A Multi-Component Synthesis Scoring Method of Gridded Fusion Products for Precipitation Quality Control

Round 1

Reviewer 1 Report

The paper "A Multi-Component Synthesis Scoring Method of Gridded Fusion Products For  Precitipation Quality Control", written by Xiaoyan Liu et al.

 

In their work, the authors deal with the typical control methods of precipitation, which is based on observations from automatic ground stations. However, typical precipitation quality control methods have certain limitations. The authors propose to expand the typical control methods  of precipitation with new components, e.g. air pressure, cloud covers, etc., resulting in a new method - gridded fusion products. They also present a new evaluation method - the scoring method. The result is higher accuracy in determining the objective quality control of surface precipitation in real time, thus changing the subjective method to an objective one.     The topic of the current post is very relevant due to the ongoing changes in the climate (global warming) and the adaptation of civilization to this change. Monitoring precipitation, or in other words water consumption, is one of the basic needs of life, which with the increasing number of inhabitants on Earth causes significant problems, and therefore precipitation must be paid due attention. the lack of precipitation will cause deep socio-economic problems for human society in the future. Results of the study of the amount of precipitation is extremely important for policy makers.   The paper is written well and clearly, pictures are OK, but description on the X- and Y-coordinates should be improved (see remarks). I recommend to publish it.   See also another remarks.

Remarks:

1/  p. 2, L. 62:  QC - quality control ? If  yes, abbreviation is missed in the earlier text.

2/ p. 3- 4, Figure 1. Seems me, short answers (see below) should be given in the text for people, who are not fully oriented in the issue of the article

·         The coordinates of the images show the area of ​​Hainan Province ?

·         What means background color (green or brown)?

·         Letters on X-, Y- scales should be written with a bigger size

·         What mean the brown squares area with a black dot?

·          This square is missing for Fig. 1a, 1b, 1f

3/ p. 5, Figure 2: Figure 2 does not need a square area, marked brown, as in Fig. 1?  Capital letters are needed for X- and Y- coordinates, the same for Figure 4.

4/ p. 8, Figure 5:  There is missing scale for total precipitation times. Should be shown on the right side of the graph.

5/ p. 9, L. 254 - 263: These several sentences are not clear for me? How do you know that Hainan data (259-260) are wrong (in Error), when reference is missing?

6/ p.12, L. 333, "cloud" - with capitol letter "Cloud".

10/08/12

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

The authors consider some weather components such as air pressure, visibility, relative humidity, wind speed, temperature difference, and clouds covers and determine their correlation with the precipitation, and find out which of the aforementioned weather components pass the significance test.

 

Moreover, the authors propose gridded fusion products to fill in the voids among weather components with a scoring method that evaluates them.  They claim to achieve an overall accuracy of greater than 75% for objective quality control of real-time surface precipitation.

 

1. Academic writing requires correct use of grammar, spelling, punctuation marks, capitalization, proper spacing, and, clear and unambiguous sentence structure. The paper has the aforementioned errors which clearly demonstrate carelessness and negligence by the authors. There is also a lack of coherence and unity in the various paragraphs that make the text somewhat ambiguous. Why do the authors not proofread it to avoid these language errors?

 

2. The paper is comprised of various contradictions means that the authors mention one statement above and then, contradict themselves below by saying or presenting a contrastive statement or numerical figure. For example, it is mentioned above that most of AWS has passed the significance test for the temperature difference while, the table shows just a 22.3% value, which is small as compared to other weather components. Why do the authors not eliminate these kinds of contradictory statements from the paper?

 

3. The paper consists of symbol mistakes in various instances. For example, they use Tem_d, Tem d, and tem_d for the temperature difference. Now, why do they not use one symbol consistently?

 

4. There are certain terms that are pretty defined and standardized in the mathematics literature. They should not misuse and loosely applied in rigorous academic discussions. Now, the authors have committed this mistake on multiple occasions. For example, they use temperature differential instead of temperature difference. These two mathematical concepts are very different and mean two distinct ideas. Why do they not pay proper attention to these mathematical intricacies?

