1 / 24

Short term variability of the ozone and other species simulated using LYRA data

Evaluate the response of the middle atmosphere to short-term solar UV irradiance variability using LYRA data from PROBA2 and PREMOS on PICARD. Goals include understanding solar influence, managing near-real-time operation, and preparation for model extension to upper atmosphere.

shornberger
Download Presentation

Short term variability of the ozone and other species simulated using LYRA data

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. Short term variability of the ozone and other species simulated using LYRA data Tatiana Egorova*, Eugene Rozanov*,**, Werner Schmutz* Ingolf Dammash*** * PMOD/WRC, Davos, Switzerland ** ETHZ, Zurich, Switzerland *** ROB, Brussels, Belgium

  2. Project idea Evaluate the response of the middle atmosphere to the short term solar UV irradiance variability Chemistry ionosphere climate model (CICM) extension of CCM SOCOL (Egorova, JASTP, 2010) LYRA on PROBA2 (ROB & PMOD/WRC) PREMOS on PICARD (PMOD/WRC) On-line LYRA and PREMOS data for space-weather community

  3. Goals • Find out how well we understand the solar influence on the middle atmosphere; • Learn how to manage near-real-time operation; • Space Weather Service is secondary goal but may become interesting if successful ! • Preparatrion to the model extention to upper atmosphere

  4. Nowcast results available on web every 6 hours Output validation to improve the model and experimental set-up Hourly/Daily Data from observations by LYRA, PREMOS, SORCE Nowcasting of neutral and ion composition in the mesosphere based on solar irradiance measurements Nowcast of anomalies of neutral and charged species with CICM SOCOLi Radiation spectrum reconstruction 120-680 nm

  5. Ozone and hydroxyl response to the solar variability January 2004 case study Hydroxyl and ozone in the mesosphere simulated with CCM SOCOL. These components are sensitive to variable solar irradiance because H2O + hv (121.5 nm) => OH + H OH goes up O3 + OH => O2 + HO2O3 decreases

  6. Experimental setup (intended) 10-member model ensemble run for the next 6 hours Hourly model output for the next 6 hours Spectral solar irradiance on model spectral grid for the next 6 hours Initialization fields for the next period Initial fields for 10 ensemble members

  7. Output data 4D: latitude, longitude, altitude, time Mixing ratio of the neutral species and electrons, negative and positive ions density for the 6 hour period after the last LYRA measurement and their statistical properties Charged components: O+, O2+, O4+, N+, NO+, N2+, H2O2+, H3O+,O2+∙N2, O2+∙H2O, H3O+∙OH, NO+∙H2O, NO+∙(H2O)2, NO+∙(H2O)3, NO+∙CO2, NO+∙N2, NO+∙H2O∙CO2, NO+∙H2O∙N2, NO+∙(H2O)2∙CO2, NO+∙(H2O)2∙N2, H+∙(H2O)2, H+∙(H2O)3, H+∙(H2O)4, H+∙(H2O)5, H+∙(H2O)6, H+∙(H2O)7, H3O+∙CO2, H3O+∙N2, H+∙(H2O)2∙CO2, H+∙(H2O)2∙N2 e¯,O¯, O2¯, O3¯, O4¯, OH¯, CO3¯, CO4¯, NO2¯, NO3¯, HCO3¯, ClO¯, Cl¯, CH3¯,O2¯∙H2O, NO3¯∙H2O, CO3¯∙H2O Neutral components: O3 , O* , O , O2*, NO, HO2, ClO, NO2 , OH, NO3, N2O5, HNO3,HONO3, ClONO2, Cl, N, N*, H2O2, H, HOCl, Cl2, Cl2O2, HCl , Br, CH2O, BrO, HBr, HOBr, BrNO3, BrCl, CH3, CH3O2, CH3O, HCO, CH3O2H, H2O, CFC-11, CFC-12, N2O, CH4, CO, H2, CBrF3

  8. Data form LYRA half calibrated (provided by IngolfDammash)

  9. Gap filled LYRA data Lyra R=0.75 Sorce/Solstice, 2008 R=0.58

  10. Gap filled LYRA data

  11. Solar spectrum reconstruction We have reconstructed solar UV irradiance for 120-680 nm required by the model from LYRA data applying linear regression analysis. We use the following formula for the reconstruction:  Fi= A + B  Pi F is solar spectral UV irradiance;  is wavelength; i is day number; A and Bcorrelation coefficients calculatedSOLSTICE/SORCE and SIM/SORCE for 2008; P is solar irradiance from LYRA (Channel 2). See Egorova et al. (ACP, 2008) for details and accuracy estimation

  12. Problems for Hartley-Higgins bands

  13. Experimental set-up Composite 1: 121-220 nm SOLSTICE/SORCE 220-700 nm SIM/SORCE Composite 2: 121-280 nm SOLSTICE/SORCE 280-700 nm SIM/SORCE

  14. Simulation with 1D model: O3 at 80km H2O + hv (121.5 nm) => OH + H O3 + OH => O2 + HO2 O3 and OH in antiphase

  15. Simulation with 1D model: OH at 80km H2O + hv (121.5 nm) => OH + H O3 + OH => O2 + HO2 O3 and OH in antiphase

  16. Simulation with 1D model: electrons at 80km NO + hv => NO++ e- O3 and electrons in phase

  17. Data sampling (daily vis. hourly) Blue- daily Red – hourly

  18. Simulation with 1D model: O3at 60km O2+ hv => O + O O2 + O + M => O3 O3+ hv => O(1D) + O2 O(1D) + H2O => OH + OH O3 and OH in phase

  19. Simulation with 1D model: OH at 60km O2+ hv => O + O O2 + O + M => O3 O3+ hv => O(1D) + O2 O(1D) + H2O => OH + OH O3 and OH in phase

  20. Vertical O3 profile: difference between two composites

  21. Electron density in the tropics Solar UV km SPE GCR Tropical mean time evolution (10-11.2003) of the electron concentration (cm-3).

  22. Conclusions • Ozone, hydroxyl, electron and ion densities show some response to the solar irradiance variability • Lyra data can be used for nowasting! If available in RT mode • Some problems with data and model remain ...

  23. End of talk

More Related