Roshydromet scientific projects involving COSMO/ICON

1. Roshydromet scientific projects involving COSMO/ICON Dmitry Kiktev 43rd COSMO Steering Committee meeting 21-22 March 2019, Offenbach

2. Current COSMO-Ru domains on SGI ICE-X cluster

3. Current COSMO-Ru domains on Cray XC-LC Cray XC-LC computer with peak performance of ~1.3Pflops was installed at the MCC of Roshydromet in the framework of the Roshydromet technical modernization project: - 936 nodes with 2 processors IntelXeon E5-2697v4 - 33 696 cores (every processors has 18 cores) - 4.608 Tb operative memory (every node has 128 Gb).

4. ICE-POP2018 project (International Collaborative Experiment for PyeongChang2018 Olympic & Paralympic winter games) COSMO-02 • Today activities are focused on verification of the different COSMO model configurations. • The main aims are • to evaluate new cloud-aerosol-radiation scheme developed within the COSMO PP T2(RC)2 framework using observations on cloud and precipitation microphysics; • to improve the practice of using spatial methods, neighborhood and object-based approaches for verification. Pyeongchang 2018 COSMO-005 Pyeongchang 2018

5. Development of early warning system for Moscow(also positioned as potential WMO demonstration project on integrated weather, environment and climate services for sustainable cities) • Agreement with Moscow government was signed at the end of 2018. • Time line for development of the system • Deterministic sub-kilometer forecasts: • 2019 – operational technology (in downscaling mode); • 2020 – operational technology (with DA); • EPS: 2020 – prototype; 2021 – operational technology

6. Current activities with urban description in TERRA_URB module - Development of detailed land-use and building morphology datasets for Moscow; - Verification and calibration of the model with TERRA_URB for Moscow region using various observational data; - Testing the latest model version (5.05_urb) in the framework of AEVUS PT.

7. Hydrological tailored application Coupling of COSMO-Ru and SnoWe with the river runoff model ECOMAG for flood modeling and short-range forecasting (in collaboration with MSU) Spatial variability and temporary changes of snow cover characteristics in Moscow region Snow density and snow water equivalent for the Moscow region were retrieved for the period of 2000-2018 using 1-D multilayer SnoWEmodel with goal to calibrate SnoWe and use it for the Moscow region for producing snow-evaluation fields.

8. Points of Snow Water Equivalent evaluation (SYNOP measurements) in the domains of COSMO-Ru Example of daily SNOWE products: Snow Water Equivalent map

9. Testing AMPT (AdditiveModel-errorperturbationsscaledby PhysicalTendencies) for stochastic representation of model-related uncertainty in an ensemble prediction system COSMO-Ru2-EPS ∆x~2.2 km, L51,M10, fc+48h, IC&BCs from a clone of COSMO-LEPS for Sochi region In a month trial, additive perturbations (without humidity and cloud fieldperturbations) appeared to yield better results than SPPT. CRPS (the lower the better) No model perturbations SPPT with Swiss setup AMPT with UVT perturbations February

10. Stochastic modeling of model errors on convective scales: a coarse-graining study Goal: build a justified multivariate spatiotemporal stochastic model for instantaneous (tendency) model errors. Needed in EDA and EPS. Approach: Evaluate 1-step model tendencies from (i) COSMO-2.2km-L65 (the “truth”) and (ii) COSMO-0.22km-L130 (the model) 2. Coarse-grain the fine-grid tendencies to the coarse grid and compute the difference – a proxy to model error. 3. Having a multivariate (i.e. T,U,V,Q,…) spatiotemporal (i.e. 4D) training sample of model errors, identify and estimate a model in the class of stochastic partial differential equations. 4. Identify roles of errors in different physical parameterizations.

11. Status of the coarse-graining study A preliminary study showed that the combination of errors from all sources in the model yields very complex structures, which are hard to be modeled (see below). A study that attempts to separate errors from different parameterizations (including errors in numerics but excluding errors in convection parameterization) is underway. Specification of time-constant, initial, and lower-boundary fields for the fine-grid and coarse-grid modelssuch that the coarse-grid-resolved field components are the same in the two models, is accomplished. The study is coordinated with C.Gebhardt and colleagues (DWD). An example of total model-error field: Looks like a superposition of several random fields with different scales - too complex to be amenable to a reasonably simple stochastic model

12. Sensitivity study to changes in land-surface properties Study of Effects of deforestation and afforestation on regional weather conditions(participation in the grant of the Russian Science Foundation) Several land-use change scenarios imitating total deforestation and afforestation of experimental area (55-59ºN, 28-37°E) for analysis of its influence to the weather phenomena were performed. Experiments with СOSMO–Ru shown that the regional deforestation can lead to increasing of continental indices and frequency of strong wind events, afforestation- to favorable conditions for fogs and increasing of precipitation. Area of experiments (current % of forests) Changes in moisture index Numbers of fogs conditions for points

13. Testing new comprehensive aerosol climatology (Macv2) vs older aerosol climatologies (Tanre, Tegen):Noon differences in the solar irradiance (Wm-2) forΔQ=QMAcv2-QTegen July January Large regional effects on Radiation fields - up to 80Wm-2 in China and noticeable changes over Europe

14. Reducing number of COSMO-ART reactions for optimization of computing resources • Large computational power is required to predict evolution of pollutant concentrations by combined atmospheric model taking into account multiples feedbacks. • A reduced scheme of chemical chains was proposed and tested. The experiments were carried out using a chain of 14, 16 reactions, and the full reaction scheme (172 reactions). • Resume • The number of reactions in COSMO/ICON-ART was reduced from 172 to 16 to shorten the calculation time. • • The reduced system satisfactory reproduces mean daily concentrations of CO, NO, NO2, O3

15. Development of combined technology of nowcasting, VSRF, SRF Radar nowcasting: Self-similarity properties in the statistical structure of precipitation fields are used. This kind of process can be described by a multiplicative cascading model. Elements of algorithm: • Spectral decomposition of precipitation fields: bandpass filters are usedto single out narrow spectral bands (cascades). • Hierarchical set of AR(1) models is implemented at all cascade levels for assessment of temporal evolution • Assembling of «composite» forecast fields.

16. Development of combined technology of nowcasting, VSRF, SRF Radar fields vs corresponding radar nowcasts and COSMO forecasts Radar Radar nowcast COSMO-RU2 Radar Radar nowcast - Properties of COSMO and radar nowcasting fields at 10 min temporal resolution are evaluated and intercompared for the appropriate blending. - RUC is to be implemented at later stages COSMO-RU2

17. Thank you