Weather and Forecasting最新文献

The Impact of Analysis Correction-based Additive Inflation on subseasonal tropical prediction in the Navy Earth System Prediction Capability 基于分析修正的加法膨胀对海军地球系统预测能力中热带副季节预测的影响

IF 2.9 3区地球科学

Weather and Forecasting Pub Date : 2024-01-09 DOI: 10.1175/waf-d-23-0046.1

Stephanie S. Rushley, M. Janiga, William Crawford, Carolyn A. Reynolds, William Komaromi, J. McLay

{"title":"The Impact of Analysis Correction-based Additive Inflation on subseasonal tropical prediction in the Navy Earth System Prediction Capability","authors":"Stephanie S. Rushley, M. Janiga, William Crawford, Carolyn A. Reynolds, William Komaromi, J. McLay","doi":"10.1175/waf-d-23-0046.1","DOIUrl":"https://doi.org/10.1175/waf-d-23-0046.1","url":null,"abstract":"\u0000Accurately simulating the Madden-Julian Oscillation (MJO), which dominates intraseasonal (30-90 day) variability in the tropics, is critical to predicting tropical cyclones (TCs) and other phenomena at extended-range (2-3 week) timescales. MJO biases in intensity and propagation speed are a common problem in global coupled models. For example, the MJO in the Navy Earth System Prediction Capability (ESPC), a global coupled model, has been shown to be too strong and too fast, which has implications for the MJO-TC relationship in that model.\u0000The biases and extended-range prediction skill in the operational version of the Navy ESPC are compared to experiments applying different versions of Analysis Correction-based Additive Inflation (ACAI) to reduce model biases. ACAI is a method in which time-mean and stochastic perturbations based on analysis increments are added to the model tendencies with the goals of reducing systematic error and accounting for model uncertainty. Over the extended boreal summer (May-November), ACAI reduces the root mean squared error (RMSE) and improves the spread-skill relationship of the total tropical and MJO-filtered OLR and low-level zonal winds. While ACAI improves skill in the environmental fields of low-level absolute vorticity, potential intensity, and vertical wind shear, it degrades the skill in the relative humidity, which increases the positive bias in the Genesis Potential Index (GPI) in the operational Navy ESPC. Northern Hemisphere integrated TC genesis biases are reduced (increased number of TCs) in the ACAI experiments, which is consistent with the positive GPI bias in the ACAI simulations.","PeriodicalId":49369,"journal":{"name":"Weather and Forecasting","volume":"30 3","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139443531","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

Comparison of Clustering Approaches in a Multi-Model Ensemble for U.S. East Coast Cold Season Extratropical Cyclones 美国东海岸冷季外热带气旋多模式集合中的聚类方法比较

IF 2.9 3区地球科学

Weather and Forecasting Pub Date : 2024-01-09 DOI: 10.1175/waf-d-23-0017.1

Benjamin M. Kiel, B. Colle

{"title":"Comparison of Clustering Approaches in a Multi-Model Ensemble for U.S. East Coast Cold Season Extratropical Cyclones","authors":"Benjamin M. Kiel, B. Colle","doi":"10.1175/waf-d-23-0017.1","DOIUrl":"https://doi.org/10.1175/waf-d-23-0017.1","url":null,"abstract":"\u0000Several clustering approaches are evaluated for 1–9-day forecasts using a multi-model ensemble that includes the GEFS, ECMWF, and Canadian ensembles. Six clustering algorithms and three clustering spaces are evaluated using mean sea-level pressure (MSLP) and 12-h accumulated precipitation (APCP) for cool-season extratropical cyclones across the Northeast United States. Using the MSLP cluster membership to obtain the APCP clusters is also evaluated, along with applying clustering determined at one lead time to cluster forecasts at a different lead time. Five scenarios from each clustering algorithm are evaluated using displacement and intensity/amount errors from the scenario nearest to the MSLP and 12-h APCP analyses in the NCEP GFS and ERA5, respectively. Most clustering strategies yield similar improvements over the full ensemble mean and are similar in probabilistic skill except that: (1) Intensity Displacement Space gives lower MSLP displacement and intensity errors; and (2) Euclidean Space and Agglomerative Hierarchical Clustering, when using either full or average linkage, struggle to produce reasonably sized clusters. Applying clusters derived from MSLP to 12-h APCP forecasts is not as skillful as clustering by 12-h APCP directly, especially if several members contain little precipitation. Use of the same cluster membership for one lead time to cluster the forecast at another lead time is less skillful than clustering independently at each forecast lead time. Finally, the number of members within each cluster does not necessarily correspond with the best forecast, especially at the longer lead times, when the probability of the smallest cluster being the best scenario was usually underestimated.","PeriodicalId":49369,"journal":{"name":"Weather and Forecasting","volume":"1 6","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139444324","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

