Towards an improved ocean forcing using scatterometer winds

Presentación para el International Ocean Vector Winds Science Team (2015 IOVWST) Meeting, 19-21 May 2015, Portland, Oregon.-- 17 pagesPeer Reviewe

Overview of Instrument Response Calibrations

The Instrument Response Calibration (IRC) constitutes a fundamental part of the Aeolus processing chain and the basis for accurate and precise wind information provided to the global user community. The IRC is a crucial instrument mode for the wind measurement and has, hence, been extensively investigated with the ALADIN Airborne Demonstrator already before launch of the Aeolus satellite. IRCs are used to determine the relationship between the Doppler frequency shift on the backscattered light, i.e. the wind speed, and the frequency response of the Rayleigh and Mie spectrometers. This is achieved by sampling a frequency range of 1 GHz in steps of 25 MHz around the nominal laser frequency for the wind measurement. Whereas Aeolus wind measurements (WVM) are obtained under an off-nadir viewing angle of 35°, IRCs are performed in nadir viewing mode, thereby trying to avoid the atmospheric horizontal wind component along the line-of-sight as well as the component of the satellite velocity. The special importance of the IRC mode has changed with time caused by the experiences gained after the launch of Aeolus

NWP calibration applied to Aeolus Mie channel winds

Aeolus is the first Doppler wind lidar (DWL) to measure wind profiles from space. Aeolus is an ESA (European Space Agency) explorer mission with the objective to retrieve winds from the collected atmospheric return signal which is the result of Mie and Rayleigh scattering of laser-emitted light by atmospheric molecules and particulates. The focus of this paper is on winds retrieved from instrument Mie channel collected data, that is, originating from Mie scattering by atmospheric aerosols and clouds. The use of simulated data from numerical weather prediction (NWP) models is a widely accepted and proven concept for the monitoring of the performance of many meteorological instruments, including Aeolus. Continuous monitoring of Aeolus Mie channel winds against model winds from the European Centre for Medium-Range Weather Forecasts (ECMWF) has revealed systematic errors in retrieved Mie winds. Following a reverse engineering approach, the systematic errors could be traced back to imperfections of the data in the calibration tables which serve as input for the on-ground wind processing algorithms. A new algorithm, denoted NWP calibration, makes use of NWP model winds to generate an updated calibration table. It is shown that Mie winds retrieved by making use of the NWP-based calibration tables show reduced systematic errors, not only when compared to NWP model winds but also when compared to an independent dataset of very-high-resolution aircraft wind data. The latter gives high confidence that the NWP-based calibration algorithm does not introduce model-related errors into retrieved Aeolus Mie winds. Based on the presented results in this paper, the NWP-based calibration table, as part of the level-2B wind processing, has become part of the operational processing chain since 01 July 2021

The impact of Aeolus wind retrievals on ECMWF global weather forecasts

Abstract Aeolus is the world's first spaceborne Doppler Wind Lidar, providing profiles of horizontal line-of-sight (HLOS) wind retrievals. Numerical weather prediction (NWP) impact and error statistics of Aeolus Level-2B (L2B) wind statistics have been assessed using the European Centre for Medium-range Weather Forecasts (ECMWF) global data assimilation system. Random and systematic error estimates were derived from observation minus background departure statistics. The HLOS wind random error standard deviation is estimated to be in the range 4.0-7.0 m/s for the Rayleigh-clear and 2.8-3.6 m/s for the Mie-cloudy, depending on atmospheric signal levels which in turn depend on instrument performance, atmospheric backscatter properties and the processing algorithms. Complex systematic HLOS wind error variations on time-scales less than one orbit were identified, most strongly affecting the Rayleigh-clear winds. NWP departures and instrument housekeeping data confirmed that it is caused by temperature gradients across the primary mirror. A successful bias correction scheme was implemented in the operational processing chain in April 2020. In Observing System Experiments (OSEs), Aeolus provides statistically significant improvement in short-range forecasts as verified by observations sensitive to temperature, wind and humidity. Longer forecast range verification shows positive impact that is strongest at the day two to three forecast range: 2% improvement in root-mean-square error for vector wind and temperature in the tropical upper troposphere and lower stratosphere, and polar troposphere. Positive impact up to 9 days is found in the tropical lower stratosphere. Both Rayleigh-clear and Mie-cloudy winds provide positive impact, but the Rayleigh accounts for most tropical impact. The Forecast Sensitivity Observation Impact (FSOI) metric is available since 9 January 2020, when Aeolus was operationally assimilated, which confirms Aeolus is a useful contribution to the global observing system, with the Rayleigh-clear and Mie-cloudy winds providing similar overall short-range impact in 2020

