The mean global surface air temperature data indicate that there might be a global warming hiatus during 1998-2012. However, whether it existed around the world is still controversial, and the characteristics of the hiatus in Northwest China remain unclear. Based on the in-situ observation data of air temperature from 1960 to 2019, we analyzed the characteristic of hiatus in Northwest China through the cumulative anomaly curve, the Mann-Kendall test, Move-t test, the Yamamoto test and the linear trend estimation. The results showed that the statistically significant change-point of the annual mean air temperature in Northwest China was in 1986, 1996, and 2012, respectively. The air temperature suddenly rose in 1996, and then kept stable from 1998 to 2012. The annual mean air temperature showed an obvious cooling trend by -0.20 ℃ decade^-1 in Northwest China from 1998 to 2012. Meanwhile, the annual mean air temperature in winter had the largest decrease rate and that of summer increased. The east of Northwest China displayed the most significant cooling during 1998-2012, and the Tibetan Plateau was still heating up at the same time. The air temperature of Northwest China rose substantially after 2012, especially in winter, and southern Xinjiang experienced the strongest warming during 2012-2019. Generally speaking, the warming hiatus was evident in Northwest China during 1998-2012 except the Tibetan Plateau. Therefore, more attention should be paid to the marked upward trend in air temperature after the hiatus in Northwest China due to the crucial environment.

Since 2012, urban heat islands (UHIs) over various cities have been re-investigated under the local climate zones (LCZ) concept. However, a systematic overview of the recent progress in terms of the LCZ-based UHI studies remains lacking. This status quo has considerably restrained the UHI studies across global cities in a more standard manner. Here we comprehensively reviewed the preceding LCZ-based UHI studies with statistical- and meta-analysis. The literature review indicates that LCZ-based UHIs have been conducted over more than 130 cities globally, mostly located in the middle latitudes (35°N-55°N) within Asia and Europe. These investigations focus either on the canopy layer UHI (represented by surface air temperature, SAT) or on the surface layer UHI (denoted by land surface temperature, LST) or both. The overview was conducted mainly from three aspects including the "data acquisition", "spatiotemporal pattern", and "associated control". Our further findings show that: (1) On "data acquisition", satellite thermal remote sensing is the most important technique for retrieving LST, with the percentage of studies that employ this technique accounting for 86.5%. But for SAT, the main approaches include measurements by fixed stations (42.5%) and mobile vehicles (19.2%) as well as simulations by models (38.3%), among which the approach by model simulation has received more attention; (2) On "spatiotemporal pattern", the mean difference between the maximum and minimum temperatures among various LCZs for SAT (3.1 K) is significantly lower than that for LST (9.8 K), with relatively high magnitudes in summer and winter compared with the other seasons for these two types of temperatures.Prominent "intra-LCZ heat islands" were observed for both the canopy and surface UHIs; (3) On "associated controls", most studies are still qualitative on the analysis of the relationships between LCZ-based UHIs and their controls (e.g., surface structure and fabric, land cover type, and human activity). Other potential controls such as building typology and adjacency among LCZ types remain less considered. We finally provided several prospects for the LCZ-based UHI studies. We hope this overview would be helpful for improving the understanding of the current progress and upcoming prospects for the LCZ-based UHI studies.

