Knowledge Resource Center for Ecological Environment in Arid Area
| 天山山区多源降水数据评估及时空格局研究 | |
| 其他题名 | Assessment of Multi - Source Precipitation Data and Estimation the Spatial- temporal Pattern of Tianshan Mountains |
| 卞薇 | |
| 出版年 | 2018 |
| 学位类型 | 硕士 |
| 导师 | 陈亚宁 |
| 学位授予单位 | 中国科学院大学 |
| 中文摘要 | 近半个多世纪，全球的增温速率达到0.175°C/10a，气候变暖加剧了水循环过程，降水作为各尺度水循环过程的重要一环，是重要的气候和气象变量，在过去半个多世纪里，降水量级、频率和降水的时空分布等方面发生了重大变化。山区降水为干旱内陆地区提供了丰富的水资源，是重要的补给源区，山区降水研究对于区域气候变化研究、生态环境恢复以及水资源配置等领域具有重要意义。气象观测站点能够提供准确的降水资料，但山区由于地形复杂，自然条件十分恶劣，气象站点极少且分布不均，气象资料缺乏，山区降水相关研究面临着较大的困难。气象站点插值数据集、卫星遥感降水资料和再分析降水资料是目前降水研究较为常见的替代资料，因其时间连续性强、空间覆盖范围广，在各时空尺度的降水相关研究中得到广泛的应用。中国天山山区是西北干旱区众多河流、农业生产和生活的重要水资源补给区，是“中亚水塔”的重要构成。天山山区降水受到地形、海拔、下垫面等的影响，表现为强烈的时空异质性。同时中国天山山区的现有气象站点大多分布在海拔2000米以下，且分布稀疏，难以满足研究需要，因此，利用不同来源降水资料估算山区降水，进而深入研究山区降水垂直分布的时空变化及其差异性成为广大学者关注的热点。本文则针对中国天山山区气象站点稀少且分布不均，降水观测资料缺乏等问题，基于已有气象资料，使用MATLAB、ARCGIS、SPSS等软件，评估不同源降水资料在中国天山山区的适用性（包括APHRODITE、TRMM3B43、ERA-Interim和GLDAS数据集）；并基于降水与植被之间的密切相关性对不同源降水资料进行降尺度处理和分析；最后利用精度更高的降水资料分析中国天山山区降水在时间和空间上的分布特征。研究结论主要如下：1、APHRODITE、TRMM3B43、ERA-Interim和GLDAS降水资料在中国天山山区有一定的适用性。整体上而言，基于站点插值获取的APHRODITE数据和基于遥感卫星获取的TRMM3B43数据的表现优于ERA-Interim和GLDAS数据，在天山山区的适用性更高。2、2000-2015年间，TRMM3B43数据呈现最优表现，并且该数据在降水较多的夏季、降水较多的海拔高度（500-1290m）和降水较多的西部与实测数据间的相对偏差较小，对低海拔地区降水存在高估，对冷季高海拔地区降水存在高估，在暖季则低估高海拔地区降水。而ERA-Interim数据整体上对实测数据存在一定程度的低估，且在降水较多的月份和区域与实测数据间的相对偏差增大。GLDAS数据高估实测降水，且存在“坦化”现象，相对来说表现最差。在对2000-2007年不同数据集与站点观测降水进行对比时发现，APHRODITE与站点降水间的一致性最好(年降水达到了0.95的显著性相关)。3、分析空间分辨率为1km×1km的MODIS NDVI数据的时空分布与降水量间的关系，发现在月和年时间尺度上，NDVI数据与降水数据均存在明显相关，在年时间尺度上，与四种降水产品均达到0.7以上的显著相关。所以能够利用1km空间分辨率的NDVI数据，使用求和法对各种来源的降水数据资料进行降尺度处理。4、利用求和法对四种降水产品的多年月平均降水和年平均降水进行了降尺度研究并进行精度验证，在时间尺度上，四种降尺度后的降水数据资料在月时间尺度上与站点实测数据的变化趋势具有一致性，APHRODITE数据集保持了较高的相关性和较低的相对偏差。在季节时间尺度上，在2000-2015年间，TRMM3B43数据整体表现较优，三种数据整体表现为高估，冬季表现较差。在年时间尺度上，APHRODITE表现最优，在2000-2015年间，TRMM3B43和ERA-Interim数据表现较好。在空间尺度上，对32个气象站点的实测数据与对应格网数据集的相对偏差做了分析，发现四种数据对实测降水整体上表现为高估，对降水较少的吐鲁番站、达坂城站和七角井站存在明显的高估，而对昭苏、巴音布鲁克和吐尔尕特等站的降水存在低估，5-9月间格网数据与实测数据间的相对偏差较小。5、基于经过验证和降尺度的降水资料，解析中国天山山区降水在时间和空间上分布的特征，发现在时间尺度上，中国天山山区三大分区降水主要集中在4-9月份，APHRODITE、TRMM3B43、ERA-Interim和GLDAS的月最大降水量分别在15.7~62mm（2000-2007年平均），17.8~56.8mm，3.3~50.7mm和17.9~51.3mm之间。而月最大降水量在不同分区也存在着一定的差异，伊犁河谷的月最大降水量四种降水产品均显示在50mm以上，东天山月最大降水量最低在20mm以下，北天山要高于南天山。在季节上，各个分区的夏季降水量最多，冬季降水最少。与实测降水最为接近的APHRODITE数据显示中国天山山区2000-2007年均降水量为450.5mm，TRMM3B43数据显示出中国天山山区2000-2015年间的年均降水量为551.6mm。 6、在空间尺度上，首先在水平方向上，受水汽来源的影响，中国天山山区降水呈现自西向东逐渐降低的趋势，并且山区降水明显多于平原区，北天山降水多于南天山多于东天山。在垂直方向上，中国天山山区降水的最大降水高度带随着月份不同而存在差异。在1-3月和12月，天山山区降水量随着海拔升高呈现增加的趋势，4-12月间，在海拔2500-3000m间存在最大降水高度带，海拔高度小于2500m时，月平均降水量随高程增加而增加，当海拔大于3000m时，降水量随高程增加出现缓慢减少的趋势。中国天山山区年平均降水的最大降水高度带因区域不同而存在差异，东天山、南天山和北天山出现在2500-3000m之间，而典型流域伊犁河谷出现在2000-2500m之间。 |
| 英文摘要 | Over the past half-century, the global warming rate was 0.175 ° C / 10a, Climate warming exacerbates the water cycle.Among them, precipitation is an important part of the water cycle process at all scales and it is an important climate and meteorological variable. Over the past half-century, major changes have taken place in precipitation magnitude, frequency, and the temporal and spatial distribution of precipitation. Precipitation in mountainous areas is an important source of recharge for arid inland water resources. Research on mountain precipitation is of great significance to the research of regional climate change, ecological restoration and rational allocation of water resources. The meteorological observation stations can provide accurate precipitation data. However, due to the complex terrain, poor natural conditions, the sparse and uneven distribution of meteorological stations and the lack of meteorological data in mountainous areas, studies on precipitation in mountainous regions are facing great difficulties. Site interpolation datasets, remote sensing precipitation products and reanalysis precipitation data are the more common alternative data for precipitation research at present. They