ALBERT

Description: This work uses a network of GPS stations over Europe from which a homogenized integrated water vapor (IWV) dataset has been retrieved, completed with colocated temperature and precipitation measurements over specific stations to (i) estimate the biases of six regional climate models over Europe in terms of humidity; (ii) understand their origins; and (iii) finally assess the impact of these biases on the frequency of occurrence of precipitation. The evaluated simulations have been performed in the framework of HYMEX/Med-CORDEX programs and cover the Mediterranean area and part of Europe at horizontal resolutions of 50 to 12 km. The analysis shows that models tend to overestimate the low values of IWV and the use of the nudging technique reduces the differences between GPS and simulated IWV. Results suggest that physics of models mostly explain the mean biases, while dynamics affects the variability. The land surface–atmosphere exchanges affect the estimation of IWV over most part of Europe, especially in summer. The limitations of the models to represent these processes explain part of their biases in IWV. However, models correctly simulate the dependance between IWV and temperature, and specifically the deviation that this relationship experiences regarding the Clausius–Clapeyron law after a critical value of temperature (Tbreak). The high spatial variability of Tbreak indicates that it has a strong dependence on local processes which drive the local humidity sources. This explains why the maximum values of IWV are not necessarily observed over warmer areas, which are often dry areas. Finally, it is shown over the SIRTA observatory (near Paris) that the frequency of occurrence of light precipitation is strongly conditioned by the biases in IWV and by the precision of the models to reproduce the distribution of IWV as a function of the temperature. The results of the models indicate that a similar dependence occurs in other areas of Europe, especially where precipitation has a predominantly convective character. According to the observations, for each range of temperature, there is a critical value of IWV from which precipitation starts to increase. The critical values and the probability of exceeding them are simulated with a bias that depends on the model. Those models, which generally present light precipitation too often, show lower critical values and higher probability of exceeding them.

Description: This study investigates the means, variability, and trends in integrated water vapour (IWV) from two modern reanalyses (ERA-Interim and MERRA-2) from 1980 to 2016 and ground-based GPS data from 1995 to 2010. It is found that the mean distributions and inter-annual variability in IWV in the reanalyses and GPS are consistent, even in regions of strong gradients. ERA-Interim is shown to exhibit a slight moist bias in the extra-tropics and a slight dry bias in the tropics (both on the order of 0.5 to 1 kg m−2) compared to GPS. ERA-Interim is also generally drier than MERRA-2 over the ocean and within the tropics. Differences in variability and trends are pointed out at a few GPS sites. These differences can be due to representativeness errors (for sites located in coastal regions and regions of complex topography), gaps and inhomogeneities in the GPS series (due to equipment changes), or potential inhomogeneities in the reanalyses (due to changes in the observing system). Trends in IWV and surface temperature in ERA-Interim and MERRA-2 are shown to be consistent, with positive IWV trends generally correlated with surface warming, but MERRA-2 presents a more general global moistening trend compared to ERA-Interim. Inconsistent trends are found between the two reanalyses over Antarctica and most of the Southern Hemisphere, and over central and northern Africa. The uncertainty in current reanalyses remains quite high in these regions, where few in situ observations are available, and the spread between models is generally important. Inter-annual and decadal variations in IWV are also shown to be strongly linked with variations in the atmospheric circulation, especially in arid regions, such as northern Africa and Western Australia, which add uncertainty in the trend estimates, especially over the shorter period. In these regions, the Clausius–Clapeyron scaling ratio is found not to be a good humidity proxy for inter-annual variability and decadal trends.

