Technical note describing the overall Cal/Val strategy for the AWS Satellite

Technical note describing the overall Cal/Val strategy for the AWS Satellite Deliverable 8, European Space Agency Project -Performance Evaluation of Arctic Weather Satellite Data (No. 4000136511/21/NL/IA) Per Dahlgren1 1 MET Norway The Arctic Weather Satellite was successfully launched 16 August 2024 and a longer LEOP (Launch and Early Operation Phase) phase started with initial testing and adjustment of orbit, during which the project team had no access to any data. Then, in October and November 2024 a limited data set of five orbits were delivered to us with observations from mid September 2024. With this data we could technically test our NWP assimilation with real AWS data and do a first evaluation of its performance. These data were then re-processed with an updated version of the ground level processor so we could also do an evaluation of the original data set versus the re-processed data. The results were presented to the Scientific Advisory Group on 3 December 2024 and also in deliverable 7 [1]. In this part of the evaluation a general health check was done by producing maps of observed AWS brightness temperatures and model equivalents, i.e. brightness temperatures modeled with RTTOV using HARMONIE-AROME (H-A) profiles of temperature and humidity as input. Then it was found that a lot of data from the first delivered 5 orbits was rejected by the NWP system quality control, especially in the beginning of the scan where almost all data were rejected. This improved significantly in the second delivery where a lot more data were approved by the NWP model. Gaussian distributions of (O-B) departures and scan dependent biases and standard deviations were also produced but the limited sample made it difficult to draw conclusions from them. In December 2024 a data stream was set up in which global AWS data acquired at Svalbard and processed at Tromsø were made available to early evaluators via EUMETSAT. We consequently set up a retrieval and processing system in which data from the EUMETSAT data store were regularly retrieved in L1B format and processed locally to obtain L1C netCDF files using the ESA level-1c processor [2]. We could then start near real time runs with the H-A NWP system. The results from these runs are summarized in deliverable 9 [3]. With the near real time runs the stability of AWS data in terms of noise, i.e. STDEV(O-B), and biases could be assessed. Comparison to heritage sensors ATMS/AMSU-A/MHS was also done. First, a stringent data selection was done. This means a sub-area over sea chosen where AWS, NOAA-20 and METOP-C had a lot of near-nadir overpasses (near-nadir was in this case chosen as +/-10 degrees scan angle). Time series of STDEV(O-B) for AWS, NOAA-20 ATMS, METOP-C AMSU-A/MHS were produced and it was found that AWS had, as expected, higher noise in the 50 GHz channels than heritage sensors and comparable values for the 183 GHz channels. Second, the same type of statistics were performed again but with data from the whole NWP domain over sea and using the full swath, i.e. not just near-nadir. It turned out that the results were very similar to the previous exercise. In discussions with ESA it was also pointed out that such comparisons are not entirely fair as 1 the different sensors have different footprint sizes, and AWS has a comparable shorter integration time and large oversampling in the 50 GHz channels. We therefore introduced a 3x3 averaging of the 50 GHz AWS channels which clearly reduced the noise down to just slightly higher than AMSU-A. A change in the ground level processor; introduction of side lobe corrections (update to the SCDB), was also detected in the NWP based statistics as a clear reduction of biases in both 50 GHz and 183 GHz channels. Scan dependent (O-B) bias statistics also showed a curve shape in the 50 GHz channels and a slope shape in the 183 GHz channels. This curve shape is probably due to debris in feedhorn 3, see [3] for further analysis. The curve shape was also seen in NWP statistics from other centres like Meteo-France and ECMWF. Introduction of side-lobe corrections mentioned above reduced biases, and to some degree, some of the scan dependency but the slope shape mentioned above remained. References [1] Dahlgren, P., Dybbroe, A., Guedj, S. Technical note describing the Quality assessment of AWS data and identified improvements for the AWS data during SIOV. (2025) Deliverable 7, European Space Agency Project -Performance Evaluation of Arctic Weather Satellite Data (No. 4000136511/21/NL/IA) [2] Rydberg, B. (2025). Remapping of AWS data. Zenodo. https://doi.org/10.5281/zenodo.15049254 [3] Dahlgren, P., McEvoy, P., Eriksson, P., Dybbroe, A., Guedj, S., Aspenes, T., Lahtinen, P. Quantification of AWS data quality and timeliness Deliverable 9, European Space Agency Project -Performance Evaluation of Arctic Weather Satellite Data (No. 4000136511/21/NL/IA) 2