Spatiotemporal change in China’s climatic growing season: 1955–2000

The timing, length, and thermal intensity of the climatic growing season in China show statistically significant changes over the period of 1955 to 2000. Nationally, the average start of the growing season has shifted 4.6–5.5 days earlier while the average end has moved 1.8–3.7 days later, increasing the length of the growing season by 6.9–8.7 days depending on the base temperature chosen. The thermal intensity of the growing season has increased by 74.9–196.8 growing degree-days, depending on the base temperature selected. The spatial characteristics of the change in the timing and length of the growing season differ from the geographical pattern of change in temperatures over this period; but the spatial characteristics of change in growing degree-days does resemble the pattern for temperatures, with higher rates in northern regions. Nationally, two distinct regimes are evident over time: an initial period where growing season indicators fluctuate near a base period average, and a second period of rapidly increasing growing season length and thermal intensity. Growing degree-days are highly correlated with March-to-November mean air temperatures in all climatic regions of China; the length of the growing season is likewise highly correlated with March-to-November mean air temperatures except in east, southeast and southwest China at base temperature of 0°C and southeast China at base temperature of 5°C. The growing season start date appears to have the greater influence on the length of the growing season. In China, warmer growing seasons are also likely to be longer growing seasons.     

Multidecadal variability in local growing season during 1901–2009

Global warming exerts a lengthening effect on the growing season, with observational evidences emerging from different regions over the world. However, the difficulty for a global overview of this effect for the last century arises from limited availability of the long-term daily observations. In this study, we find a good linear relationship between the start (end) date of local growing season (LGS) and the monthly mean temperature in April (October) using the global gridded daily temperature dataset for 1960–1999. Using homogenized daily temperature records from nine stations where the time series go back to the beginning of the twentieth century, we find that the rate of change in the start (end) date of the LGS for per degree warming in April (October) mean temperature keeps nearly constant throughout the time. This enables us to study LGS changes during the last century using global gridded monthly mean temperature data. The results show that during the period 1901–2009, averaged over the observation areas, the LGS length has increased by a rate of 0.89 days decade^?1, mainly due to an earlier start (?0.58 days decade^?1). This is smaller than those estimates for the late half of the twentieth century, because of multidecadal climate variability (MDV). A MDV component of the LGS index series is extracted by using Ensemble Empirical Mode Decomposition method. The MDV exhibits significant positive correlation with the Atlantic Multi–decadal Oscillation (AMO) over most of the Northern Hemisphere lands, but negative in parts of North America and Western Asia for start date of LGS. These are explained by analyzing differences in atmospheric circulation expressed by sea level pressure departures between the warm and cool phases of AMO. It is suggested that MDV in association with AMO accelerates the lengthening of LGS in Northern Hemisphere by 53 % for the period 1980–2009.     

Estimating daily global solar radiation during the growing season in Northeast China using the ?ngstr?m–Prescott model

Daily global solar radiation is an important input required in most crop models. In the present study, a sunshine-based model, the ?ngstr?m–Prescott model, is employed to estimate daily global solar radiation on a horizontal surface during the growing season in Northeast China. Data from six control groups are used. The controls include the entire sequence, precipitation days, and non-precipitation days both during the growing season and year-round. Estimations are validated by comparing the calculated values with the corresponding measured values. The results indicate that estimating daily global solar radiation during the growing season using data only from the growing season is better than using year-round data. Classifying days with respect to precipitation and non-precipitation is also unnecessary. The performance on estimating daily global solar radiation during the growing season using the entire data in growing season performs best. A sunshine-based equation is obtained using our method to estimate growing season daily radiation for all meteorological stations in Northeast China. The approved approach is expected to be beneficial to crop models and other agricultural purposes.     