Description: In the context of a network of sky cameras installed on atmospheric multi-instrumented sites, we present an algorithm named ELIFAN, which aims to estimate the cloud cover amount from full-sky visible daytime images with a common principle and procedure. ELIFAN was initially developed for a self-made full-sky image system presented in this article and adapted to a set of other systems in the network. It is based on red-to-blue ratio thresholding for the distinction of cloudy and cloud-free pixels of the image and on the use of a cloud-free sky library, without taking account of aerosol loading. Both an absolute (without the use of a cloud-free reference image) and a differential (based on a cloud-free reference image) red-to-blue ratio thresholding are used. An evaluation of the algorithm based on a 1-year-long series of images shows that the proposed algorithm is very convincing for most of the images, with about 97 % of relevance in the process, outside the sunrise and sunset transitions. During those latter periods, however, ELIFAN has large difficulties in appropriately processing the image due to a large difference in color composition and potential confusion between cloud-free and cloudy sky at that time. This issue also impacts the library of cloud-free images. Beside this, the library also reveals some limitations during daytime, with the possible presence of very small and/or thin clouds. However, the latter have only a small impact on the cloud cover estimate. The two thresholding methodologies, the absolute and the differential red-to-blue ratio thresholding processes, agree very well, with departure usually below 8 % except in sunrise–sunset periods and in some specific conditions. The use of the cloud-free image library gives generally better results than the absolute process. It particularly better detects thin cirrus clouds. But the absolute thresholding process turns out to be better sometimes, for example in some cases in which the sun is hidden by a cloud.

Description: For several years, global warming has been unequivocal, leading to climate change at global, regional and local scales. A good understanding of climate characteristics and local variability is important for adaptation and response. Indeed, the contribution of local processes and their understanding in the context of warming are still very little studied and poorly represented in climate models. Improving the knowledge of surface-atmosphere feedback effects at local scales is therefore important for future projections. Using observed data in the Paris region from 1979 to 2017, this study characterizes the changes observed over the last 40 years for six climatic parameters (e.g., mean, maximum and minimum air temperature at 2 metres, 2 metres relative and specific humidities and precipitation) at the annual and seasonal scales and in summer, regardless of large-scale circulation, with an attribution of which part of the change is linked to large scale circulation or thermordynamic. The results show that some trends differ from the ones observed at the regional or global scale. Indeed, in the Paris region, the maximum temperature increases faster than does the minimum temperature. The most significant trends are observed in spring and in summer, with a strong increase in temperature and a very strong decrease in relative humidity, while specific humidity and precipitation show no significant trends. The summer trends can be explained more precisely using large-scale circulation, especially regarding the evolution of the precipitation and specific humidity. The analysis indicates the important role of surface-atmosphere feedback in local variability and that this feedback is amplified or inhibited in a context of global warming, especially in an urban environment.

Description: This work uses a network of GPS stations over Europe from which a homogenised integrated water vapor (IWV) dataset has been retrieved, completed with colocated temperature and precipitation measurements over specific stations to i) estimate the biases of six regional climate models over Europe in terms of humidity; ii) understand their origins; iii) and finally assess the impact of these biases on the frequency of occurrence of precipitation. The evaluated simulations have been performed in the framework of HYMEX/Med-CORDEX programs and cover the Mediterranean area and part of Europe at horizontal resolutions of 50 to 12km. The analysis shows that models tend to overestimate the low values of IWV and the use of the nudging technique reduces the differences between GPS and simulated IWV. Results suggest that physics of models mostly explain the mean biases, while dynamics affects the variability. The land surface/atmosphere exchanges affect the estimation of IWV over most part of Europe, especially in summer. The limitations of the models to represent these processes explain part of their baises in IWV. However, models correctly simulate the dependance between IWV and temperature, and specifically the deviation that this relationship experiences regarding the Clausius-Clapeyron law after a critical value of temperature (Tbreak). The high spatial variability of Tbreak indicates that it has a strong dependence on local processes which drive the local humidity sources. This explains why the maximum values of IWV are not necessarely observed over warmer area, that are often dry area. Finally, it is shown over SIRTA observatory (near Paris) that the frequency of occurrence of light precipitation is strongly conditioned by the biases in IWV and by the precision of the models to reproduce the distribution of IWV as a function of the temperature. The results of the models indicate that a similar dependence occurs in other areas of Europe, especially where precipitation has a predominantly convective character. According to the observations, for each range of temperature, there is a critical value of IWV from which precipitation picks up. The critical values and the probability to exceed them are simulated with a bias that depends on the model. Those models which present too often light precipitation generally show lower critical values and higher probability to exceed them.

