143 research outputs found
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Vertical aerosol distribution in the southern hemispheric midlatitudes as observed with lidar in Punta Arenas, Chile (53.2° and 70.9° W), during ALPACA
Within this publication, lidar observations of the vertical aerosol distribution above Punta Arenas, Chile (53.2 S and 70.9 W), which have been performed with the Raman lidar PollyXT from December 2009 to April 2010, are presented. Pristine marine aerosol conditions related to the prevailing westerly circulation dominated the measurements. Lofted aerosol layers could only be observed eight times during the whole measurement period. Two case studies are presented showing long-range transport of smoke from biomass burning in Australia and regionally transported dust from the Patagonian Desert, respectively. The aerosol sources are identified by trajectory analyses with the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) and FLEXible PARTicle dispersion model (FLEXPART). However, seven of the eight analysed cases with lofted layers show an aerosol optical thickness of less than 0.05. From the lidar observations, a mean planetary boundary layer (PBL) top height of 1150 350m was determined. An analysis of particle backscatter coefficients confirms that the majority of the aerosol is attributed to the PBL, while the free troposphere is characterized by a very low background aerosol concentration. The ground-based lidar observations at 532 and 1064 nm are supplemented by the Aerosol Robotic Network (AERONET) Sun photometers and the space-borne Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO). The averaged aerosol optical thickness (AOT) determined by CALIOP was 0:02 0:01 in Punta Arenas from 2009 to 2010. © Author(s) 2019. This work is distributed under the Creative Commons Attribution 4.0 License
The impact of Aeolus wind retrievals on ECMWF global weather forecasts
Abstract Aeolus is the world's first spaceborne Doppler Wind Lidar, providing profiles of horizontal line-of-sight (HLOS) wind retrievals. Numerical weather prediction (NWP) impact and error statistics of Aeolus Level-2B (L2B) wind statistics have been assessed using the European Centre for Medium-range Weather Forecasts (ECMWF) global data assimilation system. Random and systematic error estimates were derived from observation minus background departure statistics. The HLOS wind random error standard deviation is estimated to be in the range 4.0-7.0 m/s for the Rayleigh-clear and 2.8-3.6 m/s for the Mie-cloudy, depending on atmospheric signal levels which in turn depend on instrument performance, atmospheric backscatter properties and the processing algorithms. Complex systematic HLOS wind error variations on time-scales less than one orbit were identified, most strongly affecting the Rayleigh-clear winds. NWP departures and instrument housekeeping data confirmed that it is caused by temperature gradients across the primary mirror. A successful bias correction scheme was implemented in the operational processing chain in April 2020. In Observing System Experiments (OSEs), Aeolus provides statistically significant improvement in short-range forecasts as verified by observations sensitive to temperature, wind and humidity. Longer forecast range verification shows positive impact that is strongest at the day two to three forecast range: 2% improvement in root-mean-square error for vector wind and temperature in the tropical upper troposphere and lower stratosphere, and polar troposphere. Positive impact up to 9 days is found in the tropical lower stratosphere. Both Rayleigh-clear and Mie-cloudy winds provide positive impact, but the Rayleigh accounts for most tropical impact. The Forecast Sensitivity Observation Impact (FSOI) metric is available since 9 January 2020, when Aeolus was operationally assimilated, which confirms Aeolus is a useful contribution to the global observing system, with the Rayleigh-clear and Mie-cloudy winds providing similar overall short-range impact in 2020
The automated multiwavelength Raman polarization and water-vapor lidar PollyXT: The neXT generation
The atmospheric science community demands autonomous and quality-assured vertically resolved measurements of aerosol and cloud properties. For this purpose, a portable lidar called Polly was developed at TROPOS in 2003. The lidar system was continuously improved with gained experience from the EARLINET community, involvement in worldwide field campaigns, and international institute collaborations within the last 10 years. Here we present recent changes of the setup of the portable multiwavelength Raman and polarization lidar PollyXT and discuss the improved capabilities of the system by means of a case study. The latest system developments include an additional near-range receiver unit for Raman measurements of the backscatter and extinction coefficient down to 120âŻm above ground, a water-vapor channel, and channels for simultaneous measurements of the particle linear depolarization ratio at 355 and 532âŻnm. Quality improvements were achieved by systematically following the EARLINET guidelines and the international PollyNET quality assurance developments. A modified ship radar ensures measurements in agreement with air-traffic safety regulations and allows for 24â7 monitoring of the atmospheric state with PollyXT
Recommended from our members
The automated multiwavelength Raman polarization and water-vapor lidar PollyXT: The neXT generation
The atmospheric science community demands autonomous and quality-assured vertically resolved measurements of aerosol and cloud properties. For this purpose, a portable lidar called Polly was developed at TROPOS in 2003. The lidar system was continuously improved with gained experience from the EARLINET community, involvement in worldwide field campaigns, and international institute collaborations within the last 10 years. Here we present recent changes of the setup of the portable multiwavelength Raman and polarization lidar PollyXT and discuss the improved capabilities of the system by means of a case study. The latest system developments include an additional near-range receiver unit for Raman measurements of the backscatter and extinction coefficient down to 120âŻm above ground, a water-vapor channel, and channels for simultaneous measurements of the particle linear depolarization ratio at 355 and 532âŻnm. Quality improvements were achieved by systematically following the EARLINET guidelines and the international PollyNET quality assurance developments. A modified ship radar ensures measurements in agreement with air-traffic safety regulations and allows for 24â7 monitoring of the atmospheric state with PollyXT
