In the framework of the National Project of Interest Nextdata, we developed procedures for the automatic flagging and formatting of trace gas, atmospheric aerosol and meteorological data to be submitted to Global Atmosphere Watch programme by the World Meteorological Organization (WMO/GAW). In this work, we describe a first prototype of a centralized system to support Italian atmospheric observatories towards a more efficient and objective data production and subsequent submission to WMO/GAW World Data Centers (WDCs). In particular, the atmospheric variables covered by this work were focused on near-surface trace gases, aerosol properties and (ancillary) meteorological parameters which are under the umbrella of the World Data Center for Greenhouse Gases (WDCGG, see https://ds.data.jma.go.jp/gmd/wdcgg/), World Data Center for Reactive Gases and World Data Center for Aerosol (WDCRG and WDCA, see http://ebas.nilu.no). For different Essential Climate Variables (ECVs), we developed specific routines for data filtering, flagging, format harmonization and creation of data products (i.e. plot of raw and valid-corrected-averaged ECV data and internal instrument parameters) useful for detecting instrumental problems or atmospheric events. A special suite of products based on the temporal aggregation of valid ECV data (like the “calendar” or “timevariation” products) were implemented for quick data dissemination towards stakeholders or citizens. Generated Level-0, Level-1 and Level-2 files are formatted according to NASA-Ames standard. The list of flags adopted is defined in the framework of ACTRIS-2 project (see https://ebas-submit.nilu.no/Submit-Data/Data-Reporting/Templates/Category/). Three different data levels are produces according with WMO/GAW WCDRG and WCDA data reporting guidelines (see also https://ebas-submit.nilu.no/Submit-Data/Data-Reporting): • Level-0: annotated raw data; format instrument specific; contains all parameters provided by the instrument; contains all parameters/info needed for processing to final value; "native" time resolution; • Level-1: data processed to final parameter (calibration and correction implemented to data series), invalid data and calibration episodes removed, "native" time resolution, normalization to standard temperature and pressure (i.e., 273.15 K, 1013.25 hPa) if necessary; • Level-2: data aggregated to hourly averages, atmospheric variability quantified by standard deviation or percentiles. The automatic processing is executed by a set of three“R” scripts specifically designed for each instrument/ECV : • “D20” is the script devoted to the production of Level-0 data files • “D21” is the script devoted to the production of Level-1 and Level-2 data files • “D22” is the script devoted to the generation of data products All the developed scripts are virtually stand-alone and any hypotetical user, after installing an "R" environment, can use them on his/her own PC (both Linux or Windows) or server, for automatic and on-demand application. Of course, some activity of customization is needed by the users to properly set current directory paths, file names, etc etc. A dedicated script containing three R functions has also been implemented for managing numflag creation and aggregation. D20 and D21 scripts have been revised for inconsistencies within the header. Users are recommended to use the version "1907".

The dataset contains measurements of the frontal variations of sample Italian glaciers monitored by Italian Glaciological Committee (CGI). Monitored glaciers are located in the Alpine chain (ca 300 glacial bodies) and in the Central Apennine (1). Source of data is based primarily on glaciological surveys coordinate by CGI and published in peer-reviewed journals or in WGMS publications (e.g., CGI, 1914–1977 and 1978–2011; Baroni et al., 2012, 2013,2014, 2015, 2016; WGMS 2014, 2015, 2016, 2017, 2018 and earlier issues). Dataset are organized in tabular form within a spreadsheet to allow a verification of the data and a subsequent construction of the relative time-distance curves (T-D curves). For each monitored glacier are furnished glacier name and inventory ID (according to CGI, WGI and WGMS) and geographic location. Metadata of common attributes of glacial resource datasets (GL_NAME, CGI_CODE, WGI_CODE, WGMS_ID, PART, SECTOR, SECT_SUBSEC, SUPERGROUP, GROUP, X_COORD, Y_COORD, MEAN_OR, YEAR) are described in "Italian glaciers multitemporal inventory V2".

