DGA Techniques aérospatiales

Abstract. ERA-Interim/Land is a global land surface reanalysis data set covering the period 1979–2010. It describes the evolution of soil moisture, soil temperature and snowpack. ERA-Interim/Land is the result of a single 32-year simulation with the latest ECMWF (European Centre for Medium-Range Weather Forecasts) land surface model driven by meteorological forcing from the ERA-Interim atmospheric reanalysis and precipitation adjustments based on monthly GPCP v2.1 (Global Precipitation Climatology Project). The horizontal resolution is about 80 km and the time frequency is 3-hourly. ERA-Interim/Land includes a number of parameterization improvements in the land surface scheme with respect to the original ERA-Interim data set, which makes it more suitable for climate studies involving land water resources. The quality of ERA-Interim/Land is assessed by comparing with ground-based and remote sensing observations. In particular, estimates of soil moisture, snow depth, surface albedo, turbulent latent and sensible fluxes, and river discharges are verified against a large number of site measurements. ERA-Interim/Land provides a global integrated and coherent estimate of soil moisture and snow water equivalent, which can also be used for the initialization of numerical weather prediction and climate models.

Abstract. A representation of atmospheric chemistry has been included in the Integrated Forecasting System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF). The new chemistry modules complement the aerosol modules of the IFS for atmospheric composition, which is named C-IFS. C-IFS for chemistry supersedes a coupled system in which chemical transport model (CTM) Model for OZone and Related chemical Tracers 3 was two-way coupled to the IFS (IFS-MOZART). This paper contains a description of the new on-line implementation, an evaluation with observations and a comparison of the performance of C-IFS with MOZART and with a re-analysis of atmospheric composition produced by IFS-MOZART within the Monitoring Atmospheric Composition and Climate (MACC) project. The chemical mechanism of C-IFS is an extended version of the Carbon Bond 2005 (CB05) chemical mechanism as implemented in CTM Transport Model 5 (TM5). CB05 describes tropospheric chemistry with 54 species and 126 reactions. Wet deposition and lightning nitrogen monoxide (NO) emissions are modelled in C-IFS using the detailed input of the IFS physics package. A 1 year simulation by C-IFS, MOZART and the MACC re-analysis is evaluated against ozonesondes, carbon monoxide (CO) aircraft profiles, European surface observations of ozone (O3), CO, sulfur dioxide (SO2) and nitrogen dioxide (NO2) as well as satellite retrievals of CO, tropospheric NO2 and formaldehyde. Anthropogenic emissions from the MACC/CityZen (MACCity) inventory and biomass burning emissions from the Global Fire Assimilation System (GFAS) data set were used in the simulations by both C-IFS and MOZART. C-IFS (CB05) showed an improved performance with respect to MOZART for CO, upper tropospheric O3, and wintertime SO2, and was of a similar accuracy for other evaluated species. C-IFS (CB05) is about 10 times more computationally efficient than IFS-MOZART.

Abstract. Southern Africa produces almost a third of the Earth's biomass burning (BB) aerosol particles, yet the fate of these particles and their influence on regional and global climate is poorly understood. ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) is a 5-year NASA EVS-2 (Earth Venture Suborbital-2) investigation with three intensive observation periods designed to study key atmospheric processes that determine the climate impacts of these aerosols. During the Southern Hemisphere winter and spring (June–October), aerosol particles reaching 3–5 km in altitude are transported westward over the southeast Atlantic, where they interact with one of the largest subtropical stratocumulus (Sc) cloud decks in the world. The representation of these interactions in climate models remains highly uncertain in part due to a scarcity of observational constraints on aerosol and cloud properties, as well as due to the parameterized treatment of physical processes. Three ORACLES deployments by the NASA P-3 aircraft in September 2016, August 2017, and October 2018 (totaling ∼350 science flight hours), augmented by the deployment of the NASA ER-2 aircraft for remote sensing in September 2016 (totaling ∼100 science flight hours), were intended to help fill this observational gap. ORACLES focuses on three fundamental science themes centered on the climate effects of African BB aerosols: (a) direct aerosol radiative effects, (b) effects of aerosol absorption on atmospheric circulation and clouds, and (c) aerosol–cloud microphysical interactions. This paper summarizes the ORACLES science objectives, describes the project implementation, provides an overview of the flights and measurements in each deployment, and highlights the integrative modeling efforts from cloud to global scales to address science objectives. Significant new findings on the vertical structure of BB aerosol physical and chemical properties, chemical aging, cloud condensation nuclei, rain and precipitation statistics, and aerosol indirect effects are emphasized, but their detailed descriptions are the subject of separate publications. The main purpose of this paper is to familiarize the broader scientific community with the ORACLES project and the dataset it produced.

