Poster - SCOPE-CM

30 Y
Years off Land
L d Surface
S f
Albedo
Alb d
from
GEO
Satellites
1
2
3
2
A.Lattanzio
A
Lattanzio ,, J. Matthews
J Matthews ,, M. Takahashi
M Takahashi ,, K. Knapp
K Knapp
pp ,, J Sch l 1,,R. Roebeling
J. Schulz
R Roebelingg1,, R. Stoeckli
R Stoeckli4
1EUMETSAT, Darmstadt, Germany EUMETSAT, Darmstadt, Germany 2NOAA National Climate Data Center, Asheville, NC USA NOAA National Climate Data Center, Asheville, NC USA 3JMA, Meteorological Satellite Center, Tokyo, Japan JMA, Meteorological Satellite Center, Tokyo, Japan
4Federal Office of Meteorology and Climatology MeteoSwiss, Zürich, Switzerland
Federal Office of Meteorology and Climatology MeteoSwiss Zürich Switzerland
Corresponding author address: Alessio Lattanzio EUMETSAT Eumetsat Allee 1 64295 Darmstadt, Germany. E‐mail: [email protected]
Corresponding author address: Alessio Lattanzio, EUMETSAT, Eumetsat
1 64295 Darmstadt Germany E mail: alessio lattanzio@eumetsat int
Abstract
The Sustained and Coordinated Processingg of Environmental Satellite Data for Climate Monitoringg ((SCOPE‐CM)) ‐ Land surface Albedo from Geostationaryy Satellites ((LAGS)) p
project
j
is involvingg the
operational meteorological satellite agencies in Europe (EUMETSAT),
(EUMETSAT) in Japan (JMA: Japan Meteorological Agency) and in the USA (NOAA: National Oceanic and Atmospheric Administration).
Administration) The
project
j t started
t t d in
i January
J
2014 and
d aims
i att the
th generation
ti off a Land
L d Surface
S f
Alb d Climate
Albedo
Cli t Data
D t Record
R
d enclosing
l i almost
l
t 30 years starting
t ti in
i the
th early
l 1980s
1980 covering
i the
th ring
i off geostationary
t ti
satellites. The main issue addressed is the limitation in quality due to clouds not removed by the embedded cloud screening procedure. As also demonstrated in a study performed by
independent researchers,
researchers the loss of quality in the retrieval is quite significant over dark dense vegetated areas.
areas Two alternative strategies are followed to efficiently improve the cloud detection
and removal. The first strategy to screen out outlier values, relies on a post processing analysis of the albedo seasonal variation together with the usage of a priori information contained in a
background albedo map.
map The second strategy to apply a robust and reliable cloud mask during the retrieval taking advantage of the information contained in the measurements of the infrared
and
d visible
i ibl channels.
h
l The
Th second
d issue
i
addressed
dd
d in
i the
th project
j t concerns the
th consistency
it
off the
th ancillary
ill
i f
information
ti needed
d d for
f the
th atmospheric
t
h i correction
ti and
d off the
th input
i
t reflectance
fl t
d t for
data
f
all exploited
p
ggeostationaryy satellites. This p
poster p
presents the activities p
performed and the results obtained.
SCOPE CM
SCOPE-CM
The aim of SCOPE‐CM is the establishment of a sustained international network to produce Climate Data Records (CDR) from multi
multi‐agency
agency mission data in operational environment for climate
monitoring.
it i The
Th satellite‐based
t llit b d key
k climate
li t variables
i bl datasets
d t t aim
i att analysis
l i off climate
li t variability
i bilit and
d trends.
t d CDRs
CDR are defined
d fi d as a “time
“ti
series
i off measurements
t off sufficient
ffi i t length,
l th consistency,
it
and continuityy and can be divided into two classes: ((i)) Fundamental Climate Data Records ((FCDR),
), a homogenous
g
long‐term
g
dataset of radiances or brightness
g
temperatures
p
encompassing
p
g
different sensors and platforms with spatial and temporal overlap; and (ii) Thematic Climate Data Record (TCDR),
(TCDR) geophysical variables derived from the FCDRs,
FCDRs which can be understood as the
satellite
lli product
d
associated
i d with
i h a Global
Gl b l Climate
Cli
Ob
Observing
i System
S
(GCOS) Essential
i l Climate
Cli
Variable
i bl (ECV).
( C ) The
h sustained
i d and
d coordinated
di
d generation
i off FCDR
C
and
d TCDR
C
i the
is
h ultimate
li
objective of SCOPE
SCOPE‐CM.
CM.
This initiative is one component of an end‐to‐end
end to end system with the final objective of
climate monitoringg havingg the satellite observations represented
p
byy the World
Meteorological Organization (WMO) Integrated Global Observing System (WIGOS) at
one end
d and
d the
th CDR user community
it att the
th other
th end.
d The
Th currentt participants
ti i
t off the
th
network are operators
p
of meteorological
g
satellites namelyy the China Meteorological
g
Administration (CMA),
(CMA) the European Organization for the Exploitation of
M
Meteorological
l i l Satellites
S lli (EUMETSAT),
(EUMETSAT) the
h Japan
J
M
Meteorological
l i l Agency
A
(JMA) and
d the
h
National Oceanic and Atmospheric Administration (NOAA).
The SCOPE‐CM
SCOPE CM LAGS project (http://www.scope‐cm.org/projects/scm‐03/)
(http://www scope cm org/projects/scm 03/) is devoted to the retrieval of land surface albedo from satellites in geostationary orbit [2].