Spatiotemporal variations in rainfall erosivity during the period of 1960–2011 in Guangdong Province,southern China

Rainfall erosivity, which shows a potential risk of soil loss caused by water erosion, is an important factor in soil erosion process. In consideration of the critical condition of soil erosion induced by rainfall in Guangdong Province of southern China, this study analyzed the spatial and temporal variations in rainfall erosivity based on daily rainfall data observed at 25 meteorological stations during the period of 1960–2011. The methods of global spatial autocorrelation, kriging interpolation, Mann–Kendall test, and continuous wavelet transform were used. Results revealed that the annual rainfall erosivity in Guangdong Province, which spatially varied with the maximum level observed in June, was classified as high erosivity with two peaks that occur in spring and summer. In the direction of south–north, mean annual rainfall erosivity, which showed significant relationships with mean annual rainfall and latitude, gradually decreased with the high values mainly distributed in the coastal area and the low values mainly occurring in the lowlands of northwestern Guangdong. Meanwhile, a significant positive spatial autocorrelation which implied a clustered pattern was observed for annual rainfall erosivity. The spatial distribution of seasonal rainfall erosivity exhibited clustering tendencies, except spring erosivity with Moran’s I and Z values of 0.1 and 1.04, respectively. The spatial distribution of monthly rainfall erosivity presented clustered patterns in January–March and July–October as well as random patterns in the remaining months. The temporal trend of mean rainfall erosivity in Guangdong Province showed no statistically significant trend at the annual, seasonal, and monthly scales. However, at each station, 1 out of 25 stations exhibited a statistically significant trend at the annual scale; 4 stations located around the Pearl River Delta presented significant trends in summer at the seasonal scale; significant trends were observed in March (increasing trends at 3 stations), June (increasing trends at 4 stations located in the Beijiang River Basin), and October (decreasing trends at 4 stations) at the monthly scale. In accordance with the mean annual rainfall over Guangdong Province, the mean annual rainfall erosivity showed two significant periodicities of 3–6 and 10–12 years at a confidence level of 95 %. In conclusion, the results of this study provide insights into the spatiotemporal variation in rainfall erosivity in Guangdong Province and support for agrolandscape planning and water and soil conservation efforts in this region.     

Changes in climatic elements in the Pan-Hexi region during 1960–2014 and responses to global climatic changes

Theoretical and Applied Climatology - In this paper, robust statistical methods (including the climatic tendency ratio, inverse distance weight (IDW), and Mann-Kendall’s non-parametric...     

Changes in Seasonal Cycle and Extremes in China during the Period 1960–2008

Recent trends in seasonal cycles in China are analyzed, based on a homogenized dataset of daily temperatures at 541 stations during the period 1960–2008. Several indices are defined for describing the key features of a seasonal cycle, including local winter/summer (LW/LS) periods and local spring/autumn phase (LSP/LAP). The Ensemble Empirical Mode Decomposition method is applied to determine the indices for each year. The LW period was found to have shortened by 2–6 d (10 yr)-1, mainly due to an earlier end to winter conditions, with the LW mean temperature having increased by 0.2°C–0.4°C (10 yr)?1, over almost all of China. Records of the most severe climate extremes changed less than more typical winter conditions did. The LS period was found to have lengthened by 2–4 d (10 yr)?1, due to progressively earlier onsets and delayed end dates of the locally defined hot period. The LS mean temperature increased by 0.1°C–0.2°C (10 yr)-1 in most of China, except for a region in southern China centered on the mid-lower reaches of the Yangtze River. In contrast to the winter cases, the warming trend in summer was more prominent in the most extreme records than in those of more typical summer conditions. The LSP was found to have advanced significantly by about 2 d (10 yr)-1 in most of China. Changes in the autumn phase were less prominent. Relatively rapid changes happened in the 1980s for most of the regional mean indices dealing with winter and in the 1990s for those dealing with summer.     

Trends of precipitation extremes during 1960–2008 in Xinjiang, the Northwest China

The spatial–temporal variability of the precipitation extremes defined by eight precipitation indices based on daily precipitation dataset was analyzed using the linear regression method and the Mann–Kendall test. The results indicate that increasing trends in the precipitation amount, rainy days, and the intensity of the extreme precipitation were identified at above 70 % of the total rain stations considered in this study, with more than 30 % of them were significant, while most stations show notable decreasing trend in the annual maximum consecutive no-rain days. Significantly increasing trends of the precipitation extremes are observed mainly in the northern Xinjiang and the north of the southern Xinjiang. Most extreme precipitation indices show a potential regime shift starting from the middle of 1980s. The magnitude of the trends is compatible with their pattern of spatial stability. The generally increasing trends in precipitation extremes are found in this study.     

