Fourth Study Conference on BALTEX Scala Cinema Gudhjem

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A Comparison between the ERA40 and the SMHI Gridded Meteorological
Data Bases with Applications to Baltic Sea Modelling
Anders Omstedt, Youmin Chen and Karin Wesslander
Göteborg University, Department of Earth Sciences: Oceanography. Box 460, SE-405 30 Göteborg Sweden. E-mail:
Anders.Omstedt@gvc.gu.se
1. Introduction
The last decade have considerable improved our possibility
to get forcing data for ocean and hydrological modelling and
process studies. For meteorological forcing of ocean models,
synoptic station values without horizontal interpolations are
available from the BALTEX data centers but also gridded
data sets (SMHI 1 0 x1 0 ). The gridded data set from SMHI has
played an important role within the BALTEX project both
within ocean and hydrological modelling. Meteorological
gridded data sets are also available from other sources
(ERA40 from European Centre for Medium-Range Weather
Forecasts, NCEP/NCAR from US-National Ocean and
Atmosphere Administration). The aim in this study is to
compare the ERA40 and the SMHI 1 0 x1 0 data for the Baltic
Sea. In the work we investigate meteorological parameters
such as wind speed, air temperature, humidity, cloudiness
and precipitation. We also use Baltic Sea modelling and
independent marine observations to evaluate the
meteorological forcing fields.
2. Gridded meteorological data
The ERA40 reanalyse project has been a major undertaking
by the ECMWF (http://www.ecmwf.int/research/era/) and
covers the period from 1957 to 2002. Through a
combination of a large number observations of different
origins and numerical modelling many different
meteorological parameters have been analysed and made
available to the research community.
The gridded data set from SMHI (SMHI 1 0 x1 0 ) covers the
period 1970 to 2003 with mainly meteorological surface
parameters. This data set is available from the BALTEX
Hydrological Data Centre (BHDC,
http://www.gkss.de/baltex/) and shortly described in
Omstedt et al. (1997).
The time period from 1 January 1971 to 31 December 2000
was used in the comparison. The two data sets have both a
resolution of 1 0 x1 0 a resolution that does not resolve the
complex geometry of the Baltic Sea. The land influence due
to coarse resolution has been analysed in the SMHI 1 0 x1 0
data set by Rutgersson et al., (2001) and Omstedt and Axell
(2003) introduced some correction methods.
3. Air temperature
The comparison of air temperatures from the Eastern
Gotland Basin are illustrated in Figure 1 and 2 as an
example of the study. In general, the SMHI 1 0 x1 0 data is
slightly colder and with larger standard deviation.
20
16
12
8
4
0
GO(TA-M)
ERA40
SMHI
-4
0 100 200
Time (Julian day)
300 400
Figure 1. A comparison between ERA40 (black line)
and SMHI 1 0 x1 0 (blue line) air temperatures above Eastern
Gotland Basin. Daily means averaged over a 30-years
period.
5
4
3
2
1
GO(TA-STD)
ERA40
SMHI
0 100 200 300 400
Time (Julian day)
Figure 2. A comparison between ERA40 (black line)
and SMHI 1 0 x1 0 (blue line) air temperatures above Eastern
Gotland Basin) Daily standard deviation averaged over a
30-years period.
4. Total cloudiness
The total cloudiness is compared in Figure 3 and 4. The
mean and standard deviation show large similarities.
Cloud climatology based on satellite data has found a
good agreement with the ERA-40 data (Karlsson, 2003).