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Journal of Geographical Sciences >

2016 , Vol. 26 >Issue 1: 59 - 69

DOI: https://doi.org/10.1007/s11442-016-1254-7

Orginal Article

Estimation of areal precipitation in the Qilian Mountains based on a gridded dataset since 1961

  • QIANG Fang ,
  • *ZHANG Mingjun ,
  • WANG Shengjie ,
  • LIU Yangmin ,
  • REN Zhengguo ,
  • ZHU Xiaofan
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  • College of Geography and Environmental Science, Northwest Normal University, Lanzhou 730070, China

Author: Qiang Fang (1987-), MS Candidate, specialized in global change and sustainable development. E-mail:

*Corresponding author: Zhang Mingjun, Professor, E-mail:

Received date: 2015-07-29

  Accepted date: 2015-08-30

  Online published: 2016-01-25

Supported by

National Natural Science Foundation of China, No.41461003

National Basic Research Program of China (973Program), No.2013CBA01801

Copyright

Journal of Geographical Sciences, All Rights Reserved
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Abstract

Based on a 0.5°×0.5° daily gridded precipitation dataset and observations in meteorological stations released by the National Meteorological Information Center, the interannual variation of areal precipitation in the Qilian Mountains during 1961-2012 is investigated using principal component analysis (PCA) and regression analysis, and the relationship between areal precipitation and drought accumulation intensity is also analyzed. The results indicate that the spatial distribution of precipitation in the Qilian Mountains can be well reflected by the gridded dataset. The gridded data-based precipitation in mountainous region is generally larger than that in plain region, and the eastern section of the mountain range usually has more precipitation than the western section. The annual mean areal precipitation in the Qilian Mountains is 724.9×108 m3, and the seasonal means in spring, summer, autumn and winter are 118.9×108 m3, 469.4×108 m3, 122.5×108 m3 and 14.1×108 m3, respectively. Summer is a season with the largest areal precipitation among the four seasons, and the proportion in summer is approximately 64.76%. The areal precipitation in summer, autumn and winter shows increasing trends, but a decreasing trend is seen in spring. Among the four seasons, summer have the largest trend magnitude of 1.7×108 m3×a-1. The correlation between areal precipitation in the mountainous region and dry-wet conditions in the mountains and the surroundings can be well exhibited. There is a negative correlation between drought accumulation intensity and the larger areal precipitation is consistent with the weaker drought intensity for this region.

Key words： gridded dataset; areal precipitation; principal component analysis; Qilian Mountains

Cite this article

QIANG Fang , *ZHANG Mingjun , WANG Shengjie , LIU Yangmin , REN Zhengguo , ZHU Xiaofan . Estimation of areal precipitation in the Qilian Mountains based on a gridded dataset since 1961[J]. Journal of Geographical Sciences, 2016 , 26(1) : 59 -69 . DOI: 10.1007/s11442-016-1254-7

