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Cloud radars are capable of providing continuous high-resolution observations of clouds and now offer new capabilities within fog layers thanks to the development of frequency-modulated continuous-wave 95 GHz cloud radars. These observations are related to the microphysical properties of clouds. Power law relations in the form of Z=a⋅LWCb are generally used to estimate liquid water content (LWC) profiles. The constants a and b from the power law relation vary with the cloud type and cloud characteristics. Due to the variety of such parameterizations, selecting the most appropriate Z –LWC relation for a continuous cloud system is complicated. Additional information such as liquid water path (LWP) from a co-located microwave radiometer (MWR) is used to scale the LWC of the cloud profile. An algorithm for estimating the LWC of fog and warm clouds using 95 GHz cloud radar–microwave radiometer synergy in a variational framework is presented. This paper also aims to propose an algorithm configuration that retrieves the LWC of clouds and fog using radar reflectivity and a climatology of the power law parameters. To do so, variations in the scaling factor ln⁡a (the logarithm of pre-factor a from power law relation) when MWR observations are available are allowed in each cloud profile to build a climatology of the scaling factor ln⁡a that can be used when MWR observations are not available. The algorithm also accounts for attenuation due to cloud droplets. In this algorithm formulation, the measure of uncertainty in the observations, the forward model, and the a priori information of desired variables acts as weights in the retrieved quantities. These uncertainties in the retrieval are analyzed in the sensitivity analysis of the algorithm. The retrieval algorithm is first tested on a synthetic profile for different perturbations in sensitivity parameters. The sensitivity study has shown that this method is susceptible to LWP information because LWP is point information for the whole cloud column. By further investigating the sensitivity analysis of various biases in LWP information, it was found that it is beneficial to incorporate LWP, even if it is biased, rather than not assimilate any LWP. The algorithm is then implemented in various cloud and fog cases at the SIRTA observatory to estimate LWC and the scaling factor. The scaling factor (ln⁡a) changes for each cloud profile, and the range of ln⁡a is consistent with suggested values in the literature. The validation of such an algorithm is challenging, as we need reference measurements of LWC co-located with the retrieved values. During the SOFOG-3D campaign (southwest of France, October 2019 to March 2020), in situ measurements of LWC were collected in the vicinity of a cloud radar and a microwave radiometer, allowing comparison of retrieved and measured LWC. The comparison demonstrated that the cloud–fog heterogeneity played a key role in the assessment. The proposed synergistic retrieval algorithm is applied to 39 cloud and fog cases at SIRTA, and the behavior of the scaling factor is studied. This statistical analysis of scaling is carried out to develop a radar-only retrieval method. The climatology revealed that the scaling factor can be linked to the maximum reflectivity of the profile. From climatology, the statistical relations for the scaling factor are proposed for fog and clouds. Thanks to the variational framework, a stand-alone radar version of the algorithm is adapted from the synergistic retrieval algorithm, which incorporates the climatology of the scaling factor as a priori information to estimate the LWC of warm clouds. This method allows the LWC estimation using only radar reflectivity and climatology of the scaling factor. [ABSTRACT FROM AUTHOR]