Abstract. We review work on extreme events, their causes and consequences, by a group of European and American researchers involved in a three-year project on these topics. The review covers theoretical aspects of time series analysis and of extreme value theory, as well as of the deterministic modeling of extreme events, via continuous and discrete dynamic models. The applications include climatic, seismic and socio-economic events, along with their prediction. Two important results refer to (i) the complementarity of spectral analysis of a time series in terms of the continuous and the discrete part of its power spectrum; and (ii) the need for coupled modeling of natural and socio-economic systems. Both these results have implications for the study and prediction of natural hazards and their human impacts.

Abstract. Precipitation is the key factor controlling the high-frequency hydrological response in catchments, and streamflow simulation is thus dependent on the way rainfall is represented in a hydrological model. A characteristic that distinguishes distributed from lumped models is the ability to explicitly represent the spatial variability of precipitation. Although the literature on this topic is abundant, the results are contrasting and sometimes contradictory. This paper investigates the impact of spatial rainfall on runoff generation to better understand the conditions where higher-resolution rainfall information improves streamflow simulations. In this study, we used the rainfall reanalysis developed by Météo-France over the whole country of France at 1 km and 1 h resolution over a 10 yr period. A hydrological model was applied in the lumped mode (a single spatial unit) and in the semidistributed mode using three unit sizes of subcatchments. The model was evaluated against observed streamflow data using split-sample tests on a large set of French catchments (181) representing a variety of sizes and climate conditions. The results were analyzed by catchment classes and types of rainfall events based on the spatial variability of precipitation. The evaluation clearly showed different behaviors. The lumped model performed as well as the semidistributed model in western France, where catchments are under oceanic climate conditions with quite spatially uniform precipitation fields. By contrast, higher resolution in precipitation inputs significantly improved the simulated streamflow dynamics and accuracy in southern France (Cévennes and Mediterranean regions) for catchments in which precipitation fields were identified to be highly variable in space. In all regions, natural variability allows for contradictory examples to be found, showing that analyzing a large number of events over varied catchments is warranted.

Abstract. This article describes the validation of a linear parameterization of the ozone photochemistry for use in upper tropospheric and stratospheric studies. The present work extends a previously developed scheme by improving the 2-D model used to derive the coefficients of the parameterization. The chemical reaction rates are updated from a compilation that includes recent laboratory work. Furthermore, the polar ozone destruction due to heterogeneous reactions at the surface of the polar stratospheric clouds is taken into account as a function of the stratospheric temperature and the total chlorine content. Two versions of the parameterization are tested. The first one only requires the solution of a continuity equation for the time evolution of the ozone mixing ratio, the second one uses one additional equation for a cold tracer. The parameterization has been introduced into the chemical transport model MOCAGE. The model is integrated with wind and temperature fields from the ECMWF operational analyses over the period 2000–2004. Overall, the results from the two versions show a very good agreement between the modelled ozone distribution and the Total Ozone Mapping Spectrometer (TOMS) satellite data and the "in-situ" vertical soundings. During the course of the integration the model does not show any drift and the biases are generally small, of the order of 10%. The model also reproduces fairly well the polar ozone variability, notably the formation of "ozone holes" in the Southern Hemisphere with amplitudes and a seasonal evolution that follow the dynamics and time evolution of the polar vortex. The introduction of the cold tracer further improves the model simulation by allowing additional ozone destruction inside air masses exported from the high to the mid-latitudes, and by maintaining low ozone content inside the polar vortex of the Southern Hemisphere over longer periods in spring time. It is concluded that for the study of climate scenarios or the assimilation of ozone data, the present parameterization gives a valuable alternative to the introduction of detailed and computationally costly chemical schemes into general circulation models.

