The poor distribution of meteorological stations results in a limited understanding of the precipitation pattern in the Tianshan Mountains. The spatial patterns of precipitation over the mid Tianshan Mountains were ch...The poor distribution of meteorological stations results in a limited understanding of the precipitation pattern in the Tianshan Mountains. The spatial patterns of precipitation over the mid Tianshan Mountains were characterized based on the TRMM 3B43 monthly precipitation data. By comparing satellite estimates with observed data, it shows that TRMM 3B43 data underestimate the precipitation in mountain region. Regression models were developed to improve the TRMM 3B43 data, using geographic location and topographic variables extracted from DEM using GIS technology. The explained variance in observed precipitation was improved from 64% (from TRMM 3B43 products alone) to over 82% and the bias reduced by over 30% when location and topographic variables were added. We recalculated all the TRMM 3B43 monthly precipitation grids for the period 1998 to 2009 using the best regression models, and then studied the variation patterns of precipitation over the mid Tianshan Mountains. The results are well explained by a general understanding of the patterns of precipitation and orographic effects. This indicated that the Tianshan Mountains strongly influences the amount and distribution of precipitation in the region. This is highlighted by the confinement of the precipitation maxima to the windward (northern slope). And complex vertical changes in the provenance and distribution of precipitation, like that a negative increasing rate of precipitation in the vertical direction exists in the north but does not in south. The results have also revealed large gradients and different patterns in seasonal precipitation that are not simply related to elevation, the distribution of precipitation may also be affected by other seasonal factors such as the sources of moist air, wind direction and temperature.展开更多
At 5 am 24 th June 2017, a catastrophic landslide hit Xinmo Village, Maoxian County, Sichuan Province, China. The slide mass rushed down from an altitude of 3400 m and traveled 2700 m in a high velocity. The 13 millio...At 5 am 24 th June 2017, a catastrophic landslide hit Xinmo Village, Maoxian County, Sichuan Province, China. The slide mass rushed down from an altitude of 3400 m and traveled 2700 m in a high velocity. The 13 million m^3 deposition buried the whole village and caused about 100 deaths. The source area of the landslide is located in a high steep slope, average slope angle is 40o and maximal angle is 65o. The strata are interbedded Triassic Zagunao Formation metamorphic sandstone and slate with the dip slope angle of 45°. Based on high-resolution satellite remote sensing image, UAV image, DEM data, and field investigation, failure mechanism, travel features, and deposit characteristics were analyzed. The results showed that this landslide was influenced by Songpinggou Fault zone. According to the topography before the failure, the landslide is located in the back scarp of an antecedent landslide induced by Diexi Earthquake in 1933. The bedding slope provided potential rupture surface. Historical seismic activities and long-term gravitational deformation caused rock mass accumulated damages. Weathering and precipitation weakened the rock mass and finally induced shearing and tension failure. A huge block detached from the top rock slope, pushed the past landslide deposits in the middle part, rushed out of the slope bottom in a high velocity and buried the Xinmo Village. The rapid movement entrained and brought the soil into the Songping Gully which recoiled with and bounced back from the opposite mountain.展开更多
基金supported by the 973 Program of China(Grant No. 2010CB951002)Natural Science Foundation of China (Grant No. 41130641)
文摘The poor distribution of meteorological stations results in a limited understanding of the precipitation pattern in the Tianshan Mountains. The spatial patterns of precipitation over the mid Tianshan Mountains were characterized based on the TRMM 3B43 monthly precipitation data. By comparing satellite estimates with observed data, it shows that TRMM 3B43 data underestimate the precipitation in mountain region. Regression models were developed to improve the TRMM 3B43 data, using geographic location and topographic variables extracted from DEM using GIS technology. The explained variance in observed precipitation was improved from 64% (from TRMM 3B43 products alone) to over 82% and the bias reduced by over 30% when location and topographic variables were added. We recalculated all the TRMM 3B43 monthly precipitation grids for the period 1998 to 2009 using the best regression models, and then studied the variation patterns of precipitation over the mid Tianshan Mountains. The results are well explained by a general understanding of the patterns of precipitation and orographic effects. This indicated that the Tianshan Mountains strongly influences the amount and distribution of precipitation in the region. This is highlighted by the confinement of the precipitation maxima to the windward (northern slope). And complex vertical changes in the provenance and distribution of precipitation, like that a negative increasing rate of precipitation in the vertical direction exists in the north but does not in south. The results have also revealed large gradients and different patterns in seasonal precipitation that are not simply related to elevation, the distribution of precipitation may also be affected by other seasonal factors such as the sources of moist air, wind direction and temperature.
基金partially supported by the National Science Foundation of China(Grant No.41572302)the Funds for Creative Research Groups of China(Grant No.41521002)
文摘At 5 am 24 th June 2017, a catastrophic landslide hit Xinmo Village, Maoxian County, Sichuan Province, China. The slide mass rushed down from an altitude of 3400 m and traveled 2700 m in a high velocity. The 13 million m^3 deposition buried the whole village and caused about 100 deaths. The source area of the landslide is located in a high steep slope, average slope angle is 40o and maximal angle is 65o. The strata are interbedded Triassic Zagunao Formation metamorphic sandstone and slate with the dip slope angle of 45°. Based on high-resolution satellite remote sensing image, UAV image, DEM data, and field investigation, failure mechanism, travel features, and deposit characteristics were analyzed. The results showed that this landslide was influenced by Songpinggou Fault zone. According to the topography before the failure, the landslide is located in the back scarp of an antecedent landslide induced by Diexi Earthquake in 1933. The bedding slope provided potential rupture surface. Historical seismic activities and long-term gravitational deformation caused rock mass accumulated damages. Weathering and precipitation weakened the rock mass and finally induced shearing and tension failure. A huge block detached from the top rock slope, pushed the past landslide deposits in the middle part, rushed out of the slope bottom in a high velocity and buried the Xinmo Village. The rapid movement entrained and brought the soil into the Songping Gully which recoiled with and bounced back from the opposite mountain.
