Regional climate downscaling with prior statistical correction of the global climate forcing

International audienceA novel climate downscaling methodology that attempts to correct climate simulation biases is proposed. By combining an advanced statistical bias correction method with a dynamical downscaling it constitutes a hybrid technique that yields nearly unbiased, high-resolution, physically consistent, three-dimensional fields that can be used for climate impact studies. The method is based on a prior statistical distribution correction of large-scale global climate model (GCM) 3-dimensional output fields to be taken as boundary forcing of a dynamical regional climate model (RCM). GCM fields are corrected using meteorological reanalyses. We evaluate this methodology over a decadal experiment. The improvement in terms of spatial and temporal variability is discussed against observations for a past period. The biases of the downscaled fields are much lower using this hybrid technique, up to a factor 4 for the mean temperature bias compared to the dynamical downscaling alone without prior bias correction. Precipitation biases are subsequently improved hence offering optimistic perspectives for climate impact studies

On the impact of the vertical resolution on chemistry-transport modelling

International audienceThis paper presents a sensitivity analysis of the modelling of air pollutant concentrations in the surface layer with the WRF/CHIMERE models. The influence of the vertical resolution near the surface is studied. The simulations are carried out over two periods (winter and summer 2009) over the Paris area. Three model configurations are used: (i) the CHIMERE mesh used for the PREVAIR forecast (8 levels from 995 to 500 hPa), (ii) a mesh refined along the whole vertical axis (20 levels from 995 to 500 hPa) and (iii) a mesh with a refinement near the surface (9 levels from 999 to 500 hPa). The results are discussed in terms of differences on surface concentrations between the reference case and an improved resolution. Adding a point close to the surface appears to be important mainly for high nocturnal concentrations in very stable boundary layers. Refining the vertical mesh, with 20 levels instead of 8, enables to model new structures in the well mixed boundary layer, but with a moderate impact at the surface. It is shown that the different model configurations lead to changes of a few mu g m(-3) at most, showing that the vertical mesh is not the most sensitive factor in chemistry-transport modelling when results are compared to surface measurements. This finding validates the fact that a simplified vertical mesh is suitable for air quality forecasting even if an improved vertical resolution close to the ground is important to take into account the urban increment

Eurodelta multi-model simulated and observed particulate matter trends in Europe in the period of 1990–2010

