Search

In the past two decades, the regional climate in China has undergone significant change, resulting in crop yield reduction and complete failure. The goal of this study is to detect the variation of temperature and precipitation for different growth periods of maize and assess their impact on phenology. The daily meteorological data in the Midwest of Jilin Province during 1960-2014 were used in the study. The ensemble empirical mode decomposition method was adopted to analyze the non-linear trend and fluctuation in temperature and precipitation, and the sensitivity of the length of the maize growth period to temperature and precipitation was analyzed by the wavelet cross-transformation method. The results show that the trends of temperature and precipitation change are non-linear for different growth periods of maize, and the average temperature in the sowing-jointing stage was different from that in the other growth stages, showing a slight decrease trend, while the variation amplitude of maximum temperature is smaller than that of the minimum temperature. This indicates that the temperature difference between day and night shows a gradually decreasing trend. Precipitation in the growth period also showed a decreasing non-linear trend, while the inter-annual variability with period of quasi-3-year and quasi-6-year dominated the variation of temperature and precipitation. The whole growth period was shortened by 10.7 days, and the sowing date was advanced by approximately 11 days. We also found that there was a significant resonance period among temperature, precipitation, and phenology. Overall, a negative correlation between phenology and temperature is evident, while a positive correlation with precipitation is exhibited. The results illustrate that the climate suitability for maize has reduced over the past decades. [ABSTRACT FROM AUTHOR]

Highlights • We obtained the nonlinear trends of extreme climate indices. • We explored the probability of extreme climate indices using tridimensional copula. • The climate of NEC had an obvious tendency of warming and drying. • High temperatures and excessive precipitation occurred frequently in western NEC. • Southeastern Jilin and northeastern Liaoning are vulnerable to low temperatures. Abstract With the acceleration of global warming, the frequent occurrence of extreme climate events has inflicted great socio-economies losses and casualties; therefore, it is particularly important to explore the characteristics of extreme climate events. Nine extreme climate indices defined by the World Meteorological Organization's Expert Team on Climate Change Detection and Indices (ETCCDI) were constructed from a long term (1960–2014) continuous dataset of 70 meteorological stations in Northeast China (NEC). We detected the current and future spatial variation characteristics using the Sen's slope estimator and R/S analysis method, respectively, and periodicities of individual extreme climate indices were calculated by Morlet continuous wavelet transform methods. Furthermore, a variety of marginal distribution functions was adopted to construct trivariate copula functions in order to calculate the joint probabilities and return periods. The results show that there were different spatiotemporal variation patterns of extreme climate indices: the extreme cold temperature index frost days (FD0) had a significant decreasing trend, summer days (SU25), tropical nights (TR20), and warm days (TX90) had a significant increasing trend. However, no significant changes in the extreme precipitation indices were detected consistently; only a few stations scattered over NEC showed significant changes in these indices. Most of the extreme temperature indices showed significant periods of about 1.5, 2, and 3 years, whereas extreme cold and precipitation indices had approximate periods of 3, 3.5, and 4 years. Southeastern Jilin and northeastern Liaoning Provinces had colder winters and higher annual precipitation than other regions. The probabilities of high temperatures and heavy precipitation were relatively high in western Liaoning, Jilin, and Heilongjiang Provinces. [ABSTRACT FROM AUTHOR]

