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Correcting winds measured with a Rayleigh Doppler lidar from pressure and temperature effects
Abstract
The molecular channel of the space-based Doppler lidar ADM-Aeolus relies on a double Fabry–Perot (FP) interferometer. The difference in photon numbers transmitted by the two FPs divided by their sum- the so-called Rayleigh response—is a function of the central frequency of the spectrum of the laser light backscattered by the atmosphere, so that a proper inversion enables the measurement of Doppler shifts and line-of-sight wind velocities. In this paper, it is shown that the relation-ship between the Rayleigh response and the Doppler shift does not depend on the sole characteristics of the instrument, but also on the atmospheric pressure and temperature (through the Rayleigh–Brillouin effect), and the likely presence of a narrow-band radiation due to particle scattering. The impact of these on the precision of inverted Doppler shifts (or line-of-sight winds) is assessed showing that a correction is needed. As they are lacking the appropriate precision, climatology profiles of pressure, temperature or aerosols cannot be used as an input. It is proposed to use data predicted by a numerical weather prediction system instead. A possible correction scheme is proposed. Its implication on the quality of retrieved Rayleigh winds is discussed.
... Information from data assimilation backgrounds (i.e., short-term forecasts) are used to reduce errors in the L2B-retrieved Rayleigh winds in two correction procedures. First, background temperature and pressure are used in the Rayleigh-Brillouin correction (Dabas et al., 2008); second, the background estimates of the Rayleigh HLOS winds are used in the M1 telescope temperature correction Weiler et al., 2021). Operationally, the European Centre for Medium-Range Weather Forecasts (ECMWF) backgrounds are used for these corrections. ...
... First, ECMWF temperature and pressure are used in the Rayleigh-Brillouin correction (Dabas et al., 2008). Without this correction, the Aeolus Rayleigh observations could not reach the quality required by NWP users. ...
... Without this correction, the Aeolus Rayleigh observations could not reach the quality required by NWP users. Estimates based on a standard atmosphere (Dabas et al., 2008) suggest that Rayleigh wind retrieval is sensitive to temperature; and Rayleigh wind error is about a relative error of 0.1% of the true line-of-sight wind for 1 K error in temperature. A typical NWP model background error is a few kelvin. ...
The 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.
... This short wavelength was chosen in order to enhance the molecular backscatter and allow measurements at high altitudes where aerosols and clouds are scarce and cannot serve as wind tracers. ALADIN implements two detection channels, a narrow-band one for the analysis of the UV light back-scattered by the particles (hydro-meteors and aerosols) that display a narrow spectrum (the 20 full-width at half-maximum is of the order of a few tens of MHz), and a wide-band channel for the light back-scattered by the air molecules with a large spectrum (the full-width at half-maximum is several GHz) (Dabas et al., 2008). The former is called the Mie channel, and the latter the Rayleigh channel. ...
... This allows the independent measurement of the backscatter and extinction coefficients of aerosols or clouds (Flamant et al., 2008), and thus provides a direct measurement of the extinction to backscatter ratio called the "lidar ratio". This ratio gives 30 an additional piece of information on the type of particle (Ackermann, 1998;Noh et al., 2007;Yorks et al., 2011; Illingworth et al., 2015; Shen et al., 2021). ...
... A first description of the L2A processor can be found in Flamant et al. (2008). Since this publication, the processor has substantially evolved. ...
Aeolus carries ALADIN, the first High Spectral Resolution Lidar (HSRL) in space. Although ALADIN was optimized to measure winds, its two measurement channels can also be used to derive optical properties of atmospheric particles, including a direct retrieval of the lidar ratio. This paper presents the two main algorithms of the optical properties product called Level 2A product, as they are implemented in version 3.12 of the processor, corresponding to the data labelled Baseline 12. The theoretical basis is the same as in Flamant et al. (2008). Here, we also show the in orbit performance of these algorithms. We also explain the adaptation of the calibration method, which is needed to cope with unforeseen variations of the instrument radiometric performance due to the in-orbit strain of the primary mirror under varying thermal conditions. Then we discuss the limitations of the algorithms and future improvements. We demonstrate that the L2A product provides valuable information about airborne particles, in particular we demonstrate the capacity to retrieve a useful lidar ratio from Aeolus observations. This is illustrated on a case of Saharan dust emission, observed in June 2020.
... The information on temperature and pressure, needed for properly modelling such Rayleigh-Brillouin spectrum characteristics, which should be collocated with the Aeolus measurements, is, however, not provided by Aeolus, nor is it available from the current Global Observation System (GOS). Therefore, the suggestion of Dabas et al. (2008) was to infer this information from a NWP which, on the other hand, contains errors which typically consist of model and representativeness errors and also errors from initial conditions. The mean temperature forecast error is a well-monitored quantity; for example, it is monitored by the WMO Lead Centre for Deterministic Forecast Verification (WMO-LCDNV, https://apps.ecmwf.int/wmolcdnv/, ...
... The majority of the distribution of a global model temperature remains below 3 K even for longer forecast ranges. Estimations provided by Dabas et al. (2008) suggest that in a standard atmosphere the temperature sensitivity of HLOS retrieval brings a relative HLOS error of about 0.2 % for 1 K error in temperature, which is well below the 0.7 % relative error specified as an ESA requirement (ESA, 2016). On the other hand, HLOS sensitivity to pressure suggests providing about an order of magnitude smaller impact with a typical model pressure error of few hectopascals. ...
... One property of the HLOS sensitivity to temperature is its approximate linear dependency with HLOS wind velocity. The slope of the median curve is ∼ 0.002 K −1 , which is in good agreement with the value for the standard atmosphere given by Dabas et al. (2008). The variability shown by the two percentiles is mostly induced by the fact that inside each bin HLOS wind velocity varies by 10 m s −1 and is less effected by the fact that atmospheric conditions, i.e. temperature and pressure, vary significantly over the same range bin. ...
The retrieval of wind from the first Doppler wind lidar of European Space Agency (ESA) launched in space in August 2018 is based on a series of corrections necessary to provide observations of a quality useful for numerical weather prediction (NWP). In this paper we examine the properties of the Rayleigh–Brillouin correction necessary for the retrieval of horizontal line-of-sight wind (HLOS) from a Fabry–Pérot interferometer. This correction is taking into account the atmospheric stratification, namely temperature and pressure information that are provided by a NWP model as suggested prior to launch. The main goal of the study is to evaluate the impact of errors in simulated atmospheric temperature and pressure information on the HLOS sensitivity by comparing the Integrated Forecast System (IFS) and Action de Recherche Petite Echelle Grande Echelle (ARPEGE) global model temperature and pressure short-term forecasts collocated with the Aeolus orbit. These errors are currently not taken into account in the computation of the HLOS error estimate since its contribution is believed to be small. This study largely confirms this statement to be a valid assumption, although it also shows that model errors could locally (i.e. jet-stream regions, below 700 hPa over both earth poles and in stratosphere) be significant. For future Aeolus follow-on missions this study suggests considering realistic estimations of errors in the HLOS retrieval algorithms, since this will lead to an improved estimation of the Rayleigh–Brillouin sensitivity uncertainty contributing to the HLOS error estimate and better exploitation of space lidar winds in NWP systems.
... The majority of global model temperature remains below 3K even for longer forecast ranges. Estimations 45 provided by Dabas et al. (2008) suggest that in a standard atmosphere the temperature sensitivity of HLOS retrieval brings a relative HLOS error of about 0.2 % for 1 K error in temperature, which is well below the 0.7 % relative error specified as an ESA requirement (ESA, 2016). On the other hand, HLOS sensitivity to pressure is suggesting to provide about an order of magnitude smaller impact with typical model pressure errors of few hPa. ...
... The slope of the median curve is ∼0.002 K −1 which is in good agreement with the value for the standard atmosphere given by 230 Dabas et al. (2008). The variability shown by the two percentiles is mostly induced by the fact that inside each bin HLOS wind velocity varies by 10 ms −1 and is less effected by the fact that atmospheric conditions, i.e. temperature and pressure, vary significantly over the same range bin. ...
... In particular, the sensitivity shown in Fig. 3(b, d) indicates a median value (over all positive HLOS) of about 245 -0.002 ms −1 hPa −1 which is in range of expected values (e.g. 0.003 ms −1 hPa −1 for the standard atmosphere as shown by Dabas et al. (2008)). The variability of the sensitivity (Fig. 3b) becomes stronger with larger absolute HLOS winds, which is induced by the effect of variable temperature and pressure conditions in a given HLOS bin. ...
The retrieval of wind from the first Doppler wind lidar of Europen Space Agency (ESA) launched in space in August 2018 is based on a series of corrections necessary to provide observations of a quality useful for Numerical Weather Prediction (NWP). In this paper we examine properties of the Rayleigh-Brillouin correction necessary for the retrieval of horizontal line-of-sight wind (HLOS) from a Fabry-Perot interferometer. This correction is taking into account the atmospheric stratification, namely temperature and pressure information that are provided by a NWP model as suggested prior launch. Since NWP models contain errors the main goal in the study is to evaluate the impact of these errors on the HLOS sensitivity by comparing the Integrated Forecast System (IFS) and Action de Recherche Petite Echelle Grande Echelle (ARPEGE) global model temperature and pressure short term forecasts collocated with the Aeolus orbit. The model error is currently not taken into account in the computation of the HLOS error estimate since its contribution is believed small. This study largely confirms this statement to be a valid assumption, although it also shows that model errors could locally (i.e. jet-stream regions, below 700 hPa over both earth poles and as well in stratosphere) be significant. For a future Aeolus follow-on missions this study suggests to consider realistic estimations of model errors in the HLOS retrieval algorithms, since this will lead to an improved estimation of the Rayleigh-Brillouin sensitivity uncertainty contributing to the HLOS error estimate and better exploitation of space lidar winds in NWP systems.
... Scattering of the laser signal occurs from molecules in the atmosphere by Rayleigh scattering, and from hydrometeors and aerosols by Mie scattering (Reitebuch, 2012). The return signal is filtered into two channels for the Mie and Rayleigh scattering, although there is some contamination between the channels that is accounted for in the processing (Dabas et al., 2008). Nineteen laser pulses are used to produce a measurement, giving a basic horizontal resolution of approximately 2.9 km (Lux et al., 2020). ...
The 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.
