cold cloud formation due to dust: operational prediction of ice … · cold cloud formation due to...
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Cold cloud formation due to dust: operational prediction of ice nuclei concentration
S. Nickovic1, B. Cvetkovic1, F. Madonna2, Marco Rosoldi2, G. Pejanovic1, and S. Petkovic1, J. Nikolic1
1Republic Hydrometeorological Service of Serbia (RHMSS), Belgrade, Serbia2Consiglio Nazionale delle Ricerche, Istituto di Metodologie per l’Analisi
Ambientale, Potenza, Italy
The Atmospheric Ice Nucleation Conference, 23-25 Jan 2017, Leeds, UK
Ice nucleation (IN) and Numerical weather Prediction (NWP)
Cold clouds – especially poorly described in NWP. Why? Since recently – not fully unclear which aerosol types are most
important for IN
Ice nucleation (IN) concentration prescribed as a constant or a climatology used
→ Missing sufficiently correct aerosol-cloud interactions in operational NWP models
climate models
Uses dust model climatology to parameterize IN
Thompson and Eidhammer (2014) dust frendly cloud physics scheme
‘Cooking’ cold clouds: our recipe
Nickovic et al, 2016, Atmos. Chem. Phys., 16, 11367–11378
DREAM modelNickovic et al 2011)
NCEP/NMM model
Dust C T, RH
INn
Thompson and Eidhammer (2014) dust-friendly cold cloud micrphysics
How much DREAM dust C is accurate?
Agia Marina (Cyprus) April 2016: DREAM dust C (upper) vs. Lidar depolarization ratio
What dust does to cold clouds??
Breakthrough in understanding the role of dust in IN process
• Cziczo et al., Science (2013)
Heterogeneous IN dominant (95%)
Dust in 2/3 ice crystals
Sampling done 1000-s km far from dust sources
Cziczo et al, 2013, Science
How to exploit this findings in NWP?
Routine prediction of ice nucleation: DREAM model
• DeMott (2015) за [-35oC <T<-5oC]
• Steinke et al (2015) за [-55oC <T<-35oC]
Дан РХМЗ, 27. септембар 2016.
TT
dustIN nCn16.27316.273
exp
%10051088.1
iceRHqpT
dustIN eSn
New IN parameterizations
IN concentration due to dust ( )in cloud schemes
• Typical today’s cloud schemes use:
or
climatology
INn
constnIN INn
Vertical distribution - Model #IN (color)vs.- MIRA55 Ice Cloud Water(black line)
May 2010 dust case - Potenza
0 2 4 6 8 10
0
1
2
3
4
5
R=0.83
1-14 May 2010 + 22-30 Sep. 2012
NL
IWP
Validating #IN parameterization
• Model runs: May 2010 and Sep 2012
Nickovic et al, 2016, Atmos. Chem. Phys., 16, 11367–11378
0 2 4 6 8 10
0
1
2
3
4
5
R=0.83
1-14 May 2010 + 22-30 Sep. 2012
NL
IWP
Model vs. Cloud radar/lidar Ice Water Content (IWC) observations (Potenza)
model dust load
model loadlog10(nIN)
MSGSEVIRI log10(IWP)
log10(nIN) /log10(IWP)overlaps
1 May
2 May
3 May
4 May
5 May
Model vs. MSG SEVIRI Ice Water Path(May 2010)
Daily #IN maps athttp://dream.ipb.ac.rs/ice_nucleation_forecast.html
NWP groups interested to use daily #IN DREAM forecasts will have it available through the WMO SDS-WAS dust project (ongoing action)
Practical benefits of predicting dust-IN
Solar power forecasting... Soret et al, 2016
Failure to predict cold clouds over Germany 4 April 2014, since no dust-IN effects are considered
DREAM-IN model rerun (left) and SEVIRI cloud phase observation (right)
4 April 2014
AVIATION
AirFrance 2009 accidentHypothesis on dust influence: dust-icenucleation
Thank you!