Articles | Volume 9, issue 3
Atmos. Meas. Tech., 9, 991–999, 2016
Atmos. Meas. Tech., 9, 991–999, 2016

Research article 09 Mar 2016

Research article | 09 Mar 2016

Real-time data acquisition of commercial microwave link networks for hydrometeorological applications

Christian Chwala1, Felix Keis1, and Harald Kunstmann1,2 Christian Chwala et al.
  • 1Karlsruhe Institute of Technology (KIT), Institute of Meteorology and Climate Research (IMK-IFU), Garmisch-Partenkirchen, Germany
  • 2University of Augsburg, Institute for Geography, Augsburg, Germany

Abstract. The usage of data from commercial microwave link (CML) networks for scientific purposes is becoming increasingly popular, in particular for rain rate estimation. However, data acquisition and availability is still a crucial problem and limits research possibilities. To overcome this issue, we have developed an open-source data acquisition system based on the Simple Network Management Protocol (SNMP). It is able to record transmitted and received signal levels of a large number of CMLs simultaneously with a temporal resolution of up to 1 s. We operate this system at Ericsson Germany, acquiring data from 450 CMLs with minutely real-time transfer to our database. Our data acquisition system is not limited to a particular CML hardware model or manufacturer, though. We demonstrate this by running the same system for CMLs of a different manufacturer, operated by an alpine ski resort in Germany. There, the data acquisition is running simultaneously for four CMLs with a temporal resolution of 1 s. We present an overview of our system, describe the details of the necessary SNMP requests and show results from its operational application.

Short summary
Commercial microwave link (CML) networks, like they are used as backbone for the cell phone network, can be used to derive rainfall information. However, data availability is limited due to the lack of suitable data acquisition systems. We have developed and currently operate a custom data acquisition system for CML networks that is able to acquire the required data for a large number of CMLs in real time. This system is the basis for a future countrywide rainfall product derived from CML data.