Historical and Future Changes of Tropical Rain Belts: Cloud and - PowerPoint PPT Presentation

Historical and Future Changes of Tropical Rain Belts: Cloud and Aerosol Processes Hui Su Chengxing Zhai 1 , Jonathan H. Jiang 1 , Longtao Wu 1 , J. David Neelin 2 , Yuk L. Yung 3 1 Jet Propulsion Laboratory, California Institute of Technology 2 University of California, Los Angeles 3 California Institute of Technology WCRP Grand Challenge 2 nd Meeting on Monsoons and Tropical Rain Belts July 2-5, Trieste, Italy

Ou Outline • Atmospheric energy constraint on global-mean precipitation • Moist static energy (MSE) framework for tropical circulation • Observations of tropical rain belt change

At Atmospheric Energy Constraint on Global-me mean Precipitation Allen and Ingram (2002, Nature) DeAngelis et al. (2015, Nature)

Cl Clear-sk sky Longwave Radiation Allan (2009, J. Clim) LW c here is clear-sky longwave radiative cooling

In Inter-mo model Spread in Clear-sk sky Shortwave Abso sorption Pendergrass and Hartmann (2012, GRL) DeAngelis et al. (2015, Nature)

Ch Changes of Hadley Ci Circulation, Cl Cloud Radiative Effects and Pre Precipitation (Su et al., 2014, JGR) “The Wet Get Wetter, The Dry Get Drier” Multi-model-mean from 15 CMIP5 coupled models ∆ = 2074-2098 in “RCP4.5” – 1980-2004 in “historical run”

Tighteni ning ng of Tropi pical Asce cent and nd High h Cl Clouds uds Key to Preci cipi pitation n Cha Chang nge in n a Warm rmer r Cl Climate Enhanced Decrease of Intensification Expansion Tightening of atmospheric Narrowing Reduced cloud tropical high of dry and of ITCZ of hydrological Hadley ascent longwave warming effect clouds clear area cycle cooling Su et al. (2017, Nature Comm.)

IT ITCZ Narrowing Linked to High Cloud Reduction (a) (b) 1.5 a BCC_csm1.1 b BCC_csm1.1m 1 c CCCMA_canam4 Interannual tropical dCF/dT s (%/K) Centennial tropical dCF/dT s (%/K) 1.0 d CNRM_cm5 e CSIRO_access1.0 q r j f CSIRO_access1.3 i j 0.5 g CSIRO_mk3.6 p o h GFDL_cm3 c m 0 g i GFDL_esm2g l a c o v w j GISS_e2r e 0.0 m b k INM_cm4 n l u f r l IPSL_cm5a-lr v s h h t q n m IPSL_cm5a-mr -0.5 p t n IPSL_cm5b-lr -1 e u o MIROC_esm s w g b p MIROC_miroc5 k -1.0 q MPI_esm-lr f a r MPI_esm-mr d s MRI_cgcm3 -1.5 -2 t NCAR_cam5 correlation = 0.51 correlation = 0.65 u NCAR_ccsm4 v NCC_noresm1-m -2.0 w MOHC_hadgem2-a -4 -3 -2 -1 0 1 -1.0 -0.5 0.0 0.5 Interannual tropical dF ω /dT s (%/K) Centennial tropical dF ω /dT s (%/K) Centennial Interannual Su et al. (2017, Nature Comm.)

Lo Longwave Effect of High Cloud Reduction (a) (b) 5 4 a BCC_csm1.1 b BCC_csm1.1m Interannual tropical dOLR/dT s (W/m 2 /K) t Centennial tropical dOLR/dT s (W/m 2 /K) c CCCMA_canam4 a b d CNRM_cm5 3 CERES e CSIRO_access1.0 4 Terra ISCCP Aqua f CSIRO_access1.3 s T+A g CSIRO_mk3.6 f u h GFDL_cm3 2 n d w f i GFDL_esm2g p l 3 v k j GISS_e2r e n o b k INM_cm4 t r g qr h h w c 1 e u l IPSL_cm5a-lr m l m IPSL_cm5a-mr c v a 2 j n IPSL_cm5b-lr p q o m o MIROC_esm 0 p MIROC_miroc5 q MPI_esm-lr i r MPI_esm-mr 1 j s MRI_cgcm3 -1 g correlation = − 0.77 t NCAR_cam5 correlation = − 0.71 u NCAR_ccsm4 v NCC_noresm1-m 0 -2 w UKMO_hadgem2-a -2.5 -2.0 -1.5 -1.0 -0.5 0.0 0.5 1.0 0.0 -1.0 -0.5 0.0 0.5 1.0 Interannual tropical dCF/dT s (%/K) Centennial tropical dCF/dT s (%/K) Interannual Centennial Su et al. (2017, Nature Comm.)