... Water vapor in the air substantially absorbs and scatters UV radiation, altering Doppler shifts at high RH. This impacts wind retrieval by deviating from the dry air conditions assumed [5,21,34]. ...
This study validated Aeolus wind observations over China from October 2020 to September 2022 using the Integrated Global Radiosonde Archive (IGRA). The results showed that most of the Aeolus observations were in good agreement with the IGRA observations. The quality of Aeolus Rayleigh-clear winds is superior to that of Mie-cloudy winds, and the wind products for ascending orbits are superior to those for descending orbits. The biases between Rayleigh-clear (Mie-cloudy) and IGRA winds are 0.61 (0.87), −0.01 (0.81), and 1.12 (1.59) m s⁻¹ for the total, ascending and descending Aeolus orbits, respectively. Further classification study based on cloud height and relative humidity reveals that the quality of Mie-cloudy winds improves with cloud altitude until stratosphere, and Rayleigh-clear winds deteriorate for high relative humidity. The results provide a basis for quality control and error correction of Aeolus wind observations.
... Designed as a high-spectral-resolution lidar with a laser wavelength of 354.8 nm, ALADIN has the capability to simultaneously acquire wind profiles and particle optical properties with its two separate optical frequency discrimination channels named Rayleigh channel and Mie channel. Detailed descriptions of the instrument design and the measurement concept are introduced in, for example, Ansmann et al. (2007), Dabas et al. (2008), Flamant et al. (2008), Reitebuch (2012), Lux et al. (2020), andFlament et al. (2021). ...
Marine aerosol affects the global energy budget and regional weather. The production of marine aerosol is primarily driven by wind at the sea–air interface. Previous studies have explored the effects of wind on marine aerosol, mostly by examining the relationships between aerosol optical depth (AOD) and surface wind speed. In this paper, utilizing the synergy of aerosol and wind observations from Aeolus, the relationships between the marine aerosol optical properties at 355 nm and the instantaneous co-located wind speeds of remote oceans are investigated at two vertical layers (within and above the marine atmospheric boundary layer (MABL)). The results show that the enhancements of the extinction and backscatter coefficients caused by wind are larger within the MABL than above it. The correlation models between extinction and backscatter with wind speed were established using power-law functions. The slope variation points occur during extinction and backscatter coefficients increasing with wind speed, indicating that the wind-driven enhancement of marine aerosol involves two phases: a rapid-growth phase with high wind dependence, followed by a slower-growth phase after the slope variation points. We also compared the AOD–wind relationship acquired from Aeolus with CALIPSO-derived results from previous research. The variation in the lidar ratio with wind speed is examined, suggesting a possible “increasing–decreasing–increasing” trend of marine aerosol particle size as wind speed increases. This study enhances the comprehension of the correlation between marine aerosol optical properties and wind speed by providing vertical information and demonstrating that their relationships are more complex than a linear or exponential relation.
... There are also known biases in the Aeolus winds that might make these data less than ideal as a comparison standard. However, these have largely been eliminated by procedures for calibration [38] and for corrections, including the Rayleigh-Brillouin correction [39], the telescope temperature correction [40,41], and the dark current correction [42]. Figure 2 shows the mapped number densities or counts per grid cell of QC'd Aeolus winds for the study period (00 UTC 1 September 2019 through 18 UTC 31 August 2020) prior to collocation. ...
Accurate atmospheric 3D wind observations are one of the top priorities for the global scientific community. To address this requirement, and to support researchers’ needs to acquire and analyze wind data from multiple sources, the System for Analysis of Wind Collocations (SAWC) was jointly developed by NOAA/NESDIS/STAR, UMD/ESSIC/CISESS, and UW-Madison/CIMSS. SAWC encompasses the following: a multi-year archive of global 3D winds observed by Aeolus, sondes, aircraft, stratospheric superpressure balloons, and satellite-derived atmospheric motion vectors, archived and uniformly formatted in netCDF for public consumption; identified pairings between select datasets collocated in space and time; and a downloadable software application developed for users to interactively collocate and statistically compare wind observations based on their research needs. The utility of SAWC is demonstrated by conducting a one-year (September 2019–August 2020) evaluation of Aeolus level-2B (L2B) winds (Baseline 11 L2B processor version). Observations from four archived conventional wind datasets are collocated with Aeolus. The recommended quality controls are applied. Wind comparisons are assessed using the SAWC collocation application. Comparison statistics are stratified by season, geographic region, and Aeolus observing mode. The results highlight the value of SAWC’s capabilities, from product validation through intercomparison studies to the evaluation of data usage in applications and advances in the global Earth observing architecture.
... Only data with flags equal to 1 were considered valid. The data were subsequently filtered according to estimated errors, and the theoretical values were calculated based on the measured signal levels, as well as the temperature and pressure sensitivity of the Rayleigh channel response (Dabas et al., 2008). Previous studies have revealed that notable observation errors appeared when the estimated errors were large (Witschas et al., 2020). ...
Observations of the vertical wind profile in Chongqing, a typical mountainous city in China, are important, but they are sparse and have low resolution. To obtain more wind profile data, this study matched the Aeolus track with ground-based wind observation sites in Chongqing in 2021. Based on the obtained results, verification and quality control studies were conducted on the wind observations of a wind profile radar (WPR) with radiosonde (RS) data, and a comparison of the Aeolus Mie-cloudy and Rayleigh-clear wind products (Aeolus winds measured in cloudy and aerosol-rich atmospheric conditions from Mie-channel-collected data and winds measured in clear-air conditions from Rayleigh-collected data) with WPR data was then performed. The conclusions can be summarized as follows: (1) a clear correlation between the wind observations of WPR and RS was found, with a correlation coefficient (R) of 0.71. Their root mean square deviation increased with height but decreased at heights between 3 and 4 km. (2) After quality control using Gaussian filtering (GF) and empirical orthogonal function construction (EOFc; G=87.23 %) of the WPR data, the R between the WPR and RS reached 0.83 and 0.95, respectively. The vertical distribution showed that GF could better retain the characteristics of WPR wind observations but with limited improvement in decreasing deviations, whereas EOFc performed better in decreasing deviations but considerably modified the original characteristics of the wind field, especially regarding intensive vertical wind shear in strong convective weather processes. (3) In terms of the differences between the Aeolus and WPR data, 56.0 % and 67.8 % deviations were observed within ±5 m s-1 for Rayleigh-clear and Mie-cloudy winds (Aeolus winds measured in cloudy and aerosol-rich atmospheric conditions from Mie-channel-collected data and winds measured in clear-air conditions from Rayleigh-collected data) vs WPR winds, respectively. Vertically, large mean differences of both Rayleigh-clean and Mie-cloudy winds versus WPR winds appeared below 1.5 km, which is attributed to the prevailing quiet and small winds within the boundary layer in Chongqing; in this case the movement of molecules and aerosols is mostly affected by irregular turbulence. Additionally, large mean differences at a height range between 4 and 8 km for Mie-cloudy versus WPR winds may be related to the high content of cloud liquid water in the middle troposphere of Chongqing. (4) The differences in both Rayleigh-clear and Mie-cloudy versus WPR winds had changed. Deviations of 58.9 % and 59.6 % were concentrated within ±5 m s-1 for Rayleigh-clear versus WPR winds with GF and EOFc quality control, respectively. In contrast, 69.1 % and 70.2 % of deviations appeared within ±5 m s-1 for Rayleigh-clear versus WPR and EOFc WPR winds, respectively. These results shed light on the comprehensive applications of multi-source wind profile data in mountainous cities or areas with sparse ground-based wind observations.
... This was implemented in March 2019. To avoid the systematic errors caused by the Rayleigh-Brillouin scattering, corrections are made for the temperature and pressure dependence of Rayleigh data using a priori information from the ECMWF model (Dabas et al., 2008). Moreover, the wind data are retrieved in 24 bins in the vertical in which the resolution varies from 0.25 km near the surface to 2 km at the higher levels. ...
The impact of using wind observations from the Aeolus satellite in a limited-area numerical weather prediction (NWP) system is being investigated using the limited-area NWP model Harmonie–Arome over the Nordic region. We assimilate the horizontal line-of-sight (HLOS) winds observed by Aeolus using 3D-Var data assimilation for two different periods, one in September–October 2018 when the satellite was recently launched and a later period in April–May 2020 to investigate the updated data processing of the HLOS winds. We find that the quality of the Aeolus observations has degraded between the first and second experiment period over our domain. However, observations from Aeolus, in particular the Mie winds, have a clear impact on the analysis of the NWP model for both periods, whereas the forecast impact is neutral when compared against radiosondes. Results from evaluation of observation minus background and observation minus analysis departures based on Desroziers diagnostics show that the observation error should be increased for Aeolus data in our experiments, but the impact of doing so is small. We also see that there is potential improvement in using 4D-Var data assimilation, which generates flow-dependent analysis increments, with the Aeolus data.
... To correct for temperature and pressure effects in the Rayleigh wind retrieval, profiles of temperature and pressure are used from the ECMWF model forecast (e.g., Dabas et al., 2008;Šavli et al., 2021). These data are included in the auxiliary meteorological data product (AUX_MET), which is described further in Section 2.3. ...
The 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 m·s, 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 m·s 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 m·s. 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.
... Finally, the current algorithm used to derive the LOS wind speed is applied only to low SRs to minimize the effect of the presence of aerosols on the sensitivity of Rayleigh-Brillouin scattering measurements. In future studies, we will improve the current algorithm so that it is functional for high-load aerosols and clouds [43]. ...
A compact and simple 355-nm direct-detection Doppler wind lidar (DDDWL) was developed to measure the line-of-sight (LOS) wind speed of the background atmosphere from atmospheric molecule return signals with and without aerosols and clouds. A receiver design with a Fabry–Perot etalon interferometer (FPEI) without an inside deposited step coating or fiber coupling is considered for the DDDWL using the double-edge technique. The receiver with the double-edge technique uses a FPEI and wedge prism to form a double-edge filter. The development of the double-edge filter in this combination is, to the best of our knowledge, an improvement at 355-nm wavelength. Considerations for the DDDWL receiver with a FPEI revealed that a full-angle light beam divergence into the FPEI and a working FPEI aperture are significant factors for the receiver design. Preliminary experimental evaluation demonstrated that the DDDWL had the potential of LOS wind speed measurements with a random error of less than 1 m/s when the signal-to-noise ratio was approximately 300. The DDDWL-measured vertical LOS wind speed profile was consistent with that of a 2-µm coherent Doppler wind lidar within the measurement error range. The preliminary experimental LOS wind measurement results demonstrated the capability of the DDDWL to measure low LOS wind speeds.
