近60年秦岭山地旱涝变化规律

随着极端气候变化,山地灾害频发。基于秦岭山地32个气象站点的实测数据,以标准化降水蒸散指数(SPEI)为旱涝量化指标,研究了过去60年秦岭山地旱涝时空变化特征、频率、周期等变化规律,结果表明:(1)1960—2019年,秦岭山地年SPEI指数以0.124/10a的速度下降,其中,90.23%的面积呈显著下降趋势,1.96%的面积呈显著上升趋势,并在1990年发生干旱突变;秦岭北坡的干旱化趋势大于南坡,且高海拔地区干旱化更为明显。(2)突变前秦岭山地湿润比例平均值为36.94%,突变后下降为18.19%;干旱比例由突变前的17.64%急剧上升到突变后的38.19%;突变前30年秦岭山地极端干旱事件、严重干旱事件极少发生,发生频率几乎为0;突变后30年严重干旱和极端干旱事件发生频率增加,秦岭南北坡极端湿润和严重湿润事件近乎销声匿迹。(3)整体上,太阳黑子与秦岭山地旱涝变化以显著负相关关系为主;ENSO事件对秦岭山地的旱涝变化影响较大,在La Nina年易发生洪涝事件,在El Ni1o年易发生干旱事件;在不同时域范围内,海表温度距平(SSTA)对秦岭山地旱涝变化的影响不同:1990年以前,SPEI与SSTA存在显著的负相关关系;1990年后,SPEI与SSTA存在5—6年的强凝聚性共振周期,且SPEI滞后SSTA约1/4周期。

基于多元线性回归模型和Anusplin的秦巴山区≥10℃积温空间模拟比较

为获取山区准确的高精度空间积温数据,采用高精度的气象插值软件Anusplin和多元线性回归模型两种方法,模拟山区≥10℃积温的空间分布,为山区积温空间模拟提供解决方法。以地形起伏较大的秦巴山区作为研究区,选用研究区内69个气象站点及其周边22个气象站点1960—2019年的逐日平均气温实测数据,采用Anusplin和多元线性回归模型两种方法,模拟了秦巴山区30 m分辨率≥10℃积温的空间分布。通过对预留气象站点实测数据进行验证,评价了两种方法在山区积温空间分布模拟复杂性问题中的适用性。结果表明:基于Anusplin的≥10℃积温的空间模拟方法较多元线性回归模型插值精度略高。即基于Anusplin的空间模拟方法能更真实地反映山区积温的空间分布情况,体现了海拔、经纬度对积温的影响,能更好地模拟复杂山区高精度的积温数据,为山区积温空间模拟提供了新的选择方法。

黄土高原植被变化对气象干旱多尺度响应特征与机制

基于黄土高原1983—2015年间的植被状况指数(VCI)与1~48个月尺度的标准化降水蒸散发指数(SPEI)和标准化降水指数(SPI),利用Pearson相关系数法、线性回归法和Mann-Kendall趋势检验法等方法研究了黄土高原地区植被对气象干旱的多时间尺度时空响应特征。结果表明:(1)1983—2015年,黄土高原植被状况整体趋于改善,但黄土高原整体干湿状况变化趋势不大。(2)黄土高原绝大部分区域植被变化与气象干旱指数呈现显著正相关关系,表明植被活动受到水分的限制较强。但是,过去几十年,黄土高原地区植被受到水分限制的影响程度有逐渐减轻的趋势。(3)黄土高原植被对短时间尺度的水分盈亏变化相对敏感,尤其是耕地和草地对1~4个月的SPEI更为敏感,而林地对SPEI的响应时间尺度较为分散。黄土高原VCI与SPEI、SPI的最大相关系数均主要出现在生长季(4—10月),表明水分条件在生长季对植被活动的影响较为显著。

中国植被生产力对干湿变化的响应

随着全球气温的持续升高,水资源可利用性对植被生长的影响是否发生了变化仍不清楚。本文评估了1982—2018年中国植被生产力对干湿变化响应的长期演变趋势及植被响应的时间尺度阈值,这将对降低陆地生态系统管理成本和双碳目标实现具有重要意义。①在研究期内中国植被生产力的水分胁迫不断增强。②在多时间尺度干湿变化中,61.18%的植被覆盖区存在过干旱化显著抑制了该区域的植被光合作用;28.89%的植被覆盖区存在过水分过剩显著抑制了该区域的植被光合作用。③干旱化显著胁迫植被生产力的最小响应时间缩短,而水分过剩显著约束植被生产力的最大响应时间延长,表明干旱化抑制植被生产力影响越来越容易,水分过剩对植被生产力产生抑制作用越来越困难。因此,1982—2018年中国植被生产力的水分约束正在增加。本文结果揭示了气候持续变暖背景下的水资源可利用性对植被生长影响的变化趋势,为水—碳耦合关系及水碳循环提供科学依据。

Spatio-temporal differentiation of climate warming(1959-2016)in the middle Qinling Mountains of China

