Atmospheric oscillations, which mostly associate with climate patterns, have great influences on global climate variables, and they usually lead to extreme climate conditions and events, which cause lots of adverse impacts on our socioeconomic statuses. This study aims to identify the influence of climate patterns on the global precipitation anomaly. Four major climate patterns are investigated, and they are El Niño/La Niña–Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), Arctic Oscillation (AO) and Antarctic Oscillation (AAO). This study adopts the NINO3.4, DMI, AO index and AAO index to represent the climate patterns of ENSO, IOD, AO and AAO, respectively. The other research data used include precipitation data from the Global Precipitation Climatology Project (GPCP).
The multiple linear regression method is used to study the relationships between the climate patterns and the global precipitation anomalies. Then, the precipitation anomalies all over the globe is modeled by those four climate pattern indexes. The signs and magnitudes of the regression coefficients for those indexes can reflect the relations of the climate patterns with the precipitations and their strength. Part of the results from the regression analysis matches well with the general understanding about the impact of those climate patterns. The influences of the climate patterns can be explained by their impact on the Walker circulation, monsoon system, jet stream, convection and atmospheric moisture transport. This suggests that the regression method is able to represent the teleconnection between the climate patterns and precipitation anomalies.
Further, for each calendar month of the year, the variations of the relationships between precipitation anomalies and climate indexes show that the influences of the climate patterns on the precipitation anomalies vary throughout the year. The variations are mainly due to the different general circulation patterns in different seasons. The strengths of the relations also vary, and they mostly change with the strength of the climate patterns. Usually the stronger the climate pattern, the stronger the relationship. The variation of the heating from the sun also explain some of the seasonal variations of the relationships.
Overall, this study indicates that the precipitation anomalies in Asia near the tropics and subtropics are significantly related to ENSO and IOD. Precipitation anomalies in Australia show significant relation with ENSO, IOD and AAO. AO has the greatest influence on the precipitation anomalies over Europe. For Africa, IOD and AAO have large influence on the precipitation anomalies on the east part and south part respectively. The south part of the North America is mainly affected by ENSO, while AO is dominant over the regions located at higher latitudes. ENSO is the dominant climate pattern affecting the precipitation anomalies in South America, and further, AAO and IOD also show some significant influences. / published_or_final_version / Civil Engineering / Master / Master of Philosophy
| Identifer | oai:union.ndltd.org:HKU/oai:hub.hku.hk:10722/195968 |
| Date | January 2013 |
| Creators | Chung, Chi-hang, 鍾志恆 |
| Contributors | Chen, J |
| Publisher | The University of Hong Kong (Pokfulam, Hong Kong) |
| Source Sets | Hong Kong University Theses |
| Language | English |
| Detected Language | English |
| Type | PG_Thesis |
| Rights | The author retains all proprietary rights, (such as patent rights) and the right to use in future works., Creative Commons: Attribution 3.0 Hong Kong License |
| Relation | HKU Theses Online (HKUTO) |
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