forecasts that are frequently overconfident. This deficiency can be corrected by increasing spread, increasing forecast accuracy, or both. A recent development in the Met Office forecasting system is the inclusion of large‐scale blending (LSB) in the convective‐scale data assimilation scheme. This method aims to reduce the synoptic‐scale forecast error in the analysis by reducing the influence of the convective‐scale data assimilation at scales that are too large to be constrained by the limited domain. These scales are instead initialised using output from the global data assimilation scheme, which we expect to reduce the forecast error and thus improve the spread–skill relationship. In this study, we quantify the impact of LSB on the spread–skill relationship of hourly precipitation accumulations by comparing forecast ensembles with and without LSB over a 17‐day summer trial period. This trial found modest but significant improvements to the spread–skill relationship as calculated using metrics based on the Fractions Skill Score. Skill is improved for a lower precipitation centile by an average of 0.56% at the largest scales, but a corresponding degradation of spread limits the overall correction. The spread–skill disparity is reduced the most in the higher centiles due to a more muted spread response, with significant reductions of up to 0.40% obtained at larger scales. Case‐study analysis using a novel extension of the Localised Fractions Skill Score demonstrates how spread–skill improvements transfer to smaller‐scale features, not just the scales that have been blended. There are promising signs that further spread–skill improvements can be made by implementing LSB more fully within the ensemble, and we encourage the Met Office to continue developing this technique.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":null,"pages":null},"PeriodicalIF":8.9,"publicationDate":"2024-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141100978","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}

引用次数: 0

Convergence of ensemble forecast distributions in weak and strong forcing convective weather regimes 弱和强强迫对流天气系统中集合预报分布的收敛性

IF 8.9 3区地球科学

Quarterly Journal of the Royal Meteorological Society Pub Date : 2024-05-23 DOI: 10.1002/qj.4684

Kirsten I. Tempest, G. C. Craig, Matjaž Puh, Christian Keil

{"title":"Convergence of ensemble forecast distributions in weak and strong forcing convective weather regimes","authors":"Kirsten I. Tempest, G. C. Craig, Matjaž Puh, Christian Keil","doi":"10.1002/qj.4684","DOIUrl":"https://doi.org/10.1002/qj.4684","url":null,"abstract":"The constraint of computational power and the huge number of degrees of freedom of the atmosphere means a sampling uncertainty exists in probabilistic ensemble forecasts. In our previous study, the uncertainty could be quantified, creating a convergence measure which converges proportional to in the limit of large ensemble size . This power law can then be extrapolated to determine how sampling uncertainty would decrease with larger ensemble sizes and hence find the necessary ensemble size. It is unknown, however, how the sampling uncertainty depends on different weather regimes. This study extends the previous idealised ensemble developed, by including weak and strong forcing convective weather regimes, to look at how sampling uncertainty convergence differs in each. Two ‐member ensembles were run, with weak and strong forcing respectively. Comparisons with a kilometre‐scale weather prediction model ensured realistic weak and strong forcing regimes by comparing the rain, convective available potential energy (CAPE), convective adjustment timescale, and distribution shapes throughout the diurnal cycle. Differences in distribution shape between the regimes led to differences in the convergence measure. Large differences in spread between weak and strong forcing runs throughout the hr period led to large differences in sampling uncertainty of the mean and standard deviation, which could be quantified according to well‐known equations. The timing of these differences was case‐dependent. For extreme statistics such as the quantile and for cases where there was precipitation, the moisture variables for the weak forcing case had the largest sampling uncertainty and required the most members for convergence proportional to . This was due to the tails of the weak forcing moisture variables containing the least amount of density. Different ensemble sizes will hence be required depending on whether one is in the weak or strong forcing convective weather regime.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":null,"pages":null},"PeriodicalIF":8.9,"publicationDate":"2024-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141103108","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}

引用次数: 0

Generating synthetic rainfall fields by R‐vine copulas applied to seamless probabilistic predictions 通过应用于无缝概率预测的 R-vine copulas 生成合成降雨场

