the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 16 Jul 2024
Distinctive dust weather intensities in North China resulted from two types of atmospheric circulation anomalies
Abstract. Dust weather in North China (NC) has worsened in recent years, posing adverse impacts on the environment, human health, and the economy. In 2021, the "3.15" super dust storm raised Beijing's PM10 (particulate matter with a diameter less than 10 μm) concentrations above 7000 μg m−3, while 2023 witnessed the highest spring dust weather frequency in nearly a decade. Although previous studies have proposed that synoptic systems such as the Mongolian cyclone and cold high can induce dust weather in NC, there has been less focus on the cold high. Furthermore, the differences in PM10 concentrations in NC caused by the two synoptic systems have not been quantified. This study demonstrates that the Mongolian cyclone was responsible for 62.4 % of the dust weather in NC, while the remaining 37.6 % was primarily caused by the cold high. The dust intensity induced by the Mongolian cyclone was stronger than that of the cold high, with average maximum PM10 concentrations of 3076 μg m−3 and 2391 μg m−3, respectively. The three-dimensional structure of atmospheric circulation anomalies and related dynamic mechanisms of the two types were concluded. A common predictor of the two dust weather types has also been identified. These findings contribute to enhancing the comprehension of dust weather in North China and offer valuable insights for both dust weather forecasting and climate prediction.
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2024-1923', Anonymous Referee #1, 29 Aug 2024
The study evaluated the intensity of dust weather from PM10 concentrations and identified the synoptic systems and related dynamic mechanisms that caused different intensities of dust weather in North China. In addition to the well-known Mongolian cyclone that had received much attention in recent years, the Mongolian cold high was also responsible for dust weather in North China. Considering both the Mongolian cyclone and the cold high for forecasting, a common predictor was proposed. The results of this study could provide references for the forecasting of dust weather and climate prediction. This paper is well written and organized. I recommend it to be published in ACP after several minor corrections.
Major comments:
- In Section 2.2, the identification method of the Mongolian cyclone was described based on its definition, but the description was not very specific. Could further details be provided?
- Section 5 focused on the common predictor of the MC type and the CH type. However, the improvement and advantage of this common predictor, compared to solely considering the Mongolian cyclone, are not clearly articulated in the text. It is recommended to provide further elaboration on this point to enhance clarity and understanding.
- In Section 6, the ability of the C3S model to reproduce I_ACA-CA was discussed, but only the ECMWF SEAS5.1 was considered. Why was only the predictive ability of one model considered? Is there a certain degree of randomness involved? It is recommended to also compare and evaluate the capabilities of other systems.
Specific comments:
- Lines 114-115: The sentence: “the main surface synoptic systems for the two types of Dust days were the Mongolian cyclone and cold high” is ambiguous. "According to the context of the text, it is proposed to be modified as: “the main surface synoptic systems for the two types of Dust days were the Mongolian cyclone and cold high respectively”.
- The abstract states that the Mongolian cyclone type accounts for 62.4%, with the remaining 37.6% being the cold high type. However, based on Fig. 1, it seems like both of the types together make up 62.4%. The percentages labeling in Fig. 1 are misleading. It is recommended to make corrections.
- Based on the content in the main text, the meteorological indices in Table 1 are calculated corresponding to the area with the most significant correlation coefficients with the daily maximum PM10 concentrations. It is recommended that, the corresponding regions where the indices are calculated should be clearly marked on the map to make the definition of the indices more explicit and clearer.
- The "L" and "H" in Fig. 7 are not explained in the caption, please add clarification.
- Line 318: The period after the subheading should be removed.
- Line 36 in Supplement: There is an error in the caption of Fig. S5: "zonal wind" should be "meridional wind".
Citation: https://doi.org/10.5194/egusphere-2024-1923-RC1 - AC1: 'Reply on RC1', Yin Zhicong, 14 Nov 2024
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RC2: 'Comment on egusphere-2024-1923', Anonymous Referee #2, 16 Sep 2024
Dust weather in North China has been studied using PM10 concentration observation and ERA5 data. Quantitative contribution of the Mongolian cyclone and the cold high to the dust days were given. A common predictor of the two dust weather types was also identified. The study will benefit the understanding the synoptic meteorological influence on dust weather in North China, but still some points need to be further clarified.
