Horizontal Line Of Sight Research Articles

Long-Term Validation of Aeolus Level-2B Winds in the Brazilian Amazon

The Atmospheric Dynamics Mission ADM-Aeolus was successfully launched in August 2018 by the European Space Agency (ESA). The Aeolus mission carried a single instrument, the first-ever Doppler wind lidar (DWL) in space, called Atmospheric LAser Doppler INstrument (ALADIN). Aeolus circled the Earth, providing vertical profiles of horizontal line-of-sight (HLOS) winds on a global scale. The Aeolus satellite’s measurements filled critical gaps in existing wind observations, particularly in remote regions such as the Brazilian Amazon. This area, characterized by dense rainforests and rich biodiversity, is essential for global climate dynamics. The weather patterns of the Amazon are influenced by atmospheric circulation driven by Hadley cells and the Intertropical Convergence Zone (ITCZ), which are crucial for the distribution of moisture and heat from the equator to the subtropics. The data provided by Aeolus can significantly enhance our understanding of these complex atmospheric processes. In this long-term validation study, we used radiosonde data collected from three stations in the Brazilian Amazon (Cruzeiro do Sul, Porto Velho, and Rio Branco) as a reference to assess the accuracy of the Level 2B (L2B) Rayleigh-clear and Mie-cloudy wind products. Statistical validation was conducted by comparing Aeolus L2B wind products and radiosonde data covering the period from October 2018 to March 2023 for Cruzeiro do Sul and Porto Velho, and from October 2018 to December 2022 for Rio Branco. Considering all available collocated winds, including all stations, a Pearson’s coefficient (r) of 0.73 was observed in Rayleigh-clear and 0.85 in Mie-cloudy wind products, revealing a strong correlation between Aeolus and radiosonde winds, suggesting that Aeolus wind products are reliable for capturing wind profiles in the studied region. The observed biases were −0.14 m/s for Rayleigh-clear and −0.40 m/s for Mie-cloudy, fulfilling the mission requirement of having absolute biases below 0.7 m/s. However, when analyzed annually, in 2022, the bias for Rayleigh-clear was −0.95 m/s, which did not meet the mission requirements.

Assessment for operational assimilation of horizontal line of sight winds from the European Space Agency's Aeolus at the Met Office

AbstractThe European Space Agency's Aeolus satellite was launched in August 2018 and began delivering horizontal line‐of‐sight (HLOS) wind observations in early September 2018. In early 2019, the Met Office began assessing the suitability of the HLOS winds for operational assimilation into its global numerical weather prediction system. We performed a number of assimilation experiments to assess the impact of HLOS wind observations on our global forecasts. We have found that assimilating HLOS winds changes the zonal winds in the analysis fields predominantly in the Tropics and Southern Hemisphere, with the largest changes being in the upper troposphere and lower stratosphere. This has a positive impact on the accuracy of the global weather forecasts, with improvements in the root‐mean‐square error seen throughout the troposphere. Assimilation of Aeolus HLOS winds improves the standard deviation of the observation minus background (a 6 hr forecast) of almost all other observation types, suggesting that the numerical weather prediction model analysis is improved, which consequently improves the 6 hr forecast. In a set of short‐period observation denial experiments, we found that assimilating Aeolus has an impact similar in magnitude to assimilating surface winds from scatterometers. Assimilating winds from the Rayleigh channel has approximately three times the impact that assimilating HLOS winds from the Mie channel does. Both channels contribute a measureable improvement to the global forecast, and we therefore started operational assimilation of winds from the Mie channel in December 2020 and the Rayleigh channel operationally in May 2022.

Impact of Aeolus horizontal line‐of‐sight wind observations on tropical cyclone forecasting in a global numerical weather prediction system

