Supermodding – A special footprint operator for mesoscale data assimilation using scatterometer winds. (16th February 2021)

• Record Type: Journal Article
• Authors: Mile, Máté; Randriamampianina, Roger; Marseille, Gert‐Jan; Stoffelen, Ad
• Is Part Of: Quarterly journal of the Royal Meteorological Society. Volume 147:Number 735(2021)
• Page Start: 1382
• Page End: 1402
• Publication Date: 2021-02-16
• Subjects: data assimilation -- high resolution -- observation footprint -- representativeness -- scatterometer -- supermodding; Meteorology -- Periodicals; 551.5
• DOI: 10.1002/qj.3979
• Languages: English
• ISSNs: 0035-9009

Abstract

Abstract: Satellite observation footprints may extend over many grid points of a high‐resolution limited‐area model, while small and fast model scales may not be traceable by the observing system. We discuss the spatial representation of scatterometer ocean surface winds for the representation of high‐resolution model state variables. A prototype observation operator called supermodding is studied in the variational assimilation framework in order to avoid correcting unconstrained small scales during the assimilation procedure. The challenges connected to small scales that are represented by the mesoscale model with respect to the application of the supermodding operator are discussed through idealised experiments. These results show that the application of the supermodding operator is able to avoid correcting unconstrained small scales, putting focus on the large scales only during data assimilation. Departure‐based diagnostics show that the footprint representation helps to reduce the standard deviation of observation minus background departures (4–5% reduction) while the statistics for the supermodding method show a further reduction (8–11%). The impact of the supermodding approach is discussed through a forecast sensitivity study using a moist total energy norm (MTEN)‐based technique and verification of the forecasts against observations. It is shown that the impact of the supermodding method to ASCAT data assimilation on the upper‐air AROME‐Arctic forecasts is observed over sea and near the surface, and that it is progressively shifted towards 700–800 hPa levels. Both supermodding at 30 km and at 60 km (i.e., twice the effective resolution of the applied scatterometer observations) show significant and consistent improvement on forecasts of lower tropospheric wind and temperature compared to the operational assimilation technique, as such demonstrating the robustness of the supermodding technique. Abstract : This study introduces the so‐called supermodding observation operator, which aims to represent the satellite footprint and to ignore the correction on the smallest scales in the data assimilation procedure. These scales are not traceable by the observing system and their initialisation detrimentally affects model initialisation at all scales. The proof of concept is discussed and demonstrated in this paper.