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Moisture availability and the relationship between daily precipitation
intensity and surface temperature
Peter Berg, Jan Haerter, Peter Thejll, Claudio Piani, Stefan Hagemann, Jens Hesselbjerg Christensen
Institute for Meteorology and Climate Research, University/Forschungszentrum Karlsruhe, Germany, Peter.Berg@imk.fzk.de
1. Introduction
What is the connection between precipitation intensity and
the surface temperature? A claim commonly made when
studying global warming is that precipitation intensity
increases as the troposphere warms (e.g. Semenov and
Bengtsson, 2002; Trenberth et al., 2003). This claim has its
origin in the relationship between the air’s moisture-holding
capacity and the temperature, as stated by the Clausius-
Clapeyron (C-C) equation. For the precipitation intensity to
follow this increase in capacity at the same rate, the supply
of moisture must then increase sufficiently to enable
saturation leading to condensation and cloud formation. To
what extent is the atmospheric moisture content actually
limited by the C-C relationship? Are there other factors that
inhibit a potential increase in the precipitation intensity as
the globe warms?
In this study, further described in Berg et al. (submitted to
JGR), we explore the relationship between surface
temperature and precipitation intensity for a gridded
observational data set of daily values covering all of Europe,
similar to what has earlier been carried out for a single
precipitation station in the Netherlands (Lenderink and van
Meijgaard, 2008). We explicitly resolve the intra-seasonal
behaviour and investigate in which seasons the precipitation
intensity dependence on temperature can be understood
using the C-C relation, and why this concept breaks down in
other seasons. The results are compared to, and further
explored using three RCMs.
Kelvin bins, and calculating the 70 th , 90 th , 99 th and 99.9 th
percentiles for each bin. The two higher percentiles are
calculated by a Generalized Pareto Distribution (GPD) fit
to the upper 20% of the data. All the calculated percentiles
show similar, i.e. parallel, results so in the rest of this text
we restrict to only discuss the 99 th percentile.
4. Results
The observations show a general monotonous positive
relationship with increasing temperature in winter, while
in summer there is a negative relationship (Fig. 1).
However, the negative trend in summer shows signs of
being interrupted and level out for the temperature range
of about ten to twenty degrees.
2. Data and models
We use the gridded 0.44 degree resolution observational
data set of daily precipitation and temperature over
European land areas, constructed for the ENSEMBLES
project (Haylock et al., 2008). We focus on the period
1961—1990, where there is good spatial and temporal
coverage of precipitation and temperature stations in the
domain. The below analysis was also performed on station
data directly, with similar results, so the gridded data are
found to be reliable.
To complement the observations we use ERA40-reanalysis
driven simulations by the HIRHAM4, REMO and HadRM3
RCMs from the ENSEMBLES project. The models use a
0.44 degree horizontal resolution, and we use only model
data over land, to be consistent with the observations.
3. Methodology
We consider daily precipitation intensity, larger than 0.1
mm/day, and the two-meter daily mean temperature.
However, the variable for studying an increase in the
moisture holding capacity, and precipitation intensity
changes, would be the cloud level temperature. A study of
the relationship between the two-meter temperature and the
cloud level temperature, using the RCMs, showed the twometer
temperature to be proportional to the cloud level
temperature, with no systematic deviations. Thus we can use
this directly to compare with the precipitation intensity.
We divide the data into months, and study the intra-seasonal
relationship between temperature and precipitation intensity.
This performed by dividing the temperature range into two
Figure 1: The 99 th percentile of precipitation intensity
larger than 0.1 mm/day as a function of daily average
temperature for observations (black), HIRHAM4 (pink),
REMO (light brown), and HadRM3 (light blue). The
dashed line in the January panel shows a C-C like increase
with temperature. Note the logarithmic vertical axis.
The RCM simulations show a very similar behaviour as
the observations (Fig. 1). The models separate between
large-scale and convective precipitation events, depending
on the circumstances leading to the precipitation event.
We utilize this separation between the precipitation types
to investigate their individual behaviour.