AbstractThe satellite Aeolus, carrying a Doppler Wind Lidar instrument, was launched in August 2018. It is the first mission of the European Space Agency to provide wind profiles globally with high vertical resolutions. The significant positive impact of assimilating the horizontal line‐of‐sight (HLOS) wind data from Aeolus on numerical weather prediction has been reported in many works. In this study, in terms of tropical cyclone (TC) forecasting, the impact of the assimilated data on the Japan Meteorological Agency's global model was investigated in detail. Especially, the direct effect in each analysis resulting from the increment was studied and validated using a reinitialised analysis experiment. The 23 TCs that occurred in the western North Pacific during the summer of 2020 were focused on in the validation period. The largest improvement of track forecasting was found for cases of the NEAR group in which Aeolus passed within 5 degrees of latitude and longitude from a TC centre. The cases of the EAST or WEST groups in which Aeolus passed east or west of the TC centre also indicated some improvements, suggesting that the prediction accuracy of wind upstream of a TC was important for track forecasting. In the NEAR group cases, the increase in positive bias of the TC central pressure was also observed in the cases wherein Aeolus passed inside the maximum wind radius of the TCs. This is explained by the inability to represent the vorticity field in the upper levels in the analyses. One of the possible reasons for this is the insufficient horizontal resolution of observation. We also include some case studies to assess how Aeolus data improved track forecasting and affected intensity forecasting of TCs, specifically.

Analytical Determination of Size and Location of Roadside Horizontal Sightline Offsets for Compound Curves

Analytical Determination of Size and Location of Roadside Horizontal Sightline Offsets for Compound Curves

On the use of consistent bias corrections to enhance the impact of AeolusLevel‐2B Rayleigh winds on National Oceanic and Atmospheric Administration global forecast skill

AbstractThe operational Aeolus Level‐2B (L2B) horizontal line‐of‐sight (HLOS) retrieved Rayleigh winds, produced by the European Space Agency (ESA), utilize European Centre for Medium‐Range Weather Forecasts (ECMWF) short‐term forecasts of temperature, pressure, and horizontal winds in the Rayleigh–Brillouin and M1 correction procedures. These model fields or backgrounds can contain ECMWF model‐specific errors, which may propagate to the retrieved Rayleigh winds. This study examines the sensitivity of the retrieved Rayleigh winds to the changes in the model backgrounds, and the potential benefit of using the same system, in this case the National Oceanic and Atmospheric Administration's Finite‐Volume Cubed Sphere Global Forecast System (FV3GFS), for both the corrections and the data assimilation and forecast procedures. It is shown that the differences in the model backgrounds (FV3GFS minus ECMWF) can propagate through the Level‐2B horizontal line‐of‐sight Rayleigh wind retrieval process, mainly the M1 correction, resulting in differences in the retrieved Rayleigh winds with mean and standard deviation of magnitude as large as 0.2 m·s−1. The differences reach up to 0.4, 0.6, and 0.7 m·s−1 for the 95th, 99th, and 99.5th percentiles of the sample distribution with maxima of ∼1.4 m·s−1. The numbers of the large differences for the combined lower and upper 5th, 1st, and 0.5th percentile pairs are ∼6,100, 1,220, and 610 between 2.5 and 25 km height globally per day respectively. The ESA‐disseminated Rayleigh wind product (based on the ECMWF corrections) already shows a significant positive impact on the FV3GFS global forecasts. In the observing system experiments performed, compared with the ESA Rayleigh winds, the use of the FV3GFS‐corrected Rayleigh winds lead to ∼0.5% more Rayleigh winds assimilated in the lower troposphere and show enhanced positive impact on FV3GFS forecasts at the day 1–10 range but limited to the Southern Hemisphere.

Analysis of Electromagnetic Wave and Multipath Suppression from Overhead Perspective

The multipath problem in indoor target detection has always been a long-standing research hotspot. Although there are many solutions to the multipath problem in a horizontal line of sight, the multipath problem of single-station radar from an overhead perspective still needs to be solved. At present, there is a lack of detailed analysis on the multipath propagation law of electromagnetic waves from an overhead perspective. This paper first analyzes the multipath propagation law of overhead perspective and reveals a combination multipath propagation phenomenon that is easily overlooked, which is formed by walls, ground, and targets. In addition, during the analysis process, the influence of coherent sources generated by multipath on angle estimation was fully considered, and verified through simulation and measured data. Then, based on the result of propagation analysis, this paper proposes a multipath ghost target suppression method. This method first establishes a multipath ghost target location dictionary based on building information, and then matches the tracking results with the dictionary to suppress successfully matched multipath ghost targets. Finally, several experiments are carried out to verify the effectiveness of this method.

