{ "version": 1, "refs": { ".zgroup": "{\"zarr_format\":2}", ".zattrs": "{\"jma_data_provider\":\"Japan Meteorological Agency (JMA)\",\"jma_data_provider_url\":\"https:\\/\\/www.jma.go.jp\\/jma\\/indexe.html\",\"jma_data_provider_address\":\"3-6-9 Toranomon, Minato City, Tokyo 105-8431, Japan\",\"jma_data_provider_email\":\"\",\"jma_data_title\":\"Japanese Reanalysis for Three Quarters of a Century (JRA-3Q)\",\"jma_data_abstract\":\"JMA is currently conducting the Japanese Reanalysis for Three Quarters of a Century (JRA-3Q), which covers the period from September 1947 onward to extend the current period of data coverage and improve the quality of long-term reanalysis. The project involves a sophisticated data assimilation system (based on the operational set-up as of December 2018) incorporating development results from the operational NWP system and sea surface temperature analysis achieved since JRA-55 (based on the operational set-up as of December 2009). New datasets of past observations are also assimilated, including rescued historical observations and reprocessed satellite data supplied by meteorological and satellite centers worldwide. Many of the deficiencies of JRA-55 are alleviated in JRA-3Q, providing a high-quality homogeneous reanalysis dataset that covers the previous 75 years.\",\"jma_data_url\":\"https:\\/\\/jra.kishou.go.jp\\/JRA-3Q\\/index_en.html\",\"jma_data_group\":\"Surface analysis fields (anl_surf125)\",\"jma_data_original_format\":\"WMO GRIB edition 2\",\"jma_data_original_grid\":\"1.25 degrees x 1.25 degrees from 90N to 90S and 0E to 358.75E (145 x 288 Latitude\\/Longitude)\",\"jma_data_documentation\":\"JRA-3Q Data Format, 1.25-degree latitude\\/longitude grid data, December 2022, 20pp.\",\"jma_data_documentation_url\":\"https:\\/\\/jra.kishou.go.jp\\/JRA-3Q\\/document\\/JRA-3Q_LL125_format_en.pdf\",\"jma_data_quality_issue_dec_2022\":\"JRA-3Q Usage, Local issues with sea ice parameters, 9 December 2022, 4pp.\",\"jma_data_quality_issue_dec_2022_url\":\"https:\\/\\/jra.kishou.go.jp\\/JRA-3Q\\/document\\/JRA-3Q_qualityissue_20221209_en.pdf\",\"jma_office\":\"Office of Earth System Modeling\",\"jma_division\":\"Numerical Prediction Division\",\"jma_department\":\"Information Infrastructure Department\",\"jma_principal_contact\":\"Mr. Shinya Kobayashi, , 1-1 Nagamine, Tsukuba, Ibaraki 305-0052, Japan\",\"jma_preliminary_publication\":\"Kobayashi, S., Y. Kosaka, J. Chiba, T. Tokuhiro, Y. Harada, C. Kobayashi, and H. Naoe, 2021: JRA-3Q: Japanese Reanalysis for Three Quarters of a Century. Joint WCRP-WWRP Symposium on Data Assimilation and Reanalysis\\/ECMWF Annual Seminar 2021, online, 13-17 September 2021, O4-2.\",\"jma_preliminary_publication_url\":\"https:\\/\\/symp-bonn2021.sciencesconf.org\\/data\\/355900.pdf\",\"jma_primary_publication\":\"Kosaka, Y., S. Kobayashi, Y. Harada, C. Kobayashi, H. Naoe, K. Yoshimoto, M. Harada, N. Goto, J. Chiba, K. Miyaoka, R. Sekiguchi, M. Deushi, H. Kamahori, T. Nakaegawa, T. Y. Tanaka, T. Tokuhiro, Y. Sato, Y. Matsushita, and K. Onogi, 2024: The JRA-3Q Reanalysis. J. Meteor. Soc. Japan, 102, 1-168 (DOI: 10.2151\\/jmsj.2024-004). (Reference to JRA-3Q data in scientific or technical papers should cite this comprehensive report.)\",\"jma_primary_publication_url\":\"https:\\/\\/www.jstage.jst.go.jp\\/article\\/jmsj\\/advpub\\/0\\/advpub_2024-004\\/_article\\/-char\\/ja\\/\",\"jma_data_source_acknowledgement\":\"This report references JRA-3Q reanalysis data from the Japan Meteorological Agency.