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Status of combining ground-based with satellite-based measurements in the atmospheric state retrieval Kerstin Ebell, Emiliano Orlandi, Anja Hünerbein, Ulrich Löhnert, Susanne Crewell. Outline. review of last status and planned steps

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Outline

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  1. Status of combining ground-based with satellite-based measurements in the atmospheric state retrieval • Kerstin Ebell, Emiliano Orlandi, Anja Hünerbein, • Ulrich Löhnert, Susanne Crewell

  2. Outline • review of last status and planned steps • first results of a combined LWC/reff_liq retrieval @ JOYCE(ground-based observations only) • next steps

  3. Summary of results last meeting • implementation of RTTOV as forward operator in the short visit to TROPOS on 11-13 March 2013 still some issues in cloudy cases • framework for a full combined retrieval using synthetic observations from clear-sky radiosondes • good results for HATPRO + satellites under idealized conditions  results of „offline“ calculations as presented in paper confirmed • AERI forward model (LBLRTM) far too slow to use for operational application • problem of non-convergence for AERI retrieval not solved yet How would the retrieval behave under real conditions? need to move on and use real observations @JOYCE

  4. „Old“ next steps • identify case studies ✔ 7 days in 04/05 2013 • preparation for operational IPT for JOYCE: • implement PAMTRA as a forward model for MWR BTs and cloud radar Z:handle T, q, LWC, and effective radius as direct model input parameter (and get rid of Z-LWC relation) ✔ • implement new LWC and reff_liq prior information ✔ • run and test new version of IPT for these cases ( LWC, reffliq, T, q) ✔ • implement IWC retrieval (Z-IWC-T method) • implement RTTOV in standard IPT version (incl. clouds)

  5. „Old“ next steps • SEVIRI: • provide SEVIRI measurements for JOYCE cases (parallax corrected) ✔ • determine surface emissivity for JOYCE site and uncertainty ✔ • determine spatial and temporal representativeness error: • use Cloudnet data and simple cloud algorithm + COSMO to simulate SEVIRI obs with a high temporal resolution  check temporal variability (representative for variability within the SEVIRI pixel ✔ • check variability of m x n SEVIRI pixels ✔ • satellite retrieval products (tau, reff) for these cases ✔ • airmass analysis ....later

  6. new LWC and reff a priori information • here: 8-year-long data set of single-layer liquid water clouds at Lindenberg (Germany) using cloud radar Z and MWR LWP MEAN and STDDEV of LWC according to Frisch et al. (1998) Reff according to Frisch et al. (2002) Frisch et al. (1998) cloud cloud top=1 top=1 0.8 0.8 Frisch et al. (2002) 0.6 0.6 normalized cloud level height 0.4 0.4 0.2 0.2 cloud cloud 0.001 0.01 0.1 2 4 6 8 base=0 base=0 prior LWC / gm-3 prior reff_lliq / micron

  7. A priori LWC and reff covariances Correlation of LWC of cloud layers Correlation of reff_liq of cloud layers cloud top cloud top cloud base cloud base cloud base cloud base cloud top cloud top

  8. Current IPT settings prior information xa with error covariance matrix Sa forward model F(x)=y with error covariance matrix Se measurementsy with error covariance matrix Se 8-year-long climatology of single-layer water clouds y: 14 MWR BTs @22.44-31.4, 51.26-58 GHz, cloud radar Z Se: random meas. error (TB:0.2-0.5 K, Z: ~1 dB) RTO(T,q,LWC) = MWR BTs Simmer (1994) PAMTRA(LWC,reff) = Z assuming lognormal DSD Mech (2007), Smith (1984)

  9. Liquid water clouds: 25.4. (IOP7) Cloudy morning (up to 4/8) until 10 UTC, only few clouds during noon, afterwards again increasing Cumulus humilis cloudiness, wind turns from south to west in the afternoon

  10. Cloud profile example on 25 April 2013 cloud at 18:12:15 UTC 5000 Aerosol & insects Insects Aerosol 4000 top 3038 m Melt. ice & cloud drop. Melt. ice Height / m LWP 126 gm-2 3000 Ice & supercooled drop. Ice base 2376 m 2000 Driz./rain & cloud drop. Driz. or rain 1000 Cloud drop. only Clear sky 09 12 15 18 21 24 Time / UTC

