Seamless Multi-Scale Modelling for Meteorology - Atmospheric Composition: Enviro-HIRLAM Applications

Transcription

1 Seamless Multi-Scale Modelling for Meteorology - Atmospheric Composition: Enviro-HIRLAM Applications by Alexander Mahura Institute for Atmospheric and Earth System Research (INAR) / Physics Faculty of Science, University of Helsinki (UHEL), Finland In linkage with multiple research projects and collaboration with many colleagues TRAKT-2018 project kick-off-meeting (at NIERSC) January 2018 St. Petersburg, Russia

2 Multi-Scale & -Processes Modelling at INAR From the poster at the INAR kick-off-meeting (Helsinki, Finland), 12 Jan 2018

3 Enviro-HIRLAM/ HARMONIE (EnviroHH) (Collaboration, Research and Development, Science Education, Dissemination, New Products and Applications) Enviro-HIRLAM linkage to the PEEX- Modelling Platform

4 Enviro-HIRLAM (Environment HIgh Resolution Limited Area Model) Seamless / online coupled integrated meteorology-chemistryaerosols downscaling modelling system for predicting weather and atmospheric composition (Baklanov et al., 2017) most recent

5 Enviro-HIRLAM as part of PEEX-Modelling Platform (Baklanov, Mahura et al., 2018) in finalization

6 Downscaling for Enviro-HIRLAM Regional-Subregional-Urban/City scales Note: in NordForsk CarboNord project ( ) at Northern hemispheric scale

7 Components of Enviro-HIRLAM Enviro-HIRLAM research and development team Baklanov et al., ; Korsholm et al., ; Mahura et al., ; Nuterman et al., ; & many other colleagues through collaboration (Denmark, Russia, Ukraine, Kazakhstan, Baltic States, Spain, Turkey, etc.) Components of the Enviro-HIRLAM modelling system Note: emission datasets used depend on research projects: MEGAPOLI, TRANSPHORM, PEGASOS, MarcoPolo, EnsCLIM, CarboNord, etc.

8 Urbanization Modules Applied Mahura et al. (2004- ) in FUMAPEX, HIRLAM, COST728, MEGAPOLI, MACC, TRANSPHORM, MarcoPolo, PEEX NWP Model NWP Initialization (urban domain/ resolution / land-cover) Model Run Land Surface Scheme ISBA Interactions Soil- Biosphere Atmosphere ISBA Tiles: low veg., forest, ice, snow, water, bare soil/ urban IF Urban Frac > 0 Pass MeteoParams Urban Modules Initialization: AHF+R+A: Urban - fraction, flux, roughness, albedo BEP: Urban - fraction, districts, characteristics SM2-U: Urban fraction, surfaces, classes, characteristics Re-calculated meteoparams and fluxes U r b a n M o d u l e s: AHF+R+A BEP SM2-U Model Output AHF+R+A BEP SM2-U

9 Urban Districts in Metropolitan Areas: Classification & Characteristics City Center High Buildings District GIS - Extraction of districts related characteristics (statistics): Morphology parameters (avg. height, volume, perimeter, compactness, space between buildings) Cover modes (surface density (SD) of buildings, of vegetation, hydrography, roads, N buildings) Aerodynamic parameters (roughness length, displacement height, frontal and lateral SD) Residential District Industrial Commercial District

10 Urban Districts in Metropolitan Areas: Classification & Characteristics Copenhagen (Denmark) Paris (France) Rotterdam (The Netherlands) Metropolitan Areas

11 EXAMPLES ON STUDIES

12 Copenhagen Metropolitan Area Denmark

13 AHF+R: Copenhagen Urban Effects Modelling Difference between runs: 01 Aug 2004, 06 UTC (control vs. urbanized run) Difference field for wind at 10 m (control vs. urbanized run) Difference field for temperature at 2 m Mahura et al. (2005-6)

14 BEP: Copenhagen Urban Effects Modelling Difference between runs: 01 Aug 2004, 06 UTC (control vs. urbanized run) Difference field for wind at 10 m (control vs. urbanized run) Difference field for temperature at 2 m Mahura et al. (2005-6)

