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

This dataset comprises six-hourly Lamb Weather Type (LWT) time series covering the period 1979-2005 for a) historical experiments run with 61 distinct GCMs from CMIP5 and 6 (specified in "get_historical_metadata.py" published at https://doi.org/10.5281/zenodo.4555367) and b) 3 distinct reanalyses (ERA-Interim, JRA-55 and ERA5, the latter extended to 2020). The LWT time series are provided on a 2.5º regular latitude-longitude grid covering the southern hemisphere between 30ºS and 70ºS. The full LWT approach covering 27 classes is applied and the corresponding results for the Northern Hemisphere were stored in a companion dataset at https://doi.org/10.5281/zenodo.4452080. The format of the files is netCDF-4, compressed with the netCDF Kitchen Sink command "ncks -4 -L 1". The Python code used to generate this dataset is available from https://doi.org/10.5281/zenodo.4555367

Note

The LWT_SH.zip file contains all relevant data. Please ignore the separate netCDF files outside this zip file. These are old files that could not be deleted during the update from version 1 to 2 due to technical issues with Zenodo.

Historial

Version 2 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, [e-mail]

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). The Norwegian Earth System Model, NorESM1-M
– part 1: Description and basic evaluation of the physical climate.
Geoscientific Model Development, 6 (3), 687–720. doi: 10.5194/gmd-6-687-2013

Bi, D., Dix, M., Marsland, S., O’Farrell, S., Sullivan, A., Bodman, R., . . . Heerde-
gen, A. (2020). Configuration and spin-up of ACCESS-CM2, the new gener-
ation Australian Community Climate and Earth System Simulator Coupled
Model. Journal of Southern Hemisphere Earth Systems Science, 70 (1), 225-
251. doi: doi:10.1071/ES19040

Bi, D., Dix, M., Marsland, S. J., O’Farrell, S., Rashid, H., Uotila, P., . . . Puri, K.
(2013). The ACCESS coupled model: description, control climate and evaluation. Australian Meteorological and Oceanographic Journal , 63 , 41-64. doi: 0.22499/2.6301.004

Boucher, O., Servonnat, J., Albright, A. L., Aumont, O., Balkanski, Y., Bastrikov,
V., . . . Vuichard, N. (2020). Presentation and evaluation of the IPSL-CM6A-
LR climate model. Journal of Advances in Modeling Earth Systems, 12 (7),
e2019MS002010. doi: 10.1029/2019MS002010

Cao, J., Wang, B., Yang, Y.-M., Ma, L., Li, J., Sun, B., . . . Wu, L.
(2018). The NUIST Earth System Model (NESM) version 3: description and prelimi-
nary evaluation. Geoscientific Model Development, 11 (7), 2975–2993.
doi: 10.5194/gmd-11-2975-2018

Cherchi, A., Fogli, P. G., Lovato, T., Peano, D., Iovino, D., Gualdi, S., . . . Navarra,
A. (2019). Global mean climate and main patterns of variability in the CMCC-
CM2 coupled model. Journal of Advances in Modeling Earth Systems, 11 (1),
185-209. doi: 10.1029/2018MS001369

Chylek, P., Li, J., Dubey, M. K., Wang, M., & Lesins, G. (2011).
Observed and model simulated 20th century arctic temperature variability: Canadian Earth
System Model CanESM2. Atmospheric Chemistry and Physics Discussions,
11 , 22893–22907. doi: 10.5194/acpd-11-22893-2011

Collins, W. J., Bellouin, N., Doutriaux-Boucher, M., Gedney, N., Halloran, P., Hinton, T., . . . Woodward, S. (2011). Development and evaluation of an Earth-System model – HadGEM2. Geoscientific Model Development, 4 (4),1051–1075.doi: 10.5194/gmd-4-1051-2011

Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., . . .
Vitart, F. (2011). The ERA-Interim reanalysis: configuration and performance
of the data assimilation system. Q. J. R. Meteorol. Soc., 137 (656, Part a),
553-597. doi: 10.1002/qj.828

Döscher, R., Acosta, M., Alessandri, A., Anthoni, P., Arneth, A., Arsouze, T., . . .
Zhang, Q. (2021). The EC-Earth3 Earth System Model for the Coupled Model
Intercomparison Project 6. Geoscientific Model Development Discussions,
2021 , 1–90. doi: 10.5194/gmd-2020-446