The frequent occurrence of chilling injury has serious impacts on national-level food security, and it mainly affects the grain yield in Northeast China. Timely and accurate measures are desirable to assess the large-scale impacts, which are the prerequisites for disaster reduction and production recovery. Therefore, we propose a novel method to efficiently assess the impact of chilling injury on soybean. Inner Mongolia is taken as a case study. The specific chilling injury events was diagnosed to occur in 1989, 1995, 2003, 2009, and 2018. The 512 combinations of cold and field management simulation scenarios were established based on the localized CROPGRO-Soybean model. Furthermore, we constructed 1600 cold vulnerability models including CDD (Cold Growth Days), simulated LAI (Leaf Area Index) and yields from the CROPGRO-Soybean model. Finally, we extracted the maximum wide dynamic vegetation index (WDRVI) and corresponding date of the critical windows of early and late growing seasons in the GEE (Google Earth Engine) platform, converted the WDRVI into actual LAI of soybean pixel, and calculated the pixel yield and losses according to the corresponding vulnerability models. The findings show that the localized CROPGRO-Soybean model can accurately simulate the growth and development processes of soybean under different cold scenarios. The soybean yields were reduced due to changes in cold stress during the whole growth period (a decrease of 1-3 ℃), which were greater than those from the local cooling treatments (the temperature of 0 ℃ for 5 consecutive days which are randomly generated during four growth periods). Moreover, simulated historical yield losses in 1989, 1995, 2003, and 2009 were 9.6%, 29.8%, 50.5%, and 15.7%, respectively, which were very close (all errors were within one standard deviation) to the actual losses (6.4%, 39.2%, 47.7%, and 13.2%, respectively). The above proposed method was applied to evaluate the yield loss of 2018 at a pixel scale. Specifically, sentinel-2A image was used for 10 m high-precision yield mapping, and the estimated losses well characterized the actual yield losses from 2018 cold event. The results highlighted that our proposed method can efficiently and accurately assess the chilling injury impact on soybean at different spatial scales. The novel method is also effective for efficient assessment of the impacts of different disasters on other crops.

In order to study the characteristics of regional drought and flood and its impact on crop yield, this paper discusses the evolution law of drought and flood in each growth stage of crop and the impact of drought and flood in different growth stages on crop yield using the technology of information diffusion and chaotic time series analysis based on the comparison of SPEI and precipitation temperature homogenization index. With Xi'an as a typical region and corn as the research object, we analyzed the meteorological data and corn yield data from 1951 to 2015. The results show that: firstly, the trend of drought and flood in each growth stage of corn in Xi'an with time shows the form of wave crest and wavetrough alternately and a certain periodicity. Each growth stage of corn shows a trend of relative abundant water after 2008. Secondly, most of the growth stages of corn are in normal state, and the frequency is about 45%. The frequency maximum of severe drought is 4.62%, which occurred in emergence-jointing, and the frequency maximum of above moderate wetness is 15.39%, which occurred in the jointing-tasselling phase. Thirdly, the largest Lyapunov exponents of all growth phases are greater than 0. Time series of drought and flood indicate chaotic feature to a certain extent. Finally, the jointing-tasselling stage is compared with other growth stages, and the correlation between yield and drought and flood is obvious, which reflects the sensitivity of this stage to water to some extent. This research is of guiding implications to disaster prevention and yield reduction of corn in Xi'an city.

The occurrence and development of global active fires under the background of global warming is an important research content. Based on the Moderate Resolution Imaging Spectroradiometer (MODIS) C6 active fire point vector data (2001-2018) of Indonesia provided by the Fire Information Resource Management System (FIRMS) of the USA, the occurrence probability, intensity and response to the El Niño of Indonesian active fires were quantified and analyzed using the GIS-based fishnet method at a 1 km×1 km grid system, in order to reveal the spatio-temporal variations of active fire occurrence frequency in Indonesia during 2001-2018. The results showed that: (1) A total area of 22.79% was affected by active fire at least once in the past 18 years, which is called as "fire-affected area", while the rest was not impacted by fire according to the MODIS observations. The proportions of "fire-affected area" in the five major islands in a descending order were 32.93% for Kalimantan, 31.44% for Sumatra, 17.16% for Sulawesi, 9.50% for Java and 7.58% for Papua, respectively. The occurrence of active fire was dominated by low probability (1/18-6/18), typically between August and October, and widely distributed in various islands, which was primarily seen in Kalimantan and Sumatra. The number of grids in a medium probability (7/18-12/18) was small but intensively distributed, especially in the eastern lowland plains of Sumatra and the southern and southwestern coasts of Kalimantan. The girds of high probability were sporadically distributed in Indonesian islands, mostly concentrated in Java and Sulawesi. (2) The intensity of active fire was dominated by level-one (once per year) and level-two (2-3 times/year), followed by level-three (4-7 times/year). The active fires of level-one to level-five (1-22 times/year) were widely distributed in various islands, and primarily seen in Kalimantan and Sumatra, while the active fires (23-165 times/year) of level-six were concentrated in Java, Sumatra and Sulawesi. It is worth noting that the distribution of grids with different intensities diminished from the center to the periphery. In addition, the intensities of active fires in different probability groups were different. The low-probability of active fire was mainly 1 time/year, followed by 1-3 and 2-7 times/year for the medium and high probability, respectively. In particular, the intensity of level-six active fire only was observed in high probability grids. (3) Indonesia's active fires between August and October had different sensitivities to strong and weak El Niño, showing increased frequency and area of active fires. The stronger an El Niño event is, the higher the response of active fire will be. The islands in a descending order of sensitivity to active fire were Sumatra, Sulawesi, Kalimantan, Java and Papua.