1 Introduction

The global average surface air temperature shows an increasing trend by 0.5-1.3℃ from 1951 to 2010 (Stocker et al., 2013), and the warming in arid region is usually more sensitive (Li et al., 2012). A general trend of transformation from warm dry and warm wet has been evidenced in the arid northwestern China since the late 1980s and early 1990s, which is shown as increasing precipitation and decreasing drought event (Shi et al., 2007), but recent studies indicate that the drying trend still exists in some regions (e.g., Ma et al., 2003; Zhang et al., 2010). The Qilian Mountains lies at the margin of the Tibetan Plateau, and many inland rivers (including Shiyang River, Heihe River and Shule River) in the arid northwestern China originate from the alpine regions (Zhang et al., 2007). The sustainable development of oasis cities in Hexi Corridor is greatly affected by the water resources from the Qilian Mountains (Zhang et al., 2014; Zhang et al., 2008). The interannual and seasonal variation of precipitation in the Qilian Mountains is a hot topic for climate change research in this region.
As the total volume of precipitation within a domain, areal precipitation, is an important parameter in hydrological studies (Yang et al., 2006), in quantization of hydrological process, precipitation is usually expressed as water volume (i.e., areal precipitation) for a region, and areal precipitation is also an important input in numerical modeling of meteorological and hydrological studies (Cole et al., 2008). To accurately estimate areal precipitation in a specific region, many approaches have been yielded in the past years (e.g., Johansson and Chen, 2005; Leonhardt et al., 2014; Allen and Degaetano, 2005; Johansson and Chen, 2003), including spatial interpolation, multiple linear regression and remote sensing. Based on the spatial interpolation of GIS (geographic information system) technique, the distribution of precipitation can be calculated with the assistance of altitude (e.g., Zhang, 2001; Shi et al., 2008). The multiple regression methods with variables of altitude and other geographic parameters are also used to estimate the spatial pattern of precipitation (e.g., Zhao et al., 2013). In addition, remote sensing inversion is also widely applied in precipitation in the past decade (e.g., Zhang et al., 2013; Shen et al., 2010), although the satellite-observed period is usually limited (compared with the in-situ meteorological records).
The various approaches exist in calculating areal precipitation, but the accuracy of estimation is greatly related with the in-situ meteorological observations. To remove the influence of uneven distribution of observation stations, it is an effective way to calculate areal precipitation by using a high-resolution gridded precipitation dataset. Although a series of monthly or daily precipitation dataset have been released by many research institutes, the precision of these datasets still need to be further evaluated (Hewitson and Crane, 2005). In 2012, a gridded daily precipitation dataset with a resolution 0.5°×0.5° (V2.0) in China was released by National Meteorological Information Center (NMIC) of China Meteorological Administration (Zhao et al., 2014). In the past years, this dataset has been widely applied in meteorological assessments of mean precipitation and its extremes (e.g., Ren et al., 2015; Wang et al., 2013; Dong et al., 2014), and is considered to be suitable to describe the spatial distribution and seasonal variation of precipitation in China.
Due to complex terrain in the Qilian Mountains, the existing in-situ meteorological observation network is still too limited to cover the entire vertical landscape of the alpine regions (Jia, 2012), and areal precipitation directly estimated using measured data may underestimate precipitation to some degree. In this study, the gridded daily precipitation dataset released by NMIC is applied to the Qilian Mountains, and the long-term changes and seasonal variation of areal precipitation for this region are assessed. In addition, the relationship between areal precipitation and drought events in the Qilian Mountains and the surroundings are also studied. This paper aims to provide scientific basis to assess the regional water resource in the Qilian Mountains and its influence on downstream oases, and also present an approach to practically calculate areal precipitation on a large scale.

2 Data and methods

2.1 Study area

The Qilian Mountains consist of a series of NW-SE trending mountain ranges lying at the northeastern margin of the Tibetan Plateau with altitudes mostly over 4000 m. The length of the mountains from east to west is approximately 850 km, and the width from south to north is approximately 250-400 km. As a vital section of ancient Silk Road, the Hexi Corridor, is located on the northern slope of the Qilian Mountains, and many oasis cities are situated in the middle and lower reaches of inland rivers originated from the Qilian Mountains. Although the Hexi Corridor belongs to the arid northwestern China with scarce precipitation and high evaporation, there are a great number of modern glaciers in the high altitudes of the Qilian Mountains. During the past decades, these glaciers have significantly retreated, which greatly influences the regional hydrological processes (Tian et al., 2014; Wang et al., 2011). According to the Second Glacier Inventory of China (Liu et al., 2015), there are 2683 glaciers with an area of 1597.81 km2 and ice volume of 84.48±3.13 km3 in the Qilian Mountains (Figure 1).
Figure 1 Distribution of observation stations and grid boxes around the Qilian Mountains

2.2 Data

In this study, the gridded data (China Ground Precipitation 0.5°×0.5° Grid Dataset V2.0) is provided by the National Meteorological Information Center (NMIC). This gridded dataset assimilated the observed daily precipitation in 2474 national meteorological stations across China during the past decades, and the initial data were strictly checked by NMIC. In order to eliminate the influence of elevation, a method of Thin Plate Smoothing Spines (TPS) in ANUSPLIN was used, and the precipitation data was interpolated to 0.5°×0.5° grids. More details of the structure for this dataset were introduced by Zhao et al. (2014). In this study, a total of 406 grid boxes in the Qilian Mountains and the surroundings during 1961-2012 are selected, and 86 grid boxes are within the mountain region.
Based on the standards of the consecutiveness and the longest time interval, 35 national meteorological stations in the Qilian Mountains and the surroundings (within 100 km to the mountains as buffer zones) were used (Figure 1). The data of observed daily precipitation are quality controlled by NMIC. There are 9 stations in the mountain region, including Tuole (3367 m), Yeniugou (3320 m), Qilian (2787.4 m), Menyuan (2850 m), Wushaoling (3045.1 m), Caka (3087.6 m), Delhi (2981.5 m), Gangca (3301.5 m) and Da Qaidam (3173.2 m).
In addition, the regional drought data is also acquired from NMIC. A total of 12 meteorological stations with accumulative drought intensity during 1961-2012 are selected in the Qilian Mountains and the surroundings (i.e., Caka, Gangca, Gonghe, Guide, Guinan, Jingyuan, Lanzhou, Linxia, Minhe, Wushaoling, Xining and Yongchang).