Abstract. This article describes the IFS-AER aerosol module used operationally in the Integrated Forecasting System (IFS) cycle 45R1, operated by the European Centre for Medium-Range Weather Forecasts (ECMWF) in the framework of the Copernicus Atmospheric Monitoring Services (CAMS). We describe the different parameterizations for aerosol sources, sinks, and its chemical production in IFS-AER, as well as how the aerosols are integrated in the larger atmospheric composition forecasting system. The focus is on the entire 45R1 code base, including some components that are not used operationally, in which case this will be clearly specified. This paper is an update to the Morcrette et al. (2009) article that described aerosol forecasts at the ECMWF using cycle 32R2 of the IFS. Between cycles 32R2 and 45R1, a number of source and sink processes have been reviewed and/or added, notably increasing the complexity of IFS-AER. A greater integration with the tropospheric chemistry scheme of the IFS has been achieved for the sulfur cycle and for nitrate production. Two new species, nitrate and ammonium, have also been included in the forecasting system. Global budgets and aerosol optical depth (AOD) fields are shown, as is an evaluation of the simulated particulate matter (PM) and AOD against observations, showing an increase in skill from cycle 40R2, used in the CAMS interim ReAnalysis (CAMSiRA), to cycle 45R1.

Abstract. Climate models are the major tools to study the climate system and its evolutions in the future. However, climate simulations often present statistical biases and have to be corrected against observations before being used in impact assessments. Several bias correction (BC) methods have therefore been developed in the literature over the last 2 decades, in order to adjust simulations according to historical records and obtain climate projections with appropriate statistical attributes. Most of the existing and popular BC methods are univariate, i.e., correcting one physical variable and one location at a time and, thus, can fail to reconstruct inter-variable, spatial or temporal dependencies of the observations. These remaining biases in the correction can then affect the subsequent analyses. This has led to further research on multivariate aspects for statistical postprocessing BC methods. Recently, some multivariate bias correction (MBC) methods have been proposed, with different approaches to restore multidimensional dependencies. However, these methods are not yet fully apprehended by researchers and practitioners due to differences in their applicability and assumptions, therefore leading potentially to different results. This study is intended to intercompare four existing MBCs to provide end users with aid in choosing such methods for their applications. For evaluation and illustration purposes, these methods are applied to correct simulation outputs from one climate model through a cross-validation method, which allows for the assessment of inter-variable, spatial and temporal criteria. Then, a second cross-validation method is performed for assessing the ability of the MBC methods to account for the multidimensional evolutions of the climate model. Additionally, two reference datasets are used to assess the influence of their spatial resolution on (M)BC results. Most of the methods reasonably correct inter-variable and intersite correlations. However, none of them adjust correctly the temporal structure as they generate bias-corrected data with usually weak temporal dependencies compared to observations. Major differences are found concerning the applicability and stability of the methods in high-dimensional contexts and in their capability to reproduce the multidimensional changes in the model. Based on these conclusions, perspectives for MBC developments are suggested, such as methods to adjust not only multivariate correlations but also temporal structures and allowing multidimensional evolutions of the model to be accounted for in the correction.

