Extreme heavy precipitation events (HPEs) pose a threat to human life but, despite regular improvement, remain difficult to predict because of the lack of adequate high frequency and high-resolution water vapor (WV) observations in the low troposphere (below 3 km). To fill this observational gap, The Water vapor Lidar Network Assimilation (WaLiNeAs) initiative aims at implementing an integrated prediction tool (IPT), coupling network measurements of WV profiles, and a numerical weather prediction system to try to improve the  forecasts of  the amount, timing, and location of rainfall associated with HPEs in southern France (struck by ~ 7 HPEs per year on average during the fall).

In the fall/winter of 2022-2023, a network of 6 mobile Raman WV lidars was specifically implemented in Southern France (Aude, Gard, Var and Bouche du Rhone) and in Corsica. The network was complemented by 2 fixed Raman WV lidars in Barcelona and Valencia with the aim to provide measurements with high vertical resolution and accuracy to be assimilated in the French Application of Research to Operations at Mesoscale (AROME-France) model, using a four-dimensional ensemble-variational approach with 15-min updates in addition to the observations operationally assimilated (radar, satellites, …). This innovative IPT is expected to enhance the model capability for kilometer-scale prediction of HPEs over southern France up to 48 h in advance.

The field campaign was conducted from October of 2022 to January 2023, to cover the period most propitious to heavy precipitation events in southern France. A consortium of French, German, Italian, and Spanish research groups operated the Raman WV lidar network

In this presentation, we will provide an overview of the precipitation events in southern France during the WaLiNeAs campaign, as well as an outline of the operations period of the different Raman WV lidars and the lidar data monitoring procedure implemented during the experiment. We will highlight the cases of interest and provide an outlook at next steps towards lidar data assimilation in AROME.

How to cite: Flamant, C. and the WaLiNeAs Team: A network of water vapor Raman lidars for improving heavy precipitation forecasting in southern France: introducing the WaLiNeAs initiative and first highlights from the 2022 field campaign, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14747, https://doi.org/10.5194/egusphere-egu23-14747, 2023.

The Mediterranean Rim, and more particularly the western Mediterranean area, is one of the most sensitive regions to climate change. The associated environmental changes are already evident through periods of drought and intense rainfall. The predictions of these phenomena are a major societal issue, which led us to use lidar systems to constrain regional modelling. The Raman lidars HORUS-1 and -2 are each composed of two telescopes of 15 cm diameter.  For each telescope N₂ and H₂O channels are associated. Lidars components have been specifically defined for this task and put into operation during the international Water vapor Lidar Network Assimilation (WaLiNeAs) campaign led by French research teams. Among the three stations managed by the LSCE team, two of them were equipped with HORUS lidar systems at the Port Camargue (43.52 N 4.13 E) and Coursan (43.23 N 3.06 E) sites. The main difference between the two HORUS lidars is the laser used. For HORUS-1 we used an ULTRA laser (optimally pumped by a flash lamp at 30 mJ/20Hz) which showed a good reliability since the beginning of the lidar installation. However, the MERION-C laser (optimally pumped by diodes at 30 mJ/100 Hz) installed in HORUS-2 did not live up to our expectations with several failures, to the point of stopping the measurements in Coursan. We will nevertheless discuss the relative interest of these two lasers in projection of future Raman lidar networks. Observations available from these two lidar systems will be presented and discussed with respect to the meteorological processes encountered during their operating periods.

We give a special acknowledgment to the ANR grant #ANR-20-CE04-0001 for the contribution to the WaLiNeAs program and a special acknowledgment to Meteo France and to the CNRS INSU national LEFE program for their financial contribution for this project. The CEA is acknowledged for the provision of its staff and facilities.

How to cite: Laly, F., Chazette, P., Totems, J., and Lagarrigue, J.: Water vapor retrieval from mini Raman lidar HORUS in the framework of the WaLiNeAs campaign, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8149, https://doi.org/10.5194/egusphere-egu23-8149, 2023.

Since there are only a very few suitable remote sensing measurements, the thermodynamic field of the atmospheric boundary layer and lower free troposphere is largely still Terra Incognita. To close this gap, we developed an automated thermodynamic profiler based on the Raman lidar technique, the Atmospheric Raman Temperature and Humidity Sounder (ARTHUS) (Lange et al. 2019).

