Meteorological network observations by MESSI weather stations during FESSTVaL 2021

<strong>Abstract: </strong>The data set contains meteorological data from a citizen science network that was part of the Field Experiment on Sub-mesoscale Spatio-Temporal Variability in Lindenberg (FESSTVaL) from May to September 2021. The network consists of 56 stations that were mostly set up in gardens of citizen participants of the project around the Meteorological Observatory Lindenberg - Richard-Aßmann-Observatory (MOL-RAO eastern Germany; 52.16°N, 14.12°E). A map of the positions of the stations can be found in this report. One of the goals was to investigate to what extent a data set gathered from a citizen science network can add value in addition to the network of the MOL-RAO and professional networks in general. The main subjects of investigation were sub-mesoscale structures such as cold pools. The 56 stations were equipped with devices called MESSI = "Mein Eigenes SubSkalen Instrument", which is a low-cost, autonomous device planned and built at Freie Universität Berlin for the use case of building meteorological Citizen Science networks. The data set comprises level-1 data, measured every 10 seconds, and level-2 data for which the level-1 data were aggregated to 1-minute time periods.<br>
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<strong>TableOfContents:</strong> Air temperature inside device; Air temperature outside device; Air temperature derived from statistical model; Surface air pressure at station level; Surface downwelling illuminance

<strong>Technical Info: </strong> dimension: level-1: 8640 x 56, level-2: 1440 x 56; temporalExtent_startDate: 2021-06-10 00:00:10; temporalExtent_endDate: 2021-10-01 00:00:00; temporalResolution: level-1: 10, level-2: 60; temporalResolutionUnit: seconds; spatialResolution: none; spatialResolutionUnit: none; horizontalResolutionXdirection: none; horizontalResolutionXdirectionUnit: none; horizontalResolutionYdirection: none; horizontalResolutionYdirectionUnit: none; verticalResolution: none; verticalResolutionUnit: meters; horizontalStart: 0; horizontalStartUnit: meters; horizontalEnd: 0; horizontalEndUnit: meters; instrumentNames: PT1000 Heraeus M222 ADS114SOxB, BMP38x, Si1151/1145; instrumentType: Resistive temperature sensor, pressure sensor, illuminance sensor; instrumentLocation: Grenzschichtmessfeld Falkenberg, Lindenberg; instrumentProvider: Texas Instruments, Bosch Sensortec, Silicon Labs

<strong>Methods: </strong>The MESSI measures air temperature, air pressure, surface downwelling illuminance and humidity (humidity data is not being published due to issues with the respective sensor during the campaign). The original time resolution is 10 seconds. As a part of the data processing a statistical model was used to establish a relation to a reference station and use this to adjust the measurements such that bias and conditional bias with respect to a DWD reference is reduced. For this processing step we used reference data of a 1-minute resolution from a ventilated station at MOL-RAO provided by Deutscher Wetterdienst (DWD, no final quality control applied) and similarly aggregated observation data of one particular MESSI position next to the DWD device. Subsequently, this model was applied to all MESSI data to get more accurate values for the air temperature than measured directly. Because the script for quality control and statistical modelling has been optimized for the 1-minute time resolution data it can be assumed that these are more accurate - especially the 3rd temperature quantity: "Air temperature derived from statistical model".

As another step of preprocessing several quality controls were applied. All measurements that did not pass these quality controls have been excluded from the dataset (values set to missing values).

The MESSI device and data processing including the statistical modelling and the applied quality controls is described in more detail in<br>
[http://dx.doi.org/10.17169/refubium-42772].

<em><strong>Quality</strong></em>: Absolute accuracy according to manufacturers of sensors is for the air temperature inside and outside device::+/- 0.15 K and for the surface air pressure at station level: +/- 50 Pa. The actual accuracy is probably lower due to assembly of the devices by the participants and other factors. In the modelling procces a root-mean-square-error of 0.64 K was estimated when comparing the value of the variable "air temperature inside device" of the MESSI with the reference sensor.

The total data availability is 53%. This is because of the filters mentioned above, failures in data transfer (see below) and mainly the fact that measurements started and ended at different times for the different stations. Best data availability is given in July and August (72% and 73%).

At some stations the MESSI had to be exchanged during the campaign due to technical issues. In some cases it can not be guaranteed that<br>
the device was measuring at the respective station position (possible untracked movement of device by citizen participant).<br>
The MESSIs did send their GPS-position to the MESSI database via "<em>LoRaWan</em>" and the "<em>The Things Network</em>" once per day. But in some cases<br>
this data transfer failed, leading to some uncertainty of the station position. These and other information can be found in fesstval_messi_station_list.csv

<strong>Units: </strong>K; K; K; Pa; lux

<strong>geoLocations:</strong>

<strong><em>BoundingBox:</em></strong> westBoundLongitude: 13° 43' 28.56'' East; eastBoundLongitude: 14° 25' 59.519'' East; southBoundLatitude: 52° 5' 31.2'' North; northBoundLatitude: 52° 18' 4.68'' North; geoLocationPlace: Germany, UTM zone 33U
<strong><em>Locations: </em></strong>56 station locations within BoundingBox (see fesstval_messi_station_list.csv); lowerBoundAltitude: 38 meter above MSL; upperBoundAltitude: 98 meter above MSL

<strong>Size:</strong> Daily files for each quantity provided as one packed tar-archive for either level-1 or level-2 data; total volume level-1 data: 1.23 Gb; total volume level-2 data: 0.37 Gb; total volume of the packed files is about 1/5 of that.

<strong>Format: </strong>netCDF

<strong>DataSources:</strong> Multiple site near-surface observations (see fesstval_messi_station_list.csv)

<strong>Contact: </strong> henning.rust (at) fu-berlin.de

<strong>Web page:</strong> https://www.cen.uni-hamburg.de/en/icdc/data/atmosphere/samd-st-datasets/samd-st-fesstval/fval-fub-messi.html

see also: https://www.cen.uni-hamburg.de/en/icdc/research/samd/observational-data/short-term-observations/fesstval.html