Impact of the Pacific–Japan teleconnection pattern on July sea fog over the northwestern Pacific: Interannual variations and global warming effect

Long, Jingchao; Zhang, Suping; Lu, Shanping; Han, Geng

doi:10.1007/s00376-015-5097-4

Cited by 9 publications

(8 citation statements)

References 26 publications

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“…Contrary to positive AO, the negative AO phase has the opposite effect, but variability is observed in corresponding wind patterns and foggy days (Liu et al 2020a ). Pacific-Japan teleconnections impact sea fog formation near the Kuril Islands; a case study performed by Long et al ( 2016 ) found sea fog occurrence in July is supported by Pacific—Japan (PJ) teleconnections, years with higher PJ index showed the formation of stable stratification of the atmosphere by strengthening of anticyclonic conditions, but the opposite was observed when PJ index was lower.…”

Section: Factors Influencing Fog Formationmentioning

confidence: 99%

A review on factors influencing fog formation, classification, forecasting, detection and impacts

Lakra

Avishek

2022

Rend. Fis. Acc. Lincei

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With the changing climate and environment, the nature of fog has also changed and because of its impact on humans and other systems, study of fog becomes essential. Hence, the study of its controlling factors such as the characteristics of condensation nuclei, microphysics, air–surface interaction, moisture, heat fluxes and synoptic conditions also become crucial, along with research in the field of prediction and detection. The current review expands for the period between 1976 to 2021, however, especially focused on the research articles published in the last two decades. It considers 250 research papers/research letters, 24 review papers, four book chapters/manuals, five news articles, 15 reports, six conference papers and five other online readings. This review is a compilation of the pros and cons of the techniques used to determine the factors influencing fog formation, its classification, tools and techniques available for its detection and forecast. Some recent advanced are also discussed in this review: role of soil properties on fogs, application of microwave communication links in the detection of fog, new class of smog, and how the cognitive abilities of humans are affected by fog. Recently India and China are facing an emergence and repetitions of fog haze/smog and thus their policies initiatives are also briefly discussed. It is concluded that the complexity in fog forecasting is high due to multiple factors playing a role at multiple levels. Most of the researchers have worked upon the role of humidity, temperature, wind, and boundary layer to predict fogs. However, the role of global wind circulations, soil properties, and anthropogenic heat requires further investigations. Literature shows that fog is being harnessed to address water insecurity in various countries, however, coastal areas of Angola, Namibia and South Africa, Kenya, Eastern Yemen, Oman, China, India, Sri Lanka, Mexico, along with the mountainous regions of Peru, Chile, and Ecuador, are some of the potential sites that can benefit from the installation of fog water harvesting systems.

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Section: Factors Influencing Fog Formationmentioning

confidence: 99%

A review on factors influencing fog formation, classification, forecasting, detection and impacts

Lakra

Avishek

2022

Rend. Fis. Acc. Lincei

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“…Comparing the results of Long et al. (2016), the relationship between the YS fog and PJ teleconnection is weak possible because the YS is away from the circulation of PJ teleconnection.…”

Section: Discussionmentioning

confidence: 66%

“…In seasonal mean, the SST and southerlies explain about 54% and 19% variance of the MJJ YS fog at interannual timescale according to a multiple linear regression. Comparing the results of Long et al (2016), the relationship between the YS fog and PJ teleconnection is weak possible because the YS is away from the circulation of PJ teleconnection.…”

Section: Data Availability Statementmentioning

confidence: 94%

“…Although previous studies have concentrated on the climatic features and synoptic boundary processes of the YS fog, fewer studies investigate its interannual variability partly due to the difficulty in distinguishing fog from low-level clouds in satellite observations (e.g., Gao et al, 2009;Norris & Leovy, 1994;Yi et al, 2015;Yi et al, 2019). A few studies on interannual variation in sea fog rely on the coastal observations and sporadic ship reports (Bai et al, 2010;Garreaud et al, 2008;Long et al, 2016). Bai et al (2010) used the Qingdao (QD) observations to show that the SST is anomalously low and high over the YS and ECS in the foggier years, respectively.…”

mentioning

confidence: 99%

“…Bai et al (2010) used the Qingdao (QD) observations to show that the SST is anomalously low and high over the YS and ECS in the foggier years, respectively. Long et al (2016) found that the Pacific-Japan (PJ) teleconnection influences the interannual variation in July fog over the northwestern Pacific through modulating local surface moist/thermal advection.…”

mentioning

confidence: 99%

See 2 more Smart Citations

Interannual Variability in Summertime Sea Fog Over the Northern Yellow Sea and Its Association With the Local Sea Surface Temperature

2021

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The Yellow Sea (YS) experiences heavy advection fog during boreal summer, which seriously affects marine transport and harbor activities. Using a set of long‐term observations, the present study reveals the interannual variability in the YS fog during its core season (May‐June‐July, MJJ). The spaceborne lidar supports that a station‐based index represents the fog over the northern YS in a seasonal mean sense. The composite soundings according to the YS fog index show that the temperature difference is evident within the boundary layer and becomes indistinguishable in the free atmosphere. This implies that the driver of the MJJ YS fog originates from the bottom boundary of the fog layer. Regression analyses of sea surface temperature (SST) and air‐sea fluxes show that the local SST strongly modulates the northern YS fog at interannual scale. The fog during foggier years features a significant decrease in specific humidity, suggesting that the colder sea surface facilitates fog occurrence through strong turbulent cooling. This study identifies the local SST as a key driver of the interannual variation in the northern YS fog during the core season and provides predictive values by linking the YS fog to the preceding SST.

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Decadal shift in sea fog frequency over the northern South China Sea in spring: Interdecadal variation and impact of the Pacific Decadal Oscillation

Han

Long

Feng

et al. 2022

Atmospheric Research

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Impact of the Pacific–Japan teleconnection pattern on July sea fog over the northwestern Pacific: Interannual variations and global warming effect

Cited by 9 publications

References 26 publications

A review on factors influencing fog formation, classification, forecasting, detection and impacts

A review on factors influencing fog formation, classification, forecasting, detection and impacts

Interannual Variability in Summertime Sea Fog Over the Northern Yellow Sea and Its Association With the Local Sea Surface Temperature

Decadal shift in sea fog frequency over the northern South China Sea in spring: Interdecadal variation and impact of the Pacific Decadal Oscillation

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