Buoyancy driven turbulence in the atmosphere Stephan de Roode (TU Delft) Applied Physics Department Clouds, Climate and Air Quality s.r.deroode@tudelft.nl 1 Clouds, Climate and Air Quality Harm Jonker, Pier Siebesma and Stephan de Roode cloud-climate feedback detailed numerical simulation N2O atmospheric boundary layer in the laboratory Multi-Scale Physics CH4 new methods for measuring emission rates Faculty of Applied Sciences Length scales in the atmosphere Earth 103 km ~1mm-100mm Landsat 60 km 65km ~mm LES 10 km ~100m 3 courtesy: Harm Jonker Global mean turbulent heat fluxes 4 source: Ruddiman, 2000 No single model can encompass all relevant processes mm 10 m 100 m 1 km Cloud microphysics turbulence Cumulus clouds DNS 10 km 100 km 1000 km Cumulonimbus Mesoscale Extratropical clouds Convective systems Cyclones 10000 km Planetary waves Large Eddy Simulation (LES) Model Cloud System Resolving Model (CSRM) Numerical Weather Prediction (NWP) Model Global Climate Model 5 DALES: Dutch Atmospheric Large-Eddy Simulation Model Dry LES code (prognostic subgrid TKE, stability dependent length scale) Frans Nieuwstadt (KNMI) and R. A. Brost (NOAA/NCAR, USA) Radiation and moist thermodynamics Hans Cuijpers and Peter Duynkerke (KNMI/TU Delft, Utrecht University) Parallellisation and Poisson solver Matthieu Pourquie and Bendiks Jan Boersma (TU Delft) Drizzle Margreet Van Zanten and Pier Siebesma (UCLA/KNMI) Atmospheric Chemistry Jordi Vila (Wageningen University) Land-surface interaction, advection schemes Chiel van Heerwaarden (Wageningen University) Particle dispersion, numerics Thijs Heus and Harm Jonker (TU Delft) Contents Governing equations & static stability Observations, large-eddy simulations and parameterizations: - Clear convection - Latent heat release & shallow cumulus - Longwave radiative cooling & stratocumulus 7 measured vertical temperature profile Static stability Q: what will happen with the air parcel if it is vertically displaced? z Temperature 8 First law of thermodynamics: Conservation of energy dq added heat 1 c vdT pd internal energy work cv = specific heat of dry air at constant volume (718 J kg-1K-1 at 0 oC) T = temperature p = air pressure = air density 9 Equation of state for dry air: gas law p R d T Combine gas law and energy conservation dp dq c pdT cp = specific heat of dry air at constant pressure (1005 J kg-1K-1 at 0 oC) Rd = gas constant for dry air (287 J kg-1K-1 ) 10 Hydrostatic equilibrium dp - g dz Gas law, energy conservation and hydrostatic equilibrium dq c pdT gdz Adiabatic process dq=0 dry adiabatic lapse rate dT g = - d -9.8 K/km dz cp 11 measured vertical temperature profile Atmospheric stability: dry air dry adiabatic lapse rate: –10K/km F z A dry air parcel, moved upwards, cools according to the dry adiabatic lapse rate. But now it is warmer than the environmental air, and experiences an upward force. unstable situation for dry air A dry air parcel, moved downwards, warms according to the dry adiabatic lapse rate. But now it is cooler than the environmental air, and experiences a downward force. F T 12 A dry air parcel, moved upwards, cools according to the dry adiabatic lapse rate. But now it is cooler than the environmental air, and experiences a downward force. F F Atmospheric stability: dry air A dry air parcel, moved downwards, warms according to the dry adiabatic lapse rate. But now it is warmer than the environmental air, and experiences an upward force. z stable situation for dry air dry adiabatic lapse rate: –10K/km measured environmental temperature profile unstable situation for dry air T 13 Harm Jonker's saline convective water tank Initial state: tank is filled with salt water Convection driven by a fresh water flux at the surface 14 Schematic by Daniel Abrahams Convective water tank 15 Movie by Phillia Lijdsman Adiabatic process dq=0 dry adiabatic lapse rate (2) dp dp dq c pdT c pdT RT 0 p R d / c p p(z) (z) = T(z) p 0 cst The potential temperature is the temperature if a parcel