2.3 Methods

To compare the precipitation difference between observed and gridded data, the nearest 4 grid boxes to the meteorological station are weighted using Inverse Distance Weighted (IDW) method, and then the weighted data is used to calculate the bias and correlation coefficients. The formula of the bias is given as follows:
(1)
where is the mean value of interpolated data, and is the means of observed data.
Principal component analysis (PCA) is used to find the main characteristics of precipitation in the Qilian Mountains, and SPSS 19 is employed.
The accumulative drought intensity is also used in this study, which can well reflect the duration and intensity of drought events (Li et al., 2014). The formula is given as follows:
Tkj|c) (2)
where Tkj is specific value on the k day in the station j, and Tkj|c is threshold value. The value of k is duration days, and j is number of stations involved on the specific day.
The nonparametric Sen’s method (Sen, 1968) is employed to study interannual trends of areal precipitation, and the significant levels of linear trend are examined using a Mann-Kendall test. The spatial distribution of correlation calculations are drawn using ArcGIS 9.3.

3 Results

3.1 Main pattern of the gridded dataset

As shown in Figure 2, the bias of gridded data mostly concentrates between 0% and 20%, and correlation coefficients are generally larger than 0.94. Figure 3a shows the spatial distribution of bias of gridded precipitation, and the bias in most regions is less than 40% (except for some stations in the western part). In Figure 3b, the correlation coefficients in higher altitude are usually larger than those in lower altitude. Generally, the interpolated grids in the study area can well reflect the spatial pattern of precipitation.
Figure 2 Numbers of stations for different ranges of bias for interpolated precipitation (a) and correlation coefficient between observed and interpolated precipitation (b) in the Qilian Mountains and the surroundings during 1961-2012
Figure 3 Spatial distribution of bias for interpolated precipitation (a) and correlation coefficient between observed and interpolated precipitation (b) in the Qilian Mountains and the surroundings during 1961-2012
Figure 4a shows the spatial distribution of annual mean precipitation in the study area during 1961-2012. The precipitation in the mountain region is generally larger than that in plain region, and the precipitation shows a decreasing trend from east to west. At the eastern section of the mountain ranges, the annual mean precipitation is larger than 550 mm. At the western section, the annual precipitation is usually less than 250 mm. During the study period, all the study area shows an increasing trend. The trend in the western part is more significant than that in the eastern part (Figure 4b). Some 11.6% and 12.8% of the grid boxes are statistically significant at the 0.01 level and 0.05 levels, respectively.
Figure 4 Spatial distribution of annual mean (a) and trend magnitude (b) of gridded precipitation in the Qilian Mountains and the surroundings during 1961-2012
The principal component analysis (PCA) is applied to the gridded precipitation in this study, and the results are shown in Figure 5. The first principal component of annual precipitation (Figure 5a) has very similar distribution value in whole region, in which the bias only exists in the northwestern corner. The negative value zone of the second principal component (Figure 5b) is consistent with the spatial domain of the high-altitude Tibetan Plateau. The third principal component (Figure 5c) exhibits negative value in southeast and positive value in northwest, in which the negative value occurs mostly in the Qilian Mountains. The study area is jointly influenced by multiple weather regimes, including the eastern Asian monsoon, Indian monsoon and Plateau monsoon as well as Westerlies circulation in the Northern Hemisphere (Zhang et al., 2007). The third principal component may reflect the distribution of dry and wet conditions. The western part of the Qilian Mountains is greatly controlled by Westerlies circulation, and shows limited precipitation. Shown in Table 1,the first principal component has a variance contribution of 68.89%, which represents the dominant character of precipitation variation. The second and third principal components show 6.75% and 6.29% in total variance, respectively, indicating a faster convergence.
Figure 5 Spatial distribution of result for principal component analysis of gridded precipitation in the Qilian Mountains and the surroundings during 1961-2012
Table 1 Result for principal component analysis of gridded precipitation in the Qilian Mountains and the surroundings during 1961-2012
Component Initial eigen value
Amount Variance contribution (%) Accumulative (%)
PCA1 279.99 68.96 68.96
PCA2 27.42 6.75 75.72
PCA3 25.54 6.29 82.01

