ID-118 : ALERA2
AFES–LETKF experimental ensemble reanalysis 2 produced on the Earth Simulator.
AFES (AGCM for the Earth Simulator) is run at a resolution of T119L48 (about 100 km in the horizontal and 48 layers in the vertical). The PREPBUFR complied by the National Centers for Environmental Prediction (NCEP) and archived at the University Corporation for Atmospheric Research (UCAR) is used for the observational data and assimilated using the LETKF (local ensemble transform Kalman filter).
National Institute of Polar Research
JSPS KAKENHI Grant Number
Funding Information Other Funding Details
ArCS Theme 1 : Predictability study on weather and sea-ice forecasts linked with user engagement
Abstract (Brief description of the experiment contents (initial conditions, boundary conditions, etc.))
Administration daily 0.25 Optimal Interpolation Sea-Surface Temperature (OISST) version 2 was used for ocean and sea ice boundary conditions. Seven and 8 reanalysis datsest were made for each study. 1) 01/DEC/2015-31/MAR/2016 CTL included all PREPBUFR data. OSE_B, OSE_Ba, OSE_E, OSE_J, OSE_L excluded additional radiosonde observation data at each station (Bear Island, Barrow, Eureka, Jan Mayen, and RV Lance). OSE excluded these all additional radiosonde observation data. 2) 26/JUL/2016-30/AUG/2016 CTL included all PREPBUFR and radiosonde observations from RVs Polarstern, Araon and Branova station. OSE_B, OSE_A, OSE_P OSE_MID and OSE_TRO excluded additional radiosonde observation data at each station (RVs Polarstern and Araon, Branova stationm midlatitude and tropical stations). 3) 15/AUG/2016-28/SEP/2016 CTL included all PREPBUFR and radiosonde observations from RV Mirai, Global Hawk and Canadian stations. OSE_M, OSE_G, OSE_C excluded additional radiosonde observation data at each station (RV Mirai, Global hawk and Canadian stations). OSE_MGC excluded these all additional radiosonde observation data.
|Temporal Characteristics||6 hourly|
Geographic Bounding Box
|North bound latitude||90.0|
|West bound longitude||0.0|
|South bound latitude||-90.0|
Dimension Name Dimension Size (slice number of the dimension) Resolution Unit row 288 1.25 (deg) column 145 T119L48 gaussian grid (deg) vertical 18 1000, 925, 850, 775, 700, 600, 500, 400, 300, 250, 200, 150, 100, 70, 50, 30, 20, 10 (hPa)
|Dimension Name||Dimension Size (slice number of the dimension)||Resolution Unit|
|column||145||T119L48 gaussian grid (deg)|
|vertical||18||1000, 925, 850, 775, 700, 600, 500, 400, 300, 250, 200, 150, 100, 70, 50, 30, 20, 10 (hPa)|
Data is distributed through GrADS Data Server. Use DODS-enabled applications, such as GrADS or NCL for visualization and NCO (ncks) to slice and download data. Meta data is displayed when accessed with a web browser.
Article (the article written using this data)
1) Sato, K., J. Inoue, A. Yamazaki, J.-H. Kim, M. Maturilli, K. Dethloff, S. R. Hudson, and M. A. Granskog (2017), Improved forecasts of winter weather extremes over midlatitudes with extra Arctic observations, J. Geophys. Res. Oceans, 122, 775–787, doi:10.1002/2016JC012197. 2) Sato, K., J. Inoue, A. Yamazaki, J.-H. Kim, A. Makshtas, V. Kustov, M. Maturilli, and K. Dethloff, 2018: Impact on predictability of tropical and mid-latitude cyclones by extra Arctic observations. Sci. Rep., 8, https://doi:10.1038/s41598-018-30594-4.
|Roll||Contact Person||Name||Kazutoshi Sato||Affiliation||Kitami Institute of Technology||Country||Japanemail@example.com|
|Roll||Contact Person||Name||Jun Inoue||Affiliation||National Institute of Polar Research||Country||Japanfirstname.lastname@example.org|
08:41 on Thu January 5, 2017
13:35 on Wed May 29, 2019