the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 07 Aug 2024
IITM High-Resolution Global Forecast Model Version 1: An attempt to resolve monsoon prediction deadlock
Abstract. The prediction of Indian monsoon rainfall variability affecting a country with a population of billions remained one of the major challenges of the numerical weather prediction community. While in recent years, there has been a significant improvement in predicting the synoptic scale transients associated with the monsoon circulation, the intricacies of rainfall variability remained a challenge. Here, an attempt is made to develop a global model using a dynamic core of a cubic octahedral grid that provides a higher resolution of 6.5 km over the global tropics. This high-resolution model has been developed to resolve the monsoon convection. Reforecasts with the IITM High-resolution Global Forecast Model (HGFM) have been run daily from June through September 2022. The HGFM model has a wave number truncation of 1534 in the cubic octahedral grid. The monsoon events have been predicted with a ten-day lead time. The HGFM model is compared to the operational GFS T1534. While the HGFM provides skills comparable to the GFS, it shows better skills for higher precipitation thresholds. This model is currently being run in experimental mode and will be made operational.
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RC1: 'Comment on gmd-2024-89', Anonymous Referee #1, 02 Nov 2024
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Review of “IITM High-Resolution Global Forecast Model Version 1: An attempt
to resolve monsoon prediction deadlock” by Krishna et al. submitted to GMD
Overview:
The authors introduced a new model that can significantly improve the prediction of monsoon, which is key to local agriculture, economy, and disaster preparedness. The prediction ability of this new model is encouraging. I think the manuscript is clearly written although some loose ends need to be addressed. Specifically, I found that the overall quality of the figures varies a lot. High-quality figures are important to convey key results. I think a major revision is needed to address this. Then it could be published at GMD. Please see my detailed comments below.
- Figure 1c, the legend needs to be fixed (solid lines vs. dash lines)
- Also figure 1c, it is inconvenient to compare the ratio of dynamics time to total time. Perhaps only using one single y-axis?
- Why only considering 200 hPa kinetic energy? How about other vertical levels?
- Figure 3: It would be better to add the model names to each panel. I am confused by lines 188-189. To me, HGFM and GFS look more similar to each other while ERA5 look quite different, especially over the gulf of Mexico and northwestern Pacific. I suggesting plotting the difference for better comparisons among the three outputs.
- Figure 4 and line 194 to 203: there are some discussions about the biases over the tropical ocean. I am wondering if there are any specific reasons why both models overestimate the precipitation over the tropical eastern Pacific? Is it due to the shallow convection scheme?
- Figure 5&6: is it cm/day or mm/day?
- Figure 7: improve the quality of this figure (mixed font sizes, panel sizes, etc.).
- Why convective precipitation is reduced from GFS to HGFM? Due to Tuning?
- What is the point of figure 13?
Citation: https://doi.org/10.5194/gmd-2024-89-RC1
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