Abstract. The implementation and application of a newly developed coupled system combining ECMWF's integrated forecast system (IFS) with global chemical transport models (CTMs) is presented. The main objective of the coupled system is to enable the IFS to simulate key chemical species without the necessity to invert the complex source and sink processes such as chemical reactions, emission and deposition. Thus satellite observations of atmospheric composition can be assimilated into the IFS using its 4D-VAR algorithm. In the coupled system, the IFS simulates only the transport of chemical species. The coupled CTM provides to the IFS the concentration tendencies due to emission injection, deposition and chemical conversion. The CTMs maintain their own transport schemes and are fed with meteorological data at hourly resolution from the IFS. The CTM used in the coupled system can be either MOZART-3, TM5 or MOCAGE. The coupling is achieved via the special-purpose software OASIS4. The scientific integrity of the coupled system is proven by analysing the difference between stand-alone CTM simulations and the tracer fields in the coupled IFS. The IFS concentration fields match the CTM fields for about 48 h with the biggest differences occurring in the planetary boundary layer (PBL). The coupled system is a good test bed for process-oriented comparison of the coupled CTM. As an example, the vertical structure of chemical conversion and emission injection is studied for a ten day period over Central Europe for the three CTMs.

Abstract. The performance of single models and ensemble prediction systems has been investigated with respect to quantitative precipitation forecasts. Evaluation is based on the potential economic value of + 72 h/ + 96 h forecasts. The verification procedure consists of taking into account all precipitation amounts that are predicted in the vicinity of an observation in order to compute spatial, multi-event contingency tables. A probabilistic forecast from an ensemble can thus be compared to a probabilistic forecast from a single model run. The main results are the following: (1) The performance of the forecasts increases with the precipitation threshold. High levels of potential value reflect high hit rates that are obtained at the expense of a high frequency of false alarms. (2) The ECMWF ensemble performs better than a single forecast based on the same model, even when the resolution of the ensemble is lower. This is true for the NCEP ensemble as well, but only for morning precipitations. (3) The ECMWF ensemble performs better than the 5-member NCEP ensemble running at 12:00 UTC, even when the population of the former is reduced to 5 members. (4) The impact of reducing the population of the ECMWF ensemble is rather small. Differences between 51 members and 21 members are hardly significant. (5) A 2-member poorman ensemble consisting of the control forecasts of the ECMWF and the NCEP ensembles performs as well as the ECMWF ensemble for afternoon precipitations.

Demand driven material requirements planning or DDMRP is a recent and promising material management method that has been developed and implemented in the practitioner world. Essentially, DDMRP represents a rethinking of the basic MRP logic. By incorporating elements drawn from Lean Systems and the Theory of Constraints and by introducing new features such as dynamic buffers, DDMRP modifies the basic MRP logic so that it is better able to satisfy customer demands in an increasingly demanding, turbulent and dynamic environment. Claims have been made by firms that DDMRP represents a superior planning approach. In this paper, we introduce and explore DDMRP. In addition, we evaluate its effectiveness relative to two other widely accepted approaches – MRP II and Kanban/Lean production – through a series of structured computer simulation experiments. The results strongly indicate that DDMRP does represent a superior approach – one that warrants further academic study.

Abstract. In general, regional and global chemistry transport models apply instantaneous mixing of emissions into the model's finest resolved scale. In case of a concentrated source, this could result in erroneous calculation of the evolution of both primary and secondary chemical species. Several studies discussed this issue in connection with emissions from ships and aircraft. In this study, we present an approach to deal with the non-linear effects during dispersion of NOx emissions from ships. It represents an adaptation of the original approach developed for aircraft NOx emissions, which uses an exhaust tracer to trace the amount of the emitted species in the plume and applies an effective reaction rate for the ozone production/destruction during the plume's dilution into the background air. In accordance with previous studies examining the impact of international shipping on the composition of the troposphere, we found that the contribution of ship induced surface NOx to the total reaches 90% over remote ocean and makes 10–30% near coastal regions. Due to ship emissions, surface ozone increases by up to 4–6 ppbv making 10% contribution to the surface ozone budget. When applying the ship plume parameterization, we show that the large scale NOx decreases and the ship NOx contribution is reduced by up to 20–25%. A similar decrease was found in the case of O3. The plume parameterization suppressed the ship induced ozone production by 15–30% over large areas of the studied region. To evaluate the presented parameterization, nitrogen monoxide measurements over the English Channel were compared with modeled values and it was found that after activating the parameterization the model accuracy increases.

