Journal metrics

Journal metrics

  • IF value: 8.792 IF 8.792
  • IF 5-year value: 8.414 IF 5-year 8.414
  • CiteScore value: 8.18 CiteScore 8.18
  • SNIP value: 2.620 SNIP 2.620
  • SJR value: 4.885 SJR 4.885
  • IPP value: 7.67 IPP 7.67
  • h5-index value: 28 h5-index 28
  • Scimago H index value: 24 Scimago H index 24
Earth Syst. Sci. Data, 8, 1-14, 2016
https://doi.org/10.5194/essd-8-1-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
15 Jan 2016
The GRENE-TEA model intercomparison project (GTMIP) Stage 1 forcing data set
T. Sueyoshi1,2, K. Saito2, S. Miyazaki1,2,a, J. Mori1,2, T. Ise3, H. Arakida4, R. Suzuki2, A. Sato5, Y. Iijima2, H. Yabuki1,2, H. Ikawa6, T. Ohta7, A. Kotani7, T. Hajima2, H. Sato2, T. Yamazaki8, and A. Sugimoto9 1National Institute of Polar Research, Tachikawa, Japan
2Japan Agency for Marine-Earth Science and Technology, Yokohama, Japan
3Kyoto University, Field Science Education and Research Center, Kyoto, Japan
4RIKEN Advanced Institute for Computational Science, Kobe, Japan
5National Research Institute for Earth Science and Disaster Prevention, Snow and Ice Research Center, Nagaoka, Japan
6National Institute for Agro-Environmental Sciences, Tsukuba, Japan
7Nagoya University, Graduate School of Bioagricultural Sciences, Nagoya, Japan
8Tohoku University, Graduate School of Science, Sendai, Japan
9Hokkaido University, Faculty of Environmental Earth Science, Sapporo, Japan
anow at: Sonic Corporation, Tachikawa, Japan
Abstract. Here, the authors describe the construction of a forcing data set for land surface models (including both physical and biogeochemical models; LSMs) with eight meteorological variables for the 35-year period from 1979 to 2013. The data set is intended for use in a model intercomparison study, called GTMIP, which is a part of the Japanese-funded Arctic Climate Change Research Project. In order to prepare a set of site-fitted forcing data for LSMs with realistic yet continuous entries (i.e. without missing data), four observational sites across the pan-Arctic region (Fairbanks, Tiksi, Yakutsk, and Kevo) were selected to construct a blended data set using both global reanalysis and observational data. Marked improvements were found in the diurnal cycles of surface air temperature and humidity, wind speed, and precipitation. The data sets and participation in GTMIP are open to the scientific community (doi:10.17592/001.2015093001).

Citation: Sueyoshi, T., Saito, K., Miyazaki, S., Mori, J., Ise, T., Arakida, H., Suzuki, R., Sato, A., Iijima, Y., Yabuki, H., Ikawa, H., Ohta, T., Kotani, A., Hajima, T., Sato, H., Yamazaki, T., and Sugimoto, A.: The GRENE-TEA model intercomparison project (GTMIP) Stage 1 forcing data set, Earth Syst. Sci. Data, 8, 1-14, https://doi.org/10.5194/essd-8-1-2016, 2016.
Short summary
This paper describes the construction of a forcing data set for land surface models (LSMs) with eight meteorological variables for the 35-year period from 1979 to 2013. The data set is intended for use in a model intercomparison (MIP) study, called GTMIP. In order to prepare a set of site-fitted forcing data for LSMs with realistic yet continuous entries, four observational sites were selected to construct a blended data set using both global reanalysis and observational data.
This paper describes the construction of a forcing data set for land surface models (LSMs) with...
Share