It uses only the ice-safe 355-nm radiation of an injection-seeded Nd:YAG laser as transmitter. The laser power is about 20 W at 200 Hz. The diameter of the receiving telescope is 40 cm. Four receiving channels (elastic, water vapor, two rotational Raman signals) allow for four independently measured parameters: temperature (T), water vapor mixing ratio (WVMR), particle extinction coefficient, and particle backscatter coefficient.

With these data, ARTHUS resolves, e.g., the strength of the inversion layer at the atmospheric boundary layer (ABL) top, elevated lids in the free troposphere, and turbulent fluctuations. Furthermore, in combination with Doppler lidars, sensible and latent heat flux profiles in the convective ABL and thus flux-gradient relationships can be studied (Behrendt et al. 2020). Consequently, ARTHUS can be applied for process studies of land-atmosphere feedback, weather and climate monitoring, model verification, and data assimilation.

Resolutions of the measurements are a few seconds and meters in the lower troposphere. With the data, also the statistical uncertainties of the measured parameters are derived. Continuous operations over long periods were achieved not only at the Land Atmosphere Feedback Observatory (LAFO) at University of Hohenheim but also during several field campaigns elsewhere covering a large variety of atmospheric conditions.

During the EUREC4A field campaign (Stevens et al, 2020), ARTHUS was deployed onboard the research vessel Maria S Merian between 18 January and 18 February 2020 to study ocean-atmosphere interaction. Here, ARTHUS was collocated with two Doppler lidars: one in vertically pointing mode and one in a 6-beam scanning mode.

Between 15 July and 20 September 2021, ARTHUS was deployed at the Lindenberg Observatory of the German Weather Service (DWD). The objective of the campaign was to investigate the long-term stability of ARTHUS by comparisons with four local radiosondes. Indeed, the very high accuracy during day and night were verified.

ARTHUS participated in WaLiNeAs (Water Vapor Lidar Network Assimilation) between 15 September and 10 December 2022. For this campaign, ARTHUS was deployed at the west coast of Corsica. The objective was to implement an integrated prediction tool to enhance the forecast of heavy precipitation events in southern France, primarily demonstrating the benefit of assimilating vertically resolved WVMR lidar data in the new version of the French operational AROME numerical weather prediction system.

At the conference, highlights of ARTHUS’ measurements during WaLiNeAs will be shown.

References:

Behrendt et al. 2020, https://doi.org/10.5194/amt-13-3221-2020

Lange et al. 2019, https://doi.org/10.1029/2019GL085774

Stevens et. al. 2021, https://doi.org/10.5194/essd-2021-18

How to cite: Lange, D., Behrendt, A., and Wulfmeyer, V.: The Atmospheric Raman Temperature and Humidity Sounder: Highlights of Four Years of Automated Measurements of the Atmospheric Boundary Layer and Free Troposphere, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10606, https://doi.org/10.5194/egusphere-egu23-10606, 2023.

A newly available Raman lidar (Purple Pulse Lidar Systems) for vertical profiling of atmospheric water vapor, temperature and aerosols was evaluated during the TEAMx pre-campaign (TEAMx-PC22) in summer 2022 in the Inn Valley (Austria). TEAMx (Multi-scale transport and exchange processes in the atmosphere over mountains – programme and experiment) is an international research program addressing exchange processes in the atmosphere over mountains and their parametrization in numerical weather models and climate models. Prior to the multi disciplinary measurement campaign, planned in 2024/2025, the pre-campaign 2022 was rather performed for testing (new) instruments and measurement sites and finding synergies between certain devices.

The Raman lidar system is capable of profiling water vapor and temperature throughout the entire planetary boundary layer (typically 3 km to 4 km agl. on summer days) continuously with a basic temporal resolution of 10 s and a reasonable vertical resolution of 30 m to 100 m. Depending on conditions and temporal averaging, water vapor profiles could even be obtained up to ~7.5 km agl. during nighttime. The lidar system was located at the University of Innsbruck (downtown). It was operated side by side with a vertically staring Doppler wind lidar and a nearby (50 m) scanning Doppler wind lidar on the rooftop of the university building, which provide vertical profiles of the vertical wind component at a 1-s interval and vertical profiles of the three-dimensional wind vector at a 10-min interval, respectively. During the measurement period (Aug 2022 to Sep 2022), operational radiosondes were launched in close proximity, at Innsbruck Airport, roughly 3 km to the west of the lidar site. In addition to the daily ascent at 2 UTC, radiosondes were launched at about 8, 14 and 20 UTC on selected days with potentially complex meteorological conditions. We present a first assessment of the Raman lidar measurements through comparisons with the radiosonde data. Together with data from the wind lidars, we also present an interpretation for significant meteorological situations and events, such as foehn, a passing front, a thunderstorm and the formation of a convective boundary layer during a warm period.