[2] The retrieval scheme,
scheme based
on a method
h d proposed
d by
b Pinty et all [3],
[ ] simultaneously
l
l estimates aerosoll opticall depth
d h and
d surface
f
albedo
lb d and
d provides
d an uncertainly
l estimation for
f each
h pixell [4],
[ ] important for
f climate
l
analysis . The SCOPE
SCOPE‐CM
CM IOGEO project (http://www.scope
(http://www scope‐cm
cm.org/projects/scm
org/projects/scm‐06/)
06/) that will provide inter
inter‐satellite
satellite calibrated VIS,IR,
VIS IR WV radiances to serve as consistent input for reanalysis.
reanalysis
GEO Ring Temporal and Spatial Coverage
Earth spatial coverage with a ring of geostationary satellites (upper panel) . Potential
temporal coverage of the SCOPE‐CM
SCOPE CM CDR (middle panel).
panel) Proof of concept of albedo
composite
p
from GEO (0.3‐3.0 
m)) and comparison
p
with MCD43C3 (at least 75% of the
albedo values from full inversion and a maximum of 25% information is used
from an archetypal
yp BRDF database for a pperiod in Mayy 2001 ((right
g p
panel).
)
M t
Meteosat
t Dataset
D t
t Validation
V lid ti
I
Improved
d Cloud
Cl d Screening
S
i
Essential is the validation of the full CDR involving independent experts.
experts EUMETSAT conducted
such a validation studyy for the Meteosat First Generation land surface albedo CDR [3].
A simple cloud mask based on the generation of a background reflectance map and a more
sophisticated
p
cloud mask ggenerated at CM SAF have been used to check the impact
p on the p
pixel
based albedo retrieval.
retrieval Common to both methods is the fact that they can be applied to all past
and
d currentt GEO satellites
t llit similar
i il to
t Meteosat
M t
t First
Fi t Generation
G
ti (MSG,GOES,
(MSG GOES GMS,MTSAT).
GMS MTSAT)
CMSAF CM
NO CM
BCK CM
BCK CM
CMSAF CM
CMSAF
CM
NO CM
BCK CM
The validation
Th
lid ti
f
focused
d on temporal
t
l
consistencyy ((upper
pp p
plots),
), comparison
p
with in‐situ measurements (middle
plots)
l ) and
d with
i h other
h satellite
lli based
b d
retrievals (bottom plot). The study
confirmed the quality and the value of
the CDR and also some issues to be
further evaluated and solved (cloud
contamination,
t i ti
aerosoll LUT boundary
b
d
effect,, topographic
p g p effects).
)
The effect of clouds, as expected, is negligible on desert area. On rain forest regions sensed
under low VZA the impact is to increase the number of retrievals (left panel).
panel) In a similar
region in South
So th America sensed under
nder high VZA the effect is opposite (right panel),
panel) leading
to a decrease of retrieved p
pixels with an efficient removal of unrealisticallyy high
g albedo
values caused by cloud contamination.
contamination The usage of a background albedo climatology value
or off the
th analysis
l i off seasonall variations
i ti
t screen outt clouds
to
l d after
ft retrieval
t i l are still
till under
d
investigation.
S
Summary
 SCOPE‐CM
SCOPE CM is a framework established by the WMO in order to generate CDRs. The main
actors are satellite data providers.
providers The second phase of the framework started middle 2014
with 10 p
projects
j
(http://www.scope‐cm.org/);
p //
p
g/
 Th
The SCOPE‐CM
SCOPE CM project
j t on land
l d surface
f
albedo
lb d retrieval
t i l from
f
geostationary
t ti
satellites
t llit has
h
successfully implemented retrieval software at EUMETSAT, NOAA and JMA;
 Qualityy analysis
y byy independent
p
scientists has shown that amongg other things
g residual
undetected clouds are an issue for product quality;
 The positive impact of a new cloud mask applicable to all historic and current geostationary
satellites on the quality of the retrieval has been shown;
R f
References
[[1 ]]National Research Council ((NRC),
), 2004: Climate data records from Environmental Satellites,, National Academies
P
Press,
W hi t DC,
Washington
DC 150 pp.
[2] Lattanzio, A. et al., Land Surface Albedo from Geostationaryy Satellites: a multi‐agency
g y collaboration within
SCOPE CM Bull.
SCOPE‐CM,
Bull Amer.
Amer Meteor.
Meteor Soc.,
Soc 94,
94 205–214,
205 214 doi:175/BAMS‐D‐11‐00230.1,
doi:175/BAMS D 11 00230 1 2013.
2013
[3] Pinty, B. et al.,2000a: Surface albedo retrieval from Meteosat: Part 1: Theory, Journal of Geophysical Research,
105 18099‐18112.
105,
18099‐18112
[4] Govaerts Y.M., Lattanzio A., 2007: Retrieval error estimation of surface albedo derived from geostationary large
band satellite observations: Application to Meteosat
Meteosat‐2
2 and ‐7
7 data.
data Journal of Geophysical
Research,
h 112, D05102, doi:10.1029/2006JD007313.
d
/
[[5]] Fell,, F. Et al.,, G.,, 2012: Evaluation of the Meteosat Surface Albedo Climate Data Record ((ALBEDOVAL),
), Final Report,
p , 119 p
pages.
g
A il bl at http://www.eumetsat.int/website/home/Data/ClimateService/index.html
Available
h //
i / b i /h
/D /Cli
S i /i d h l