\",\"jma_ncar_cooperative_agreement\":\"Letter dated 6 October 2023: Dr. Thomas Hauser (CISL Director, Associate NCAR Director) requests approval from JMA to archive JRA-3Q data in NCAR's Research Data archive (RDA) in alignment with the Terms and Conditions of Request Submission and Archival of Data to the RDA presented at https:\\/\\/rda.ucar.edu\\/resources\\/daas\\/terms-and-conditions\\/. The JRA-3Q data will be securely stored on NCAR disk storage with a tape backup copy maintained on NCAR's Quasar tape system. When accessing JRA-3Q data from NCAR's High Perforamnce Computing systems or from web data gateways, users will implicity agree to the conditions of use and conditions of the assigned data license provided by JMA. NCAR will monitor its data usage and share the metrics with JMA when called upon to do so. NCAR serves a broad research and education community, is managed by the University Corporation for Atmospheric Research (UCAR) and sponsored by the National Science Foundation (NSF). Letter dated 24 October 2023: Mr. Gouki Chiba (Director-General, Information Infrastructure Department, Japan Meteorological Agency) acting for Mr. Obayashi Masanori (Director-General, Japan Meteorological Agency) approves JMA provision of JRA-3Q data to the National Center for Atmospheric Research (NCAR) under the Creative Commons License CC BY-NC-SA 4.0. The intellectual property rights of the datasets belong exclusively to JMA.\",\"jma_jra3q_cobe_sst\":\"In JRA-3Q, the sea surface temperature (SST) specified as the lower boundary condition is the Centennial In Situ Observation-based Estimates of the Variability of SSTs and Marine Meteorological Variables Version 2 (COBE-SST2) with a resolution of 1 degree based on in situ observations until May 1985 and the Merged Satellite and In-Situ Data Global Daily Sea Surface Temperature (MGDSST) with a resolution of 0.25 degree based on satellite observations since June 1985. To enable evaluation of changes in product characteristics following the switch from COBE-SST2 to MGDSST, a sub-product using COBE-SST2 (JRA-3Q-COBE) is also provided for the period from June 1985 to December 1990.\",\"rda_principal_archive\":\"Research Data Archive (RDA)\",\"rda_principal_archive_url\":\"https:\\/\\/rda.ucar.edu\\/\",\"rda_dataset\":\"ds640.0\",\"rda_dataset_title\":\"Japanese Reanalysis for Three Quarters of a Century (JRA-3Q)\",\"rda_dataset_url\":\"https:\\/rda.ucar.edu\\/datasets\\/ds640.0\\/\",\"rda_dataset_group\":\"JRA-3Q 1.25 degree surface analysis fields (anl_surf125) [netCDF4]\",\"rda_dataset_doi\":\"10.5065\\/AVTZ-1H78\",\"rda_dataset_license\":\"Creative Commons License CC BY-NC-SA 4.0\",\"rda_how_to_cite_this_dataset_esip\":\"Japan Meteorological Agency. 2023, updated monthly. Japanese Reanalysis for Three Quarters of a Century (JRA-3Q). Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory. https:\\/\\/doi.org\\/10.5065\\/AVTZ-1H78. Accessed dd mmm yyyy. [Please fill in the 'Accessed' date with the day, month, and year (e.g. - 5 Aug 2011) you last accessed the data from the RDA.]\",\"rda_how_to_cite_this_dataset_agu\":\"Japan Meteorological Agency. (2023). Japanese Reanalysis for Three Quarters of a Century (JRA-3Q) (Updated monthly) [Dataset]. Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory. https:\\/\\/doi.org\\/10.5065\\/AVTZ-1H78. Accessed dd mmm yyyy. [Please fill in the 'Accessed' date with the day, month, and year (e.g. - 5 Aug 2011) you last accessed the data from the RDA.]\",\"rda_how_to_cite_this_dataset_ams\":\"Japan Meteorological Agency, 2023: Japanese Reanalysis for Three Quarters of a Century (JRA-3Q). Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory, accessed dd mmm yyyy, https:\\/\\/doi.org\\/10.5065\\/AVTZ-1H78. [Please fill in the 'Accessed' date with the day, month, and year (e.g. - 5 Aug 2011) you last accessed the data from the RDA.]\",\"rda_how_to_cite_this_dataset_datacite\":\"Japan Meteorological Agency (2023): Japanese Reanalysis for Three Quarters of a Century (JRA-3Q). Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory. Dataset. https:\\/\\/doi.org\\/10.5065\\/AVTZ-1H78. Accessed dd mmm yyyy. [Please fill in the 'Accessed' date with the day, month, and year (e.g. - 5 Aug 2011) you last accessed the data from the RDA.]\",\"rda_principal_affiliation\":\"National Center for Atmospheric Research (NCAR)\",\"rda_principal_affiliation_url\":\"https:\\/\\/ncar.ucar.edu\\/\",\"rda_principal_affiliation_postal_address\":\"P.O. Box 3000, Boulder, CO 80307-3000\",\"rda_principal_affiliation_shipping_address\":\"3090 Center Green Dr., Boulder, CO 80301\",\"rda_laboratory\":\"Computational and Information Systems Lab (CISL)\",\"rda_division\":\"Information Systems Division (ISD)\",\"rda_section\":\"Data Engineering and Curation Section (DECS)\",\"rda_manager\":\"Doug Schuster \",\"rda_download_specialist\":\"Chi-Fan Shih \",\"rda_computational_specialist\":\"Dave Stepaniak \",\"rda_grib2_to_netcdf4_format_conversion_specialist\":\"Dave Stepaniak \",\"rda_compression_specialist\":\"Dave Stepaniak \",\"rda_archive_specialist\":\"Dave Stepaniak \",\"rda_web_services_contributors\":\"Riley Conroy ; Tom Cram ; Bob Dattore ; Hua Ji \",\"rda_jra3q_tape_history\":\"For data prior to 1 January 2022, JMA shipped JRA-3Q and JRA-3Q-COBE data on 3 LTO-5 and 107 LTO-6 tapes to Chi-Fan Shih (NCAR), who forwarded the tapes to a Tape Ark data center located in the United States (1950 N.Stemmons Fwy, Suite 2033, Dallas, TX, 75207) for reading and Globus upload to NCAR HPC storage. Mr. Shih returned the tapes to JMA. The Tape Ark corporate website is https:\\/\\/www.tapeark.com, with headquarters located in Perth, Western Australia (Level 1, 2 Brook Street, East Perth, WA, 6004). (For questions concerning coordination of the JRA-3Q tape archive within JMA, Mr. Hitoshi Sato, Senior Scientific Officer, , has been designated for this purpose.)\",\"rda_data_output_grid\":\"1.25 degrees x 1.25 degrees from 90N to 90S and 0E to 358.75E (145 x 288 Latitude\\/Longitude)\",\"unidata_nc4lib_python_module\":\"netCDF4\",\"unidata_nc4lib_python_module_url\":\"https:\\/\\/unidata.github.io\\/netcdf4-python\\/\",\"unidata_nc4lib_python_module_version\":\"4.8.1 of Oct 31 2022 22:17:45 $\",\"Conventions\":\"CF-1.10\",\"rda_python_version\":\"3.9.16\",\"rda_processing_program\":\".\\/ds640.0.jra3q.production.py\",\"numpy_version\":\"1.23.5\",\"numpy_url\":\"https:\\/\\/numpy.org\\/\",\"numpy_citation\":\"Harris, C.R., Millman, K.J., van der Walt, S.J. et al. Array programming with NumPy. Nature 585, 357-362 (2020). DOI:10.1038\\/s41586-020-2649-2.\",\"scipy_version\":\"1.10.0\",\"scipy_url\":\"https:\\/\\/scipy.org\\/\",\"scipy_citation\":\"Pauli Virtanen, Ralf Gommers, Travis E. Oliphant, Matt Haberland, Tyler Reddy, David Cournapeau, Evgeni Burovski, Pearu Peterson, Warren Weckesser, Jonathan Bright, Stefan J. van der Walt, Matthew Brett, Joshua Wilson, K. Jarrod Millman, Nikolay Mayorov, Andrew R. J. Nelson, Eric Jones, Robert Kern, Eric Larson, CJ Carey, Ilhan Polat, Yu Feng, Eric W. Moore, Jake VanderPlas, Denis Laxalde, Josef Perktold, Robert Cimrman, Ian Henriksen, E.A. Quintero, Charles R Harris, Anne M. Archibald, Antonio H. Ribeiro, Fabian Pedregosa, Paul van Mulbregt, and SciPy 1.0 Contributors. (2020) SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python. Nature Methods, 17(3), 261-272.