... The derivative of the HLOS wind with respect to pressure and temperature is also provided to make a correction to the HLOS winds from the Rayleigh channel using the difference between the background values and those used at ECMWF to process these data. However, this correction is generally smaller than 0.1 m⋅s −1 (Dabas et al., 2008;Salvi et al., 2021) and thus not applied in this study. ...
The 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.
... In addition to HLOS observations, the Aeolus L2B processor developed by ECMWF and the Royal Netherlands Meteorological Institute (KNMI) provides an observation instrument noise estimate. Furthermore, to reduce systematic errors, corrections for the temperature and pressure dependence of the Rayleigh winds are performed using a priori information from the ECMWF model interpolated along the Aeolus track (Dabas et al., 2008). The measurements within an observation are classified into an observation type, clear or cloudy, using measurement-scale (2.9 km) optical properties, such as scattering ratio. ...
In August 2018, the first Doppler wind lidar, developed by the European Space Agency (ESA), was launched on board the Aeolus satellite into space. Providing atmospheric wind profiles on a global basis, the Earth Explorer mission is expected to demonstrate improvements in the quality of numerical weather prediction (NWP). For the use of Aeolus observations in NWP data assimilation, a detailed characterization of the quality and the minimization of systematic errors is crucial. This study performs a statistical validation of Aeolus observations, using collocated radiosonde measurements and NWP forecast equivalents from two different global models, the ICOsahedral Nonhydrostatic model (ICON) of Deutscher Wetterdienst (DWD) and the European Centre for Medium-Range Weather Forecast (ECMWF) Integrated Forecast System (IFS) model, as reference data. For the time period from the satellite's launch to the end of December 2019, comparisons for the Northern Hemisphere (23.5–65∘ N) show strong variations of the Aeolus wind bias and differences between the ascending and descending orbit phase. The mean absolute bias for the selected validation area is found to be in the range of 1.8–2.3 ms-1 (Rayleigh) and 1.3–1.9 ms-1 (Mie), showing good agreement between the three independent reference data sets. Due to the greater representativeness errors associated with the comparisons using radiosonde observations, the random differences are larger for the validation with radiosondes compared to the model equivalent statistics. To achieve an estimate for the Aeolus instrumental error, the representativeness errors for the comparisons are determined, as well as the estimation of the model and radiosonde observational error. The resulting Aeolus error estimates are in the range of 4.1–4.4 ms-1 (Rayleigh) and 1.9–3.0 ms-1 (Mie). Investigations of the Rayleigh wind bias on a global scale show that in addition to the satellite flight direction and seasonal differences, the systematic differences vary with latitude. A latitude-based bias correction approach is able to reduce the bias, but a residual bias of 0.4–0.6 ms-1 with a temporal trend remains. Taking additional longitudinal differences into account, the bias can be reduced further by almost 50 %. Longitudinal variations are suggested to be linked to land–sea distribution and tropical convection that influences the thermal emission of the earth. Since 20 April 2020 a telescope temperature-based bias correction scheme has been applied operationally in the L2B processor, developed by the Aeolus Data Innovation and Science Cluster (DISC).
... The observations are then made by averaging up to 30 individual measurements for both Rayleigh and Mie channels which results in a horizontally averaged wind data of about 80 km. The higher signal-to-noise ratio observed for the Mie channel made it possible to have the horizontal integration length being decreased dependence of Rayleigh data using a priori information from the ECMWF model (Dabas et al., 2008). Moreover, the wind data is retrieved in 24 bins in the vertical where the resolution varies from 0.25 km near the surface to 2 km at the higher levels. ...
The impact of using wind speed data from the Aeolus satellite in a limited area Numerical Weather Prediction (NWP) system is being investigated using the limited area NWP model Harmonie-Arome over the Nordic region. We assimilate the Horizontal Line of Sight (HLOS) winds observed by Aeolus using 3D-Var data assimilation for two different periods, one in Sept–Oct 2018 when the satellite was recently launched, and a later period in Apr–May 2020 to investigate the updated data processing of the HLOS winds. We find that the quality of the Aeolus observations have degraded between the first and second experiment period over our domain. However observations from Aeolus, in particular the Mie winds, have a clear impact on the analysis of the NWP model for both periods whereas the forecast impact is neutral when compared against radiosondes. Results from evaluation of observation minus background and observation minus analysis departures based on Desroziers diagnostics show that the observation error should be increased for Aeolus data in our experiments, but the impact of doing so is small. We also see that there is potential improvement in using 4D-Var data assimilation, which generate flow-dependent analysis increments, with the Aeolus data.
... Few reports are available regarding the influence of the backscattering ratio and temperature and wind correction in the troposphere [29,30]. The influence of temperature and the backscattering ratio on the Doppler frequency shift of the Mie scattering spectrum used for wind measurement and its offset is analyzed in this paper. ...
A high spectral resolution lidar (HSRL) for simultaneously detecting vertical wind, temperature, and the backscattering ratio in the troposphere is developed. The atmospheric temperature and vertical wind are determined by the Rayleigh scattering spectrum width and Mie scattering spectrum Doppler shift, respectively. The influence of temperature and the backscattering ratio on vertical wind measurement accuracy is also analyzed. The temperature and backscattering ratio affect the wind measurement, which produces the vertical wind offset. A correction considering the effects of the method is conducted considering real-time and on-site temperature profiles and the backscattering ratio to correct wind measurement sensitivity. Measurements of HSRL taken under different weather conditions (fine and hazy days) are demonstrated. Good agreement between the HSRL and the radiosonde measurements was obtained considering lapse rates and temperature inversions. The maximum temperature offsets were 1.3 and 4 K at a height of 1.5 km on fine and hazy days, respectively. Then, real-time and on-site temperature profiles and backscattering ratios were applied to correct the real-time and on-site wind. The corrected wind profiles showed satisfactory agreement with the wind profiles acquired from the calibrated wind lidar. The maximum detection offsets of the retrieved wind speed were reduced from 1 m/s to 0.55 m/s and from 1 m/s to 0.21 m/s, respectively, which were decreases of 0.45 and 0.79 m/s in fine and hazy days after correction of sensitivity. It is evident that the corrected wind method can reduce the influence of temperature and the backscattering ratio on the wind measurement and the offset of vertical wind. The reliability of the method is also proven.
... Different instrument response calibration approaches have been studied using both measured and simulated response calibration to characterize and calibrate the ALADIN Rayleigh channel (Tan et al., 2008;Dabas et al., 2008;Rennie et al., 2017). Currently, only measured Rayleigh response calibrations (MRRC) are used for the A2D (Marksteiner, 2013;Lux et al., 2018;Marksteiner et al., 2018). ...
Aeolus, launched on 22 August in 2018, is the first ever satellite to directly observe wind information from the surface up to 30 km on a global scale. An airborne prototype instrument called ALADIN airborne demonstrator (A2D) was developed at the German Aerospace Center (DLR) for validating the Aeolus measurement principle based on realistic atmospheric signals. To obtain accurate wind retrievals, the A2D uses a measured Rayleigh response calibration (MRRC) to calibrate its Rayleigh channel signals. However, differences exist between the respective atmospheric temperature profiles that are present during the conduction of the MRRC and the actual wind measurements. These differences are an important source of wind bias since the atmospheric temperature has a direct effect on the instrument response calibration. Furthermore, some experimental limitations and requirements need to be considered carefully to achieve a reliable MRRC. The atmospheric and instrumental variability thus currently limit the reliability and repeatability of a MRRC. In this paper, a procedure for a simulated Rayleigh response calibration (SRRC) is developed and presented in order to resolve these limitations of the A2D MRRC. At first the transmission functions of the A2D Rayleigh channel double-edge Fabry–Pérot interferometers (FPIs) in the internal reference path and the atmospheric path are characterized and optimized based on measurements performed during different airborne and ground-based campaigns. The optimized FPI transmission functions are then combined with the laser reference spectrum and the temperature-dependent molecular Rayleigh backscatter spectrum to derive an accurate A2D SRRC which can finally be implemented into the wind retrieval. Using dropsonde data as a reference, a statistical analysis based on a dataset from a flight campaign in 2016 reveals a bias and a standard deviation of line-of-sight (LOS) wind speeds derived from a SRRC of only 0.05 and 2.52 m s-1, respectively. Compared to the result derived from a MRRC with a bias of 0.23 m s-1 and a standard deviation of 2.20 m s-1, the accuracy improved and the precision is considered to be at the same level. Furthermore, it is shown that the SRRC allows for the simulation of receiver responses over the whole altitude range from the aircraft down to sea level, thus overcoming limitations due to high ground elevation during the acquisition of an airborne instrument response calibration.
... As the first ever airborne direct detection wind lidar, A2D has been deployed in several ground and airborne campaigns over the last 12 years (Li et al., 2010;Marksteiner, 2013;Weiler, 2017;Lux et al., 2018;Marksteiner et al., 2018). 5 Different instrument response calibration approaches have been studied using both measurement and simulation to characterize or rather calibrate the ALADIN Rayleigh channel (Tan et al., 2008;Dabas et al., 2008;Rennie et al., 2017). ...
