Connecting Global Modes of Variability to Climate in High Mountain Asia
Oscillations in global modes of variability (MoVs) form global teleconnections that affect regional climate variability and modify the potential for severe and damaging weather conditions. Understanding the link between certain MoVs and regional climate can improve the ability to more accurately pre...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-01-01
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| Series: | Atmosphere |
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| Online Access: | https://www.mdpi.com/2073-4433/15/2/142 |
| _version_ | 1797298998146498560 |
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| author | Elias C. Massoud Young-Kwon Lim Lauren C. Andrews Manuela Girotto |
| author_facet | Elias C. Massoud Young-Kwon Lim Lauren C. Andrews Manuela Girotto |
| author_sort | Elias C. Massoud |
| collection | DOAJ |
| description | Oscillations in global modes of variability (MoVs) form global teleconnections that affect regional climate variability and modify the potential for severe and damaging weather conditions. Understanding the link between certain MoVs and regional climate can improve the ability to more accurately predict environmental conditions that impact human life and health. In this study, we explore the connection between different MoVs, including the Arctic oscillation (AO), Eurasian teleconnection, Indian Ocean dipole (IOD), North Atlantic oscillation (NAO), and El Niño southern oscillation (Nino34), with winter and summer climates in the High Mountain Asia (HMA) region, including geopotential height at 250 hPa (z250), 2 m air temperature (T2M), total precipitation (PRECTOT), and fractional snow cover area (fSCA). Relationships are explored for the same monthly period between the MoVs and the climate variables, and a lagged correlation analysis is used to investigate whether any relationship exists at different time lags. We find that T2M has a negative correlation with the Eurasian teleconnection in the Inner Tibetan Plateau and central China in both winter and summer and a positive correlation in western China in summer. PRECTOT has a positive correlation with all MoVs in most regions in winter, especially with the IOD, and a negative correlation in summer, especially with the Eurasian teleconnection. Snow cover in winter is positively correlated with most indices throughout many regions in HMA, likely due to wintertime precipitation also being positively correlated with most indices. Generally, the AO and NAO show similar correlation patterns with all climate variables, especially in the winter, possibly due to their oscillations being so similar. Furthermore, the AO and NAO are shown to be less significant in explaining the variation in HMA climate compared to other MoVs such as the Eurasian teleconnection. Overall, our results identify different time windows and specific regions within HMA that exhibit high correlations between climate and MoVs, which might offer additional predictability of the MoVs as well as of climate and weather patterns in HMA and throughout the globe. |
| first_indexed | 2024-03-07T22:43:10Z |
| format | Article |
| id | doaj.art-fbfb2e938c6d4056aed2e237cb7aa243 |
| institution | Directory Open Access Journal |
| issn | 2073-4433 |
| language | English |
| last_indexed | 2024-03-07T22:43:10Z |
| publishDate | 2024-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Atmosphere |
| spelling | doaj.art-fbfb2e938c6d4056aed2e237cb7aa2432024-02-23T15:06:59ZengMDPI AGAtmosphere2073-44332024-01-0115214210.3390/atmos15020142Connecting Global Modes of Variability to Climate in High Mountain AsiaElias C. Massoud0Young-Kwon Lim1Lauren C. Andrews2Manuela Girotto3Computational Sciences and Engineering Division, Oak Ridge National Laboratory, Oak Ridge, TN 37830, USAGlobal Modeling & Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD 20771, USAGlobal Modeling & Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, MD 20771, USADepartment of Environmental Science, Policy, and Management, University of California Berkeley, Berkeley, CA 94720, USAOscillations in global modes of variability (MoVs) form global teleconnections that affect regional climate variability and modify the potential for severe and damaging weather conditions. Understanding the link between certain MoVs and regional climate can improve the ability to more accurately predict environmental conditions that impact human life and health. In this study, we explore the connection between different MoVs, including the Arctic oscillation (AO), Eurasian teleconnection, Indian Ocean dipole (IOD), North Atlantic oscillation (NAO), and El Niño southern oscillation (Nino34), with winter and summer climates in the High Mountain Asia (HMA) region, including geopotential height at 250 hPa (z250), 2 m air temperature (T2M), total precipitation (PRECTOT), and fractional snow cover area (fSCA). Relationships are explored for the same monthly period between the MoVs and the climate variables, and a lagged correlation analysis is used to investigate whether any relationship exists at different time lags. We find that T2M has a negative correlation with the Eurasian teleconnection in the Inner Tibetan Plateau and central China in both winter and summer and a positive correlation in western China in summer. PRECTOT has a positive correlation with all MoVs in most regions in winter, especially with the IOD, and a negative correlation in summer, especially with the Eurasian teleconnection. Snow cover in winter is positively correlated with most indices throughout many regions in HMA, likely due to wintertime precipitation also being positively correlated with most indices. Generally, the AO and NAO show similar correlation patterns with all climate variables, especially in the winter, possibly due to their oscillations being so similar. Furthermore, the AO and NAO are shown to be less significant in explaining the variation in HMA climate compared to other MoVs such as the Eurasian teleconnection. Overall, our results identify different time windows and specific regions within HMA that exhibit high correlations between climate and MoVs, which might offer additional predictability of the MoVs as well as of climate and weather patterns in HMA and throughout the globe.https://www.mdpi.com/2073-4433/15/2/142teleconnectionsHigh Mountain Asiamodes of variabilitygeopotential heighttemperatureprecipitation |
| spellingShingle | Elias C. Massoud Young-Kwon Lim Lauren C. Andrews Manuela Girotto Connecting Global Modes of Variability to Climate in High Mountain Asia Atmosphere teleconnections High Mountain Asia modes of variability geopotential height temperature precipitation |
| title | Connecting Global Modes of Variability to Climate in High Mountain Asia |
| title_full | Connecting Global Modes of Variability to Climate in High Mountain Asia |
| title_fullStr | Connecting Global Modes of Variability to Climate in High Mountain Asia |
| title_full_unstemmed | Connecting Global Modes of Variability to Climate in High Mountain Asia |
| title_short | Connecting Global Modes of Variability to Climate in High Mountain Asia |
| title_sort | connecting global modes of variability to climate in high mountain asia |
| topic | teleconnections High Mountain Asia modes of variability geopotential height temperature precipitation |
| url | https://www.mdpi.com/2073-4433/15/2/142 |
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