are widely used in precipitation-related studies on various spatio-temporal scales because of their strong temporal continuity and wide spatial coverage.Chinese Tianshan Mountain is an important water supply area for many rivers and agricultural production and living in the northwest arid area, and is an important part of "Central Asia Water Tower". Affected by topography, elevation, underlying surface, etc., precipitation in Tianshan Mountains has a strong temporal and spatial heterogeneity. At the same time, most of the existing weather stations in China's Tianshan Mountains are distributed below 2000 meters above sea level and are sparsely distributed to meet the research needs. Therefore, using the precipitation data from different sources to estimate the precipitation in the mountainous areas, and further studying the spatial and temporal variations of the vertical distribution of precipitation in the mountainous areas and their differences has become the focus of attention of the majority of scholars.In this paper, aiming at the rare and uneven weather stations in mountainous areas of China's Tianshan Mountains and the lack of precipitation data, based on the existing meteorological data, using MATLAB, ARCGIS, SPSS and other softwares to assess the applicability of different source precipitation data in China's Tianshan Mountains (including APHRODITE, TRMM3B43, ERA-Interim and GLDAS datasets); Based on the close relationship between precipitation and vegetation, the scaling of different source precipitation data was studied. The temporal and spatial variation characteristics of precipitation in the Tianshan Mountains of China were analyzed based on the higher resolution precipitation data. The main conclusions are as follows:1. APHRODITE, TRMM3B43, ERA-Interim and GLDAS precipitation data have certain applicability in China's Tianshan Mountains. Overall, the APHRODITE data obtained from site interpolation and the TRMM3B43 data obtained from remote sensing satellites performed better than ERA-Interim and GLDAS data and are more applicable in the Tianshan Mountains.2. The data of TRMM3B43 showed the best performance between 2000 and 2015, and the data showed relatively small deviation from the measured data in the summer with more precipitation, the altitude with more precipitation (500-1290m) and the more precipitation in the west, there is an overestimation of precipitation in low altitude areas, overestimation of precipitation in high altitudes in cold seasons, and underestimation of precipitation in high altitudes in warm seasons. However, the ERA-Interim data as a whole have underestimated the measured data to a certain extent, and the relative deviations in the months and regions with the measured data increase. The overall GLDAS data overestimates the measured precipitation, and there is a phenomenon of "decontamination", which is the poorest relative performance. Comparisons of observed precipitation between different datasets and stations during 2000-2007 found that APHRODITE had the best agreement with precipitation at the site (annual precipitation reached a significant correlation of 0.95).3. Analyzing the relationship between the temporal and spatial distribution of MODIS NDVI data with the spatial resolution of 1km × 1km and precipitation, we find that there is a significant correlation between NDVI data and precipitation data on monthly and yearly time scales. On the time scale, significantly correlated with all four precipitation products reaching above 0.7. Based on the NDVI data, it is feasible to use the summation method to downscaling precipitation products.4. Using the summation method, we study the multi-year average precipitation and annual average precipitation of four kinds of precipitation products and verify the accuracy. On the time scale, the measured data of four kinds of down-scaling precipitation