Oscar Paul
New member
I am currently working with the WRF model and have encountered an intriguing observation regarding the spatial-temporal patterns in the model outputs when using adaptive time step settings.
In my simulations, I have noticed significant differences in the spatial-temporal patterns between the outputs generated at 3-hourly intervals and those generated at 1-hourly intervals when employing adaptive timestep.
While I understand that adaptive time step allows for varying temporal resolutions to optimize computational efficiency and the 3 hourly plots is giving a reasonable spatial pattern in comparison to observations. When I switched to hourly intervals output for better understanding the localized and intensive patterns temporally using adaptive timestep, I am puzzled by the discrepancies in the patterns. The namelist for the physics and dynamics section is kept same for both the cases.
The difference is observed at 9th hour in simulation run. I have attached the spatial pattern at 9 UTC for 3 hourly interval plots and hourly interval plots of accumulated precipitation. These differences are notable across various meteorological variables wind fields and cloud fraction.
My queries are as follows:
1. Mechanism Behind Spatio-Temporal Pattern Variation: What could be the underlying mechanism driving the observed differences in spatio-temporal patterns between 3-hourly and 1-hourly outputs with adaptive timestep? Are these differences primarily attributed to the adaptive timestep scheme itself or are there other factors at play?
2. Implications on Model Accuracy: How do these discrepancies impact the accuracy and reliability of the WRF model outputs? Are there any known biases or limitations associated with using adaptive timestep in capturing localized meteorological phenomena?
I would greatly appreciate any insights, experiences, or references that you can share regarding these queries. Additionally, if anyone has encountered similar observations or conducted related studies, I would be eager to hear about your findings and recommendations.
Thank you for your attention and assistance. I look forward to engaging in fruitful discussions and advancing our collective understanding of WRF modeling.
Best regards,
Oscar Paul
Research Scholar, IIT Madras
In my simulations, I have noticed significant differences in the spatial-temporal patterns between the outputs generated at 3-hourly intervals and those generated at 1-hourly intervals when employing adaptive timestep.
While I understand that adaptive time step allows for varying temporal resolutions to optimize computational efficiency and the 3 hourly plots is giving a reasonable spatial pattern in comparison to observations. When I switched to hourly intervals output for better understanding the localized and intensive patterns temporally using adaptive timestep, I am puzzled by the discrepancies in the patterns. The namelist for the physics and dynamics section is kept same for both the cases.
The difference is observed at 9th hour in simulation run. I have attached the spatial pattern at 9 UTC for 3 hourly interval plots and hourly interval plots of accumulated precipitation. These differences are notable across various meteorological variables wind fields and cloud fraction.
My queries are as follows:
1. Mechanism Behind Spatio-Temporal Pattern Variation: What could be the underlying mechanism driving the observed differences in spatio-temporal patterns between 3-hourly and 1-hourly outputs with adaptive timestep? Are these differences primarily attributed to the adaptive timestep scheme itself or are there other factors at play?
2. Implications on Model Accuracy: How do these discrepancies impact the accuracy and reliability of the WRF model outputs? Are there any known biases or limitations associated with using adaptive timestep in capturing localized meteorological phenomena?
I would greatly appreciate any insights, experiences, or references that you can share regarding these queries. Additionally, if anyone has encountered similar observations or conducted related studies, I would be eager to hear about your findings and recommendations.
Thank you for your attention and assistance. I look forward to engaging in fruitful discussions and advancing our collective understanding of WRF modeling.
Best regards,
Oscar Paul
Research Scholar, IIT Madras
