Tag Archives: Tibet

下载GAME/TIBET数据

GAME/TIBET是中日合作的陆气相互作用研究项目,在青藏公路沿线布设了一些站点进行相关项目(如自动气象站、地面辐射、降水、径流、土壤温度/湿度、卫星同步观测、探空等)的观测。时间跨度大概是1997-1998,先进行了第一阶段的观测(POP),然后开展加密观测(IOP)。国内能获取数据的地方大概是寒旱区科学数据中心(http://westdc.westgis.ac.cn)或者WDCD冰川冻土中心,后者其实是前者的英文版本。但目前两者数据服务器不大稳定。
另一个可能获取其数据的地方是DIAS的GAME/Tibet数据中心,由日方负责人Koike
Toshio教授团队维护,网址是http://search.diasjp.net/en/dataset/GAME_Tibet,有完善的文档记录,如果对GAME-TIBET观测项目不清楚的话,可以进去看。
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ZT: 参观青藏高原冻土站有感

南昭瑾

2018 年暑假,我有幸与南京师范大学地理科学学院的老师和哥哥姐姐们,一起考察了青藏高原生态环境和寒区工程。这次特殊的经历让我收获了很多。

7 月20 日7 时,我们一行两辆越野车从格尔木出发,经过西大滩、昆仑山口和五道梁,进入可可西里腹地,一共350多公里,抵达北麓河冻土站时已是下午3时30分。

北麓河站海拔4628 米,含氧量只有平原地区的50%左右,大家都坐了很长时间的车,同行的老师和哥哥姐姐们都有不同程度的高原反应,我站在地上也感觉整个人轻飘飘的。风很大,我后悔没有带些更厚的衣服来。老师说,高原上如果感冒了后果会很严重,所以我只好戴上帽子竖起衣领抵御风寒。不远处,刘永智老爷爷已经在门口迎接我们了。

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吐糟行程单邮寄

前阵子连续出差,不少航班行程单来不及在机场打印,或者机场没有该航空公司的点,因此只能选择了邮寄。象东航这些大公司,在官网或App上选择邮寄,都能很快速的收到。这些事大公司还是做的不错,另外比如退票,也总是很快就能收到东航的退款,象厦门航空的一次退票经历我就打了十几个电话,长达个把月的沟通,才把钱要回来,然后感觉我好像白赚了一笔钱似的。行程单邮寄这个事一样,一些小公司就不行了。象最近坐了西藏航空从兰州到哈尔滨的的行程,当初在其官网上买(这个公司没有App),选择了邮寄行程单,并提交了地址。结果十几天后也没有动静。打电话到客服,告诉我行程单没有打印。客服小姐担心过了七天就无法打印,比较好心说她来试试,如果过期了她也没法子。耐心等待后是好结果,还能打印并给我补寄。然后我把邮寄地址都补录了一遍(前面我录在官网上的地址等信息据说客服没法看到),这次应该可以了。

这个教训告诉我们,如果靠行程单报销,三天内没有收到,就应该给客服确认了。国内的很多公司跟人都不靠谱,官网上的信息很多时候是作样子,根本没人来处理。

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2018暑假祁连八宝河—青藏高原野外实践(7/13-7/23/2018)

前期准备

购买保险、常用药品;租车事宜;地形图或下载好离线卫星图;行车路线、住宿预定等事宜。

Day 1,南京——兰州,高铁

租借和购买野外所需仪器和材料;

Day 2,兰州——张掖,高铁,宿张掖

火车上午抵达,下午参观中科院黑河遥感试验站

Day 3,张掖——龙首电站——莺落峡——草滩庄水利枢纽——祁连,宿祁连

龙首电站,讲解水力发电及潜在影响;

莺落峡水库对莺落峡水文站观测结果的影响,讲解径流还原的必要性;

黑河干流莺落峡出来后,部分分流到干渠,其余通过自然河流向下,讲解黑河流域干、支、斗、毛到田间的分级渠系结构,讲解黑河分水方案;

草滩庄水利枢纽对自然河道进一步进行控制,至此分解为东西子渠;

莺落峡水文站、草滩庄水利枢纽结合Google地图的卫星照片可以找到;百度地图缺卫星照

至祁连路上经峨堡、阿柔大寺,可停留。 Continue reading

基于机器学习模型的青藏高原日降水数据的订正研究

[1] H Chen, C Ning, Z Nan, et al. Correction of Daily Precipitation Data over the Qinghai-Tibetan Plateau with Machine Learning Models[J]. 2017, 39(3): 583—592.[陈浩,宁忱,南卓铜,等. 基于机器学习模型的青藏高原日降水数据的订正研究[J]. 冰川冻土. 2017, 39(3): 583—592.]

