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The atmospheric hydrological cycle and climate feedbacks: recent advances Richard P. Allan Department of Meteorology, University of Reading Thanks to Brian.

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Presentation on theme: "The atmospheric hydrological cycle and climate feedbacks: recent advances Richard P. Allan Department of Meteorology, University of Reading Thanks to Brian."— Presentation transcript:

1 The atmospheric hydrological cycle and climate feedbacks: recent advances Richard P. Allan Department of Meteorology, University of Reading Thanks to Brian Soden and Viju John

2 Introduction Observational records and climate projections provide abundant evidence that freshwater resources are vulnerable and have the potential to be strongly impacted by climate change, with wide-ranging consequences for human societies and ecosystems. IPCC (2008) Climate Change and Water

3 Increased Precipitation More Intense Rainfall More droughts Wet regions get wetter, dry regions get drier? Regional projections?? Precipitation Change (%) Climate model projections (IPCC 2007) Precipitation Intensity Dry Days

4 Range of cloud feedback Uncertainty in strength of cloud feedback Water vapour and T- lapse rate ALLCloud Surface reflection Total range Strength of Feedback (Wm -2 / o C) Hawkins and Sutton (2010) Clim. Dyn.See IPCC (2007)

5 How should the water cycle respond to climate change? See discussion in: Allen & Ingram (2002) Nature; Trenberth et al. (2003) BAMS Hawkins and Sutton (2010) Clim. Dyn.

6 Allen and Ingram (2002) Nature How should the water cycle respond to climate change? 7%/K 3%/K

7 NCAS-Climate Talk 15 th January 2010 Trenberth et al. (2009) BAMS Physical basis: energy balance

8 NCAS-Climate Talk 15 th January 2010 Radiative cooling, clear (Wm -2 K -1 ) Models simulate robust response of clear-sky radiation to warming (~2 Wm -2 K -1 ) and a resulting increase in precipitation to balance (~2 %K -1 ) e.g. Allen and Ingram (2002) Nature, Stephens & Ellis (2008) J. Clim Allan (2009) J. Clim

9 NCAS-Climate Talk 15 th January 2010 CCWindT s -T o RH o Muted Evaporation changes in models are explained by small changes in Boundary Layer: 1) declining wind stress 2) reduced surface temperature lapse rate (T s -T o ) 3) increased surface relative humidity (RH o ) Richter and Xie (2008) JGR Evaporation

10 Current changes in tropical ocean column water vapour Low level water vapour strongly constrained by Clausius Clapeyron relationship (~7%/K) Changing observing systems applied to reanalyses cause spurious variability (e.g. ERA Interim) John et al. (2009) models Water Vapour (mm)

11 Physical basis: water vapour Clausius-Clapeyron –Low-level water vapour (~7%/K) –Intensification of rainfall –Moisture transport –Enhanced P-E patterns See Held and Soden (2006) J Clim

12 Extreme Precipitation Physical basis: water vapour Low-level moisture rises with warming at ~7%/K due to Clausius Clapeyron Large-scale rainfall fuelled by moisture convergence –e.g. Trenberth et al. (2003) BAMS Intensification of rainfall Extra latent heating: –Offsets some of extra condensation /stabilises atmosphere? (OGorman and Schneider, 2009 PNAS) –Invigorates storms? (Lenderink and van Meijgaard (2010) Environ. Res. Lett)

13 Contrasting precipitation response expected Precipitation Heavy rain follows moisture (~7%/K) Mean Precipitation linked to radiation balance (~3%/K) Light Precipitation (-?%/K) Temperature For discussion: Trenberth et al. (2003) Bull. Americ. Meteorol. Soc; Allen & Ingram (2002) Nature

14 Models ΔP [IPCC 2007 WGI] Is there a contrasting precipitation response in wet and dry regions? Rainy season: wetter Dry season: drier Chou et al. (2007) GRL Precip trends, 0-30 o N The Rich Get Richer?

