Quarterly Journal of the Royal Meteorological Society最新文献

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

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

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

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

{"title":"Causal dependencies and Shannon entropy budget: Analysis of a reduced‐order atmospheric model","authors":"Stéphane Vannitsem, Carlos A. Pires, David Docquier","doi":"10.1002/qj.4805","DOIUrl":"https://doi.org/10.1002/qj.4805","url":null,"abstract":"The information entropy budget and the rate of information transfer between variables is studied in the context of a nonlinear reduced‐order atmospheric model. The key ingredients of the dynamics are present in this model; namely, the baroclinic instability, the instability related to the presence of an orography, the dissipation related to the surface friction, and the large‐scale meridional imbalance of energy. For the parameters chosen, the solutions of this system display a chaotic dynamics reminiscent of the large‐scale atmospheric dynamics in the extratropics. The detailed information entropy budget analysis of this system reveals that the linear rotation terms play a minor role in the generation of uncertainties compared with the orography and the surface friction. Additionally, the dominant contribution comes from the nonlinear advection terms, and their decomposition in synergetic (covariability) and single (impact of each single variable on the target one) components reveals that for some variables the covariability dominates the information transfer. The estimation of the rate of information transfer based on time series is also discussed, and an extension of the Liang's approach to nonlinear observables is proposed.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":null,"pages":null},"PeriodicalIF":8.9,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141781355","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}

{"title":"Insights from very‐large‐ensemble data assimilation experiments with a high‐resolution general circulation model of the Red Sea","authors":"Sivareddy Sanikommu, Naila Raboudi, Mohamad El Gharamti, Peng Zhan, Bilel Hadri, Ibrahim Hoteit","doi":"10.1002/qj.4813","DOIUrl":"https://doi.org/10.1002/qj.4813","url":null,"abstract":"Ensemble Kalman Filters (EnKFs), which assimilate observations based on statistics derived from an ensemble of samples of ocean states, have become the norm for ocean data assimilation (DA) and forecasting. These schemes are commonly implemented with inflation and localization techniques to increase their ensemble spread and to filter out spurious long‐range correlations resulting from the limited‐size ensembles imposed by computational burden constraints. Such ad‐hoc methods were found to be not necessary in ensemble DA experiments with simplified ocean/atmospheric models and large ensembles. Here, we conduct a series of one‐year‐long ensemble experiments with a fully realistic EnKF‐DA system in the Red Sea using tens ‐to thousands of ensemble members. The system assimilates satellite and in‐situ observations and accounts for model uncertainties by integrating a 4‐km‐resolution ocean model with European Center for Medium Range Weather Forecast (ECMWF) atmospheric ensemble fields, perturbed internal physics and initial conditions for forecasting. OceanOur results indicate that accounting for model uncertainties is more beneficial than simply increasing the ensemble size, with the improvements due to large ensembles leveling off at about 250 members. Besides, and in contrast to what is commonly observed with simplified models, the investigated ensemble DA system still required localization even when implemented with thousands of members. These findings are explained by: (i) amplified spurious long‐range correlations produced by the low‐rank nature of the ECMWF atmospheric forcing ensemble; and (ii) non‐Gaussianity generated by the perturbed internal physical parameterization schemes. Large‐ensemble forcing fields and non‐Gaussian DA methods might be needed to get full benefits from large ensembles in ocean DA.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":null,"pages":null},"PeriodicalIF":8.9,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141781356","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}

{"title":"Estimating the gain of increasing the ensemble size from analytical considerations","authors":"Bo Christiansen","doi":"10.1002/qj.4815","DOIUrl":"https://doi.org/10.1002/qj.4815","url":null,"abstract":"Model ensembles may provide estimates of uncertainties arising from unknown initial conditions and model deficiencies. Often, the ensemble mean is taken as the best estimate, and quantities such as the mean‐squared error between model mean and observations decrease with the number of ensemble members. But the ensemble size is often limited by available resources, and so some idea of how many ensemble members that are needed before the error has saturated would be advantageous. The behaviour with ensemble size is often estimated by producing subsamples from a large ensemble. But this strategy requires that this large ensemble is already available. Fortunately, in many situations, the dependence on ensemble size follows simple analytical relations when the quantity under interest (such as the mean‐squared error between ensemble mean and observations) is calculated over many grid points or time points. This holds both for ensemble means and the related sampling variance. Here, we present such relations and demonstrate how they can be used to estimate the gain of increasing the ensemble. Whereas previous work has mainly focused on the size of the model ensemble, we recognize that uncertainties in observations play a role. We therefore also study the effect of using the mean of an ensemble of reanalyses. We show how the analytical relations can be used to estimate the point where the gain of increasing the size of the model ensemble is dwarfed by the gain of increasing the number of reanalyses. We demonstrate these points using two climate model ensembles: a large multimodel ensemble and a large single‐model initial‐condition ensemble.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":null,"pages":null},"PeriodicalIF":8.9,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141781357","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}

