Sensitivity analysis by the adjoint chemistry transport model DRAISfor an episode in the Berlin Ozone (BERLIOZ) experiment

International audienceThe Berlin Ozone Experiment (BERLIOZ) was carried out in summer 1998. One of its purposes was the evaluation of Chemistry Transport Models (CTM). CTM KAMM/DRAIS was one of the models considered. The data of 20 July were selected for evaluation. On that day, a pronounced ozone plume developed downwind of the city. Evaluation showed that the KAMM/DRAIS model is able to reproduce the meteorological and ozone data observed, except at farther distances (60?80 km) downwind of the city. In that region, the DRAIS model underestimates the measured ozone concentrations by 10?15 ppb, approximately. Therefore, this study was conducted to detect possible reasons for this deviation. A comprehensive sensitivity analysis was carried out to determine the most relevant model parameters. The adjoint DRAIS model was developed for this purpose, because for this study the application of this model is the most effective method of calculating the sensitivities. The least squares of the measured and simulated ozone concentrations between 08:00 UTC and 16:00 UTC at two stations 30 km and 70 km downwind of the city centre were chosen as distance function. The model parameters considered in this study are the complete set of initial and boundary species concentrations, emissions, and reaction rates, respectively. A sensitivity ranking showing the relevance of the individual parameters in the set is determined for each parameter set. In order to find out which modification in the parameter sets most reduces the cost function, simplified 4-D data assimilation was carried out. The result of this data assimilation shows that modifications of the reaction rates provide the best agreement between the measured and the simulated ozone concentrations at both stations. However, the modified reaction rates seem to be unrealistic for the whole simulation period. Therefore, the good agreement should not be overestimated. The agreement is still acceptable when the parameters in the other sets are modified together. The investigation demonstrates that an analysis of this type can help to explain inconsistencies between observations and simulations. But in the case considered here the inconsistencies cannot be explained by an error in only one parameter set

Climate change projections for CORDEX-Africa with COSMO-CLM regional climate model and differences with the driving global climate models

In the framework of the coordinated regional climate downscaling experiment (CORDEX), an ensemble of climate change projections for Africa has been created by downscaling the simulations of four global climate models (GCMs) by means of the consortium for small-scale modeling (COSMO) regional climate model (RCM) (COSMO-CLM, hereafter, CCLM). Differences between the projected temperature and precipitation simulated by CCLM and the driving GCMs are analyzed and discussed. The projected increase of seasonal temperature is found to be relatively similar between GCMs and RCM, although large differences (more than 1 °C) exist locally. Differences are also found for extreme-event related quantities, such as the spread of the upper end of the maximum temperature probability distribution function and, in turn, the duration of heat waves. Larger uncertainties are found in the future precipitation changes; this is partly a consequence of the inter-model (GCMs) variability over some areas (e.g. Sahel). However, over other regions (e.g. Central Africa) the rainfall trends simulated by CCLM and the GCMs show opposite signs, with CCLM showing a significant reduction in precipitation at the end of the century. This uncertain and sometimes contrasting behaviour is further investigated by analyzing the different models’ response to the land–atmosphere interaction and feedback. Given the large uncertainty associated with inter-model variability across GCMs and the reduced spread in the results when a single RCM is used for downscaling, we strongly emphasize the importance of exploiting fully the CORDEX-Africa multi-GCM/multi-RCM ensemble in order to assess the robustness of the climate change signal and, possibly, to identify and quantify the many sources of uncertainty that still remain

Sensitivity of european temperature to albedo parameterization in the regional climate model COSMO-CLM linked to extreme land use changes