Impact of assimilating Aeolus observations in the global model ICON: A global statistical overview

AbstractGlobal wind profiles provided by the satellite mission Aeolus are an important recent supplement to the Global Observing System. This study investigates the impact of Aeolus horizontal line‐of‐sight wind observations in the operational global assimilation and forecasting system of Deutscher Wetterdienst that is based on the Icosahedral Nonhydrostatic (ICON) model. For this purpose, an observing system experiment was conducted and evaluated for a 3‐month period from July 2020 to October 2020. The Aeolus Rayleigh clear and Mie cloudy data quality and consistency were derived from observation minus background statistics. To correct for an altitude‐dependent bias, a model‐based bias correction scheme has been implemented. Comparisons of the systematic changes in the analysis and the respective forecasts provide an overview of the overall impact of the Aeolus horizontal line‐of‐sight wind assimilation in ICON. Increased influence of Aeolus wind profiles is found in jet regimes (e.g., amplification of the zonal wind component), around large‐scale circulation systems, and convectively active areas in the Tropics. The reduction in forecast error is largest in the tropical upper troposphere and stratosphere, as well as in the mid and upper troposphere of the Southern Hemisphere. The Northern Hemisphere shows a somewhat smaller but still beneficial impact of Aeolus observations. The verification with other conventional observations shows a mean relative reduction in short‐range forecast error between 0.1% and 0.6% in the Northern Hemisphere and up to 1.6% in the Tropics and the Southern Hemisphere. When verifying against the European Centre for Medium‐Range Weather Forecast Reanalysis v5, forecast errors of zonal wind, temperature, and geopotential up to 5 days lead time are reduced by 2–4% on global average and up to 5–8% around the tropical tropopause.

Long-term validation of Aeolus L2B wind products at Punta Arenas, Chile, and Leipzig, Germany

Abstract. Ground-based observations of horizontal winds have been performed at Leipzig (51.35∘ N, 12.43∘ E), Germany, and at Punta Arenas (53.15∘ S, 70.91∘ W), Chile, in the framework of the German initiative EVAA (Experimental Validation and Assimilation of Aeolus observations) with respect to the validation of the Mie and Rayleigh wind products of Aeolus (L2B data). In Leipzig, at the Leibniz Institute for Tropospheric Research (TROPOS), radiosondes have been launched for the Aeolus overpasses on each Friday (ascending orbit) since the middle of May 2019. In Punta Arenas, scanning Doppler cloud radar observations have been performed in the framework of the DACAPO-PESO campaign (dacapo.tropos.de) for more than 3 years from the end of 2018 until the end of 2021 and could be used to validate Aeolus measurements on its ascending and descending orbits. We present two case studies and long‐term statistics of the horizontal winds derived with the ground-based reference instruments compared to Aeolus horizontal line-of-sight (HLOS) winds. The wind products of Aeolus considered are the Mie cloudy and Rayleigh clear products. It was found that the deviation of the Aeolus HLOS winds from the ground reference is usually of Gaussian shape, which allowed the use of the median bias and the scaled median absolute deviation (MAD) for the determination of the systematic and random errors of Aeolus wind products, respectively. The case study from August 2020 with impressive atmospheric conditions at Punta Arenas shows that Aeolus is able to capture strong wind speeds of up to more than 100 m s−1. The long-term validation was performed in Punta Arenas covering the period from December 2018 to November 2021 and in Leipzig from May 2019 until September 2022. This analysis showed that the systematic error of the Aeolus wind products could be significantly lowered during the mission lifetime with the changes introduced into the processing chain (different versions are called baselines). While in the early mission phase, systematic errors of more than 2 m s−1 (absolute values) were observed for both wind types (Mie and Rayleigh), these biases could be reduced with the algorithm improvements, such as the introduction of the correction for temperature fluctuations at the main telescope of Aeolus (M1 temperature correction) with Baseline 09. Hence, since Baseline 10, a significant improvement in the Aeolus data was found, leading to a low systematic error (close to 0 m s−1) and similar values for the midlatitudinal sites in both hemispheres. The random errors for both wind products were first decreasing with an increasing baseline but later increasing again due to performance losses of the Aeolus lidar instrument. Nevertheless, no significant increase in the systematic error in the Aeolus wind products was found. Thus, one can conclude that the uncertainty introduced by the reduced atmospheric return signal received by Aeolus mostly affects the random error. Even when considering all the challenges during the mission, we can confirm the general validity of Aeolus observations during its lifetime. Therefore, this space explorer mission could demonstrate that it is possible to perform active wind observations from space with the applied technique.