{"title":"Ensemble weather forecast post‐processing with a flexible probabilistic neural network approach","authors":"Peter Mlakar, Janko Merše, Jana Faganeli Pucer","doi":"10.1002/qj.4809","DOIUrl":"https://doi.org/10.1002/qj.4809","url":null,"abstract":"Ensemble forecast post‐processing is a necessary step in producing accurate probabilistic forecasts. Many post‐processing methods operate by estimating the parameters of a predetermined probability distribution; others operate on a per‐lead‐time or per‐station basis. All of the aforementioned factors either limit the expressive power of the methods in question or require additional models, one for each lead time and station. We propose a novel, neural network‐based method that produces forecasts for all lead times jointly and requires a single model for all stations. We incorporate normalizing spline flows as flexible parametric distribution estimators, which enables us to model complex forecast distributions. Furthermore, we demonstrate the effectiveness of our method in the context of the EUPPBench benchmark, where we conduct 2‐m temperature forecast post‐processing for stations in a subregion of Europe. We show that our novel method exhibits state‐of‐the‐art performance on the benchmark, improving upon other well‐performing entries. Additionally, by providing a detailed comparison of three variants of our novel post‐processing method, we elucidate the reasons why our method outperforms per‐lead‐time‐based approaches and approaches with distributional assumptions.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":null,"pages":null},"PeriodicalIF":8.9,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141785774","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}

{"title":"A momentum budget study of the semi‐annual oscillation in the Whole Atmosphere Community Climate Model","authors":"Aleena M. Jaison, Lesley J. Gray, Scott Osprey, Anne K. Smith, Rolando R. Garcia","doi":"10.1002/qj.4782","DOIUrl":"https://doi.org/10.1002/qj.4782","url":null,"abstract":"The representation of the semi‐annual oscillation (SAO) in climate models shows a common easterly bias of several tens of metres per second compared to observations. These biases could be due to deficiencies in eastward tropical wave forcing, the position or strength of the climatological summertime jet or the strength/timing of the Brewer–Dobson circulation. This motivates further analysis of the momentum budget of the upper stratosphere within models and a more detailed comparison with reanalyses to determine the origin of the bias. In this study, the transformed Eulerian mean momentum equation is used to evaluate the different forcing terms that contribute to the SAO in the MERRA2 reanalysis dataset. This is then compared with the equivalent analysis using data from a climate simulation of the Whole Atmosphere Community Climate Model (WACCM). The comparison shows that WACCM underestimates eastward forcing by both resolved and parameterised waves at equatorial latitudes when compared with MERRA2 and also has a weaker tropical upwelling above 1 hPa.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":null,"pages":null},"PeriodicalIF":8.9,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141781359","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}

{"title":"Grey‐zone simulations of shallow‐to‐deep convection transition using dynamic subgrid‐scale turbulence models","authors":"Georgios A. Efstathiou, Robert S. Plant, Fotini Katopodes Chow","doi":"10.1002/qj.4817","DOIUrl":"https://doi.org/10.1002/qj.4817","url":null,"abstract":"We examine the ability of two dynamic turbulence closure models to simulate the diurnal development of convection and the transition from dry to shallow cumuli and then to deep convection. The dynamic models are compared with the conventional Smagorinsky scheme at a range of cloud‐resolving and grey‐zone resolutions. The dynamic schemes include the Lagrangian‐averaged, scale‐dependent dynamic Smagorinsky model and a Lagrangian‐averaged, dynamic mixed model. The conventional Smagorinsky model fails to reproduce the shallow convection stage beyond the large‐eddy simulation regime, continuously building up the convective available potential energy that eventually leads to an unrealistic deep convection phase. The dynamic Smagorinsky model significantly improves the representation of shallow and deep convection; however, it exhibits issues similar to the conventional scheme at coarser resolutions. In contrast, the dynamic mixed model closely follows the large‐eddy simulation results across the range of sub‐kilometre simulations. This is achieved by the combined effect of an adaptive length scale and the inclusion of the Leonard terms, which can produce counter‐gradient fluxes through the backscatter of energy from the subgrid to the resolved scales and enable appropriate non‐local contributions. A further sensitivity test on the inclusion of the Leonard terms on all hydrometeor fluxes reveals the strong interaction between turbulent transport and microphysics and the possible need for further optimisation of the dynamic mixed model coefficients together with the microphysical representation.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":null,"pages":null},"PeriodicalIF":8.9,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141781358","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}