At the Ivancich landslide an inclinometer monitoring network has been installed on November 1998. The inclinometer network measured from November 1998 to December 2006, and consists of several inclinometers refer to an extended monitoring network of the landslide. For the Ivancich landslide were considered 4 inclinometers (103, 113B, 117 and 202), the data of which were published in Calò, F.; Ardizzone, F.; Castaldo, R.; Lollino, P.; Tizzani, P.; Guzzetti, F.; Lanari, R.; Angeli, M.G.; Pontoni, F.; Manunta. M.. Enhanced landslide investigations through advanced DInSAR techniques: The Ivancich case study, Assisi, Italy. Remote Sensing of Environment 142, 69-82. The monitoring network allowed sub-surface displacement measurements, and led to the identification of the depth and thickness of slide shear zones. The inclinometer system consists of an inclinometer probe used to survey ground movement causes by the casing movement, calculated by comparing data from the initial data recorded. These instruments measure relative horizontal displacements affecting the casing. The bottom end of the casing is used as a stable reference and must be embedded beyond the displacement zone. Relative displacement over time is recorded by repeating measurements at the same depths. In particular, was recorded the tilt of two perpendicular planes, named “A” and “B”. In a standard inclinometer survey, the probe is draw from the bottom to the top of the casing. The inclinometer is a sensitive measuring instrument, and accurate inclinometer measurements depend on the instrument quality and the care taken during the execution of the measures.

The Ivancich SAR ground deformation time series include deformation data obtained from Cosmo SkyMED satellite acquisition, and published in: Calò et al. (2014) Enhanced landslide investigations through advanced DInSAR techniques: The Ivancich case study, Assisi, Italy. Remote Sensing of Environment, 142: 69-82. This dataset is a courtesy of Ing. Maceo Giovanni Angeli (IRPI-CNR) and Dr. Geol. Fabrizio Pontoni (private consultant). In particular provide 522966 SBAS targets displacement (relative to the Assisi municipality, Monte Subasio and Valle Umbra territory), in descending orbit and in full-resolution scale (3mx3m), for the observed period from December 2009 to February 2012. The archive provide for each SBAS targets: - X (East) and Y (North) UTM WGS84 coordinates (m); - Temporal interferometric coherence [coer.]; - Deformation velocity (cm/year) [vel.]; - Azimuth and Range coordinates [azimuth/range]; - Latitude and Longitude coordinates (deg.) [Lat./Lon]; - Topography (m) [topo]; - Deformation Data (cm), related to the date of the exploited SAR images. The date of the exploited images are expressed as: day/month/year. The time series present a weekly temporal sampling, and provide long-time series of deformation, allowing to following the evolution of surface displacement over time.

In the framework of the National Project of Interest Nextdata, we developed procedures for the automatic flagging and formatting of trace gas, atmospheric aerosol and meteorological data to be submitted to Global Atmosphere Watch programme by the World Meteorological Organization (WMO/GAW). In this work, we describe a first prototype of a centralized system to support Italian atmospheric observatories towards a more efficient and objective data production and subsequent submission to WMO/GAW World Data Centers (WDCs). In particular, the atmospheric variables covered by this work were focused on near-surface trace gases, aerosol properties and (ancillary) meteorological parameters which are under the umbrella of the World Data Center for Greenhouse Gases (WDCGG, see https://ds.data.jma.go.jp/gmd/wdcgg/), World Data Center for Reactive Gases and World Data Center for Aerosol (WDCRG and WDCA, see http://ebas.nilu.no). For different Essential Climate Variables (ECVs), we developed specific routines for data filtering, flagging, format harmonization and creation of data products (i.e. plot of raw and valid-corrected-averaged ECV data and internal instrument parameters) useful for detecting instrumental problems or atmospheric events. A special suite of products based on the temporal aggregation of valid ECV data (like the “calendar” or “timevariation” products) were implemented for quick data dissemination towards stakeholders or citizens. Generated Level-0, Level-1 and Level-2 files are formatted according to NASA-Ames standard. The list of flags adopted is defined in the framework of ACTRIS-2 project (see https://ebas-submit.nilu.no/Submit-Data/Data-Reporting/Templates/Category/). Three different data levels are produces according with WMO/GAW WCDRG and WCDA data reporting guidelines (see also https://ebas-submit.nilu.no/Submit-Data/Data-Reporting): • Level-0: annotated raw data; format instrument specific; contains all parameters provided by the instrument; contains all parameters/info needed for processing to final value; "native" time resolution; • Level-1: data processed to final parameter (calibration and correction implemented to data series), invalid data and calibration episodes removed, "native" time resolution, normalization to standard temperature and pressure (i.e., 273.15 K, 1013.25 hPa) if necessary; • Level-2: data aggregated to hourly averages, atmospheric variability quantified by standard deviation or percentiles. The automatic processing is executed by a set of three“R” scripts specifically designed for each instrument/ECV : • “D20” is the script devoted to the production of Level-0 data files • “D21” is the script devoted to the production of Level-1 and Level-2 data files • “D22” is the script devoted to the generation of data products All the developed scripts are virtually stand-alone and any hypotetical user, after installing an "R" environment, can use them on his/her own PC (both Linux or Windows) or server, for automatic and on-demand application. Of course, some activity of customization is needed by the users to properly set current directory paths, file names, etc etc. A dedicated script containing three R functions has also been implemented for managing numflag creation and aggregation. D20 and D21 scripts have been revised for inconsistencies within the header. Users are recommended to use the version "1907".

