Clouds and Convection

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Max-Planck-Institut Clouds and Convection Cathy Hohenegger, Axel Seifert, Bjorn Stevens, Verena Grützun, Thijs Heus, Linda Schlemmer, Malte Rieck

Max-Planck-Institut Shallow convection Deep convection 2

Why do we care of convective clouds? è Weather 3

Why do we care of convective clouds? è Weather è Damaging effects Hamburg main railway station, 06.06.2011 4

Why do we care of convective clouds? è Weather è Damaging effects è Abundant (S. Warren) 5

Why do we care of convective clouds? è Weather è Damaging effects è Abundant 35% (S. Warren) 6

Why do we care of convective clouds? è Weather è Damaging effects è Abundant è Key player in water and energy cycles: è modify radiation è transport heat, moisture and momentum è produce precipitation 7

But convection is hard to simulate Accumulated precipitation, 1 May 2010-30 Sept. 2010 (Axel Seifert) 8

But convection is hard to simulate Mean diurnal cycle, 28 June-14 July 2010 (Axel Seifert) 9

Issue 1: Clouds can be very small g/kg Cloud liquid water content 12 Local Time, 3 km height 10

Issue 1: Clouds can be very small g/kg Cloud liquid water content 12 Local Time, 3 km height Skamarock (2004) true resolution = 7Δx 11

Issue 1: Clouds can be very small Brute-force solution: increasing the horizontal resolution è Bryan et al. 2003 : deep convection, 100 m è Craig and Dörnbrack 2008 : buoyant thermal, O(10 m) è Matheou et al. 2011 : shallow convection, 20 m 2 Δx~10 m, Germany area: 357021 km, 3.6 billion points only in the horizontal. Still need some form of parameterization 12

Max-Planck-Institut Issue 2: Clouds are complex Pictures taken by Louise Nuijens 13

Issue 2: Clouds are complex è Because of large-scale forcing? è Pure luck? è Because of previous clouds? è Because of the land surface? 14

Scientific Goal Improve our understanding and modeling ability of shallow to deep convective clouds 15

Scientific Goal Improve our understanding and modeling ability of shallow to deep convective clouds è better understand the processes controlling the cloud size distribution, especially the role of local effects such as surface condition, inhomogeneities in the boundary layer, versus the large-scale flow è express the properties of individual clouds in form of joint probability density functions to formulate a spectral scale-adaptive convection scheme 16

Our main tool: large-eddy simulation (LES) è Solve the basic equations describing atmospheric motion è Resolution O(10-100m) in the horizontal, explicit convection è Domain size 20 km x 20 km x 20 km è Allow to document and investigate the cloud properties, life cycle and interactions with the environment è More detailed information than observations è Well-established and successful (GCSS) 17

Our main tool: large-eddy simulation (LES) (Malte Rieck) 18

Our main tool: large-eddy simulation (LES) (Dylan Dussel) 19

Our main tool: large-eddy simulation (LES) (Dylan Dussel) 20

Our main tool: large-eddy simulation (LES) (Dylan Dussel) 21

Our main tool: large-eddy simulation (LES) (Dylan Dussel) 22

Our main tool: large-eddy simulation (LES) (Dylan Dussel) 23

Our main tool: large-eddy simulation (LES) (Dylan Dussel) 24

Method Forecast bias Idealisation Large-eddy simulations OBS Process analysis: tracking Understanding Parameterization development Single column model and/or full model 25

Still difficulties in simulating convection, even with convection-permitting models Hans Ertel research group on clouds and convection http://www.mpimet.mpg.de/wissenschaft/atmosphaere-im-erdsystem/arbeitsgruppen/wolken-und-konvektiveprozesse.html 26