Titelangaben
Parlow, Eberhard ; Foken, Thomas:
Ground-based Mobile Measurement Systems.
In: Foken, Thomas
(Hrsg.):
Springer Handbook of Atmospheric Measurements. -
Cham
: Springer
,
2021
. - S. 1367-1383
. - (Springer Handbooks
)
ISBN 978-3-030-52170-7
DOI: https://doi.org/10.1007/978-3-030-52171-4_50
Abstract
While stationary measurements can be performed relatively frequently, they do not permit detailed spatial analyses of meteorological variables, particularly air temperature. This problem can be resolved by making the sensor mobile and then taking measurements at a variety of locations within the area of interest. Mobile measurements have therefore been used in climatological research since the early twentieth century. Due to improvements in and the miniaturization of the relevant measurement technologies, mobile measurements have undergone a renaissance since the 1970s. Urban climatology has become an important field of great scientific interest. The realization that the measurements of just one urban weather station—generally located (in line with the recommendations of the World Meteorological Organization) on short-cut lawn—is not sufficient to represent all of the climates present in an urban area has led to the acceptance of and even the need for mobile measurements taken on cars, bikes, or buses. New methodologies have been implemented, and advances in digital measurement and storage on data loggers have made mobile measurements an important tool for spatially distributed studies of air temperature, air humidity, and air pollution.
Three important aspects must be considered when mobile measurements are analyzed:
(1) A complete mobile measurement covers a time interval for the measurement, within which the meteorological variable changes its value. This change has to be corrected for to obtain quasi-synchronous data.
(2) Since the instrumentation changes location, accurate geolocation of the measured data must be guaranteed. This can be achieved by operating a global navigation satellite system (GNSS) in parallel with the measurements.
(3) Due to the spatial dimension of the measured data, it is convenient to perform some of the data analysis and visualization using modern geographic information system (GIS) technologies.