microphysical and radiative properties of ice clouds evaluation of the representation of clouds in...
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Microphysical and radiative properties of ice Microphysical and radiative properties of ice clouds clouds
Evaluation of the representation of clouds in Evaluation of the representation of clouds in modelsmodels
J. Delanoë and A. ProtatJ. Delanoë and A. Protat
IPSL / CETPIPSL / CETP
Assessment of the statistical representativenessAssessment of the statistical representativeness of the observationsof the observationsQuantification of the radiative importance of missed cloudsQuantification of the radiative importance of missed clouds
Statistics of ice crystal density / area versus crystal diameterStatistics of ice crystal density / area versus crystal diameter
Microphysical and radiative properties of ice clouds (2 years, Microphysical and radiative properties of ice clouds (2 years, interannual interannual
& intraseasonal variability, as a function of cloud height)& intraseasonal variability, as a function of cloud height)
Evaluation of NWP model representation of clouds Evaluation of NWP model representation of clouds (2 years, per season, and as a function of cloud height)(2 years, per season, and as a function of cloud height)
Outline :Outline :
Statistical representativeness Statistical representativeness of the CloudNet observationsof the CloudNet observations
Observations were not fully continuous over the three sites :Observations were not fully continuous over the three sites :Cabauw most continuous (commercial radar + operational lidar ceilometer) Cabauw most continuous (commercial radar + operational lidar ceilometer)
Chilbolton intermediate (commercial ceilometer but home-built radar Chilbolton intermediate (commercial ceilometer but home-built radar failures)failures)
Palaiseau least continuous (lidar + new home-built radar)Palaiseau least continuous (lidar + new home-built radar)
Instrumental effects Instrumental effects bias cloud parameters ? bias cloud parameters ?Lidar extinguished by low-level clouds. Ice clouds missedLidar extinguished by low-level clouds. Ice clouds missed
Lidar at SIRTA shut down when precipitation or drizzle threateningLidar at SIRTA shut down when precipitation or drizzle threateningRadar limited sensitivity. Thin ice clouds missedRadar limited sensitivity. Thin ice clouds missed
Model profiles over the two years used as referenceModel profiles over the two years used as reference
Partial temporal sampling : sub-sampling of this dataset at radar, lidar, Partial temporal sampling : sub-sampling of this dataset at radar, lidar, coincident radar-lidar, and cumulative radar-lidar hours of operations coincident radar-lidar, and cumulative radar-lidar hours of operations
Lidar : remove lidar hours of operation when real low-level clouds are Lidar : remove lidar hours of operation when real low-level clouds are observedobserved
Radar sensitivity : convert model IWCs into synthetic radar reflectivities. Radar sensitivity : convert model IWCs into synthetic radar reflectivities. Remove synthetic reflectivities below real sensitivityRemove synthetic reflectivities below real sensitivity
Radar or Lidar OK
Lidar OK
Radar~OK
Lidar OK
VerticalVerticalDistributionDistribution
Frequency of Frequency of occurrenceoccurrence Cloud FractionCloud Fraction
Statistical representativeness Statistical representativeness of the CloudNet observationsof the CloudNet observations
Optical depth of clouds Optical depth of clouds missed with -45 dBZ@1 kmmissed with -45 dBZ@1 km
Not negligible for the least sensitive radar : Not negligible for the least sensitive radar : = 0.05 is around 10 Wm= 0.05 is around 10 Wm-2-2 net radiative flux net radiative flux
Statistical representativeness Statistical representativeness of the CloudNet observationsof the CloudNet observations
Mean = 0.02Std = 0.06
Mean = 0.003Std = 0.011
Optical depth of clouds Optical depth of clouds missed with -55 dBZ@1 kmmissed with -55 dBZ@1 km
Cloud climatology from cloud radar Cloud climatology from cloud radar observations : Radar sensitivity issueobservations : Radar sensitivity issue
Palaiseau / Chilbolton radars : -45 dBZ mean sensitivity during CloudNet Palaiseau / Chilbolton radars : -45 dBZ mean sensitivity during CloudNet (from -55 dBZ to -35 dBZ, decaying 95 GHz tube)(from -55 dBZ to -35 dBZ, decaying 95 GHz tube)
Cabauw radar : -55 dBZ mean sensitivity (constant during CloudNet, 35 Cabauw radar : -55 dBZ mean sensitivity (constant during CloudNet, 35 GHz)GHz)
Impact on cloud climatology ?Impact on cloud climatology ?
