Track forecast:Operational capability and new techniques-Summary from the Tenth International Workshop on Tropical Cyclones(IWTC-10)

In this paper,we summarize findings from the Tenth International Workshop on Tropical Cyclones(IWTC-10)subgroup on operational track forecasting techniques and capability.The rate of improvement in the accuracy of official forecast tracks(OFTs)appears to be slowing down,at least for shorter lead times,where we may be approaching theoretical limits.Operational agencies continue to use consensus methods to produce the OFT with most continuing to rely on an unweighted consensus of four to nine NWP models.There continues to be limited use of weighted consensus techniques,which is likely a result of the skills and additional maintenance needed to support this approach.Improvements in the accuracy of ensemble mean tracks is leading to increased use of ensemble means in consensus tracks.Operational agencies are increasingly producing situation-dependent depictions of track uncertainty,rather than relying on a static depiction of track forecast certainty based on accuracy statistics from the preceding 5 years.This trend has been facilitated by the greater availability of ensemble NWP guidance,particularly vortex parameter files,and improved spread in ensembles.Despite improving spread-skill relationships,most ensemble NWP systems remain under spread.Hence many operational centers are looking to leverage“super-ensembles”(ensembles of ensembles)to ensure the full spread of location probability is captured.This is an important area of service development for multi-hazard impact-based warnings as it supports better decision making by emergency managers and the community in the face of uncertainty.©2023 The Shanghai Typhoon Institute of China Meteorological Administration.Publishing services by Elsevier B.V.on behalf of KeAi Communication Co.Ltd.This is an open access article under the CC BY-NC-ND license(http://creativecommons.org/licenses/by-nc-nd/4.0/).

Recommendations for improved tropical cyclone formation and position probabilistic Forecast products

Prediction of the potentially devastating impact of landfalling tropical cyclones(TCs)relies substantially on numerical prediction systems.Due to the limited predictability of TCs and the need to express forecast confidence and possible scenarios,it is vital to exploit the benefits of dynamic ensemble forecasts in operational TC forecasts and warnings.RSMCs,TCWCs,and other forecast centers value probabilistic guidance for TCs,but the International Workshop on Tropical Cyclones(IWTC-9)found that the“pull-through”of probabilistic information to operational warnings using those forecasts is slow.IWTC-9 recommendations led to the formation of the WMO/WWRP Tropical Cyclone-Probabilistic Forecast Products(TC-PFP)project,which is also endorsed as a WMO Seamless GDPFS Pilot Project.The main goal of TC-PFP is to coordinate across forecast centers to help identify best practice guidance for probabilistic TC forecasts.TC-PFP is being implemented in 3 phases:Phase 1(TC formation and position);Phase 2(TC intensity and structure);and Phase 3(TC related rainfall and storm surge).This article provides a summary of Phase 1 and reviews the current state of the science of probabilistic forecasting of TC formation and position.There is considerable variability in the nature and interpretation of forecast products based on ensemble information,making it challenging to transfer knowledge of best practices across forecast centers.Communication among forecast centers regarding the effectiveness of different approaches would be helpful for conveying best practices.Close collaboration with experts experienced in communicating complex probabilistic TC information and sharing of best practices between centers would help to ensure effective decisions can be made based on TC forecasts.Finally,forecast centers need timely access to ensemble information that has consistent,user-friendly ensemble information.Greater consistency across forecast centers in data accessibility,probabilistic forecast products,and warnings and their communication to users will produce more reliable information and support improved outcomes.