Tropical Upper Tropospheric cloud systems from AIRS in synergy with CALIPSO and CloudSat : Properties and feedbacks

Transcription

1 Tropical Upper Tropospheric cloud systems from AIRS in synergy with CALIPSO and CloudSat : Properties and feedbacks Sofia Protopapadaki, Claudia Stubenrauch, Artem Feofilov Laboratoire de Météorologie Dynamique / IPSL, France April 2017, A-Train symposium, Pasadena, California 1

2 Context High altitude clouds represent ~40% of total cloud cover (Stubenrauch et al. 2013) Formed in situ, or as the outflow of convective systems AIRS-LMD Modulate Earth's energy budget and heat transport Cloud feedbacks main uncertainty in climate models! Blue : High clouds, (Dark light decreasing εcld ) What is the role of cirrus in modulating the Earth s climate? How do clouds change in warming climate? rad. heating atm. circulation GEWEX* Process Evaluation Study on Upper Tropospheric Clouds & Convection Working group coordinated by C.Stubenrauch & G.Stephens (meetings: Nov 2015, Apr 2016, Mar 2017) multiple communities involved: observations, radiative transfer, process & climate modelling Methodology : cloud system approach, anchored on IR sounder data prepare synergetic data vertical dimension, atmospheric environment, heating rates

3 Why using IR Sounders to derive cirrus properties? TB, Tcld, ɛcld relation TOVS, ATOVS, AIRS, CrIS, IASI (1,2,3), IASI-NG >1979/ / / 2012 / :30 AM/PM, 1:30 AM/PM, 9:30 AM/PM long time series & good areal coverage climate studies good spectral resolution sensitive to cirrus retrieval day & night modular retrieval code: LMD-CIRS (LMD Cloud retrieval from IR Sounders) used for AIRS, IASI (LMD) & for TOVS/ATOVS (CM-SAF) Weighted χ method 2 get cloud properties: εcld, pcld, Tcld AIRS-CIRS (reanalysis V2) Stubenrauch et al (submitted ACP) ISCCP from GEWEX Cloud assessment Database (Stubenrauch et al. 2013) relative high cloud amount : CAHR = CAH/CA Tcld & εcld are independent variables, whereas TBIR depends on Tcld & on ɛcld AIRS cloud height evaluation with CALIPSO V2 V1 % AIRS and IASI -LMD L2 Data (V1) : distributed by: January 3

4 From pixels to cloud systems Clouds are extended objects, driven by dynamics organized systems Method : regroup adjacent grids containing high clouds AIRS :1 July 2007, AM Fill data gaps using PDF method Cb Ci thinci mid/low clr sky convective cores / thick Ci anvil / thin Ci εcld >0.98 / 0.5<εcld<0.98 / εcld<0.50 High cloud definition : Pcld - Ptropo<250 hpa Cb Ci thinci mid/low clr sky Cloud systems Spatial continuity constrains on cloud systems: adjacent high clouds ( 70% in 0.5 x 0.5 ) Pcld difference < 50 hpa AIRS-CIRS dataset IASI-CIRS dataset 4

5 Goal: relate anvil properties to convective strength Strategy: need proxies to identify convective cores cld > 0.98 to identify mature convective systems convective fraction: to describe the convective strength TminCb 5

6 Convective core definition Emissivity is a proxy for convective core, cirrus and thin cirrus definition Synergies : AMSR-E rain rate ERA-Interim vertical wind Convective cores : ε > 0.98 maximum rain rate sharply increases Vertical updraft has largest amplitude distinguish systems: with & without convection, count convective cores 6

7 Cloud system statistics Upper Tropospheric cloud systems cover about 20% of the latitude band ±30 : multi-core systems dominate 1-core ~2% No core ~5% Total HC coverage ~20% multicore ~13% Tropics (±30deg) HCA* [%] Core εcld >0.98 Multi-core single-core No core Systems count ~1% <4% ~95% coverage ~65% ~10% ~25% Average size [km2] ~200*104 ~10*104 ~104 Non-convective Ci : ~25% of high cloud cover 50% of isolated Ci originate from convection (Luo & Rossow 2004, Riihimaki et al. 2012) *HCA High (P-Ptropo <250 hpa) Cloud Amount 7

8 Proxy for maturity Machado & Rossow 1993 Formation Protopapadaki et al Cb size cld system size Maturity Tmin(Cb) rain rate Dissipation Dissipation of fragments use Cb fraction as proxy of maturity Cloud system composition depends on maturity phase: developing systems have higher convective fraction than dissipating systems to study convection depth, systems at same life stage need to be selected previous system tracking studies (Machado et al, 1998, Fiolleau and Roca, 2013) have shown that convective fraction is correlated with the life-cycle stage 8

9 Convective strength & system properties How do the anvil properties change with convective strength? Depending on available data, different convection characteristics can be explored: vertical updraft, Level of Neutral Buoyancy (LNB), Echo Top Hight (ETH), area of heavy rainfall, width of convective core, mass flux, cold cloud top: T B & Tcld mature systems with 1 conv. core colder (higher) cloud systems have a higher max RR & are larger land/ ocean quantitatively different in agreement with other analyses 9

10 Convective strength & anvil properties mature systems with 1 conv. core Colder convective systems larger horizontal extent and larger fraction of thin cirrus Protopapadaki et al 2017 Fraction (AIRS cloud systems) Takahashi et al, 2017 in preparation ETH 10 dbz (km) (CloudSat conv. core) collocation of AIRS and CloudSat convective systems (H. Takahashi, JPL) Comparison of different Convective Strength Proxies 10 (ETH & LNB) confirm relation

11 Heating rates of anvil parts Cirrus anvils might regulate convection as they stabilize the atmospheric column by their heating (Stephens et al. 2008, Lebsock et al. 2010) Heating affected by: areal coverage, εcld distribution, vertical structure of cirrus anvils Two Strategies for UT cloud systems heating rates estimation: a) compute heating rates using RRTM by categorizing: a) atmospheric situation (T & H2O profiles), b) cloud types b) sort FLXHR-LIDAR heating rates by cloud type (εcld & vertical structure from Calipso CloudSat, Feofilov et al. 2015) Takahashi et al

12 Summary & outlook Motivation: advance understanding on UT cloud system properties Work realized within the GEWEX UTCC PROES group Focus on tropical convective systems : cloud system approach anchored on IR sounder data : horizontal extent, convective cores/cirrus anvil/thin cirrus, maturity, using εcld, pcld observational metrics on anvil properties in relation to convective strength: fraction of thin cirrus within anvil increases with convective strength confirmed using proxies of convective strength from CloudSat systems to be investigated in CRM and in GCM simulations (under different parameterizations of convection/detrainment/microphysics) Next step: include heating rates of UT anvils in these studies 12