Aeolus, launched on 22 August in 2018, is the first ever satellite to directly observe wind information from the surface up to 30 km on a global scale. An airborne prototype instrument called ALADIN airborne demonstrator (A2D) was developed at the German Aerospace Center (DLR) for validating the Aeolus measurement principle based on realistic atmospheric signals. To obtain accurate wind retrievals, the A2D uses a measured Rayleigh response calibration (MRRC) to calibrate its Rayleigh channel signals. However, differences exist between the respective atmospheric temperature profiles that are present during the conduction of the MRRC and the actual wind measurements. These differences are an important source of wind bias since the atmospheric temperature has a direct effect on the instrument response calibration. Furthermore, some experimental limitations and requirements need to be considered carefully to achieve a reliable MRRC. The atmospheric and instrumental variability thus currently limit the reliability and repeatability of a MRRC. In this paper, a procedure for a simulated Rayleigh response calibration (SRRC) is developed and presented in order to resolve these limitations of the A2D MRRC. At first the transmission functions of the A2D Rayleigh channel double-edge Fabry-Pérot interferometers (FPIs) in the internal reference path and the atmospheric path are characterized and optimized based on measurements performed during different airborne and ground-based campaigns. The optimized FPI transmission functions are then combined with the laser reference spectrum and the temperature-dependent molecular Rayleigh backscatter spectrum to derive an accurate A2D SRRC which can finally be implemented into the wind retrieval. Using dropsonde data as a reference, a statistical analysis based on a dataset from a flight campaign in 2016 reveals a bias and a standard deviation of line-of-sight (LOS) wind speeds derived from a SRRC of only 0.05 and 2.52 m/s, respectively. Compared to the result derived from a MRRC with a bias of 0.23 m/s and a standard deviation of 2.20 m/s, the accuracy improved and the precision is considered to be at the same level. Furthermore, it is shown that the SRRC allows for the simulation of receiver responses over the whole altitude range from the aircraft down to sea level, thus overcoming limitations due to high ground elevation during the acquisition of an airborne instrument response calibration.
... The Lidar system aims to perform wind measurements over 15 km altitude during both daytime and nighttime. In such altitude, the inelastic Brillouin scattering and the elastic Mie scattering can be ignored for most occasions except the existence of polar stratospheric clouds or aerosols from volcano eruptions [38,39]. The spectrum of dominated Rayleigh backscatter is thermally broadened and can be approximated by a Gaussian lineshape, ...
A well-designed filter assembly is incorporated to an earlier mobile Rayleigh Doppler Lidar developed at University of Science and Technology of China (USTC) for wind measurement round the clock. The filter assembly consists of two cascaded Fabry-Perot Etalons (FPEs) and a narrow-band interference filter (IF), which are optimized to filter out strong solar background radiation during daytime. The high resolution FPE is mainly used to compress the whole bandwidth of the filter assembly, whereas the low resolution FPE with relatively large free spectral range (FSR) is primarily used to block the unwanted periodic transmission peaks of high resolution FPE arising within the narrow-band IF passband. Some test experiments are carried out and demonstrate that the filter assembly have an overall peak transmission of 33.32% with a bandwidth of 2.41 pm at 355 nm. When applying it to the USTC mobile Rayleigh Doppler Lidar, the daytime background is only 3% or less than before. Consequently, the detectable altitude during daytime increases to ∼51 km with wind velocity accuracy of ±7.6 m/s.
The Joint Aeolus Tropical Atlantic Campaign (JATAC) conducted 2022 in Cabo Verde has provided quantitative lidar measurements, in particular from the NASA Langley High Altitude Lidar Observatory (HALO) on-board DC-8 aircraft, for process level understanding of tropical dynamics, as well as for satellite validation. For the first time, optical properties of particles (i.e., backscatter, extinction, attenuated backscatter, and depolarization coefficients) have been measured for extended tropospheric sections collocated with the Aeolus satellite overpasses with limited geolocation and time offsets. This has contributed to the evaluation of the Aeolus Level-2A (L2A) aerosol optical properties product. In addition, localized aerosol profiles were measured by the ground-based multiwavelength Raman polarization and water-vapor lidar PollyXT. With this study, we assess the quality of the Aeolus L2A product retrieved with the Standard Correct Algorithm (SCA) and the Maximum Likelihood Estimation (MLE) as part of the September 2022 dataset reprocessed with the L2A processor version 16. The focus is given to the 355 nm aerosol retrievals given at finer horizontal resolution, i.e., so-called Aeolus measurement level of ≈ 18 km. They are compared to the 532 nm HALO airborne profiles which are converted to 355 nm using the backscatter Angstrom exponent. HALO and PollyXT polarization lidars also provide insights about the L2A algorithms limitations when looking at non-spherical particles such as Saharan dust. Even though having no cross-polarized component the Aeolus measurements can be corrected using collocated observations with such instruments that include both co-polarized and cross-polarized components of the backscattered light. Moreover the cross with independent lidar measurements allows to estimate lower limits for Aeolus backscatter detection.
Since its launch by the European Space Agency in 2018, the Aeolus satellite has been using the first Doppler wind lidar in space to acquire three-dimensional atmospheric wind profiles around the globe. Especially in the tropics, these observations compensate for the currently limited number of other wind observations, making an assessment of the quality of Aeolus wind products in this region crucial for numerical weather prediction. To evaluate the quality of the Aeolus L2B wind products across the tropical Atlantic Ocean, 20 radiosondes corresponding to Aeolus overpasses were launched from the islands of Sal, Saint Croix, and Puerto Rico during August–September 2021 as part of the Joint Aeolus Tropical Atlantic Campaign. During this period, Aeolus sampled winds within a complex environment with a variety of cloud types in the vicinity of the Intertropical Convergence Zone and aerosol particles from Saharan dust outbreaks. On average, the validation for Aeolus Rayleigh-clear revealed a random error of 3.8–4.3 m s-1 between 2 and 16 km, and 4.3–4.8 m s-1 between 16 and 20 km, with a systematic error of -0.5±0.2 m s-1. For Mie-cloudy, the random error between 2 and 16 km is 1.1–2.3 m s-1 and the systematic error is -0.9±0.3 m s-1. It is therefore concluded that Rayleigh-clear winds do not meet the mission's random error requirement, while Mie winds most likely do not fulfil the mission bias requirement. Below clouds or within dust layers, the quality of Rayleigh-clear observations are degraded when the useful signal is reduced. In these conditions, we also noticed an underestimation of the L2B estimated error. Gross outliers, defined as large deviations from the radiosonde data, but with low error estimates, account for less than 5 % of the data. These outliers appear at all altitudes and under all environmental conditions; however, their root cause remains unknown. Finally, we confirm the presence of an orbital-dependent bias observed with both radiosondes and European Centre for Medium-Range Weather Forecasts model equivalents. The results of this study contribute to a better characterisation of the Aeolus wind product in different atmospheric conditions and provide valuable information for further improvement of the wind retrieval algorithm.
Aeolus carried the first Doppler wind lidar to measure wind profiles from space. Aeolus was a European Space Agency explorer mission with the objective to retrieve winds data from the collected atmospheric return signal that is the result of Mie and Rayleigh scattering of laser emitted light by atmospheric molecules and particulates. During the course of the mission the quality of Aeolus winds measured in clear‐air conditions from Rayleigh‐channel‐collected data, so called Rayleigh‐clear winds, improved substantially. The same is true for winds measured in cloudy and aerosol‐rich atmospheric conditions from Mie‐channel‐collected data, the so‐called Mie‐cloudy winds. For the latter conditions, good quality winds can in principle also be obtained from Rayleigh‐channel‐collected data, the so‐called Rayleigh‐cloudy winds, if contamination of the purely molecular signal by Mie scattering is well addressed. We assess a linear and nonlinear correction for Mie contamination, the latter with the aid of numerical weather prediction model data for determing the correction parameters. We show that the nonlinear correction is able to provide unbiased Rayleigh‐cloudy winds. This makes Rayleigh‐cloudy winds suitable for use in numerical weather prediction, but also for direct comparison with other wind observations obtained in cloudy conditions, such as atmospheric motion wind vectors.
Global 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.
Aeolus is the first satellite mission to acquire vertical profiles of horizontal line‐of‐sight winds globally and thus fills an important gap in the Global Observing System, most notably in the Tropics. This study explores the impact of this dataset on analyses and forecasts from the European Centre for Medium‐Range Weather Forecasts (ECMWF) and Deutscher Wetterdienst (DWD), focusing specifically on the West African Monsoon (WAM) circulation during the boreal summers of 2019 and 2020. The WAM is notoriously challenging to forecast and is characterized by prominent and robust large‐scale circulation features such as the African Easterly Jet North (AEJ‐North) and Tropical Easterly Jet (TEJ). Assimilating Aeolus generally improves the prediction of zonal winds in both forecasting systems, especially for lead times above 24 h. These improvements are related to systematic differences in the representation of the two jets, with the AEJ‐North weakened at its southern flank in the western Sahel in the ECMWF analysis, while no obvious systematic differences are seen in the DWD analysis. In addition, the TEJ core is weakened in the ECMWF analysis and strengthened on its southern edge in the DWD analysis. The regions where the influence of Aeolus on the analysis is greatest correspond to the Intertropical Convergence Zone (ITCZ) region for ECMWF and generally the upper troposphere for DWD. In addition, we show the presence of an altitude‐ and orbit‐dependent bias in the Rayleigh‐clear channel, which causes the zonal winds to speed up and slow down diurnally. Applying a temperature‐dependent bias correction to this channel contributes to a more accurate representation of the diurnal cycle and improved prediction of the WAM winds. These improvements are encouraging for future investigations of the influence of Aeolus data on African Easterly Waves and associated Mesoscale Convective Systems.
During the first 3 years of the European Space Agency's Aeolus mission, the German Aerospace Center (Deutsches Zentrum für Luft- und Raumfahrt, DLR) performed four airborne campaigns deploying two different Doppler wind lidars (DWL) on board the DLR Falcon aircraft, aiming to validate the quality of the recent Aeolus Level 2B (L2B) wind data product (processor baseline 11 and 12). The first two campaigns, WindVal III (November–December 2018) and AVATAR-E (Aeolus Validation Through Airborne Lidars in Europe, May and June 2019), were conducted in Europe and provided first insights into the data quality at the beginning of the mission phase. The two later campaigns, AVATAR-I (Aeolus Validation Through Airborne Lidars in Iceland) and AVATAR-T (Aeolus Validation Through Airborne Lidars in the Tropics), were performed in regions of particular interest for the Aeolus validation: AVATAR-I was conducted from Keflavik, Iceland, between 9 September and 1 October 2019 to sample the high wind speeds in the vicinity of the polar jet stream; AVATAR-T was carried out from Sal, Cape Verde, between 6 and 28 September 2021 to measure winds in the Saharan dust-laden African easterly jet. Altogether, 10 Aeolus underflights were performed during AVATAR-I and 11 underflights during AVATAR-T, covering about 8000 and 11 000 km along the Aeolus measurement track, respectively. Based on these collocated measurements, statistical comparisons of Aeolus data with the reference lidar (2 µm DWL) as well as with in situ measurements by the Falcon were performed to determine the systematic and random errors of Rayleigh-clear and Mie-cloudy winds that are contained in the Aeolus L2B product. It is demonstrated that the systematic error almost fulfills the mission requirement of being below 0.7 m s-1 for both Rayleigh-clear and Mie-cloudy winds. The random error is shown to vary between 5.5 and 7.1 m s-1 for Rayleigh-clear winds and is thus larger than specified (2.5 m s-1), whereas it is close to the specifications for Mie-cloudy winds (2.7to2.9 m s-1). In addition, the dependency of the systematic and random errors on the actual wind speed, the geolocation, the scattering ratio, and the time difference between 2 µm DWL observation and satellite overflight is investigated and discussed. Thus, this work contributes to the characterization of the Aeolus data quality in different meteorological situations and allows one to investigate wind retrieval algorithm improvements for reprocessed Aeolus data sets.