The impacts of assimilating Aeolus horizontal line-of-sight winds on numerical predictions of Hurricane Ida (2021) and a mesoscale convective system over the Atlantic Ocean

Abstract. The Aeolus satellite, the first spaceborne wind lidar launched by the European Space Agency (ESA) on 22 August 2018, provides global measurements of horizontal line-of-sight (HLOS) winds. The assimilation of Aeolus HLOS winds has been proven to improve numerical weather predictions (NWPs). Still, its influences on forecasts of tropical cyclones (TCs) and tropical convective systems have yet to be examined in detail. This study investigates the impacts of assimilating Aeolus HLOS winds on the analysis and forecasts of Hurricane Ida (2021) and a mesoscale convective system (MCS) embedded in an African easterly wave (AEW) over the Atlantic Ocean (AO) with the mesoscale community Weather Research and Forecasting (WRF) model and the NCEP Gridpoint Statistical Interpolation (GSI)-based three-dimensional ensemble-variational (3DEnVAR) hybrid data assimilation (DA) system. Mie-cloudy and Rayleigh-clear winds are assimilated. The results for Ida (2021) show that assimilating Aeolus HLOS winds leads to better track predictions. The intensity forecasts are improved in some cases, even with limited coverage of Aeolus HLOS winds within the inner core region of Ida (2021). In addition, the structure of heavy precipitation associated with Ida (2021) is refined after the assimilation of Aeolus HLOS winds. Further diagnosis demonstrates that the improved intensity and precipitation forecasts result from enhanced divergence in the upper level of the troposphere after the assimilation of Aeolus HLOS winds. Additional results from the MCS associated with an AEW indicate that assimilating Aeolus HLOS winds enhances forecasts of its precipitation structure and the associated low-level divergence. Findings from this study suggest that the assimilation of Aeolus HLOS winds has the potential to improve forecasts for TCs and tropical convective systems.

Investigation of links between dynamical scenarios and particularly high impact of Aeolus on numerical weather prediction (NWP) forecasts

Abstract. Global wind profiles from the Aeolus satellite mission provide an important source of wind information for numerical weather prediction (NWP). Data assimilation experiments show large mean changes in the analysis and a significant reduction in forecast errors. At Deutscher Wetterdienst (DWD), a 3-month observing system experiment (OSE), from July 2020 to October 2020, was performed to evaluate the impact of the Aeolus horizontal line-of-sight (HLOS) wind observations in the operational data assimilation system of the ICOsahedral Nonhydrostatic (ICON) global model. To better understand the underlying dynamics leading to the overall beneficial impact, specific time periods and regions with a particularly high impact of Aeolus are investigated. In this study, we illustrate three examples of atmospheric phenomena that constitute dynamical scenarios for significant forecast error reduction through the assimilation of Aeolus: the phase shift of large-scale tropical circulation systems, namely the Quasi-Biennial Oscillation (QBO) and the El Niño–Southern Oscillation (ENSO), and the interaction of tropical cyclones undergoing extratropical transition (ET) with the midlatitude waveguide.

Validation of Aeolus wind profiles using ground-based lidar and radiosonde observations at Réunion island and the Observatoire de Haute-Provence

Abstract. The European Space Agency's (ESA) Aeolus satellite mission is the first Doppler wind lidar in space, operating in orbit for more than 4 years since August 2018 and providing global wind profiling throughout the entire troposphere and the lower stratosphere. The Observatoire de Haute-Provence (OHP) in southern France and the Observatoire de Physique de l'Atmosphère de La Réunion (OPAR) are equipped with ground-based Doppler Rayleigh–Mie lidars, which operate on similar principles to the Aeolus lidar and are among essential instruments within the ESA Aeolus calibration and validation (cal/val) program. This study presents the validation results of the L2B Rayleigh clear horizontal line-of-sight (HLOS) winds from September 2018 to January 2022. The point-by-point validation exercise relies on a series of validation campaigns at both observatories: AboVE (Aeolus Validation Experiment), held in September 2019 and June 2021 at OPAR and in January 2019 and December 2021 at OHP. The campaigns involved time-coordinated lidar acquisitions and radiosonde ascents collocated with the nearest Aeolus overpasses. During AboVE-2, Aeolus was operated in a campaign mode with an extended range bin setting allowing inter-comparisons up to 28.7 km. We show that this setting suffers from larger random error in the uppermost bins, exceeding the estimated error, due to lack of backscatter at high altitudes. To evaluate the long-term evolution in Aeolus wind product quality, twice-daily routine Météo-France radiosondes and regular lidar observations were used at both sites. This study evaluates the long-term evolution of the satellite performance along with punctual collocation analyses. On average, we find a systematic error (bias) of −0.92 and −0.79 m s−1 and a random error (scaled MAD) of 6.49 and 5.37 m s−1 for lidar and radiosondes, respectively.