Previous studies based on observations and models are uncertain about the biophysical impact of af- and deforestation in the northern hemisphere mid-latitude summers, and show either a cooling or warming. The spatial distribution, magnitude and direction are still uncertain. In this study, the effect of three different albedo parameterizations in the regional climate model COSMO-CLM (v5.09) is examined performing idealized experiments at 0.44° horizontal resolution across the EURO-CORDEX domain during 1986–2015. De- and af-forestation simulations are compared to a simulation with no land cover change. Emphasis is put on the impact of changes in radiation and turbulent fluxes. A clear latitudinal pattern is found, which results partly due to the strong land cover conversion from forest- to grassland in the high latitudes and open land to forest conversion in mid-latitudes. Afforestation warms the climate in winter, and strongest in mid-latitudes. Results are indifferent in summer owing to opposing albedo and evapotranspiration effects of comparable size but different sign. Thus, the net effect is small for summer. Depending on the albedo parameterization in the model, the temperature effect can turn from cooling to warming in mid-latitude summers. The summer warming due to deforestation to grassland is up to 3°C higher than due to afforestation. The cooling by grass or warming by forest is in magnitude comparable and small in winter. The strength of the described near-surface temperature changes depends on the magnitude of the individual biophysical changes in the specific background climate conditions of the region. Thus, the albedo parameterization need to account for different vegetation types. Furthermore, we found that, depending on the region, the land cover change effect is more important than the model uncertainty due to albedo parameterization. This is important information for model development

Precipitation frequency in Med-CORDEX and EURO-CORDEX ensembles from 0.44° to convection-permitting resolution: impact of model resolution and convection representation

Recent studies using convection-permitting (CP) climate simulations have demonstrated a step-change in the representation of heavy rainfall and rainfall characteristics (frequency-intensity) compared to coarser resolution Global and Regional climate models. The goal of this study is to better understand what explains the weaker frequency of precipitation in the CP ensemble by assessing the triggering process of precipitation in the different ensembles of regional climate simulations available over Europe. We focus on the statistical relationship between tropospheric temperature, humidity and precipitation to understand how the frequency of precipitation over Europe and the Mediterranean is impacted by model resolution and the representation of convection (parameterized vs. explicit). We employ a multi-model data-set with three different resolutions (0.44°, 0.11° and 0.0275°) produced in the context of the MED-CORDEX, EURO-CORDEX and the CORDEX Flagship Pilot Study "Convective Phenomena over Europe and the Mediterranean" (FPSCONV). The multi-variate approach is applied to all model ensembles, and to several surface stations where the integrated water vapor (IWV) is derived from Global Positioning System (GPS) measurements. The results show that all model ensembles capture the temperature dependence of the critical value of IWV (IWVcv), above which an increase in precipitation frequency occurs, but the differences between the models in terms of the value of IWVcv, and the probability of its being exceeded, can be large at higher temperatures. The lower frequency of precipitation in convection-permitting simulations is not only explained by higher temperatures but also by a higher IWVcv necessary to trigger precipitation at similar temperatures, and a lower probability to exceed this critical value. The spread between models in simulating IWVcv and the probability of exceeding IWVcv is reduced over land in the ensemble of models with explicit convection, especially at high temperatures, when the convective fraction of total precipitation becomes more important and the influence of the representation of entrainment in models thus becomes more important. Over lowlands, both model resolution and convection representation affect precipitation triggering while over mountainous areas, resolution has the highest impact due to orography-induced triggering processes. Over the sea, since lifting is produced by large-scale convergence, the probability to exceed IWVcv does not depend on temperature, and the model resolution does not have a clear impact on the results

The first multi-model ensemble of regional climate simulations at kilometer-scale resolution, part I: evaluation of precipitation