Major comments
- It should be identified that if there are only two dust weather types of the Mongolian cyclone and the cold high which can influence the dust in North China?
- It’s not so clear that how to get daily maximum PM10 concentration in North China from hourly observation data at the stations? If only maximum value in one station is considered, maybe the regional characteristics can not be represented due to local effect.
- In many previous studies, dust weather phenomenon and visibility observation were used to characterize the dust spatial-temporal distribution, which may lead different result with this study only using PM10 concentration. For example, April is the most frequent dust weather month in previous studies, but it’s May in this manuscript. It should be pointed out and discussed.
- There is strict definition of dust weathers in meteorological society with several grads of floating dust, blowing dust, sand and dust storm, severe sand and dust storm. Its well know that high PM10 concentration is a major result from dust weather, but the threshold value need to be investigated further to match with the meteorological definition of dust weather. Also, PM2.5 and PM10 ratio should considered to remove anthropogenic aerosol impact.
- How about the weather with the maximum PM10 concentration between 500 and 1000 μg/m3?
- The area of concern in this paper is limited at 34-42°N, 105-120°E, but the dust weather is a large-scale process that has an important impact on the entire northern region of China, and the two types of atmospheric circulation such as cold high and Mongolia cyclone will also affect Inner Mongolia and Northeast China. The introduction should also be supplemented by a statement of the rationale for the selection of the region, how it differs from other work, and the geographical importance of the selected area of analysis.
Specific comments
- In the Data and method section, it is recommended to add a description of the study area and the number of PM10 stations used, as well as a distribution map.
- From table 2, it can be seen that the correlation between I_SAT and I_Gust10 and PM10 concentration is significantly higher than that of I_ACA-CA. There is no explanation in the text.
- The lines of Figure 6 are light and similar in color, and there is no illustration of the lines in the figure.
Citation: https://doi.org/10.5194/egusphere-2024-1923-RC2 - AC2: 'Reply on RC2', Yin Zhicong, 14 Nov 2024
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RC3: 'Comment on egusphere-2024-1923', Anonymous Referee #3, 16 Sep 2024
Line 11，line 304, what’s "3.15" super dust storm? -> should likely be: a super dust storm occurred in 15 March 2021 (hereafter “3.15” dust for short) ? I would not to use such kind of strange abbreviate.
Introduction, mentioned some numbers of PM concentration, to avoid misleading you would better to clearly indicate how these numbers obtained, such as of the maximum concentration among station observation or as of the peak value in center of the system, or as of the means averaging over a specific region in north China or other region of interest.
Fig. 1b, is it more reasonable to show composite of cyclones and cold highs separately? Because the Mongolian cyclones and cold highs are not counterparts but independent in physics.
Section 4, line 143-- , why talk anomalies in circulation relevant to synoptic cyclone and cold high? For example, readers may doubt the reality and reasonablity of the system if you talk typhoon in anomalous SLP fields. It seems better to show composites for original circulation field together with the anomalies, anyway, to avoid the possible confusing between the real synoptic system and the patterns exiting only in anomalous fields.
Section 4, need to carefully clarify and refine. Synoptic processes and climate processes are combined/mixed. Case composites, as I see, are essentially synoptic configuration for multi-variables/fields, and can hardly to tell which is the cause and which is the effect.
Dust are uplifted locally or transported into the region? Omega alone seems cannot explain why there are high PM concentration in both Mongolian cyclone and cold high cases, and the anomalous omega are also of very large scale extending toward the far west arid lands beyond the region of NC. Or simply caused by the horizontal wind speed at surface? Anyway, need to clarify the logics and consistence.
