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Zhihong Jiang
,
Hao Yang
,
Zhengyu Liu
,
Yanzhu Wu
, and
Na Wen

Abstract

This study investigates the influence of different sea surface temperature (SST) modes on the winter temperature in China using the generalized equilibrium feedback assessment (GEFA). It is found that the second EOF mode of winter temperature in China during 1958–2010 shows a typical northeast–southwest (NE–SW) pattern, which is a major spatial mode of Chinese winter temperature at interannual scales. The winter temperature of the NE–SW pattern is forced mainly by SST modes in the tropical Pacific and Atlantic. For 2009/10, the tropical Pacific El Niño mode and tropical Atlantic tripole mode have the largest contribution to the response. The physical mechanism of the cold northeast–warm southwest (CNE–WSW) pattern is also explained in terms of GEFA of the responses of the atmospheric circulation. The northerly flow at the low level transports cold air to northern and northeastern China, resulting in a lower temperature there. Meanwhile, the anomaly meridional wind advects warm air from the southern oceans to southwestern China, leading to warming there.

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Sheng Huang
,
Weijiang Li
,
Jiahong Wen
,
Mengru Zhu
,
Yao Lu
, and
Na Wu

Abstract

Driven by both climate change and urbanization, extreme rainfall events are becoming more frequent and having an increasing impact on urban commuting. Using hourly rainfall data and “metro” origin–destination (OD) flow data in Shanghai, China, this study uses the Prophet time series model to calculate the predicted commuting flows during rainfall events and then quantifies the spatiotemporal variations of commuting flows due to rainfall at station and OD levels. Our results show the following: 1) In general, inbound commuting flows at metro stations tend to decrease with hourly rainfall intensity, varying across station types. The departure time of commuters is usually delayed by rainfall, resulting in a significant stacking effect of inbound flows at metro stations, with a pattern of falling followed by rising. The sensitivity of inbound flows to rainfall varies at different times, high at 0700 and 1700 LT and low at 0800, 0900, 1800, and 1900 LT because of the different levels of flexibility of departure time. 2) Short commuting OD flows (≤15 min) are more affected by rainfall, with an average increase of 7.3% and a maximum increase of nearly 35%, whereas long OD flows (>15 min) decrease slightly. OD flows between residential and industrial areas are more affected by rainfall than those between residential and commercial (service) areas, exhibiting a greater fluctuation of falling followed by rising. The sensitivity of OD flows to rainfall varies across metro lines. The departure stations of rainfall-sensitive lines are mostly distributed in large residential areas that rely heavily on the metro in the morning peak hours and in large industrial parks and commercial centers in the evening peak hours. Our findings reveal the spatiotemporal patterns of commuting flows resulting from rainfall at a finer scale, which provides a sound basis for spatial and temporal response strategies. This study also suggests that attention should be paid to the surges and stacking effects of commuting flows at certain times and areas during rainfall events.

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