EUM CIMSS

The generation of Climate Data Records (CDRs) of Atmospheric Motion Vectors (AMVs) at EUMETSAT is within the framework of ERA-CLIM, to Prepare the observations for a 20th century reanalysis.

Geostationary (2004 – 2012): MSG-SEVIRI: EUMETSAT algorithm

Polar orbiting (2007 – 2013): AVHRR on Metop two algorithms: EUMETSAT algorithm CIMSS algorithm

Roger Huckle, Marie Doutriaux-Boucher, Alessio Lattanzio, and Joerg Schulz EUMETSAT, Eumetsat-Allee 1, 64295 Darmstadt, Germany; roger.huckle@eumetsat.int

Introduction The Algorithms

MSG – SEVIRI Once per hour Four images used Average of three

intermediate vectors NWP data for initial height

assignment (EBBT) Final height by CCC method Retrieval in four channels: VIS (0.8), WV (6.2 & 7.3), IR (10.8)

AVHRR – EUMETSAT Every orbit Two images used Reprojection on local grid. Final vector from backward

tracking Forward tracking only for QI NWP data for first guess &

initial height assignment (in every image)

Final height from CCC method.

AVHRR – CIMSS Every orbit Three images used Reprojection on common grid Average of two intermediate

vectors NWP data for first guess,

initial and final height assignment

Cloud base method for AMVs below 600 hPa

Polar – METOP-A/AVHRR Results

Change in height assignment and quality control

MET9 became operational

Change in height assignment CCC

Atmospheric Motion Vectors from EUMETSAT for the use in global reanalysis

Geostationary – MSG/SEVIRI Results

Creation of stable data record.

Discontinuities and gaps in the data record caused by satellite and algorithm changes are removed using the latest retrieval algorithm for the entire time.

The number of winds in the reprocessed data record are more smooth than before.

LATI

TUD

E

2004 2005 2006 2007 2008 2009 2010 2011

Hovmöller diagram for average speed from 2004 to 2011 (all heights).

Recurring annual variability in average speed distribution clearly visible in the northern subtropics.

Constantly high wind speeds (> 25m/s) over the southern oceans (roaring forties).

North Pole

South Pole

Average monthly speed per year from 2007 to 2012. Annual cycle similar every year and in both data records.

RIGHT: Height distribution of AMVs for one month. Dip in distribution of CIMSS AMVs below 600 hPa due to Cloud Base method. ABOVE: Correlated AMV speeds EUM & CIMSS. Good agreement but fast bias for EUM AMVs.

Conclusion

Climate Data Records for AMVs were generated at EUMETSAT from geostationary (SEVIRI onboard MSG) and polar satellites (AVHRR onboard METOP-A) - MSG AMVs (2004 – 2012) - AVHRR AMVs ( 2007 – 2013) (using two algorithms)

Removal of breaks and discontinuities in the data record caused by instrument and algorithm changes Gaps in the data record filled where possible Steady pattern and behaviour of MSG wind speeds Additional coverage of the northern and southern Jet Stream in EUMETSAT AVHRR AMV data record Similar annual cycle of wind speed for both AVHRR algorithms over North and South Pole Difference in height assignment between the two AVHRR algorithms with CIMSS shifting AMVs lower in the atmosphere. Fast bias for EUMETSAT AVHRR AMVs compared to radiosondes, CIMSS AMVs with slow bias Vector difference against radiosondes smaller for CIMSS AMVs than for EUMETSAT algorithm.

Data

Input AVHRR: AVHRR L1B BT channel 4 Cloud mask (EUM only)

IASI L2 sounding ERA-Interim forecast data Full 60 model layers for

EUMETSAT algorithm. Selected 13 pressure layers

for CIMSS algorithm.

Input MSG: SEVIRI L1.5 images Cloud Analysis product ERA-Interim forecast data

Full 60 model layers for EUMETSAT algorithm (reduced to 32)

Output AVHRR: Nearly 7 years of polar AMVs

from both algorithms Quality Indicator (QI) for each

AMV

Output MSG: 9 years of AMVs and other MSG

products. Quality Indicator (QI) for each

AMV

Validation: RAOBCORE – quality controlled

radiosondes [5] ERA-Interim Analysis (not

shown)

Shift of CIMSS AMVs

to lower altitudes due

to Cloud Base method

for height assignment

North Pole

South Pole

Polar AMVs from EUMETSAT and CIMSS AMVs collocated with RAOBCORE radiosondes:

Fast bias for EUM and slow bias for CIMSS AMVs.

Vector difference smaller for CIMSS than for EUM AMVs.

Comparison against Radiosondes

2007 2008 2009 2010 2011 2012

AMV vertical distribution (in hPa) for a three-months period from October to January 2010.

1050

875

700

525

350

175

0

Alti

tude (

hP

a)

Number of retrieved winds (QI>50) in

October 2009. The total number of winds

retrieved over the South pole is 738946.

Nu

mb

er o

f w

ind

s

Nu

mb

er o

f w

ind

s

Number of retrieved winds (QI>50) in

October 2009. The total number of winds

retrieved over the South pole is 796806.

Wind speed (QI>50)correlation for October

2010 over the South pole. The total number

of winds retrieved over the South pole is

1983499.