Northern Hemisphere Lamb Weather Types from historical GCM experiments and various reanalyses

This dataset contains 6-hourly instantaneous categorial data of the Lamb circulation types (Lamb 1972) on a 2.5 degrees longitude-latitude grid covering the northern hemisphere extratropics between 30ºN and 70ºN for the period 1979-2005. These "Lamb catalogues" were calculated for the historical experiments of 61 distinct GCMs from the Coupled Model Intercomparison Project phase 5 and 6 and for three distinct reanalyses (ERA5 extended to 2020 from version 5 onwards, ERA-Interim and JRA-55). For 13 out of 56 GCMs, 72 additional runs are provided to explore the role of internal model variability. For more information, please refer to the following article: Brands, S. (2021): A circulation-based performance atlas of the CMIP5 and 6 models for regional climate studies in the northern hemisphere. Geoscientific Model Development, https://doi.org/10.5194/gmd-2020-418 or contact: swen.brands@gmail.com Reference: Lamb, H.: British Isles Weather types and a register of daily sequence of circulation patterns, 1861-1971, Geophysical Memoir, 116, 85pp., HMSO, 1972. CAUTION: When unpacked, this dataset occupies 110 GB of your local disk space. Update information: Version 2 of this archive includes the model_source_attributes.txt file containing the "source" attributes stored in the netCDF files obtained from ESGF. This attribute provides details about the individual component models within the coupled model configurations used in CMIP5 and 6. Version 3 of this archive includes 10 new GCMs, two additional runs for CNRM-CM6-1 and an updated version of model_source_attributes.txt Version 3.1 includes README.txt, which explains the content of the files located in the tar.gz file. Version 4 further includes Lamb Weather Type catalogues for the ERA5 reanalysis and 4 additional GCMs. All files have been compressed individually. The file is depreciated and no longer updated. It is replaced by the Python function available from https://doi.org/10.5281/zenodo.4555367. This function contains an exhaustive metadata archive of the 60 GCMs considered here. Version 4.1 The LWT catalogue for CMCC-CM2-HR4 is included for consistency with the respective Southern Hemisphere dataset published at https://doi.org/10.5281/zenodo.7612987 Version 5 is a major dataset update featuring the following improvements: 1. The attributes from the netCDF source files "psl...nc" obtained from ESGF were copied into the files available here. These attributes are indicated with the prefix "udata...." (for "underlying data"). 2. All non-standard calenders from the underlying netCDF files from ESGF were converted into standard using the "xarray.Dataset.convert_calendar" function. The original calendar information was stored as additional netCDF attribute. 3. The "patch" method from Python's xesmf module was used to regrid the original psl data from the native GCM grid available from ESGF to the regular lat-lon 2.5° grid common to all applied GCMs and reanalyses. contact: Swen Brands, brandssf@ifca.unican.es Principal Research Articles, Software and Complementary Datasets Associated with this Dataset Brands, S. (2022). A circulation-based performance atlas of the CMIP5 and 6 models for regional climate studies in the Northern Hemisphere mid-to- high latitudes. Geoscientific Model Development, 15 (4), 1375–1411. doi: https://doi.org/10.5194/gmd-15-1375-2022 Brands, S. (2022). A circulation-based performance atlas of the CMIP5 and 6 mod- els for regional climate studies in the northern hemisphere [data set]. Zenodo. doi: https://doi.org/10.5281/zenodo.4452080 Brands, S. (2022). Common error patterns in the regional atmospheric circulation simulated by the CMIP multi-model ensemble. Geophysical Research Letters, 49 (23), e2022GL101446. doi: https://doi.org/10.1029/2022GL101446 Brands, Swen, Tatebe, Hiroaki, Danek, Christopher, Fernández, Jesús, Swart, Neil C., Volodin, Evgeny, Kim, YoungHo, Collier, Mark, Bi, Dave, & Tongwen, Wu. (2022). Python code to calculate Lamb circulation types derived from historical CMIP simulations and reanalysis data. In Geoscientific Model Development: Vols. gmd-2020-418 (Version 4). Zenodo. https://doi.org/10.5281/zenodo.6390256 Brands, S., Fernández-Granja, J. A., Bedia, J., Casanueva, A., & Fernández, J. (2023). Auxiliary online material to Brands et al. (2023): A global climate model performance atlas for the Southern Hemisphere extratrop- ics based on regional atmospheric circulation patterns. figshare. doi: https://doi.org/10.6084/m9.figshare.22193443.v1 Brands, S., Fernández-Granja, J. A., Bedia, J., Casanueva, A., & Fernández, J. (2023b). Southern Hemisphere Lamb Weather Types from historical GCM experiments and various reanalyses (1.0) [data set]. Zenodo. doi: https://doi.org/10.5281/zenodo.7612988 Brands, S., Tatebe, H., Danek, C., Fernández, J., Swart, N., Volodin, E., . . . Tong- wen, W. (2023). GCM metadata archive get historical metadata.py (v1.1). Zenodo. doi: https://doi.org/10.5281/zenodo.7715383 Fernández-Granja, J. A., Brands, S., Bedia, J., Casanueva, A., & Fernández, J. (2023). Exploring the limits of the Jenkinson–Collison weather types clas- sification scheme: a global assessment based on various reanalyses. Climate Dynamics. doi: 10.1007/s00382-022-06658-7 References of the source GCMs and Early References of the Lamb Weather Typing Method Bentsen, M., Bethke, I., Debernard, J. B., Iversen, T., Kirkevåg, A., Seland, Ø., . . . Kristjánsson, J. E. (2013). 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II , 97 (5), 931-965. doi: 10.2151/jmsj.2019-051 Yukimoto, S., Yoshimura, H., Hosaka, M., Sakami, T., Tsujino, H., Hirabara, M., . . . Kitoh, A. (2011). Meteorological Research Institute-Earth System Model version 1 (MRI-ESM1) — model description —.Technical Reports of the Meteorological Research Institute, 64 , 1-96. Ziehn, T., Chamberlain, M. A., Law, R. M., Lenton, A., Bodman, R. W., Dix, M., . . . Srbinovsky, J. (2020). The Australian Earth System Model: ACCESS- ESM1.5. Journal of Southern Hemisphere Earth Systems Science, 70 , 193-214. doi: https://doi.org/10.1071/ES19035The underlying Python code for this dataset is provided in the separate Zenodo entry: https://doi.org/10.5281/zenodo.455536