How to cite: Vogelmann, H., Federer, M., Speidel, J., and Gohm, A.: Assessing the performance of a Combined Water Vapor / Temperature / Aerosol Raman Lidar within the TEAMx pre-campaign in the Inn Valley (Innsbruck, Austria) during Summer 2022, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13101, https://doi.org/10.5194/egusphere-egu23-13101, 2023.

Ice clouds in the Arctic are expected to have different radiative properties compared to mid latitude cirrus, because of the different humidity and temperature profile and also the prevalent aerosol loading in northern latitudes which govern their formation. During the late winter and early spring 2022 the HALO-(AC)3 campaign was conducted out of Kiruna (Sweden) to probe artic clouds with an airborne remote sensing payload. For this purpose, the German research aircraft HALO was equipped with a water vapor Differential Absorption Lidar (DIAL), a cloud radar, micro-wave radiometers, radiation measurements in the visible, near infrared and thermal region and a drop-sonde dispenser. A total of 25 flights where performed mainly over the sea between Svalbard and Greenland and up to nearly 90°N.

The primary observable to study ice cloud formation is the relative humidity, which is not directly measurable by lidar, but can only be computed with the aid of additional temperature information. By comparison with a large number of dropsondes launched during flight, we will show that the temperature field from ECMWF IFS analyses and short-term forecasts provides sufficient accuracy to retrieve the relative humidity for ice cloud studies. Using this method we will analyse different scenarios of arctic cirrus formation: under stable artic conditions, during a warm air intrusion and while a cold air outbreak. An interesting special case is the modification of cirrus properties by the presence of an aerosol layer which is most probably composed of long range transported Sharan dust. 

How to cite: Wirth, M. and Groß, S.: Characterisation of Arctic Cirrus by Airborne Water Vapor and High Spectral Resolution Lidar, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2024, https://doi.org/10.5194/egusphere-egu23-2024, 2023.

The mixing layer height (MLH) indicates the change between vertical mixing of air near the surface and less turbulent air above. MLH is important for the dispersion of air pollutants and greenhouse gases, and assessing the performance of numerical weather prediction systems. Existing lidar-based MLH detection algorithms typically do not use the full resolution of the ceilometer, require manual feature engineering, and often do not enforce temporal consistency of the MLH profile. Given the large-scale availability of lidar remote sensing data and the high temporal and spatial resolution at which it is recorded, this domain is very suitable for machine learning approaches such as deep learning. This presentation introduces a completely new approach to estimate MLH: the Deep-Pathfinder algorithm, based on deep learning techniques for image segmentation.

The concept of Deep-Pathfinder is to represent the 24-hour MLH profile as a mask (i.e., black indicating the mixing layer, white indicating the non-turbulent atmosphere above) and directly predict the mask from an image with lidar observations. Range-corrected signal (RCS) data at 12-second temporal and 10-meter vertical resolution was obtained from Lufft CHM 15k ceilometers at five locations in the Netherlands (2020–2022). High-resolution annotations were created for 50 days, informed by a visual inspection of the RCS image, the manufacturer's layer detection algorithm, gradient fields, thermodynamic MLH estimates, and humidity profiles of the 213-meter mast at Cabauw.

Our model is based on a customised U-Net architecture with MobileNetV2 encoder to ensure fast inference times. A nighttime variable indicated whether the sample occurred between sunset and sunrise and hence, whether an estimate of the stable or convective boundary layer was required. Model calibration was performed on the Dutch National Supercomputer Snellius. First, input samples were randomly cropped to 224x224 pixels, covering a 45-minute period and maximum altitude of 2240 meters. Then, the model was pre-trained on 19.4 million samples of unlabelled data. Finally, the labelled data was used to fine-tune the model for the task of mask prediction. Performance on a test set was compared to MLH estimates from ceilometer manufacturer Lufft and the STRATfinder algorithm.