Collaborative Exploration of Storm-Scale Probabilistic Guidance for NWS Forecast Operations 为 NWS 预报业务提供风暴尺度概率指导的合作探索

IF 2.9 3区地球科学

Weather and Forecasting Pub Date : 2024-01-08 DOI: 10.1175/waf-d-23-0174.1

Katie A. Wilson, P. Burke, Burkely T. Gallo, Patrick S. Skinner, T. T. Lindley, Chad M. Gravelle, Stephen W. Bieda, Jonathan G. Madden, Justin W. Monroe, Jorge E. Guerra, Dale A. Morris

{"title":"Collaborative Exploration of Storm-Scale Probabilistic Guidance for NWS Forecast Operations","authors":"Katie A. Wilson, P. Burke, Burkely T. Gallo, Patrick S. Skinner, T. T. Lindley, Chad M. Gravelle, Stephen W. Bieda, Jonathan G. Madden, Justin W. Monroe, Jorge E. Guerra, Dale A. Morris","doi":"10.1175/waf-d-23-0174.1","DOIUrl":"https://doi.org/10.1175/waf-d-23-0174.1","url":null,"abstract":"\u0000The operational utility of the NOAA National Severe Storm Laboratory’s storm-scale probabilistic Warn-on-Forecast System (WoFS) was examined across the watch-to-warning time frame in a virtual NOAA Hazardous Weather Testbed (HWT) experiment. Over four weeks, 16 NWS forecasters from local Weather Forecast Offices, the Storm Prediction Center, and the Weather Prediction Center participated in simulated forecasting tasks and focus groups. Bringing together multiple NWS entities to explore new guidance impacts on the broader forecast process is atypical of prior NOAA HWT experiments. This study therefore provides a framework for designing such a testbed experiment, including methodological and logistical considerations necessary to meet the needs of both local office and national center NWS participants. Furthermore, this study investigated two research questions: (1) How do forecasters envision WoFS guidance fitting into their existing forecast process? and (2) How could WoFS guidance be used most effectively across the current watch-to-warning forecast process? Content and thematic analyses were completed on flowcharts of operational workflows, real-time simulation interactions, and focus group activities and discussions. Participants reported numerous potential applications of WoFS, including improved coordination and consistency between local offices and national centers, enhanced hazard messaging, and improved operations planning. Challenges were also reported, including the knowledge and training required to incorporate WoFS guidance effectively and forecasters’ trust in new guidance and openness to change. The solutions identified to these challenges will take WoFS one step closer to transition, and in the meantime, improve the capabilities of WoFS for experimental use within the operational community.","PeriodicalId":49369,"journal":{"name":"Weather and Forecasting","volume":"49 8","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139447284","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

Verification of the Global Forecast System, North American Mesoscale Forecast System, and High-Resolution Rapid Refresh Model Near-Surface Forecasts by use of the New York State Mesonet 利用纽约州中间网验证全球预报系统、北美中尺度预报系统和高分辨率快速刷新模式近地表预报