Changing structure of the precipitation process during 1960–2005 in Xinjiang, China

Using daily precipitation data spanning 1960–2005 from 51 meteorological stations in Xinjiang province, China, spatial and temporal changes in consecutive maximum wet days in the year, summer, and winter were investigated. Fifteen precipitation extreme indices, which reflect the attributes of consecutive maximum wet days, were defined, and the modified Mann–Kendall test was applied to detect the tendencies, and changes in the indices were evaluated through linear regression with the F test. Results showed that: (1) two consecutive wet days occurred most frequently in the year and summer, and the fractional contributions and precipitation intensities decreased as the duration increased; in winter, one wet day had the maximum possibility, fractional contributions decreased and intensities increased as the duration increased. (2) The possibility of consecutive wet days which had short durations reduced, while those of long durations increased; annual fractional contributions of short durations decreased, while those of long durations increased; summer and winter fractional contribution of all durations decreased first and then increased; the intensities of all durations increased. (3) The wet tendency was identified in Xinjiang; the wet trend in Southern Xinjiang was more significant than Northern Xinjiang in summer, while in winter the wet tendency in Northern Xinjiang was more pronounced.     

Spatiotemporal variations of potential evapotranspiration and aridity index in relation to influencing factors over Southwest China during 1960–2013

This study investigated the spatial–temporal patterns and trends of potential evapotranspiration (ET₀) and aridity index (AI) over Southwest China during 1960–2013 based on daily temperature, precipitation, wind speed, sunshine duration, total solar radiation, and relative humidity data from 108 meteorological stations. The Penman–Monteith model, Mann–Kendall (M–K) test, moving t test, and Morlet wavelet method were used. The results indicated that ET₀ and AI across the region displayed decreasing trends, but the former was significant. After 2000, regionally average trends in ET₀ and AI increased rapidly, indicating that droughts increased over Southwest China in recent years. Spatially, the changes of ET₀ and AI were dissimilar and not clustered, either. Temporally, both ET₀ and AI displayed obvious abrupt change points over different timescales and that of AI was during the winter monsoon period. Significant periodic variations with periods of 27, 13, and 5 years were found in ET₀, but only of 13 and 5 years existed in AI. Correlation analysis revealed that the sunshine duration and wind speed were the dominant factors affecting ET₀ and that AI showed strong negative correlation with precipitation. The findings of this study enhance the understanding of the relationship between climate change and drought in Southwest China, while the mechanism controlling the variation in drought requires further study.     

Spatiotemporal Variability of Surface Wind Speed during 1961–2017 in the Jing–Jin–Ji Region,China

Wind speed variations are influenced by both natural climate and human activities. It is important to understand the spatial and temporal distributions of wind speed and to analyze the cause of its changes. In this study, data from 26 meteorological stations in the Jing–Jin–Ji region of North China from 1961 to 2017 are analyzed by using the Mann–Kendall(MK) test. Over the study period, wind speed first decreased by-0.028 m s-1 yr-1(p 0.01) in1961–1991, and then increased by 0.002 m s1-yr1-(p 0.05) in 1992–2017. Wind speed was the highest in spring(2.98 m s-1), followed by winter, summer, and autumn. The largest wind speed changes for 1961–1991 and1992–2017 occurred in winter(-0.0392 and 0.0065 m s-1 yr1-, respectively); these values represented 36% and 58%of the annual wind speed changes. More than 90.4% of the wind speed was concentrated in the range of 1–5 m s-1,according to the variation in the number of days with wind speed of different grades. Specifically, the decrease in wind speed in 1961–1991 was due to the decrease in days with wind speed of 3–5 m s-1, while the increase in wind speed in 1992–2017 was mainly due to the increase in days with wind speed of 2–4 m s-1. In terms of driving factors,variations in wind speed were closely correlated with temperature and atmospheric pressure, whereas elevation and underlying surface also influenced these changes.     

