Abnormal striated patterns were detected in the simulated meteorological fields from the Weather Research and Forecasting (WRF) regional modeling system over the San Francisco Bay Area with 1-km resolution. These spatial abnormalities appeared not only in the 2-dimensional fields, such as temperature at 2 meters, wind at 10 meters and planetary boundary layer (PBL) height, but also in 3-dimensional fields extended to around 1300 meter in the upper levels. Similar abnormal spatial patterns were also found in air pollutant concentrations simulated by the Community Multi-Scale Air Quality (CMAQ) model using these WRF meteorological inputs. We used WRF version 3.8. We were not clear what caused these striated abnormalities. So we tried the following sensitivity tests:
1. Set diff_opt=2 (previously diff_opt=1), coupled with km_opt=4
2. Adjusted diff_6th_factor
3. Set sf_sfclay_physics=99 (previously sf_sfclay_physics=1)
4. Replaced PX-ACM2 with Noah-YSU
The above tests which were made in WRF version 3.8 had little impacts on the abnormal spatial patterns. However, the WRF model results were improved significantly and abnormalities in the simulated meteorological fields were minimized when using updates to WRF version 4.0.1 with the same namelist options (please see the attachment) as those in version 3.8. The abnormalities in CMAQ simulated air pollution concentrations were also mitigated.
Would you offer us insights on what caused these abnormal patterns and what updates in WRF version 4.0.1 helped “removed” these abnormalities? We were quite impressed with the significant improvement on the WRF v4.0.1 model performance, and the following CMAQ results. But we are really puzzled with the why. Hope your expertise and experience can help us solve the puzzle! What we have found and learned from WRF can also benefit the CMAQ modeling work.
Attached, please find the namlist file from WRF version 4.0.1. The namelist file of version 3.8 is almost identical with this one, except that there’re no parameters of force_use_old_data and hybrid_opt.
The attached plots show the PBL and total PM2.5 from the run using version 3.8 (left) and the run using version 4.0.1 (right).
1. Set diff_opt=2 (previously diff_opt=1), coupled with km_opt=4
2. Adjusted diff_6th_factor
3. Set sf_sfclay_physics=99 (previously sf_sfclay_physics=1)
4. Replaced PX-ACM2 with Noah-YSU
The above tests which were made in WRF version 3.8 had little impacts on the abnormal spatial patterns. However, the WRF model results were improved significantly and abnormalities in the simulated meteorological fields were minimized when using updates to WRF version 4.0.1 with the same namelist options (please see the attachment) as those in version 3.8. The abnormalities in CMAQ simulated air pollution concentrations were also mitigated.
Would you offer us insights on what caused these abnormal patterns and what updates in WRF version 4.0.1 helped “removed” these abnormalities? We were quite impressed with the significant improvement on the WRF v4.0.1 model performance, and the following CMAQ results. But we are really puzzled with the why. Hope your expertise and experience can help us solve the puzzle! What we have found and learned from WRF can also benefit the CMAQ modeling work.
Attached, please find the namlist file from WRF version 4.0.1. The namelist file of version 3.8 is almost identical with this one, except that there’re no parameters of force_use_old_data and hybrid_opt.
The attached plots show the PBL and total PM2.5 from the run using version 3.8 (left) and the run using version 4.0.1 (right).