1 / 23

Variability of the Earth’s OLR inferred from reanalyses and satellite observations

Variability of the Earth’s OLR inferred from reanalyses and satellite observations. Richard Bantges, Claudio Belotti, Helen Brindley and Jon Murray. Space & Atmospheric Physics. CLARREO Science Team Meeting, July 2010. Outline. Modelled ‘clear-sky’ IR variability from ERA Interim reanalyses

padma
Download Presentation

Variability of the Earth’s OLR inferred from reanalyses and satellite observations

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. Variability of the Earth’s OLR inferred from reanalyses and satellite observations Richard Bantges, Claudio Belotti, Helen Brindley and Jon Murray Space & Atmospheric Physics CLARREO Science Team Meeting, July 2010 © Imperial College London

  2. Outline • Modelled ‘clear-sky’ IR variability from ERA Interim reanalyses • Clear-sky IR spectral signatures from satellite interferometer data • All-sky sampling studies using SEVIRI • Future developments and activities © Imperial College London

  3. (1) Modelled ‘clear-sky’ variability from ERA Interim • ERA Interim covers period 1989 onward • Profiles of T, H2O(g), O3 from reanalyses • CO2, CH4, N2O from UKMO records (total column, 5 year global mean, interpolation) • Surface emissivity constant at 0.99 globally • Spectral radiances simulated at nadir using Oxford RFM © Imperial College London

  4. RFM model runs • So far: 1989, 1994, 1999, 2004-2008 • monthly mean fields (‘clear-sky’ but using all profiles) • 37 atmospheric levels (1000-1mb) • spatially resolved 1.5°x1.5° • 100-2500cm-1, spectral resolution 0.5cm-1 • ~29000 RT simulations per month © Imperial College London

  5. ERA Interim – temperature anomalies Step change: 1998: SSU replaced by AMSU-A Temperature anomaly (K) © Imperial College London

  6. ERA Interim: 3 & 5 yr global average differences O3 Std. dev. (1σ) BT (K) CO2 CH4 CO2 H2O © Imperial College London

  7. ERA Interim – Annual mean atmospheric profiles © Imperial College London

  8. ERA Interim: 3 year global variability 2004-2006 2005-2007 2006-2008 Std. dev. (1σ) BT (K) © Imperial College London

  9. El Niño Southern Oscillation Index 2008 2004 © Imperial College London

  10. ERA Interim: 3 & 5 year zonal averages Std. dev. (1σ) BT (K) Std. dev. (1σ) BT (K) © Imperial College London

  11. (2) Spectral signatures from satellite data © Imperial College London

  12. Data / Methodology • IMG – level 1D (band3, calibrated, unapodized) • IASI – level 1C (band1&2, calibrated, apodized) (±2.5° off nadir) • IMG & IASI resampled to 0.02cm-1 dispersion grid • IMG data convolved with the IASI instrument function • Semi-empirical wavenumber shift applied to IMG to match IASI • SST – ERSST v3b (Extended Reconstruction Sea Surface Temperature) • Central Pacific region (±10°N, 130-180°W) • AMJ average, cloudy spectra removed using brightness temperature at 10.8μm contrast with SST. (5K).

  13. Cloud-free IASI / IMG (Central Pacific – AMJ)

  14. (3) All-sky sampling studies using SEVIRI • Investigate impact of sampling strategies using narrow-band spectral channels • What is the effect of increased spectral resolution on previous results? (e.g. Doelling, Kirk-Davidoff) • What is seen at different wavelengths? • What degree of averaging is required to meet desired accuracy (i.e. do we need all wavelengths – e.g. different requirements may have different needs)? © Imperial College London

  15. All-sky sampling: method • Channels: 6.2, 7.3, 8.7, 10.8, 12.0, 13.4 microns. Temporal/Spatial resolution: Data every fifteen minutes, from approx 75N-75S, 75W-75E. • 3 months of data processed so far (from 2010) • Sampling strategy: Fly through 1 true-polar orbiter with SEVIRI pixel size (~10-25 km) footprint sampling every 200 km along ‘pseudo’ satellite track • Results binned to 15 x 15 degree averages and compared to fully sampled fields. © Imperial College London

  16. 8.7 13.4 12.0 10.8 7.3 6.2 SEVIRI narrow-band channels A typical clear-sky spectrum of outgoing thermal energy

  17. SEVIRI – 10.8 mm, 1 month average True Sampled NOTE: Questions were raised over the validity of the satellite tracks used. These results are pending further investigation. © Imperial College London Sampled - true

  18. SEVIRI – 10.8 mm, 3 month average True Sampled NOTE: Questions were raised over the validity of the satellite tracks used. These results are pending further investigation. Sampled - true

  19. SEVIRI – 6.2 mm, 3 month average NOTE: Questions were raised over the validity of the satellite tracks used. These results are pending further investigation. © Imperial College London

  20. ‘Zonal’ averages (across SEVIRI disk) NOTE: Questions were raised over the validity of the satellite tracks used. These results are pending further investigation. © Imperial College London

  21. Summary (1) • Shown from ERA Interim model studies that 3 yr lifetime may not be sufficient to fully sample the “natural” variability • ENSO record suggest that 5 year would be better at capturing variability • Initial studies using (IASI & IMG) satellite data show consistency with inter annual and longer term ERA interim mean profiles (for well mixed GHGs) • Water vapour and ozone require more detailed anaylses © Imperial College London

  22. Summary (2) • Initial investigations of sampling strategy highlight that different levels of sampling accuracy will be obtained in different wavelength bands • Caution - the maximum IR differences aren’t always observed at 10.8mm © Imperial College London

  23. Future developments • Extend the period of ERA interim to look at a full 10 year cycle • Treatment / assessment of uncertainties introduced by cloud fields within ERA interim modelling • Extend IASI / IMG comparisons to 60N/S • IASI clear / all sky inter-annual variability • Full year (+) sampling strategy with SEVIRI (can adapt sampling) • Extend letter of agreement between NCEO & NASA • Submitted proposal SDT- TIR & FIR studies- Calibration / Validation © Imperial College London

More Related