Abstract. This paper assesses the detectability of changes in global streamflow. First, a statistical detection method is applied to observed (no missing data which represent 42% of global discharge) and reconstructed (gaps are filled in order to cover a larger area and about 60% of global discharge) streamflow. Observations show no change over the 1958–1992 period. Further, an extension to 2004 over the same catchment areas using reconstructed data does not provide evidence of a significant change. Conversely, a significant change is found in reconstructed streamflow when a larger area is considered. These results suggest that changes in global streamflow are still unclear. Moreover, changes in streamflow as simulated by models from Coupled Model Intercomparison Project 5 (CMIP5) using the historic and future RCP 8.5 scenarios are investigated. Most CMIP5 models are found to simulate the climatological streamflow reasonably well, except for over South America and Africa. Change becomes significant between 2016 and 2040 for all but three models.

This paper presents a new air traffic complexity metric based on non-linear dynamical systems. Previous work has shown that the structure and organization of traffic are important factors in the perception of the complexity of an air traffic situation. The new metric captures these important aspects of complexity by identifying the organization of trajectories in a traffic pattern. This paper investigates only the features of this new metric without quantifying directly the connection between complexity and the metric. Authors of previous work in this area have proposed metrics that generally have not explicitly addressed the effects of organization in the traffic flow on complexity. In order to capture the effect of organization, the metric is based on a dynamical system which fits as closely as possible the observations given by the aircraft positions and speeds. Two approaches are presented. The first one is based on a linear dynamical system and produces an aggregate complexity metric. The second approach, uses a non-linear dynamical system model that fits the observations without error. This metric can be used to identify high (or low) complexity areas on a map, and, by capturing the organization properties of the traffic, captures some of the key factors involved in ATC complexity. A complexity map for the northwest area of France is shown as an example of the application of the model to real radar data. Such maps are an example of the usefulness of these methods for comparing the relative complexity of different regions of airspace.

Abstract. We present an open-access dataset of grape harvest dates (GHD) series that has been compiled from international, French and Spanish literature and from unpublished documentary sources from public organizations and from wine-growers. As of June 2011, this GHD dataset comprises 380 series mainly from France (93% of the data) as well as series from Switzerland, Italy, Spain and Luxemburg. The series have variable length (from 1 to 479 data, mean length of 45 data) and contain gaps of variable sizes (mean ratio of observations/series length of 0.74). The longest and most complete ones are from Burgundy, Switzerland, Southern Rhône valley, Jura and Ile-de-France. The most ancient harvest date of the dataset is in 1354 in Burgundy. The GHD series were grouped into 27 regions according to their location, to geomorphological and geological criteria, and to past and present grape varieties. The GHD regional composite series (GHD-RCS) were calculated and compared pairwise to assess their reliability assuming that series close to one another are highly correlated. Most of the pairwise correlations are significant (p-value < 0.001) and strong (mean pairwise correlation coefficient of 0.58). As expected, the correlations tend to be higher when the vineyards are closer. The highest correlation (R = 0.91) is obtained between the High Loire Valley and the Ile-de-France GHD-RCS. The strong dependence of the vine cycle on temperature and, therefore, the strong link between the harvest dates and the temperature of the growing season was also used to test the quality of the GHD series. The strongest correlations are obtained between the GHD-RCS and the temperature series of the nearest weather stations. Moreover, the GHD-RCS/temperature correlation maps show spatial patterns similar to temperature correlation maps. The stability of the correlations over time is explored. The most striking feature is their generalised deterioration at the late 19th–early 20th century. The possible effects on GHD of the phylloxera crisis, which took place at this time, are discussed. The median of all the standardized GHD-RCS was calculated. The distribution of the extreme years of this general series is not homogenous. Extremely late years all occur during a two-century long time window from the early 17th to the early 19th century, while extremely early years are frequent during the 16th and since the mid-19th century.

