Assimilation of OLCI total column water vapour in the Met Office global numerical weather prediction system
Abstract The representation of water vapour in numerical weather prediction models is still subject to significant uncertainties, which are partly due to the lack of observations of water vapour in the lower troposphere over land and sea‐ice areas. There are now several satellite datasets of total c...
| Published in: | Meteorological Applications |
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| Main Author: | |
| Format: | Article in Journal/Newspaper |
| Language: | English |
| Published: |
Wiley
2021
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| Subjects: | |
| Online Access: | https://doi.org/10.1002/met.2029 https://doaj.org/article/6988bd23a1b84d9c82dad21c28483f43 |
| Summary: | Abstract The representation of water vapour in numerical weather prediction models is still subject to significant uncertainties, which are partly due to the lack of observations of water vapour in the lower troposphere over land and sea‐ice areas. There are now several satellite datasets of total column water vapour available, which make use of the reflected radiances from the surface in the near‐infrared spectral region where there are water vapour absorption bands. The ocean and land cover imager (OLCI) on the Sentinel‐3A and 3B satellites measures the top of atmosphere radiances in the near infrared, and a total column water vapour product is retrieved and made available in near real time. Comparisons of the total column water vapour from OLCI with NWP model 6‐h forecasts, collocated ground‐based GNSS measurements and radiosonde profiles have been undertaken to determine the accuracy of the product. Following the monitoring, some experiments were made to assimilate the OLCI total column water vapour over land using the Met Office 4D‐Var assimilation system. A 5‐month trial assimilating the OLCI data has shown consistently positive impacts on the forecast scores with some changes to the water vapour distribution in the model. |
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