ERA*

Presentación para la ponencia Scatterometer new products en el 2nd Globcurrent User Consultation Meeting, 4-6 November 2015, Brest, France.-- 35 pagesSurface winds derived from earth Observation satellites are increasingly required for use in monitoring and forecasting of the ocean. A drawback of space-borne wind observing systems, such as scatterometers, is that they provide time and space coverage unsuitable for, among others, high-resolution ocean model forcing. As such, blended ocean forcing products combining scatterometer data and numerical weather prediction (NWP) output, are being developed over the past few years. These products, which provide full global coverage at increased temporal resolution (e.g., daily), however, generally only resolve spatial scales closer to NWP-resolved (200km) rather than scatterometer-resolved scales (25 km). Therefore, information on wind-current interaction, on the diurnal wind cycle and on wind variability in moist convection areas is lost in these blended products. Moreover, known systematic NWP model (parameterization) errors are propagated in the blended products at times and locations where no scatterometer winds are available. Direct forcing from ERA-interim or an operational global meteorological model results in even more extensive physical drawbacks, but has the advantage of increased temporal coverage. We propose to maintain this increased temporal coverage in a gridded wind and stress product, but also to maintain most beneficial physical qualities of the scatterometer winds, i.e., 25-km spatial resolution, wind-current interaction, variability due to moist convection, etc., and, at the same time avoid the large-scale NWP parameterization and dynamical errors. In fact, collocations of scatterometer and global NWP winds show these physical differences, where the local mean and variability of these differences are rather constant in time and thus could be added to the ERA-interim time record in order to better represent physical interaction processes and avoid NWP model errors. Correction of either the wind vector biases and wind vector variability is expected to affect ocean forcing. Moreover, the collocation process provides NWP winds, but sampled like a scatterometer and, therefore, provides information on the scatterometer wind sampling error. Prior to merging different scatterometer data sources, a comprehensive characterization of the scatterometer corrections is required. We provide an assessment of the corrections and sampling errors for the tandem scatterometer data set composed by ASCAT-A/B, RapidScat, Oceansat-2 and HY-2A, which, so far offer the most complementary orbits in terms of the diurnal cycle. All comparisons involve the stress-equivalent 10m wind, U10S, which avoids effects of atmospheric stratification and mass density to affect the computed wind differences. U10S may be easily computed from global NWP or moored buoy measurements for comparison to the scatterometer equivalents. U10S, in turn, can be easily related to ocean surface stressPeer Reviewe

Correction of wind bias for the lidar on-board Aeolus using telescope temperatures

The European Space Agency satellite Aeolus provides continuous profiles of the horizontal line-of-sight wind component at a global scale. It was successfully launched into space in August 2018 with the goal to improve numerical weather prediction (NWP). Aeolus data has already been successfully assimilated into several NWP models and has already helped to significantly improve the quality of weather forecasts. To achieve this major milestone the identification and correction of several systematic error sources was necessary. One of them is related to small temperatures fluctuations across the 1.5 m diameter primary mirror of the telescope which cause varying wind biases along the orbit of up to 8 m/s. This paper presents a detailed overview of the influence of the telescope temperature variations on the Aeolus wind products and describes the approach to correct for this systematic error source in the operational near-real-time (NRT) processing. It was shown that the telescope temperature variations along the orbit are due to changes of the top-of-atmosphere short- and long-wave radiation of the Earth and the response of the telescope’s thermal control system to that. To correct for this effect ECMWF model-equivalent winds are used as bias reference to describe the wind bias in a multiple linear regression model as a function of various temperature sensors located on the primary telescope mirror. This correction scheme has been in operational use at ECMWF since April 2020 and is capable of reducing a large part of the telescope-induced wind bias. In cases where the influence of the temperature variations is particularly strong it was shown that the bias correction can improve the orbital bias variation by up to 53 %. Moreover, it was demonstrated that the approach of using ECMWF model-equivalent winds is justified by the fact that the global bias of models u-component winds w.r.t to radiosondes is smaller than 0.3 m/s. However, this paper also presents the alternative of using Aeolus ground return winds which serve as zero wind reference in the multiple linear regression model. The results show that the approach based on ground return winds only performs 10.8 % worse than the ECMWF model-based approach and thus has good potential for future applications for upcoming reprocessing campaigns or even in the NRT processing of Aeolus wind products

ESA's Space-based Doppler Wind Lidar Mission Aeolus - First Wind and Aerosol Product Assessment Results