The Eurodelta-Trends (EDT) multi-model experiment, aimed at assessing the efficiency of emission mitigation measures in improving air quality in Europe during 1990–2010, was designed to answer a series of questions regarding European pollution trends; i.e. were there significant trends detected by observations? Do the models manage to reproduce observed trends? How close is the agreement between the models and how large are the deviations from observations? In this paper, we address these issues with respect to particulate matter (PM) pollution. An in-depth trend analysis has been performed for PM10 and PM2.5 for the period of 2000–2010, based on results from six chemical transport models and observational data from the EMEP (Cooperative Programme for Monitoring and Evaluation of the Long-range Transmission of Air Pollutants in Europe) monitoring network. Given harmonization of set-up and main input data, the differences in model results should mainly result from differences in the process formulations within the models themselves, and the spread in the model-simulated trends could be regarded as an indicator for modelling uncertainty. The model ensemble simulations indicate overall decreasing trends in PM10 and PM2.5 from 2000 to 2010, with the total reductions of annual mean concentrations by between 2 and 5 (7 for PM10) µg m−3 (or between 10 % and 30 %) across most of Europe (by 0.5–2 µg m−3 in Fennoscandia, the north-west of Russia and eastern Europe) during the studied period. Compared to PM2.5, relative PM10 trends are weaker due to large inter-annual variability of natural coarse PM within the former. The changes in the concentrations of PM individual components are in general consistent with emission reductions. There is reasonable agreement in PM trends estimated by the individual models, with the inter-model variability below 30 %–40 % over most of Europe, increasing to 50 %–60 % in the northern and eastern parts of the EDT domain. Averaged over measurement sites (26 for PM10 and 13 for PM2.5), the mean ensemble-simulated trends are −0.24 and −0.22 µg m−3 yr−1 for PM10 and PM2.5, which are somewhat weaker than the observed trends of −0.35 and −0.40 µg m−3 yr−1 respectively, partly due to model underestimation of PM concentrations. The correspondence is better in relative PM10 and PM2.5 trends, which are −1.7 % yr−1 and −2.0 % yr−1 from the model ensemble and −2.1 % yr−1 and −2.9 % yr−1 from the observations respectively. The observations identify significant trends (at the 95 % confidence level) for PM10 at 56 % of the sites and for PM2.5 at 36 % of the sites, which is somewhat less that the fractions of significant modelled trends. Further, we find somewhat smaller spatial variability of modelled PM trends with respect to the observed ones across Europe and also within individual countries. The strongest decreasing PM trends and the largest number of sites with significant trends are found for the summer season, according to both the model ensemble and observations. The winter PM trends are very weak and mostly insignificant. Important reasons for that are the very modest reductions and even increases in the emissions of primary PM from residential heating in winter. It should be kept in mind that all findings regarding modelled versus observed PM trends are limited to the regions where the sites are located. The analysis reveals considerable variability of the role of the individual aerosols in PM10 trends across European countries. The multi-model simulations, supported by available observations, point to decreases in concentrations playing an overall dominant role. Also, we see relatively large contributions of the trends of and to PM10 decreasing trends in Germany, Denmark, Poland and the Po Valley, while the reductions of primary PM emissions appear to be a dominant factor in bringing down PM10 in France, Norway, Portugal, Greece and parts of the UK and Russia. Further discussions are given with respect to emission uncertainties (including the implications of not accounting for forest fires and natural mineral dust by some of the models) and the effect of inter-annual meteorological variability on the trend analysis.The Ineris coordination of the EURODELTA-Trends exercise has been supported by the French Ministry in charge of Ecology in the context of the Task Force on Measurement and Modelling of the EMEP program of the LRTAP Convention. The CHIMERE simulations were performed using the TGCC supercomputers under GENCI computing allocation. The work of EMEP MSC-W has been supported by the EMEP Trust Fund under the United Nations Economic Commission for Europe (UN ECE). Funding for the MATCH participation was jointly divided between Nordforsk through the research programme Nordic Welfare (grant no. 75007), the Swedish Environmental Protection Agency through the SCAC research programme, and the 2017–2018 Belmont Forum and BiodivERsA joint call for research proposals, under the BiodivScen ERA-Net COFUND programme, with the funding organisations AKA (contract no. 326328), ANR (grant no. ANR-18-EBI4-007), BMBF (KFZ; grant no. 01LC1810A), FORMAS (contract nos. 2018-02434, 2018-02436, 2018-02437, and 2018-02438) and MICINN (APCIN; grant no. PCI2018-093149). Giancarlo Ciarelli has been supported by ADEME and the Swiss National Science Foundation (grant no. P2EZP2_175166). MINNI participation in this project was supported by the “Cooperation Agreement for support to international Conventions, Protocols and related negotiations on air pollution issues”, funded by the Italian Ministry for the Environment, Land and Sea. Financial support for the Institute for Advanced Sustainability Studies (IASS) has been provided by the Federal Ministry of Education and Research of Germany (BMBF) and the Ministry for Science, Research and Culture of the State of Brandenburg (MWFK). The work of CIEMAT has been supported by the Ministry for the Ecological Transition and Demographic Challenge (MITERD).Peer Reviewed"Article signat per 23 autors/es: Svetlana Tsyro, Wenche Aas, Augustin Colette, Camilla Andersson, Bertrand Bessagnet, Giancarlo Ciarelli, Florian Couvidat, Kees Cuvelier, Astrid Manders, Kathleen Mar, Mihaela Mircea, Noelia Oter, Maria-Teresa Pay, Valentin Raffort, Yelva Roustan, Mark R. Theobald, Marta G. Vivanco, Hilde Fagerli, Peter Wind, Gino Briganti, Andrea Cappelletti, Massimo D'Isidoro, and Mario Adani"Postprint (published version

