RRA WRF simulations of the mid-Pliocene and present-day conditions over High Mountain Asia

doi:10.26050/WDCC/RRA_WRF_simulations

Wang, Xun et al.

ExperimentDOI
Summary
The data was produced employing the Advanced Research Weather Research and Forecasting model (WRF) version 4.1.2 (Skamarock et al., 2019) for the dynamical downscaling of GCM data. WRF is a fully compressible non-hydrostatic atmospheric simulation system. Two sensitivity simulations were conducted using 15-year time slices for the present day and the mid-Pliocene simulated by ECHAM5 as initial and boundary conditions (Mutz et al., 2018; Botsyun et al., 2020). Except for the atmospheric forcing data, other parameters were the same in both simulations.

The model domain has a grid spacing of 30 km. In the vertical direction, 28 terrain-following eta-levels were used. The model time steps are 120 seconds with a 6 hourly data output and are aggregated to daily values in post processing. The boundary conditions were updated every 6 h. The daily re-initialization strategy from Maussion et al. (2011) and Maussion et al. (2014) were employed: each simulation starts at 12 UTC and contains 36 h, with the first 12 h as the spin-up time. This strategy kept the large-scale circulation patterns simulated by WRF closely constrained by the forcing data, while concurrently allowing WRF to develop the mesoscale atmospheric features. Physical parameterization schemes were consistent with the ones used for high-resolution dynamical downscaling in High Mountain Asia in Wang et al. (2021). The data format follows the guidelines of the [UC]² Data Standard (http://www.uc2-program.org/uc2_data_standard.pdf).
Project
RRA (Regionally Refined Analyses)
Contact
Dr. Marco Otto (
 marco.otto@nulltu-berlin.de
0000-0003-4464-2673)
Spatial Coverage
Longitude 23.63 to 142.37 Latitude -.8 to 60.11
Longitude 23.63 to 142.37 Latitude -.8 to 60.11
Temporal Coverage
2000-01-01 to 2014-12-31 (calendrical)
1903-01-01 to 1917-12-31 (calendrical, arbitrary numbered years)
Use constraints
Creative Commons Attribution 4.0 International (CC BY 4.0) (https://creativecommons.org/licenses/by/4.0/)
Data Catalog
World Data Center for Climate
Size
109.24 GiB (117297066965 Byte)
Format
NetCDF
Status
completely archived
Creation Date
Future Review Date
2031-07-01
Cite as
Wang, Xun; Schmidt, Benjamin; Scherer, Dieter; Otto, Marco (2021). WRF dynamical downscaling of present-day and mid-Pliocene atmospheric conditions over High Mountain Asia. World Data Center for Climate (WDCC) at DKRZ. https://doi.org/10.26050/WDCC/RRA_WRF_simulations

BibTeX RIS
Description
Approved by Schmidt, B. and Wang, X. (June 2021).
Find the model at doi:10.5065/D6MK6B4K
The data is described in this publication by Wang et al., 2021 (https://doi.org/10.1029/2020JD033965)
Product contains derived data.
Level 3b - Gridded Geophysical Variable - Basic Quality Control
Description
The product is missing values on the first and last day of each time slice, but is complete in spatial and parameter terms.
Description
Summary:
Findable: 6 of 7 level;
Accessible: 2 of 3 level;
Interoperable: 3 of 4 level;
Reusable: 5 of 10 level
Method
F-UJI online v2.2.1 automated
Method Description
Checks performed by WDCC. Metrics documentation: https://doi.org/10.5281/zenodo.4081213 Metric Version: metrics_v0.5
Method Url
Result Date
2022-12-06
Result Date
2021-07-13
Description
1. Number of data sets is correct and > 0: passed;
2. Size of every data set is > 0: passed;
3. The data sets and corresponding metadata are accessible: passed;
4. The data sizes are controlled and correct: passed;
5. The temporal coverage description (metadata) is consistent to the data: passed;
6. The format is correct: passed;
7. Variable description and data are consistent: passed
Method
WDCC-TQA checklist
Method Description
Checks performed by WDCC. The list of TQA metrics are documented in the 'WDCC User Guide for Data Publication' Chapter 8.1.1
Method Url
Result Date
2021-07-13
Contact typePersonORCIDOrganization

Is referenced by

[1] DOI Wang, Xun; Schmidt, Benjamin; Otto, Marco; Ehlers, Todd A.; Mutz, Sebastian G.; Botsyun, Svetlana; Scherer, Dieter. (2021). Sensitivity of Water Balance in the Qaidam Basin to the Mid‐Pliocene Climate. doi:10.1029/2020jd033965

Is documented by

[1] DOI Botsyun, S.; Ehlers, T. A.; Mutz, S. G.; Methner, K.; Krsnik, E.; Mulch, A. (2020). Opportunities and Challenges for Paleoaltimetry in “Small” Orogens: Insights From the European Alps. doi:10.1029/2019gl086046
[2] DOI Maussion, F.; Scherer, D.; Finkelnburg, R.; Richters, J.; Yang, W.; Yao, T. (2011). WRF simulation of a precipitation event over the Tibetan Plateau, China – an assessment using remote sensing and ground observations. doi:10.5194/hess-15-1795-2011
[3] DOI Maussion, Fabien; Scherer, Dieter; Mölg, Thomas; Collier, Emily; Curio, Julia; Finkelnburg, Roman. (2014). Precipitation Seasonality and Variability over the Tibetan Plateau as Resolved by the High Asia Reanalysis*. doi:10.1175/jcli-d-13-00282.1
[4] DOI Wang, Xun; Tolksdorf, Vanessa; Otto, Marco; Scherer, Dieter. (2020). WRF‐based dynamical downscaling of ERA5 reanalysis data for High Mountain Asia: Towards a new version of the High Asia Refined analysis. doi:10.1002/joc.6686
[5] DOI Mutz, Sebastian G.; Ehlers, Todd A.; Werner, Martin; Lohmann, Gerrit; Stepanek, Christian; Li, Jingmin. (2018). Estimates of late Cenozoic climate change relevant to Earth surface processes in tectonically active orogens. doi:10.5194/esurf-6-271-2018

Is compiled by

[1] DOI Skamarock, W. C; Klemp, J. B.; Dudhia, J.; Gill, D. O.; Liu, Z., Berner, J.; Wang, W.; Powers, J. G.; Duda, M. G.; Barker, D. M.; Huang, X.-Y. (2019). A Description of the Advanced Research WRF Model Version 4. doi:10.5065/1dfh-6p97

Attached Dataset Groups ( 2 )

Search on group level...Details for selected entry
[Entry acronym: RRA_WRF_simulations] [Entry id: 3889342]