Meteorology and Atmospheric Physics最新文献

{"title":"A forecasting method for corrected numerical weather prediction precipitation based on modal decomposition and coupling of multiple intelligent algorithms","authors":"Changqing Meng, Zhihan Hu, Yuankun Wang, Yanke Zhang, Zijiao Dong","doi":"10.1007/s00703-024-01030-2","DOIUrl":"https://doi.org/10.1007/s00703-024-01030-2","url":null,"abstract":"<p>Numerical weather models often face significant challenges in achieving high prediction accuracy. To enhance the predictive performance of these models, a solution involving the integration of deep learning algorithms has been proposed. This paper introduces a machine learning approach for correcting the numerical weather forecast results from the Weather Research and Forecasting (WRF) model. Initially, the WRF model is used to simulate summer precipitation in the Jinsha River Basin. Subsequently, the adaptive noise-robust empirical mode decomposition (CEEMDAN) method is employed to decompose WRF simulation errors. These decomposed subsequences are then input into four machine learning algorithms and two metaheuristic optimization algorithms to predict the error sequences. Finally, the predicted error subsequences are merged and superimposed on the WRF simulation values to obtain the corrected precipitation. Research findings demonstrate that the integration of machine learning algorithms with WRF significantly improves prediction accuracy. The correlation coefficient of the optimal model increases by 158%, and Nash-Sutcliffe Efficiency (NSE) increases by 149% compared to before correction. This indicates that correcting the WRF model through deep learning methods effectively enhances precipitation forecasting accuracy.</p>","PeriodicalId":51132,"journal":{"name":"Meteorology and Atmospheric Physics","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2024-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142226187","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of climate change on the behaviour of solar radiation using AFR-CORDEX model over West Africa","authors":"O. S. Ojo, I. Emmanuel, K. D. Adedayo, E. O. Ogolo, B. Adeyemi","doi":"10.1007/s00703-024-01033-z","DOIUrl":"https://doi.org/10.1007/s00703-024-01033-z","url":null,"abstract":"<p>The study evaluated the impact of climate change on incoming solar radiation (RSDS) in West Africa by comparing observed data from the CMSAF solar products (SARAH and CLARA-A1) for the period 1983–2019 with simulated data from the AFR-CORDEX models (RegCM-4.7 and CCCma-canRCM4) for the historical period (1983–2004) and various RCP emission scenarios (2.6, 4.5, 8.5) for 2005–2099. The values of the RCP in parentheses signify the level of increasing radiative forcings due to varying emission controls. Assessment metrics like correlation coefficient (R), Taylor Skill Score (TSS), and root mean square errors (RMSE) were employed for comparative analysis on annual and seasonal timescales. The analyses revealed annual mean RSDS intensities of 256.22 for SARAH, 238.53 for CLARA-A1, 270.81 for Historical, 270.26 for RCP 2.6, 255.90 for RCP 4.5, and 271.93 for the RCP 8.5 scenarios in watts per square metres. The TSS analyses showed average agreement values between observed CMSAF and simulated AFR-CORDEX solar radiation with values of 0.8450 and 0.8575 with historical, 0.8750 and 0.8600 with RCP 2.6, 0.9025 and 0.8550 with RCP 4.5, and 0.8675 and 0.8525 with RCP 8.5 scenarios for SARAH and CLARA-A1 respectively. All the metrics showed better agreement with SARAH than CLARA-A1, likely due to the associated cloud influence on CLARA-A1. Notably, the CORDEX-CCCma-canRCM4 model under RCP 4.5 demonstrated the highest accuracy, with an average correlation of 0.82 and a mean TSS of 0.90 against the SARAH reference dataset. The results suggest the AFR-CORDEX model, particularly the CCCma-canRCM4 for RCP 4.5 scenario, could reliably predict solar radiation and inform climate change impacts on solar energy potential in West Africa under moderate emission conditions.</p>","PeriodicalId":51132,"journal":{"name":"Meteorology and Atmospheric Physics","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2024-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142205159","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Urban heat island characteristics of Yangtze river delta in a heatwave month of 2017","authors":"Ying Gao, Ning Zhang, Yan Chen, Ling Luo, Xiangyu Ao, Wenjuan Li","doi":"10.1007/s00703-024-01027-x","DOIUrl":"https://doi.org/10.1007/s00703-024-01027-x","url":null,"abstract":"<p>The analysis of urban thermal environment based on Local Climate Zone (LCZ) is helpful to understand the fine structure of urban heat island (UHI), so as to provide a scientific basis for urban ecological environment management. This research focused on