Dufresne, J.-L., Foujols, M.-A., Denvil, S., Caubel, A., Marti, O., Aumont, O., . . .
Vuichard, N. (2013). Climate change projections using the IPSL-CM5 Earth
System Model: from CMIP3 to CMIP5. Clim. Dyn., 40 (9-10), 2123-2165. doi:
10.1007/s00382-012-1636-1

Dunne, J. P., Horowitz, L. W., Adcroft, A. J., Ginoux, P., Held, I. M., John, J. G.,
. . . Zhao, M. (2020). The GFDL Earth System Model version 4.1 (GFDL-
ESM 4.1): Overall coupled model description and simulation characteristics.
Journal of Advances in Modeling Earth Systems, 12 (11), e2019MS002015. doi:
https://doi.org/10.1029/2019MS002015

Dunne, J. P., John, J. G., Adcroft, A. J., Griffies, S. M., Hallberg, R. W., Shevli-
akova, E., . . . Zadeh, N. (2012). GFDL’s ESM2 Global Coupled Climate-
Carbon Earth System Models. Part I: Physical formulation and baseline
simulation characteristics.Journal of Climate, 25 (19), 6646–6665.
doi: https://doi.org/10.1175/JCLI-D-11-00560.1

Griffies, S., Winton, M., Donner, L., Horowitz, L., Downes, S., Farneti, R., . . .
Zadeh, N. (2011). The GFDL-CM3 coupled climate model: Characteristics
of the ocean and sea ice simulations. Journal of Climate, 24 , 3520-3544. doi:
10.1175/2011JCLI3964.1

Hajima, T., Watanabe, M., Yamamoto, A., Tatebe, H., Noguchi, M. A., Abe, M., . . .
Kawamiya, M. (2020). Development of the MIROC-ES2L Earth system model
and the evaluation of biogeochemical processes and feedbacks.
Geoscientific Model Development, 13 (5), 2197–2244. doi: 10.5194/gmd-13-2197-2020

Hazeleger, W., Wang, X., Severijns, C., Briceag, S., Bintanja, R., Sterl, A., . . .
van der Wiel, K. (2011). Ec-earth v2.2: Description and validation of a new
seamless earth system prediction model.Climate Dynamics, 39 , 1-19.
doi: 10.1007/s00382-011-1228-5

Held, I. M., Guo, H., Adcroft, A., Dunne, J. P., Horowitz, L. W., Krasting, J., . . .
Zadeh, N. (2019). Structure and performance of GFDL’s CM4.0 climate
model. Journal of Advances in Modeling Earth Systems, 11 (11), 3691-3727.
doi: 10.1029/2019MS001829

Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater,
J., . . . Thépaut, J.-N. (2020). The ERA5 global reanalysis. Quarterly
Journal of the Royal Meteorological Society, 146 (730), 1999-2049.
doi:https://doi.org/10.1002/qj.3803

Jones, P. D., Hulme, M., & Briffa, K. R. (1993). A comparison of Lamb circulation
types with an objective classification scheme. International Journal of Clima-
tology, 13 (6), 655-663. doi: https://doi.org/10.1002/joc.3370130606

Kelley, M., Schmidt, G. A., Nazarenko, L. S., Bauer, S. E., Ruedy, R., Russell,
G. L., . . . Yao, M.-S. (2020). GISS-E2.1: Configurations and climatology.
Journal of Advances in Modeling Earth Systems, 12 (8), e2019MS002025. doi:
10.1029/2019MS002025

Kobayashi, S., Ota, Y., Harada, Y., Ebita, A., Moriya, M., Onoda, H., . . . Taka-
hashi, K. (2015). The JRA-55 Reanalysis: General specifications and basic
characteristics. Journal of the Meteorological Society of Japan. Ser. II , 93 (1),
5-48. doi: 10.2151/jmsj.2015-001

Lamb, H. (1972). British Isles weather types and a register of daily sequence of cir-
culation patterns, 1861-1971. Geophysical Memoir , 116 , 85pp. (HMSO)

Lee, J., Kim, J., Sun, M.-A., Kim, B.-H., Moon, H., Sung, H. M., . . . Byun, Y.-
H. (2019). Evaluation of the Korea Meteorological Administration Ad-
vanced Community Earth-System model (K-ACE). Asia-Pacific Journal of Atmospheric Sciences, 56 , 381–395.
doi: https://doi.org/10.1007/

Lee, W.-L., Wang, Y.-C., Shiu, C.-J., Tsai, I., Tu, C.-Y., Lan, Y.-Y., . . . Hsu, H.-H.
(2020). Taiwan Earth System Model version 1: description and evaluation
of mean state. Geoscientific Model Development, 13 (9), 3887–3904. doi:
10.5194/gmd-13-3887-2020