Ob Observational Constraint on Hydrological Sensitivity (a) (b) 3.0 3.0 a BCC_csm1.1 Temperature mediated global L v dP/dTs (W/m 2 /K) b BCC_csm1.1m correlation = 0.68 correlation = 0.64 c CCCMA_canam4 Interannual global L v dP/dTs (W/m 2 /K) d CNRM_cm5 s 3 3 e CSIRO_access1.0 j s f CSIRO_access1.3 g CSIRO_mk3.6 m l h GFDL_cm3 2.5 2.5 i GFDL_esm2g b t u k b j GISS_e2r p u l 2 2 v k INM_cm4 n d k d fh l IPSL_cm5a-lr r r v n o m j a m IPSL_cm5a-mr a n IPSL_cm5b-lr q w t c o MIROC_esm 2.0 2.0 h f e p MIROC_miroc5 q 1 1 p q MPI_esm-lr w g e r MPI_esm-mr o s MRI_cgcm3 c t NCAR_cam5 OBS. u NCAR_ccsm4 v NCC_noresm1-m 0 0 1.5 1.5 w UKMO_hadgem2-a 0 0 2 2 4 4 6 6 0 0 1 1 2 2 3 3 Interannual tropical dOLR/dTs (W/m 2 /K) Interannual global L v dP/dTs (W/m 2 /K) • Observation-based Interannual dP/dT s : 2.1%/K to 3.0%/K • Observation-constrained hydrological sensitivity: 2.6%/K to 2.9%/K • The multi-model-mean of the 21 models is 2.6%/K Su et al. (2017, Nature Comm.)

Mo Moisture Static Energy Budget , ! " # + % ⋅ '# + (! ) * = ) - (/ + 0 + 1) 5 ! " 3 + % ⋅ '3 + (! ) 3 = − (/ − 8) 6 7 ; < ; < 9 = : − % ⋅ '> − ?@ ; > = = ∆/ BCD ≈ − 6 7 ∆/ "FGHI ≈ − 6 7 ∆(! ) 3 (! ) ∆3 5 5 Xie et al. (2015, Nature. Clim. Change) ∆/ BCD ∝ ∆(

Mo Moisture Static Energy Budget > Y = F + Z + [ = \ + [ 6 $ 7 + 8 + 9 ⋅ ; 7 + 8 + 36 < ℎ = ! "#$ ? @ ↑ − + 1 ↓ − + $ ↑ − / $ ↓ + / 1 ↑ − / 1 ↓ ) + ( + ) ↑ ) + (+ 1 ! "#$ = & + ( + ) = ( + $ 3(U, W, ?, X) = −Ω 1 (?) 3 4 OP+ = ⟨Ω 1 −6 < ℎ ⟩ D A B ≈ E F G HIJ / GM GMS ∆3 4 ∝ ∆! "#$

Ra Radiative Changes of Clouds and Water Vapor Voigt and Shaw (2015, Nature Geo.)

