科罗拉多落基山脉山体效应定量化研究

Quantitative research of mass elevation effect in Colorado Rocky Mountains

落基山脉作为北美最大的内陆山地,其山体效应对林线分布具有很大影响,导致林线海拔远高于周围内陆山体及其他海岸山地。然而,以往落基山脉山体效应研究多集中于定性研究,但是山体效应如何量化,如何根据落基山脉的地形气候条件构建区域山体效应的定量化模型,目前鲜有研究。通过分析台站处山体增温及量化落基山脉山体效应的影响因子,并计算最热月均温10℃等温线的海拔高度,来定量化地估算科罗拉多落基山脉山体效应值大小及其对林线分布的影响。结果表明:(1)用山体增温值表示山体效应大小是合理且比较理想的指标。科罗拉多落基山脉增温显著,所有台站的增温均值为2.07℃,增温幅度为0.78~4.29℃。(2)科罗拉多落基山脉山体效应的主要影响因素为山体基面高度和降水大陆度,二者与山体增温构建的线性拟合模型具有较高的解释能力,判定系数高达71.2%。(3)科罗拉多落基山脉不同纬度带山体内外最热月10℃等温线分布高度对比表明,山体内部理想林线高度均高于山体外部的理想林线分布,内外分布差异为400~700 m。定量分析科罗拉多落基山脉的山体效应模型,优化了区域尺度的山体效应模型精度,有助于深入认识山体效应及其对垂直带分布的影响。

Rocky Mountains is the Northern America＇s largest inland mountains. Its mass elevation effect（MEE） imposes substantial forcing on treeline altitude. As a result, its treeline elevation is much higher than other inland mountains and coastal mountains of the continent.However, most existing literatures on MEE are from a qualitative perspective. This study applied meteorological station records, NCAR/NCEP free air temperature and DEM data to calculate MEE-related temperature increases from inner to out of the Colorado Rocky Mountains（ΔT） and to quantify values of MEE factors, including latitude, mountain bass elevation（MBE）, hydric continentality and surface openness. Thereby the magnitude of MEE was computed with ΔT and MEE factors. MEE＇s impacts on treeline distribution were estimated through isothermal line altitude of the warmest month 10℃ from inner to out of mountains of different ranges. Elevation of isothermal line was interpolated by MODIS land surface temperature data coupled with elevation and deduced temperature lapse rate. Results show that：（1） ΔT is an ideal indicator for MEE. ΔT at adopted stations ranges from 0.78 °C to 4.29° C, whereas mean value is 2.07 ℃. ΔT showed a descending trend from outer ranges toward inner ranges. The greatest ΔT occurred at the center ranges between 38°-39°N.（2） The resulted MEE model for the Colorado Rocky Mountains taking MBE and hydric continentality as independent variables has a high explanatory power of R^2 of 71.2%. MBE had the most significant contribution to the model with 55.21%, whereas latitude and surface openness were eliminated.（3） The 10 ℃ isothermal line of the hottest month in the Colorado Rockies was higher in inner ranges than in outer ranges at all the three latitudes, with a difference of 400 m to 700 m. At 38°N and 39°N, differences of 10℃ isothermal line elevation between inner and outer ranges showed strong variation, whereas less at 40°N. This difference corresponds well to air temperature difference between the inner and outer mountain ranges. The findings suggest that MEE was crucial for driving treeline up to higher elevation in the Rocky Mountains. This study developed a quantitative model for the MEE of the Colorado Rocky Mountains and improved our understanding of MEE and its significance for treeline distribution.