[Display omitted] • The severity of compound dry and hot events in Inner Mongolia has increased in the last 40 years. • Among the four large-scale circulation patterns, the largest influence on the SDHI in Inner Mongolia is AMO and the smallest is ENSO. • The joint effect of large-scale circulation patterns on SDHI is greater than the independent effect. In recent decades, frequent compound dry and hot events (CDHEs) have posed a great threat to humans and the ecological environment, especially in Inner Mongolia, which has typical arid and semi-arid characteristics. Therefore, while exploring the characteristics of the spatial and temporal evolution of the CDHEs in Inner Mongolia, and elucidating their teleconnections with large-scale circulation indexes, it can not only provide useful enlightenment for ecological protection, but also provide more detailed information for understanding the corresponding details of CDHEs with large-scale circulation indexes. In this study, monthly temperature and precipitation data from 115 meteorological stations in Inner Mongolia for each summer from 1981 to 2020 were used to establish a standardised dry and hot index (SDHI), characterising the severity of extreme compound events of drought and high temperature in Inner Mongolia. This data was also used to analyse the spatial and temporal characteristics of such compound events over the past 40 years. Thereafter, Pearson's correlation, stepwise multiple regression models, and multivariate wavelet analysis methods were used to assess the relationship between the atmospheric circulation index and SDHI in terms of linear, non-linear, and different combinations of the four large-scale circulation indexes. The results show that SDHI performs well in the assessment of CDHEs in Inner Mongolia and shows great similarities with historical records. The overall trend of CDHEs in Inner Mongolia over the past 40 years has intensified over time. Spatially, abnormal and moderate dry and hot events mainly occurred in Inner Mongolia before the 21st century, and the frequency of occurrence was higher in the eastern region than in the western region. Furthermore, the severity of CDHEs has increased significantly since the 21st century, with severe and extreme dry and hot events occurring more frequently in the western region than in the eastern region. The results of the correlation analysis show that, among the four large-scale circulation indexes, the Atlantic Multidecadal Oscillation (AMO) has the greatest influence on the CDHEs in Inner Mongolia when it is positive, with the highest significance, and when the Pacific Decadal Oscillation (PDO) and North Atlantic Oscillation (NAO) show negative phases, they are more likely to cause dry and hot events in Inner Mongolia. Further, where the number of stations negatively influenced by NAO is higher, the effect of El Niño Southern Oscillation (ENSO) on dry and hot events is usually insignificant. Partial wavelet coherence (PWC) analysis suggests that the independent effects of circulation factors may be weaker but appear to be stronger due to their interdependence with other circulation patterns. Finally, the multiple wavelet coherence (MWC) results show that the changes in SDHI values can be best explained by a combination of two or more factors. [ABSTRACT FROM AUTHOR]

In the context of global climate change, drought has become an important factor that affects the maize yield in China. To analyse the impact of drought on maize yield loss in Northeast China in current and future climate scenarios, the Composite Meteorological Drought Index (CI) is introduced to reconstruct the following drought indicators: drought accumulative days (DAD), drought accumulative intensity (DAI), and consecutive drought days (CDD). These three drought indicators are used to describe the three-dimensional characteristics of drought in this study. Sen’s slope method and three-dimensional copula functions are adopted to analyse the variety of drought features, and Ensemble Empirical Mode Decomposition (EEMD) is used to analyse the variations in maize yield. A temporal assessment of the standardized yield residuals series (SYRS) of maize from 1961 to 2014 is conducted. A panel regression model is applied to demonstrate the drought impact on maize yield at various growth stages under the RCP4.5 scenario. The results show that the drought risk level for midwest Jilin Province, western Liaoning, and eastern Heilongjiang increase with global warming in the current scenario. The shorter three-dimensional joint return periods, 44–80 yr, were mainly located in western Jilin Province, Liaodong Peninsula, and northwestern Liaoning. Eastern Heilongjiang has a slightly longer joint return period of 80–100 yr. The SYRS shows a strong statistical correlation with drought indicator variations; drought-prone regions exhibit strong positive correlations. In comparison, excess precipitation regions show strong negative correlations with drought indicators in most growth stages. Drought indicators have a relatively strong association with SYRS at the milky–mature maize growth stage, and the occurrence of drought during this period primarily determines the maize yield changes in the future. Maize yield changes are −2.04%, −2.65% and −1.57% for Liaoning, Jilin, and Heilongjiang Province under the RCP4.5 scenario. These results can be used as a tool for early warning of drought risk to maize, and will accelerate the progress of drought disaster risk management. [ABSTRACT FROM AUTHOR]