Li, L., Lin, P., Yu, Y.-Q., Zhou, T., Liu, L., Liu, J., . . . Qiao, F.-L.
(2013). The Flexible Global Ocean-Atmosphere-Land System Model, Grid-point ver-
sion 2: FGOALS-g2. Advances in Atmospheric Sciences, 30 , 543-560.doi:
10.1007/s00376-012-2140-6

Li, L., Yu, Y., Tang, Y., Lin, P., Xie, J., Song, M., . . . Wei, J. (2020). The Flex-
ible Global Ocean-Atmosphere-Land System Model Grid-point version 3
(FGOALS-g3): Description and evaluation. Journal of Advances in Model-
ing Earth Systems, 12 (9), e2019MS002012. doi: https://doi.org/10.1029/
2019MS002012

Martin, T. H. D. T. G. M., Bellouin, N., Collins, W. J., Culverwell, I. D., Halloran,
P. R., Hardiman, S. C., . . . Wiltshire, A. (2011). The HadGEM2 family of Met
Office Unified Model climate configurations. Geoscientific Model Development,
4 (3), 723–757. doi: 10.5194/gmd-4-723-2011

Mauritsen, T., Bader, J., Becker, T., Behrens, J., Bittner, M., Brokopf, R., . . .
Roeckner, E. (2019). Developments in the MPI-M Earth System Model version
1.2 (MPI-ESM1.2) and its response to increasing CO2. Journal of Advances in
Modeling Earth Systems, 11 (4), 998-1038. doi: 10.1029/2018MS001400

Pak, G., Noh, Y., Lee, M.-I., Yeh, S.-W., Kim, D., Kim, S.-Y., . . . Kim, Y. H.
(2021). Korea Institute of Ocean Science and Technology Earth System Model
and its simulation characteristics. Ocean Science Journal , 56 , 18-45.
doi: 10.1007/s12601-021-00001-7

Park, S., Shin, J., Kim, S., Oh, E., & Kim, Y.
(2019). Global climate simulated by the Seoul National University Atmosphere Model version 0 with a unified
convection scheme (SAM0-UNICON). Journal of Climate, 32 (10), 2917-2949.
doi: 10.1175/JCLI-D-18-0796.1

Roberts, M., Baker, A., Blockley, E., Calvert, D., Coward, A., Hewitt, H., . . . Vi-
dale, P. (2019). Description of the resolution hierarchy of the global coupled
HadGEM3-GC3.1 model as used in CMIP6 HighResMIP experiments. Geosci-
entific Model Development Discussions, 1-47. doi: 10.5194/gmd-2019-148

Schmidt, G. A., Kelley, M., Nazarenko, L., Ruedy, R., Russell, G. L., Aleinov, I.,
. . . Zhang, J. (2014). Configuration and assessment of the GISS ModelE2
contributions to the CMIP5 archive. Journal of Advances in Modeling Earth
Systems, 6 (1), 141-184. doi: 10.1002/2013MS000265

Scoccimarro, E., Gualdi, S., Bellucci, A., Sanna, A., Giuseppe Fogli, P., Manzini, E.,
. . . Navarra, A. (2011). Effects of tropical cyclones on ocean heat transport
in a high-resolution coupled general circulation model.
Journal of Climate, 24 (16), 4368-4384. doi: 10.1175/2011JCLI4104.1

Seland, Ø., Bentsen, M., Seland Graff, L., Olivié, D., Toniazzo, T., Gjermundsen,
A., . . . Schulz, M. (2020). The Norwegian Earth System Model, NorESM2 –
evaluation of the CMIP6 DECK and historical simulations. Geoscientific Model
Development, 2020 , 1–68. doi: 10.5194/gmd-2019-378

Semmler, T., Danilov, S., Gierz, P., Goessling, H. F., Hegewald, J., Hinrichs, C.,
. . . Jung, T. (2020). Simulations for CMIP6 with the AWI Climate Model AWI-CM-1-1.
Journal of Advances in Modeling Earth Systems, 12 (9), e2019MS002009. doi: 10.1029/2019MS002009

Swapna, P., Koll, R., Aparna, K., Kulkarni, K., Ag, P., Ashok, K., . . . Goswami,
B. N. (2015). The IITM Earth System Model: Transformation of a seasonal
prediction model to a long term climate model. Bulletin of the American
Meteorological Society, 96 , 1351–1367. doi: 10.1175/BAMS-D-13-00276.1