Pollution atmosphérique et climat

National audienceClimate change and air quality are closely related: through the policy measures implemented to mitigate these major environmental threats but also through the geophysical processes that drive them. We designed, developed and implemented a comprehensive regional air quality and climate modelling system to investigate future air quality in Europe taking into account the combined pressure of future climate change and long range transport. Using the prospective scenarios of the last generation of pathways for both climate change (emissions of well mixed greenhouse gases) and air pollutants, we can provide a quantitative view into the possible future air quality in Europe. We find that ozone pollution will decrease substantially under the most stringent scenario but the efforts of the air quality legislation will be adversely compensated by the penalty of global warming and long range transport for the business as usual scenario. For particulate matter, the projected reduction of emissions efficiently reduces exposure levels.Changement climatique et qualité de l'air sont intimement liés : à travers les politiques de gestion mises en oeuvre pour atténuer ces menaces environnementales majeures mais aussi à travers les processus géophysiques qui les gouvernent. Afin de pouvoir étudier l'évolution de la pollution atmosphérique en Europe en prenant en compte l'influence conjointe du changement climatique et du transport à longue distance, nous avons conçu, développé et mis en oeuvre un système complet de modélisation régionale du climat et de la qualité de l'air. En utilisant des scénarios prospectifs de dernière génération relatifs au changement climatique (émissions de gaz à effet de serre) mais aussi pour les polluants à courte durée de vie, nous avons pu proposer une quantification de l'évolution future de la qualité de l'air en Europe. D'après le scénario le plus volontariste, la pollution liée à l'ozone sera réduite de manière substantielle mais les efforts positifs induits par les politiques de gestion de la qualité de l'air seront contrebalancés par le changement climatique et le transport à longue distance pour le scénario statu-quo. En ce qui concerne les particules, les réductions d'émissions futures réduiront de manière efficace les niveaux d'exposition

Evaluation of the chimere model at high resolution over Europe : focus on urban area

International audienc

Trace gas/aerosol boundary concentrations and their impacts on continental-scale AQMEII modeling domains

Copyright 2011 Elsevier B.V., All rights reserved.Over twenty modeling groups are participating in the Air Quality Model Evaluation International Initiative (AQMEII) in which a variety of mesoscale photochemical and aerosol air quality modeling systems are being applied to continental-scale domains in North America and Europe for 2006 full-year simulations for model inter-comparisons and evaluations. To better understand the reasons for differences in model results among these participating groups, each group was asked to use the same source of emissions and boundary concentration data for their simulations. This paper describes the development and application of the boundary concentration data for this AQMEII modeling exercise. The European project known as GEMS (Global and regional Earth-system Monitoring using Satellite and in-situ data) has produced global-scale re-analyses of air quality for several years, including 2006 (http://gems.ecmwf.int). The GEMS trace gas and aerosol data were made available at 3-hourly intervals on a regular latitude/longitude grid of approximately 1.9° resolution within 2 "cut-outs" from the global model domain. One cut-out was centered over North America and the other over Europe, covering sufficient spatial domain for each modeling group to extract the necessary time- and space-varying (horizontal and vertical) concentrations for their mesoscale model boundaries. Examples of the impact of these boundary concentrations on the AQMEII continental simulations are presented to quantify the sensitivity of the simulations to boundary concentrations. In addition, some participating groups were not able to use the GEMS data and instead relied upon other sources for their boundary concentration specifications. These are noted, and the contrasting impacts of other data sources for boundary data are presented. How one specifies four-dimensional boundary concentrations for mesoscale air quality simulations can have a profound impact on the model results, and hence, this aspect of data preparation must be performed with considerable care.Peer reviewedFinal Accepted Versio