Results showed that days with a clear convective boundary layer were captured well by all three methods, with minimal differences between them. The Lufft wavelet covariance transform algorithm contained a slight temporal shift in MLH estimates. Further, it had more missing data in complex atmospheric conditions. STRATfinder estimates for the nocturnal boundary layer were consistently low due to guiding restrictions in the algorithm. In contrast, Deep-Pathfinder followed short-term fluctuations in MLH more closely due to the use of high-resolution input data. Path optimisation algorithms like STRATfinder have good temporal consistency but can only be evaluated after a full day of ceilometer data has been recorded. Deep-Pathfinder retains the advantages of temporal consistency by assessing MLH evolution in 45-minute samples, however, it can also provide real-time estimates. This makes a deep learning approach as presented here valuable for operational use, as real-time MLH detection better meets the requirements of users in aviation, weather forecasting and air quality monitoring.

How to cite: Wijnands, J., Apituley, A., Alves Gouveia, D., and Noteboom, J. W.: Deep-Pathfinder: A machine learning algorithm for mixing layer height detection based on lidar remote sensing data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-135, https://doi.org/10.5194/egusphere-egu23-135, 2023.

In the last two decades, several scientific studies have highlighted the adverse effects, primarily on population health, transportation, and climate, of urban atmospheric particulate due to anthropogenic emissions. For these reasons, aerosols have been monitored through both, remote sensing and in-situ observation platforms, also to establish if the reduction emission policies implemented at the government level have had positive outcomes. In this study, for the first time, we assess how the vertically resolved properties of the atmospheric particulate have changed and consequently their radiative effect during the last twenty years in Barcelona, Spain, one of the largest metropolitan areas of the Mediterranean basin. This study is carried out in the frame of the ACTRIS project through synergy between lidar measurements and the meteorological variables, e.g. wind, temperature, and humidity at the surface. This research, thanks to twenty-year measurements, can shed some light on the meteorological processes and conditions that can lead to haze formation and can help decision-makers to adopt mitigation strategies to preserve large marine Mediterranean metropolitan regions.

How to cite: Lolli, S., Comeron, A., Gíl-Diaz, C., Landi, T., Munoz-Porcar, C., Oliveira, D., Rodriguez-Gomez, A., Sïcard, M., Alastuey, A., Querol, X., and Reche, C.: Climatological assessment of the vertically resolved optical aerosol properties by lidar measurements and their influence on radiative budget over the last two decades at UPC Barcelona, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4339, https://doi.org/10.5194/egusphere-egu23-4339, 2023.

In recent years there is a growing interest in real-time aerosol profiling and in this context, the use of automated lidars and ceilometers (ALC) for aerosol remote sensing increased. Ceilometers were originally developed to measure cloud-base height automatically. Apart from this, they also provide vertically resolved backscatter information. Several algorithms have been developed to calibrate this signal and to derive aerosol concentration from it, bringing up new opportunities in air quality monitoring and boundary layer research.

The quality of ALCs is often evaluated by comparing the attenuated backscatter to measurements from high-power lidars. This approach is suitable to validate the backscatter signal. However, for the validation of the aerosol concentration, a direct comparison with an in-situ, optical aerosol measurement is more significant.

In this work, a comparison study was performed using the Jülich Observatory for Cloud Evolution. Data were processed and calibrated with algorithms by E-Profile (https://www.eumetnet.eu/activities/observations-programme/current-activities/e-profile/alc-network/). The aerosol retrieval was performed using a Klett inversion algorithm. Close to the JOYCE site a 120 m meteorological tower is located. This tower was used as a platform for the in-situ aerosol measurement, where an optical particle sizer was mounted 100 m above the ceilometer position.

We will show the setup and data processing of the in-situ measurements as well as an approach how ceilometer raw data can be processed, calibrated and used to retrieve aerosol concentration. First results of the comparison will be presented to evaluate the quality of ALC aerosol-measurement.

How to cite: Müller, M., Löhnert, U., and Bohn, B.: Ceilometer aerosol retrieval and comparison with in-situ tower-measurements, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7093, https://doi.org/10.5194/egusphere-egu23-7093, 2023.