Here we present the first multi-model ensemble of regional climate simulations at kilometer-scale horizontal grid spacing over a decade long period. A total of 23 simulations run with a horizontal grid spacing of ∼3 km, driven by ERA-Interim reanalysis, and performed by 22 European research groups are analysed. Six different regional climate models (RCMs) are represented in the ensemble. The simulations are compared against available high-resolution precipitation observations and coarse resolution (∼ 12 km) RCMs with parameterized convection. The model simulations and observations are compared with respect to mean precipitation, precipitation intensity and frequency, and heavy precipitation on daily and hourly timescales in different seasons. The results show that kilometer-scale models produce a more realistic representation of precipitation than the coarse resolution RCMs. The most significant improvements are found for heavy precipitation and precipitation frequency on both daily and hourly time scales in the summer season. In general, kilometer-scale models tend to produce more intense precipitation and reduced wet-hour frequency compared to coarse resolution models. On average, the multi-model mean shows a reduction of bias from ∼ −40% at 12 km to ∼ −3% at 3 km for heavy hourly precipitation in summer. Furthermore, the uncertainty ranges i.e. the variability between the models for wet hour frequency is reduced by half with the use of kilometer-scale models. Although differences between the model simulations at the kilometer-scale and observations still exist, it is evident that these simulations are superior to the coarse-resolution RCM simulations in the representing precipitation in the present-day climate, and thus offer a promising way forward for investigations of climate and climate change at local to regional scales

Porcine transcriptome analysis based on 97 non-normalized cDNA libraries and assembly of 1,021,891 expressed sequence tags.

RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are.BACKGROUND: Knowledge of the structure of gene expression is essential for mammalian transcriptomics research. We analyzed a collection of more than one million porcine expressed sequence tags (ESTs), of which two-thirds were generated in the Sino-Danish Pig Genome Project and one-third are from public databases. The Sino-Danish ESTs were generated from one normalized and 97 non-normalized cDNA libraries representing 35 different tissues and three developmental stages. RESULTS: Using the Distiller package, the ESTs were assembled to roughly 48,000 contigs and 73,000 singletons, of which approximately 25% have a high confidence match to UniProt. Approximately 6,000 new porcine gene clusters were identified. Expression analysis based on the non-normalized libraries resulted in the following findings. The distribution of cluster sizes is scaling invariant. Brain and testes are among the tissues with the greatest number of different expressed genes, whereas tissues with more specialized function, such as developing liver, have fewer expressed genes. There are at least 65 high confidence housekeeping gene candidates and 876 cDNA library-specific gene candidates. We identified differential expression of genes between different tissues, in particular brain/spinal cord, and found patterns of correlation between genes that share expression in pairs of libraries. Finally, there was remarkable agreement in expression between specialized tissues according to Gene Ontology categories. CONCLUSION: This EST collection, the largest to date in pig, represents an essential resource for annotation, comparative genomics, assembly of the pig genome sequence, and further porcine transcription studies.Published versio

The first multi-model ensemble of regional climate simulations at kilometer-scale resolution. Part I: Evaluation of precipitation

Here we present the first multi-model ensemble of regional climate simulations at kilometer-scale horizontal grid spacing over a decade long period. A total of 23 simulations run with a horizontal grid spacing of ∼ 3 km, driven by ERA-Interim reanalysis, and performed by 22 European research groups are analysed. Six different regional climate models (RCMs) are represented in the ensemble. The simulations are compared against available high-resolution precipitation observations and coarse resolution (∼ 12 km) RCMs with parameterized convection. The model simulations and observations are compared with respect to mean precipitation, precipitation intensity and frequency, and heavy precipitation on daily and hourly timescales in different seasons. The results show that kilometer-scale models produce a more realistic representation of precipitation than the coarse resolution RCMs. The most significant improvements are found for heavy precipitation and precipitation frequency on both daily and hourly time scales in the summer season. In general, kilometer-scale models tend to produce more intense precipitation and reduced wet-hour frequency compared to coarse resolution models. On average, the multi-model mean shows a reduction of bias from ∼ −40 at 12 km to ∼ −3 at 3 km for heavy hourly precipitation in summer. Furthermore, the uncertainty ranges i.e. the variability between the models for wet hour frequency is reduced by half with the use of kilometer-scale models. Although differences between the model simulations at the kilometer-scale and observations still exist, it is evident that these simulations are superior to the coarse-resolution RCM simulations in the representing precipitation in the present-day climate, and thus offer a promising way forward for investigations of climate and climate change at local to regional scales. © 2021, The Author(s)