3.2 Temporal variation of areal precipitation

The seasonal variation of areal precipitation during 1961-2012 in the Qilian Mountains shows increasing trend in summer (Figure 6b), autumn (Figure 6c) and winter (Figure 6d) with tendency rates of 16.50×108 m3×a-1, 2.67×108 m3×a-1 and 1.19×108 m3×a-1, respectively, and a decreasing trend at -0.17×108 m3×a-1 in spring (Figure 6a). The trends in spring are statistically significant at the 0.01 levels. Generally, there is significant seasonal diversity of areal precipitation in the Qilian Mountains. The trend magnitude in summer is the largest among the four seasons, and the least trend magnitude is seen in spring.
Figure 6 Interannual variation of areal precipitation in the Qilian Mountains during 1961-2012
Additionally, the areal precipitation in each season is different (Table 2). The mean annual precipitation in the past 52 years is 724.9×108 m3, in which the areal precipitation in spring, summer, autumn and winter are 118.9×108 m3, 469.4×108 m3, 122.5×108 m3 and 14.1×108 m3, respectively. The areal precipitation in summer shows the largest (64.76%), and the least is in winter (1.94%). If the study period is subdivided into two stages before and after the year 1987 (as mentioned by Shi et al., 2007), the areal precipitation amounts in each season during 1987-2012 are larger than that during 1961-1986 by 2.80%, 5.96%, 2.36% and 24.58%, respectively, and annual areal precipitation during 1987-2012 is larger than during 1961-1986 by 5.15%.
Table 2 Decadal mean of annual and seasonal areal precipitation in the Qilian Mountains during 1961-2012
Decade Areal precipitation (108 m3)
Spring Summer Autumn Winter Annual
1961-1970 138.4 422.2 117.3 10.0 687.9
1971-1980 86.4 470.4 123.5 14.1 694.4
1981-1990 134.4 476.6 126.5 15.4 752.9
1991-2000 110.7 462.3 98.9 15.2 687.0
2001-2010 124.6 494.0 147.8 16.1 782.5
1961-1986 117.3 455.8 121.1 12.5 706.7
1987-2012 120.5 483.0 124.0 15.6 743.1
1961-2012 118.9 469.4 122.5 14.1 724.9
Percentage (%) 16.40 64.76 16.90 1.94
The areal precipitation in each season of the Qilian Mountains has been analyzed in the above section, while there is spatial diversity in the area for each grade in annual precipitation (Figure 7). The gridded precipitation in this study has been divided into 7 grades. In most areas, the annual precipitation is between 300 mm and 600 mm, in which the areas with precipitation of 300-400 mm, 400-500 mm and 500-600 mm are 4.63×104 km2 (22.3%), 5.12×104 km2 (24.7%) and 3.44×104 km2 (16.6%), respectively. Precipitation above 600 mm is occupied to 0.49×104 km2 (2.3% in total area), while precipitation below 300 mm is occupied to 7.03×104 km2, which are 33.9% in the total area.
Figure 7 Area distributions for each grade of annual precipitation in the Qilian Mountains

3.3 Relationship between areal precipitation and drought intensity

Drought is a phenomenon which moisture is anomalous short with unbalanced precipitation and evapotranspiration, and widely occurs in Northwest China (Huang et al., 2011). In this section, the relationship between areal precipitation anomaly and drought accumulation intensity is analyzed. The percentage of areal precipitation is applied, and are divided into 8-25 (Larger), -8-8 (Normal) and -25 to - 8 (Less). In order to reflect the relationship between areal precipitation and drought, grades of drought accumulation intensity are also divided into -38 to -28 (stronger drought), -28 to -18 (drought), and -18 to -8 (weaker drought) in Figure 8.
Figure 8 Relationship between areal precipitation anomaly and drought accumulation intensity in the Qilian Mountains and the surroundings
In different percentages of annual areal precipitation, the percentage of stations of drought accumulation intensity demonstrates weaker (75%), which is larger than stronger drought accumulation intensity (17%). From weaker drought accumulation intensity, stations of larger percentage for annual areal precipitation are much more. In stronger stations, less percentage for annual areal precipitation are larger. Generally, there is negative correlation between drought accumulation intensity and areal precipitation, in which more precipitation exists in weaker drought intensity and precipitation can well reflect drought accumulation intensity.