First assessment of Aeolus Standard Correct Algorithm particle backscatter coefficient retrievals in the eastern Mediterranean

Abstract. Since 2018, the Aeolus satellite of the European Space Agency (ESA) has acquired wind HLOS (horizontal line-of-sight) profiles throughout the troposphere and up to the lower stratosphere, filling a critical gap in the Global Observing System (GOS). Aeolus, carrying ALADIN (Atmospheric LAser Doppler INstrument), the first UV HSRL (High Spectral Resolution Lidar) Doppler lidar ever placed in space, provides also vertically resolved optical properties of particulates (aerosols and clouds). The present study focuses on the assessment of Aeolus L2A particulate backscatter coefficient (baseline 2A11), retrieved by the Standard Correct Algorithm (SCA), in the eastern Mediterranean, a region hosting a variety of aerosol species. Ground-based retrievals acquired by lidar instruments operating in Athens (central Greece), Thessaloniki (northern Greece) and Antikythera (southwestern Greece) serve as reference. All lidar stations provide routine measurements to the PANACEA (PANhellenic infrastructure for Atmospheric Composition and climatE chAnge) network. A set of ancillary data, including sun-photometric observations (AERONET), reanalysis products (CAMS and MERRA-2), satellite observations (MSG-SEVIRI and MODIS Aqua) and backward-trajectories modelling (FLEXPART), is utilized towards an optimum characterization of the probed atmospheric conditions under the absence of a classification scheme in Aeolus SCA profiles. First, emphasis is given on the assessment of Aeolus SCA backscatter coefficient under specific aerosol scenarios over Antikythera island. Due to the misdetection of the cross-polar component of the backscattered lidar signal, Aeolus underestimates the aerosol backscatter coefficient by up to 33 % when non-spherical mineral particles are recorded (10 July 2019). A good performance is revealed on 3 July 2019, when horizontally homogeneous loads of fine spherical particles are confined below 4 km. For other two cases (8 July 2020 and 5 August 2020), due to noise issues, the SCA performance degrades in terms of depicting the stratification of aerosol layers composed of particles of different origin. According to the statistical assessment analysis of 43 identified cases, a poor-to-moderate performance is revealed for the unfiltered (aerosols plus clouds) SCA profiles, which improves substantially when cloud-contaminated profiles are excluded from the collocated sample. This improvement is evident at both Aeolus vertical scales (regular scales have 24 bins and mid-bin scales have 23 bins), and it is justified by the drastic reduction in the bias (from 0.45 to 0.27 Mm−1 sr−1 for SCA and from 0.69 to 0.37 Mm−1 sr−1 for SCA mid-bin) and root mean square error (from 2.00 to 1.65 Mm−1 sr−1 for SCA and from 1.88 to 1.00 Mm−1 sr−1 for SCA mid-bin) scores. In the vertical, the SCA performance degrades at the lowermost bins due to either the contamination from surface signals or the increased noise levels for the aerosol retrievals. Among the three PANACEA stations, the best agreement is found at the remote site of Antikythera with respect to the urban sites of Athens and Thessaloniki. Finally, all key Cal/Val (calibration and validation) aspects necessary for future relevant studies, the recommendations for a possible Aeolus follow-on mission and an overview of the ongoing related activities are thoroughly discussed.

