 |
| Titel |
Total column water vapour measurements from GOME-2 MetOp-A and MetOp-B |
| VerfasserIn |
M. Grossi, P. Valks, D. Loyola, B. Aberle, S. Slijkhuis, T. Wagner, S. Beirle, R. Lang |
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| ISSN |
1867-1381
|
| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Measurement Techniques ; 8, no. 3 ; Nr. 8, no. 3 (2015-03-05), S.1111-1133 |
| Datensatznummer |
250116204
|
| Publikation (Nr.) |
 copernicus.org/amt-8-1111-2015.pdf |
|
|
|
|
|
| Zusammenfassung |
| Knowledge of the total column water vapour (TCWV) global distribution is
fundamental for climate analysis and weather monitoring. In this work, we
present the retrieval algorithm used to derive the operational TCWV from the
GOME-2 sensors aboard EUMETSAT's MetOp-A and MetOp-B satellites and perform
an extensive inter-comparison in order to evaluate their consistency and
temporal stability. For the analysis, the GOME-2 data sets are generated by
DLR in the framework of the EUMETSAT O3M-SAF project using the GOME Data
Processor (GDP) version 4.7. The retrieval algorithm is based on a classical
Differential Optical Absorption Spectroscopy (DOAS) method and combines a
H2O and O2 retrieval for the computation of the trace gas vertical
column density. We introduce a further enhancement in the quality of the
H2O total column by optimizing the cloud screening and developing an
empirical correction in order to eliminate the instrument scan angle
dependencies. The overall consistency between measurements from the newer
GOME-2 instrument on board of the MetOp-B platform and the GOME-2/MetOp-A
data is evaluated in the overlap period (December 2012–June 2014).
Furthermore, we compare GOME-2 results with independent TCWV data from the
ECMWF ERA-Interim reanalysis, with SSMIS satellite measurements during the
full period January 2007–June 2014 and against the combined SSM/I + MERIS
satellite data set developed in the framework of the ESA DUE GlobVapour
project (January 2007–December 2008). Global mean biases as small as ±0.035 g cm−2 are found between GOME-2A and all other data sets. The
combined SSM/I-MERIS sample and the ECMWF ERA-Interim data set are typically
drier than the GOME-2 retrievals, while on average GOME-2 data overestimate
the SSMIS measurements by only 0.006 g cm−2. However, the size of these
biases is seasonally dependent. Monthly average differences can be as large
as 0.1 g cm−2, based on the analysis against SSMIS measurements, which
include only data over ocean. The seasonal behaviour is not as evident when
comparing GOME-2 TCWV to the ECMWF ERA-Interim and the SSM/I+MERIS data sets,
since the different biases over land and ocean surfaces partly compensate
each other. Studying two exemplary months, we estimate regional differences
and identify a very good agreement between GOME-2 total columns and all three
data sets, especially for land areas, although some discrepancies (bias
larger than ±0.5 g cm−2) over ocean and over land areas with high
humidity or a relatively large surface albedo are observed. |
| |
|
| Teil von |
|
|
|
|
|
|
|
|