Based on air temperature observation data from 32 meteorological stations, temperature changes in the middle Qinling Mountains from 1959 to 2016 were analysed with respect to the north-south, seasonal and altitude differences. Our research mainly showed the following results. The annual temperature(TA) rose approximately 0.26℃/10 a within the past 58 years. This warming trend was stronger on the northern slope than on the southern slope, and a warming trend reversal occurred in 1994 on the northern slope, which was three years earlier than on the southern slope. The temperature changes for the four seasons were not synchronized, and the trend in spring contributed the most to the TA trend, followed by winter, autumn, and summer. The temperature difference between summer and winter(TDSW) decreased significantly over the past 58 years. The temperature change in the middle Qinling Mountains was clearly dependent on altitude. With increases in altitude, the TA increased gradually and became stronger while the TDSW decreased gradually and became weaker. Differences in temperature change between the north and south were mainly observed in low-altitude areas. With increase in altitude, the differences gradually tended to disappear.

Sensitivity and areal differentiation of vegetation responses to hydrothermal dynamics on the northern and southern slopes of the Qinling Mountains in Shaanxi province

The Qinling Mountains,located at the junction of warm temperate and subtropical zones,serve as the boundary between north and south China.Exploring the sensitivity of the response of vegetation there to hydrothermal dynamics elucidates the dynamics and mechanisms of the main vegetation types in the context of changes in temperature and moisture.Importance should be attached to changes in vegetation in different climate zones.To reveal the sensitivity and areal differentiation of vegetation responses to hydrothermal dynamics,the spatio-temporal variation characteristics of the normalized vegetation index(NDVI)and the standardized precipitation evapotranspiration index(SPEI)on the northern and southern slopes of the Qinling Mountains from 2000 to 2018 are explored using the meteorological data of 32 meteorological stations and the MODIS NDVI datasets.The results show that:1)The overall vegetation coverage of the Qinling Mountains improved significantly from 2000 to 2018.The NDVI rise rate and area ratio on the southern slope were higher than those on the northern slope,and the vegetation on the southern slope improved more than that on the northern slope.The Qinling Mountains showed an insignificant humidification trend.The humidification rate and humidification area of the northern slope were greater than those on the southern slope.2)Vegetation on the northern slope of the Qinling Mountains was more sensitive to hydrothermal dynamics than that on the southern slope.Vegetation was most sensitive to hydrothermal dynamics from March to June on the northern slope,and from March to May(spring)on the southern slope.The vegetation on the northern and southern slopes was mainly affected by hydrothermal dynamics on a scale of 3–7 months,responding weakly to hydrothermal dynamics on a scale of 11–12 months.3)Some 90.34%of NDVI and SPEI was positively correlated in the Qinling Mountains.Spring humidification in most parts of the study area promoted the growth of vegetation all the year round.The sensitivity of vegetation responses to hydrothermal dynamics with increasing altitude increased first and then decreased.Elevations of 800 to 1200 m were the most sensitive range for vegetation response to hydrothermal dynamics.The sensitivity of the vegetation response at elevations of 1200–3000 m decreased with increasing altitude.As regards to vegetation type,grass was most sensitive to hydrothermal dynamics on both the northern and southern slopes of the Qinling Mountains;but most other vegetation types on the northern slope were more sensitive to hydrothermal dynamics than those on the southern slope.

秦岭陕西段南北坡植被对干湿变化响应敏感性及空间差异

秦岭位于暖温带与亚热带交界处,也是中国南北地理分界线,秦岭南北坡植被对干湿变化响应敏感性,可以折射出暖温带、亚热带地区主要植被类型对干湿变化的响应规律和机制特征,对深入理解不同气候带植被变化规律具有重要意义。本文利用秦岭山地32个气象站点的气象数据和MODIS NDVI时间序列数据集,探讨了2000—2018年秦岭南北坡NDVI和SPEI时空变化特征,揭示了南北坡植被对干湿变化响应敏感性及其空间差异。结果表明:①2000—2018年秦岭植被覆盖情况整体显著改善,但秦岭南坡NDVI上升幅度和面积占比均高于北坡,南坡植被比北坡改善情况好。秦岭湿润化趋势不显著,但秦岭北坡湿润化速率和面积占比均大于南坡。②秦岭北坡植被比南坡植被更易受干湿变化影响,秦岭北坡植被对3—6月总体干湿变化最为敏感,南坡植被对3—5月(春季)干湿变化最为敏感。秦岭南北坡植被主要受3~7个月尺度干湿变化影响,对11~12个月尺度的干湿变化响应较弱。③秦岭有90.34%的区域NDVI与SPEI呈正相关,大部分地区春季湿润化能促进全年植被生长;随海拔上升,植被对干湿变化响应敏感性先上升再下降,海拔800~1200 m是植被响应最敏感的海拔段,海拔1200~3000 m随海拔上升植被响应敏感性下降;南北坡草丛均是对干湿变化响应最为敏感的植被类型,但秦岭北坡多数植被类型对干湿变化响应比南坡敏感。