IF 2.9 3区地球科学

Weather and Forecasting Pub Date : 2023-12-29 DOI: 10.1175/waf-d-23-0094.1

Lauriana C. Gaudet, Kara J. Sulia, R. Torn, Nick P. Bassill

{"title":"Verification of the Global Forecast System, North American Mesoscale Forecast System, and High-Resolution Rapid Refresh Model Near-Surface Forecasts by use of the New York State Mesonet","authors":"Lauriana C. Gaudet, Kara J. Sulia, R. Torn, Nick P. Bassill","doi":"10.1175/waf-d-23-0094.1","DOIUrl":"https://doi.org/10.1175/waf-d-23-0094.1","url":null,"abstract":"Global Forecast System (GFS), North American Mesoscale Forecast System (NAM), and High-Resolution Rapid Refresh (HRRR) 2-m temperature, 10-m wind speed, and precipitation accumulation forecasts initialized at 1200 UTC are verified against New York State Mesonet (NYSM) observations from 1 January 2018 through 31 December 2021. NYSM observations at 126 site locations are used to calculate standard error statistics (e.g., forecast error, root mean square error) for temperature and wind speed and contingency table statistics for precipitation across forecast hours, meteorological seasons, and regions. The majority of the focus is placed on the first 18 forecast hours to allow for comparison among all three models. A daily NYSM station-mean temperature error analysis identified a slight cold bias at temperatures below 25°C in the GFS, a cool-to-warm bias as forecast temperatures warm in the HRRR, and a warm bias at temperatures above 30°C in each model. Differences arise when considering temperature biases with respect to lead times and seasons. Wind speeds are over-forecast at all ranges in each season, and forecast wind speeds ≥ 18 m s−1 are rarely observed. Performance diagrams indicate overall good forecast performance at precipitation thresholds of 0.1–1.5 mm, but with a high frequency bias in the GFS and NAM. This paper provides an overview of deterministic forecast performance across NYS, with the aim of sharing common biases associated with temperature, wind speed, and precipitation with operational forecasters and is the first step in developing a real-time model forecast uncertainty prediction tool.","PeriodicalId":49369,"journal":{"name":"Weather and Forecasting","volume":"12 3","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139147001","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

The influence of time varying sea-ice concentration on Antarctic and Southern Ocean numerical weather prediction 海冰浓度时变对南极和南大洋数值天气预报的影响

IF 2.9 3区地球科学

Weather and Forecasting Pub Date : 2023-12-28 DOI: 10.1175/waf-d-22-0220.1

Zhaohui Wang, Alexander D. Fraser, Phil Reid, Richard Coleman, S. O’Farrell

{"title":"The influence of time varying sea-ice concentration on Antarctic and Southern Ocean numerical weather prediction","authors":"Zhaohui Wang, Alexander D. Fraser, Phil Reid, Richard Coleman, S. O’Farrell","doi":"10.1175/waf-d-22-0220.1","DOIUrl":"https://doi.org/10.1175/waf-d-22-0220.1","url":null,"abstract":"Although operational weather forecasting centres are increasingly using global coupled atmosphere-ocean-ice models to replace atmosphere-only models for short- and medium-range (10-day) weather forecasting, the influence of sea ice on such forecasting has yet to be fully quantified, especially in the Southern Ocean. To address this gap, a polar-specific version of the Weather Research and Forecasting model is implemented with a circumpolar Antarctic domain to investigate the impact of daily updates of sea-ice concentration on short- and medium- range weather forecasting. A statistically-significant improvement in near-surface atmospheric temperature and humidity is shown from +24 hours to +192 hours when updating the daily sea-ice concentration in the model. The forecast skill improvements for 2 m temperature and dewpoint temperature are enhanced from June to September, which is the period of late sea-ice advance. Regionally, model improvement is shown to occur in most sea-ice regions, although the improvement is strongest in the Ross Sea and Weddell Sea sectors. The surface heat budget also shows remarkable improvement in outgoing radiative heat fluxes and both sensible and latent heat fluxes. This idealised research demonstrates the non-negligible effect of including more accurate time-varying sea-ice concentration in numerical weather forecasting.","PeriodicalId":49369,"journal":{"name":"Weather and Forecasting","volume":"20 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139149577","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

Severe convective storms in limited instability organized by pattern and distribution 按模式和分布组织的有限不稳定性中的强对流风暴