IF 8.9 3区地球科学

Quarterly Journal of the Royal Meteorological Society Pub Date : 2024-05-21 DOI: 10.1002/qj.4751

Peter Schaumann, Martin Rempel, Ulrich Blahak, Volker Schmidt

{"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":null,"pages":null},"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}

引用次数: 0

Extending a dry‐environment convection parameterization to couple with moist turbulence and a baseline evaluation in the GRIST model 将干燥环境对流参数化扩展到与潮湿湍流耦合以及 GRIST 模型中的基线评估

IF 8.9 3区地球科学

Quarterly Journal of the Royal Meteorological Society Pub Date : 2024-05-20 DOI: 10.1002/qj.4763

Xiaohan Li, Wenchao Chu, Yi Zhang, Yiming Wang

{"title":"Extending a dry‐environment convection parameterization to couple with moist turbulence and a baseline evaluation in the GRIST model","authors":"Xiaohan Li, Wenchao Chu, Yi Zhang, Yiming Wang","doi":"10.1002/qj.4763","DOIUrl":"https://doi.org/10.1002/qj.4763","url":null,"abstract":"This study presents an extension of a dry‐environment convection scheme (Tiedtke–Bechtold) to couple with a boundary‐layer moist turbulence scheme. The deep and shallow convective updraught is modified to develop in a moist environment and the large‐scale budget of cloud condensate takes account of the influence of compensation subsidence. An ambiguous layer is introduced in the sub‐cloud layer transport of shallow convection to mimic the non‐local transport that is ignored in the moist local turbulence scheme. Long‐term global simulation suggests that the modified convection and moist turbulence improve low cloud and short‐wave cloud radiative forcing. This includes a more realistic climatological structure of stratocumulus‐to‐cumulus transition and ameliorated biases in liquid water path. For short to mid‐term hindcasts in June 2021, the modified convection coupled with moist turbulence mitigates some regional over‐forecasts of precipitation. They improve the forecast ability for light and moderate precipitation. The modified model still retains the capability to capture the diurnal features of continental rainfall.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":null,"pages":null},"PeriodicalIF":8.9,"publicationDate":"2024-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141123509","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}

引用次数: 0

Post‐processing output from ensembles with and without parametrised convection, to create accurate, blended, high‐fidelity rainfall forecasts 对有参数化对流和无参数化对流的集合输出进行后处理，以创建准确、混合、高保真的降雨预报

IF 8.9 3区地球科学

Quarterly Journal of the Royal Meteorological Society Pub Date : 2024-05-18 DOI: 10.1002/qj.4753

Estíbaliz Gascón, Andrea Montani, Tim D. Hewson

{"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":null,"pages":null},"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}

引用次数: 0

Sampling and misspecification errors in the estimation of observation‐error covariance matrices using observation‐minus‐background and observation‐minus‐analysis statistics 使用观测减背景和观测减分析统计估计观测误差协方差矩阵时的抽样误差和误判误差

IF 8.9 3区地球科学

Quarterly Journal of the Royal Meteorological Society Pub Date : 2024-05-18 DOI: 10.1002/qj.4750

Guannan Hu, Sarah L. Dance

{"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":null,"pages":null},"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}

引用次数: 0

Optimization of CMIP6 models for simulation of summer monsoon rainfall over India by analysis of variance 通过方差分析优化模拟印度夏季季风降雨的 CMIP6 模型

IF 8.9 3区地球科学

Quarterly Journal of the Royal Meteorological Society Pub Date : 2024-05-18 DOI: 10.1002/qj.4757

Akshay Kulkarni, P. V. S. Raju, Raghavendra Ashrit, Archana Sagalgile, Bhupendra Bahadur Singh, Jagdish Prasad