Description: Water vapour plays a key role in the climate system. However, its short residence time in the atmosphere and its high variability in space and time make it challenging when it comes to study trends and variability. There are several sources of water vapour data. In this work we use Integrated Water Vapour (IWV) estimated from GPS observations and atmospheric reanalyses. Monthly and seasonal means, interannual variability, and linear trends are analysed and compared for the period between 1995 and 2010. A general good agreement is found but this study highlights issues in both GPS and reanalysis data sets. In GPS, gaps and inhomogeneities in the time series are evidenced, which affect mainly variability and trend estimation. In ERA-Interim, too strong trends in certain regions (e.g. drying over northern Africa and Australia, and moistening over northern South America) were found. Representativeness differences in coastal areas and regions of complex topography (mountain ranges, islands) are also evidenced as limitations to the intercomparison of the point observations and reanalysis data. A general good agreement is found for the means and variabilities, with the exception of a few stations where representativeness issues are suspected. Monthly IWV trends are also found to be in good sign agreement, with the exception of a handful of stations where, in addition to representativeness errors, there might be inhomogeneities in the GPS time series. Seasonal trends are found to be different and more intense than monthly trends, which emphasizes the influence of atmospheric circulation on IWV trends. In order to assess strong trends over regions lacking GPS stations, a second reanalysis, MERRA-2, is introduced. The period of analysis is extended to 1980–2016 (the longest period the reanalyses have in common) and differences with the shorter period are found. This exemplifies how much IWV trends are dependent on the time period at study and must be interpreted carefully. Temperature trends are also computed for both reanalyses. The Clausius-Clapeyron scaling ratio is found to not be a good humidity proxy at seasonal and regional scales. Regions over northern Africa and Australia, where ERA-Interim and MERRA-2 disagree, are investigated further. Dynamics at these regions is assessed by analyzing the wind fields at 925 hPa and is shown to be tightly linked with the trends and variability in IWV.

Description: For several years, global warming has been unequivocal, leading to climate change at global, regional and local scales. A good understanding of climate characteristics and local variability is important for adaptation and response. Indeed, the contribution of local processes and their understanding in the context of warming are still very little studied and poorly represented in climate models. Improving the knowledge of surface–atmosphere feedback effects at local scales is therefore important for future projections. Using observed data in the Paris region from 1979 to 2017, this study characterizes the changes observed over the last 40 years for six climatic parameters (e.g. mean, maximum and minimum air temperature at 2 m, 2 m relative and specific humidities and precipitation) at the annual and seasonal scales and in summer, regardless of large-scale circulation, with an attribution of which part of the change is linked to large-scale circulation or thermodynamic. The results show that some trends differ from the ones observed at the regional or global scale. Indeed, in the Paris region, the maximum temperature increases faster than does the minimum temperature. The most significant trends are observed in spring and in summer, with a strong increase in temperature and a very strong decrease in relative humidity, while specific humidity and precipitation show no significant trends. The summer trends can be explained more precisely using large-scale circulation, especially regarding the evolution of the precipitation and specific humidity. The analysis indicates the important role of surface–atmosphere feedback in local variability and that this feedback is amplified or inhibited in a context of global warming, especially in an urban environment.

Description: In the context of an atmospheric network of multi-instrumented sites equipped with sky camera for cloud monitoring, we present an algorithm named ELIFAN which aims at estimating the cloud cover amount from full sky visible daytime images with a common principle and procedure. ELIFAN was initially developped for a self-made full sky image system presented in this article, and adapted to a set of other systems in the network. It is based on red over blue ratio thresholding for the distinction of cloudy and clear sky pixels of the image, and on the use of a blue sky library. Both an absolute (without use of reference image) and a differential (based on a blue sky reference image) red/blue ratio thresholding are used. An evaluation of the algorithm based on a one-year long series of images shows that the proposed algorithm is very convincing for most of the images, with more than 95 % of relevance in the process, outside the sunrise and sunset transitions. During those latter periods though, ELIFAN has large difficulties to appropriately process the image, due to a drastic difference of color composition and a potential confusion between clear and cloudy sky at that time. The two thresholding methodologies, the absolute and the differential red/blue ratio thresholding processes, agree very well with departure usually below 8 %, except in sunrise/sunset periods and in some specific conditions. The use of the clear sky library gives generally better results than the absolute process. Especially, it better detects the thin cirrus clouds. But the absolute thresholding process turns out to be sometimes better, for example in fully cloudy skies. The combination of pyranometer, ceilometer and sky camera illustrates the performance of ELIFAN, and reveals the comple-mentarity of the three instruments. We especially show that a similar cloud cover amount is deduced from both the sky imager and the ceilometer when the clouds are low (below 3 km). But they can lead to significantly different cloud cover estimates when the clouds are high. In this case, we find that the sky imager catches more appropriately the cloud cover estimate, due to its 2D integrated point of view and to the loss of sensitivity of the ceilometer above 7 km.