Evaluation and Redesign Based on Highway Geometric Design Guidelines 2021 (Case Study of Sampakan–Singosaren Road KM 13.8, Bantul Regency)

This study aims to : (1) evaluate the geometric design of the Sampakan–Singosaren street km 13,8 Bantul Regency based on Panduan Desain Geometrik Jalan Bina Marga 2021; (2) identify the factor considered as evaluation, (3) propose alternative design and (4) to evaluate the differences between existing geometric design and alternative geometric design. The study used trial-and-error modeling for existing, and alternative geometric using Auto cad Civil 3D Student Version and analyzed according to Bina Marga standard. Then, a comparison of the existing and alternative geometric designs is calculated based on Bina Marga Geometric Design Standard 2021. The result indicates of study that there are 2 (two) existing curves with (1) each radius range at 37 m and 30 m, respectively; (2) the horizontal sight line offset on the first curve and the second curve was 4,7 m and 0.7 m, and the driving speed of 40 km/h. Furthermore, there is some parameter that does not meet the requirements, so an alternative design is required to fulfill the requirements of Bina Marga Geometric Design Standard 2021; (3) The designed shift on the new track to ± 9 m east and ± 5 m south; (4) the radius in both curve (S-C-S) is about 44 m, (5) horizontal sight line offset on the first curve and the second curve was 8,38 m and 7,557 m. Some changes to the existing and alternative design are the larger radius, the lower super elevation, new track is more flexible, and the better JPH and horizontal sight line offset.

Impacts of Aeolus horizontal Line‐Of‐Sight (HLOS) wind assimilation on the Korean integrated model (KIM) forecast system

AbstractThe Korean Integrated Model (KIM) forecast system, based on a hybrid four‐dimensional ensemble‐variational method, was extended to assimilate Horizontal Line‐Of‐Sight (HLOS) wind observations from the Atmospheric Laser Doppler Instrument (ALADIN) on board the Atmospheric Dynamic Mission Aeolus satellite. In a global cycling experiment, assimilation of Aeolus HLOS wind observations led to reductions in the average root‐mean‐square error of 0.8 and 0.5% for the zonal and meridional wind analyses when compared against European Center for Medium‐Range Weather Forecasts (ECMWF) Integrated Forecast System (IFS) analyses. Even though the observed variable is wind, there was also an overall beneficial impact on analyses of the mass variables. In the Southern Hemisphere (SH), the reduced analysis errors led to forecast skill improvements out to 72 h. In contrast, in the Northern Hemisphere (NH) there was relatively little reduction of analysis errors, but wind forecasts were nevertheless improved, and these positive impacts lasted longer – out to 120 h rather than 72 h. Experiments suggest that the relatively poor long‐range performance in the SH high latitudes was due to problems with the mass increments derived from Aeolus wind increments via the ensemble‐based part of the hybrid background error covariance (B), which eventually led to adverse effects on the wind variables as forecasts progressed in the SH. This study shows that it is necessary to estimate the ensemble B in the Antarctic region with its high elevation more accurately in order to effectively use the Aeolus observation information.

Validation of the Aeolus L2B Rayleigh winds and ECMWF short‐range forecasts in the upper troposphere and lower stratosphere using Loon super pressure balloon observations

AbstractThe novel Aeolus satellite, which carries the first Doppler wind lidar providing profiles of horizontal line‐of‐sight (HLOS) winds, addresses a significant gap in direct wind observations in the global observing system. The gap is particularly critical in the tropical upper troposphere and lower stratosphere (UTLS). This article validates the Aeolus Rayleigh–clear wind product and short‐range forecasts of the European Centre for Medium‐Range Weather Forecasts (ECMWF) with highly accurate winds from the Loon super pressure balloon network at altitudes between 16 and 20 km. Data from 229 individual balloon flights are analysed, applying a collocation criterion of 2 hr and 200 km. The comparison of Aeolus and Loon data shows systematic and random errors of 0.31 and 6.37 ms, respectively, for the Aeolus Rayleigh–clear winds. The horizontal representativeness error of Aeolus HLOS winds (nearly the zonal wind component) in the UTLS ranges from 0.6–1.1 ms depending on the altitude. The comparison of Aeolus and Loon datasets against ECMWF model forecasts suggests that the model systematically underestimates the HLOS winds in the tropical UTLS by about 1 ms. While Aeolus winds are currently considered as point winds by the ECMWF data assimilation system, the results of the present study demonstrate the need for a more realistic HLOS wind observation operator for assimilating Aeolus winds.