Fig.2, Z500 and U200, I would like to suggest authors to change legend, say, Z500 shown in contour lines, so helpful to demonstrate mid-troposphere trough and ridge, and helpful to explain near surface cyclone before the trough/behind the ridge.
Section 5, all predictors are simultaneous fitting variables identified in composite analysis. Readers may find of interest if you demonstrate how the cyclone and cold highs generates/develops/moves/strengthens and construct a set of predictor and predicting the dust in advance accordingly.
Citation: https://doi.org/10.5194/egusphere-2024-1923-RC3 - AC3: 'Reply on RC3', Yin Zhicong, 14 Nov 2024
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2024-1923', Anonymous Referee #1, 29 Aug 2024
The study evaluated the intensity of dust weather from PM10 concentrations and identified the synoptic systems and related dynamic mechanisms that caused different intensities of dust weather in North China. In addition to the well-known Mongolian cyclone that had received much attention in recent years, the Mongolian cold high was also responsible for dust weather in North China. Considering both the Mongolian cyclone and the cold high for forecasting, a common predictor was proposed. The results of this study could provide references for the forecasting of dust weather and climate prediction. This paper is well written and organized. I recommend it to be published in ACP after several minor corrections.
Major comments:
- In Section 2.2, the identification method of the Mongolian cyclone was described based on its definition, but the description was not very specific. Could further details be provided?
- Section 5 focused on the common predictor of the MC type and the CH type. However, the improvement and advantage of this common predictor, compared to solely considering the Mongolian cyclone, are not clearly articulated in the text. It is recommended to provide further elaboration on this point to enhance clarity and understanding.
- In Section 6, the ability of the C3S model to reproduce I_ACA-CA was discussed, but only the ECMWF SEAS5.1 was considered. Why was only the predictive ability of one model considered? Is there a certain degree of randomness involved? It is recommended to also compare and evaluate the capabilities of other systems.
Specific comments:
- Lines 114-115: The sentence: “the main surface synoptic systems for the two types of Dust days were the Mongolian cyclone and cold high” is ambiguous. "According to the context of the text, it is proposed to be modified as: “the main surface synoptic systems for the two types of Dust days were the Mongolian cyclone and cold high respectively”.
- The abstract states that the Mongolian cyclone type accounts for 62.4%, with the remaining 37.6% being the cold high type. However, based on Fig. 1, it seems like both of the types together make up 62.4%. The percentages labeling in Fig. 1 are misleading. It is recommended to make corrections.
- Based on the content in the main text, the meteorological indices in Table 1 are calculated corresponding to the area with the most significant correlation coefficients with the daily maximum PM10 concentrations. It is recommended that, the corresponding regions where the indices are calculated should be clearly marked on the map to make the definition of the indices more explicit and clearer.
- The "L" and "H" in Fig. 7 are not explained in the caption, please add clarification.
- Line 318: The period after the subheading should be removed.
- Line 36 in Supplement: There is an error in the caption of Fig. S5: "zonal wind" should be "meridional wind".
Citation: https://doi.org/10.5194/egusphere-2024-1923-RC1 - AC1: 'Reply on RC1', Yin Zhicong, 14 Nov 2024
-
RC2: 'Comment on egusphere-2024-1923', Anonymous Referee #2, 16 Sep 2024
Dust weather in North China has been studied using PM10 concentration observation and ERA5 data. Quantitative contribution of the Mongolian cyclone and the cold high to the dust days were given. A common predictor of the two dust weather types was also identified. The study will benefit the understanding the synoptic meteorological influence on dust weather in North China, but still some points need to be further clarified.
Major comments
- It should be identified that if there are only two dust weather types of the Mongolian cyclone and the cold high which can influence the dust in North China?
- It’s not so clear that how to get daily maximum PM10 concentration in North China from hourly observation data at the stations? If only maximum value in one station is considered, maybe the regional characteristics can not be represented due to local effect.
- In many previous studies, dust weather phenomenon and visibility observation were used to characterize the dust spatial-temporal distribution, which may lead different result with this study only using PM10 concentration. For example, April is the most frequent dust weather month in previous studies, but it’s May in this manuscript. It should be pointed out and discussed.