Since the start of the European Space Agency's Aeolus mission in 2018, various studies were dedicated to the evaluation of its wind data quality and particularly to the determination of the systematic and random errors in the Rayleigh-clear and Mie-cloudy wind results provided in the Aeolus Level-2B (L2B) product. The quality control (QC) schemes applied in the analyses mostly rely on the estimated error (EE), reported in the L2B data, using different and often subjectively chosen thresholds for rejecting data outliers, thus hampering the comparability of different validation studies. This work gives insight into the calculation of the EE for the two receiver channels and reveals its limitations as a measure of the actual wind error due to its spatial and temporal variability. It is demonstrated that a precise error assessment of the Aeolus winds necessitates a careful statistical analysis, including a rigorous screening for gross errors to be compliant with the error definitions formulated in the Aeolus mission requirements. To this end, the modified Z score and normal quantile plots are shown to be useful statistical tools for effectively eliminating gross errors and for evaluating the normality of the wind error distribution in dependence on the applied QC scheme, respectively. The influence of different QC approaches and thresholds on key statistical parameters is discussed in the context of the Joint Aeolus Tropical Atlantic Campaign (JATAC), which was conducted in Cabo Verde in September 2021. Aeolus winds are compared against model background data from the European Centre for Medium-Range Weather Forecasts (ECMWF) before the assimilation of Aeolus winds and against wind data measured with the 2 µm heterodyne detection Doppler wind lidar (DWL) aboard the Falcon aircraft. The two studies make evident that the error distribution of the Mie-cloudy winds is strongly skewed with a preponderance of positively biased wind results distorting the statistics if not filtered out properly. Effective outlier removal is accomplished by applying a two-step QC based on the EE and the modified Z score, thereby ensuring an error distribution with a high degree of normality while retaining a large portion of wind results from the original dataset. After the utilization of the described QC approach, the systematic errors in the L2B Rayleigh-clear and Mie-cloudy winds are determined to be below 0.3 m s-1 with respect to both the ECMWF model background and the 2 µm DWL. Differences in the random errors relative to the two reference datasets (Mie vs. model is 5.3 m s-1, Mie vs. DWL is 4.1 m s-1, Rayleigh vs. model is 7.8 m s-1, and Rayleigh vs. DWL is 8.2 m s-1) are elaborated in the text.
In August 2018, the European Space Agency (ESA) launched the first Doppler wind lidar into space, which has since then been providing continuous profiles of the horizontal line-of-sight wind component at a global scale. Aeolus data have been successfully assimilated into several numerical weather prediction (NWP) models and demonstrated a positive impact on the quality of the weather forecasts. To provide valuable input data for NWP models, a detailed characterization of the Aeolus instrumental performance as well as the realization and minimization of systematic error sources is crucial. In this paper, Aeolus interferometer spectral drifts and their potential as systematic error sources for the aerosol and wind products are investigated by means of instrument spectral registration (ISR) measurements that are performed on a weekly basis. During these measurements, the laser frequency is scanned over a range of 11 GHz in steps of 25 MHz and thus spectrally resolves the transmission curves of the Fizeau interferometer and the Fabry–Pérot interferometers (FPIs) used in Aeolus. Mathematical model functions are derived to analyze the measured transmission curves by means of non-linear fit procedures. The obtained fit parameters are used to draw conclusions about the Aeolus instrumental alignment and potentially ongoing drifts. The introduced instrumental functions and analysis tools may also be applied for upcoming missions using similar spectrometers as for instance EarthCARE (ESA), which is based on the Aeolus FPI design.
The European Space Agency (ESA) Earth Explorer Atmospheric Dynamics Mission Aeolus is the first satellite mission providing wind profile information on a global scale, and its wind products have been released on 12 May 2020. Here we verify and intercompare the wind observations from ESA’s satellite mission Aeolus and the European Centre for Medium-Range Weather Forecasts (ECMWF) fifth generation atmospheric reanalyses (ERA5) with radiosonde (RS) observations over China, to allow a fitting application of Aeolus winds. Aeolus provides wind observations in aerosol-free (referred to as Rayleigh-clear winds) and cloudy atmospheres (Mie-cloudy winds). In terms of Aeolus and RS winds, the correlation coefficient (R) and mean difference of Rayleigh-clear (Mie-cloudy) vs RS winds are 0.94 (0.97) and −0.24 ± 7.01 (0.18 ± 4.42) m/s, respectively. The vertical profiles of wind speed differences between Aeolus and RS winds are similar to each other during ascending and descending orbits. The comparison of ECMWF winds relative to Aeolus winds provides the R and mean difference of Rayleigh-clear (Mie-cloudy) winds, which are 0.95 (0.97) and −0.16 ± 6.78 (−0.21 ± 3.91) m/s, respectively. The Rayleigh-clear and Mie-cloudy winds are very consistent with the ECMWF winds, likely due to the assimilation of Aeolus wind observations into the ECMWF analysis. Moreover, we find that among the results of comparing Aeolus with RS and ECMWF winds, a small difference between Rayleigh-clear winds relative to RS winds is appeared in the height range of 2–3 km during descending orbits. This result may be due to the high vertical velocity during the descending orbits. The mean differences between Rayleigh-clear (Mie-cloudy) winds and RS winds during the ascending and descending orbit phase are −0.07 ± 0.69 (−0.72 ± 1.48) and 0.3 ± 1.25 (0.1 ± 1.32) m/s. These small deviations indicate that the performance of Aeolus wind products may be unaffected by the orbit phase or HLOS wind conditions. In addition, the R and mean difference between ERA5 and RS zonal wind components are 0.97 and −0.46 ± 3.12 m/s, respectively. Overall, the Aeolus winds over China are similar to the RS and ECMWF winds. The findings give us sufficient confidence and information to apply Aeolus wind products in numerical weather prediction in China and in climate change research.
Aeolus carries the Atmospheric LAser Doppler INstrument (ALADIN), the first high-spectral-resolution lidar (HSRL) in space. Although ALADIN is optimized to measure winds, its two measurement channels can also be used to derive optical properties of atmospheric particles, including a direct retrieval of the lidar ratio.
This paper presents the standard correct algorithm and the Mie correct algorithm, the two main algorithms of the optical properties product called the Level-2A product, as they are implemented in version 3.12 of the processor, corresponding to the data labelled Baseline 12. The theoretical basis is the same as in . Here, we also show the in-orbit performance of these algorithms. We also explain the adaptation of the calibration method, which is needed to cope with unforeseen variations of the instrument radiometric performance due to the in-orbit strain of the primary mirror under varying thermal conditions. Then we discuss the limitations of the algorithms and future improvements.
We demonstrate that the L2A product provides valuable information about airborne particles; in particular, we demonstrate the capacity to retrieve a useful lidar ratio from Aeolus observations. This is illustrated using Saharan dust aerosol observed in June 2020.
The European Space Agency (ESA) Earth Explorer satellite Aeolus provides continuous profiles of the horizontal line-of-sight wind component globally from space. It was successfully launched in August 2018 with the goal to improve numerical weather prediction (NWP). Aeolus data have already been successfully assimilated into several NWP models and have already helped to significantly improve the quality of weather forecasts. To achieve this major milestone the identification and correction of several systematic error sources were necessary. One of them is related to small fluctuations of the temperatures 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-1. 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 in the top-of-atmosphere reflected shortwave and outgoing longwave radiation of the Earth and the related response of the telescope's thermal control system. To correct for this effect ECMWF model-equivalent winds are used as a 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 model u-component winds with respect to radiosondes is smaller than 0.3 m s-1. Furthermore, this paper presents the alternative of using Aeolus ground return winds which serve as a 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 a good potential for future applications for upcoming reprocessing campaigns or even in the NRT processing of Aeolus wind products.
The first space-based Doppler wind lidar (DWL) on board the Aeolus satellite was launched by the European Space Agency (ESA) on 22 August 2018 to obtain global profiles of horizontal line-of-sight (HLOS) wind speed. In this study, the Raleigh-clear and Mie-cloudy winds for periods of baseline 2B02 (from 1 October to 18 December 2018) and 2B10 (from 28 June to 31 December 2019 and from 20 April to 8 October 2020) were validated using 33 wind profilers (WPRs) installed all over Japan, two ground-based coherent Doppler wind lidars (CDWLs), and 18 GPS radiosondes (GPS-RSs). In particular, vertical and seasonal analyses were performed and discussed using WPR data. During the baseline 2B02 period, a positive bias was found to be in the ranges of 0.5 to 1.7 m s-1 for Rayleigh-clear winds and 1.6 to 2.4 m s-1 for Mie-cloudy winds using the three independent reference instruments. The statistical comparisons for the baseline 2B10 period showed smaller biases, -0.8 to 0.5 m s-1 for the Rayleigh-clear and -0.7 to 0.2 m s-1 for the Mie-cloudy winds. The vertical analysis using WPR data showed that the systematic error was slightly positive in all altitude ranges up to 11 km during the baseline 2B02 period. During the baseline 2B10 period, the systematic errors of Rayleigh-clear and Mie-cloudy winds were improved in all altitude ranges up to 11 km as compared with the baseline 2B02. Immediately after the launch of Aeolus, both Rayleigh-clear and Mie-cloudy biases were small. Within the baseline 2B02, the Rayleigh-clear and Mie-cloudy biases showed a positive trend. For the baseline 2B10, the Rayleigh-clear wind bias was generally negative for all months except August 2020, and Mie-cloudy wind bias gradually fluctuated. Both Rayleigh-clear and Mie-cloudy biases did not show a marked seasonal trend and approached zero towards September 2020. The dependence of the Rayleigh-clear wind bias on the scattering ratio was investigated, showing that there was no significant bias dependence on the scattering ratio during the baseline 2B02 and 2B10 periods. Without the estimated representativeness error associated with the comparisons using WPR observations, the Aeolus random error was determined to be 6.7 (5.1) and 6.4 (4.8) m s-1 for Rayleigh-clear (Mie-cloudy) winds during the baseline 2B02 and 2B10 periods, respectively. The main reason for the large Aeolus random errors is the lower laser energy compared to the anticipated 80 mJ. Additionally, the large representativeness error of the WPRs is probably related to the larger Aeolus random error. Using the CDWLs, the Aeolus random error estimates were in the range of 4.5 to 5.3 (2.9 to 3.2) and 4.8 to 5.2 (3.3 to 3.4) m s-1 for Rayleigh-clear (Mie-cloudy) winds during the baseline 2B02 and 2B10 periods, respectively. By taking the GPS-RS representativeness error into account, the Aeolus random error was determined to be 4.0 (3.2) and 3.0 (2.9) m s-1 for Rayleigh-clear (Mie-cloudy) winds during the baseline 2B02 and 2B10 periods, respectively.