Séférian, R., Nabat, P., Michou, M., Saint-Martin, D., Voldoire, A., Colin, J., . . .
Madec, G. (2019). Evaluation of CNRM Earth System Model, CNRM-ESM2-1: Role of Earth system processes in present-day and future climate. Journal of Advances in Modeling Earth Systems, 11 (12), 4182-4227.
doi: 10.1029/2019MS001791

Tamura, T., Ohshima, K. I., & Nihashi, S. (2008). Mapping of sea ice production for
antarctic coastal polynyas. Geophysical Research Letters, 35 (7). doi: https://
doi.org/10.1029/2007GL032903

Tatebe, H., Ogura, T., Nitta, T., Komuro, Y., Ogochi, K., Takemura, T., . . . Ki-
moto, M. (2019). Description and basic evaluation of simulated mean state,
internal variability, and climate sensitivity in MIROC6.
Geoscientific Model Development, 12 (7), 2727–2765. doi: 10.5194/gmd-12-2727-2019

Tegen, I., Neubauer, D., Ferrachat, S., Siegenthaler-Le Drian, C., Bey, I., Schutgens,
N., . . . Lohmann, U. (2019). The global aerosol–climate model ECHAM6.3–
HAM2.3 – part 1: Aerosol evaluation. Geoscientific Model Development, 12 (4),
1643–1677. doi: 10.5194/gmd-12-1643-2019

Voldoire, A., Saint-Martin, D., Sénési, S., Decharme, B., Alias, A., Chevallier, M.,
. . . Waldman, R. (2019). Evaluation of CMIP6 DECK experiments with
CNRM-CM6-1. Journal of Advances in Modeling Earth Systems, 11 (7), 2177-
2213. doi: 10.1029/2019MS001683

Voldoire, A., Sanchez-Gomez, E., Salas y Melia, D., Decharme, B., Cassou, C., Sen-
esi, S., . . . Chauvin, F. (2013). The CNRM-CM5.1 global climate model:
description and basic evaluation. Clim. Dyn., 40 (9-10), 2091-2121.
doi: 10.1007/s00382-011-1259-y

Volodin, E., Diansky, N., & Gusev, A. (2010). Simulating present-day climate
with the INMCM4.0 coupled model of the atmospheric and oceanic general
circulations. Izvestiya, Atmospheric and Oceanic Physics, 46 , 414-431. doi:
https://doi.org/10.1134/S000143381004002X

Volodin, E., Mortikov, E., Kostrykin, S., Galin, V., Lykossov, V., Gritsun, A.,
. . . Iakovlev, N. (2017). Simulation of the present-day climate with
the climate model INMCM5. Climate Dynamics, 49 , 3715–3734.
doi: https://doi.org/10.1007/s00382-017-3539-7

Watanabe, M., Suzuki, T., O’ishi, R., Komuro, Y., Watanabe, S., Emori, S., . . .
Kimoto, M. (2010). Improved climate simulation by MIROC5: Mean states,
variability, and climate sensitivity. Journal of Climate, 23 , 6312-6335. doi:
10.1175/2010JCLI3679.1

Watanabe, S., Hajima, T., Sudo, K., Nagashima, T., Takemura, T., Okajima, H., . . .
Kawamiya, M. (2011). MIROC-ESM 2010: model description and basic results
of CMIP5-20c3m experiments. Geoscientific Model Development, 4 , 845-872.
doi: 10.5194/gmd-4-845-2011

Wu, T., Lu, Y., Fang, Y., Xin, X., Li, L., Li, W., . . . Liu, X. (2019). The Beijing
Climate Center Climate System Model (BCC-CSM): the main progress from
CMIP5 to CMIP6. Geoscientific Model Development, 12 (4), 1573–1600. doi:
10.5194/gmd-12-1573-2019

Wu, T., Song, L., Li, W., Wang, Z., Zhang, H., Xin, X., . . . Zhou, M.
(2014). An overview of BCC Climate System Model development and application
for climate change studies. Acta Meteorologica Sinica, 28 , 34–56. doi:
10.1007/s13351-014-3041-7

Yukimoto, S., Kawai, H., Koshiro, T., Oshima, N., Yoshida, K., Urakawa, S., . . .
Ishii, M. (2019). The Meteorological Research Institute Earth System Model
version 2.0, MRI-ESM2.0: Description and basic evaluation of the physical
component.

Journal of the Meteorological Society of Japan. Ser. 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/ES19035