Abstract:The effect of urbanization on the urban thermal environment (UTE) has attracted increasing research attention for its significant relationship to local climatic change and habitat comfort. Using quantitative thermal remote sensing and spatial statistics methods, here we analyze four Landsat TM/ETM+ images of Guangzhou in South China acquired respectively on 13 October 1990, 2 January 2000, 23 November 2005, and 2 January 2009, to investigate the spatiotemporal variations in the land surface temperature (LST) over five land use/land cover (LULC) types and over different urban/rural zones. The emphases of this study are placed on the urban heat island (UHI) intensity and the relationships among LST, the normalized difference built-up index (NDBI), and the normalized difference vegetation index (NDVI). Results show that: (1) the UHI effect existed obviously over the period from 1990 to 2009 and high temperature anomalies were closely associated with built-up land and densely populated and heavily industrialized districts; (2) the UHI intensities represented by the mean LST difference between the urban OPEN ACCESSRemote Sens. 2012, 4 2034 downtown area and the suburban area were on average 0.88, 0.49, 0.90 and 1.16 K on the four dates, at the 99.99% confidence level; and (3) LST is related positively with NDBI and negatively with NDVI. The spatiotemporal variation of UTE of Guangzhou could be attributed to rapid urbanization, especially to the expanding built-up and developing land, declining vegetation coverage, and strengthening of anthropogenic and industrial activities which generate increasing amounts of waste heat. This study provides useful information for understanding the local climatic and environment changes that occur during rapid urbanization.

The Weather Research Forecasting model is applied for convection-permitting regional climate simulations over the western United States using three different land surface schemes (Noah, NoahMP, and CLM). Simulated precipitation, temperature, and snow water equivalent (SWE) are evaluated by comparing against Snow Telemetry (SNOTEL) and Parameter-elevation Regressions on Independent Slopes Model (PRISM) observations. The results show that all simulations realistically reproduce the spatial and temporal variability of precipitation without significant sensitivity to the choice of land surface scheme, even though they tend to overestimate the magnitude of the SNOTEL data by about 15%. Comparing the bias with respect to the SNOTEL data, CLM is superior in 2 m maximum temperature, while NoahMP is most skillful in 2 m minimum temperature. Land surface parameterizations have high impacts on snowpack simulations. The SWE peaks too early with an unrealistically low value and also ablates too fast in Noah. NoahMP improves the SWE estimate to some extent, and CLM best represents the observations. Overall, CLM and NoahMP outperform Noah. Further analysis reveals that these differences are largely attributed to distinct rainfall-snowfall partitioning, snow albedo treatment, vegetation treatment, and surface data in these schemes.

Patterns of biomass and carbon (C) storage distribution across Chinese pine (Pinus tabulaeformis) natural secondary forests are poorly documented. The objectives of this study were to examine the biomass and C pools of the major ecosystem components in a replicated age sequence of P. tabulaeformis secondary forest stands in Northern China. Within each stand, biomass of above- and belowground tree, understory (shrub and herb), and forest floor were determined from plot-level investigation and destructive sampling. Allometric equations using the diameter at breast height (DBH) were developed to quantify plant biomass. C stocks in the tree and understory biomass, forest floor, and mineral soil (0–100 cm) were estimated by analyzing the C concentration of each component. The results showed that the tree biomass of P. tabulaeformis stands was ranged from 123.8 Mg·ha–1 for the young stand to 344.8 Mg·ha–1 for the mature stand. The understory biomass ranged from 1.8 Mg·ha–1 in the middle-aged stand to 3.5 Mg·ha–1 in the young stand. Forest floor biomass increased steady with stand age, ranging from 14.9 to 23.0 Mg·ha–1. The highest mean C concentration across the chronosequence was found in tree branch while the lowest mean C concentration was found in forest floor. The observed C stock of the aboveground tree, shrub, forest floor, and mineral soil increased with increasing stand age, whereas the herb C stock showed a decreasing trend with a sigmoid pattern. The C stock of forest ecosystem in young, middle-aged, immature, and mature stands were 178.1, 236.3, 297.7, and 359.8 Mg C ha–1, respectively, greater than those under similar aged P. tabulaeformis forests in China. These results are likely to be integrated into further forest management plans and generalized in other contexts to evaluate C stocks at the regional scale.

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Forest lightning fire is a recurrent and serious problem in the Daxinganling Mountains of northeastern China. Information on the spatial distribution of fire danger is needed to improve local fire prevention actions. The Maxent (Maximun Entropy Models), which is prevalent in modeling habitat distribution, was used to predict the possibility of lightning fire occurrence in a 1 × 1 km grid based on history fire data and environment variables in Daxinganling Mountains during the period 2005-2010.We used a jack-knife test to assess the independent contributions of lightning characteristics, meteorological factors, topography and vegetation to the goodness-of-fit of models and evaluated the prediction accuracy with the kappa statistic and AUC (receiver operating characteristic curve) analysis. The results showed that rainfall, number of strikes and lightning current intensity were major factors, and vegetation and geographic variable were secondary, in affecting lightning fire occurrence. The predicted model performs well in terms of accuracy, with an average AUC and maximum kappa value of 0.866 and 0.782, respectively, for the validation sample. The prediction accuracy also increased with the sample size. Our study demonstrated that the Maxent model can be used to predict lightning fire occurrence in the Daxinganling Mountains. This model can provide guidance to forest managers in spatial assessment of daily fire danger. OPEN ACCESSForests 2015, 6 1423

