By birgitterf |

NORA3

The NORA3 atmospheric hindcast (NORA3_atmosphere) (Haakenstad et al., 2021; Haakenstad and ) is produced by running the non-hydrostatic HARMONIE-AROME model (Seity et al.,2011, Bengtsson et al.,2017, Muller et al.,2017) with 3km horizontal resolution and 65 vertical levels. The model runs 9 hourly forecasts four times a day. Each forecast starts from an assimilated state of the last forecast adapted to surface observations. Model levels are forced with ERA-5 (https://climate.copernicus.eu/climate-reanalysis).

The NORA3 wave hindcast (NORA3_wave) (Breivik et al., 2022) is produced by running the wave model WAM cycle 4.7.0 (Günther et al., 1992; Hasselmann et al., 1988; Komen et al., 1994) with wind forcing from NORA_atmosphere (HARMONIE-AROME Cy40h1.2 hindcast with 3km horizontal resolution), daily ice concentration fields from the ARC-MFC physical reanalysis system of the Copernicus Marine Service (CMEMS) and wave spectra from ERA-5 (https://climate.copernicus.eu/climate-reanalysis) at the boundaries. The WAM model was set up with 30 frequencies logarithmically spanning the range 0.0345–0.5476 Hz and 24 directional bins. 
 

Data availability

NORA3_atmosphere 

  • https://thredds.met.no/thredds/dodsC/nora3wavesubset_files/atm_hourly/arome3km_1hr<yyyymm>.nc
    • Mean sea level pressure
    • Air temperature 2m
    • Relative humidity 2m
    • cloud_area_fraction for high, medium and low cloud types
    • fog
    • lifting condensation level
    • wind speed and direction, 10m
    • surface net longwave radiation and surface net shortwave radiation
    • precipitation amount hourly
  • https://thredds.met.no/thredds/dodsC/nora3wavesubset_files/wind_hourly/arome3kmwind_1hr_<yyyymm>.nc
    • wind speed and direction in 10, 20, 50, 100, 250, 500, 750m height every hour
  • https://thredds.met.no/thredds/dodsC/nora3wavesubset_files/atm_v2/arome3km_3hr_<yyyymm>.nc
    • Air temperature in 50, 100, 150, 200, 300 m height every 3 hours
    • Relative humidity in 50, 100, 150, 200, 300 m height every 3 hours
    • Wind speed and direction in 50, 100, 150, 200, 300 m height every 3 hours
    • Sea surface temperature every 3 hours (updated every 6 hours)

NORA3_wave

  • https://thredds.met.no/thredds/dodsC/nora3wavesubset_files/wave_v2/<yyyymm>_NORA3wave_sub.nc
    • Geographical subset of all wave parameters in monthly files
  • https://thredds.met.no/thredds/dodsC/nora3wavesubset_files/wave_v4/<yyyymm>_NORA3wave_sub_time_unlimited.nc
    • Permuted files for fast access to time series in single geographic locations

 

References:

Bengtsson, L., Andrae, U., Aspelien, T., Batrak, Y., Calvo, J., de Rooy, W., et al. (2017). The HARMONIE–AROME model configuration in the ALADIN–HIRLAM NWP system. Monthly Weather Review, 145(5), 1919–1935. https://doi.org/10.1175/MWR-D-16-0417.1

Breivik, Ø., Carrasco, A., Haakenstad, H., Aarnes, O. J., Behrens, A., Bidlot, J.-R., Björkqvist, J.-V., Bohlinger, P., Furevik, B. R., Staneva, J., and Reistad, M.(2022). The impact of a reduced high-wind Charnock parameter on wave growth with application to the North Sea, the Norwegian Sea, and the Arctic Ocean. Journal of Geophysical Research: Oceans, 127, e2021JC018196. https://doi.org/10.1029/2021JC018196

Günther, H., Hasselmann, S., & Janssen, P. A. E. M. (1992). Wamodel Cycle 4 (revised version) (tech. Rep. No. 4). Deutsches KlimaRechenZentrum.

Haakenstad, H., Breivik, Ø., Furevik, B., Reistad, M., Bohlinger, P., & Aarnes, O. J. (2021). NORA3: A nonhydrostatic high-resolution hindcast of the North Sea, the Norwegian Sea, and the Barents Sea. Journal of Applied Meteorology and Climatology. https://doi.org/10.1175/JAMC-D-21-0029.1

Haakenstad, H., & Breivik, Ø. (2022). NORA3. Part II: Precipitation and Temperature Statistics in Complex Terrain Modeled with a Nonhydrostatic Model, Journal of Applied Meteorology and Climatology, 61(10), 1549-1572.  DOI: https://doi.org/10.1175/JAMC-D-22-0005.1

Hasselmann, S., Hasselmann, K., Bauer, E., Janssen, P. A. E. M., Komen, G. J., Bertotti, L., et al. (1988). The WAM model—A third generation ocean wave prediction model. Journal of Physical Oceanography, 18, 1775–1810. https://doi.org/10.10/bhs3rr

Komen, G. J., Cavaleri, L., Donelan, M., Hasselmann, K., Hasselmann, S., & Janssen, P. A. E. M. (1994). Dynamics and modelling of ocean waves. Cambridge University Press.

Müller, M., Y. Batrak, J. Kristiansen, M. A. Ø. Køltzow, and G. Noer, 2017a: Characteristics of a convective-scale weather forecasting system for the European Arctic. Mon. Wea. Rev., 145, 4771–4787, https://doi.org/10.1175/MWR-D-17-0194.1. 

Müller, M., and Coauthors, 2017b: AROME-MetCoOp: A Nordic convective-scale operational weather prediction model. Wea. Forecasting, 32, 609–627, https://doi.org/10.1175/WAF-D-16-0099.1.

Seity, Y., Brousseau, P., Malardel, S., Hello, G., Bénard, P., Bouttier, F., et al. (2011). The AROME-France convective-scale operational model. Monthly Weather Review, 139(3), 976–991. https://doi.org/10.1175/2010MWR3425.1