Global-Mean Precipitation Change per degree of Surface Warming (%/K) 3.5 3 2.5 2 1.5 1 0.5 0 ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' ' m 2 m r r r m 1 m 5 0 3 6 3 r 5 r r 5 4 m s - l m l l m - m . m e m . . m - - c - m 2 1 - s c 1 1 3 s s a b o m - 1 e _ s s k e - e - e 2 m s c c 5 a s a 5 r m - _ e C _ s s m _ _ _ s c r m 1 m i c 5 m s e e S m e c o U n C M L C s _ c m m c c _ D S _ e _ n e a M c c O R N _ _ c c O g R I _ _ I _ R _ s c F c A C G R C P B a a d c _ C N L L I A C R G _ _ _ I O M P C C _ ' S a ' A ' S C I L M C C O O ' N B C S P P R M h S N M ' ' N ' C R R C I I ' I ' _ P ' ' ' ' M ' ' O B C I I I S S ' ' C ' M C C C ' ' ' K U ' AMIP Historical RCP4.5 ITCZ Precipitation Change per degree of Surface Warming (%/K) 9 8 7 6 5 4 3 2 1 0 'BCC_csm1-1' 'BCC_csm1-1-m' 'BNU_esm' 'CCCMA_canesm2' 'CMCC_cm' 'CNRM_cm5' 'CSIRO_access1.0' 'CSIRO_access1.3' 'CSIRO_mk3.6' 'GFDL_cm3' 'GISS_e2-r' 'IPSL_cm5a-lr' 'IPSL_cm5a-mr' 'IPSL_cm5b-lr' 'MIROC_esm' 'MIROC_miroc5' 'MPI_esm-lr' 'MPI_esm-mr' 'NCAR_cam5' 'NCAR_ccsm4' 'NCC_noresm' 'UKMO_hadgem2-es' AMIP Historical RCP4.5

In Inter-mo model Spread of Circulation and Precipitation Changes 8.0 R = 0.78 7.2 6.4 (1/P up ) dP up /dT s (%K − 1 ) 5.6 4.8 4.0 3.2 2.4 1.6 AMIP Historical 0.8 RCP4.5 0.0 -6 -4 -2 0 2 4 6 8 (1/W up ) dW up /dT s (%K − 1 ) ∆" ∝ ∆$ %

En Energetic c Constraint of Tropical Circu culation Change 8.0 6.6 R = 0.74 5.2 (1/W up ) dW up /dT s (%K − 1 ) 3.8 2.4 1.0 -0.4 -1.8 -3.2 AMIP Historical -4.6 RCP4.5 -6.0 -10 -5 0 5 10 15 20 25 (1/F net ) dF net /dT s (%K − 1 ) ∆" # ∝ ∆% &'(

Lo Longwave Cloud Radiative Effect 8.0 R = − 0.52 6.6 5.2 (1/W up ) dW up /dT s (%K − 1 ) 3.8 2.4 1.0 -0.4 -1.8 -3.2 AMIP Historical -4.6 RCP4.5 -6.0 -10 -5 0 5 cld /dT s (%K − 1 ) (1/F net ) dOLR TOA • Less longwave loss at TOA leads to a stronger ascent

Cl Clear-sk sky Shortwave Abso sorption 8.0 6.6 R = 0.43 5.2 (1/W up ) dW up /dT s (%K − 1 ) 3.8 2.4 1.0 -0.4 -1.8 -3.2 AMIP Historical -4.6 RCP4.5 -6.0 0 2 4 6 8 10 12 14 clr /dT s (%K − 1 ) (1/F net ) dF SW • Greater clear-sky shortwave absorption leads to a stronger ascent

Th The Role of Absorbing Aerosols 15 14 R = 0.51 13 clr /dT s (%K − 1 ) 12 11 10 9 (1/F net ) dF SW 8 7 6 5 Historical 4 3 0.000 0.001 0.002 0.003 0.004 0.005 0.006 0.007 dABS aero /dT s (%K − 1 )

Ob Observed Narrow owing of the ITCZ Wodzicki and Rapp (2016, JGR)

Ob Observed Narrow owing of the ITCZ Su et al. (2018, in prep)

CM CMIP5 Simulations of the Narrowing Su et al. (2018, in prep)

Su Summary • The changes of the ITCZ intensity and area are strongly constrained by atmospheric energy budget. • Model diversity in the radiative effects of tropical high clouds and absorbing aerosols contributes significantly to the inter-model spread in the ITCZ intensity and area changes in the past decades. • Observational evidence of the narrowing of ITCZ is robust.