4 Discussion

Areal precipitation is an important hydrological parameter, and has been calculated by using different methods across the world (e.g., Johansson and Chen, 2005; Leonhardt et al., 2014; Allen and Degaetano, 2005; Johansson and Chen, 2003), but uneven spatial distribution of observation stations greatly influenced the accuracy of estimated areal precipitation. To find a practical method in related studies, the procedure based on a gridded precipitation dataset released by NMIC is recommended in this study. Compared with spatial interpolation methods (usually operated in GIS) and multiple regressions using geographical parameters, the procedure in this study is much more convenient and can be widely used in different field. In addition, this method also has longer time series (dated back to the 1960s) than the inversion method of remote sensing.
The fluctuation of precipitation can reflect regional dry and wet conditions (Ma et al., 2003; Huang et al., 2015). In the Qilian Mountains, the study of the relationship between areal precipitation and drought event can deepen the knowledge of climate change in arid northwestern China and the Tibetan Plateau. In this paper, the drought accumulation intensity is studied, and the results are useful to understand the hydrological process and regional drought events, especially in the Hexi oasis.

5 Conclusions

A gridded dataset is used to calculate areal precipitation in the Qilian Mountains during the past decades, and the spatial distribution and interannual variation of areal precipitation in the study area are studied. The conclusions are given as follows:
(1) The gridded dataset can well reflect precipitation pattern in the Qilian Mountains and the surroundings. The precipitation in mountainous region is generally larger than that in plain region, and the eastern section of the mountain range usually has more precipitation than the western section.
(2) The annual mean value of areal precipitation in the Qilian Mountains is 724.9×108 m3, in which the areal precipitation in spring, summer, autumn, and winter are 118.9×108 m3, 469.4×108 m3, 122.5×108 m3 and 14.1×108 m3, respectively. The tendency rate of areal precipitation in summer is the largest among the four seasons, and the lowest trend magnitude is seen in spring.
(3) There is negative correlation between drought accumulation intensity and areal precipitation, in which more precipitation is consistent with lower drought intensity.

The authors have declared that no competing interests exist.

References

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Dong Lei, Zhang Mingjun, Wang Shengjieet al., 2014. Extreme precipitation events in arid areas in northwest China based on gridded data.Journal of Natural Resources, 29(12): 2048-2057. (in Chinese)According to the gridded Chinese ground precipitation dataset with a resolution of0.5° 0.5° released by National Meteorological Information Center, extreme precipitation indices including maximum 1- day precipitation(RX1day), maximum 5- day precipitation(RX5day), very wet day precipitation(R95), wet day precipitation(PRCPTOT), consecutive dry days(CDD) and simple daily intensity index(SDII) in arid areas in Northwest China during 1961-2011 is analyzed using Sen's slope, correlation analysis and other methods. The connection between each extreme precipitation index and the Arctic oscillation is discussed, and the gridded indices in this study are compared with those in previous research using observation data. The result indicates that most indices show a slightly increasing trend, except CDD with statistically significant decrease(P0.01). Spatially, RX1 day, RX5 day, R95, PRCPTOT and SDII have significantly increased in the western part and slightly decreased in the east part,and CDD generally presents a decreasing trend. The higher correlation(P0.05) exists between NCAR- based summer Arctic oscillations index and CDD, which indicates a relation between Arctic oscillation in summer and drought events in the study area. Compared with the previous research using observation data, the gridded data have greater spatial coverage, which is good at describing detailed spatial variation, especially in the mountainous regions like the Tianshan Mountains and Altai Mountains.