We present newly developed software for the data analysis and quality assurance of lidar systems operated in the ACTRIS (Aerosol Clouds and Trace Gases Research Infrastructure) research infrastructure. The software development is coordinated by the Meteorological Institute of Munich (MIM), which operates as one of the central facilities of the Center of Aerosol Remote Sensing (CARS) of ACTRIS. In the frame of ACTRIS, a large number of national facilities (NF) are operating lidar systems for aerosol remote sensing. In order to ensure homogeneously high data quality, CARS is developing appropriate common software tools to assist data processing, system intercomparison, and routine quality assurance of lidar data. Here, we present two such software tools, developed and tested using the long experience of the EARLINET (European Aerosol Research Lidar Network) community.

The ARC (Algorithm for Rayleigh Calculations) has been designed to calculate the cross-section and depolarization ratio of molecular back-scattering. The effect of Rotational Raman (RR) scattering is included line-by-line in ARC considering especially the partial blocking of the RR spectrum due to transmission through narrow-band interference filters. The algorithm supports calculation in variable meteorological conditions for an atmosphere that consists of up to five major gas components (N₂, O₂, CO₂, Ar, H₂O). Such a tool is needed in order to properly take into account the effect of air temperature in the molecular depolarization ratio measured by the NF lidar systems. It is also crucial for designing lidars that rely on RR scattering such as temperature and RR aerosol lidars and can even be applied for the algorithmic correction of unwanted effects introduced by the interference filter in such systems.

The second software package developed by CARS-MIM is ATLAS (AuTomated Lidar Analysis Software). It has been designed for the operational analysis of the quality assurance tests that should be regularly performed and submitted to CARS by the NF for the ACTRIS labeling process. ATLAS currently supports the analysis of all main CARS test procedures, that is, the Rayleigh fit, the Telecover, and the Polarization Calibration. It can also be used to directly compare signals from two lidar systems; It has already been applied in the first intercomparison campaign of CARS reference systems, organized in September 2022 in Magurele, Romania. The software takes raw lidar data as input so the user can detect otherwise-hidden issues in the preprocessing steps. At the time of writing, ATLAS is compatible with all ACTRIS lidar systems. Future updates will include automated syncing of the system metadata from the handbook of instruments of the network, currently hosted by the Single Calculus Chain (SCC), and a graphical user interface that will facilitate its adoption by the NF users. Both software packages are written in python and are open-source projects.

How to cite: Siomos, N., Binietoglou, I., Paschou, P., Adam, M., D'Amico, G., Gast, B., Haarig, M., and Freudenthaler, V.: ARC and ATLAS: CARS software tools for the data analysis and quality assurance of lidar measurements performed within ACTRIS, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13218, https://doi.org/10.5194/egusphere-egu23-13218, 2023.

The uncertainties of the Earth-atmosphere energy budget are associated with a poor understanding of direct and indirect aerosol effects. Dust is a mixture of different minerals, and its chemical and microphysical properties change during transport. Therefore, the influence of dust aerosols on radiative effects is characterized by great uncertainty. Due to meteorological atmospheric patterns, aerosol intrusions are very frequent in the Mediterranean, which is a climatic hot spot and where climate change is much stronger than in other parts of the world. In this study, we analyzed and assessed long-term trends of the surface and columnar heating rate and the radiative effects of dust aerosols using lidar observations. These measurements were taken in the framework of the European Aerosol Research Lidar Network (EARLINET) at Istituto di Metodologie per l'Analisi Ambientale (IMAA) with the Raman/elastic lidar MUSA (40°36′N, 15°44′E). The radiative transfer model Fu–Liou–Gu (FLG) was used to solve aerosol (no clouds) radiative fluxes, with aerosol extinction coefficient profiles from lidar observations as input data. All the cases of dust intrusion that occurred in the last twenty years were selected to understand how they affected the Earth-atmosphere radiative budget, both at the surface and at the top-of-the-atmosphere. In the future, these studies will be important for improving the accuracy of climate predictions.

How to cite: De Rosa, B., Mona, L., Lolli, S., Amodeo, A., and Mytilinaios, M.: Columnar heating rate and  radiative effects of dust aerosols using 20 years of lidar observations., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13419, https://doi.org/10.5194/egusphere-egu23-13419, 2023.