Correction of wind bias for the lidar on-board Aeolus using telescope temperatures
The European Space Agency satellite Aeolus provides continuous profiles of the horizontal line-of-sight wind component at a global scale. It was successfully launched into space in August 2018 with the goal to improve numerical weather prediction (NWP). Aeolus data has already been successfully assimilated into several NWP models and has already helped to significantly improve the quality of weather forecasts. To achieve this major milestone the identification and correction of several systematic error sources was necessary. One of them is related to small temperatures fluctuations across the 1.5âm diameter primary mirror of the telescope which cause varying wind biases along the orbit of up to 8âm/s. This paper presents a detailed overview of the influence of the telescope temperature variations on the Aeolus wind products and describes the approach to correct for this systematic error source in the operational near-real-time (NRT) processing. It was shown that the telescope temperature variations along the orbit are due to changes of the top-of-atmosphere short- and long-wave radiation of the Earth and the response of the telescopeâs thermal control system to that. To correct for this effect ECMWF model-equivalent winds are used as bias reference to describe the wind bias in a multiple linear regression model as a function of various temperature sensors located on the primary telescope mirror. This correction scheme has been in operational use at ECMWF since April 2020 and is capable of reducing a large part of the telescope-induced wind bias. In cases where the influence of the temperature variations is particularly strong it was shown that the bias correction can improve the orbital bias variation by up to 53â%. Moreover, it was demonstrated that the approach of using ECMWF model-equivalent winds is justified by the fact that the global bias of models u-component winds w.r.t to radiosondes is smaller than 0.3âm/s. However, this paper also presents the alternative of using Aeolus ground return winds which serve as zero wind reference in the multiple linear regression model. The results show that the approach based on ground return winds only performs 10.8â% worse than the ECMWF model-based approach and thus has good potential for future applications for upcoming reprocessing campaigns or even in the NRT processing of Aeolus wind products
Characterization of dark current signal measurements of the ACCDs used on-board the Aeolus satellite
Even just shortly after the successful launch of the European Space Agency satellite Aeolus in August 2018, it turned out that dark current signal anomalies of single pixels (so-called âhot pixelsâ) on the accumulation charge-coupled devices (ACCDs) of the Aeolus detectors detrimentally impact the quality of the aerosol and wind products, potentially leading to wind errors of up to several meters per second. This paper provides a detailed characterization of the hot pixels that occurred during the first 1.5âyears in orbit. The hot pixels are classified according to their characteristics to discuss their impact on wind measurements. Furthermore, mitigation approaches for the wind retrieval are presented and potential root causes for hot pixel occurrence are discussed. The analysis of the dark current signal anomalies reveals a large variety of anomalies ranging from pixels with random telegraph signal (RTS)-like characteristics to pixels with sporadic shifts in the median dark current signal. Moreover, the results indicate that the number of hot pixels almost linearly increased during the observing period between 2 September 2018 and 20 May 2020 with 6â% of the ACCD pixels affected in total at the end of the period leading to 9.5â% at the end of the mission lifetime. This work introduces dedicated instrument calibration modes and ground processors, which allowed for a correction shortly after a hot pixel occurrence. The achieved performance with this approach avoids risky adjustments to the in-flight hardware operation. It is demonstrated that the success of the correction scheme varies depending on the characteristics of each hot pixel itself. With the herein presented categorization, it is shown that multi-level RTS pixels with high fluctuation are the biggest challenge for the hot pixel correction scheme. Despite a detailed analysis in this framework, no conclusion could be drawn about the root cause of the hot pixel issue
ESA's Space-based Doppler Wind Lidar Mission Aeolus - First Wind and Aerosol Product Assessment Results
The European Space Agency (ESA) wind mission,
Aeolus, hosts the first space-based Doppler Wind
Lidar (DWL) world-wide. The primary mission
objective is to demonstrate the DWL technique for
measuring wind profiles from space, intended for
assimilation in Numerical Weather Prediction
(NWP) models. The wind observations will also be
used to advance atmospheric dynamics research
and for evaluation of climate models. Mission spinoff products are profiles of cloud and aerosol
optical properties. Aeolus was launched on 22
August 2018, and the Atmospheric LAser Doppler
INstrument (Aladin) instrument switch-on was
completed with first high energy output in wind
mode on 4 September 2018. The on-ground
data processing facility worked excellent, allowing
L2 product output in near-real-time from the start
of the mission. First results from the wind profile
product (L2B) assessment show that the winds are
of very high quality, with random errors in the free
Troposphere within (cloud/aerosol backscatter
winds: 2.1 m/s) and larger (molecular backscatter