The European Space Agency (ESA) wind mission, Aeolus, hosts the first space-based Doppler Wind Lidar (DWL) world-wide. The primary mission objective is to demonstrate the DWL technique for measuring wind profiles from space, intended for assimilation in Numerical Weather Prediction (NWP) models. The wind observations will also be used to advance atmospheric dynamics research and for evaluation of climate models. Mission spinoff products are profiles of cloud and aerosol optical properties. Aeolus was launched on 22 August 2018, and the Atmospheric LAser Doppler INstrument (Aladin) instrument switch-on was completed with first high energy output in wind mode on 4 September 2018. The on-ground data processing facility worked excellent, allowing L2 product output in near-real-time from the start of the mission. First results from the wind profile product (L2B) assessment show that the winds are of very high quality, with random errors in the free Troposphere within (cloud/aerosol backscatter winds: 2.1 m/s) and larger (molecular backscatter winds: 4.3 m/s) than the requirements (2.5 m/s), but still allowing significant positive impact in first preliminary NWP impact experiments. The higher than expected random errors at the time of writing are amongst others due to a lower instrument outand input photon budget than designed. The instrument calibration is working well, and some of the data processing steps are currently being refined to allow to fully correct instrument alignment related drifts and elevated detector dark currents causing biases in the first data product version. The optical properties spin-off product (L2A) is being compared e.g. to NWP model clouds, air quality model forecasts, and collocated ground-based observations. Features including optically thick and thin particle and hydrometeor layers are clearly identified and are being validated

Data quality of Aeolus wind measurements

The European Space Agency (ESA)'s Earth Explorer Aeolus was launched in August 2018 carrying the world's first spaceborne wind lidar, the Atmospheric Laser Doppler Instrument (ALADIN). ALADIN uses a high spectral resolution Doppler wind lidar operating at 355nm to measure profiles of line-of-sight wind components in near-real-time (NRT). ALADIN samples the atmosphere from 30km altitude down to the Earth's surface or to the level where the lidar signal is attenuated by optically thick clouds. The global wind profiles provided by ALADIN help to improve weather forecasting and the understanding of atmospheric dynamics as they fill observational gaps in vertically resolved wind profiles mainly in the tropics, southern hemisphere, and over the northern hemisphere oceans. In January 2020, the European Centre for Medium-Range Weather Forecasts (ECMWF) became the first numerical weather prediction (NWP) centre to assimilate Aeolus observations for operational forecasting. A main prerequisite for beneficial impact is data of sufficient quality. Such high data quality has been achieved through close collaboration of all involved parties within the Aeolus Data Innovation and Science Cluster (DISC), which was established after launch to study and improve the data quality of Aeolus products. The tasks of the Aeolus DISC include the instrument and platform monitoring, calibration, characterization, retrieval algorithm refinement, processor evolution, quality monitoring, product validation, and impact assessment for NWP. The achievements of the Aeolus DISC for the NRT data quality and the current status of Aeolus wind measurements will be described and summarized. Further, an outlook on future improvements and the availability of reprocessed datasets with enhanced data quality will be provided

Initial Assessment of the Performance of the First Wind Lidar in Space on Aeolus

Soon after its successful launch in August 2018, the spaceborne wind lidar ALADIN (Atmospheric LAser Doppler INstrument) on-board ESA's Earth Explorer satellite Aeolus has demonstrated to provide atmospheric wind profiles on a global scale. Being the first ever Doppler Wind Lidar (DWL) instrument in space, ALADIN contributes to the improvement in numerical weather prediction (NWP) by measuring one component of the horizontal wind vector. The performance of the ALADIN instrument was assessed by a team from ESA, DLR, industry, and NWP centers during the first months of operation. The current knowledge about the main contributors to the random and systematic errors from the instrument will be discussed. First validation results from an airborne campaign with two wind lidars on-board the DLR Falcon aircraft will be shown

The Aeolus Data Innovation and Science Cluster

The Data Innovation and Science Cluster (DISC) is a core element of ESA's data quality strategy for the Aeolus mission, which was launched in August 2018. Aeolus provides for the first-time global observations of vertical profiles of horizontal wind information by using the first Doppler wind lidar in space. The Aeolus DISC is responsible for monitoring and improving the quality of the Aeolus aerosol and wind products, for the upgrade of the operational processors as well as for impact studies and support of data usage. It has been responsible for multiple significant processor upgrades which reduced the systematic error of the Aeolus observations drastically. Only due to the efforts of the Aeolus DISC team members prior to and after launch, the systematic error of the Aeolus wind products could be reduced to a global average below 1 m/s which was an important pre-requisite for making the data available to the public in May 2020 and for its use in operational weather prediction. In 2020, the reprocessing of earlier acquired Aeolus data, another important task of the Aeolus DISC, also started. In this way, also observations from June to December 2019 with significantly better quality could be made available to the public, and more data will follow this and next year. Without the thorough preparations and close collaboration between ESA and the Aeolus DISC over the past decade, many of these achievements would not have been possible