PP-AWARE : A ppraisal of "Challenging W e A ther " Fo RE casts

1. PP-AWARE: Appraisal of "Challenging WeAther"FoREcasts Joint Project Proposal: WG5 &WG4 (collaboration with WG7) The goal of the PP is to provide COSMO Community with an overview of forecast methods and forecast evaluation approaches that are linked to high impact weather (not necessarily considered extreme to all users). Key forecast quality and verification aspects to consider in this project include: • How well high-impact weather is represented in the observations, including biases and random errors, and their sensitivity to observation density. • How well high-impact weather is represented in models, including systematic and stochastic errors, and their sensitivity to model resolution. • How well high-impact weather is represented in postprocessing. • The predictability, current predictive skill, and the user’s interpretation of forecast value in high-impact weather situations (observed and/or forecast). COSMO SMC meeting, 5-6 February 2019

2. Motivation • Despite significant progress in short-range forecasting, HIW continues to cause most part of damage to the economy and society, up to losses of human lives • In COSMO consortium, there have been several studies partially related to CW aspects. However, up to now there haven’t been a project explicitly focusing on evaluation and development of HIW forecasts • Necessity to tackle scientific problems, which step beyond the concerns of a single strategic area and a Working Group • Challenging weather (CW) or high impact weather (HIW), are events the local society is not routinely experiencing: extreme in amplitude (intense winds, or heavy convective precipitation), rare (lie in a tail of climatological distribution for a particular location) or high impact by being prolonged ‘regimes’ (droughts, heat-waves or cold-spells), while others can be considered challenging if society is particularly vulnerable (e.g. impact of fog on transportation). • Forecast methods and verification are important aspects of any CW consideration. Many newer diagnostic approaches provide useful information to aid understanding of errors in model processes for related weather regimes. CW phenomena as fog or lightning are usually not directly forecasted by NWP models, and thus appropriate empirical methods are applied for their prediction.

3. Known deficiencies to be addressed are: Often a mismatch between what models can provide and what warnings need to be made for: Lightning, hail, wind gusts, fog, etc. Large uncertainty with extreme events (Ensemble/probabilistic forecasts to measure "extremeness“). Models may not capture the intensity of high impact events (Sub-grid scale processes, Coarse resolution, Difficulty representing processes) Main weather parameters of interest: • Convection related (thunderstorms, heavy precipitation, lightnings, hail, squall lines) • severe wind (and wind gusts) • min-max temperature (persistence) • visibility (fog) • extreme convective phenomena like tornadoes, dust-devils • clear-air turbulence (CAT), etc.

4. Proposed Tasks (based on available contributions) Task 1. Challenges in observing CW/HIW (WG5 and WG4 related) Consider which observations are necessary to verify HIW forecasts, and issues related to observation sparseness, quality, and thresholds. Effort will be given to identify the dependence of HIW prediction improvements on dense observations, to identify observation requirements for monitoring the selected hazards and/or for assessing forecast accuracy, and quantify the role of observation uncertainty. Task 2: Overview of appropriate verification measures for HIW (WG5 related) The verification of HIW events requires metrics that remain useful for rare events. Characteristics include to be less dependent on the base rate (climatology of the event), minimized dependency on spatial and temporal scales, sampling of observational data and less dependent on the verification grid. SubTasks: Survey for assessment of proper verification approaches for phenomena – continuous vs. discrete verification (occurrence vs. specific values). Role of SEEPS and EDI-SEDI for the evaluation of extreme precipitation forecasts Task 3: Extreme Value Theory (EVT) approach (WG5 related) EVT is a branch of statistics which studies the properties of extreme values, and enables them to be fit with theoretical distributions (or probability models). EVT is a branch of statistics which studies the properties of extreme values, and enables them to be fit with theoretical distributions (or probability models). EVT is a branch of statistics which studies the properties of extreme values, and enables them to be fit with theoretical distributions (or probability models). COSMO SMC meeting, 5-6 February 2019

5. Proposed Tasks (based on available contributions) Task 4: Verification applications (with a focus on spatial methods) to HIW(WG5 and WG7 related)Verification applications (with a focus on spatial methods) to HIW (WG5 and WG7 related) Work connected with and continued from PP-INSPECT and MesoVICT projects. SubTasks: Verification of forecasts of intense convective phenomena Lightning potential index (LPI) Verification CRA (Contiguous rain area) and FSS analysis DIST methodology tuned on high threshold events Feature-based analysis of intense precipitation using SAL approach and comparison with LPI Comparative verification of NWC and NWP results using spatial verification methods as part of the SINFONY project at DWD. Task 5. Overview of forecast methods, representation and user-oriented products linked to HIW (WG4 related) SubTasks: Methods used to predict fog/visibility forecasts as direct model output (DMO) Overview of postprocessing techniques for HIW forecasts Improving existing forecast methods Forecast Tools of HIW phenomena at MeteoSwiss Comparison of postprocessing techniques vs. DMO and human forecasts QPF evaluation approaches Representation of HIW forecast for decision making Product generation and calibration of convection-permitting ensemble

6. PP-AWARE Project Participants DWD: Chiara Marsigli, Michael Hoff MeteoSwiss: Daniel Cattani HNMS: F. Gofa, D. Boucouvala IMGW-PIB: Andrzej Mazur, Joanna Linkowska, GrzegorzDuniec RHM: A. Bundel, E. Tatarinovich, A.Muraviev ARPAE: M.S. Tesini Required Resources Task0: 0.5FTEs Task1: 0.2 FTEs Task2: 0.7FTEs Task3: 0.3 FTEs Task4: 1.15 FTEs Task5: 1.05 FTEs Project Duration: Two years Start Date: To be decided