- There is strict definition of dust weathers in meteorological society with several grads of floating dust, blowing dust, sand and dust storm, severe sand and dust storm. Its well know that high PM10 concentration is a major result from dust weather, but the threshold value need to be investigated further to match with the meteorological definition of dust weather. Also, PM2.5 and PM10 ratio should considered to remove anthropogenic aerosol impact.
- How about the weather with the maximum PM10 concentration between 500 and 1000 μg/m3?
- The area of concern in this paper is limited at 34-42°N, 105-120°E, but the dust weather is a large-scale process that has an important impact on the entire northern region of China, and the two types of atmospheric circulation such as cold high and Mongolia cyclone will also affect Inner Mongolia and Northeast China. The introduction should also be supplemented by a statement of the rationale for the selection of the region, how it differs from other work, and the geographical importance of the selected area of analysis.
Specific comments
- In the Data and method section, it is recommended to add a description of the study area and the number of PM10 stations used, as well as a distribution map.
- From table 2, it can be seen that the correlation between I_SAT and I_Gust10 and PM10 concentration is significantly higher than that of I_ACA-CA. There is no explanation in the text.
- The lines of Figure 6 are light and similar in color, and there is no illustration of the lines in the figure.
Citation: https://doi.org/10.5194/egusphere-2024-1923-RC2 - AC2: 'Reply on RC2', Yin Zhicong, 14 Nov 2024
-
RC3: 'Comment on egusphere-2024-1923', Anonymous Referee #3, 16 Sep 2024
Line 11，line 304, what’s "3.15" super dust storm? -> should likely be: a super dust storm occurred in 15 March 2021 (hereafter “3.15” dust for short) ? I would not to use such kind of strange abbreviate.
Introduction, mentioned some numbers of PM concentration, to avoid misleading you would better to clearly indicate how these numbers obtained, such as of the maximum concentration among station observation or as of the peak value in center of the system, or as of the means averaging over a specific region in north China or other region of interest.
Fig. 1b, is it more reasonable to show composite of cyclones and cold highs separately? Because the Mongolian cyclones and cold highs are not counterparts but independent in physics.
Section 4, line 143-- , why talk anomalies in circulation relevant to synoptic cyclone and cold high? For example, readers may doubt the reality and reasonablity of the system if you talk typhoon in anomalous SLP fields. It seems better to show composites for original circulation field together with the anomalies, anyway, to avoid the possible confusing between the real synoptic system and the patterns exiting only in anomalous fields.
Section 4, need to carefully clarify and refine. Synoptic processes and climate processes are combined/mixed. Case composites, as I see, are essentially synoptic configuration for multi-variables/fields, and can hardly to tell which is the cause and which is the effect.
Dust are uplifted locally or transported into the region? Omega alone seems cannot explain why there are high PM concentration in both Mongolian cyclone and cold high cases, and the anomalous omega are also of very large scale extending toward the far west arid lands beyond the region of NC. Or simply caused by the horizontal wind speed at surface? Anyway, need to clarify the logics and consistence.
Fig.2, Z500 and U200, I would like to suggest authors to change legend, say, Z500 shown in contour lines, so helpful to demonstrate mid-troposphere trough and ridge, and helpful to explain near surface cyclone before the trough/behind the ridge.
Section 5, all predictors are simultaneous fitting variables identified in composite analysis. Readers may find of interest if you demonstrate how the cyclone and cold highs generates/develops/moves/strengthens and construct a set of predictor and predicting the dust in advance accordingly.
Citation: https://doi.org/10.5194/egusphere-2024-1923-RC3 - AC3: 'Reply on RC3', Yin Zhicong, 14 Nov 2024
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Qianyi Huo
Zhicong Yin
Xiaoqing Ma
Huijun Wang
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(1472 KB) - Metadata XML
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Supplement
(2355 KB) - BibTeX
- EndNote
- Final revised paper