 

5. It is important that all the formulas are correctively mentioned in the paper but, the authors are using one formula while mentioning the other one. For example, they use formula 7 for determining the score but, they reference/quote Formula 4. Why do they not proofread it to eliminate these errors?

 

6. It is a pretty common practice to define and introduce a term before using it. It is very much important in the case of abbreviations. The authors do not follow this standard practice. For example, they use one term “TS” without ever introducing and defining it. Why do they not obey this standard practice?

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 3 Report

The manuscript concerns quality control of precipitation data registered by ground automatic weather stations. The authors indicate the restrictions of typical quality methods when applying to precipitation. They propose an indirect one using other weather variables (air pressure, visibility, relative humidity, wind speed, temperature difference, and the sum of cloud cover of 125-875 hPa) associated with the precipitation process. The paper generally accomplishes its objective and introduces a method to validate precipitation data registered by AWS, mainly located in remote locations. Section 2.3 is the one I am not sure is necessary. What is its overall contribution to the manuscript? Please check it or write it. 

Comments

Line 10. Rewrite to “However, the typical quality control methods have”

Lines 10-11. Replace sentence by “However, the typical quality control methods apply to rainfall present restrictions because of its discontinuity in time and space.”

Lines 12 and 13. Rephrase for clarity, suggestion “The multi-component comprehensive consistency approach is a subjective quality control method using changes in other weather components associated with the precipitation process.”

Lines 13-15. Rewrite, my suggestion is “The present study determined the reference weather components for precipitation by calculating the correlation coefficient between weather components and precipitation and the proportions that passed the significance tests.”

Line 18. Replace “ a variety” by “various”

Line 19. Add “an” after “into”

Line 22. Delete “an”

Line 26. Unclear, It could be “Weather forecasting and services are getting more precisely due to meteorological advancements, and data quality control requirements are rising.”

Line 28. Automatic instead of Automated, add “the” after “on”

Lines 30 and 31. Replace “the majority” by “most”

Line 40. Replaced by “to cover the AWS completely.”

Line 44. Add “In addition,” before Real-time

Line 49. Add “and” before “is”

Lines 49-53. Rephrase the sentence for better clarity

Lines 62-64. No clear sentence, please rephrase it.

Line 76. Better “weather-detection”

Line 79. Write “components” instead of “component”

Line 89. Better if you use “article” instead of “manuscript”. Replace “go over” by “review”

Line 93. Add “Finally,” before “a conclusion”

Line 100. Replace “The formula” by “Equation”, here and everywhere in the text.

Line 113. Add “the” before “wind”

Line 115. Put a comma after AWS

Line 125. What does it mean artificial visibility?

Line 116. Put a comma after test, and replace “were” by “was”. Replace “strong” by “large”

Line 134. I apologize by my ignorance, but, Are the correlation too low despite that they passed the statistical test?

Line 143. Change “evaluate further”

Line 148. Change to “high humidity levels, and high salt levels.”

Lines 153-156. Rephrase. Suggestion “Furthermore, more than half of the stations (outside of the first four categories) that failed the significance test for temperature differences were those located nearby water bodies. Their moderating effect on temperature may have diminished the magnitude of the temperature response to precipitation processes.”

Line 162. Change to “minimum hourly”

Line 164. Add “However” before upon.

Line 166. Components instead of “component”

Line 167. Monthly correlations, I have my doubts, I understand of correlating hourly “other weather variables” with precipitation in order to find a quality control method, but how and why do you jump from hourly to monthly analysis? What is the purpose of this? Do you consider that precipitation is an accumulative variable? So, in line 169, “monthly average correlation what does really mean?

Line 171. Change to “to investigate further”

Line 177. Use “So why” instead of “Why”

Line 178. Replace by “from”

Line 194. Replace by “that occurs”

Line 195. Replace by “is”

Line 204. Add an “a” before “strong”

Line 215. Figure 3. It seems that the correlation ecoefficiencies are too low.

Line 240. What do you mean with “manual horizontal visibility?