the three biggest cities, Shanghai, Nanjing and Hangzhou, in Yangtze River Delta (YRD) and the UHI characteristics in a heatwave month (July 2017) were investigated. Based on the observations of automatic weather stations, the spatiotemporal characteristics of air temperature and canopy urban heat island intensity (UHII) of each LCZ in three cities under different weather conditions were compared and analyzed by using the LCZ clustering method, and the effects of water bodies, urban greening and sea breeze on urban heat island were discussed. Results show that the air temperature and urban heat island intensity of different LCZs would vary due to the differences in urban geometry, building materials, the proportion of impervious surface and anthropogenic heat. The LCZ based UHII in the three YRD typical cities showed similar characteristics: compact high-rise (LCZ 1), compact mid-rise (LCZ 2) and open mid-rise (LCZ 5) had higher UHII while sparsely built (LCZ 9) had lower UHII. The diurnal variation of UHII in the three cities are different: the UHII diurnal curves of Nanjing and Hangzhou were “U” type, while that of Shanghai was shallow “W” type, which was because Shanghai was vulnerable to sea breeze during the summer day. In addition to land and sea location, large water bodies and urban greening would also impact the spatiotemporal patterns of urban thermal environment.</p>","PeriodicalId":51132,"journal":{"name":"Meteorology and Atmospheric Physics","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2024-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141940449","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Variations in air-sea heat fluxes during lifetime of intense tropical cyclones over the Bay of Bengal","authors":"Pravat Rabi Naskar, Mrutyunjay Mohapatra, Gyan Prakash Singh","doi":"10.1007/s00703-024-01026-y","DOIUrl":"https://doi.org/10.1007/s00703-024-01026-y","url":null,"abstract":"<p>In this study, we have tried to find out the influence of air-sea heat fluxes (particularly the Surface Latent Heat Flux (SLHF) and the Surface Sensible Heat Flux (SSHF)) on the intensity of Intense Tropical Cyclones’ (ITCs’). We have analysed 32 ITCs which originated in the Bay of Bengal (BoB) during 1990–2019. We have used IMD best track data for track and vital parameters of ITCs. We have also used high resolution (0.25°×0.25°) ERA5 SLHF, SSHF and SST data for their variations during the lifetime of ITCs. It is observed that the SLHF_max during the whole lifetime and the study period is highly correlated with ITCs’ intensity (i.e. with the central pressure (CP) and the maximum sustained wind speed (MSW)) whereas the SSHF_max shows weak correlations with ITCs’ intensity. This suggests the strong association between the SLHF_max and ITCs intensity and strong latent heat flux exchange between the ocean and atmosphere during the whole lifetime and the study period. Similar results are observed in the pre-monsoon and the post-monsoon season. In the pre-monsoon season the association of SLHF_max with the ITCs intensity is stronger than the post-monsoon season due to strong background conditions, pointing towards the strong air-sea interaction. The SLHF_max in the growing and the decaying stage are also highly correlated with ITCs’ intensity but correlation coefficients of ITCs’ intensity with the SLHF_max in the decaying stage are slightly higher than those of in the growing stage. It is also found that the SSHF_max has an appreciable correlation with ITCs’ intensity during the growing stage whereas it has negligible correlation with ITCs’ intensity during the decaying stage pointing towards the influence of sensible heat flux in the growing stage of ITCs. It is also noticed that during rapid decay (RD) the SLHF_max is highly correlated with ITCs’ intensity possibly due to cold wakes which rapidly diminishes the SLHF but during rapid intensification the SLHF does not increase so rapidly due to the sluggish WISHE feedback, hence the SLHF_max during rapid intensification (RI) is not appreciably correlated with ITCs’ intensity.</p>","PeriodicalId":51132,"journal":{"name":"Meteorology and Atmospheric Physics","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141547995","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Validation of ERA5 rainfall data over the South Pacific Region: case study of Fiji Islands","authors":"Philip Obaigwa Sagero, Arti Pratap, Royford Magiri, Victor Ongoma, Phillip Okello","doi":"10.1007/s00703-024-01025-z","DOIUrl":"https://doi.org/10.1007/s00703-024-01025-z","url":null,"abstract":"<p>Rainfall variability has a significant impact on hydrological cycle. Understanding rainfall variability over Fiji Islands is important for decision-making in the backdrop of global warming. Reanalysis rainfall products are commonly used to