  11. IPT results LWC effective radius • LWC profile shape closer to prior in upper part of clouds • rel. LWC (reff) uncertainties between 30 and 300% (10-30%) prior 20 20 IPT 15 15 1-σ Cloud level Cloud level 10 10 5 5 0 0 0.01 0.1 0 5 10 15 20 LWC / gm-3 reff_liq / micron

  12. Sensitivity to DSD in forward model LWC effective radius • retrieved profiles of LWC and reff_liq in particular may substantially vary depending on chosen DSD • reff_liq may vary up to 50%  uncertainty due to DSD assumptions needs to be taken into account in Se as forward model uncertainty prior 20 20 IPT 15 15 1-σ logn, σx=0.24 Cloud level Cloud level Cloud level 10 10 logn, σx=0.52 5 5 mono 0 0 0.01 0.1 0 5 10 15 20 LWC / gm-3 reff_liq / micron

  13. Sensitivity to prior uncertainties • simple experiment: assume diagonal Sa • vary prior uncertainty of LWC and reff from 10-100 % What is the effect on the uncertainty of the retrieved profile? LWC uncertainty reff_liq uncertainty 100 100 100 30 80 80 80 20 60 60 60 uncertainty of prior reff_liq / % uncertainty of prior reff_liq / % 40 10 40 40 20 0 0 20 20 % % 60 60 100 100 20 20 40 40 80 80 uncertainty of prior LWC / % uncertainty of prior LWC / % • larger prior uncertainty  larger retrieval uncertainties • here: accurate prior LWC more important Why?

  14. Sensitivity to prior uncertainties How much information in the retrieved LWC and reff_liq profile comes from the measurements / forward model? DOF LWC / # cloud layers DOF reff_liq / # cloud layers all information 100 100 100 100 80 80 80 80 60 60 no information (all informationcomes from prior profile) 60 60 uncertainty of prior reff_liq / % uncertainty of prior reff_liq / % 40 40 % 40 40 % 20 20 0 0 20 20 • for LWC, retrieval relies strongly on prior information • measurement information mainly used to constrain reff profile • undertermined problem: Z  reff, LWC(MWR only adds 1 DOF information to LWC profile, i.e. LWP) 60 60 100 100 20 20 40 40 80 80 uncertainty of prior LWC / % uncertainty of prior LWC / % DOF: Degrees of freedom for signal

  15. All profiles: 09-21 UTC  stable IPT performance

  16. retrieved LWC profiles

  17. retrieved LWC profiles LWC LWC uncertainty rel. LWC uncertainty • LWC profiles reasonable • large uncertainties especially in the lower part of the clouds cloud top=1 0.8 mean 0.01 10 100 0.1 1 0.01 0.1 1 0.6 rel. LWC unc. / % LWC unc. / gm-3 LWC / gm-3 normalized cloud level height 0.4 0.2 cloud base=0

  18. LWP and IWV comparison IPT-prior • good agreement between IPT and HATPRO regr. bias: 2.6 gm-2, stddev: 11.6 gm-2) • IWV of various retrievals/ radiosonde in consistentIPT vs. HATPRO:bias: -0.4 kgm-2,stddev: 0.7 kgm-2 IPT-HATPRO regr. LWP difference / gm-2 IWV / kgm-2 IPT HATPRO regr. GPS SONDE

  19. retrieved reff_liq profiles

  20. retrieved reffliq profiles reffliq reffliq uncertainty • reffliq between 10-13 micron • decreases with height, 2. maximum below cloud top mean cloud top=1 0.8 normalized cloud level height 0.6 0.4 10 0 1 2 3 8 12 14 reffliq / micron reffliq uncertainty / micron 0.2 cloud base=0

  21. DOF for LWC and reff_liq % • 80% of LWC information comes from a priori • large uncertainties in retrieved LWC • 60-80% or reff information from radar measurements • mean uncertainty of 10% in retrieved reffliq Some independent observations very valuable! %

  22. Ongoing analysis • retrieval of LWC only: reffliq is treated as a forward model parameter; forward model uncertainties included in Se: • tests where reffliq is updated in each iteration step using lwc in this iteration step and Frisch et al. (2002)  concergence problems unrealistic DOF for LWC • tests with fixed effective radius unrealistic DOF for LWC  further checks needed

  23. „New“ next steps • further testing with updated IPT version needed • treatment of drizzle • independent assessment of results: comparison to sunphotometer-in-cloud-mode retrieval • inclusion of IWC-Z-T method • inclusion of reff_ice retrieval • implement RTTOV in standard IPT version (incl. clouds) might also use synthetic profiles • no direct input of liquid effective radius! only possible to choose from following cloud types: stratus continental, stratus maritime, cumulus continental clean, cumulus continental polluted, cumulus maritime, cirrus  needs to be adapted • reff_ice as direct input parameter (use Jenny‘s reff here as prior?) reminder: no prior inform. for IWC and reffice!