This paper used HEC-HMS hydrological model and statistical analysis method to examine the relationship between flood eigenvalues (i.e. flood volume, peak flow) and landscape pattern indexes of different landscapes. And on the basis of the above relationships, this paper constructed a flood ecological risk index to quantitatively calculate the basin's flood-landscape ecological risk. Then, the spatio-temporal risk change analysis of the whole basin and comparative risk analysis between selected sub-basins were performed. The Qinhuai River basin was selected as the study area, and two historical landscape distributions (2003 and 2017) were used in this study. The results showed that, for different landscapes, there are certain relationships between landscape patterns and flood eigenvalues, for different landscapes, the response indexes and degrees are different. From 2003 to 2017, the flood-landscape ecological risk increased and showed significant spatial differences. Landscape patterns have significant impacts on regional floods. In urbanization process, avoiding forming large-scale landscape patches, increasing landscape abundance of landscapes, and increasing contact area between different types of landscape patches can be helpful to reduce the negative effects of the increase of urban landscape area on flood.

Environmental stress is used to indicate the integrated pressure on regional environmental system caused by various pollutant outputs during human life and production activities. Based on the pollutant emission and socio-economic database of the counties in Beijing-Tianjin-Hebei (BTH) region, this paper comprehensively calculates the environmental stress index (ESI) by entropy weight method at the county scale, and analyzes the spatio-temporal pattern and the differences among four types of Major Functional Zones (MFZ) in this region from 2012 to 2016. In addition, the socio-economic driving forces of environmental stress is quantitatively estimated by means of geographical weighted regression (GWR) method based on the STIRPAT model framework. The results show that: (1) The situation of environmental stress in the BTH region had been significantly alleviated, with an ESI decline of 54.68% since 2012. The decline was most significant in central urban areas of Beijing, Tangshan, Tianjin and Shijiazhuang, and Binhai New District. The degree of environmental stress in counties decreased gradually from the central urban areas to the suburban areas, and the high-level stress counties were eliminated in 2016. (2) The spatial spillover effect of environmental stress had been further enhanced on the county scale since 2012, and the spatial locking and path dependence emerged in cities of Tangshan and Tianjin. (3) Urbanized zones (development-optimized and development-prioritized zones) are the major bearing areas of environmental pollutants in the BTH region, with ESI accounting for 65.98% of the whole region, which should be focused on prevention and control of environmental pollution. (4) The controlling factors of environmental stress in counties include population size and economic development level. In addition, technical capacity of environmental disposal, agricultural production input intensity, territorial development intensity and urbanization had a certain degree of influence. (5) There was spatial heterogeneity in the driving effects of various driving factors on the environmental stress. Therefore, it is necessary to adopt differentiated environmental governance and reduction countermeasures from emission sources, according to the intensity and spatial difference of driving forces, so as to improve the accuracy and adaptability of environmental collaborative control in the BTH region.