15 BEP: Long-Term Verification Urban station N-6180: Copenhagen area : Verification July 2004 August 2004 Diurnal variability for 00 UTC forecasts for the average wind velocity at 10 m for the urban station N 6180 in the Copenhagen metropolitan area as function of the forecast length based on the DMI HIRLAM I01+BEP /U0D/ and I01 CTRL /C0D/ model runs vs. observations Mahura et al. (2007-8)

16 Paris Metropolitan Area France

17 Downscaling for Paris Metropolitan Area (meteorology & chemistry) Enviro-HIRLAM downscaling (from left to right: CTRL km & 2.5+URB) meteorological (top air temperature, middle humidity) and chemical (bottom ozone) fields on 4 Jul 2009, Mahura et al. ( ) UTC.

18 Paris Metropolitan Area: T2m Diurnal cycle variability of the difference fields (Enviro-HIRLAM-P01: control vs. urban runs) for air temperature at 2m on 4 Jul 2009 (from 00 till 24 UTCs). Mahura et al. ( )

19 Paris Metropolitan Area: T2m / AHF Diurnal cycle variability of the difference fields (Enviro-HIRLAM-P01: urban vs. control runs) for air temperature at 2m with changing anthropogenic heat fluxes (100, 150, 200, and 250 W/m2) on 4 Mahura et al. ( ) Jul 2009 at 06 and 24 UTCs

20 Paris Metropolitan Area: Temporal Variability of Meteo.Parameters Variability of (from left-to-right) boundary layer height, total cloud cover, surface temperature, wind speed on 4 Jul 2009 at (top) 09 UTC and (bottom) 21 UTC based on Enviro-HIRLAM model run at 2.5 km resolution with URB=BEP+AHF included. Mahura et al. ( )

21 Shanghai Metropolitan Area China

22 Downscaling for Enviro-HIRLAM: Modelling Domains vs. Metropolitan Areas Enviro-HIRLAM model downscaling domains ( km resolutions) Urban areas in domains C15 C15-15 km C05-5 km C05 C km C02 Mahura et al. ( ) Shanghai metropolitan area (MA)

23 Regional (15km)- Enviro-HIRLAM Downscaling: Aerosols PM10 (ug/m3) SubRegional (5km)- Urban (2.5km)- / Shanghai Mahura et al. ( )

24 Downscaling to Metropolitan Areas (MA) Beijing MA Mahura et al. ( ) Shanghai MA Perl-River-Delta operational Case studies for assessments 05/04/2018

25 15 km: PM2.5 T2m U10m RH2m Mahura et al. ( )

26 5 km: PM2.5 T2m U10m RH2m Mahura et al. ( ) 05/04/

27 2.5 km: PM2.5 T2m U10m RH2m Mahura et al. ( )

28 2.5km: Shanghai MA: PM10 Diurnal cycle: 20 Jul 2010 Mahura et al.,

29 Enviro-HIRLAM: In other projects & applications

30 Enviro-HIRLAM: CarboNord / PEEX-CRUCIAL Mahura, Nuterman et al. ( )

31 Enviro-HIRLAM: Rotterdam Mahura, Nuterman et al. ( )

32 Enviro-HIRLAM: Birch Pollen Phenological model output Emission rate & fractions of birch trees Normalized concentrations 24 hours forecast 48 hours forecast Copenhagen, Denmark Source: silam.fmi.fi Enviro-HIRLAM model output Collaboration Danish Asthma Allergy Association, Finish Meteorological Institute Normalized concentrations 24 hours forecast 48 hours forecast Copenhagen, Denmark Mahura, Rasmussen et al. ( )

33 Enviro-HIRLAM: Road Weather stretches for 296 roads (at distances of 1 km) Add line source traffic emissions (daily and weekly variability) road stretches in Ribe Amt region Collaboration Danish Road Directorate Mahura, Petersen et al. ( )

34 Thank you, Thank you, Thank you To many colleagues and many research projects