{"title":"Optimization of CMIP6 models for simulation of summer monsoon rainfall over India by analysis of variance","authors":"Akshay Kulkarni, P. V. S. Raju, Raghavendra Ashrit, Archana Sagalgile, Bhupendra Bahadur Singh, Jagdish Prasad","doi":"10.1002/qj.4757","DOIUrl":"https://doi.org/10.1002/qj.4757","url":null,"abstract":"The advent of weather and climate models has equipped us to forecast or project monsoon rainfall patterns over various spatiotemporal scales; however, utilizing a single model is not usually sufficient to yield accurate projection due to the inherent uncertainties associated with the individual models. An ensemble of models or model runs is often used for better projections as a multimodel ensemble (MME). This study analyzes the accuracy of MME in simulating the Indian summer monsoon rainfall (ISMR) variability using Coupled Model Intercomparison Project Phase 6 (CMIP6) simulations. The results highlighted that although the MME primarily reproduces the observed pattern and annual cycle of rainfall, significant biases are noted over homogeneous meteorological regions of India, except northeast India. To overcome this issue, an analysis of variance (ANOVA) and post hoc statistical tests are employed to identify a group of models for which the modified MME gives a better estimate of rainfall and reduces the bias significantly. Our findings underscore the potential of ANOVA and post hoc tests as a practical approach to enhancing the accuracy of multimodel ensemble rainfall for the assessment of model projections.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":null,"pages":null},"PeriodicalIF":8.9,"publicationDate":"2024-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141059629","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}

引用次数: 0

Urban boundary‐layer flows in complex terrain: Dynamic interactions during a hot and dry summer season in Phoenix, Arizona 复杂地形中的城市边界层流动：亚利桑那州凤凰城夏季炎热干燥季节的动态相互作用

IF 8.9 3区地球科学

Quarterly Journal of the Royal Meteorological Society Pub Date : 2024-05-17 DOI: 10.1002/qj.4752

A. Brandi, A. Martilli, F. Salamanca, M. Georgescu

{"title":"Urban boundary‐layer flows in complex terrain: Dynamic interactions during a hot and dry summer season in Phoenix, Arizona","authors":"A. Brandi, A. Martilli, F. Salamanca, M. Georgescu","doi":"10.1002/qj.4752","DOIUrl":"https://doi.org/10.1002/qj.4752","url":null,"abstract":"Anthropogenic modification of natural landscapes to urban environments impacts land–atmosphere interactions in the boundary layer. Ample research has demonstrated the effect of such landscape transitions on development of the urban heat island (UHI), but considerably less attention has been given to impacts on regional wind flow. Here, we use a set of high‐resolution (1 km grid spacing) regional climate modeling simulations with the Weather Research and Forecasting model coupled to a multilayer urban canopy scheme to investigate the dynamical interaction between the urban boundary layer of the Phoenix metro (United States) area and the thermal circulation of the complex terrain it resides within. We conduct paired simulations for the extremely hot and dry summer of 2020, using a contemporary urban representation and a pre‐settlement landscape representation to examine the effect of the built environment on local to regional‐scale wind flow. Analysis of our simulation results shows that, during the summer of 2020, (a) the thermo‐topographical circulation dominates over both urban and rural areas for a majority of the diurnal cycle; (b) the built environment obstructs wind flow in the inertial sublayer during the late afternoon and the nighttime, whereas more intense daytime urban sensible heat flux dampens the urban‐roughness‐induced drag effect through a deeper urban boundary layer and vigorous mixing; (c) the Phoenix metro UHI does not result in a well‐developed and clearly discernible induced circulation as observed in other urban areas and described in the scientific literature; (d) shortly before dawn, the local UHI is able to affect the local thermo‐topographical circulation through flow intensity modulation that results in an ~10 km eastward shift of the center of mass convergence. Our results highlight the need for future research—both observational and simulation based—into urbanizing regions where multiscale flows are dominant.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":null,"pages":null},"PeriodicalIF":8.9,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140963414","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}

引用次数: 0

Tailoring data assimilation to discontinuous Galerkin models 为非连续伽勒金模型量身定制数据同化方法

IF 8.9 3区地球科学

Quarterly Journal of the Royal Meteorological Society Pub Date : 2024-05-17 DOI: 10.1002/qj.4737

