A multi-decadal review of CloudSat and CALIPSO
Fielding (ECMWF)
via monitoring against ERA5 Mark
Marta Janisková (ECMWF)
EarthCARE pre-launch science and validation workshop, ESA-ESRIN, 14 Nov 2023

+2 dB

2006
-2 dB

2007

CloudSat minus ERA5 12-hr mean (dB)

2008
2009
2010

2011
2012
2013

2014
2015
2016
© ECMWF December 6, 2023

2017
time

What is ERA5?
“ERA5 is the fifth generation ECMWF reanalysis for the global climate andweather for the past 8 decades. Data is available from 1940 onwards [to thepresent day]. ERA5 replaces the ERA-Interim reanalysis.”“Reanalysis combines model data with observations from across the world into
a globally complete and consistent dataset using the laws of physics…”“Reanalysis does not have the constraint of issuing timely forecasts, so
there is more time to collect observations, and when going further back in time,to allow for the ingestion of improved versions of the original observations,which all benefit the quality of the reanalysis product.”

Source: climate.copernicus.eu

Motivation• Assess the stability of CloudSat and CALIPSO observations anddemonstrate their potential for inclusion in future re-analyses.
• Demonstrate and test monitoring system in preparation forEarthCARE observations.
• Provide a ‘stepping stone’ for comparison of EarthCARE CPR radarreflectivity with CloudSat.
• Evaluate quality of CloudSat and CALIPSO data for assimilation
experiments in more recent observing systems.
• Investigate ERA5 biases in representation of clouds.

Monitoring CloudSat and CALIPSO against ERA5

• IFS ‘monitor-only’ experiment using CY48R1 re-initialised with ERA5model fields using the same horizontal resolution of TL399 spectraltruncation (corresponding to ~30 km on a reduced gaussian grid) and137 vertical levels:– Period: 1 June 2006 – 31 December 2017
• Observations of cloud radar reflectivity (at 94 GHz, CloudSat), cloudlidar backscatter (at 532 nm, CALIPSO) horizontally averaged to ERA5grid.

• Use same observation operator as assimilation (evolved from COSP,
now with ‘triple column’ approach*).

• Initial conditions are from ERA5 (CY41R2, operational in 2016), whilethe 12-hour forecast uses operational cycle (CY48R1).
*See Fielding and Janisková 2020, QJRMS

Daily mean bias (dB)Monitoring CloudSat and CALIPSO against ERA5 – mean bias
Battery anomaly

Daily mean bias (dB)

2006

2008

2010

Switch to 2nd laser

CloudSat radar reflectivity

Day-time only

Battery anomaly -> end ofnighttime operations

CALIPSO lidar backscatter

Change in pointing angle

Both CloudSat and CALIPSO are a long, stable record of clouds

2018Daily number of obs.

Monitoring CloudSat and CALIPSO against ERA5 – number of obs.
Battery anomaly

Daily number of obs.

2006

2008

2010

Switch to 2nd laser

CloudSat radar reflectivity

Day-time only

Battery anomaly -> end ofnighttime operations

CALIPSO lidar backscatter

Change in pointing angle

Both CloudSat and CALIPSO are a long, stable record of clouds

2018

Monitoring regional biases - CloudSat
ArcticDaily mean bias (dB)NH extra-tropics

Tropics

Seasonal cycle – modelbiases!

Tropics bias unchanged
throughout period

SH extra-tropics

Antarctic

7

EUROPEAN CENTRE FOR MEDIUM-RANGE WEATHER FORECASTS

2006

2018

Monitoring regional biases - CALIPSO
ArcticDaily mean bias (dB)

Seasonal cycle – modelbiases!

NH extra-tropics
TropicsTropics bias unchanged
throughout period

SH extra-tropics

Antarctic
8

EUROPEAN CENTRE FOR MEDIUM-RANGE WEATHER FORECASTS

2006

2018

Data requirements for reanalysis and data homogenization• Do the observations cover a significant period?
• Does impact justify additional cost?
• Do the observations have consistent data quality?
• Do the observations impact the mean state? Is bias correction appropriate
throughout?

Can we address CloudSat’s
reduction in sensitivity and loss ofnight-time operations?
CloudSat’s reduction in sensitivity
Stephens et al., 2018
EUROPEAN CENTRE FOR MEDIUM-RANGE WEATHER FORECASTS

9

1. Monitoring CloudSat’s sensitivity changeFirstpercentileof in-cloudmean Z…discard observations below – 24 dBZ
EUROPEAN CENTRE FOR MEDIUM-RANGE WEATHER FORECASTS

10

2. Day-time only operations

mean bias (dB)

2008

2012

std. dev. (dB)number ofobs.
EUROPEAN CENTRE FOR MEDIUM-RANGE WEATHER FORECASTS

11

Homogenizing the CloudSat dataset
Daily meanbias (dB)

Std. dev. (dB)

Number ofobs.
EUROPEAN CENTRE FOR MEDIUM-RANGE WEATHER FORECASTS

12

Homogenizing the CloudSat dataset – remove daylight obs.
Daily mean
bias (dB)

Std. dev. (dB)

Number ofobs.
EUROPEAN CENTRE FOR MEDIUM-RANGE WEATHER FORECASTS

13

Homogenizing the CloudSat dataset – adjust sensitivity
Daily mean
bias (dB)

Std. dev. (dB)

➢ Only 3% observations lost for 3 dB of sensitivity!
Number ofobs.
EUROPEAN CENTRE FOR MEDIUM-RANGE WEATHER FORECASTS

14

Model biases are waiting to be solved by EarthCARE!
ERA5 vs CALIPSOCY48R1 vs CERESTOA Longwave flux

Too littleoutgoingBackscatter bias - High clouds
Too much

Too little
backscatterdB

Too muchbackscatterToo muchoutgoing
TOA Shortwave flux

Backscatter bias - Low clouds
Too little
reflection

Too little
backscatterdB

Too muchreflection

Period: Dec. 2021 – Feb 2022

Too muchbackscatter

Period: Jan. 2009 – June 2011

Cold air outbreaks poorly represented – DJF 2010-2016 mean bias low clouds(p>700 hPa)
CloudSat vs ERA5CALIPSO vs ERA5
Too little
reflectivity

Too little
backscatterdBdB

Too muchreflectivity

Too muchbackscatter

Reanalyses need help too!
EUROPEAN CENTRE FOR MEDIUM-RANGE WEATHER FORECASTS

16Summary• CloudSat and CALIPSO data quality are enviable.
• Monitoring EarthCARE against ERA5 will allow indirect comparison
with CloudSat and CALIPSO.
• Datasets are suitable for inclusion in reanalyses – likely too late for
ERA6 (deadline < 6 months), further testing required on assimilation
impact.
• CloudSat, CALIPSO and EarthCARE earmarked for ERA7 (2030?).
• EarthCARE will be a catalyst for reducing model errors throughsynergistic active/passive approaches that target compensatingbiases.