Meteorological observations during the SWERUS-C3 Arctic Ocean expedition 2014 and colocated regional climate model output

Joseph Sedlar

Observations of the atmospheric thermodynamic structure, wind profiles and surface energy budget components from the Eastern Arctic Ocean in July through early October 2014.

The data were collected and processed as part of the Arctic Clouds in Summer Experiment (ACSE) during the SWERUS-C3 expedition onboard the icebreaker Oden.

The observational data are combined with model simulation output from six regional climate models. Models and observations are colocated every hour with the icebreaker's position, facilitating model versus observations, and inter-model, comparison efforts.

Citation

Joseph Sedlar (2020) Meteorological observations during the SWERUS-C3 Arctic Ocean expedition 2014 and colocated regional climate model output. Dataset version 1. Bolin Centre Database. https://doi.org/10.17043/oden-swerus-2014-rcm-metobs-1

References

Sedlar, J., Tjernström, M., Rinke, A., Orr, A., Cassano, J., Fettweis, X., Heinemann, G., Seefeldt, M., Solomon, A., Matthes, H., Phillips, T., Webster, S. (2020). Confronting Arctic troposphere, clouds, and surface energy budget representations in regional climate models with observations. J. Geophys. Res. Atmos., 125, e2019JD031783. https://doi.org/10.1029/2019JD031783

Achtert, P., O'Connor, E. J., Brooks, I. M., Sotiropoulou, G., Shupe, M. D., Pospichal, B., Brooks, B. J., Tjernström, M. (2020). Properties of Arctic liquid and mixed phase clouds from ship-borne Cloudnet observations during ACSE 2014. Atmos. Chem. Phys. Discuss. (in review). https://doi.org/10.5194/acp-2020-56

Sedlar, J., Tjernström, M. (2019). A process-based climatological evaluation of AIRS level 3 tropospheric thermodynamics over the high-latitude Arctic, J. Appl. Meteorol. Climatol., 58, 1867⁠ – ⁠1886, https://doi.org/10.1175/JAMC-D-18-0306.1

Tjernström, M., Achtert, P., Shupe, M. D., Prytherch, J., Sedlar, J., Brooks, B. J., Brooks, I. M., Persson, P. O. G., Sotiropoulou, G., Salisbury, D. J. (2019). Arctic summer air-mass transformation, surface inversions and the surface energy budget. Journal of Climate: 32, 769⁠ – ⁠789. https://doi.org/10.1175/JCLI-D-18-0216.1

Prytherch, J., Brooks, I. M., Crill, P. M., Thornton, B. F., Salisbury, D. J., Tjernström, M., Anderson, L. G., Geibel, M. C., Humborg, C. (2017). Direct determination of the air-sea CO₂ gas transfer velocity in Arctic sea-ice regions. Geophys. Res. Lett., 44. https://doi.org/10.1002/2017GL073593

Sotiropoulou, G., Tjernström, M., Sedlar, J., Achtert, P., Brooks, B. J., Brooks, I. M., Persson, P. O. G., Prytherch, J., Salisbury, D. J., Shupe, M. D., Johnston, P. E., Wolfe, D. (2016). Atmospheric conditions during the Arctic Clouds in Summer Experiment (ACSE): Contrasting open-water and sea-ice surfaces during melt and freeze-up seasons. J. Clim., 29, 8721⁠ – ⁠8744. https://doi.org/10.1175/JCLI-D-16-0211.1

Achtert, P., Brooks, I. M., Brooks, B. J., Prytherch, J., Persson, P. O. G., Tjernström, M. (2015): Measurement of wind profiles over the Arctic Ocean from ship-borne Doppler lidar. Atmos. Meas. Tech. 8, 4993⁠ – ⁠5007. https://doi.org/10.5194/amt-8-4993-2015

Tjernström, M., Shupe, M. D., Brooks, I. M., Persson, P. O. G., Prytherch, J., Salisbury, D. J., Sedlar, J., Achtert, P., Brooks, B. J., Johnston, P. E, Sotiropoulou, G., Wolfe, D. (2015). Warm-air advection, air mass transformation and fog causes rapid ice melt. Geophys. Res. Lett., 42. https://doi.org/10.1002/2015GL064373

Data description

Herein are the 1-hr surface (1D) variables and the profile (2D) variables from the ACSE meteorological field program during SWERUS-C3 2014 (Achtert et al. 2015, Tjernström et al. 2015, Sotiropoulou et al. 2016, Prytherch et al. 2017, Sedlar and Tjernström 2019, Tjernström et al. 2019, Achtert et al. 2020). The observations and regional climate model datasets are grouped together and included in two separate netCDF files:

1. for 1D near-surface or column-integrated properties (13.1 MB); and
2. 2D profiles (422.5 MB).

