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AbstractClimate elements are important indicators of climate change in China's main grainproducing areas during the April–September growth season and affect the growth and yield of crops. This paper combines grain concentration and geographical detector to divide the North and South regions of China's main grain production. The linear trend and Morlet wavelet transform methods are used to analyse the characteristics of climate change based on observational climate data from April to September 1981–2015. The results show that the climate in the North region is warm and dry during the growth season, whereas the climate is warm and humid in the South region. The main periods of the change in temperature in the North and South regions are 3 years, and that in precipitation is 5 years, and that in sunshine hours is 3-4 years. Changes in the climate elements in various provinces show complex, varying and regional characteristics of cold-warm and dry-wet cycles. The changes in climate elements are significant and different climatic conditions and regions have variouspossible impacts on grain production in China during the growth season. For China's agricultural-economy sustainable development and grain security, the study suggests that governments should place more emphasis on climatic elements changes during the growth season, and invest more money in disaster prevention and mitigation, especially in the main grain producing areas.Key words: grain-producing regions; changes in climate elements; growth season; climate trend50 coefficient; climate tendency rate; wavelet analysis [ABSTRACT FROM AUTHOR]

The cloud feedback is very important for climate change. In this paper, the long-term variability of clouds in East Asia and their influence on the radiation budget are studied quantitatively by analyzing satellite observations, so as to determine the cloud feedback on regional warming. We firstly analysis the 18-year's (Mar.2000-Feb.2018) trend of cloud optical thickness (COT) over East Asia based on the retrievals of the Moderate Resolution Imaging Spectrometer (MODIS), and calculate the cloud radiative forcing of water cloud and ice cloud using BCC_RAD radiation transfer model based on the COTs, and then discuss the impact of COT's variation on the cloud radiative forcing. The water cloud COTw is found to increase in northeast China (~0.05 per year) and east China sea (~0.05 per year), and to decrease at south China (~-0.07 per year) and south Japan (~-0.05 per year). The ice cloud COTi is found to increase at northeast China (~0.06 per year) and north Japan (~0.08 per year), whereas decrease significantly at Tibetan plateau (~-0.07 per year). The annual mean shortwave-, longwave- and net-radiative forcing caused by the water cloud in East Asia at the top of the atmosphere are -72.4 W m-2, 15.7 W m-2 and -56.7 W m-2, respectively; the corresponding forcing caused by ice cloud are -88.5 W m-2, 55.7 W m-2 and -32.7 W m-2 respectively. The effects of COTw and COTi variations on radiation in different regions are different remarkably. Both positive feedback (e.g. south China, 0~0.4 W m-2 per year) and negative feedback (e.g. northeast China, -0.4~0 W m-2 per year) occurs, which indicates that the cloud feedback to regional warming is significant and may be opposite at different areas. [ABSTRACT FROM AUTHOR]

Spatio-temporal variations in precipitation are affecting agricultural production in China in the context of climate change. Based on daily precipitation data from 63 national meteorological stations on the Huang-Huai-Hai Plain from 1963 to 2012, this paper analysed the spatio-temporal variations in precipitation in terms of precipitation days and intensity, using spatial interpolation, linear trend estimation and wavelet analysis. The results indicated that: (i) from 1963 to 2012, the number of annual precipitation days and intensity decreased gradually from the southeast to the northwest. Additionally, the distribution of the extreme precipitation index was similar to that of the annual precipitation index; (ii) the number of annual precipitation days and heavy precipitation days gradually decreased, while precipitation intensity and extreme precipitation days and extreme rainfall intensity remained relatively stable or decreased. The spatial patterns of annual variation trends were considerably different. The annual precipitation days and intensity trends are consistent with the overall trend, while that of the extreme rainfall index in some regions differs from the overall trend; (iii) the precipitation index displayed different periodic oscillations during the period, and the precipitation index values differed at different time scales. However, all the precipitation index values exhibited a 28-yr oscillation. [ABSTRACT FROM AUTHOR]

Articles in the issue are introduced including a paper by Schmidt et al. on use of the Hubble Space Telescope to characterize the protoplanet 2 Pallas located in the main asteroid belt, a paper by Cheng et al. on dating of rocky cave deposits in China that are indicative of climate history, and a paper by Ji et al. on ear-related anatomical distinctions in mammals.

In this paper, we study the spatiotemporal characteristics of precipitable water, precipitation, evaporation, and water–vapor flux divergence in different seasons over northeast China and the water balance of that area. The data used in this paper is provided by the European Center for Medium-Range Weather Forecasts (ECMWF). The results show that the spatial distributions of precipitable water, precipitation, and evaporation feature that the values of elements above in the southeastern area are larger than those in the northwestern area; in summer, much precipitation and evaporation occur in the Changbai Mountain region as a strong moisture convergence region; in spring and autumn, moisture divergence dominates the northeast of China; in winter, the moisture divergence and convergence are weak in this area. From 1979 to 2010, the total precipitation of summer and autumn in northeast China decreased significantly; especially from 1999 to 2010, the summer precipitation always demonstrated negative anomaly. Additionally, other elements in different seasons changed in a truly imperceptible way. In spring, the evaporation exceeded the precipitation in northeast China; in summer, the precipitation was more prominent; in autumn and winter, precipitation played a more dominating role than the evaporation in the northern part of northeast China, while the evaporation exceeded the precipitation in the southern part.The Interim ECMWF Re-Analysis (ERA-Interim) data have properly described the water balance of different seasons in northeast China. Based on ERA-Interim data, the moisture sinks computed through moisture convergence and moisture local variation are quite consistent with those computed through precipitation and evaporation, which proves that ERA-Interim data can be used in the research of water balance in northeast China. On a seasonal scale, the moisture convergence has a greater influence than the local moisture variation on a moisture sink, and the latter is variable slightly, generally as a constant. Likewise, in different seasons, the total precipitation has a much greater influence than the evaporation on the moisture sink. [ABSTRACT FROM AUTHOR]

In their 2008 paper entitled “Impact of recent climatic change …”, Xiao et al. [Xiao, G., Zhang, Q., Yao, Y., Zhao, H., Wang, R., Bai, H., Zhang, F., 2008. Impact of recent climatic change on the yield of winter wheat at low and high altitudes in semi-arid northwestern China. Agric. Ecosyst. Environ. 127, 37–42] presented evidence for increasing grain yield of winter wheat (Triticum aestivum L.) from 1981 to 2005 at two locations in China, as well as for non-linear effects of rainfall and mean temperature on yield. Inspection of their graphs suggested that the responses were overstated. Reanalysis of five graphs indicated that yield had increased at just one site, that there was no effect of rainfall, and that mean temperature only affected yield at the higher site. This temperature effect was described with an exponential function (r 2 =0.32), but the response could equally be considered linear (r 2 =0.27). Overall, the reanalyses suggest that four described relations were incorrect due to errors in analysis or reporting. The results highlight the difficulties with using regression with historic data to detect effects of climatic change on agriculture. [Copyright &y& Elsevier]