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Hewitson B C, Crane R G, 2005. Gridded area-averaged daily precipitation via conditional interpolation.Journal of Climate, 18(1): 41-57.A growing need for gridded observational datasets of area-average values to support research, specifically in relation to climate models, raises questions about the adequacy of traditional interpolation techniques. Conventional interpolation techniques (particularly for precipitation) suffer from not recognizing the changing spatial representivity of stations as a function of the driving synoptic state, nor the bounded nature of the precipitation field-that the precipitation field is spatially discontinuous. Further, many interpolation techniques explicitly estimate new point location values, and do not directly address the need arising from climate modeling for area-average values. A new procedure, termed conditional interpolation, is presented to estimate daily gridded area-average precipitation from station observations. The approach explicitly recognizes that the point observations represent a mixture of synoptic forcing shared in common with surrounding stations, and a response that is unique to the station. Consequently the spatial representivity of a station is conditional on the synoptic forcing and is a function of the radial direction from the station. The conditional interpolation accommodates this in a two-stage process through conditioning the interpolation parameters as a function of the synoptic state. First, the spatial pattern of wet/dry conditions is estimated, following which the magnitude of the precipitation is derived for those locations determined as wet. In a test based on a high-resolution dataset for South Africa the conditional interpolation is very effective in defining the spatial extent of the precipitation field. It then derives gridded values that are representative of the area average. In comparison, both these characteristics appear to be significantly overestimated by one of the commonly used interpolation schemes (Cressman interpolation). Overall the interpolation conditioned by the synoptic state appears to better estimate realistic gridded area-average values.

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Huang Xiaoyan, Zhang Mingjun, Jia Wenxionget al., 2011. Variation of surface humidity and its influential factors in Northwest China.Advances in Water Science, 22(2): 151-159. (in Chinese)Based on the daily data of 112 meteorological stations from 1960 to 2009,the potential evaporation(PE) is calculated using the UN Food and Agriculture Organization(FAO)Penman-Monteith model,and then the humid index is reconstructed from the PE in Northwest China.With the method of Inverse Distance Weighted,Mann-Ken-dall,etc,the temporal and spatial variations of humid index are discussed,as well as its impact factors.The result indicates that the humid index increases in the last 50 years with an increasing rate of 0.006/10a,which are obvious in spring and winter.From northwest to southeast,the humid index displays a marked high-low-high trend in spatial distribution.According to the spatial variation,the study areas can be divided into three sub-regions:obvious increasing,light increasing and continuous decreasing.The influential factors have different impacts on the surface humidity index during different times in the past 50 years,showing a positive correlation with precipitation and-relative humidity,and negative correlation with sunshine duration,potential evaporation and wind speed.

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Jia Wenxiong, 2012. Temporal and spatial changes of precipitation in Qilian Mountains and Hexi Corridor during 1960-2009.Acta Geographica Sinica, 67(5): 631-644. (in Chinese)Based on daily precipitation data of 18 weather stations in Qilian Mountains and Hexi Corridor during 1960 to 2009, the spatial and temporal changes of day number and intensity for different grades of precipitation were analyzed by the methods of linear trend, five-year moving trend, IDW, Morlet wavelet and Mann-Kendall. The results indicated that the spatial distributions of day number and intensity for different grades of precipitation changed from east to west and from south to north. In the last 50 years, the annual variations of day number of different grades of precipitation were increasing in most of the regions and the increasing scales are decreasing from east to west, which is consistent with the intensity of heavy rainfall events. However the annual variations present an increasing trend in some parts or decreasing in other parts in terms of the intensities of light rain, moderate rain and extreme rain. The annual changes of day number of different grades of precipitation showed an increasing trend, and they are significant for light rain, moderate rain and heavy rain. Intensity of light rain and heavy rain prohibited an unobvious decreasing trend, but it is opposite to intensities of moderate rain and extreme rain. The main change cycles of day number of different grades of precipitation have quasi-periods of 2a, 5a, 8a, 11a and 19a, and those of intensity of different grades of precipitation have quasi-periods of 2a, 5a, 11a, 15a and 25a. Except for the abrupt decrease in intensity of light rain, the day number and intensity of different grades of precipitation increased abruptly.