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⁻¹ for the Rayleigh‐clear and 2.8–3.6 m·s⁻¹ 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.
Aeolus is the first satellite mission to directly observe wind profile information on a global scale. After implementing a set of bias corrections, the Aeolus data products went public on 12 May 2020. However, Aeolus wind products over China have thus far not been evaluated extensively by ground-based remote sensing measurements. In this study, the Mie-cloudy and Rayleigh-clear wind products from Aeolus measurements are validated against wind observations from the radar wind profiler (RWP) network in China. Based on the position of each RWP site relative to the closest Aeolus ground tracks, three matchup categories are proposed, and comparisons between Aeolus wind products and RWP wind observations are performed for each category separately. The performance of Mie-cloudy wind products does not change much between the three matchup categories. On the other hand, for Rayleigh-clear and RWP wind products, categories 1 and 2 are found to have much smaller differences compared with category 3. This could be due to the RWP site being sufficiently approximate to the Aeolus ground track for categories 1 and 2. In the vertical, the Aeolus wind products are similar to the RWP wind observations, except for the Rayleigh-clear winds in the height range of 0–1 km. The mean absolute normalized differences between the Mie-cloudy (Rayleigh-clear) and the RWP wind components are 3.06 (5.45), 2.79 (4.81), and 3.32 (5.72) m/s at all orbit times and ascending and descending Aeolus orbit times, respectively. This indicates that the wind products for ascending orbits are slightly superior to those for descending orbits, and the observation time has a minor effect on the comparison. From the perspective of spatial differences, the Aeolus Mie-cloudy winds are consistent with RWP winds in most of east China, except in coastal areas where the Aeolus Rayleigh-clear winds are more reliable. Overall, the correlation coefficient R between the Mie-cloudy (Rayleigh-clear) wind and RWP wind component observation is 0.94 (0.81), suggesting that Aeolus wind products are in good agreement with wind observations from the RWP network in China. The findings give us sufficient confidence in assimilating the newly released Aeolus wind products in operational weather forecasting in China.
The European Space Agency (ESA) Earth Explorer Atmospheric Dynamics Mission Aeolus is the first satellite mission providing wind profile information on a global scale, and its wind products have been released on 12 May 2020. In this study, we verify and inter-compare the wind observations 15 from ESA's satellite mission Aeolus and the European Centre for Medium-Range Weather Forecasts (ECMWF) fifth generation atmospheric reanalyses (ERA5) with radiosonde (RS) observations over China, to allow a fitting application of Aeolus winds. Aeolus provides wind observations in aerosol-free (referred to as Rayleigh-clear winds) and cloudy atmospheres (Mie-cloudy winds). In terms of Aeolus and RS winds, the correlation coefficient (R) and mean difference of Rayleigh-clear (Mie-20 cloudy) vs RS winds are 0.90 (0.92) and 0.09±9.62 (0.59±8.05) m/s, respectively. The vertical profiles of wind speed differences between Aeolus and RS winds are opposite to each other during ascending and descending orbits, indicating that the performance of Aeolus wind product is affected by the orbit phase. The comparison of ECMWF winds relative to Aeolus winds provides the R and mean difference of Rayleigh-clear (Mie-cloudy) winds, which are 0.95 (0.97) and 0.16±6.78 25 (0.21±3.91) m/s, respectively. The Rayleigh-clear and Mie-cloudy winds are almost consistent with the ECMWF winds, likely due to the assimilation of Aeolus wind observations into the ECMWF winds. 2 Moreover, we find that among the results of comparing Aeolus with RS and ECMWF winds, the wind speed difference of Rayleigh-clear winds is large in the height range of 0−1 km, especially during descending orbits. This indicates that the performance of low-altitude Rayleigh-clear wind products could be affected by the near-surface aerosols. In addition, the R and mean difference between ERA5 and RS zonal wind components are 0.89 and 1.46±6.33 m/s, respectively. The RS zonal winds tend 5 to be larger than those from ERA5. The wind speed difference between RS and ERA5 zonal winds in low-lying area is low and insignificant, while it is relatively high and significant over the Qinghai-Tibet Plateau areas. Overall, the Aeolus winds over China are similar to the RS and ECMWF winds. The RS and ERA5 zonal winds are somewhat different over high altitude area, but these differences are acceptable for application of wind products. The findings give us sufficient confidence and 10 information to apply Aeolus wind products in numerical weather prediction in China and in climate change research.
In the process of wind retrieval for Rayleigh Doppler lidar, besides atmospheric temperature and pressure, the accuracy of the wind retrieval result is also affected by Mie signal. When the Mie scattering sigal is large, especially in the cases such as high altitude clouds or volcanic ash and so on, the wind retrieval result will largely deviate from the ture value if the aerosol signal is ignored due to temperature uncertainty and Mie signal contamination. A nonlinear iterative algorithm is proposed, which can retrieve both wind and atmospheric temperature by using the mesured signal with outgoing laser pointing to the zenith. The initial operating point of laser is optimized. Simulation results show that the proposed algorithm can retrieve scattering ratio effectively, and by combination with the nonlinear iterative algorithm of wind retrieval, this algorithm can eliminate the effect of aerosol backscattering signal and then improve the atmopheric wind speed and the temperature retrieval accuracy effectively.
The wind measurement principle and the structure of Rayleigh Doppler lidar are introduced. The method for Fabry-Perot(FP) etalon transmission curve calibration is given. The problem is pointed out that to fit the transmission curve by using Lorentz or Voigt function may induce large error: the relative error would be up to 8% by Lorentz fitting especially. A least-square nonlinear fitting procedure is proposed, which can eliminate the fitting error and improve the wind precision. After the dominant role that the temperature uncertainty plays in wind retrieval process is considered, a nonlinear iterative algorithm is proposed, which can retrieve both wind temperature and atmospheric temperature. Simulation results show that the algorithm proposed can improve wind retrieval accuracy effectively compared with the traditional method without the Mie-induced effect, and the wind retrieval accuracy of the algorithm proposed will be degraded with Mie-induced effect but still better than that of traditional method.
Global wind profile measurement has, for a long time, been a first priority for numerical weather prediction. The demonstration, from ground-based observations, that a double-edge Fabry–Pérot interferometer could be efficiently used for deriving wind profiles from the molecular scattered signal in a very large atmospheric vertical domain has led to the choice of the direct detection technique in space and the selection of the Atmospheric Dynamics Mission (ADM)-Aeolus by the European Space Agency (ESA) in 1999. ADM-Aeolus was successfully launched in 2018, after the technical issues raised by the lidar development had been solved, providing the first global wind profiles from space in the whole troposphere. Simulated and real-time assimilation of the projected horizontal wind information was able to confirm the expected improvements in the forecast score, validating the concept of a wind profiler using a single line-of-sight lidar from space.
The question is raised here about consolidating the results gained from ADM-Aeolus mission with a potential operational follow-on instrument. Maintaining the configuration of the instrument as close as possible to the one achieved (UV emission lidar with a single line of sight), we revisit the concept of the receiver by replacing the arrangement of the Fizeau and Fabry–Pérot interferometers with a unique quadri-channel Mach–Zehnder (QMZ) interferometer, which relaxes the system's operational constraints and extends the observation capabilities to recover the radiative properties of clouds. This ability to profile wind and cloud/aerosol radiative properties enables the meeting of the two highest priorities of the meteorological forecasting community regarding atmospheric dynamics and radiation.
We discuss the optimization of the key parameters necessary in the selection of a high-performance system, as based on previous work and development of our airborne QMZ lidar. The selected optical path difference (3.2 cm) of the QMZ leads to a very compact design, allowing the realization of a high-quality interferometer and offering a large field angle acceptance. Performance simulation of horizontal wind speed measurements with different backscatter profiles shows results in agreement with the targeted ADM-Aeolus random errors, using an optimal 45∘ line-of-sight angle. The Doppler measurement is, in principle, unbiased by the atmospheric conditions (temperature, pressure, and particle scattering) and only weakly affected by the instrument calibration errors. The study of the errors arising from the uncertainties in the instrumental calibration and in the modeled atmospheric parameters used for the backscattered signal analysis shows a limited impact under realistic conditions. The particle backscatter coefficients can be retrieved with uncertainties better than a few percent when the scattering ratio exceeds 2, such as in the boundary layer and in semi-transparent clouds. Extinction coefficients can be derived accordingly. The chosen design further allows the addition of a dedicated channel for aerosol and cloud polarization analysis.