IF 2.9 3区地球科学

Weather and Forecasting Pub Date : 2023-12-26 DOI: 10.1175/waf-d-23-0130.1

Trevor A. Campbell, G. Lackmann, Maria J. Molina, Matthew D. Parker

{"title":"Severe convective storms in limited instability organized by pattern and distribution","authors":"Trevor A. Campbell, G. Lackmann, Maria J. Molina, Matthew D. Parker","doi":"10.1175/waf-d-23-0130.1","DOIUrl":"https://doi.org/10.1175/waf-d-23-0130.1","url":null,"abstract":"Severe convection occurring in high-shear, low-CAPE (HSLC) environments is a common cool-season threat in the Southeastern United States. Previous studies of HSLC convection document the increased operational challenges that these environments present compared to their high-CAPE counterparts, corresponding to higher false-alarm ratios and lower probability of detection for severe watches and warnings. These environments can exhibit rapid destabilization in the hours prior to convection, sometimes associated with the release of potential instability. Here, we use self-organizing maps (SOMs) to objectively identify environmental patterns accompanying HSLC cool season severe events and associate them with variations in severe weather frequency and distribution. Large scale patterns exhibit modest variation within the HSLC subclass, featuring strong surface cyclones accompanied by vigorous upper-tropospheric troughs and northward-extending regions of instability, consistent with prior studies. In most patterns, severe weather occurs immediately ahead of a cold front. Other convective ingredients, such as lower-tropospheric vertical wind shear, near-surface equivalent potential temperature (θe) advection, and the release of potential instability, varied more significantly across patterns. No single variable used to train SOMs consistently demonstrated differences in the distribution of severe weather occurrence across patterns. Comparison of SOMs based on upper and lower quartiles of severe occurrence demonstrated that the release of potential instability was most consistently associated with higher-impact events in comparison to other convective ingredients. Overall, we find that previously developed HSLC composite parameters reasonably identify high-impact HSLC events.","PeriodicalId":49369,"journal":{"name":"Weather and Forecasting","volume":"6 4","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139155588","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

Relating Tropical Cyclone Intensification Rate to Precipitation and Convective Features in the Inner Core 热带气旋加强率与内核降水和对流特征的关系

IF 2.9 3区地球科学

Weather and Forecasting Pub Date : 2023-12-19 DOI: 10.1175/waf-d-23-0155.1

Xinxi Wang, Haiyan Jiang, Oscar Guzman

{"title":"Relating Tropical Cyclone Intensification Rate to Precipitation and Convective Features in the Inner Core","authors":"Xinxi Wang, Haiyan Jiang, Oscar Guzman","doi":"10.1175/waf-d-23-0155.1","DOIUrl":"https://doi.org/10.1175/waf-d-23-0155.1","url":null,"abstract":"\u0000Using Tropical Rainfall Measuring Mission Microwave Imager observations of global tropical cyclones (TCs) from 1998 to 2013, relationships between TC intensification rate and inner-core convective and precipitation parameters are examined by decoupling the dependency of these parameters on TC intensity and that on TC intensification rate. Sixteen TC intensity change-intensity categories are categorized based on the initial intensity and 24-h future intensity change. The results show that the TC inner-core mean rain rate, convective intensity, and stratiform rain occurrence, and axisymmetric index of convective intensity increase significantly with TC intensification rate for each TC intensity category. The symmetry of rain rate and stratiform rainfall occurrence also increase significantly with TC intensification rate for each intensity category, except from slowly intensifying (SI) to rapidly intensifying (RI) group when the initial intensity is major hurricane. The RI major hurricanes have significantly more asymmetric rainfall distribution and distribution of stratiform rainfall occurrence than those of SI major hurricanes. For TCs with initial intensity in tropical depression, tropical storm, and major hurricane categories, the RI group has a significantly more asymmetric pattern of shallow precipitation/convection occurrence in the inner core than the SI group, while it has a significantly more symmetric pattern of deep convection occurrence than the SI group. The inner-core size, as quantified by the radius of maximum azimuthal mean rainfall decreases with both TC intensification rate and TC intensity.","PeriodicalId":49369,"journal":{"name":"Weather and Forecasting","volume":" 19","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138962579","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

The Pacific Northwest Heat Wave of 25-30 June 2021: Synoptic/Mesoscale Conditions and Climate Perspective 2021 年 6 月 25-30 日的西北太平洋热浪：综合/中尺度条件和气候展望

IF 2.9 3区地球科学

Weather and Forecasting Pub Date : 2023-12-18 DOI: 10.1175/waf-d-23-0154.1

Clifford F. Mass, David Ovens, John Christy, Robert Conrick

{"title":"The Pacific Northwest Heat Wave of 25-30 June 2021: Synoptic/Mesoscale Conditions and Climate Perspective","authors":"Clifford F. Mass, David Ovens, John Christy, Robert Conrick","doi":"10.1175/waf-d-23-0154.1","DOIUrl":"https://doi.org/10.1175/waf-d-23-0154.1","url":null,"abstract":"\u0000An unprecedented heatwave occurred over the Pacific Northwest and southwest Canada on 25-30 June 2021, resulting in all-time temperature records that greatly exceeded previous record maximum temperatures. The impacts were substantial, including several hundred deaths, thousands of hospitalizations, a major wildfire in Lytton, British Columbia, and severe damage to regional vegetation. Several factors came together to produce this extreme event: a record-breaking mid-tropospheric ridge over British Columbia in the optimal location, record-breaking mid-tropospheric temperatures, strong subsidence in the lower atmosphere, low-level easterly flow that produced downslope warming on regional terrain and the removal of cooler marine air, an approaching low-level trough that enhanced downslope flow, the occurrence at a time of maximum solar insolation, and drier than normal soil moisture. It is shown that all-time record temperatures have not become more frequent and that annual high temperatures are only increased at the rate of baseline global warming. Although anthropogenic warming may have contributed as much as 1°C to the event, there is little evidence of further amplification from increasing greenhouse gases. Weather forecasts were excellent for this event, with highly accurate predictions of the extreme temperatures.","PeriodicalId":49369,"journal":{"name":"Weather and Forecasting","volume":" 16","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138963706","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

