ReOBS: a new approach to synthesize long-term multi-variable dataset and application to the SIRTA supersite

Abstract

Abstract.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

The diurnal cycle of cloud profiles over land and ocean between 51° S and 51° N, seen by the CATS spaceborne lidar from the International Space Station

“…Ground-based observation sites provide long-term records of atmospheric properties over periods that often cannot be reached by satellite instruments (Chiriaco et al, 2018). Nowadays such sites are often well equipped with active remote sensing instruments.…”

“…Descriptions of the cloud diurnal cycle based on active ground-based measurements are, however, scarce. In this study, we compare CATS cloud cycles with those derived from active measurements at three ground-based sites, two continental, and one oceanic: Elouragini and Flamant, 1996), which were curated, packaged, and made available in the framework of the SIRTA-ReOBS project (Chiriaco et al, 2014(Chiriaco et al, , 2018. The LNA requires human supervision and does not operate under precipitation, leading to irregular sampling and almost no nighttime measurements.…”

Authors' comment to referee 2

“…Data availability. The SIRTA ReOBS netCDF file is available at https://doi.org/10.14768/4F63BAD4-E6AF-4101-AD5A-61D4A34620DE (Chiriaco et al, 2018b). GPS IWV data have been processed by Bock (2016): https://doi.org/10.14768/06337394-73a9-407c-9997-0e380dac559.…”

“…1), from 2003 (Haeffelin et al, 2005). This observatory has collected many observations, which are now synthesized into the so-called "SIRTA-ReOBS dataset" described in Chiriaco et al (2018a) and used in Chiriaco et al (2014) and Bastin et al (2018). After many steps of data quality control and harmonization, the "SIRTA-ReOBS" file contains hourly averages of more than 50 variables at this site.…”

ELIFAN, an algorithm for the estimation of cloud cover from sky imagers

“…Such systems were also historically developed in the late 1970s or early 1980s, like that mentioned in Benech et al (1980). This type of design is used in several recent developments (e.g., Pfister et al, 2003;Long et al, 2006;Mantelli Neto et al, 2010;Chow et al, 2011).…”