overcome observed data quality challenges especially over ungauged highland areas. However, an evaluation of reanalysed datasets is important to ensure accurate and reliable climate information generated using such datasets, especially for small Island with high variable topography like Fiji. This work aims to validate the spatiotemporal performance of European Centre for Medium-Range Weather Forecasts (ECMWF) fifth-generation reanalysis rainfall (ERA5) data against ground-based station data from 19 stations for the period 1971–2020 over Fiji Islands. Correlation coefficient and difference statistics: bias, and root mean square error, are used to assess the performance of the data. Further, common Empirical Orthogonal Function (common EOFs) analysis was used to evaluate spatiotemporal performance of ERA5 datasets. The results of the station-by-station comparison shows that interpolated ERA5 annual rainfall matches the corresponding results from rain gauges remarkably well for many stations. The correlation coefficient values range from 0.5 to 0.85, while the bias spans from a negative 282 to a positive 575, and the root mean square error (RMSE) varies between 285 and 662 mm for the annual rainfall across the study area. However, there is overestimation and underestimation of the observed rainfall by ERA5 datasets. The leading common EOF principal component for annual rainfall suggests that the inter-annual variability in ERA5 dataset is generally consistent with observed station datasets, cross validation results indicated high scores (correlations of 0.82), with limited spatial variation. This work presents a reliable data assessment of the ERA5 data over Fiji Islands, indicating there is good match of the annual observed rain gauged station data and ERA5. The findings give accuracy references for further use of the ERA5 data in understanding rainfall variability and change over the region.</p>","PeriodicalId":51132,"journal":{"name":"Meteorology and Atmospheric Physics","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2024-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141505080","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Large-scale dynamics of extreme precipitation in the tropical Andes: combining weather radar observations and reanalysis data","authors":"M. Córdova, Johanna Orellana-Alvear, Jörg Bendix, R. Rollenbeck, R. Célleri","doi":"10.1007/s00703-024-01022-2","DOIUrl":"https://doi.org/10.1007/s00703-024-01022-2","url":null,"abstract":"","PeriodicalId":51132,"journal":{"name":"Meteorology and Atmospheric Physics","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141362444","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Atmospheric processes dominate the changes in autumn rain hours over the Sichuan Basin: 1960–2018","authors":"Xiang Ni","doi":"10.1007/s00703-024-01024-0","DOIUrl":"https://doi.org/10.1007/s00703-024-01024-0","url":null,"abstract":"","PeriodicalId":51132,"journal":{"name":"Meteorology and Atmospheric Physics","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2024-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141371058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improved temperature prediction using deep residual networks in Hunan Province, China","authors":"Li Zhou, Fei Huo, Ronghui Cai, He Chen, Lin Xu","doi":"10.1007/s00703-024-01023-1","DOIUrl":"https://doi.org/10.1007/s00703-024-01023-1","url":null,"abstract":"","PeriodicalId":51132,"journal":{"name":"Meteorology and Atmospheric Physics","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2024-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141373893","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deterministic ensemble Kalman filter based on two localization techniques for mitigating sampling errors with a quasi-geostrophic model","authors":"Mingheng Chang, Jikai Duan, Xiangyue Chen, Wenpeng Wang, Hongchao Zuo, Yulong Bai, Bolong Chen, Lei Ma","doi":"10.1007/s00703-024-01015-1","DOIUrl":"https://doi.org/10.1007/s00703-024-01015-1","url":null,"abstract":"","PeriodicalId":51132,"journal":{"name":"Meteorology and Atmospheric Physics","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2024-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141122248","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparative testing of selected solar radiation shields under hot Mediterranean summer conditions","authors":"Vasileios D. Sakalis, Stylianos A. Tsatalas","doi":"10.1007/s00703-024-01021-3","DOIUrl":"https://doi.org/10.1007/s00703-024-01021-3","url":null,"abstract":"","PeriodicalId":51132,"journal":{"name":"Meteorology and Atmospheric Physics","volume":null,"pages":null},"PeriodicalIF":2.0,"publicationDate":"2024-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140967699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}