products and stations have a more consistent trend on the monthly time scale, the APHRODITE dataset maintains a high correlation and low relative bias. On the seasonal time scale, overall TRMM3B43 data performed better over the period 2000-2015. All three data were overestimated as a whole and the winter performance was poor. APHRODITE performed best on a year-scale, and TRMM3B43 and ERA-Interim performed better between 2000 and 2015. On the spatial scale, the relative deviation between the measured data of 32 meteorological stations and the corresponding grid dataset is analyzed. It is found that the four kinds of data are generally overestimated for the measured precipitation, the Turpan, Dabancheng and Qiaojing stations with less precipitation have obvious overestimation, while there is underestimation of precipitation in Zhaosu, Bayinbuluke and Tuergat stations, from May to September, the relative deviation between the grid data and the measured data is small.5. Based on the validated and downscaling precipitation data, the spatial and temporal distribution of precipitation in Tianshan Mountains was analyzed. It is found that on the time scale, precipitation in the three major parts of the Tianshan Mountains in China is mainly concentrated in April-September, the monthly maximum precipitation of APHRODITE, TRMM3B43, ERA-Interim and GLDAS was between 15.7 and 62 mm (2000-2007 average), 17.8 and 56.8 mm, 3.3 and 50.7 mm and 17.9 and 51.3 mm, respectively. However, the monthly maximum precipitation in different sub-regions also has some differences. The monthly precipitation in the Ili Valley is above 50 mm, the minimum monthly precipitation in the East Tianshan is below 20 mm, and the northern Tianshan is higher than that of the southern Tianshan. In the seasons, all sub-districts are dominated by summer precipitation and winter precipitation is the least. The APHRODITE data, which is closest to the observed precipitation, shows that the average precipitation in China's Tianshan Mountains was 450.5 mm from 2000 to 2007, and the TRMM3B43 data show that the annual precipitation in China's Tianshan Mountains from 2000 to 2015 was 551.6 mm.6. On the spatial scale, firstly, in the horizontal direction, the precipitation in the mountainous areas of China's Tianshan Mountains tended to decrease gradually from west to east due to the impact of water vapor sources. The precipitation in the mountainous areas was significantly more than that in the plain areas. The precipitation in the northern Tianshan Mountains was more than that in the southern Tianshan Mountains East Tianshan. In the vertical direction, the maximum precipitation in China's Tianshan Mountains varies with different months. In January-March and December, the Tianshan Mountains show an increasing trend with the elevation increasing, between April and December, there is a maximum precipitation zone between 2500-3000m above sea level, when the altitude is less than 2500m, the monthly average precipitation increases with elevation, when the elevation is more than 3000m, the precipitation tends to decrease slowly with elevation increasing. The maximum precipitation of annual mean precipitation in the Tianshan Mountains in China varies with different regions, with the eastern Tianshan、the northern Tianshan and the southern Tianshan appearing between 2500-3000m and the Ili Valley appearing between 2000-2500m. |
| 中文关键词 | 山区降水 ; 中国天山山区 ; 不同源降水资料 ; 降尺度 ; 降水时空分布 |
| 英文关键词 | Mountain precipitation，China Tianshan mountainous area，Different source precipitation data，Downscaling，Temporal and spatial distribution of precipitation |
| 语种 | 中文 |
| 国家 | 中国 |
| 来源学科分类 | 自然地理学 |
| 来源机构 | 中国科学院新疆生态与地理研究所 |
| 资源类型 | 学位论文 |
| 条目标识符 | http://119.78.100.177/qdio/handle/2XILL650/288198 |
| 推荐引用方式 GB/T 7714 | 卞薇. 天山山区多源降水数据评估及时空格局研究[D]. 中国科学院大学,2018. |
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