The impact of NOAA-AVHRR SST data assimilation in the HIRLAM NWP model

S de Haan

Numerical weather prediction (NWP) models can profit from input of
accurate satellite measured sea surface temperatures (SST). In April
2000 the project 'SST in HIRLAM' is finished at KNMI. HIRLAM (HIgh
Resolution Limited Area Model) is the NWP model runned operationally
at KNMI. The project was split in two parts: validate SST's measured
by the NOAA-AVHRR sensor and study the impact of the assimilation of
AVHRR-SST on the forecast quality of HIRLAM. The first part is
presented at the last EUMETSAT Conference in Copenhagen. In this paper
the second part will be presented.

The SST fields are assimilated using synoptic SST measurements and 7
days daily composites of NOAA-AVHRR SST. The error characteristics are
derived from a four year data set of NOAA-AVHRR SST recordings at
KNMI. The study area is roughly a square from Iceland to Corsica
covering the North Sea and a large part of the Atlantic Ocean. In
three different time periods two 12-hour HIRLAM high resolution
forecast are made over this region one with conventional SST fields
and the other with SST fields originating from the NOAA-AVHRR
measurements.

The assimilation scheme, error characteristics and the impact results
of the NOAA-AVHRR SST will be discussed.

Bibliografische gegevens

S de Haan. The impact of NOAA-AVHRR SST data assimilation in the HIRLAM NWP model
published, EUMETSAT, no