\",\"rda_wgrib2_version\":\"3.1.1\",\"rda_system_information\":\"Linux crhtc34 5.14.21-150400.24.46-default #1 SMP PREEMPT_DYNAMIC Thu Feb 9 08:38:18 UTC 2023 (2d95137) x86_64 x86_64\",\"rda_system_location\":\"NCAR-Wyoming Supercomputing Center (NWSC)\",\"rda_system_location_address\":\"8120 Veta Dr, Cheyenne, WY 82009\",\"rda_system_location_url\":\"https:\\/\\/www2.cisl.ucar.edu\\/ncar-wyoming-supercomputing-center\",\"rda_campaign_storage_source_location\":\"\\/gpfs\\/csfs1\\/collections\\/rda\\/transfer\\/tapeark\\/Hist\\/Daily\",\"rda_campaign_storage_work_location\":\"\\/gpfs\\/csfs1\\/collections\\/rda\\/work\\/davestep\\/ds640.0-JRA3Q\",\"rda_campaign_storage_web_data_location\":\"\\/gpfs\\/csfs1\\/collections\\/rda\\/data\\/ds640.0\",\"rda_pbs_walltime\":\"-l walltime=1:00:00 (Total wall clock to process all 'anl_surf125' parameters for 1949-07)\",\"rda_pbs_resource_selection\":\"-l select=1:ncpus=1:mem=20G\",\"rda_processing_begin\":\"Fri Apr 5 06:31:49 MDT 2024\",\"rda_processing_end\":\"Fri Apr 5 06:31:52 MDT 2024\",\"rda_processing_elapsed_time_seconds\":4,\"rda_processing_elapsed_time_includes_compression\":\"True\",\"rda_compression_history\":\"Compression of this netCDF4 file achieved with python 3.9.16, netCDF4 python module 4.8.1 of Oct 31 2022 22:17:45 $, zlib compression technology (run time version 1.2.13), using createVariable method and api, compression level 4, shuffle set to True, and fletcher32 set to False. The compression classification is reversible lossless data compression.\",\"rda_github_software_repository\":\"https:\\/\\/github.com\\/NCAR\\/rda-jra3q-processing\\/tree\\/main\",\"rda_software_license\":\"MIT License. Copyright (c) 2018 National Center for Atmospheric Research. Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the 'Software'), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and\\/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED 'AS IS', WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.\",\"rda_nsf_statement\":\"This material is based upon work supported by the National Center for Atmospheric Research, a major facility sponsored by the National Science Foundation and managed by the University Corporation for Atmospheric Research. Any opinions, findings and conclusions or recommendations expressed in this material do not necessarily reflect the views of the National Science Foundation.\",\"rda_alias_formatted_ncdump_tcshrc\":\"alias ncdumpf \\\"ncdump -h \\\\!:2 | fmt -s -w \\\\!:1 | egrep --color ':?[a-zA-Z0-9_]+ =|'\\\" # Remove any backslashes preceding each single or double quote. Remove one backslash preceding each !. Example use: 'ncdumpf 100 ncfile.nc' produces a 100 character wide formatted and highlighted output of 'ncdump -h ncfile.nc'.\",\"rda_function_formatted_ncdump_bashrc\":\"ncdumpf(){ file=$2; width=$1; ncdump -h $file | fmt -w $width -s | egrep --color ':?[a-zA-Z0-9_]+ =|$'; } # Remove any backslashes preceding each single quote. Example use: 'ncdumpf 100 ncfile.nc' produces a 100 character wide formatted and highlighted output of 'ncdump -h ncfile.nc'.\",\"rda_related_datasets\":\"ds640.1, Near Real-Time Japanese Reanalysis for Three Quarters of a Century (JRA-3Q), https:\\/\\/rda.ucar.edu\\/datasets\\/ds640.1\\/\"}", "time/.zarray": "{\n \"shape\": [\n 124\n ],\n \"chunks\": [\n 124\n ],\n \"dtype\": \"