Line 257. Put a dot after data. Rephrase to “Its overall quality is close to the leading international standard.”

Line 261. Replace by “proportions”

Line 265. Once again. Correlation seems to be low. I would expect larger correlations because you need clouds to have precipitation. (like figure 7)

Lines 268-270. Rephrase. “Figure 7 provides an additional analysis of the percentages of cloud coverage stations that match surface precipitation at each level during the sub-precipitation timeframe.”

Line 275. Replace by “high-level”.

Line 280. Add “the” before “`parametric”

Lines 282-285. No clear. Please rephrase. Suggestion “A score of 1 is given if a weather component exhibits the corresponding characteristics of the precipitation process at the time of suspected precipitation and 0 points for exhibiting opposing characteristics. 0.5 points were given for exhibiting characteristics relative to the previous time and 0.5 points for exhibiting characteristics close to the later time), 0.5 points for not exhibiting the relevant characteristics.”

Line 289. Ad “of” before 95

Line 291. Change to “The daily behavior from 14:00 pm to 7:00 am local time is generally”

Line 292. Add “the” before precipitation

Line 293-295. Rephrase. Suggestion “To avoid confusion, only when the temperature (relative humidity) at the precipitation time is an extreme value compared with values of the time before and after is considered a characteristic of the precipitation process.”

Line 303. Better “One hundred sixty-eight”

Lines 308-313. Rephrase. Suggestion “The ideal QC solution is to have the highest possible hit rate and the lowest possible false alarm rate and miss rate. However, if the hit rate is too low, the QC method cannot effectively identify false precipitation. On the other hand, if the false alarm rate is too high, it detects too much false alarm precipitation and requires manual QC to screen it, which would consume human resources. If the miss rate is too high, it misses too much false precipitation for good QC to be effective.”

Lines 315-326. Rephrase. Suggestion “The regional-level AWS M0307 is an AWS where there is only precipitation observation at the station and cannot be quality controlled using the conventional multi-component synthesis method. Hourly rainfall at the station at 10:00 (Beijing time) on 29 May 2021 was 9.6 mm and was judged as suspicious by MDOS. Therefore, we introduced the temperature and relative humidity products of HRCLDAS, the visibility products of CLDAS, and the cloud cover products of 3Dcloud as the reference weather components of the precipitation process. During the precipitation period, the temperature increased, relative humidity decreased, and visibility increased (Figure 8). The cloud cover time-barometric profile of the AWS shows no clouds above the station during precipitation times (Figure 9). So by introducing gridded fusion products, we can use the multi-component synthesis method to conclude that this precipitation is wrong.”

Line 327. Replace by “we used the scoring method to calculate the precipitation score”

Line 338. Replace by “being”

Lines 353-358. NO cleaer.

Line 357. Add “the” before previous.

Line 358. Add “the” before difference

Line 359. Replace by “air temperature variation”

Line 360. Add “from” before diurnal

Lines 375-386. Rephrase. Suggestion “We expected this scoring method to be very effective because it was based on the response characteristics of various weather components to the precipitation process. Its principle is universal and simple. Moreover, the artificial subjective analysis method with multiple weather components at AWS has been used in daily work for many years and has a deep foundation. However, we found that the correlation between some weather components and the precipitation process is not significant, such as the temperature of the water-adjacent AWS such as the 2-minute average wind, so it is unreasonable to use the changes of these weather components to quality control the precipitation. Additionally, it has been discovered that this approach is significantly impacted by the diurnal variation of weather components, particularly temperature, humidity, and visibility. Moreover, traditional techniques like the difference method are ineffective in removing the diurnal variation.”

Line 387. Replace “get rid of” by “to eliminate”

Line 392. Add “In addition,” before by converting…

Lines 395-396. Rephrase. “Our ultimate objective is to efficiently and accurately automate real-time AWS precipitation data quality control.”

Lines 399-403. Rephrase. No clear.

 

 

Comments for author File: Comments.pdf

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

The Authors have well addressed all the concerns raised by the reviewer. The reviewer has no more concerns.