Description: The Coordinated Regional Climate Downscaling Experiment (CORDEX) is a scientific effort of the World Climate Research Program (WRCP) for the coordination of regional climate initiatives. In order to accept an experiment, CORDEX provides experiment guidelines, specifications of regional domains and data access/archiving. CORDEX experiments are important to study climate at the regional scale, and at the same time, they also have a very prominent goal in providing regional climate data of high quality. Data requirements are intended to cover all the possible needs of stake holders, and scientists working on climate change mitigation and adaptation policies in various scientific communities. The required data and diagnostics are grouped into different levels of frequency, priority, and some of them even have to be provided as statistics (minimum, maximum, mean) over different time periods. Most commonly, scientists need to post-process the raw output of regional climate models, since the latter was not originally designed to meet the specific CORDEX data requirements. This post-processing procedure includes the computation of diagnostics, statistics, and final homogenization of the data, which is often computationally costly and time consuming. Therefore, the development of specialized software and/or code is required. The current paper presents the development of a specialized module (version 1.3) for the Weather Research and Forecasting (WRF) model, capable of outputting the required CORDEX variables. Additional diagnostic variables not required by CORDEX, but of potential interest to the regional climate modeling community, are also included in the module. Generic definitions of variables are adopted in order to overcome model and/or physics parameterization dependence of certain diagnostics and variables, thus facilitating a robust comparison among simulations. The module is computationally optimized, and the output is divided in different priority levels following CORDEX specifications (Core, Tier1, and additional) by selecting pre-compilation flags. This implementation of the module does not add a significant extra cost when running the model, for example the addition of the Core variables slows the model time-step by less than a 5%. The use of the module reduces the requirements of disk storage by about a 50%.

Description: A scientific approach is presented to aggregate and harmonize a set of 60 geophysical variables at hourly timescale over a decade, and to allow multiannual and multi-variable studies combining atmospheric dynamics and thermodynamics, radiation, clouds and aerosols from ground-based observations. Many datasets from ground-based observations are currently in use worldwide. They are very valuable because they contain complete and precise information due to their spatio-temporal co-localization over more than a decade. These datasets, in particular the synergy between different type of observations, are under-used because of their complexity and diversity due to calibration, quality control, treatment, format, temporal averaging, metadata, etc. Two main results are presented in this article: (1) a set of methods available for the community to robustly and reliably process ground-based data at an hourly timescale over a decade is described and (2) a single netCDF file is provided based on the SIRTA supersite observations. This file contains approximately 60 geophysical variables (atmospheric and in ground) hourly averaged over a decade for the longest variables. The netCDF file is available and easy to use for the community. In this article, observations are “re-analyzed”. The prefix “re” refers to six main steps: calibration, quality control, treatment, hourly averaging, homogenization of the formats and associated metadata, as well as expertise on more than a decade of observations. In contrast, previous studies (i) took only some of these six steps into account for each variable, (ii) did not aggregate all variables together in a single file and (iii) did not offer an hourly resolution for about 60 variables over a decade (for the longest variables). The approach described in this article can be applied to different supersites and to additional variables. The main implication of this work is that complex atmospheric observations are made readily available for scientists who are non-experts in measurements. The dataset from SIRTA observations can be downloaded at http://sirta.ipsl.fr/reobs.html (last access: April 2017) (Downloads tab, no password required) under https://doi.org/10.14768/4F63BAD4-E6AF-4101-AD5A-61D4A34620DE.