Comparing the atmospheric boundary layer in a high-resolution model with ground-based observations: a detailed look at boundary layer clouds T. Marke, V. Schemann, U. Löhnert, J. H. Schween and Claudia Acquistapace Institute for Geophysics and Meteorology University of Cologne
24.05.2018 ISARS Conference, Cologne, Germany
Content • Motivation for this study • Research questions • Methodology • Results: • Representation of clouds • Cloud thermodynamics • PBL dynamics
• Conclusions and future work
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Some facts about boundary layer clouds in a changing climate
• Dufresne and Bony, (2008): The representation of low level clouds in climate models is a major contribution to uncertainties in prediction of future climate.
• Quaas et al, (2009): The net response of PBL clouds to changes of aerosols or greenhouse gases contributes greatly and on very short time scales to the net radiative response of the atmospheric column. 2
THE ICOsahedral Non hydrostatic atmospheric (ICON) model ICON has three main versions: 1) ICON – CLIMATE
Max-Planck Institute for Meteorology (MPI-M) Hamburg, Germany
2) ICON – NWP
German Weather Service (DWD) Offenbach, Germany
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3) ICON Large Eddy Model (LEM)
What's special about ICON-LEM? - Domain size and topography - LES type simulation (resolutions of 625, 312, 156 m), no convection parameterization, resolved clouds, 3D Smagorinsky turbulence) - Forcing with analysis NWP data (COSMO) - Open boundaries (instead of periodic boundary conditions) - 1 way nesting - Microphysics: 2 moments scheme from Seifert and Beheng (2006), for warm rain Seifert and Beheng (2001) (Heinze et al., 2017)
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Is it right?
Cloud water content from domain 3 (ICON), at 12:15
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Observations from cloud profiling supersites A cloud profiling supersite is a station equipped with at least • a microwave radiometer • a ceilometer • a cloud radar • ….
from Löhnert et al, 2015 (BAMS)
supersite observations characterize dynamical and thermodinamical processes in the planetary boundary layer (PBL)
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Research questions: 1.) Is ICON-LEM capable of reproducing the main low cloud features in the first place? 2.) Do any major biases exist? 3.) If so, which model physics or cloud-/precipitation processes can they be attributed to?
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Method: matching with correlation in time
OBS HITS
ICON 8
Method: matching with correlation in time
OBS MISSES
ICON 8
Method: matching with correlation in time
OBS CORRECT NEGATIVES
ICON 8
Method: matching with correlation in time
OBS FALSE ALARMS
ICON 8
How does it perform at a glance?
17,3%
Correct negatives
44,6%
25,2%
hits
misses
12,9%
False alarms
61,9% Well forecasted 9
Cloud properties for hits
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How does it perform at a glance?
17,3%
Correct negatives
44,6%
25,2%
hits
misses
12,9%
False alarms
38,1% Something went wrong
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Cloud properties for misses and false alarms • It misses typical PBL clouds • “Fake clouds” (false alarms) are thin, very high and with small LWP values 12
What’s the physics behind these misclassification? ---> a look at convective condensation level (CCL)
1. The model shows a pretty good agreement for Tccl with radiosondes. 2. The surface temperatures is approximately equal to Tccl from 9.00 to 15.00 13
On CCL height and clouds
CCL height determined from radiosondes corresponds to the height where clouds are found in the observations 14
On CCL height and clouds
The z_ccl calculated from ICON fits to the radiosondes, except some spikes at noon 15
On CCL height and clouds
1. most of the hits are the clouds coupled to the PBL thermodynamics 2. the majority of the false alarms occurs after 14h, and have cloud base much higher than the z_ccl.
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On CCL height and clouds
1) clouds are missed between 8:00 and 10:00 and in the spikes region 2) the presence of a cloud aloft at 2500 between 14.00 and 17.00, decoupled from the PBL is causing some falsely assigned hits.
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What about the dynamics? Variance of w PDFs • The interval with largest variances in w in ICON corresponds to the time interval in which most clouds are identified as HITS (9.00 to 15.00) • the lack of formation of clouds after 15.00 which we saw in the previous slide corresponds to a decrease of the variance of w in ICON between 15.00 and 18.00. 18
Conclusions • A method for comparing one-to-one ground-based observations and model output has been tested on one case study. • Good agreement among Zccl from radiosondes and ICON-LEM despite some rare spikes at noon. • Cloud formation does not appear to be strictly coupled to the thermodynamics described by Zccl • Clouds do not form as often as they should, especially: • in the early morning during the first PBL development • In occurrence of spikes of Zccl • after 15.00, when the variance of w decreases compared to observations. Contact:
[email protected]
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Backup slides
If we look at some statistics for PBL clouds:
comparing ground-based cloud fraction with the column output of ICON over JOYCE discrepancies in the PBL development appear.
IN all this work we use column output over the JOYCE supersite 7
Method: matching with correlation in time
t0 T0 - 7.5 min
T0 + 7.5 min
What about the dynamics? Shear of H wind
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Skills score parameters 44,6%
17,3%
Correct negatives
25,2%
hits
61,9% Good forecasted
misses
12,9%
False alarms
POD = 0.64 FAR = 0.22 BIAS = 0.82 ACC = 0.62 POFD = 0.43
38,1% Something went wrong 10