Predicting Tropical Cyclone Formation with Deep Learning 利用深度学习预测热带气旋的形成

IF 2.9 3区地球科学

Weather and Forecasting Pub Date : 2023-12-14 DOI: 10.1175/waf-d-23-0103.1

Quan Nguyen, Chanh Kieu

{"title":"Predicting Tropical Cyclone Formation with Deep Learning","authors":"Quan Nguyen, Chanh Kieu","doi":"10.1175/waf-d-23-0103.1","DOIUrl":"https://doi.org/10.1175/waf-d-23-0103.1","url":null,"abstract":"\u0000Exploring new techniques to improve the prediction of tropical cyclone (TC) formation is essential for operational practice. Using convolutional neural networks, this study shows that deep learning can provide a promising capability for predicting TC formation from a given set of large-scale environments at certain forecast lead times. Specifically, two common deep-learning architectures including the residual net (ResNet) and UNet are used to examine TC formation in the Pacific Ocean. With a set of large-scale environments extracted from the NCEP/NCAR reanalysis during 2008–2021 as input and the TC labels obtained from the best track data, we show that both ResNet and UNet reach their maximum forecast skill at the 12–18 hour forecast lead time. Moreover, both architectures perform best when using a large domain covering most of the Pacific Ocean for input data, as compared to a smaller subdomain in the western Pacific. Given its ability to provide additional information about TC formation location, UNet performs generally worse than ResNet across the accuracy metrics. The deep learning approach in this study presents an alternative way to predict TC formation beyond the traditional vortex-tracking methods in the current numerical weather prediction.","PeriodicalId":49369,"journal":{"name":"Weather and Forecasting","volume":"81 3","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138971430","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

Jumpiness in ensemble forecasts of Atlantic tropical cyclone tracks 大西洋热带气旋路径集合预报的跳跃性

IF 2.9 3区地球科学

Weather and Forecasting Pub Date : 2023-12-13 DOI: 10.1175/waf-d-23-0113.1

David S. Richardson, H. Cloke, John A. Methven, F. Pappenberger

{"title":"Jumpiness in ensemble forecasts of Atlantic tropical cyclone tracks","authors":"David S. Richardson, H. Cloke, John A. Methven, F. Pappenberger","doi":"10.1175/waf-d-23-0113.1","DOIUrl":"https://doi.org/10.1175/waf-d-23-0113.1","url":null,"abstract":"\u0000We investigate the run-to-run consistency (jumpiness) of ensemble forecasts of tropical cyclone tracks from three global centers: ECMWF, the Met Office and NCEP. We use a divergence function to quantify the change in cross-track position between consecutive ensemble forecasts initialized at 12-hour intervals. Results for the 2019-2021 North Atlantic hurricane season show that the jumpiness varied substantially between cases and centers, with no common cause across the different ensemble systems. Recent upgrades to the Met Office and NCEP ensembles reduced their overall jumpiness to match that of the ECMWF ensemble. The average divergence over the set of cases provides an objective measure of the expected change in cross-track position from one forecast to the next. For example, a user should expect on average that the ensemble mean position will change by around 80-90 km in the cross-track direction between a forecast for 120 hours ahead and the updated forecast made 12 hours later for the same valid time. This quantitative information can support users’ decision making, for example in deciding whether to act now or wait for the next forecast. We did not find any link between jumpiness and skill, indicating that users should not rely on the consistency between successive forecasts as a measure of confidence. Instead, we suggest that users should use ensemble spread and probabilistic information to assess forecast uncertainty, and consider multi-model combinations to reduce the effects of jumpiness.","PeriodicalId":49369,"journal":{"name":"Weather and Forecasting","volume":"155 4","pages":""},"PeriodicalIF":2.9,"publicationDate":"2023-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139006396","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