would be brought adiabatically to a reference pressure p0 16 Balloon observations at Cabauw during daytime 17 Q: what makes this case challlenging for modeling? LES results of a convective boundary layer: Buoyancy flux warm air going down g g w' v ' w'' v entrainment of warm air warm air going up w' w' w' g w' w' w' 2 p' 2 w' v ' w' 2 t v z z x j 2 18 Q: what is sign of the mean tendency for v? LES results Buoyancy flux and vertical velocity variance w' w' w' g w' w' w' 2 p' 2 w' v ' w' 2 t v z z x j 2 19 LES results of a convective boundary layer resolved TKE budget E g U V w' w' w' 1 w' p' w' v ' u' w' v' w' t v z z z z 20 LES results Humidity flux Flux-jump relation: w'q'T = -weDq Dq H q w' q' t z H w e + w ls t q w eDq w' q' z0 t H we and wls are of the order 1 cm s-1 21 Entrainment scaling Large-scale subsidence Entrainment atmospheric boundary layer w' v ' top w e D v Aw' v ' sfc we A w' v ' sfc D v , A 0.2 H w e + w ls t 22 Photograph: Adriaan Schuitmaker Conservation of energy: saturated case L vdq l heat released by condensation c vdT internal energy 1 pd work ql = liquid water content Lv = enthalpy of vaporization of water (2.5x106 J kg-1 at 0 oC) 23 For a moist adiabatic process, the liquid water static energy (sl) is a conserved variable cp T gz L v q l = sl constant sl meteorologists dT g L v dq l - s dz cp c p dz 24 Atmospheric stability: conditional instability measured environmental temperature profile F F z A dry air parcel, moved upwards, cools according to the dry adiabatic lapse rate. But now it is cooler than the environmental air, and experiences a downward force. A moist air parcel, moved upwards, cools according to the wet adiabatic lapse rate. But now it is warmer than the environmental air, and experiences an upward force. dry adiabatic lapse rate F wet adiabatic lapse rate T 25 Atmospheric stability: conditional instability stable for dry and moist air stable for dry air z possibly unstable for moist air T 26 Q: why possibly unstable for moist air? Convective transport in Shallow Cumulus: Characteristics Courtesy Bjorn Stevens LES Heus TU Delft 27 28 Shallow cumulus movie by Thijs Heus Stratocumulus 29 Longwave radiative flux (FL) profile in cloud F 1 , net L 8 K / hr ! ! ! t c z p Cloud top cooling! Turbulence in stratocumulus: LES results and observations Nighttime Daytime Standard transport parameterization approach: w K z w M ( ) u w S t z This unwanted situation can lead to: •Double counting of processes •Inconsistencies •Problems with transitions between different regimes: dry pbl shallow cu scu shallow cu shallow cu deep cu 32 How to estimate updraft fields and mass flux? The old working horse: Betts 1974 JAS Arakawa&Schubert 1974 JAS Tiedtke 1988 MWR Gregory & Rowntree 1990 MWR Kain & Fritsch 1990 JAS And many more…….. Entraining plume model: c (c ) for l , qt z 1 M M z 1 wc2 g v v b wc2 aB, B 2 z 0 M Plus boundary conditions at cloud base. Downgradient-diffusion models w' ' K z K c l E1/ 2 E U U g u' w' v' w' w' ' w' E' w' p' / v t z z v z 34 Downgradient-diffusion models E U U g u' w' v' w' w' ' w' E' w' p' / v t z z v z 2 2 U U U V 2 u' w' v' w' K K S m m z z z z g g v w' v ' K H K H N 2 v v z E 3/2 cd l l c m,h E w' E' w' p' / 2K m z z E 1/ 2 N for stable stratification 35 Analytical solutions for stable stratifications see Baas et al. (2008) Stable boundary layer solutions 36 Turbulence and clouds: do we care? 37 Climate Model Sensistivity estimates of GCM’s participating in IPCC AR4 Source: IPCC Chapter 8 2007 • Spread in climate sensitivity: concern for many aspects of climate change research, assesment of climate extremes, design of mitigation scenarios. What is the origin of this spread? Radiative Forcing, Climate feedbacks, Relative Contributions to the uncertainty in climate feedbacks Cloud feedback Surface albedo feedback Water vapor feedback Radiative effects only Source: Dufresne & Bony, Journal of Climate 2008 Uncertainty in climate sensitivity mainly due to (low) cloud feedbacks