Multidecadal variability in local growing season during 1901–2009

Abstract

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.

Changes in the Local Growing Season in Eastern China during 1909-2012

“…The present study shows a historical perspective of changes in growing season in China. Xia et al (2013) found that multidecadal variability in LGS indices could be linked to the Atlantic Multidecadal Oscillation (AMO), which is expressed as the multidecadal variations of the North Atlantic sea surface temperature with a period of about 65−80 years and amplitude of 0.4°C (Schlesinger and Ramankutty 1994;Trenberth and Shea 2006). They suggested that the AMOrelated multidecadal variability accelerates the lengthening of LGS in the Northern Hemisphere by about 53% for the last three decades.…”

“…The Ds (De) shows an advancing (delaying) rate of about −2.0 (1.5) days per decade for the period 1965−2012, leading to a lengthening of LGS with a rate of about 3.5 days per decade. et al 2011 ;Xia et al 2013). EEMD is also efficient for obtaining the long-term trend and multidecadal variability component in the climate series , which are focused on by the present study.…”

“…The same is concluded for De (Fig 2b). Xia et al (2013) showed that the linear relationship is almost constant throughout the last century, by analyzing the longterm (1901−2008) daily temperature series at 9 stations over the world. Therefore, it is feasible to estimate changes in LGS back to the 19th century, by using the linear relationship estimated from the latest data-rich era and long-term monthly mean temperature data.…”

“…For each year, the start (Ds) of LGS is the date when local temperature rises above Tm in the spring (in April) and the end (De) of LGS is the date when local temperature falls below Tm in the autumn (in October). We will investigate the long-term LGS variation following steps (1) to obtain the Ds and De time series for 1960−2011, by using the daily temperature records at each station; (2) to calculate the linear relationship between Ds and April temperature and that between De and October temperature (using the method developed by Xia et al 2013), based on the daily dataset for 1960−2011; (3) to reconstruct the long-term (back to the 19th century) series of Ds and De, by using the linear relationship and monthly temperature at each station; and (4) to calculate the long-term variations of Ds and De.…”

“…Yet this has not been well studied due to the lack of long-term daily observations. Xia et al (2013) found a good linear relationship between the start (end) date of local growing season (LGS, a definition made by Christidis et al 2007) and the monthly mean temperature in April (October) by analyzing the global gridded daily temperature data for the period 1960−1999. This enabled them to reconstruct the time series of the LGS indices (start and end) over the world for the period 1901−2009, by using that linear relationship and monthly (April and October) mean temperature data.…”