Validation of the Aeolus Level-2B wind product over Northern Canada and the Arctic

Abstract. In August 2018, the European Space Agency (ESA) launched the Aeolus satellite, whose Atmospheric LAser Doppler INstrument (ALADIN) is the first space-borne 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 (L2B) wind product is carried out, progressing from specific locations in the Canadian North to the pan-Arctic. In particular, Aeolus data are compared to a limited sample of coincident ground-based Ka-band radar measurements at Iqaluit, Nunavut, to a larger set of coincident radiosonde measurements over the Canadian North, 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 of the first laser flight model (flight model A – FM-A; September to October 2018), the early phase of the second laser flight model (flight model B – FM-B; August to September 2019), and the middle phase of FM-B (December 2019 to January 2020). The adjusted r-squared between Aeolus and other local datasets is around 0.9 except for lower values for the comparison to the Ka-band radar, reflecting limited sampling opportunities with the radar data. This consistency is degraded by about 10 % for the Rayleigh winds in the summer due to solar background noise and other possible errors. 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 to 25 km a.g.l.). In all three periods, Aeolus standard deviations are found to be 5 % to 40 % greater than those from ECCC-B and ERA5. We found that the 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. Our work shows that the high quality of the Aeolus dataset that has been demonstrated globally applies to the sparsely sampled Arctic region. It also demonstrates the lack of available independent wind measurements in the Canadian North, lending urgency to the need to augment the observing capacity in this region to ensure suitable calibration and validation of future space-borne Doppler wind lidar (DWL) missions.

A statistically optimal analysis of systematic differences between Aeolus horizontal line-of-sight winds and NOAA's Global Forecast System

Abstract. The European Space Agency Aeolus mission launched a first-of-its-kind spaceborne Doppler wind lidar in August 2018. To optimize the assimilation of the Aeolus Level-2B (B10) horizontal line-of-sight (HLOS) winds, significant systematic differences between the observations and numerical weather prediction (NWP) background winds should be removed. Total least squares (TLS) regression is used to estimate speed-dependent systematic differences between the Aeolus HLOS winds and the National Oceanic and Atmospheric Administration (NOAA) Finite-Volume Cubed-Sphere Global Forecast System (FV3GFS) 6 h forecast winds. Unlike ordinary least squares regression, TLS regression optimally accounts for random errors in both predictors and predictands. Large, well-defined, speed-dependent systematic differences are found in the lower stratosphere and troposphere in the tropics and Southern Hemisphere. Correction of these systematic differences improves the forecast impact of Aeolus data assimilated into the NOAA global NWP system.

Optimization and impact assessment of Aeolus HLOS wind assimilation in NOAA's global forecast system

AbstractThe European Space Agency Aeolus mission launched the first‐of‐its‐kind space‐borne Doppler wind lidar in August 2018. The Aeolus Level‐2B (L2B) Horizontal Line‐of‐Sight (HLOS) wind observations are integrated into the NOAA Finite‐Volume Cubed‐Sphere Global Forecast System (FV3GFS). Components of the data assimilation system are optimized to increase the forecast impact from these Aeolus observations. Three observing‐system experiments (OSEs) are performed using the Aeolus L2B HLOS winds for the period of August 2–September 16, 2019: a baseline experiment assimilating all observations that are operationally assimilated in NOAA's FV3GFS but without Aeolus; an experiment adding the Aeolus L2B HLOS winds on top of the baseline configuration; and an experiment adding the Aeolus L2B HLOS winds on top of the baseline but also including a total least‐squares (TLS) regression bias correction applied to the HLOS winds. The variances of the Aeolus HLOS wind random errors (i.e., observation errors) are estimated using the Hollingsworth–Lonnberg (HL) method. Results from both OSEs demonstrate positive impact of Aeolus L2B HLOS winds on the NOAA global forecast. The largest impact is seen in the tropical upper troposphere and lower stratosphere where the Day 1–3 wind vector forecast root‐mean‐square error (RMSE) is reduced by up to 4%. Additionally, the assimilation of Aeolus impacts the steering currents ambient to tropical cyclones, resulting in a 15% reduction in track forecast error in the Eastern Pacific basin Day 2–5 forecasts, and a 5% and 20% reduction in track forecast error in the Atlantic basin at Day 2 and Day 5, respectively. In most cases, the additional TLS bias correction increases the positive impact of Aeolus data assimilation in the NOAA global numerical weather prediction (NWP) system when compared to the assimilation of Aeolus without bias correction.