Ivo Pasmans, Yumeng Chen, A. Carrassi, Chris K. R. T. Jones

{"title":"Tailoring data assimilation to discontinuous Galerkin models","authors":"Ivo Pasmans, Yumeng Chen, A. Carrassi, Chris K. R. T. Jones","doi":"10.1002/qj.4737","DOIUrl":"https://doi.org/10.1002/qj.4737","url":null,"abstract":"In recent years discontinuous Galerkin (DG) methods have received increased interest from the geophysical community. In these methods the solution in each grid cell is approximated as a linear combination of basis functions. Ensemble data assimilation (DA) aims to approximate the true state by combining model outputs with observations using error statistics estimated from an ensemble of model runs. Ensemble data assimilation in geophysical models faces several well‐documented issues. In this work we exploit the expansion of the solution in DG basis functions to address some of these issues. Specifically, it is investigated whether a DA–DG combination (a) mitigates the need for observation thinning, (b) reduces errors in the field's gradients, and (c) can be used to set up scale‐dependent localisation. Numerical experiments are carried out using stochastically generated ensembles of model states, with different noise properties, and with Legendre polynomials as basis functions. It is found that strong reduction in the analysis error is achieved by using DA–DG and that the benefit increases with increasing DG order. This is especially the case when small scales dominate the background error. The DA improvement in the first derivative is, on the other hand, marginal. We think this to be a counter‐effect of the power of DG to fit the observations closely, which can deteriorate the estimates of the derivatives. Applying optimal localisation to the different polynomial orders, thus exploiting their different spatial length, is beneficial: it results in a covariance matrix closer to the true covariance than the matrix obtained using traditional optimal localisation in state space.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":null,"pages":null},"PeriodicalIF":8.9,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140962332","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}

引用次数: 0

Assessment of short‐range forecast error atmosphere–ocean cross‐correlations from the Met Office coupled numerical weather prediction system 气象局耦合数值天气预报系统对大气-海洋交叉相关性短程预报误差的评估

IF 8.9 3区地球科学

Quarterly Journal of the Royal Meteorological Society Pub Date : 2024-05-17 DOI: 10.1002/qj.4735

Azin Wright, Amos S. Lawless, Nancy K. Nichols, Daniel J. Lea, Matthew J. Martin

{"title":"Assessment of short‐range forecast error atmosphere–ocean cross‐correlations from the Met Office coupled numerical weather prediction system","authors":"Azin Wright, Amos S. Lawless, Nancy K. Nichols, Daniel J. Lea, Matthew J. Martin","doi":"10.1002/qj.4735","DOIUrl":"https://doi.org/10.1002/qj.4735","url":null,"abstract":"Operational data assimilation systems for coupled atmosphere–ocean prediction are usually “weakly coupled”, in which there is no explicit interaction between the atmosphere and ocean within the data assimilation step. Explicitly allowing for cross‐correlations between the ocean and the atmosphere may have potential benefits in improving the consistency of atmosphere and ocean analyses, as well as allowing a better use of observations at the interface. To understand whether such correlations are significant on the time‐scales of numerical weather prediction, we investigate the atmosphere–ocean cross‐correlations of short‐term forecast errors from the Met Office coupled prediction system, considering their temporal and spatial variability. We find that significant correlations exist between atmosphere and ocean forecast errors on these time‐scales, and that these vary diurnally, from day to day, spatially and synoptically. For correlations between errors in the atmospheric wind and ocean temperature, positive correlations in the North Atlantic region are found to be synoptically dependent, with correlation structures extending into the ocean throughout the deep mixed layer, beyond a depth of 100 m. In contrast, negative correlations over the Indian Ocean are very shallow and are associated with the diurnal cycle of solar radiation. The significance and variability of cross‐correlations indicates that there should be a benefit from including them in data assimilation systems, but it will be important to allow for some flow‐dependence in the correlations. Furthermore, the differing vertical extents of the cross‐correlations in different regions implies the need for situation‐dependent localisation of ensemble correlations when including them in coupled data assimilation systems.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":null,"pages":null},"PeriodicalIF":8.9,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140964427","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}

引用次数: 0