Valuation of the ERA-40 reanalysis clouds and radiation data with

Evaluation of ERA-40 clouds and radiation data with
CM SAF CLARA-A1 in the North Sea Area
N.H. Schade, BSH, Hamburg, Germany, M. Stengel, J. Trentmann, R. Hollmann*, DWD, Offenbach, Germany
Departmental Research Programme
National Meteorological Service in Germany
(DWD)
German Maritime and Hydrographic Agency
(BSH)
German Federal Institute of Hydrology (BfG)
German Federal Waterways Engineering
and Research Institute (BAW)
Background
֠ The quality of cloud and radiation calculations defines to a great extent the quality of the results of coupled Ocean-Atmosphere models. For their assessment, reference
data of homogeneous high quality are needed over a long time period. Satellites provide the only data source for both parameters over the North Sea Area. Here, we use
the EUMETSAT CM SAF Cloud, Albedo and Radiation dataset CLARA-A1 (www.cmsaf.eu) and evaluate the ERA-40 reanalysis clouds and radiation data.
֠ CLARA-A1 is derived from AVHRR data on board NOAA and MetOp-A satellites. Total cloud cover (TCC) has been validated against globally distributed synoptic
observations on airports and several other satellite products (PATMOS-X, MODIS, ISCCP, A-Train). Solar global radiation (SGR) has been validated against the Baseline
Surface Radiation Network (BSRN) station data world wide. Both data sets show good agreement. Therefore, CLARA-A1 can be considered as reference.
Data
CM SAF CLARA-A1
(Satellite product)
ERA-40
(Re-analysis)
Spatial resolution: 0.25° x 0.25°
Spatial resolution: 1.125° x 1.121°
Coverage: Global
Coverage: Global
CM SAF satellite-based climate data
records (e.g. Karlsson et al., 2013)
ECMWF 40 Year Re-analysis data
archive (e.g. Uppala et al., 2005)
CM SAF CLARA-A1 vs. ERA-40
Fig.3: Boxplots of monthly mean TCC in % (left) and monthly mean SGR in W/m² (right) from
CM SAF CLARA-A1 satellite data (blue) and ERA-40 (back) for the SE box (Fig.2) and the
period 1982-2001. In addition, monthly mean SGR station data from Norderney (red) are
displayed. Boxes mark the 25th and 75th percentiles with the median, whiskers the ± 2.7 σ
values of the distribution. Outliers are shown as red plusses. The 95% significance intervals of
the median values are indicated by the notches.
Fig.4: Time series of
monthly mean TCC in %
(top) and SGR in W/m²
(bottom) for CLARA-A1
(blue) and ERA-40 (black)
in the SE box for the
period 1982-2001. In
addition, monthly mean
SGR station data from
Norderney (red) are
displayed.
Fig.1: Mean CM SAF CLARA-A1 (top row) and ERA-40 (second row) total cloud cover (TCC) in %
(left) and solar global radiation (SGR) in W/m² (right) in the North Sea for the period 1982-2001.
The respective differences are calculated on the ERA-40 grid (bottom row). Shown are the annual,
winter (DJF), spring (MAM), summer (JJA), and autumn (SON) mean values (from left to right
respectively).
Fig.2: Mean number of cloud cover observations per day from CLARA-A1 satellite data over the
time period 1982-2001 (left) and their grid points, separated into four different boxes (NW=magenta,
NE=green, SW=blue, SE=red).
Summary & Conclusion
Fig.5: Left four graphs: Time series of annual mean TCC from CM SAF CLARA-A1 satellite
data (blue) and ERA-40 (back) for the four boxes in Fig.2 and the period 1982-2001. Right four
graphs: Same, but for annual mean SGR . In addition, SGR station data from Norderney (red)
are displayed in the south eastern box
֠ Comparisons of daily mean CM SAF CLARA-A1 total cloud covers (TCC) and solar global radiation (SRG) data with ERA-40 show an underestimation
of the reanalysis TCC of about 10 % in the monthly mean values, less in the winter, more in the summer months (Fig.1). Also, the reanalysis SGR is
underestimated, with the exception of the summer months. This contradicts the lower TCCs and may be caused by the parameterisation of the
atmospheric processes and/or the coarse resolution of the reanalysis. Nevertheless, the SGR distributions are in far better agreement overall (Fig.3/4).
֠ Time series of SGR data reveal a breaking point in 1988/89 (Fig.5, right) which can be related to a climate shift signal observed in various other
studies (e.g. Francis and Vavrus, 2012), originating in winter 1987/88 through enhanced loss in sea ice and snow cover in the Northern Hemisphere
(Watanabe and Nitta, 1999) and increased sea surface temperatures in the North Sea (Loewe et al., 2009). It might also be partly related to a negative
trend in the CLARA-A1 TCC data due to changed temporal sampling (i.e. morning-evening satellites, see Karlsson et al., 2013). The climate shift signal is
assumed to be sustained through inherent strong local and hemisphere-wide atmospheric Teleconnection patterns. Additional analyses of modified Lamb
Weather Types reveal an increase of 24 % in the occurrence of warm westerly types in the winter months 1988-95 compared to 1980-87 (not shown). No
changes can be found in the other seasons, which supports the assumptions stated above.
֠ The climate shift signal is weaker in the reanalysis’ SGR, and non-existent in TCC data, whereas CLARA-A1 TCCs in fact show lower values since
1989 (Fig.5, left) with the exception of the years 1993 & 1998. Further investigations have to be undertaken to validate the observed issues.
Literature: Francis, JA., and SJ. Vavrus (2012): Evidence linking Arctic Amplification to extreme weather in mid-latitudes. Geophys. Res. Let., 39, 6pp.
Karlsson, K.G., et al. (2013): CLARA-A1: A cloud, albedo, and radiation dataset from 28 yr of global AVHRR data. Atm. Chem. Phys., 13, 5351-5367.
Loewe, P. et al. (2009): System Nordsee – Zustand 2005 im Kontext langzeitlicher Entwicklungen. Berichte des BSH, Nr. 38, BSH, Hamburg und Rostock, 220pp.
Uppala, S.M. and co-authors (2005): The ERA-40 re-analysis. Quart.J.R. Meteorol. Soc., 131, 2961-3012.
Watanabe, M., and T. Nitta (1999): Decadal changes in the atmospheric circulation and associated surface climate variations in the Northern Hemisphere Winter. J.Climate, 12,494-510.
WCRP The Climate Symposium
13-17 October 2014, Darmstadt, Germany
*Contact:
Rainer Hollmann
Deutscher Wetterdienst
(DWD)
Frankfurter Straße 135
D-63065 Offenbach,
Germany
Email:
[email protected]

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