Precise knowledge about the prevailing aerosol content in the atmosphere is very important for several reasons, as aerosols are involved in multiple important processes that not only have a direct impact on air quality, but also influence cloud formation and the earth's radiation budget. Besides that, continuous aerosol observations provide valuable information on atmospheric transport dynamics.
Aerosol backscatter coefficient measurements with elastic backscatter lidars are conducted since multiple decades [1], while the implemented retrieval algorithms predominantly refer to the seminal publications by Klett 1985, Fernald 1984 and Sasano 1985 [2,3,4]. The respective inversion algorithm is often simply called the 'Klett inversion', being a main reason why this algorithm is most often adapted. While more sophisticated aerosol lidars (e.g. Raman lidars, HSRL, ...) have been developed since, simple elastic backscatter lidar measurements are still very frequently conducted as they are technically easy to implement, often as a byproduct. In most cases, the corresponding retrieval algorithms still refer to the 'Klett inversion'.
Unfortunately, the inversion algorithm by Klett 1985 is afflicted by a sign error. In his publication, the sign error is hidden within a substitute, making it very hard to be recognized, representing a major pitfall. A comprehensive literature review revealed, that large parts of the aerosol lidar community are aware of this problem and have tacitly corrected it or, to a much smaller amount, even referred to an erratum which was published by Kaestner in 1986 [5].
However, at the same time and up to this date, a considerable error propagation can be found in literature as well, using and referring to the incorrect algorithm with the sign error included.
Therefore, we want to renew the awareness towards this sign error and show a corrected and slightly improved Klett inversion algorithm. In addition, we present the overall implication resulting from the uncorrected inversion algorithm by using exemplary case studies. Depending on the lidar location and prevailing atmospheric conditions, potential errors reach from marginal to major, often preventing error detection solely based on the magnitude of the calculated results. Simple a posteriori corrections are not possible, as the error magnitude depends on multiple factors.

[1] T. Trickl, H. Giehl, H. Jäger, and H. Vogelmann. 35 yr of stratospheric aerosol measurements at Garmisch-Partenkirchen: From Fuego to Eyjafjalla-   jökull, and beyond. Atmospheric Chemistry and Physics, 13(10):5205–5225, 2013.
[2] James D. Klett. Lidar inversion with variable backscatter/extinction ratios. Appl. Opt., 24(11):1638–1643, June 1985.
[3] Frederick G. Fernald. Analysis of atmospheric lidar observations: Some comments. Appl. Opt., 1984.
[4] Yasuhiro Sasano, Edward V. Browell, and Syed Ismail. Error caused by using a constant extinction/backscattering ratio in the lidar solution. Appl. Opt., 24(22):3929–3932, November 1985.
[5] Martina Kaestner. Lidar inversion with variable backscatter/extinction ratios: Comment. Applied Optics, 25(6):833–835, March 1986.

How to cite: Speidel, J. and Vogelmann, H.: Is your aerosol backscatter retrieval afflicted by a sign error?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13643, https://doi.org/10.5194/egusphere-egu23-13643, 2023.

Nitrous Oxide, N2O, is the third most important GHG contributing to human-induced global warming, after carbon dioxide and methane. Its growth rate is constantly increasing and its global warming potential is estimated to be 273 times higher than that of CO2 over 100 years. The major anthropogenic source is nitrogen fertilization in croplands. Soil N2O emissions are increasing due to interactions between nitrogen inputs and global warming, constituting an emerging positive N2O-climate feedback. The recent increase in global N2O emissions exceeds even the most pessimistic emission trend scenarios developed by the IPCC, underscoring the urgency of mitigating N2O emissions (Global Carbon Project, 2020). Estimating N2O emissions from agriculture is inherently complex and comes with a high degree of uncertainty, due to variability in weather and soil characteristics, in agricultural management options and in the interaction of field management with environmental variables. Further sources of N2O are processes in the chemical industry and combustion processes. The sink of N2O in the stratosphere increases the NOx concentration which catalytically depletes ozone. Better N2O measurements thus are urgently needed, particularly by means of remote sensing.