Abstract. On 28 February 2018, 57 mm of precipitation associated with a warm conveyor belt (WCB) fell within 21 h over South Korea. To investigate how the large-scale circulation influenced the microphysics of this intense precipitation event, we used radar measurements, snowflake photographs and radiosounding data from the International Collaborative Experiments for Pyeongchang 2018 Olympic and Paralympic Winter Games (ICE-POP 2018). The WCB was identified with trajectories computed with analysis wind fields from the Integrated Forecast System global atmospheric model. The WCB was collocated with a zone of enhanced wind speed of up to 45 m s−1 at 6500 m a.s.l., as measured by a radiosonde and a Doppler radar. Supercooled liquid water (SLW) with concentrations exceeding 0.2 g kg−1 was produced during the rapid ascent within the WCB. During the most intense precipitation period, vertical profiles of polarimetric radar variables show a peak and subsequent decrease in differential reflectivity as aggregation starts. Below the peak in differential reflectivity, the specific differential phase shift continues to increase, indicating early riming of oblate crystals and secondary ice generation. We hypothesise that the SLW produced in the WCB led to intense riming. Moreover, embedded updraughts in the WCB and turbulence at its lower boundary enhanced aggregation by increasing the probability of collisions between particles. This suggests that both aggregation and riming occurred prominently in this WCB. This case study shows how the large-scale atmospheric flow of a WCB provides ideal conditions for rapid precipitation growth involving SLW production, riming and aggregation. Future microphysical studies should also investigate the synoptic conditions to understand how observed processes in clouds are related to large-scale circulation.

Abstract. Coupled Chemistry Aerosol-Tracer Transport model to the Brazilian developments on the Regional Atmospheric Modeling System (CCATT-BRAMS, version 4.5) is an on-line regional chemical transport model designed for local and regional studies of atmospheric chemistry from the surface to the lower stratosphere suitable both for operational and research purposes. It includes gaseous/aqueous chemistry, photochemistry, scavenging and dry deposition. The CCATT-BRAMS model takes advantage of BRAMS-specific development for the tropics/subtropics as well as the recent availability of preprocessing tools for chemical mechanisms and fast codes for photolysis rates. BRAMS includes state-of-the-art physical parameterizations and dynamic formulations to simulate atmospheric circulations down to the meter. This on-line coupling of meteorology and chemistry allows the system to be used for simultaneous weather and chemical composition forecasts as well as potential feedback between the two. The entire system is made of three preprocessing software tools for user-defined chemical mechanisms, aerosol and trace gas emissions fields and the interpolation of initial and boundary conditions for meteorology and chemistry. In this paper, the model description is provided along with the evaluations performed by using observational data obtained from ground-based stations, instruments aboard aircrafts and retrieval from space remote sensing. The evaluation accounts for model applications at different scales from megacities and the Amazon Basin up to the intercontinental region of the Southern Hemisphere.