For the last 25 years, CO-PDD (Cézeaux-Aulnat-Opme-puy de Dôme) has evolved to become a full instrumented platform for atmospheric research. It has received credentials as a national observing platform in France and is internationally recognized as a global station in the GAW (Global Atmosphere Watch) network. It is a reference site of European and national research infrastructures ACTRIS (Aerosol Cloud and Trace gases Research Infrastructure) and ICOS (Integrated Carbon Observing System). The site located on top of the puy de Dôme mountain (1465 m a.s.l.) is completed by additional sites located at lower altitudes and adding the vertical dimension to the atmospheric observations: Opme (660 m a.s.l.), Cézeaux (410 m), and Aulnat (330 m). The integration of different sites offers a unique combination of in situ and remote sensing measurements capturing and documenting the variability of particulate and gaseous atmospheric composition, but also the optical, biochemical, and physical properties of aerosol particles, clouds, and precipitations. Given its location far away from any major emission sources, its altitude, and the mountain orography, the puy de Dôme station is ideally located to sample different air masses in the boundary layer or in the free troposphere depending on time of day and seasons. It is also an ideal place to study cloud properties with frequent presence of clouds at the top in fall and winter. As a result of the natural conditions prevailing at the site and of the very exhaustive instrumental deployment, scientific studies at the puy de Dôme strongly contribute to improving knowledge in atmospheric sciences, including the characterization of trends and variability, the understanding of complex and interconnected processes (microphysical, chemical, biological, chemical and dynamical), and the provision of reference information for climate/chemistry models. In this context, CO-PDD is a pilot site to conduct instrumental development inside its wind tunnel for testing liquid and ice cloud probes in natural conditions, or in situ systems to collect aerosol and cloud. This paper reviews 25 years (1995–2020) of atmospheric observation at the station and related scientific research contributing to atmospheric and climate science. [ABSTRACT FROM AUTHOR]

Particle number concentration and size distribution are important variables needed to constrain the role of atmospheric particles in the Earth radiation budget, both directly and indirectly through CCN activation. They are also linked to regulated variables such as particle mass (PM) and therefore of interest to air quality studies. However, data on their long-term variability are scarce, in particular at high altitudes. In this paper, we investigate the diurnal and seasonal variability of the aerosol total number concentration and size distribution at the puy de Dôme research station (France, 1465 m a.s.l.). We report a variability of aerosol particle total number concentration measured over a five-year (2003-2007) period for particles larger than 10 nm and aerosol size distributions between 10 and 500 nm over a two-year period (January 2006 to December 2007). Concentrations show a strong seasonality with maxima during summer and minima during winter. A diurnal variation is also observed with maxima between 12:00 and 18:00 UTC. At night (00:00-06:00 UTC), the median hourly total concentration varies from 600 to 800 cm-3 during winter and from 1700 to 2200 cm-3 during summer. During the day (08:00-18:00 UTC), the concentration is in the range of 700 to 1400 cm-3 during winter and of 2500 to 3500 cm-3 during summer. An averaged size distribution of particles (10- 500 nm) was calculated for each season. The total aerosol number concentrations are dominated by the Aitken mode integral concentrations, which drive most of the winter to summer total concentrations increase. The night to day increase in dominated by the nucleation mode integral number concentration. Because the site is located in the free troposphere only a fraction of the time, in particular at night and during the winter season, we have subsequently analyzed the variability for nighttime and free tropospheric (FT)/residual layer (RL) conditions only. We show that a seasonal variability is still observed for these FT/RL conditions. The FT/RL seasonal variation is due to both seasonal changes in the air mass origin from winter to summer and enhanced concentrations of particles in the residual layer/free troposphere in summer. The later observation can be explained by higher emissions intensity in the boundary layer, stronger exchanges between the boundary layer and the free troposphere as well as enhanced photochemical processes. Finally, aerosols mean size distributions are calculated for a given air mass type (marine/continental/regional) according to the season for the specific conditions of the residual layer/free troposphere. The seasonal variability in aerosol sources seems to be predominant over the continent compared to the seasonal variation of marine aerosol sources. These results are of regional relevance and can be used to constrain chemical-transport models over Western Europe. [ABSTRACT FROM AUTHOR]

