Abstract

In August 2018, the European Space Agency launched the Aeolus satellite, whose Atmospheric LAser Doppler INstrument (ALADIN) is the first spaceborne Doppler wind lidar to regularly measure vertical profiles of horizontal line-of-sight (HLOS) winds with global sampling. This mission is intended to assess improvement to numerical weather prediction provided by wind observations in regions poorly constrained by atmospheric mass, such as the tropics, but also, potentially, in polar regions such as the Arctic where direct wind observations are especially sparse. There remain gaps in the evaluation of the Aeolus products over the Arctic region, which is the focus of this contribution. Here, an assessment of the Aeolus Level-2B wind product is carried out from measurement stations in Canada’s north, to the pan-Arctic, with Aeolus data being compared to Ka-band radar measurements at Iqaluit, Nunavut; to radiosonde measurements over Northern Canada; to Environment and Climate Change Canada (ECCC)’s short-range forecast; and to the reanalysis product, ERA5, from the European Centre for Medium-Range Weather Forecasts (ECMWF). Periods covered include the early phase during the first laser nominal flight model (FM-A; 2018-09 to 2018-10), the early phase during the second flight laser (FM-B; 2019-08 to 2019-09), and the mid-FM-B periods (2019-12 to 2020-01). The adjusted r-square between Aeolus and other local datasets are around 0.9, except for somewhat lower values in comparison with the ground-based radar, presumably due to limited sampling. This consistency degraded by about 10 % for the Rayleigh winds in the summer, presumably due to scattering from the solar background. Over the pan-Arctic, consistency, with correlation greater than 0.8, is found in the Mie channel from the planetary boundary layer to the lower stratosphere (near surface to 16 km a.g.l.) and in the Rayleigh channel from the troposphere to the stratosphere (2 km to 25 km a.g.l.). Zonal and meridional projections of the HLOS winds are separated to account for the systematic changes in HLOS winds arising from sampling wind components from different viewing orientations in the ascending and descending phases. In all cases, Aeolus standard deviations are found to be 20 % greater than those from ECCC-B and ERA5. We found that L2B estimated error product for Aeolus is coherent with the differences between Aeolus and the other datasets, and can be used as a guide for expected consistency. Thus, our work confirms the quality of the Aeolus dataset over the Arctic and shows that the new Aeolus L2B wind product provides a valuable addition to current wind products in regions such as the Arctic Ocean region where few direct wind observations have been available to date.

Highlights

  • A better characterization of the global wind field would advance the initialization of numerical weather prediction (NWP) and 35 thereby improve our knowledge of the characteristics and transport of moisture, energy, and other fields in the global atmosphere (Baker et al.,1995; Graham et al, 2000, Naakka et al, 2019)

  • An assessment of the Aeolus Level2B wind product is carried out from measurement stations in Canada’s north, to the pan-Arctic, with Aeolus data being compared to Ka-band radar measurements at Iqaluit, Nunavut; to radiosonde measurements over Northern Canada; to Environment and Climate Change Canada (ECCC)’s short-range forecast; and to the reanalysis product, ERA5, from the European Centre for Medium-Range Weather Forecasts (ECMWF)

  • The purpose of this paper is to evaluate the quality of Aeolus wind products over Northern Canada and the Arctic in comparison with several available observational products, including the dataset from the Canadian Arctic Weather Science (CAWS) project supersites, that contain a suite of ground based remote sensing and in-situ instruments for enhanced 65 meteorological observations located at Iqaluit, NU (64° N, 69° W) and Whitehorse, YK (61° N, 135° W) (Joe et al, 2020)

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Summary

Introduction

A better characterization of the global wind field would advance the initialization of numerical weather prediction (NWP) and 35 thereby improve our knowledge of the characteristics and transport of moisture, energy, and other fields in the global atmosphere (Baker et al.,1995; Graham et al, 2000, Naakka et al, 2019). Altitude resolved wind observations are available from aircraft reports and surfaced-based observations (e.g., radiosondes and wind profilers). Those are generally scattered and especially rare over large water surfaces like oceans, and the polar regions. Winds derived from passive spacebased observations, such as atmospheric motion vectors (AMVs) and spaceborne scatterometer, are retrieved from the 40 movements of clouds and water vapour (Velden et al, 2017; Mizyak et al, 2016) or from scattering from the ocean surface. Spaceborne scatterometers are limited to ocean near-surface winds and their 45 accuracy is sensitive to surface weather conditions (Chiara et al, 2017; Young et al, 2017). Improving altituderesolved winds from remote sensing on a global scale requires adoption of active sensors, which have only recently become feasible for deployment from space based platforms (Dabas, 2010)

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