Submitted by on Tue, 08/24/2010 - 09:30
  • Dee, D. P., and 35 co-authors, 2011: The ERA-Interim reanalysis: Configuration and performance of the data assimilation system. Quart. J. R. Meteorol. Soc., 137, 553-597. DOI: 10.1002/qj.828. Free and Open access!
  • Simmons, A. J. et al., 2014:  Estimating low-frequency variability and trends in atmospheric temperature using ERA-Interim. Quart. J. R. Meteorol. Soc., DOI: 10.1002/qj.2317. Free and Open access!
  • Simmons, A. J., K. M. Willett, P. D. Jones, P. W. Thorne, and D. P. Dee, 2010: Low-frequency variations in surface atmospheric humidity, temperature and precipitation: Inferences from reanalyses and monthly gridded observational datasets. J. Geophys. Res., 115, D01110, doi:10.1029/2009JD012442.
  • Kobayashi, S., M. Matricardi, D. P. Dee, and S. Uppala, 2009: Toward a consistent reanalysis of the upper stratosphere based on radiance measurements from SSU and AMSU-A. Quart. J. R. Meteorol. Soc., 135, 2086-2099, doi: 10.1002/qj.514.
  • Dee, D. P., and S. Uppala, 2009: Variational bias correction of satellite radiance data in the ERA-Interim reanalysis. Quart. J. R. Meteorol. Soc., 135, 1830-1841, doi:10.1002/qj.493.
  • Uppala, S., et al., 2005: The ERA-40 re-analysis. Quart. J. R. Meteorol. Soc., 131, 2961-3012, doi:10.1256/qj.04.176.


Albeht Rodrigu… (not verified)

Thu, 09/15/2016 - 13:01

Dear Sr.

How is the 0.5, 0.25 and other degree resoltution from N128 reduced Gaussian grid in ERa-Interim. Where

Dear Dr. Upal, To obtain help, you will need to provide significantly more information. From where have you obtained this code? For example, what is the URL that you used to access the file? What type of file contains this time code? For example, is this a binary file, a netcdf file, or a GRIB file? If it is a netcdf file, please send the output of the command "ncdump -h " best wishes,

Yi (not verified)

Wed, 10/21/2015 - 01:05

Hello, It's known that the ERA-Interim data is produced by atmospheric model. And SST output also can be found in data portal. Is that calculated in atmospheric model? then, how is it calculated? or If the SST is forced to atmospheric model, which SST data is forced? Thanks

In ERA-Interim the SST and sea-ice are prescribed fields, the provider of which varies with time, see Table I of Dee et al. (2011), The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q.J.R. Meteorol. Soc., 137: 553–597. doi: 10.1002/qj.828. This table lists the providers from 1989 onwards. For the ten years before 1989, you should read the discussion in Section 2 of Simmons, A. J. and Poli, P. (2015), Arctic warming in ERA-Interim and other analyses. Q.J.R. Meteorol. Soc., 141: 1147–1162. doi: 10.1002/qj.2422.

Dick Dee (not verified)

Thu, 03/13/2014 - 06:34

Gil, the only quantitative result we have is based on a sensitivity test performed some years ago with the ECMWF model (no data assimilation) that showed that the error resulted in a 1K warming in the model climate from 10 hPa upwards (zonally averaged over a 1-year period). The model version and resolution was different from ERA-Interim but I don't think that matters very much. What does matter is that the use of observations in ERA-Interim (temperatures from radiosondes as well as satellite data) must have reduced the bias. We never did a clean test in the reanalysis context so I can't be more precise. Of course there are other problems with biases in stratospheric temperatures - see Adrian SImmons's latest paper in QJ for a very thorough discussion (

Gil Compo (not verified)

Wed, 03/12/2014 - 11:44

Dear ECMWFers, What is the vertical extent of the "upper stratosphere" related to the the temperature bias issue: "Due to an error in the ECMWF forecast model, incident solar radiation at the top of the atmosphere is approximately 3Wm-2 higher than intended. This has resulted in a slightly warmer (approximately 1K) upper stratosphere for the entire ERA-Interim period (4 May 2009). " mentioned at thanks, gil compo

Dr. Siddarth S… (not verified)

Tue, 04/30/2013 - 04:28

Dear Sir, Please let me know the accuracy of humidty and temperature for ECMWF and ERA-Interim in different height levels, i.e. in troposphere and stratosphere. Please provide the references also. This matter is urgent. Looking forward to see your reply at the earliest. With best regards Siddarth Shankar Das

Quantifying with definitive assurance the accuracy of a data point as defined by ISO 5725-1 (trueness and precision) requires an absolute reference. However, the atmosphere is not covered at all times and all locations with such a network of absolute measurement points. Please read the ERA-Interim page on the NCAR Climate Data Guide for a detailed qualitative discussion of all the difficulties in estimating accuracy in reanalyses ( ). However, with these limitations in mind, we can estimate quantitatively the relative accuracy (trueness and precision) of atmospheric reanalyses, with respect to unevenly distributed and imperfect observations. Of course, these metrics are only valid at the observation locations and times, but they may serve as guidance. First, look for example at Figure 16 by Poli et al. 2010 for regional vertical profile estimates of global relative accuracy (trueness estimated by bias, and precision estimated by standard deviation) of ERA-Interim temperatures, with respect to radiosondes. Bear in mind that these numbers are not an upper bound as errors could be correlated or present similar biases, as radiosondes are assimilated in reanalyses, so the errors in either radiosondes and in ERA-Interim could be larger than the difference between the two. These numbers are also not a lower bound for the relative accuracy of radiosondes and ERA-Interim, as in some locations and times the errors could be smaller than shown by these estimates covering large areas of the globe. The same Figure also shows comparison with aircraft measurements, which gives you a hint to appreciate the relative accuracy estimates using another observation reference. Second, depending on your application, the variation in time of the accuracy (trueness and precision) may also be of importance. Look at time-series, e.g. Figure 18 by Dee et al. 2011 (see Figure 19 for humidity), as well as Figures 6, 7, and 9 by Poli et al. 2010 to appreciate the magnitude of changes in relative accuracy (trueness and precision). Last, for a hint at how these relative accuracy estimates vary locally in the spatial domain, consider also that remote regions may present larger errors due to paucity of observational information in the reanalyses, such as shown in Figure 1 by Dee and Uppala 2009 for locations at latitudes greater than 70 degrees North.

Dee, D. P. and Uppala, S. (2009), Variational bias correction of satellite radiance data in the ERA-Interim reanalysis. Q.J.R. Meteorol. Soc., 135: 1830–1841. doi: 10.1002/qj.493

Poli, P., Healy, S. B. and Dee, D. P. (2010), Assimilation of Global Positioning System radio occultation data in the ECMWF ERA–Interim reanalysis. Q.J.R. Meteorol. Soc., 136: 1972–1990. doi: 10.1002/qj.722

Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J., Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N. and Vitart, F. (2011), The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q.J.R. Meteorol. Soc., 137: 553–597. doi: 10.1002/qj.828

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