Global warming has contributed to the extension of the growing season in North Hemisphere. In this paper, we investigated the spatial characteristics of the date of the start of the season (SOS), the date of the end of the season (EOS) and the length of the season (LOS) and their change trends from 1982 to 2015 in Northeast China. Our results showed that there was a significant advance of SOS and a significant delay of EOS, especially in the north part of Northeast China. For the average change slope of EOS in the study area, the delay trend was 0.25 d/y, which was more obvious than the advance trend of −0.13 d/y from the SOS. In particular, the LOS of deciduous needleleaf forest (DNF) and grassland increased with a trend of 0.63 d/y and 0.66 d/y from 1982 to 2015, indicating the growth season increased 21.42 and 22.44 days in a 34-year period, respectively. However, few negative signals were detected nearby Hulun Lake, suggesting that the continuous climate warming in the future may bring no longer growing periods for the grass in the semiarid areas as the drought caused by climate warming may limit the vegetation growth.

No abstract

Coal mining subsidence is a common human geological disaster that was particularly conspicuous in China. It seriously restricts the sustainable development of mining areas, and it not only damages land resources but also triggers a series of ecological and environmental problems that may result in social and economic issues. This report studied the coal mining subsidence area of Longkou in Shandong province and uses digital elevation data (DEM) of the mining area before subsidence in 1978 as the baseline elevation. Through image algorithms, we obtained coal mining subsidence region data for 1984, 1996, 2000, and 2004. And with spatial data sources of the same period of TM/ETM ? and SPOT5 remote sensing images, BP artificial neural network (BPNN) classification is used to extract surface landscape information in the subsidence area. With the support of GIS technology, superimposing subsidence area on the surface landscapeusing the largest landscape ecology patch index, landscape shape index, landscape condensation index, and the index of landscape distribution-report analyzes the mining landscape changes before and after subsidence. This study also carries on exploratory research with the landscape changes, thereby providing a scientific basis for integrated prevention and treatment.

Numerous studies have documented the effects of irrigation on local, regional, and global climate. However, most studies focused on the cooling effect of irrigated dryland in semiarid or arid regions. In our study, we focused on irrigated paddy fields in humid regions at mid to high latitudes and estimated the effects of paddy field expansion from rain-fed farmland on local temperatures based on remote sensing and observational data. Our results revealed much significant near-surface cooling in spring (May and June) rather than summer (July and August) and autumn (September), which was −2.03 K, −0.73 K and −1.08 K respectively. Non-radiative mechanisms dominated the local temperature response to paddy field expansion from rain-fed farmland in the Sanjiang Plain. The contributions from the changes to the combined effects of the non-radiative process were 123.6%, 95.5%, and 66.9% for spring (May and June), summer (July and August), and autumn (September), respectively. Due to the seasonal changes of the biogeophysical properties for rain-fed farmland and paddy fields during the growing season, the local surface temperature responses, as well as their contributions, showed great seasonal variability. Our results showed that the cooling effect was particularly obvious during the dry spring instead of the warm, wet summer, and indicated that more attention should be paid to the seasonal differences of these effects, especially in a region with a relatively humid climate and distinct seasonal variations.

The irrigated paddy fields have expanded greatly at semi-arid western Jilin province of China in recent over ten years, the sources of which are rain-fed cornfields, swamp meadow and saline alkali land mainly. Based on regional land use data, remote sensing data and meteorological data, this paper evaluates the land surface temperature changes response to land surface biophysical processes changes resulting from land use change (LUC), and dissociates the effect of radiative change (albedo) and non-radiative change (evapotranspiration and turbulent process) quantitatively using the energy redistribution factor. The results show that, the total land surface temperature changes based on energy redistribution factor are consistent with that based on remote sensing data on the whole, which have significant and different seasonal variations for agriculture adjustment of rain-fed cornfields to irrigated paddy fields and nature land reclamation. Generally, the largest Land surface temperature changes (ΔTs) are most pronounced in May and June for agriculture adjustment of rain-fed cornfields to irrigated paddy fields, which is −1.85 K averagely. Notable decline of albedo from saline alkali land to irrigated paddy fields in April to June greatly counteracts the cooling effect of non-radiative processes changes, while the largest ΔTs is found of −2. 54 K in dry summer months of July and August. For swamp meadows to irrigated paddy fields, non-radiative process is strengthened from June to September, the cooling effect of which is −1.69 K averagely. This study provides a case reference of local temperature change and obvious changes of land surface non-radiative terms at semi-arid area for adjustment of agricultural activities and land use changes.