[1] To examine the potential sensitivity of the Huang-Huai-Hai Plain (3H) region of China to potential changes in future precipitation and temperature, a hydrological evaluation using the VIC hydrological model under different climate scenarios was carried out. The broader perspective is providing a scientific background for the adaptation in water resource management and rural development to climate change. Twelve climate scenarios were designed to account for possible variations in the future with respect to the baseline of historic climate patterns. Results from the six representative types of climate scenarios (+2 C and +5 C warming, and 0%, +15%, À15% change in precipitation) show that rising temperatures for normal precipitation and for wet scenarios (+15% precipitation) yield greater increased evapotranspiration in the south than in the north, which is confirmed by the remaining six scenarios described below. For a 15% change in precipitation, the largest increase or decrease of evapotranspiration occurs between 33 and 36 N and west of 118 E, a region where evapotranspiration is sensitive to precipitation variation and is affected by the amount of water available for evaporation. Rising temperatures can lead to a south-to-north decreasing gradient of surface runoff. The six scenarios yield a large variation of runoff in the southern end of the 3H, which means that this zone is sensitive to climate change through surface runoff change. The Jiangsu province in the southeastern part of the 3H region shows an obvious sensitivity in soil moisture to climate change. On a regional mean scale, the hydrological change induced by the increasing precipitation from 15% to 30% is more obvious than that induced by greater warming of +5 C relative to +2 C. These simulations identify key regions of sensitivity in hydrological variation to climate change in the provinces of 3H, which can be used as guides in implementing adaptation.Citation: Dan, L., J. Ji, Z. Xie, F. Chen, G. Wen, and J. E. Richey (2012), Hydrological projections of climate change scenarios over the 3H region of China: A VIC model assessment,

& Introduction Siberian larch (Larix sibirica) is a highly climate sensitive species. Presently, the Altay Mountains is covered by widespread forests dominated by Siberian larch and thus has a great potential for dendroclimatological studies. However, tree-ring network of the Altay Mountains has not yet been well developed. The development of the new chronologies and the knowledge about the influence of climatic variables on tree growth is needed. & Method X-ray densitometric techniques were applied to obtain ring width (RW) and maximum latewood density (MXD) of Siberian larch from two upper tree line sites in the Altay Mountains, China. Climatic responses in ring widths and maximum latewood densities from the Altay Mountains (China, Russia, and Mongolia) were investigated by simple correlation analyses. To assess the common growth forces among the individual sites of the Altay Mountains, simple correlation, principal component analyses, and spatial correlation analysis were applied over the common period of the chronologies. & Results Ring width and maximum latewood density increases with decreasing precipitation, increasing temperature from late spring to late summer during the growing season. Based on the results of principal component analyses and spatial correlation analysis, summer temperature (June-July) is the most important forces on the Siberian larch growth of the Altay Mountains. The growth of Siberian larch in the Altay Mountains captures the current warming trend. The growth of Siberian larch did not clearly lose its sensitivity under most recent warming in our study areas. & Conclusions The new MXD chronologies is presently the longest, absolutely dated, tree-ring density record yet developed from China. The climate response analysis shows that the RW and MXD of Siberian larch have strong responses to temperature in the growing season. Thus, MXD and RW of Siberian larch provides the best information for climate reconstruction in the warm season. Tree-rings of Siberian larch allow detecting the recently observed warming trend and putting it into the long-term climatic context in the Altay Mountains, due to the strong growth sensitivity to temperature change.

Climate change has influenced the glaciers and water resources in the Hindukush‐Karakorum‐Himalaya region. The relatively short instrumental record of northern Pakistan makes long‐term climate change assessments difficult. In this paper, tree‐ring width chronologies were developed from two stands of spruce species (Picea smithiana) in the Karakoram region of northern Pakistan. The results of the correlation analysis revealed that tree‐ring growth of spruce was limited by annual (June–May) precipitation. Based on the regional chronology, we developed an annual precipitation reconstruction for the period 1540–2016 CE. The precipitation reconstruction equation accounts for 40% of the regional precipitation variance during the instrumental period 1946–2016. Dry episodes with rainfall below the 477‐year average occurred from 1569 to 1577, 1598 to 1612, 1621 to 1621, 1638 to 1654, 1673 to 1680, 1697 to 1720, 1728 to 1739, 1753 to 1761, 1777 to 1793, 1801 to 1840, 1860 to 1874, 1914 to 1932, 1960 to 1985, 1998 to 2011. Wet episodes occurred from 1540 to 1568, 1578 to 1597, 1613 to 1620, 1632 to 1637, 1655 to 1672, 1681 to 1696, 1721 to 1727, 1740 to 1752, 1762 to 1776, 1794 to 1800, 1841 to 1859, 1875 to 1913, 1933 to 1959, 1986 to 1997. Furthermore, the results of spatial correlation analyses show that the reconstructed precipitation represents the regional precipitation variations for northern Pakistan and nearby high‐altitude mountains. The out‐of‐phase relationship in tree‐ring records of the Karakoram region and surrounding areas suggests that the Karakoram was under the control of large‐scale ocean–atmosphere–land circulations on a decadal timescale in the past centuries. In addition, by the comparison between the precipitation reconstruction and the instrumental data, we found that the drought risk of Karakoram has increased in the past 70 years and that extreme events are likely to become more severe and more frequent under the backdrop of climatic warming.