15 First argument: P ~ Mq. So if P constrained to rise more slowly than q, this implies reduced M P~Mq Consequences: Circulation response

16 First argument: P ~ Mq. So if P constrained to rise more slowly than q, this implies reduced M Second argument: ω=Q/σ. Subsidence (ω) induced by radiative cooling (Q) but the magnitude of ω depends on (Г d -Г) or static stability (σ). If Г follows MALR increased σ. This offsets Q effect on ω. See Held & Soden (2006) and Zelinka & Hartmann (2010) JGR P~Mq Consequences: Circulation response

17 Models/observations achieve muted precipitation response by reducing strength of Walker circulation. Vecchi et al. (2006) Nature P~Mq Consequences: Circulation response

18 Precip. (%) Allan and Soden (2008) Science Can we use observations to seek/confirm robust responses?

19 Tropical ocean precipitation dP/dSST: GPCP:10%/K ( ) AMIP:3-11 %/K ( ) dP/dt trend GPCP: 1%/dec ( ) AMIP: %/dec ( ) (land+ocean) SSM/I GPCP Allan et al. (2010) Environ. Res. Lett.

20 Zhang et al Nature Detection of zonal trends over land

21 Contrasting precipitation response in wet and dry regions of the tropical circulation Allan and Soden (2007); Allan et al. (2010) Environ. Res. Lett. descent ascent ModelsObservations Precipitation change (%) Sensitivity to reanalysis dataset used to define wet/dry regions

22 Contrasting wet/dry precipitation responses Large uncertainty in magnitude of change: satellite datasets and models & time period TRMM GPCP Ascent Region Precipitation (mm/day) John et al. (2009) GRL Robust response: wet regions become wetter at the expense of dry regions. Is this an artefact of the reanalyses?

23 Current trends in 30% wettest, 70% driest regions of tropical oceans Wet/dry trends remain – GPCP record may be suspect for dry region –SSM/I dry region record: inhomogeneity 2000/01? GPCP trends –Wet: 1.8%/decade –Dry: -2.6%/decade –Upper range of model trend magnitudes Models DRY WET Allan et al. (2010) Environ. Res. Lett.

24 Analyse daily rainfall over tropical oceans –SSM/I v6 satellite data, (F08/11/13) –Climate model data (AMIP experiments) Create rainfall frequency distributions Calculate changes in the frequency of events in each intensity bin Does frequency of most intense rainfall rise with atmospheric warming? Precipitation Extremes Can we seek robust responses in precipitation extremes using satellite observations? METHOD

25 Increases in the frequency of the heaviest rainfall with warming: daily data from models and microwave satellite data (SSM/I) Reduced frequencyIncreased frequency Allan and Soden (2008) Science; Allan et al. (2010) Environ. Res. Lett.

26 Increase in intense rainfall with tropical ocean warming (close to Clausius Clapeyron) SSM/I satellite observations at upper range of model range Turner and Slingo (2009) ASL: dependence on convection scheme? Observational evidence of changes in intensity/duration (Zolina et al GRL) Links to physical mechanisms/relationships required (Haerter et al GRL)

27 Yu and Weller (2007) BAMS (Wentz et al. 2007, Science) Are models underestimating current precipitation/evaporation responses?

28 Could decadal fluctuations in atmospheric circulation be influencing current water cycle response? –Sohn and Park (2010) JGR Walker circulation index (top) and sea level pressure anomalies (bottom) over equatorial Pacific ( ) Hadley circulation index over 15 o S-30 o N band

29 Could changes in aerosol influence decadal changes in the hydrological cycle? e.g. Wild et al. (2008) GRL Wielicki et al. (2002) Science; Wong et al. (2006) J. Clim; Loeb et al. (2007) J. Clim Mishchenko et al. (2007) Science

30 Andrews et al. (2009) J Climate Is water cycle response sensitive to nature of radiative forcing?

31 How does the water cycle respond to ramp-down in CO 2 ? CO 2 forcing experiments Initial precip response supressed by CO 2 forcing Stronger response after CO 2 rampdown HadCM3: Wu et al. (2010) GRL CMIP3 coupled model ensemble mean: Andrews et al. (2010) Environ. Res. Lett. Degree of hysteresis determined by forcing related fast responses and linked to ocean heat uptake

