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.