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The systematic bias of the estimated average temperature using daily Tmax and Tmin records relative to the standard average temperature of four time-equidistant observations and its effect on the estimated trend of long-term temperature change have not been well understood. This paper attempts to evaluate the systematic bias across mainland China using the daily data of national observational stations. The results revealed that the positive bias of annual mean temperature was large, reaching 0.58°C nationally on average; regional average bias was lowest in the northwest arid region and highest in the Qinghai–Tibetan Plateau; the bias was low in spring and summer and high in autumn and winter, reaching its lowest point in mid- and late May and highest point in early November. Furthermore, the bias showed a significant upward trend in the past 50 years, with a rising rate of 0.021°C (10 yr)−1, accounting for about 12% of the overall warming as estimated from the data of the observational network; the largest positive trend bias was found in the northwest arid region, while the east monsoon region experienced the smallest change; the most remarkable increase of the bias occurred after early 1990s. These results indicate that the customarily applied method to calculate daily and monthly mean temperature using Tmax and Tmin significantly overestimates the climatological mean and the long-term trend of surface air temperature in mainland China. [ABSTRACT FROM AUTHOR]

Middle and eastern routes of the South-North Water Diversion Project (SNWDP) of China, which are approximately located within the area 28°-42°N and 110°-122°E, are being constructed. This paper investigates the past climatic variations on various time scales using instrumental and proxy data. It is found that annual mean surface air temperature has increased significantly during the past 50-100 years, and winter and spring temperatures in the northern part of the region have undergone the most significant changes. A much more significant increase occurs for annual mean minimum temperature and extreme low temperature than for annual mean maximum temperature and extreme high temperature. No significant trend in annual precipitation is found for the region as a whole for the last 50 and 100 years, although obvious decadal and spatial variation is detectable. A seesaw pattern of annual and summer precipitation variability between the north and the south of the region is evident. Over the last 100 years, the Haihe River basin has witnessed a significant negative trend of annual precipitation, but no similar trend is detected for the Yangtze and Huaihe River basins. Pan evaporation has significantly decreased since the mid-1960s in the region in spite of the fact that the trend appears to have ended in the early 1990s. The negative trend of pan evaporation is very significant in the plain area between the Yangtze and Yellow Rivers. There was a notable series of dry intervals lasting decades in the north of the region. The northern drought of the past 30 years is not the most severe in view of the past 500 years; however, the southern drought during the period from the 1960s to the 1980s may have been unprecedented. The dryness-wetness index (DWI) shows significant oscillations with periodicities of 9.5 and 20 years in the south and 10.5 and 25 years in the north. Longer periodicities in the DWI series include 160-170- and 70-80-yr oscillations in the north, and 100-150-yr oscillations in the south. The observed climate change could have implications for the construction and management of the SNWDP. The official approval and start of the hydro project was catalyzed by the severe multiyear drought of 1997-2003 in the north, and the operation and management of the project in the future will also be influenced by climate change-in particular by precipitation variability. This paper provides a preliminary discussion of the potential implications of observed climate change for the SNWDP. [ABSTRACT FROM AUTHOR]

It is argued that the occurrence of cold events decreases under the background of global warming. However, from the mid-1990s to the early 2010s, northern China experienced a period of increasing occurrence of low temperature extremes (LTE). Factors responsible for this increase of LTE are investigated in this analysis. The results show that the interdecadal variation of the winter mean temperature over mid- and high-latitude Eurasia acts as an important thermal background. It is characterized by two dominant modes, the "consistent cooling" pattern and the "warm high-latitude Eurasia and cold midlatitude Eurasia" pattern, from the mid-1990s to the early 2010s. The two patterns jointly provide a cooling background for the increase of LTE in northern China. Meanwhile, though the interdecadal variation of the Arctic Oscillation (AO), Ural blocking (UB), and Siberian high (SH) are all highly correlated with the occurrence of LTE in northern China, the AO is found to play a dominant role. On one hand, the AO directly affects the occurrence of LTE because of its dynamic structure; on the other hand, it takes an indirect effect by affecting the intensity of UB and SH. Further analyses show that the winter temperature in mid- and high-latitude Eurasia and the AO are independent factors that influence the increase of LTE in northern China from the mid-1990s to the early 2010s. [ABSTRACT FROM AUTHOR]

In this study, the interdecadal variability of the relationship between ENSO and winter synoptic temperature variability (STV) over the Asian–Pacific–American region is investigated based on observational data from 1951 to 2018. An interdecadal shift in the ENSO–STV relationship occurred in the 1980s over Eastern China, changing from significant in period 1 (P1; 1951–87) to insignificant in period 2 (P2; 1988–2018). But the ENSO–STV relationship is significantly stable over North America for the whole period. In addition, a possible reason for this interdecadal shift in the ENSO–STV relationship over Eastern China is also investigated. During P1, the ENSO pattern is significantly correlated to the temperature gradient over Northeast Asia, which is the key region influencing the intensification of extratropical eddies. The intensification of extratropical eddies over Northeast Asia is directly associated with the magnitude of STV over Eastern China. But in P2, the ENSO pattern is not related to the temperature over Northeast Asia. Therefore, the change in the ENSO pattern from P1 to P2 contributes to the interdecadal shift in the ENSO–STV relationship in the 1980s over Eastern China by influencing the temperature gradient over Northeast Asia, while ENSO can influence the temperature gradient over North America for the whole period. Furthermore, the possible role of the ENSO patterns in P1 and P2 is also examined by using an atmospheric general circulation model, highlighting that the pattern of SST variation is a determining factor in regulating STV in different regions. [ABSTRACT FROM AUTHOR]