In what follows Cabauw for climatology (+interannual+intraseasonal+cloud type) In what follows Cabauw for climatology (+interannual+intraseasonal+cloud type) Palaiseau+Chilbolton+Cabauw with degraded sensitivity for regional variabilityPalaiseau+Chilbolton+Cabauw with degraded sensitivity for regional variability
Statistics of Statistics of (D) / A(D) from RadOn(D) / A(D) from RadOn
From VT-Z relationship for each ice cloudFrom VT-Z relationship for each ice cloud most representative most representative (D) / (D) / A(D) A(D)
Statistics over the three CloudNet sites : very similar characteristicsStatistics over the three CloudNet sites : very similar characteristicsTwo main families : prinstine crystals (HC / HP) or Aggregates (BF 95)Two main families : prinstine crystals (HC / HP) or Aggregates (BF 95)
Statistics of Statistics of (D) / A(D) from RadOn(D) / A(D) from RadOn Function of cloud height and cloud thickness Function of cloud height and cloud thickness
3-8 km, 8-12 km classes : clouds whose thickest part is in this range (depth < 4 km)
Statistics of Statistics of (D) / A(D) from RadOn(D) / A(D) from RadOn
Parameterization of the density-diameter relationship as a function Parameterization of the density-diameter relationship as a function of the cloud macrophysical properties (temperature, Zof the cloud macrophysical properties (temperature, ZTOPTOP, thickness, , thickness,
combination ? )combination ? )Using 1 parameter :
Only cloud thickness shows a clear trend
a() = 0.002880 + 0.000371
b() = 0.124370 - 1.397455
a=(0.000770 - 0.001236) zT
+ (-0.004440 + 0.012798)b=(-0.000553 +0.051365) zT
+ (0.122159 - 1.763399)
Using 2 parameters :cloud thickness + zTOP
Validation : needs airborne in-situ density + radar obs. (Crystal-Face ?)
A cloud climatology from the RadOn documentationA cloud climatology from the RadOn documentation1- Macrophysical properties (global)1- Macrophysical properties (global)
Cabauw radar only for climatologyCabauw radar only for climatologyThe three radars (Cabauw degraded) for regional variabilityThe three radars (Cabauw degraded) for regional variability
Mean Cloud thickness
Mean Cloud mid-height Mean Cloud top height
Palaiseau / Chilbolton very similarCabauw : wider distribution (more low-level and thinner clouds, less 2 to 4 km thick clouds)
Regional Regional variabilityvariability
0-3km 3-8km >8km
Cabauw (degraded sensitivity) 18% 72% 10%
Chilbolton 4% 84% 12%
Palaiseau 8% 86% 6%
A cloud climatology from the RadOn documentationA cloud climatology from the RadOn documentation1- Macrophysical properties1- Macrophysical properties
(Interannual / intraseasonal variability)(Interannual / intraseasonal variability)
Interannual variability is found very small for all parametersInterannual variability is found very small for all parameters
0-3km 3-8km > 8km
DJF 26 % 70% 4 %
MAM 20 % 71 % 9 %
JJA 4 % 60 % 36 %
SON 4 % 71 % 25 %
Cloud mid-height
Cloud top height
A cloud climatology from the RadOn A cloud climatology from the RadOn documentationdocumentation
2- Microphysical / radiative properties (global)2- Microphysical / radiative properties (global)ZTOP-Z
ZTOP-Z
ZTOP-Z
IWC
Re
IWC
Re VT
A cloud climatology from the RadOn A cloud climatology from the RadOn documentationdocumentation
2- Microphysical / radiative properties2- Microphysical / radiative properties(as a function of cloud height)(as a function of cloud height) 0-3 km, 3-8 km,
8-12 km classes :clouds whose
thickest part is in this height range(depth < 4 km)
Thick clouds : depth > 4 km
Result for IWC:Large variability
Same for and Re
A cloud climatology from the RadOn A cloud climatology from the RadOn documentationdocumentation
2- Microphysical / radiative properties2- Microphysical / radiative properties(Interannual / intraseasonal variability)(Interannual / intraseasonal variability)
IWC
IWC IWC
largest IWC / in autumn
smallest in spring (factor 2)
Evaluation of representation of cloudsEvaluation of representation of clouds in in NWP models NWP models from RadOn cloud statistics : global histogramsfrom RadOn cloud statistics : global histograms
ECMWF, RACMO (prognostic scheme) very good
MET-OFFICE (prognostic scheme) good shape overestimation
METEO-FRANCE (diagnostic scheme) changed scheme during CloudNet statistics mixes both
Evaluation of representation of cloudsEvaluation of representation of clouds in in NWP models NWP models from RadOn cloud statistics : skills for different cloud from RadOn cloud statistics : skills for different cloud
typestypes
Model skills are different for the different cloud types Low-level ice clouds : ECMWF best match, the other models too narrow and IWC
overestimateMidlevel ice clouds : Met-Office almost perfect. ECMWF / RACMO good structure,
negative biasHigh-altitude clouds : largest diffs between models. ECMWF best match, small IWCs too
small.RACMO : left part OK, distribution too narrow and significant underestimation of the
large IWCs. Met-Office and Meteo-France good histogram structure, but systematic positive bias.Thick clouds : Met-Office best match, slight shift towards larger IWCs. ECMWF and
RACMO do a reasonable job, but underestimation of the intermediate IWCs.
Evaluation of representation of cloudsEvaluation of representation of clouds in in NWP models NWP models from RadOn cloud statistics : skills at different seasonsfrom RadOn cloud statistics : skills at different seasons
No large seasonal difference in skills for all models. ECMWF / RACMO good agreement with the observations for all seasons.
Meteo-France has a too narrow distribution whatever the season Met-Office model is systematically shifted towards larger IWCs (less in winter).
Evaluation of representation of cloudsEvaluation of representation of clouds in in NWP models NWP models from RadOn cloud statistics : mean profilesfrom RadOn cloud statistics : mean profiles
ECMWF / RACMO reasonable job at Chilbolton and PalaiseauOnly RACMO OK for Cabauw. Representation of the smallest IWCs in ECMWF ?
Met-Office good vertical structure but overestimation throughout the troposphere.
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