选择了5种机器学习模型,即k最近邻方法(KNN)、多元自回归样条方法(MARS)、支持向量机(SVM)、多项对数线性模型(MLM)和人工神经网络(ANN),利用海拔、相对湿度、坡向、植被、风速、气温和坡度等因子订正ITPCAS和CMORPH两种常用的青藏高原日降水数据集。五折交叉验证表明,KNN的订正精度最高。在三个验证站点(唐古拉、西大滩和五道梁)的误差分析,以及对青藏高原年降水量的空间分析均表明,KNN对CMORPH的订正效果显著,对ITPCAS在局部区域有一定订正效果,ITPCAS及其订正值的降水空间分布准确度高于CMORPH的订正值。主成分分析法表明降水订正是气象和环境因子综合作用的结果。

下载:Link 1 (from冰川冻土); precip.machine.learning-wyd-2017 (Local)

A paper on evaluation of some simple permafrost models on QTP

Zhao S, Nan Z*, Huang Y, Zhao L. The application and evaluation of simple permafrost distribution models on the Qinghai-Tibet Plateau. Permafrost and Periglacial Processes. 2017, 28(2): 391-404. DOI:10.1002/ppp.1939.

ABSTRACT

The performance of simple permafrost distribution models widely used on the Qinghai–Tibet Plateau (QTP) has not been fully evaluated. In this study, two empirical models (the elevation model and mean annual ground temperature model) and three semi-physical models (the surface frost number model, the temperature at the top of permafrost model and the Kudryavtsev model) were investigated. The simulation results from the models were compared to each other and validated against existing permafrost maps of the entire QTP and in three representative areas investigated in the field. The models generally overestimated permafrost distribution in the investigated areas, but they captured the broad characteristics of permafrost distribution on the entire QTP, and performed best in areas with colder, continuous permafrost. Large variations in performance occurred at elevations of 3800–4500 m asl and in areas with thermally unstable permafrost. The two empirical models performed best in areas where permafrost is strongly controlled by elevation, such as eastern QTP. In contrast, the three semi-physical models were better in southern island permafrost areas with relatively flat terrain, where local factors considerably impact the distribution of permafrost. Model performance could be enhanced by explicitly considering the effects of elevation zones and regional conditions.

Links: Baidu;

三篇IGARSS 2016会议论文:关于多层土壤数据和降水较正

1. Wu X, Nan Z.A multilayer soil texture dataset for permafrost modeling over Qinghai-Tibetan Plateau.In Proceeding of 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS),2016. 4917-4920. (wu et al. 2016, igarss )
2. Wang Y, Nan Z*, Chen H, Wu X.Correction of daily precipitation data of ITPCAS dataset over the Qinghai-Tibetan Plateau with KNN model.In Proceeding of 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS),2016. 593-596. (wang et al. 2016, igarss)
3. Ning C, Wang Y, Nan Z*, Chen H, Liu C.Study on correction of daily precipitation data of the Qinghai-Tibetan plateau with machine learning models.In Proceeding of 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS),2016. 517-520. (ning et al. 2016, igarss)

一种简单有效的MODIS LST内插方法

一种简单有效的MODIS LST内插方法

Zhuotong Nan ([email protected], 南卓铜)

本软件实现了一种新的基于相似性原理的MODIS陆表温度(LST)的插值方法。这种LST数据空间插值方法利用具有相似温度变化特征的已知LST像元集合推算缺失的LST。在青藏高原的案例表明传统的地统计方法基本无法处理大范围连续的数据丢失(比如因为云),而本方法明显优于传统方法,可能较合理的得到缺失LST。此方法尤其适用于大范围山地区域。

This tool implements a new interpolation method for MODIS land surface temperature (LST) following the theory of similarity. It estimates the missing LST pixels by known LST pixel sets which bear similar characteristics of LST variation as the missing pixels. A case study on the Qinghai Tibet plateau has already been carried out, showing its obvious advantages over the traditional geostatistic methods, the latter was unable to do with a large area and temporally continuous data missing situations. This approach is especially good for a study area with a large area and mountainous terrain.

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fig 1a, with this approach

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fig 1b, with Kriging

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