  24. Towards the paper... Working Title: „Atmospheric profiling combining ground-based with satellite-based observations at the Jülich Observatory for Cloud Evolution JOYCE“ • IPT application to selected cases: analysis of results, sensitivity studies • characterization of selectes cases (history of airmass, Anja‘s trajectory analysis, results of satellite retrievals (JS, AH?), could be used to constrain forward model/prior information) • evaluation: comparison to radiosoundings, tower data, GPS, radiative closure at surface?

  25. 1 IPT Extension: 1.1 Ground-based IR (IGMK) • inclusion of LBLRTM to simulate spectral IR radiances in clear-sky cases (AERI, IASI) (fast IR RTM not yet availabe) Furthermore: • in order to be able to retrieve both, LWC and reff, inclusion of forward model PAMTRA to simulate MWR BTs and cloud radar Z • prior information for LWC and reff • clear-sky information content study combining both ground and satellite-based instrumentation no broadband IRR, no fast forward model IR, but spectral IR in clear-sky cases from ground and space with a line-by–line model no ice cloud properties

  26. 1 IPT Extension: 1.2 Satellite IRT (TROPOS, IGMK, FUB) • RTTOV implemented in the IPT: information content study for clear-sky cases • IR RTO also run from a satellite perspective (IASI) RTTOV not used in IPT for cloudy cases yet, but interface available

  27. 1 IPT Extension: 1.3 Satellite reflectances (FUB, TROPOS, IGMK) • reff and optical thickness of SEVIRI not included in IPT so far (as prior?) should be rather used to check retrieval output (Where do ground-based and satellite-based retrievals deliver same results?) more reasonable to directly include reflectances?

  28. 3 Spatial representativeness: 3.2 Cloud structure synergy (IGMK, TROPOS) • first case studies of ground-based IPT @ JOYCE no analysis of variability of clouds/representativity of IPT results, no comparison of 2D ground LWP/IWV structures with satellite infomation

  29. 4 Towards Long-term Application: 4.1 Operational Aspects (IGMK, FUB, TROPOS) no long-term application yet, still test phase @ JOYCE; AMF data not used

  30. 4 Towards Long-term Application: 4.2 Radiative Impact Study (TROPOS, IGMK) no

  31. 5 Publications and reporting (IGMK, TROPOS, FUB) to be written:Atmospheric profiling combining ground-based with satellite-based observations at the Jülich Observatory for Cloud Evolution JOYCE

  32. 2 Cloud history: 2.1 Cloud tracking (FUB,TROPOS)

  33. 2 Cloud history: 2.2 Cloud properties & history (FUB,TROPOS)

  34. 3 Spatial representativeness: 3.1 Cloud structure HRVIS (FUB,TROPOS)

  35. Selected cases

  36. Clear sky: 4.5., IOP 11 only very few high clouds in the morning, afterwards perfect clear-sky conditions, weak westerly winds

  37. Liquid water cloud: 21.4. clear-sky in the early morning, rapidly increasing cloudiness with weak wind rotating from NW to W, overcast from 06 UTC on

  38. Liquid water cloud: 23.4. mostly overcast, light rain between 11-14 UTC, weak SW-wind

  39. Liquid water cloud: 30.5. strong cloudiness with only few clearings (7/8), at late afternoon short clearance at about 17 UTC, afterwards again overcast situation, wind from south

  40. Ice cloud: 27.4. most of the time completely overcast with rain in the morning, significant lower temperatures than the day before, weak northerly winds

  41. Ice cloud: 30.4. broken cloudiness during morning and evening, in between overcast cloudiness, weak easterly winds, no rain

  42. Ice above liquid cloud: 18.5., IOP13 SUNHAT mostly overcast until late afternoon, some light rain in the morning, clearing up at late afternoon (15 UTC), low cumulus clouds during daytime, clear-sky conditions in the evening, low windspeed

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