In August 2018, the first Doppler Wind Lidar, developed by the European Space Agency (ESA), was launched on board the Aeolus satellite into space. Providing atmospheric wind profiles on a global basis, the Earth Explorer mission is expected to demonstrate improvements in the quality of numerical weather prediction (NWP). For the use of Aeolus observations in NWP data assimilation, a detailed characterization of the quality and the minimization of systematic errors is crucial. This study performs a statistical validation of Aeolus observations, using collocated radiosonde measurements and NWP forecast equivalents from two different global models, the ICOsahedral Nonhydrostatic model (ICON) of Deutscher Wetterdienst (DWD) and the European Centre for Medium-Range Weather Forecast (ECMWF) Integrated Forecast System (IFS) model, as reference data. For the time period from the satellite's launch to the end of December 2019, comparisons for the northern hemisphere (23.5–65° N) show strong variations of the Aeolus winds bias and differences between the ascending and descending orbit phase. The mean absolute bias for the selected validation area is found to be in the range of 1.8–2.3 m s−1 (Rayleigh) and 1.3–1.9 m s−1 (Mie), showing good agreement between the independent reference data sets. Due to lower representativeness, the random differences are larger for the validation using radiosonde observations compared to the model equivalent statistics. To achieve an estimate for the Aeolus instrumental error, the representativeness errors for the comparisons are determined, besides the estimation of the model and radiosonde observational error. The resulting Aeolus errors estimates are in the range of 4.1–4.4 m s−1 (Rayleigh) and 1.9–3.0 m s−1 (Mie). Investigations of the Rayleigh wind bias on a global scale show that in addition to the satellite flight direction and seasonal differences, the systematic differences depend on latitude. A latitude based bias correction approach is able to reduce the bias, but a residual bias of 0.4–0.6 m s−1 with a temporal trend remains. Taking additional longitudinal differences into account, the bias can be reduced further by almost 50 %. Longitudinal variations are suggested to be linked to land-sea distribution and tropical convection that influences the thermal emission of the earth. Since 20 April 2020 a bias correction scheme has been applied operationally in the L2B processor, developed by the Aeolus Data Innovation and Science Cluster (DISC).
Aeolus, launched on 22 August 2018, is the first ever satellite to directly observe wind information from space on a global scale. An airborne prototype called ALADIN Airborne Demonstrator (A2D) was developed at the German Aerospace Center (DLR) for validating the Aeolus measurement principle based on realistic atmospheric signals. However, atmospheric and instrumental variability currently limit the reliability and repeatability of the A2D instrument response calibration. In this study, a simulated Rayleigh response calibration (SRRC) is presented for resolving the limitations of A2D instrument response calibration.
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.
Soon after the launch of Aeolus on 22 August 2018, the first ever wind lidar in space developed by the European Space Agency (ESA) has been providing profiles of the component of the wind vector along the instrument's line of sight (LOS) on a global scale. In order to validate the quality of Aeolus wind observations, the German Aerospace Center (Deutsches Zentrum für Luft- und Raumfahrt e.V., DLR) recently performed two airborne campaigns over central Europe deploying two different Doppler wind lidars (DWLs) on board the DLR Falcon aircraft. The first campaign – WindVal III – was conducted from 5 November 2018 until 5 December 2018 and thus still within the commissioning phase of the Aeolus mission. The second campaign – AVATARE (Aeolus Validation Through Airborne Lidars in Europe) – was performed from 6 May 2019 until 6 June 2019. Both campaigns were flown out of the DLR site in Oberpfaffenhofen, Germany, during the evening hours for probing the ascending orbits. All together, 10 satellite underflights with 19 flight legs covering more than 7500 km of Aeolus swaths were performed and used to validate the early-stage wind data product of Aeolus by means of collocated airborne wind lidar observations for the first time. For both campaign data sets, the statistical comparison of Aeolus horizontal line-of-sight (HLOS) observations and the corresponding wind observations of the reference lidar (2 µm DWL) on board the Falcon aircraft shows enhanced systematic and random errors compared with the bias and precision requirements defined for Aeolus. In particular, the systematic errors are determined to be 2.1 m s-1 (Rayleigh) and 2.3 m s-1 (Mie) for WindVal III and -4.6 m s-1 (Rayleigh) and -0.2 m s-1 (Mie) for AVATARE. The corresponding random errors are determined to be 3.9 m s-1 (Rayleigh) and 2.0 m s-1 (Mie) for WindVal III and 4.3 m s-1 (Rayleigh) and 2.0 m s-1 (Mie) for AVATARE. The Aeolus observations used here were acquired in an altitude range up to 10 km and have mainly a vertical resolution of 1 km (Rayleigh) and 0.5 to 1.0 km (Mie) and a horizontal resolution of 90 km (Rayleigh) and down to 10 km (Mie). Potential reasons for those errors are analyzed and discussed.
Shortly after the successful launch of the European Space Agency's wind mission Aeolus, co-located airborne wind lidar observations were performed in central Europe; these observations employed a prototype of the satellite instrument – the ALADIN (Atmospheric LAser Doppler INstrument) Airborne Demonstrator (A2D). Like the direct-detection Doppler wind lidar on-board Aeolus, the A2D is composed of a frequency-stabilized ultra-violet (UV) laser, a Cassegrain telescope and a dual-channel receiver to measure line-of-sight (LOS) wind speeds by analysing both Mie and Rayleigh backscatter signals. In the framework of the first airborne validation campaign after the launch and still during the commissioning phase of the mission, four coordinated flights along the satellite swath were conducted in late autumn of 2018, yielding wind data in the troposphere with high coverage of the Rayleigh channel. Owing to the different measurement grids and LOS viewing directions of the satellite and the airborne instrument, intercomparison with the Aeolus wind product requires adequate averaging as well as conversion of the measured A2D LOS wind speeds to the satellite LOS (LOS*). The statistical comparison of the two instruments shows a positive bias (of 2.6 m s-1) of the Aeolus Rayleigh winds (measured along its LOS*) with respect to the A2D Rayleigh winds as well as a standard deviation of 3.6 m s-1. Considering the accuracy and precision of the A2D wind data, which were determined from comparison with a highly accurate coherent wind lidar as well as with the European Centre for Medium-Range Weather Forecasts (ECMWF) model winds, the systematic and random errors of the Aeolus LOS* Rayleigh winds are 1.7 and 2.5 m s-1 respectively. The paper also discusses the influence of different threshold parameters implemented in the comparison algorithm as well as an optimization of the A2D vertical sampling to be used in forthcoming validation campaigns.
Shortly after the successful launch of ESA’s wind mission Aeolus, carried out by the European Space Agency, collocated airborne wind lidar observations were performed in Central Europe, employing the prototype of the satellite instrument, the ALADIN Airborne Demonstrator (A2D). Like the direct-detection Doppler wind lidar on-board Aeolus, the A2D is composed of a frequency-stabilised ultra-violet laser, a Cassegrain telescope and a dual-channel receiver to measure line-of-sight (LOS) wind speeds by analysing both Mie and Rayleigh backscatter signals. In the frame of the first airborne validation campaign after the launch still during the commissioning phase of the mission, four coordinated flights along the satellite swath were conducted in late autumn of 2018, yielding wind data in the troposphere with high coverage of the Rayleigh channel. Owing to the different measurement grids and viewing directions of the satellite and airborne instrument, intercomparison with the Aeolus wind product requires adequate averaging as well as conversion of the measured A2D LOS wind speeds to the satellite LOS. The statistical comparison of the two instruments with model wind data from the ECMWF shows biases of the A2D and Aeolus LOS wind speeds of -0.9 m/s and +1.6 m/s, respectively, while the random errors are around 2.5 m/s. The paper also discusses the influence of different threshold parameters implemented in the comparison algorithm as well as optimization of the A2D vertical sampling to be used in forthcoming validation campaigns.
We present an experimental and theoretical study of the coherent
Rayleigh-Brillouin scattering in gases in the kinetic regime. Gas
density perturbation waves were generated by two crossing pump laser
beams through optical dipole forces. A probe laser beam was then
coherently scattered from the perturbation waves. The line shape of the
scattered light was modeled using kinetic theory. The model takes into
account the internal energy modes of the gas particles and is applicable
to both molecular and atomic gases. We discuss the implication of
coherent Rayleigh-Brillouin scattering on kinetic theory and photon
matter interaction.
We present an experimental and theoretical study of the coherent Rayleigh-Brillouin scattering in gases in the kinetic regime. Gas density perturbation waves were generated by two crossing pump laser beams through optical dipole forces. A probe laser beam was then coherently scattered from the perturbation waves. The line shape of the scattered light was modeled using kinetic theory. The model takes into account the internal energy modes of the gas particles and is applicable to both molecular and atomic gases. We discuss the implication of coherent Rayleigh-Brillouin scattering on kinetic theory and photon matter interaction.
We analyze in detail, in the kinetic regime, the behavior of a model kinetic equation previously used by us for the description of the density fluctuation spectrum in molecular gases. We find that over a small range of wavelengths and frequencies the predicted spectrum contains an unphysical feature, namely a shallow dip in the Rayleigh line. This effect is traced to the modelled elastic collision operator and has gone unnoticed in similar models of monatomic gases. We propose a modified model which corrects this feature and which appears to reproduce the details seen in light-scattering experiments.
Within the framework of the Wang Chang–Uhlenbeck kinetic equation, we propose a model description of molecular gases. The model is related to the models earlier discussed by Hanson and Morse. In our formulation, the model requires no adjustable parameters to analyze the light scattering spectrum from a molecular gas. We apply the model theory to recent Brillouin scattering experiments on hydrogen, deuterium, and hydrogen deuteride and find excellent agreement.
We have developed a Fabry–Perot interferometer and image-plane detector system to be used as a receiver for a Doppler lidar. This system incorporates the latest technology in multichannel detectors, and it is an important step toward the development of operational wind profiler systems for the atmosphere (troposphere, stratosphere, and lower mesosphere). The instrumentation includes a stable high-resolution optically contacted plane étalon and a multiring anode detector to scan the image plane of the Fabry–Perot interferometer spatially. The high wavelength resolution provided by the interferometer permits the aerosol and molecular components of the backscattered signal to be distinguished, and the Doppler shift of either component can then be used to determine the wind altitude profile. The receiver performance has been tested by measuring the wind profile in the boundary layer. The Fabry–Perot interferometer and image-plane detector characteristics are described and sample measurements are presented. The potential of the system as a wind profiler in the troposphere, the stratosphere, and the mesosphere is also considered.