Attributes are included for each variable, describing the variable long name, averaging method (cell_methods), units, and missing values. Grouping observations and models together in the same netCDF files facilitates straightforward comparisons between the observations and the models.

Observational data include general meteorology measurements from near-surface sensors onboard Oden, retrievals of data products from remote sensing instrumentation, and radiosounding profiles launched continuously every 6 hours. Besides the 6 hourly radiosoundings, all other measurements/data products are produced at much higher temporal frequencies. From these higher frequency measurements/products, 1-hour averages and instantaneous snapshots were produced. The following measurements/data products are included in these files, including citations to where the raw measurements can be found:

1. Near-surface meteorology (data source: Weather data from the MISU weather station during the SWERUS-C3 Arctic Ocean expedition in 2014)

   • Vaisala PTU pressure, temperature and relative humidity sensor.
   • Gill WindSonic M 2D sonic anemometer wind speed and direction sensor (measured with respect to bow of the ship; ship’s navigation data used to derive true wind speed/direction).
   • Eppley Precision Spectral Pyranometer and PIR pyrgeometer for downwelling broadband shortwave and longwave horizontal irradiance, respectively.
   • Surface skin temperature from two KT15 infrared thermometers viewing the sea/ice surface of the port and starboard.

2. Eddy covariance measurements on the ship’s bow mast approximately 20 m above sea level, to derive 30 min friction velocity, sensible and latent heat fluxes (data source: Micrometeorological data from icebreaker Oden’s foremast during the SWERUS-C3 Arctic Ocean expedition in 2014)

   • Metek heated sonic anemometer measuring 3D wind speeds at 20 Hz. Wind speed/direction corrected for platform motion and flow distortion.
   • Aspirated temperature and relative humidity sensor at approximately equal height as sonic anemometer.

3. 94 GHz W-band cloud radar (raw data obtained from Matthew Shupe, CIRES, University of Colorado, Boulder, USA)

   • Zenith viewing Doppler cloud radar measuring Doppler velocity weighted power returned from cloud droplets and hydrometeors (rain, ice, snow).
   • Cloud boundaries (data product used in Achtert et al. 2020 to retrieve vertical profiles of cloud liquid and ice water content).

4. Vaisala CL51 ceilometer (raw data obtained from Michael Tjernström, Department of Meteorology, Stockholm University, Sweden)

   • Zenith viewing lidar measuring backscatter of aerosol and cloud particles.
   • Retrieval of liquid cloud base height in up to 3 layers (data product used in Achtert et al. 2020 to retrieve vertical profiles of cloud liquid and ice water content).

5. Dual channel (24/31 GHz) microwave radiometer (raw data obtained from Matthew Shupe, CIRES, University of Colorado, Boulder, USA)

   • Passive zenith viewing microwave brightness temperatures with retreivals of column integrated water vapor and cloud liquid water path (data product used in Achtert et al. 2020 to retrieve vertical profiles of cloud liquid and ice water content).

6. Radiosounding profiles every 6 hours (raw data obtained from Michael Tjernström, Department of Meteorology, Stockholm University, Sweden)

   • Temperature and specific humidity profiles as a function of pressure and height.
   • Wind speed and wind direction as a function of pressure and height.

Regional climate model (RCM) output of general meteorology, energy fluxes, and vertical profiles of thermodynamics, dynamics, and cloud microphysics are included in the 1D and 2D data files for six models, with a total of 10 different simulations. These models include the

• HIRHAM5,
• CCLM,
• MAR_v3.9.6,
• CAFS,
• WRF_CU and
• MetUM.

The HIRHAM5, CCLM, and CAFS RCMs provided more than one simulation (Sedlar et al. 2020). Each model simulation is stored as a group in the netCDF files under the following names (see Tables 1 and 2 in Sedlar et al. 2020 for model details):

• hirham5_v1: HIRHAM5, Alfred Wegener Institute, Germany
• hirham5_v2: HIRHAM5, Alfred Wegener Institute, Germany
• hirham5_v3: HIRHAM5, Alfred Wegener Institute, Germany
• mar_v3.9.6: MAR, University of Liege, Belgium
• cclmi: CCLM, University of Trier, Germany
• cclm5: CCLM, University of Trier, Germany
• cafs_bsl; CAFS, NOAA ESRL Physical Sciences Division and CIRES University of Colorado Boulder, USA
• cafs_ini: CAFS, NOAA ESRL Physical Sciences Division and CIRES University of Colorado Boulder, USA
• wrf_cu: WRF, CIRES University of Colorado, Boulder
• MetUM: UM, UK Met Office and British Antarctic Survey, UK

Comments

A detailed description of the meteorological measurements is found in Sotiropoulou et al. (2016).

Details regarding the retrievals of cloud microphysical properties from combined cloud radar, lidar and thermodynamic profiles, are found in Achtert et al. (2020).