Interannual variation in grain yield of rice has been observed at both farm and regional scales, which is related to the climate variability. Previous studies focus on predicting the trend of climate change in the future and its potential effects on rice production using climate models; however, field studies are lacking to examine the climatic causes underlying the interannual yield variability for different rice cultivars. Here a 6-year field experiment from 2012 to 2017 was conducted using one hybrid (Yangliangyou6, YLY6) cultivar and one inbred (Huanghuazhan, HHZ) cultivar to determine the climate factors responsible for the interannual yield variation. A significant variation in grain yield was observed for both the inbred and hybrid cultivars across six planting years, and the coefficient of variation for grain yield was 7.3–10.5%. The night temperature (average daily minimum temperature, Tmin) contributed to the yield variability in both cultivars. However, the two cultivars showed different responses to the change in Tmin. The yield variation in HHZ was mainly explained by the effects of Tmin on grain filling percentage and grain weight, while the change in spikelets m−2 in response to Tmin accounted for the yield variability in YLY6. Further analysis found that spikelets m−2 of YLY6 significantly and negatively correlated with Tmin from transplanting to heading. For HHZ, the grain filling percentage and grain weight were significantly affected by Tmin of the week prior to heading and from heading to maturity, respectively. Overall, there were differences in the response mechanism between hybrid and inbred cultivars to high night temperature. These will facilitate the development of climate-resilient cultivars and appropriate management practices to achieve a stable grain yield. [ABSTRACT FROM AUTHOR]

Temperature seasonality, the difference between summer and winter temperatures in mid–high latitudes, is an important component of the climate. Whether humans have had detectable influences on changing surface temperature seasonality at scales smaller than the subcontinental scale, where humans are directly impacted, is not clear. In this study, the first detection and attribution analysis of changes in temperature seasonality in China has been carried out. Detection and attribution of both summer and winter temperatures were also conducted, with careful consideration of observational uncertainty and the inconsistency between observation and model simulations induced by the long coastline and country border in China. The results show that the response to external forcings is robustly detectable in the spatiotemporal pattern of weakening seasonality and in that of warming winter temperature, although models may have underestimated the observed changes. The response to external forcings is detectable and consistent with the observed change in summer temperature averaged over China. Human influences are detectable in changes in seasonality and summer and winter temperatures, most robustly in winter, and these influences can be separated from those of natural forcing when averaged over China. The recent increase in summer temperature was found to be due to external forcings, and the warming hiatus in winter temperature from 1998 to 2013 was due to a statistically significant cooling trend induced by internal variability. These results will give insights into the understanding of the warming hiatus in China, as well as the hot summers and cold winters in recent years. [ABSTRACT FROM AUTHOR]

Three methods were used to distinguish the characteristics of changes in climate variability and normalized difference vegetation index (NDVI) during the period from 1982 to 2000 in China. Great changes in climate variability and an increased trend in NDVI were observed. The changes in precipitation variability were greater than the changes in temperature variability in each month, which is attributed to changes in the monsoon system in East Asia. The abrupt changes in climate and NDVI were more significant in 1983 than in the other years due to the impacts of El Niño/Southern Oscillation (ENSO). Using these results, the influences of changes in climate variability on vegetation were studied in the whole nation, and eight regions were defined according to the vegetation division map of China. The results show that abrupt climate changes at a small scale cannot cause abrupt NDVI changes directly. At a nationwide level, over a longer time scale the persistence of above/below average temperature determines the changes in NDVI; at a shorter time scale, changes in the magnitude of precipitation influence NDVI significantly. Such regional climate variability affects vegetation in different ways owing to the diversity of vegetation types, climatic conditions and topography of the land. [ABSTRACT FROM AUTHOR]

Due to the lack of long-term climate records, our understanding of paleoclimatic variability in the Tibetan Plateau (TP) is still limited. In this study, we developed a tree-ring width (TRW) chronology based on tree-ring cores collected from our study site, southeastern TP. This chronology responded well to the mean maximum temperatures of May–June and was thus used to reconstruct early summer (May–June) maximum temperature during the period 1541–2019. The reconstruction explained 33.6% of the climatic variance during the calibration period 1962–2019. There were 34 extremely warm years (7.2% of total years) and 36 extremely cold years (7.5% of total years) during the reconstruction period. The spatial correlation analysis and the comparison with other local temperature reconstructions confirmed the reliability and representativeness of our reconstruction. The results of the ensemble empirical mode decomposition (EEMD) analysis indicated quasi-oscillations of 2.9–4.2 years, 4.5–8.3 years, 11.1–15.4 years, 20–33.3 years, 50.4 years, 159.7 years, and 250 years in this temperature reconstruction which may be associated with ENSO cycles, solar activity, and PDO. [ABSTRACT FROM AUTHOR]