32 Forcing related fast responses Andrews et al. (2010) GRL Total Slow Surface/Atmospheric forcing determines fast adjustment of precipitation Robust slow response to T Mechanisms described in Dong et al. (2009) J. Clim CO 2 physiological effect potentially substantial (Andrews et al Clim. Dyn.; Dong et al J. Clim) Hydrological Forcing: HF=kdT-dAA-dSH (Ming et al GRL; also Andrews et al GRL) Precipitation response (%/K)

33 One of the largest challenges remains improving predictability of regional changes in the water cycle… Changes in circulation systems are crucial to regional changes in water resources and risk yet predictability is poor. How will catchment-scale runoff and crucial local impacts and risk respond to warming? What are the important land-surface and ocean-atmosphere feedbacks which determine the response?

34 Future work: Binning precipitation by regime Vertical motion (ω) %iles ascent descent Coldest Warmest Precipitation (mm/day) Warm convective Sub tropics * * - mid-latitudes

35 Regime-dependent responses (a) P (mm/day); % area (b) Model–GPCP P (%) (c) – P (%/K); (d) ω Vertical motion (ω) percentiles ascent descent Models overestimate drizzle in tropics Robust increases in precipitation for mid/high latitudes & convective tropics Less rainfall in dry tropics. Reduced circulation.

36 Global mean precipitation –Controlled by energy balance (~2-3%/K) –Water vapour and clear-sky radiative cooling Intense rainfall –Low-level moisture rises fuel intensification of rainfall (~7%/K) Wet/dry region responses –Contrasting wet/dry region responses (wet get wetter) –Moisture transport & water vapour/energy balance constraints Outstanding Issues –Regional responses –Aerosol and decadal variability –Links to Cloud Feedback –Observing System –Transient responses: fast adjustment to forcing Conclusions

37 Extra Slides

38 A=0.4(1-A)=0.6 dP w /dT=7%/KdP d /dT dP/dT=3%/K Assume wet region follows Clausius Clapeyron (7%/K) and mean precip follows radiation constraint (~3%/K) P w =6 mm/dayP d =1 mm/day P=3 mm/day WetDry A is the wet region fractional area P is precipitation T is temperature

39 A=0.4(1-A)=0.6 dP w /dT=7%/KdP d /dT dP/dT=3%/K Assume wet region follows Clausius Clapeyron (7%/K) and mean precip follows radiation constraint (~3%/K) dP / dT = A( dP w / dT )+(1-A)( dP d / dT ) dP d = (dP-AdP w )/(1-A) P w =6 mm/dayP d =1 mm/day P=3 mm/day WetDry APwPw PdPd dP d /dTs (mm/day/K) (%/K) A is the wet region fractional area P is precipitation T is temperature

40 Trends in clear-sky radiation in coupled models Clear-sky shortwave absorptionSurface net clear-sky longwave Allan (2009) J. Clim

41 Surface net longwave and water vapour Allan (2009) J. Climate ERA40 NCEP SRB SSM/I Surface net longwave strongly dependent on column water vapour (CWV) Increased water vapour enhances ability of atmosphere to cool to the surface Extra clear-sky cooling acts to reduce stability and enhance precipitation

42 Precipitation in the Europe- Atlantic region (summer) Dependence on NAO

43 Physical Basis: Moisture Transport Change in Moisture Transport, dF (pg/day) If the flow field remains relatively constant, the moisture transport scales with low-level moisture. Model simulation scaling Held and Soden (2006) J Climate

44 Projected (top) and estimated (bottom) changes in Precipitation minus Evaporation Δ(P-E) Held and Soden (2006) J Climate ~

45 Sample grid boxes: –30% wettest –70% driest Do wet/dry trends remain? Avoid reanalyses in defining wet/dry regions Allan et al. (2010) Environ. Res. Lett.


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