Condensations trails (or contrails) that form behind aircraft have been of climatic interest for many years; yet, their radiative forcing is still uncertain. A number of studies estimate the radiative impact of contrails to be similar to, or even larger than, that of CO2 emitted by aviation. Hence, contrail mitigation may represent a significant opportunity to reduce the overall climate effect of aviation. Here we analyze an 8-year data set of radiosonde observations from Trappes, France, in terms of the potential for contrail and induced cirrus formation. We focus on the contrail vertical and temporal distribution and test mitigation opportunities by changing flight altitudes and fuel type. Potential contrail formation is identified with the Schmidt–Appleman criterion (SAc). The uncertainty of the SAc, due to variations in aircraft type and age, is estimated by a sensitivity study and is found to be larger than the radiosonde measurement uncertainties. Linkages between potential contrail formation layers and the thermal tropopause, as well as with the altitude of the jet stream maximum, are determined. While non-persistent contrails form at the tropopause level and around 1.5 km above the jet stream, persistent contrails are located approximately 1.5 km below the thermal tropopause and at the altitude of the jet stream. The correlation between contrail formation layers and the thermal tropopause and jet stream maximum allows to use these quantities as proxies to identify potential contrail formation in numerical weather prediction models. The contrail mitigation potential is tested by varying today's flight altitude distribution. It is found that flying 0.8 km higher during winter and lowering flight altitude in summer reduces the probability for contrail formation. Furthermore, the effect of prospective jet engine developments and their influence on contrail formation are tested. An increase in propulsion efficiency leads to a general increase in the potential occurrence of non-persistent and persistent contrails. Finally, the impact of alternative fuels (ethanol, methane, and hydrogen) is estimated and found to generally increase the likelihood of non-persistent contrails and, to a more limited extent, persistent contrails. [ABSTRACT FROM AUTHOR]

In the French Mediterranean, large fires have significant socioeconomic and environmental impacts. We used a long-term georeferenced fire time series (1958–2017) to analyze both spatial and temporal distributions of large fires (LFs; ≥100 ha). The region was impacted in some locations up to six times by recurrent LFs and 21 % of the total area burned by LFs occurred on a surface that previously burned in the past, with potential impact on forest resilience. We found contrasting patterns between the east and the west of the study area, the former experiencing fewer LFs but of a larger extent compared to the latter, with an average time of occurrence between LFs exceeding 4000 ha <7 years mostly in the eastern coastal area and >50 years in the west. This longitudinal gradient in LF return level contrasts with what we would expect from mean fire weather conditions strongly decreasing eastwards during the fire season but is consistent with larger fuel cover in the east, highlighting the strong role of fuel continuity in fire spread. Additionally, our analysis confirms the sharp decrease in both LF frequency and burned area in the early 1990s, due to the efficiency of fire suppression and prevention reinforced at that time, thereby weakening the functional climate–fire relationship across the region. [ABSTRACT FROM AUTHOR]

Large wildfires across parts of France can cause devastating damage which puts lives, infrastructure, and the natural ecosystem at risk. In the climate change context, it is essential to better understand how these large wildfires relate to weather and climate and how they might change in a warmer world. Such projections rely on the development of a robust modeling framework linking large wildfires to present-day atmospheric variability. Drawing from a MODIS product and a gridded meteorological dataset, we derived a suite of biophysical and fire danger indices and developed generalized linear models simulating the probability of large wildfires (>100 ha) at 8 km spatial and daily temporal resolutions across the entire country over the last two decades. The models were able to reproduce large-wildfire activity across a range of spatial and temporal scales. Different sensitivities to weather and climate were detected across different environmental regions. Long-term drought was found to be a significant predictor of large wildfires in flammability-limited systems such as the Alpine and southwestern regions. In the Mediterranean, large wildfires were found to be associated with both short-term fire weather conditions and longer-term soil moisture deficits, collectively facilitating the occurrence of large wildfires. Simulated probabilities on days with large wildfires were on average 2–3 times higher than normal with respect to the mean seasonal cycle, highlighting the key role of atmospheric variability in wildfire spread. The model has wide applications, including improving our understanding of the drivers of large wildfires over the historical period and providing a basis on which to estimate future changes to large wildfires from climate scenarios. [ABSTRACT FROM AUTHOR]

