The RAOBCORE/RICH software package has been developed at University of Vienna since 2004. It has been initially funded by an EU Marie Curie fellowship for Dr. Leopold Haimberger and has then been funded by three FWF projects: P18120-N10, P21772-N22 and the current project P25260-N29, which is herewith gratefully acknowledged. We also acknowledge funding from EU FP7 collaborative projects ERA-CLIM and ERA-CLIM2
News: Comprehensive radiosonde/PILOT temperature and wind archive on 16 standard pressure levels
Within the framework of EU-project ERA-CLIM, a comprehensive radiosonde/PILOT wind archive has been developed. It can be accessed via PANGAEA (http://doi.pangaea.de/10.1594/PANGAEA.823617) over their standardized portal. It can be also accesses as a collection of NetCDF files via http://srvx7.img.univie.ac.at/~lorenzo/download_DATA/download_DATA.php
The password is "data". The archive does not yet contain homogeneity adjustments. These will be published separately.
RAOBCORE and RICH homogeneity adjustments for upper air temperatures from the global radiosonde network. The homogeneity adjustments are required for serious analysis of the upper air climate of the past decades and may be used also for improving the data input for climate data assimilation efforts (often called reanalyses) such as ERA-40 or ERA-Interim.
The adjustment process has two steps:
1) Detection of shifts in existing radiosonde observation time series
2) Estimation of the size of the shifts through comparison with suitable reference series.
Breakpoints in observed radiosonde temperature time series are detected through time series analysis of innovation statistics from ERA-40 (1958-1978) and ERA-Interim (1979 onwards). This means that background forecast time series have been used as reference for break detection. The rationale for this approach is documented in Haimberger (2007) (J. Climate).
The background forecast time series serve well as a reference for break detection but once the breakpoints are known, there are several options for breaksize estimation. We have implemented two options so far:
One is to use again the background forecasts as reference. This has been done in the RAOBCORE homogenization method.
The current version of radiosonde temperature adjustments is v1.5.1 It basically consists of a single ASCII-file containing the stationIDs and all the adjustments and adjustment dates on 16 pressure levels for 00GMT and 12GMT. The adjustments can be added to the original datasets to yield homogenized time series.
A RAOBCORE- v1.5 adjusted temperature anomaly dataset with 10x5 degree resolution can be downloaded as ftp://srvx7.img.univie.ac.at/pub/v1.5.1/raobcore15_gridded_2014.nc
It covers the period 1958-2011. For some users it may be of interest to have also the raw gridded radiosonde data, which are available as ftp://srvx7.img.univie.ac.at/pub/v1.5.1/raobcore_raw_gridded_2014.nc
Using the background forecasts as reference has the disadvantage that the forecasts themselves may be influenced by biases in the radiosonde temperatuers. They may also be influenced by biases from other observing systems, most notably satellites. This problem can be avoided by creating reference series from neighboring radiosonde stations for breakpoint adjustment. This works well as long as the radiosonde network is not too sparse and as long one takes care that only homogeneous pieces of the neighboring time series are used. RICH is superficially documented in Haimberger, Tavolato and Sperka (2008). A more detailed documentation can be found at Haimberger, Tavolato and Sperka (2012).
A gridded NetCDF formatted RICH-adjusted radiosondet dataset based on RAOBCORE v1.5 can be downloaded as
ftp://srvx7.img.univie.ac.at/pub/v1.5.1/rich15obs_mean_gridded_2014.nc This file is based on RICH-obs, which uses composites of neighboring observations for break adjustments.
The mean of RICH-tau (v1.5) that uses composites of innovations can be found at ftp://srvx7.img.univie.ac.at/pub/v1.5.1/ens/rich15tau_mean_gridded_2014.nc.
Other formats of RAOBCORE- and RICH adjusted data
The RICH datasets above are means of 32 realizations of RICH based on one realization of RAOBCORE. One can download individual ensemble members of RICH-obs and RICH-tau from ftp://srvx7.img.univie.ac.at/pub/v1.5.1/ens/
Station time series with monthly and daily resolution are available on request from leopold.haimberger(at)univie.ac.at
- Haimberger, L., C. Tavolato and S. Sperka, 2012: Homogenization of the global radiosonde dataset through combined comparison with reanalysis background series and neighboring stations. J. Climate 25, 8108–8131
- Ladstädter, F., Steiner, A. K., Foelsche, U., Haimberger, L., Tavolato, C., and Kirchengast, G., 2011: An assessment of differences in lower stratospheric temperature records from (A)MSU, radiosondes, and GPS radio occultation, Atmos. Meas. Tech., 4, 1965-1977, doi:10.5194/amt-4-1965-2011
- Mayer, M., and Haimberger, L., 2011. Poleward atmospheric energy transports and their variability as evaluated from ECMWF reanalysis data. Journal of Climate, in press. [pdf]
- Haimberger, L., C. Tavolato and S. Sperka, 2008: Towards elimination of the warm bias in historic radiosonde temperature records - some new results from a comprehensive intercomparison of upper air data, J. Climate 21, 4587-4606.
- Santer, B., P. Thorne, L. Haimberger, K. Taylor, T. Wigley, J. Lanzante, S. Solomon, M. Free, P. Gleckler, P. Jones, T. Karl, S. Klein, C. Mears, G. Schmidt, D. Seidel, S. Sherwood, and F. Wentz, 2008: Consistency of modelled and observed temperature trends in the tropical troposphere. Int. J. Climatol., 28,
- Haimberger, L., 2007: Homogenization of radiosonde temperature time series using innovation statistics. J. Climate 20, 1377-1403.
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