Tropospheric Ozone Assessment Report : Present-day ozone distribution and trends relevant to human health

This study quantifies the present-day global and regional distributions (2010–2014) and trends (2000–2014) for five ozone metrics relevant for short-term and long-term human exposure. These metrics, calculated by the Tropospheric Ozone Assessment Report, are: 4th highest daily maximum 8-hour ozone (4MDA8); number of days with MDA8 > 70 ppb (NDGT70), SOMO35 (annual Sum of Ozone Means Over 35 ppb) and two seasonally averaged metrics (3MMDA1; AVGMDA8). These metrics were explored at ozone monitoring sites worldwide, which were classified as urban or non-urban based on population and nighttime lights data.Present-day distributions of 4MDA8 and NDGT70, determined predominantly by peak values, are similar with highest levels in western North America, southern Europe and East Asia. For the other three metrics, distributions are similar with North–South gradients more prominent across Europe and Japan. Between 2000 and 2014, significant negative trends in 4MDA8 and NDGT70 occur at most US and some European sites. In contrast, significant positive trends are found at many sites in South Korea and Hong Kong, with mixed trends across Japan. The other three metrics have similar, negative trends for many non-urban North American and some European and Japanese sites, and positive trends across much of East Asia. Globally, metrics at many sites exhibit non-significant trends. At 59% of all sites there is a common direction and significance in the trend across all five metrics, whilst 4MDA8 and NDGT70 have a common trend at ~80% of all sites. Sensitivity analysis shows AVGMDA8 trends differ with averaging period (warm season or annual). Trends are unchanged at many sites when a 1995–2014 period is used; although fewer sites exhibit non-significant trends. Over the longer period 1970–2014, most Japanese sites exhibit positive 4MDA8/SOMO35 trends. Insufficient data exist to characterize ozone trends for the rest of Asia and other world regions

Regional climate hindcast simulations within EURO-CORDEX: evaluation of a WRF multi-physics ensemble

In the current work we present six hindcast WRF (Weather Research and Forecasting model) simulations for the EURO-CORDEX (European Coordinated Regional Climate Downscaling Experiment) domain with different configurations in microphysics, convection and radiation for the time period 1990?2008. All regional model simulations are forced by the ERA-Interim reanalysis and have the same spatial resolution (0.44°). These simulations are evaluated for surface temperature, precipitation, short- and longwave downward radiation at the surface and total cloud cover. The analysis of the WRF ensemble indicates systematic temperature and precipitation biases, which are linked to different physical mechanisms in the summer and winter seasons. Overestimation of total cloud cover and underestimation of downward shortwave radiation at the surface, mostly linked to the Grell?Devenyi convection and CAM (Community Atmosphere Model) radiation schemes, intensifies the negative bias in summer temperatures over northern Europe (max ?2.5 °C). Conversely, a strong positive bias in downward shortwave radiation in summer over central (40?60%) and southern Europe mitigates the systematic cold bias over these regions, signifying a typical case of error compensation. Maximum winter cold biases are over northeastern Europe (?2.8 °C); this location suggests that land?atmosphere rather than cloud?radiation interactions are to blame. Precipitation is overestimated in summer by all model configurations, especially the higher quantiles which are associated with summertime deep cumulus convection. The largest precipitation biases are produced by the Kain?Fritsch convection scheme over the Mediterranean. Precipitation biases in winter are lower than those for summer in all model configurations (15?30%). The results of this study indicate the importance of evaluating not only the basic climatic parameters of interest for climate change applications (temperature and precipitation), but also other components of the energy and water cycle, in order to identify the sources of systematic biases, possible compensatory or masking mechanisms and suggest pathways for model improvement.The contribution from Universidad de Cantabria was funded by the Spanish R&D programme through projects CORWES (CGL2010-22158-C02-01) and WRF4G (CGL2011-28864), co-funded by the European Regional Development Fund. M. García-Díez acknowledges financial support from the EXTREMBLES (CGL2010-21869) project

