While climate information from General Circulation Models (GCMs) are usually too coarse for climate impact modelers or decision makers from various disciplines (e.g., hydrology, agriculture), Regional Climate Models (RCMs) and Regional Earth System Models (RESMs) provide feasible solutions for downscaling GCM output to finer spatiotemporal scales. However, it is well known that the model performance depends largely on the choice of the physical parameterization schemes, but optimal configurations may vary from region to region. Besides land-surface processes, the most crucial processes to be parameterized in ESMs include radiation (RA), cumulus convection (CU), cloud microphysics (MP), and planetary boundary layer (PBL), partly with complex interactions. Before conducting long-term climate simulations, it is therefore indispensable to identify a suitable combination of physics parameterization schemes for these processes. Using the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis product ERA-Interim as lateral boundary conditions, we derived an ensemble of 16 physics parameterization runs for a larger domain in Northern sub-Saharan Africa (NSSA), northwards of the equator, using two different CU-, MP-, PBL-, and RA schemes, respectively, using the Weather Research and Forecasting (WRF) model (Version v3.9) for the period 2006-2010 in a resolution of 0.1 degree horizontal resolution.
Conclusions about suitable physical parameterization schemes may vary within the study area. We therefore want to stimulate the development of own performance evaluation studies for climate simulations or subsequent impact studies over specific (sub-)regions in NSSA. For this reason, selected climate surface variables of the physics ensemble (i.e. the 16 experiments from 2006-2010) are provided.
For more information about the setup of the experiments, please see:
Laux et al., 2021: A high-resolution regional climate model physics ensemble for Northern sub-Saharan Africa. Frontiers in Earth Science (under revision).
SQA - Scientific Quality Assurance 'approved by author'
Result Date
2021-08-05
Technical Quality Assurance (TQA)
TQA - Technical Quality Assurance 'approved by WDCC'
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
[1] DOISkamarock, William C.; Klemp, Joseph B.; Dudhia, Jimy; Gill, David O.; Barker, Dale; Duda, Michael G.; Huang, Xiang-yu; Wang, Wei; Powers, Jordan G. (2008). A Description of the Advanced Research WRF Version 3. doi:10.5065/D68S4MVH