Variability and predictability of Northeast China climate during 1948–2012

In this work, authors examine the variabilities of precipitation and surface air temperature (T2m) in Northeast China during 1948–2012, and their global connection, as well as the predictability. It is noted that both the precipitation and T2m variations in Northeast China are dominated by interannual and higher frequency variations. However, on interdecadal time scales, T2m is shifted significantly from below normal to above normal around 1987/1988. Statistically, the seasonal mean precipitation and T2m are largely driven by local internal atmospheric variability rather than remote forcing. For the precipitation variation, circulation anomalies in the low latitudes play a more important role in spring and summer than in autumn and winter. For T2m variations, the associated sea surface pressure (SLP) and 850-hPa wind (uv850) anomalies are similar for all seasons in high latitudes with significantly negative correlations for SLP and westerly wind anomaly for uv850, suggesting that a strong zonal circulation in the high latitudes favors warming in Northeast China. The predictability of precipitation and T2m in Northeast China is assessed by using the Atmospheric Model Inter-comparison Project type experiments which are forced by observed sea surface temperature (SST) and time-evolving greenhouse gas (GHG) concentrations. Results suggest that T2m has slightly higher predictability than precipitation in Northeast China. To some extent, the model simulates the interdecadal shift of T2m around 1987/1988, implying a possible connection between SST (and/or GHG forcing) and surface air temperature variation in Northeast China on interdecadal time scales. Nevertheless, the precipitation and T2m variations are mainly determined by the unpredictable components which are caused by the atmospheric internal dynamic processes, suggesting low predictability for the climate variation in Northeast China.     

Detection of trends in precipitation during 1960–2008 in Jiangxi province, southeast China

Changes in precipitation exert an enormous impact on human life, and it is of vital importance to study regular patterns of meteorological and hydrological events. In order to explore the changing spatial and temporal patterns of precipitation amounts, precipitation extremes and precipitation concentration in Jiangxi province in southeast China between 1960 and 2008, several precipitation indices series were analysed using the Mann–Kendall test in this study. Our results indicate remarkable differences among the stations with negative and positive precipitation trends at the annual, seasonal and monthly scales, significant increasing trends are mainly found during January, August, winter and summer, while significant decreasing trends mostly are observed during October and autumn. For precipitation extremes, most precipitation indices suggest that both the intensity and the days of extreme precipitation are increasing; the mean precipitation amount, especially, on a wet day shows a significant positive trend. When it comes to precipitation concentration, the monthly rainfall heterogeneity shows an insignificant downward trend, while the contribution of the days with greatest rainfall displays an insignificant upward trend. Furthermore, the long-range persistence is detected for changing process of precipitation amount, extreme precipitation and precipitation concentration using the Rescaled Range Analysis.     

Interdecadal change in the Antarctic Circumpolar Wave during 1951–2010

In this study,we defined an index of the Antarctic Circumploar Wave(ACW) and analyzed its variability for the period 1951-2010.A regime shift of the circumpolar westerly in the Southern Ocean and an interdecadal change of the ACW,which occurred around the mid-1970s,were identified.Associated with these changes,the variations of the ACW show three distinct sub-periods:1951-1973,1974-1980,and 1981-2010.They are characterized by different speeds,amplitudes,and wave structures.We briefly investigated possible mechanisms responsible for the different behaviors of the ACW during the three periods.     

Projected changes in Malawi’s growing season

Climate Dynamics - Regional climate model projections at 30-km resolution are used to predict future mid-century and late-century growing season changes over Malawi due to global warming under the...     

Discrete wavelet transform-based investigation into the variability of standardized precipitation index in Northwest China during 1960–2014

This study analyses spatio-temporal trends in precipitation, temperature, and river discharge in the northeast of Iran during recent decades (1953–2013). The Pettitt, SNHT, Buishand, Box-Pierce, Ljung-Box, and McLeod-Li methods were applied to examine homogeneity in time series studied. The nonparametric Mann-Kendall and Sen’s slope estimator tests were used to detect possible significant (p < 0.05) temporal trends in hydrometeorological time series and their magnitude, respectively. For time series with autocorrelation, the trend-free pre-whitening (TFPW) method was used to determine significant trends. To explore spatial distributions of trends, their magnitudes were interpolated by the inverse distance whitening (IDW) method. Trend analysis shows that for daily, monthly, and annual precipitation time series, 12.5, 19, and 12.5 % of the stations revealed significant increasing trends, respectively. For mean temperature, warming trends were found at 38, 23, and 31 % of the stations on daily, monthly, and annual timescales, in turn. Daily and monthly river discharge decreased at 80 and 40 % of the stations. Overall, these results indicate significant increases in precipitation and temperature but decreases in river discharge during recent decades. Hence, it can be concluded that decreasing trends in river discharge time series over the northeast of Iran during 1953–2013 are in response to warming temperatures, which increase the rate of evapotranspiration. Differences between the results of our comprehensive large-scale study and those of previous researches confirm the necessity for more model-based local studies on climatic and environmental changes across the northeast of Iran.