Airborne or satellite based N2O lidar remote sensing combines the advantages of high measurement accuracy, large-area coverage and nighttime measurement capability. Past initial feasibility studies revealed that Integrated-Path Differential-Absorption (IPDA) lidar providing vertical column concentrations of N2O would be the method of choice. In this current study we use the latest HITRAN spectroscopic data in order to identify appropriate N2O absorption lines in the wavelength region between 2.9 and 4.6 µm. The infrared spectral region challenges both lidar transmission and detection options. On the transmitter side, the use of optical parametric conversion schemes looks promising, while HgCdTe avalanche photodiode (APD), superconducting nanowire single-photon (SNSPD) or upconversion detectors (UCD) could offer high-efficiency low-noise signal detection. These options are implemented into a lidar simulation model in order to identify the optimal lidar system configuration for measuring N2O from aircraft or satellite using state-of-the-art technology.

How to cite: Kiemle, C., Fruck, C., and Fix, A.: Nitrous Oxide, N2O: Spectroscopic Investigations for Future Lidar Applications, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7065, https://doi.org/10.5194/egusphere-egu23-7065, 2023.

Within the frame of the project CONCERNING (COmpact RamaN lidar for Atmospheric CO₂ and ThERmodyNamic ProfilING), we investigated the feasibility and the limits of a ground-based Raman lidar system dedicated to the measurement of CO₂ profiles. The performance of the lidar system was evaluated through a set of numerical simulations. The possibility of exploiting both CO₂ Raman lines of the ν1:2ν2 resonance was explored. An accurate quantification of the contribution of the Raman O₂ lines on the signal and other (e.g., aerosol, absorbing gases) disturbance sources was carried out. The signal integration over the vertical and over time required to reach a useful signal to noise ratio both in day-time and night-time needed for a quantitative analysis of carbon dioxide sources and sinks was evaluated. The above objectives were obtained developing an instrument simulator software consisting of a radiative transfer model able to simulate, in a spectrally resolved manner, all laser light interaction mechanisms with atmospheric constituents, a consistent background signal, and all the devices present in the considered Raman lidar experimental setup. The results indicate that the simulated lidar system, provided to have a low overlap height, could perform measurements on the low troposphere (<1 km) gradients (1-5 ppm) with sufficient precision both in day-time and night-time with an integration time of 1-3 h and a vertical resolution of 75 m. The selected Raman lidar setup is currently being tested and we aim to present preliminary results during the conference.

How to cite: Di Paolantonio, M., Di Girolamo, P., Dionisi, D., Di Bernardino, A., Di Iorio, T., Franco, N., Giuliano, G., Iannarelli, A. M., Liberti, G. L., and Summa, D.: Performance Simulation and Preliminary Measurements of a Raman Lidar for the Retrieval of CO2 Atmospheric Profiles, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16149, https://doi.org/10.5194/egusphere-egu23-16149, 2023.

Cirrus clouds, forming in the cold upper troposphere, are composed of ice crystals with various sizes and nonspherical shapes. They are observed at all latitudes covering over 30% of the Earth’s surface. Studies reveal that they have a significant impact on the radiation balance of our planet and, consequently, on the climate evolution. The radiative effect of cirrus clouds is strongly determined by the cloud microphysical, thermal, and optical properties. Furthermore, global aviation affects the Earth’s radiation balance by inducing contrails and exerting an indirect effect on the microphysical properties of naturally-formed cirrus clouds. In the last decades, the Arctic surface has been warming faster than other regions of the globe, which is known as Arctic Amplification. The thin and small-coverage cirrus clouds over the Arctic are presumed to largely contribute to it. Unfortunately, however, the optical and microphysical properties of cirrus clouds over the Arctic and the exact role they play in the elevated warming of the Arctic are far from understanding. Compared with the intensive studies of cirrus clouds in the tropics and midlatitude regions, cirrus cloud measurements and model studies at high latitudes are sparse. In this study, we present the comparisons of the particle linear depolarization ratio (PLDR) and occurrence rates of cirrus clouds at midlatitudes (35–60 ^oN; 30 ^oW–30 ^oE) and high latitudes (60–80 ^oN; 30 ^oW–30 ^oE) based on the analysis of lidar measurements of CALIPSO in the years 2018–2021. The results show that cirrus clouds at high latitudes appear at lower altitudes than the midlatitude cirrus clouds. The PLDR and occurrence rates of cirrus clouds at high latitudes are smaller than the midlatitude cirrus clouds. Furthermore, air traffic over Europe was significantly reduced in 2020 (starting from March) and only moderately reduced in 2021 due to the COVID-19 pandemic. Under this condition we are able to study the difference in the aviation impacts on the cirrus cloud properties at high latitudes and midlatitudes.

