Effect of Flow-Dependent Unbalanced Background Error Variances on Tropical Cyclone Forecasting

Round 1

Reviewer 1 Report

The article makes a good impression, it carries out a research stage of a new method for processing initial signals in order to improve meteorological forecasts. According to the given list of references, articles by the same authors about the initial stages of this method were previously published, which characterizes the authors and their work positively. This study investigates the effect of flow-dependent unbalanced variance on predictions using the Data Assimilation Ensemble (EDA) method. The authors describe the process of formation the B – matrix that provides a weighting of priori states, information spreading and smoothing, balance relationship construction. The variables to be analyzed are vorticity, unbalanced divergence, unbalanced mass (temperature and surface pressure) and specific humidity. As presented equations indicate, vorticity plays a crucial role in describing the balance relationship among different variables. Observation data were used as humidity, temperature, pressure and wind, this is provided by radio sounding, surface or aircraft measurements and others. Most of the observations are unconventional data, such as AMSU-A (Advanced Microwave Sounding Unit-A), ATMS (advanced technology microwave sounder), GPSRO (global positioning system radio occultation), etc., which can detect radiations in the atmospheric column.  Three experiments were performed using the method developed by the authors, called Yin-He Global Spectral Model (YHGSM), which is a global NWP model .The dynamical core of the model satisfies the dry-mass conservation. Representation of background error variance considerably affects the forecast performance of data assimilation systems for forecasts. The three experiments (ensemble estimates for all control variables, vorticity only, and climatology estimates for all variables) are investigated to examine the effects. Results presented in three Tables and series of Figures. Presented work demonstrates that EDA system can improve the meteorological forecasting. The article can be published in journal in the presented form .

 

Author Response

It is a great honor to have your approval of our work, thank you very much for your careful reading and positive comments.

Reviewer 2 Report

1. The abstract needs to be revised and refer to the all results. The abstract should be comprehensive and complete.

2. In the introduction section, the importance and necessity of the subject should be mentioned.

3. Please added one paragraph about the direct aim this study at the end of the introduction section.

4. The literature should be definitely enriched with papers dealing with your subject

5. Please state the importance of this survey in the study area and also the importance of the study area.

6. Further discussion about the results.

7. The conclusion is weak and needs to be corrected and revised.

8. Re-checked the references list and citations.

9. The poor English language (syntax and grammar) is evident throughout the manuscript.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 3 Report

Review of the manuscript entitled “Effect of Flow-dependent Unbalanced Background Error Variances on Tropical Cyclone Forecasting” by Zhang et al.,

 

Comments

The manuscript discusses the importance of how an accurate representation of the background error variance can improve the forecast performance of variational data assimilation systems for tropical cyclones (TCs). An ensemble data assimilation (EDA) system is used to estimate the day-to-day variances, and three experiments (ensemble estimates for all control variables, vorticity only, and climatological estimates for all variables) are investigated to examine the effects.

 

 

The authors have addressed an important issue related to the forecasting of the Tropical Cyclone. The manuscript is well-written and easy to follow. I recommend the manuscript for its publication in present form.   

Comments for author File: Comments.pdf

Author Response

It is a great honor to have your approval of our work, thank you very much for your positive comments and the time spending on the manuscript.