Results of light-scattering experiments on helium and xenon gas mixtures are presented for a large range of wave vectors, densities, and compositions. In the experiments these variables are varied independently from each other. In this manner we are able to show that the hydrodynamic eigenfrequencies, reduced with respect to the product of the wave vector k and the adiabatic sound velocity cs, are a function of the product of the wave vector and the mean free path lHe only. By comparing the experimentally obtained dispersion curves and the predictions of the hydrodynamic theory, we find that the value of klHe at which the theory ceases to be valid is independent of the composition. We show that the longitudinal current-current correlation function ω2I(k,ω) is a useful function in the study of light-scattering spectra that are featureless. For large reduced wave vectors we find a sound mode that is solely supported by the fluctuations in the xenon density. This is the slow sound mode.
Coherent Rayleigh-Brillouin scattering in gases has been studied experimentally for the first time in the kinetic regime and shown to give line shapes that differ significantly from the spontaneous Rayleigh-Brillouin scattering. A kinetic model was developed to obtain an analytic solution of the line shape for monatomic gases, and good agreement with the experimental data was achieved.
A compact twelve-channel photon-counting device based on existing Generation II imaging technology has been developed for use as the image-plane detector of the Dynamics Explorer Fabry-Perot interferometer. The device has an S-20 photocathode, three-microchannel plate electron multiplication stages, and an equal-area concentric-ring segmented anode whose geometry mimics that of the interference ring pattern produced by a plane etalon. The twelve channels sample equal and contiguous intervals in the spectrum. The purpose of the development has been to utilize the signal multiplex advantage of a multichannel detector in the measurement of Doppler shifts and line-broadening effects for naturally occurring atmospheric emission features of low intensity. The design, testing, calibration, and flight performance of the novel detector system are presented. In addition, measured emission line profiles at high resolution from the satellite instrument are presented to illustrate the operation of the device.
The University of Michigan has developed an incoherent-detection Doppler lidar system that continuously measures vertical profiles of horizontal winds and aerosol backscatter. An overview of the instrument is given, followed by a description of improvements that have been made to control the system stability. Most notably, an active feedback system has been implemented to improve the laser frequency stability. A detailed forward model of the instrument is developed that includes many subtle effects, such as detector nonlinearity. A nonlinear least-squares inversion method is then described that permits the recovery of Doppler shift and aerosol backscatter without requiring assumptions about the molecular component of the signal. Examples of wind and aerosol backscatter profiles are shown to illustrate the capabilities of the fitting method.
The application of heterodyne lidar to observe molecular scattering is considered. Despite the reduced Rayleigh cross section, infrared systems are predicted to require mean power levels comparable with those of current and proposed direct detection lidars that operate with the thermally broadened spectra in the visible or ultraviolet. Rayleigh–Brillouin scattering in the kinetic and hydrodynamic (collisional) regimes encountered in the infrared is of particular interest because the observed spectrum approaches a triplet of relatively narrow lines that are more suitable for wind, temperature, and pressure measurements.
A theoretical and experimental study is conducted for the direct-detection Doppler Lidar developed by the Service d’Aéronomie du Centre National de la Recherche Scientifique. Thanks to a specific design, the double-edge technique that applies primarily to Rayleigh scattering can also be employed in presence of aerosols backscatter. We focus on a careful estimate of the particle-induced error on the wind measurements. With a theoretical model for the Fabry–Perot interferometer and two sets of calibration measurements, the true spectral properties of the interferometer and the calibration curves are recovered. Furthermore, the particle-induced error is estimated for varying values of the scattering ratio at 532 nm. When applied to real atmospheric signals, this error is shown to be negligible. A comparison between ancillary data and the wind and backscatter ratio as retrieved from the Doppler lidar signals confirms our estimate.
Since 1989 Service d’Aéronomie du Centre National de la Recherche Scientifique has used an incoherent Doppler lidar technique for wind measurements in the atmosphere. A new-generation Rayleigh–Mie Doppler lidar has been designed and is currently operated at the Observatoire de Haute Provence (France). We give a detailed description of this instrument and highlight two important upgrades leading to quasi-simultaneous and absolute measurements of the wind from ≈8 to 50 km altitude. The possible sources of error are identified and quantified in terms of accuracy in the wind determination. Experimental results are given in detail, and a validation of the measurements is performed with the help of ancillary data. A first climatological description of the mean wind is briefly reported.
The possibility to measure winds in the middle atmosphere with a Doppler lidar has just been demonstrated. It is aimed to study the wave-mean flow interaction, when used in association with the Rayleigh lidar providing density and temperature profiles and their fluctuations. The new Doppler lidar relies on the Rayleigh scattering from air molecules and is designed to cover the height range 25-60 km, a region where radars cannot operate. The Doppler shift of the backscattered echo is measured by inter-comparing the signal detected through each of two high-resolution, narrow band-pass, Fabry-Perot interferometers tuned on either side of the emitted laser line.
The kinetic model of Bhatnagar, Gross, and Krook is used to study the double Fourier transform of the time-dependent density correlation function G(r, t). The results are appropriate to a dilute fluid for arbitrary ratio of wavelength to mean free path. The results of the model calculations are compared to those derived from the linearized hydrodynamic equations. Since neutron and light-scattering experiments can be analyzed in terms of G(r, t), this comparison indicates that the hydrodynamic description should be applicable for momentum transfers less than (ℏ2lambda), where lambda is the collision mean free path in the fluid.
The number-density fluctuation spectrum, Sn(K⃗, ω), of xenon has been studied in the dilute-gas limit. Spectra of He-Ne laser light scattered through an angle of 10.58° at room temperature were measured for pressures ranging from 0.02 to 0.6 atm. Over this range Sn(K⃗, ω) evolves from the Gaussian kinetic form to three peaked hydrodynamic form. Measured spectra were used to evaluate various kinetic and hydrodynamic calculations of Sn(K⃗, ω) through this transition. Spectra obtained from the Boltzmann equation using the Gross-Jackson kinetic modeling procedure, for both Maxwell and hard-sphere intermolecular potentials, are in excellent agreement with the measurements. Among the hydrodynamic theories tested only the generalized hydrodynamics of Selwyn and Oppenheim satisfactorily provides the initial nonhydrodynamic corrections to the Navier-Stokes equations.
The ADM-Aeolus is primarily a research and demonstration mission flying the first Doppler wind lidar in space. Flexible data processing tools are being developed for use in the operational ground segment and by the meteorological community. We present the algorithms developed to retrieve accurate and representative wind profiles, suitable for assimilation in numerical weather prediction. The algorithms provide a flexible framework for classification and weighting of measurement-scale (1–10 km) data into aggregated, observation-scale (50 km) wind profiles for assimilation. The algorithms account for temperature and pressure effects in the molecular backscatter signal, and so the main remaining scientific challenge is to produce representative winds in inhomogeneous atmospheric conditions, such as strong wind shear, broken clouds, and aerosol layers. The Aeolus instrument provides separate measurements in Rayleigh and Mie channels, representing molecular (clear air) and particulate (aerosol and clouds) backscatter, respectively. The combining of information from the two channels offers possibilities to detect and flag difficult, inhomogeneous conditions. The functionality of a baseline version of the developed software has been demonstrated based on simulation of idealized cases.
The possibility to measure winds in the middle atmosphere with a Doppler LIDAR was demonstrated in 1989. It has been used since then to study the wave-mean flow interaction, in association with the Rayleigh LIDAR providing density and temperature and their fluctuations. The Doppler LIDAR relies on Rayleigh scattering from air molecules and was originally designed to cover the height range 25–60 km, a region where radars cannot operate. The Doppler shift of the backscattered echo is measured by inter-comparing the signal detected through each of two narrow band-passes of a single dual Fabry-Perot interferometer tuned to either side of the emitted laser line. Its extension to lower altitudes where Mie scattering is present is under study.
A kinetic theory approach to collision processes in ionized and neutral gases is presented. This approach is adequate for the unified treatment of the dynamic properties of gases over a continuous range of pressures from the Knudsen limit to the high-pressure limit where the aerodynamic equations are valid. It is also possible to satisfy the correct microscopic boundary conditions. The method consists in altering the collision terms in the Boltzmann equation. The modified collision terms are constructed so that each collision conserves particle number, momentum, and energy; other characteristics such as persistence of velocities and angular dependence may be included. The present article illustrates the technique for a simple model involving the assumption of a collision time independent of velocity; this model is applied to the study of small amplitude oscillations of one-component ionized and neutral gases. The initial value problem for unbounded space is solved by performing a Fourier transformation on the space variables and a Laplace transformation on the time variable. For uncharged gases there results the correct adiabatic limiting law for sound-wave propagation at high pressures and, in addition, one obtains a theory of absorption and dispersion of sound for arbitrary pressures. For ionized gases the difference in the nature of the organization in the low-pressure plasma oscillations and in high-pressure sound-type oscillations is studied. Two important cases are distinguished. If the wavelengths of the oscillations are long compared to either the Debye length or the mean free path, a small change in frequency is obtained as the collision frequency varies from zero to infinity. The accompanying absorption is small; it reaches its maximum value when the collision frequency equals the plasma frequency. The second case refers to waves shorter than both the Debye length and the mean free path; these waves are characterized by a very heavy absorption.
The ADM-Aeolus wind retrieval algorithms. Tellus 60A, doi:10.1111/j.1600-0870 On the kinetic model description of Rayleigh-Brillouin scattering from molecular gases Light-scattering studies of dynamical processes in disparate mass gas mixtures
- D G H Tan
- E Andersson
- De Kloe
- J Marseille
- G.-J Stoffelen
- A And
- G Boley
- C D Desai
Tan, D. G. H., Andersson, E., De Kloe, J., Marseille, G.-J., Stoffelen, A. and co-authors. 2007. The ADM-Aeolus wind retrieval algorithms. Tellus 60A, doi:10.1111/j.1600-0870.2007.00285.x. Tenti, G., Boley, C. D. and Desai, R. C. 1974. On the kinetic model description of Rayleigh-Brillouin scattering from molecular gases. Can. J. Phys. 52, 285. Wegdam, G. H. and Schaink, H. M. 1989. Light-scattering studies of dynamical processes in disparate mass gas mixtures. Phys. Rev. A 40, 7301–7311.
ILIAD: Impact of Line Shape on Wind Mea-surements and Correction Methods
- R Flamant
- C Loth
- A Dabas
- M.-L Denneulin
Coherent Rayleigh-Brillouin scattering in monatomic gases in the kinetic regime. Paper #AIAA-2002-3235, 22nd AIAA Aerodynamic Measure-ment Technology and Ground Testing Conference
- X Pan
- M N Shneider
- R B Miles