Simulated Effects of Cropland Expansion on Summer Climate in Eastern China in the Last Three Centuries

To understand the effects of the land use/cover changes due to agricultural development on summer climate in Eastern China, four 12-year simulations using the WRF-SSiB model were performed. We found that agricultural development resulted in warming and rainy effects. In the middle to lower reaches of the Yellow River and the Yangtze River, the warming effects were approximately 0.6°C and resulted from increased surface net radiation and sensible heat fluxes. In Northeast China, the warming effects were very small due to increases in latent heat fluxes which resulted from the extensive conversion from grassland to cropland. The rainy effect resulted from increases in convective rainfall, which was associated with a warming surface in certain areas of the Yellow River and Yangtze River and a large increase in the surface moisture flux in Northeast China. Conversely, in the middle to lower reaches of the Yellow River and the Yangtze River, the grid-scale rainfall decreased because the climatological northward wind, which is moist and warm, was partially offset by a southward wind anomaly. These findings suggest that the agricultural development left footprints not only on the present climate but also on the historical climate changes before the industrial revolution

Comparison of Satellite and Ground-Based Phenology in China’s Temperate Monsoon Area

Continuous satellite datasets are widely used in tracking vegetation responses to climate variability. Start of season (SOS), for example, can be derived using a number of methods from the time series of satellite reflectance data; however, various methods often produce different SOS measures which limit the application of satellite data in phenological studies. Therefore, we employed five methods to estimate SOS from the Advanced Very High Resolution Radiometer (AVHRR)/normalized difference vegetation index (NDVI) dataset. Subsequently, we compared the SOS with the ground-based first leaf date (FLD) of 12 deciduous broadleaved plant species at 12 sites of the Chinese Phenological Observation Network (CPON). The results show that the latitudinal patterns of five satellite-derived SOS measures are similar to each other but different from the pattern of ground phenology. For individual methods, the variability of SOS time series is significantly different from ground phenology except for HANTS, Polyfit, and Midpoint methods. The SOS calculated using the Midpoint method showed significant correlations with ground phenophases most frequently (in 47.1% of cases). Using the SOS derived from the Midpoint method, significantly earlier trends in SOS were detected in 50.7% of the natural vegetation area from 1982 to 2006

Variation of Main Phenophases in Phenological Calendar in East China and Their Response to Climate Change

Based on the phenological data from China Phenological Observation Network, we compiled the phenological calendars of 3 phenological observation stations (Shanghai, Nanjing, and Hefei) in East China for 1987–1996 and 2003–2012 according to the sequences of mean phenophases. We calculated the correlated coefficient and the root mean square error (RMSE) between phenophases and the beginning of meteorological seasons to determine the beginning date of phenological season. By comparing new phenological calendars with the old ones, we discussed the variation of phenophases and their responses to temperature. The conclusions are as follows. (1) The beginning dates of spring and summer advanced, while those of autumn and winter delayed. Thus, summers got longer and winters got shorter. (2) The beginning time of the four phenological seasons was advancing during 1987–1996, while it was delaying during 2003–2012. (3) Most spring and summer phenophases occur earlier and most autumn and winter phenophases occur later in 2003–2012 than in 1987–1996. (4) The beginning time of phenological seasons was significantly correlated with temperature. The phenological sensitivities to temperature ranged from −6.49 to −6.55 days/°C in spring, −3.65 to −5.02 days/°C in summer, 8.13 to 10.27 days/°C in autumn, and 4.76 to 10.00 days/°C in winter

Crop Yield and Temperature Changes in North China during 601–900 AD

Depending on the descriptions of crop yield and social response to crop failure/harvest from Chinese historical documents, we classified the crop yield of North China during 601–900 AD into six categories and quantified each category to be the crop yield grades. We found that the regional mean crop yield had a significant (P<0.01) negative trend at the rate of −0.24% per decade. The interannual, multiple-decadal, and century-scale variability accounted for ~47%, ~30%, and ~20% of the total variations of crop yield, respectively. The interannual variability was significantly (P<0.05) persistent across the entire period. The multiple-decadal variability was more dominant after 750 AD than that before 750 AD, while the century-scale variability was more dominant before 750 AD than that after 750 AD. The variations of crop yield could be partly explained by temperature changes. On one hand, the declining trend of crop yield cooccurred with the climate cooling trend from 601 to 900 AD; on the other hand, the crop yield was positively correlated with temperature changes at 30-year resolution with the correlation coefficient of 0.59 (P<0.1). These findings supported that high (low) crop yield occurred in the warming (cooling) climate

Based on the phenological data from China Phenological Observation Network, we compiled the phenological calendars of 3 phenological observation stations

according to the sequences of mean phenophases. We calculated the correlated coefficient and the root mean square error (RMSE) between phenophases and the beginning of meteorological seasons to determine the beginning date of phenological season. By comparing new phenological calendars with the old ones, we discussed the variation of phenophases and their responses to temperature. The conclusions are as follows

Spatiotemporal Simulation of Tourist Town Growth Based on the Cellular Automata Model: The Case of Sanpo Town in Hebei Province

Spatiotemporal simulation of tourist town growth is important for research on land use/cover change under the influence of urbanization. Many scholars have shown great interest in the unique pattern of driving urban development with tourism development. Based on the cellular automata (CA) model, we simulated and predicted the spatiotemporal growth of Sanpo town in Hebei Province, using the tourism urbanization growth model. Results showed that (1) average annual growth rate of the entire region was 1.5 Ha2 per year from 2005 to 2010, 4 Ha2 per year from 2010 to 2015, and 2.5 Ha2 per year from 2015 to 2020; (2) urban growth rate increased yearly, with regional differences, and had a high degree of correlation with the Euclidean distance of town center, traffic route, attractions, and other factors; (3) Gougezhuang, an important village center in the west of the town, demonstrated traffic advantages and increased growth rate since 2010; (4) Magezhuang village has the largest population in the region, so economic advantages have driven the development of rural urbanization. It showed that CA had high reliability in simulating the spatiotemporal evolution of tourist town, which assists the study of spatiotemporal growth under urbanization and rational protection of tourism resources