The warming or cooling effects on regional climate in response to early land use change may be strengthened, weakened, or eliminated by the same or opposite effect in the subsequent land use/management period. Taking the Sanjiang Plain in China as our study area, this paper analyzed the surface temperature change due to land use/land management changes from the mid‐1950s to 2015, based on the land surface temperature response model and the observation minus reanalysis (OMR) method using remote sensing data, meteorological observation data, and reanalysis data. Results revealed a magnitude of monthly mean land surface warming up to 1.31 °C due to the land use change from wetland to rain‐fed farmland and a cooling effect of −1.32 °C caused by the land management change from rain‐fed farmland to paddy fields during the growing season. The trends were confirmed using OMR method. Land surface temperature change based on remote sensing data was divided into radiative and nonradiative forcing. The nonradiative processes play a dominant role in regulating the local surface temperature. The monthly mean temperature differences in response to land use changes differ greatly during the growing season. The temperature difference was greater in May and June (spring) than in July and August (summer). Our study shows that the land use impact on regional climate could be switched dramatically, and it would be basically consistent with the impact of natural wetlands before reclamation in our study area right now, which provides important information for mitigating and adapting to global climate change at regional scale.

Land cover change, as one of the most important driving forces to climate change, has become the research focus of the global environmental change research and global land project. More researchers studied on the global influence of Land-Use and Land-Cover Change and proved that land use change occurred at different temperature zones may produce different climate effects. For example, deforestation in tropical areas would lead to higher temperatures as the decreasing of evapotranspiration caused by the reduction of roughness and the decreasing of drag coefficient and leaf area index while, in boreal areas, similar deforestation would cause lower temperature as the increasing of albedo particularly during winter with the snow cover. However, the impact of deforestation in the temperate regions on the climate still existed uncertainty and the impacts of deforestation at different humidity conditions on climate has not explored yet. From this perspective, this article used Weather Research and Forecasting model to simulate the impact of deforestation on the temperature of Northeastern China. In this study, we designed two scenarios in July and December, respectively: One was simulated without human intervention, and the second one was simulated with the current forest covers. The results showed that the temperature in both summer and winter showed a decreasing trend when the conversion of forest to farmland occurred in northeastern China. In order to further explore the humidity impacts on the temperature, we performed sample analysis on humid, sub-humid, and semiarid regions. According to the results, the maximum variation of temperature was found in humid areas, especially in December when the temperature decreased around 4-5°C, while the change in semi-arid and sub-humid areas is relatively small.

In the context of global climate change, the extent of snow cover in Siberia has significantly decreased since the 1970s, especially in spring. The changes of snow cover at middle and high latitudes have significant impacts on the meteorological and hydrological processes because the snow cover can affect the surface energy, water balance, and the development of the atmospheric boundary layer. In this paper, the temporal and spatial changes in snow cover were firstly estimated based on a long time series of remote sensing snow cover data, both showing a decreased trend. Based on this, we estimated the radiative forcing caused by the snow cover changes from the 1970s to the 2010s and compared it with the radiative forcing caused by the vegetation cover changes over the same time period in Siberia, indicating that the snow cover changes in Siberia can accelerate climate warming and the vegetation cover changes here have the opposite effect. Furthermore, the snow cover changes may play a more important role than the vegetation cover changes in regulating the surface radiation balance in Siberia on the regional scale.