In the framework of the National Project of Interest Nextdata, we developed procedures for the automatic flagging and formatting of trace gas, atmospheric aerosol and meteorological data to be submitted to Global Atmosphere Watch programme by the World Meteorological Organization (WMO/GAW). In this work, we describe a first prototype of a centralized system to support Italian atmospheric observatories towards a more efficient and objective data production and subsequent submission to WMO/GAW World Data Centers (WDCs). In particular, the atmospheric variables covered by this work were focused on near-surface trace gases, aerosol properties and (ancillary) meteorological parameters which are under the umbrella of the World Data Center for Greenhouse Gases (WDCGG, see https://ds.data.jma.go.jp/gmd/wdcgg/), World Data Center for Reactive Gases and World Data Center for Aerosol (WDCRG and WDCA, see http://ebas.nilu.no). For different Essential Climate Variables (ECVs), we developed specific routines for data filtering, flagging, format harmonization and creation of data products (i.e. plot of raw and valid-corrected-averaged ECV data and internal instrument parameters) useful for detecting instrumental problems or atmospheric events. A special suite of products based on the temporal aggregation of valid ECV data (like the “calendar” or “timevariation” products) were implemented for quick data dissemination towards stakeholders or citizens. Generated Level-0, Level-1 and Level-2 files are formatted according to NASA-Ames standard. The list of flags adopted is defined in the framework of ACTRIS-2 project (see https://ebas-submit.nilu.no/Submit-Data/Data-Reporting/Templates/Category/). Three different data levels are produces according with WMO/GAW WCDRG and WCDA data reporting guidelines (see also https://ebas-submit.nilu.no/Submit-Data/Data-Reporting): • Level-0: annotated raw data; format instrument specific; contains all parameters provided by the instrument; contains all parameters/info needed for processing to final value; "native" time resolution; • Level-1: data processed to final parameter (calibration and correction implemented to data series), invalid data and calibration episodes removed, "native" time resolution, normalization to standard temperature and pressure (i.e., 273.15 K, 1013.25 hPa) if necessary; • Level-2: data aggregated to hourly averages, atmospheric variability quantified by standard deviation or percentiles. The automatic processing is executed by a set of three“R” scripts specifically designed for each instrument/ECV : • “D20” is the script devoted to the production of Level-0 data files • “D21” is the script devoted to the production of Level-1 and Level-2 data files • “D22” is the script devoted to the generation of data products All the developed scripts are virtually stand-alone and any hypotetical user, after installing an "R" environment, can use them on his/her own PC (both Linux or Windows) or server, for automatic and on-demand application. Of course, some activity of customization is needed by the users to properly set current directory paths, file names, etc etc. A dedicated script containing three R functions has also been implemented for managing numflag creation and aggregation. D20 and D21 scripts have been revised for inconsistencies within the header. Users are recommended to use the version "1907".

The Gardiola in situ ground deformation time series include deformation data from the topographic monitoring network, installed on the Gardiola landslide. In particular, provide the differential displacement (in cm), of planimetric and altimetric displacement, for each prism of the network. The archive provide time series of twenty-three optical target, for an observed period from March 2004 to April 2009. The time series present a very high temporal sampling (hourly), and provide the differential displacement for the planimetric (Δxy) and altimetric (Δz) displacement (in cm). All the spikes interpreted as noise were been delete to the time series.