Eurodelta multi-model simulated and observed particulate matter trends in Europe in the period of 1990-2010

The Eurodelta-Trends (EDT) multi-model experiment, aimed at assessing the efficiency of emission mitigation measures in improving air quality in Europe during 1990-2010, was designed to answer a series of questions regarding European pollution trends; i.e. were there significant trends detected by observations? Do the models manage to reproduce observed trends? How close is the agreement between the models and how large are the deviations from observations? In this paper, we address these issues with respect to particulate matter (PM) pollution. An in-depth trend analysis has been performed for PM10 and PM2.5 for the period of 2000-2010, based on results from six chemical transport models and observational data from the EMEP (Cooperative Programme for Monitoring and Evaluation of the Long-range Transmission of Air Pollutants in Europe) monitoring network. Given harmonization of set-up and main input data, the differences in model results should mainly result from differences in the process formulations within the models themselves, and the spread in the model-simulated trends could be regarded as an indicator for modelling uncertainty.The model ensemble simulations indicate overall decreasing trends in PM10 and PM2.5 from 2000 to 2010, with the total reductions of annual mean concentrations by between 2 and 5 (7 for PM10) mu g m(-3) (or between 10 % and 30 %) across most of Europe (by 0.5-2 mu g m(-3) in Fennoscandia, the north-west of Russia and eastern Europe) during the studied period. Compared to PM2.5, relative PM10 trends are weaker due to large interannual variability of natural coarse PM within the former. The changes in the concentrations of PM individual components are in general consistent with emission reductions. There is reasonable agreement in PM trends estimated by the individual models, with the inter-model variability below 30 %-40 % over most of Europe, increasing to 50 %-60 % in the northern and eastern parts of the EDT domain.Averaged over measurement sites (26 for PM10 and 13 for PM2.5), the mean ensemble-simulated trends are - 0.24 and -0.22 mu g m(-3) yr(-1) for PM10 and PM2.5, which are somewhat weaker than the observed trends of - 0.35 and -0.40 mu g m(-3) yr(-1) respectively, partly due to model underestimation of PM concentrations. The correspondence is better in relative PM10 and PM2.5 trends, which are -1.7 % yr(-1) and -2.0 % yr(-1) from the model ensemble and -2.1 % yr(-1) and -2.9 % yr(-1) from the observations respectively. The observations identify significant trends (at the 95 % confidence level) for PM10 at 56 % of the sites and for PM2.5 at 36 % of the sites, which is somewhat less that the fractions of significant modelled trends. Further, we find somewhat smaller spatial variability of modelled PM trends with respect to the observed ones across Europe and also within individual countries.The strongest decreasing PM trends and the largest number of sites with significant trends are found for the summer season, according to both the model ensemble and observations. The winter PM trends are very weak and mostly insignificant. Important reasons for that are the very modest reductions and even increases in the emissions of primary PM from residential heating in winter. It should be kept in mind that all findings regarding modelled versus observed PM trends are limited to the regions where the sites are located.The analysis reveals considerable variability of the role of the individual aerosols in PM10 trends across European countries. The multi-model simulations, supported by available observations, point to decreases in SO42- concentrations playing an overall dominant role. Also, we see relatively large contributions of the trends of NH4+ and NO3- to PM10 decreasing trends in Germany, Denmark, Poland and the Po Valley, while the reductions of primary PM emissions appear to be a dominant factor in bringing down PM10 in France, Norway, Portugal, Greece and parts of the UK and Russia. Further discussions are given with respect to emission uncertainties (including the implications of not accounting for forest fires and natural mineral dust by some of the models) and the effect of inter-annual meteorological variability on the trend analysis.Peer reviewe