For many years real-time climate monitoring for temperature over France has been performed using a national index built by averaging the daily mean temperatures of constant subset of 30 stations with long-term series. In order to derive climate indices at finer scales, a spatialization of extreme daily temperatures (called ANASTASIA) had been produced on a 1 km regular grid using a regression-kriging method. The production covers 1947 to present period. Cross-validation shows low biases after the 1960s. The temporal homogeneity of the product is satisfying at the national scale from the 1970s. However, a high impact of the network density has been found and the use of a too coarse observation network deteriorates the analysis creating temporal heterogeneities. Finally, the ANASTASIA analysis has been used for real-time monitoring over France and detection of heat and cold wave episodes. The new products based on ANASTASIA are consistent with the current operational ones at national scale while bringing added values at local scales. [ABSTRACT FROM AUTHOR]

SCOPE Climate (Spatially COherent Probabilistic Extended Climate dataset) is a 25-member ensemble of 142-year daily high-resolution reconstructions of precipitation, temperature, and Penman–Monteith reference evapotranspiration over France, from 1 January 1871 to 29 December 2012. SCOPE Climate provides an ensemble of 25 spatially coherent gridded multivariate time series. It is derived from the statistical downscaling of the Twentieth Century Reanalysis (20CR) by the SCOPE method, which is based on the analogue approach. SCOPE Climate performs well in comparison to both dependent and independent data for precipitation and temperature. The ensemble aspect corresponds to the uncertainty related to the SCOPE method. SCOPE Climate is the first century-long gridded high-resolution homogeneous dataset available over France and thus has paved the way for improving knowledge on specific past meteorological events or for improving knowledge on climate variability, since the end of the 19th century. This dataset has also been designed as a forcing dataset for long-term hydrological applications and studies of the hydrological consequences of climate variability over France. SCOPE Climate is freely available for any non-commercial use and can be downloaded as NetCDF files from 10.5281/zenodo.1299760 for precipitation, 10.5281/zenodo.1299712 for temperature, and 10.5281/zenodo.1251843 for reference evapotranspiration. [ABSTRACT FROM AUTHOR]

The article presents a study that investigates the efficacy of the atmosphere ocean general circulation model (AOGCM) of the Institut Pierre Simon Laplace (IPSLCM5A) in assessing warm climate of the mid-Pliocene period in France. Researchers evaluated the atmospheric circulation using the AOGCM. They found that the model is effective because it produces detailed reports of the mid-Pliocene Warm Period (mPWP).

Snow avalanche activity is controlled to a large extent by snow and weather patterns. However, its response to climate fluctuations remains poorly documented. Previous studies have focused on direct extraction of trends in avalanche and winter climate data, and this study employs a time-implicit method to model annual avalanche activity in the French Alps during the 1958-2009 period from its most representative climatic drivers. Modelled snow and weather data for different elevations and aspects are considered as covariates that explain actual observed avalanche counts, modelled instability indexes, and a combination of both avalanche activity indicators. These three series present relatively similar fluctuations over the period and good consistency with historically harsh winters. A stepwise procedure is used to obtain regression models that accurately represent trends as well as high and low peaks with a small number of physically meaningful covariates, showing their climatic relevance. The activity indicators and their regression models seen as time series show, within a high interannual variability, a predominant bell-shaped pattern presumably related to a short period of colder and snowier winters around 1980, as well as a very slight but continuous increase between 1975 and 2000 concomitant with warming. Furthermore, the regression models quantify the respective weight of the different covariates, mostly temperature anomalies and south-facing snowpack characteristics to explain the trends and most of the exceptional winters. Regional differences are discussed as well as seasonal variations between winter and spring activity and confirm rather different snow and weather regimes influencing avalanche activity over the Northern and Southern Alps, depending on the season. [ABSTRACT FROM AUTHOR]

The article offers information on the Data on French Regionalized climate scenarios and Impacts on the environment and Adaptation of Societies (DRIAS) project in France. The two-year project was supported financially by the Ministry of Ecology, Sustainable Development, Transportation, and Housing's (MEDDTL) Management and Impact of Climate Change (GICC). Furthermore, DRIAS accessibility for the regional climate data is also reported.