How to cite: Li, Q. and Groß, S.: CALIPSO observations of cirrus cloud properties: investigation of latitude differences and possible aviation impacts, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11893, https://doi.org/10.5194/egusphere-egu23-11893, 2023.

Clouds play an important role for the energy budget of Earth. But, when it comes to predicting the climate's future, their behavior in response to climate change is a major source of uncertainty. To understand and accurately predict the Earth's energy budget and climate, it is necessary to have a thorough understanding of the cloud variability, including their vertical distribution and optical properties.

Satellite observations have been able to provide ongoing monitoring of clouds all around the globe. Among them, active sounders hold a special place thanks to their capability of measuring the vertical position of the cloud with an accuracy of about 100 meters and with a typical horizontal sampling on the order of hundreds of meters. However, clouds retrieved from two spaceborne lidars are different, because the instruments use different wavelengths, pulse energies, pulse repetition frequencies, telescopes, and detectors. In addition, they do not overpass the atmosphere at the same local time.

In this work, we discuss the approach to merging the clouds retrieved from the space-borne lidar ALADIN/Aeolus, which has been orbiting the Earth since August 2018 and operating at 355nm wavelength with the clouds measured since 2006 by CALIPSO lidar, which operates at 532nm.

We demonstrate how to compensate for the existing instrumental differences to get an almost comparable cloud dataset and we discuss the importance of the aforementioned differences between the instruments. The method developed in this study sets the path for adding future lidars (e.g. ATLID/EarthCare) to the global climate lidar cloud record.

How to cite: Feofilov, A., Chepfer, H., and Noël, V.: Merging clouds retrieved from ALADIN/Aeolus and CALIOP/CALIPSO spaceborne lidars, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13416, https://doi.org/10.5194/egusphere-egu23-13416, 2023.

CALIGOLA (Cloud Aerosol Lidar for Global Scale Observations of the Ocean-Land-Atmosphere System) is a mission funded by the Italian Space Agency (ASI), aimed at the development of a space-borne Raman Lidar. A Phase A study to assess the technological feasibility of the laser source and receiver system is currently underway at the Leonardo S.p.A., while scientific studies in support of the mission are conducted by the University of Basilicata. Scientific and technical studies are furthermore supported by other Italian institutions (CNR-ISMAR, CNR-IMAA), with NASA also having expressed an interest in contributing to the mission .

Mission objectives include the observation of the Earth atmosphere, surface (ocean and land). Among the atmospheric objectives, the characterization of the global scale distribution of natural and anthropogenic aerosols, their radiative properties and interactions with clouds, and the measurements of ocean color, suspended particulate matter and marine chlorophyll.

The expected performance of CALIGOLA has been assessed based on the application of an end-to-end lidar simulator. Specifically, sensitivity studies have been carried out to define the technical specifications for the laser source, the telescope, the optics of transceiver, the detectors and the acquisition system. Simulations reveal that the system can measure Rotational Raman echoes from nitrogen and oxygen molecules stimulated at the three lengths wavelength of 355, 532 and 1064 nm. Simulations also reveal that elastic signals are strong enough to meet the requirements under different environmental conditions. As reference signal, several options have been considered. Among others, a temperature-insensitive rotational Raman signal including rotational lines from nitrogen and oxygen molecules.

A careful analysis of different potential orbits is ongoing, with the goal to identify solutions which maximize performance and scientific impact of both atmospheric and oceanic measurements. Near noon-midnight equatorial crossing times are preferable on the ocean side for diel vertical migration and phytoplankton observations, but degrade significantly the performances of atmospheric measurements due to the high solar background. For this reason is essential to find an orbit in which the solar contribution is low enough to obtain acceptable atmospheric results and at the same time the oceanic measurements are far enough from the night-day transitions for as many days a year as possible to assure correct interpretation of phytoplankton physiology. To counterbalance the degraded signal performances also lower obit height are considered, as well as the use of polarized filters to reduce the amount of solar radiation. The estimated performances under different conditions and considering different orbits will be showed during the presentation.

How to cite: Franco, N., Di Girolamo, P., Summa, D., Di Paolantonio, M., and Dionisi, D.: Preliminary Studies and Performance Simulations in support of the mission “CALIGOLA”, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16695, https://doi.org/10.5194/egusphere-egu23-16695, 2023.