Exploiting Aeolus level-2b winds to better characterize atmospheric motion vector bias and uncertainty

Abstract. The need for highly accurate atmospheric wind observations is a high priority in the science community, particularly for numerical weather prediction (NWP). To address this need, this study leverages Aeolus wind lidar level-2B data provided by the European Space Agency (ESA) as a potential comparison standard to better characterize atmospheric motion vector (AMV) bias and uncertainty. AMV products from geostationary (GEO) and low Earth orbiting (LEO) satellites are compared with reprocessed Aeolus horizontal line-of-sight (HLOS) global winds observed in August–September 2019. Winds from two Aeolus observing modes are compared with AMVs, namely Rayleigh-clear (RAY; derived from the molecular scattering signal) and Mie-cloudy (MIE; derived from the particle scattering signal). Quality-controlled (QC'd) Aeolus winds are co-located with QC'd AMVs in space and time, and the AMVs are projected onto the Aeolus HLOS direction. Mean co-location differences (MCDs) and the standard deviation (SD) of those differences (SDCDs) are determined and analyzed. As shown in other comparison studies, the level of agreement between AMV and Aeolus wind velocities (HLOSVs) varies with the AMV type, geographic region, and height of the co-located winds, as well as with the Aeolus observing mode. In terms of global statistics, QC'd AMVs and QC'd Aeolus HLOSVs are highly correlated for both observing modes. Aeolus MIE winds are shown to have great potential value as a comparison standard to characterize AMVs, as MIE co-locations generally exhibit smaller biases and uncertainties compared to RAY co-locations. Aeolus RAY winds contribute a substantial fraction of the total SDCDs in the presence of clouds where co-location/representativeness errors are also large. Stratified comparisons with Aeolus HLOSVs are consistent with known AMV bias and uncertainty in the tropics, NH extratropics, the Arctic, and at mid- to upper-levels in clear and cloudy scenes. AMVs in the SH/Antarctic generally exhibit larger-than-expected MCDs and SDCDs, most probably due to larger AMV height assignment errors and co-location/representativeness errors in the presence of high wind speeds and strong vertical wind shear, particularly for RAY comparisons.

Impact of the Aeolus Level‐2B horizontal line‐of‐sight winds in the Environment and Climate Change Canada global forecast system

AbstractThe European Space Agency Aeolus mission was launched in August 2018. This satellite carries the first Doppler lidar able to provide global measurements of wind profiles. Aeolus Level‐2B products have been generated and monitored by the European Centre for Medium‐Range Weather Forecasts (ECMWF) in near real‐time since a few weeks after the launch. These products include the horizontal line‐of‐sight (HLOS) winds that are suitable for data assimilation in numerical weather prediction systems. This article presents a series of observing system experiments conducted over summer 2019 to assess the value of the Level‐2B HLOS winds and their impact on the Environment and Climate Change Canada global forecasts. The impact of atmospheric motion vectors (AMVs) on forecasts is also examined and compared with the impact of HLOS winds. Two datasets are used: the HLOS winds produced in near real‐time at ECMWF and those reprocessed later in fall 2020. It is found that the near real‐time data are significantly biased and should be corrected. A look‐up table bias correction based on observation minus background departures is applied to this dataset as initially proposed by ECMWF. The reprocessed data are of better quality and bias corrected using the telescope's primary mirror temperature variations as predictor. The impacts of the near real‐time and reprocessed HLOS winds on forecasts are generally positive for both temperature and wind. The impacts are largest in the troposphere over the Tropics and polar regions. The positive impacts on forecasts are larger with the reprocessed data, particularly in the stratosphere, where a significant degradation over the Southern Hemisphere is found from assimilating the near real‐time data. The normalized forecast error reductions at days 1 and 2 for the wind are ∼1.25% over the Tropics and Southern Hemisphere. The positive impact of the HLOS winds on forecasts is enhanced by ∼40% when the AMVs are not assimilated in the control experiment. The forecast error reduction from assimilating AMVs is, however, two times larger than from assimilating HLOS winds in the extratropics. Conversely, the impact of HLOS winds on forecasts is generally larger in the Tropics.