1 / 20

Why observations? Understand processes -> develop parametrizations

clay
Download Presentation

Why observations? Understand processes -> develop parametrizations

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. ”UrbanBoundary-layer Atmosphere Network”Curtis Wood, Leena Järvi, Rostislav Kouznetsov, Ari Karppinen, Jaakko Kukkonen, Annika Nordbo, Timo Vesala, Achim Drebs, Anne Hirsikko, Sylvain Joffre, Timo Vihma, Irene Suomi, Carl Fortelius, Ewan O’Connor, Dmitri Moisseev, Markku KangasThanks to co-authors and the help from many support/technical/admin staff (and many research grants including EC, Finnish Academy)

  2. Why observations? • Understand processes -> develop parametrizations • Live data -> numerical models (e.g. data assimilation) -> climatology • Validate models (AQ, CTM, NWP)

  3. Why urban? • Most of us live in cities (even more work in cities) • NWP resolution getting finer (hence motivates physics’ devlopment )

  4. What is the science? NWP -> effect of surface on atmosphere (ABL scale and smaller) AQ -> e.g. want pollutant distributions near ground • ABL depth affects concentrations, especially of surface-released quantities Hence urban ABL • Variation in space and time of wind, temperature, moisture • The surface energy budget Sat 4th Feb 2012, 23:48 (Helsinki)

  5. Surface energy budget INPUTS/OUTPUTS HEAT FLUXES Net radiation – ground heat + storage = Sensible + Latent (vapour) + Anthropogenic Rn G S H LE A Net radiation: Shortwave & longwave radiation Rn H LE A S G

  6. Helsinki UrBAN Aims • Develop observation network • Research high-latitude urban ABL • Provide data for evaluation, assessment & improvement of urban sub-models/parametrizations in NWP/AQ models

  7. Map made by Annika Nordbo, from HSY data

  8. Flux stations • Eddy-covariance method • Tower-based measurement • SMEAR-III, Torni (+more) momentum • 1st case-study in this presentation: • 4th September 2011 • Mostly clear skies (cumulus) Latent heat Particle flux CO2 flux Sensible heat www.atm.helsinki.fi/SMEAR

  9. SMEAR III • Dec 2005 → • 31 m • EC (τ, H, LE, Fc , Fp) • Basic meteorology • T & U profiles • Gases, particles AJ Kieloaho • FireStation • Jul2010–Jan2011 • 42 m • EC (τ, H, LE, Fc , Fp) • Hotel Torni • Oct 2010 → • 60 m • EC (τ, H, LE, Fc , Fp) JFJ Korhonen Matemaattis-luonnontieteellinen tiedekunta / Henkilön nimi / Esityksen nimi

  10. Sensible heat flux

  11. Scintillometer • Scintillations (twinkling) due to refraction • Related to temperature gradient Structure parameter for T 4.3km path Kumpula-Torni • Can be related to sensible heat flux Transmitter Receiver

  12. -> City-scale (Kumpula-Torni) -> Downtown (Sitra-Elisa) Rosa Gierens

  13. Sodar • Variables: • Profile of vertical velocity • Atmospheric boundary-layer depth (based on backscatter gradient) • Single vertically-pointing antenna (1D) • 5 s sounding interval • 20-400m range; with 10-m resolution • Kumpula, then Pasila ABL depth Turbulence (day)

  14. Lidar • Scanning, doppler • “HALO Photonics Streamline” • Several km range (~30m resolution) • Vertical profiles: turbulence, wind, aerosol (e.g. pollution or volcanic ash) • Custom scans (any angle) • Deep ABL seen by lidar • Shallow ABL seen by sodar

  15. IntercomparisonCase-study 2: 03 January 2012 r = 0.96 rmse = 0.48 m/s bias= –0.23 m/s (SMEAR-III greater than lidar) Finnish Meteorological Institute

  16. Auxiliary measurements: Useful for… – mesoscale effects? -- background data? Finnish Meteorological Institute

  17. Overview • Helsinki UrBAN is among the most comprehensive urban networks • Many science results already published, e.g.: • Urban carbon dioxode exchange of many annual cycles (about average for worldwide cities) • Initial anthropogenic heat flux estimate (e.g. 13 W/m2 around SMEAR-III) • Much more unstable downtown (anthrop heat flux, plus storage release)

  18. SWOT analysis for the observation network Strengths: • Growing observational network • Some collaboration with corresponding UK studies • Helsinki TestBed • Unique site (strong seasonality, high-latitude) Weaknesses: • Moderate current funding • No street canyon work Opportunities: • Write proposals • Bring together many people/skills (e.g. workshops) • Connect with companies and customers (e.g. Vaisala, HSY) Threats: • Skills too varied? • Not many people’s priority • No current external future funding?

  19. New/planned activities: Finnish Meteorological Institute

  20. Pääkaupunkiseudunortoilmakuva 2011: Espoon, Helsingin, Kauniaisten, Vantaan,Kirkkonummen ja Keravan kaupungit sekä HSY ”UrbanBoundary-layer Atmosphere Network”Curtis Wood, Leena Järvi, Rostislav Kouznetsov, Ari Karppinen, Jaakko Kukkonen, Annika Nordbo, Timo Vesala, Achim Drebs, Anne Hirsikko, Sylvain Joffre, Timo Vihma, Irene Suomi, Carl Fortelius, Ewan O’Connor, Dmitri Moisseev, Markku KangasThanks to co-authors and the help from many support/technical/admin staff (and many research grants including EC, Finnish Academy) Any ideas for best use of our network?

More Related