Abstract. The coupling between soil, vegetation and atmosphere is thought to be crucial
in the development and intensification of weather extremes, especially
meteorological droughts, heat waves and severe storms. Therefore, understanding
the evolution of the atmospheric boundary layer (ABL) and the role of
land–atmosphere feedbacks is necessary for earlier warnings,
better climate projection and timely societal adaptation. However, this
understanding is hampered by the difficulties of attributing cause–effect
relationships from complex coupled models and the irregular space–time
distribution of in situ observations of the land–atmosphere system.
As such, there is a need for simple deterministic appraisals that
systematically discriminate land–atmosphere interactions from observed weather
phenomena over large domains and climatological time spans. Here, we present a
new interactive data platform to study the behavior of the ABL and
land–atmosphere interactions based on worldwide weather balloon soundings and an ABL model. This
software tool – referred to as CLASS4GL (http://class4gl.eu, last access: 27 May 2018) – is developed with the objectives of (a) mining appropriate global observational data from ∼15 million weather balloon
soundings since 1981 and combining them with satellite and reanalysis data and (b) constraining and initializing a numerical model of the daytime
evolution of the ABL that serves as a tool to interpret these observations
mechanistically and deterministically.
As a result, it fully automizes extensive global
model experiments to assess the effects of land and
atmospheric conditions on the ABL evolution as observed in different
climate regions around the world.
The suitability of the set of
observations, model formulations and global parameters employed by
CLASS4GL is extensively validated. In most cases, the framework is able to
realistically reproduce the observed daytime response of the mixed-layer height,
potential temperature and specific humidity from the balloon soundings. In this
extensive global validation exercise, a bias of 10.1 m h−1, −0.036 K h−1 and 0.06 g kg−1 h−1 is found for the
morning-to-afternoon evolution of the mixed-layer height, potential temperature
and specific humidity. The virtual tool is in continuous development and
aims to foster a better process understanding of the drivers of the
ABL evolution and their global distribution, particularly during
the onset and amplification of weather extremes. Finally, it can also be
used to scrutinize the representation of land–atmosphere feedbacks and
ABL dynamics in Earth system models, numerical weather prediction
models, atmospheric reanalysis and satellite retrievals, with the
ultimate goal of improving local climate projections, providing earlier
warning of extreme weather and fostering a more effective development of
climate adaptation strategies. The tool can be easily downloaded via
http://class4gl.eu (last access: 27 May 2018) and is open source.