winds: 4.3 m/s) than the requirements (2.5 m/s), but
still allowing significant positive impact in first
preliminary NWP impact experiments. The higher
than expected random errors at the time of writing
are amongst others due to a lower instrument outand input photon budget than designed. The
instrument calibration is working well, and some of
the data processing steps are currently being
refined to allow to fully correct instrument
alignment related drifts and elevated detector dark
currents causing biases in the first data product
version. The optical properties spin-off product
(L2A) is being compared e.g. to NWP model
clouds, air quality model forecasts, and collocated
ground-based observations. Features including
optically thick and thin particle and hydrometeor
layers are clearly identified and are being validated
ALADIN laser frequency stability and its impact on the Aeolus wind error
The acquisition of atmospheric wind profiles on a global scale was realized by the launch of the Aeolus satellite, carrying the unique Atmospheric LAser Doppler INstrument (ALADIN), the first Doppler wind lidar in space. One major component of ALADIN is its high-power, ultraviolet (UV) laser transmitter, which is based on an injection-seeded, frequency-tripled Nd:YAG laser and fulfills a set of demanding requirements in terms of pulse energy, pulse length, repetition rate, and spatial and spectral beam properties. In particular, the frequency stability of the laser emission is an essential parameter which determines the performance of the lidar instrument as the Doppler frequency shifts to be detected are on the order of 10^8 smaller than the frequency of the emitted UV light. This article reports the assessment of the ALADIN laser frequency stability and its influence on the quality of the Aeolus wind data. Excellent frequency stability with pulse-to-pulse variations of about 10âMHz (root mean square) is evident for over more than 2 years of operations in space despite the permanent occurrence of short periods with significantly enhanced frequency noise (>â30âMHz). The latter were found to coincide with specific rotation speeds of the satellite's reaction wheels, suggesting that the root cause are micro-vibrations that deteriorate the laser stability on timescales of a few tens of seconds. Analysis of the Aeolus wind error with respect to European Centre for Medium-Range Weather Forecasts (ECMWF) model winds shows that the temporally degraded frequency stability of the ALADIN laser transmitter has only a minor influence on the wind data quality on a global scale, which is primarily due to the small percentage of wind measurements for which the frequency fluctuations are considerably enhanced. Hence, although the Mie wind bias is increased by 0.3âm/s at times when the frequency stability is worse than 20âMHz, the small contribution of 4â% from all Mie wind results renders this effect insignificant (<â0.1âm/s) when all winds are considered. The impact on the Rayleigh wind bias is negligible even at high frequency noise. Similar results are demonstrated for the apparent speed of the ground returns that are measured with the Mie and Rayleigh channel of the ALADIN receiver. Here, the application of a frequency stability threshold that filters out wind observations with variations larger than 20 or 10âMHz improves the accuracy of the Mie and Rayleigh ground velocities by only 0.05 and 0.10âm/s, respectively, however at the expense of useful ground data
Data quality of Aeolus wind measurements
The European Space Agency (ESA)'s Earth Explorer Aeolus was launched in August 2018 carrying the world's first spaceborne wind lidar, the Atmospheric Laser Doppler Instrument (ALADIN). ALADIN uses a high spectral resolution Doppler wind lidar operating at 355nm to measure profiles of line-of-sight wind components in near-real-time (NRT). ALADIN samples the atmosphere from 30km altitude down to the Earth's surface or to the level where the lidar signal is attenuated by optically thick clouds.
The global wind profiles provided by ALADIN help to improve weather forecasting and the understanding of atmospheric dynamics as they fill observational gaps in vertically resolved wind profiles mainly in the tropics, southern hemisphere, and over the northern hemisphere oceans. In January 2020, the European Centre for Medium-Range Weather Forecasts (ECMWF) became the first numerical weather prediction (NWP) centre to assimilate Aeolus observations for operational forecasting.
A main prerequisite for beneficial impact is data of sufficient quality. Such high data quality has been achieved through close collaboration of all involved parties within the Aeolus Data Innovation and Science Cluster (DISC), which was established after launch to study and improve the data quality of Aeolus products. The tasks of the Aeolus DISC include the instrument and platform monitoring, calibration, characterization, retrieval algorithm refinement, processor evolution, quality monitoring, product validation, and impact assessment for NWP.
The achievements of the Aeolus DISC for the NRT data quality and the current status of Aeolus wind measurements will be described and summarized. Further, an outlook on future improvements and the availability of reprocessed datasets with enhanced data quality will be provided
HETEAC: The Aerosol Classification Model for EarthCARE
We introduce the Hybrid End-To-End Aerosol Classification (HETEAC) model for the upcoming EarthCARE mission. The model serves as the common baseline for development, evaluation, and implementation of EarthCARE algorithms. It shall ensure the consistency of different aerosol products from the multi-instrument platform as well as facilitate the conform specification of broad-band optical properties necessary for the EarthCARE radiative closure efforts. The hybrid approach ensures the theoretical description of aerosol microphysics consistent with the optical properties of various aerosol types known from observations. The end-to-end model permits the uniform representation of aerosol types in terms of microphysical, optical and radiative properties
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