Abstract. The Development of Methodologies for Water Vapour Measurement (DEMEVAP) project aims at assessing and improving humidity sounding techniques and establishing a reference system based on the combination of Raman lidars, ground-based sensors and GPS. Such a system may be used for climate monitoring, radiosonde bias detection and correction, satellite measurement calibration/validation, and mm-level geodetic positioning with Global Navigation Satellite Systems. A field experiment was conducted in September–October 2011 at Observatoire de Haute-Provence (OHP). Two Raman lidars (IGN mobile lidar and OHP NDACC lidar), a stellar spectrometer (SOPHIE), a differential absorption spectrometer (SAOZ), a sun photometer (AERONET), 5 GPS receivers and 4 types of radiosondes (Vaisala RS92, MODEM M2K2-DC and M10, and Meteolabor Snow White) participated in the campaign. A total of 26 balloons with multiple radiosondes were flown during 16 clear nights. This paper presents preliminary findings from the analysis of all these data sets. Several classical Raman lidar calibration methods are evaluated which use either Vaisala RS92 measurements, point capacitive humidity measurements, or GPS integrated water vapour (IWV) measurements. A novel method proposed by Bosser et al. (2010) is also tested. It consists in calibrating the lidar measurements during the GPS data processing. The methods achieve a repeatability of 4–5%. Changes in the calibration factor of IGN Raman lidar are evidenced which are attributed to frequent optical re-alignments. When modelling and correcting the changes as a linear function of time, the precision of the calibration factors improves to 2–3%. However, the variations in the calibration factor, and hence the absolute accuracy, between methods and types of reference data remain at the level of 7%. The intercomparison of radiosonde measurements shows good agreement between RS92 and Snow White measurements up to 12 km. An overall dry bias is found in the measurements from both MODEM radiosondes. Investigation of situations with low RH values (< 10%RH) in the lower and middle troposphere reveals, on occasion, a lower RH detection limit in the Snow White measurements compared to RS92 due to a saturation of the Peltier device. However, on other occasions, a dry bias is found in RS92, instead. On average, both RS92 and Snow White measurements show a slight moist bias at night-time compared to GPS IWV, while the MODEM measurements show a large dry bias. The IWV measurements from SOPHIE (night-time) and SAOZ (daytime) spectrometers, AERONET photometer (daytime) and calibrated Raman lidar (night-time) showed excellent agreement with the GPS IWV measurements.

Abstract. The assessment of tropical cyclone (TC) statistics requires the direct, objective, and automatic detection and tracking of TCs in reanalyses and model simulations. Research groups have independently developed numerous algorithms during recent decades in order to answer that need. Today, there is a large number of trackers that aim to detect the positions of TCs in gridded datasets. The questions we ask here are the following: does the choice of tracker impact the climatology obtained? And, if it does, how should we deal with this issue? This paper compares four trackers with very different formulations in detail. We assess their performances by tracking TCs in the ERA5 reanalysis and by comparing the outcome to the IBTrACS observations database. We find typical detection rates of the trackers around 80 %. At the same time, false alarm rates (FARs) greatly vary across the four trackers and can sometimes exceed the number of genuine cyclones detected. Based on the finding that many of these false alarms (FAs) are extra-tropical cyclones (ETCs), we adapt two existing filtering methods common to all trackers. Both post-treatments dramatically impact FARs, which range from 9 % to 36 % in our final catalogs of TC tracks. We then show that different traditional metrics can be very sensitive to the particular choice of tracker, which is particularly true for the TC frequencies and their durations. By contrast, all trackers identify a robust negative bias in ERA5 TC intensities, a result already noted in previous studies. We conclude by advising against using as many trackers as possible and averaging the results. A more efficient approach would involve selecting one or a few trackers with well-known and complementary properties.

Abstract. Several major storms pounded western Europe in January 2018, generating large damages and casualties. The two most impactful ones, Eleanor and Friederike, are analysed here in the context of climate change. Near surface wind speed station observations exhibit a decreasing trend in the frequency of strong winds associated with such storms. High-resolution regional climate models, on the other hand, show no trend up to now and a small increase in storminess in future due to climate change. This shows that factors other than climate change, which are not in the climate models, caused the observed decline in storminess over land. A large part is probably due to increases in surface roughness, as shown for a small set of stations covering the Netherlands and in previous studies. This observed trend could therefore be independent from climate evolution. We concluded that human-induced climate change has had so far no significant influence on storms like the two mentioned. However, all simulations indicate that global warming could lead to a marginal increase (0 %–20 %) in the probability of extreme hourly winds until the middle of the century, consistent with previous modelling studies. This excludes other factors, such as surface roughness, aerosols, and decadal variability, which have up to now caused a much larger negative trend. Until these factors are correctly simulated by climate models, we cannot give credible projections of future storminess over land in Europe.