The Ivancich SAR ground deformation time series include deformation data obtained from ERS-1/2 and Envisat ASAR satellites acquisition, and published in: Calò et al. (2014) Enhanced landslide investigations through advanced DInSAR techniques: The Ivancich case study, Assisi, Italy. Remote Sensing of Environment, 142: 69-82. This dataset is a courtesy of Ing. Maceo Giovanni Angeli (IRPI-CNR) and Dr. Geol. Fabrizio Pontoni (private consultant). In particular provide 124919 SBAS targets displacement (relative to Central Umbria territory), in descending orbit and in full-resolution scale (5mx20m), for the observed period from April 1992 to November 2010. The archive provide for each SBAS targets: - X (East) and Y (North) UTM WGS84 coordinates (m); - Temporal interferometric coherence [coer.]; - Deformation velocity (cm/year) [vel.]; - Azimuth and Range coordinates [azimuth/range]; - Latitude and Longitude coordinates (deg.) [Lat./Lon]; - Topography (m) [topo]; - Deformation Data (cm), related to the date of the exploited SAR images. The date of the exploited images are expressed as: day/month/year. The time series present a monthly temporal sampling, and provide long-time series of deformation, allowing to following the evolution of surface displacement over time.

At the Grange Orgiera landslide a topographic monitoring network has been installed on August 2009. The topographic network has located upstream Grange Orgiera hamlet, in correspondence to the left frontal lobe of the landslide. The network consists of a robotic total station, associated to a solar panel and a backup battery that guarantees its operation, and a GSM modem that allows a download of the data by remote connection; eight prisms, seven of which inside the landslide and one close to the landslide foot, and two reference points outside the landslide. This network allowed the monitoring of the left frontal lobe of the landslide, which threatened the Puy village. The topographic network was installed on July 2009 and recorded during the spring-autumn months, in particular from August 2009 since October 2009. In 2010 have been installed five new prisms within the landslide body, near the left frontal lobe of the landslide, and the monitoring network recorded from July 2010 to September 2010. The monitoring network allowed several automatic displacement measurements of the prisms inside and outside the landslide, using a robotic total station Leica TCA 1800. This high-performance instrument for the ground displacement surveying, allow to measure the angle (Hz and V) and distance measurement. Data collected by this total station permit to improve knowledge on surface ground deformation, and the geomorphological evolution of the landslide. In particular, the TCA 1800 total station used is characterized by: - Angle-measurement accuracy: Standard deviation (ISO 17123-2) of 1” (0.3 mgon); - Distance measurement (IR): Standard deviation (ISO 17123-4) 1mm + 2 ppm; Range 2.500 m, under average atmospheric conditions, i.e. visibility 15 km. - Automatic target recognition (ATR), under good atmospheric conditions: Accuracy at below 200 m of 1 mm; Accuracy at 500 m of 2 mm – 3 mm. For more information: http://www.leica-geosystems.com/downloads123/zz/tps/tps2000/brochures/tps2000_brochure_it.pdf

The SAR ground deformation time series relevant to Sampeyre frame include deformation data obtained from ASAR-Envisat satellite acquisitions (images available in the framework of Category-1A project, part of the ESA Geohazard Supersites initiative), and elaborated by the ESA’s G-POD service with the SBAS technique. In particular, the analysis provided 65535 measure points, for the observed period from April 2005 to October 2010, relative to the entire frame. The archive provide for each SBAS targets: - ID: Gr1; Gr2; Gr n - East and North UTM WGS84 coordinates (m); - Temporal interferometric coherence [CohT]; - Deformation velocity (cm/year) [Vel]; - Azimuth and Range coordinates [Az/Rg]; - Latitude and Longitude coordinates (deg) [Lat/Lon]; - Topography (m) [RT]; - Deformation Data (cm), related to the date of the exploited SAR images. The date of the exploited images are expressed as: [year+((month-1)*30+day)/365]. The SBAS results, relevant to the entire frame (normally around 100x100 km), have an accuracy of 1 mm/yr for mean velocity measurements, and 5 mm for the deformation measurements [Casu et al., 2006]. The deformation time series present a monthly temporal sampling, and provide long time series of deformation, allowing to follow the evolution of surface displacement over time.