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Johansson B, Chen D, 2003. The influence of wind and topography on precipitation distribution in Sweden: Statistical analysis and modeling.International Journal of Climatology, 23(12): 1523-1535.Abstract To estimate daily catchment precipitation from point observations there is a need to understand the spatial pattern, particularly in mountainous regions. One of the most important processes occurring there is orographic enhancement, which is affected by, among other things, wind speed and wind direction. The objective of this paper was to investigate whether the relationship between precipitation, airflow and topography could be described by statistical relationships using data easily available in an operational environment. The purpose was to establish a statistical model to describe basic patterns of precipitation distribution. This model, if successful, can be used to account for the topographical influence in precipitation interpolation schemes. A statistical analysis was carried out to define the most relevant variables, and, based on that analysis, a regression model was established through stepwise regression. Some 15 years of precipitation data from 370 stations in Sweden were used for the analysis. The geostrophic wind, computed from pressure observations, was assumed to represent the airflow at the relevant altitude. Precipitation data for each station were divided into 48 classes representing different wind directions and wind speeds. Among the variables selected, the single most important one was found to be the location of a station with respect to a mountain range. On the upwind side, precipitation increased with increasing wind speed. On the leeward side there was less variation in precipitation, and wind speed did not affect the precipitation amounts to the same degree. For ascending air, slope multiplied by wind speed was another important factor. The effect of slope was enhanced close to the coast, and reduced for mountain valleys with upwind barriers. The stepwise procedure led to a regression model that also included the meridional and zonal wind components. Their inclusion might indicate the importance of air mass characteristics not explicitly accounted for. Copyright 2003 Royal Meteorological Society

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Johansson B, Chen D, 2005. Estimation of areal precipitation for runoff modeling using wind data: A case study in Sweden.Climate Research, 29(1): 53-61.In mountainous regions, rainfall distribution is influenced by topography in combination with wind speed and direction. This has implications for estimates of catchment precipitation as input to hydrological models. The objective of this work was to investigate if wind information can be used to improve the accuracy of precipitation estimates, particularly for operational applications. A geostrophic wind, computed from pressure observations, was assumed to represent the airflow at an altitude relevant for precipitation distribution. Interpolated values of precipitation (optimal interpolation) were verified directly against point observations. In some mountainous catchments with low annual evapotranspiration, estimates of long-term mean areal precipitation could be verified through the water balance equation. The effects of the interpolations with and without wind information on the performance of a rainfall-runoff model were also investigated. There were 2 main factors in favour of using wind information in the interpolation: (1) a better description of the seasonal distribution; and (2) a lower sensitivity to reductions in the number of meteorological stations.

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Leonhardt G, Sun S, Rauch Wet al., 2014. Comparison of two model based approaches for areal rainfall estimation in urban hydrology.Journal of Hydrology, 511(4): 880-890.We introduce and compare two different approaches to estimate mean areal rainfall intensity in urban catchments. Both methods are based on the same lumped hydrological model that is calibrated beforehand. The first method uses a reverse model, i.e. an inverse formulation of a rainfall-runoff model. Rainfall intensities and their uncertainties are estimated from runoff data only. The second method estimates parameters of a rainfall error model using a Bayesian approach. It requires measurements of both runoff and rainfall. Although the two approaches are conceptually rather different, they address the same issue - the quantification of areal rainfall intensities and their related measurement errors - and a comparison is hence of interest. The merits and faults of the two methods are discussed. Results show that both methods provide best estimates of hyetographs with maximum intensities and total depths in a realistic order of magnitude, whereas the uncertainty of rainfall estimated with the reverse model is rather large.

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Li Baofu, Chen Yaning, Shi Xun, 2012. Why does the temperature rise faster in the arid region of northwest China.Journal of Geophysical Research: Atmospheres, 117(D16): 81-81.During 1960-2010, the air temperature in the arid region of northwest China had a significant rising trend (P < 0.001), at a rate of 0.343°C/decade, higher than the average of China (0.25°C/decade) and that of the entire globe (0.13°C/decade) for the same period. Based on the analysis of the data from 74 meteorological stations in the region for 1960-2010, we found that among the four seasons the temperature change of winter has been playing the most important role in the yearly change in this region. We also found that the winter temperature in this region has a strong association with the Siberian High (correlation coefficient: R = -0.715) and the greenhouse gas emission (R = 0.51), and between the two the former is stronger. We thus suggest that the weakening of the Siberian High during the 1980s to 1990s on top of the steady increasing of the greenhouse emission is the main reason for the higher rate of the temperature rise in the arid region of the northwest China.

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Li Yunjie, Ren Fumin, Li Yipinget al., 2014. A study of the characteristics of the southwestern China regional meteorological drought events during 1960-2010.Acta Meteorologica Sinica, 72(2): 266-276. (in Chinese)An objective identification technique for the regional extreme events (OITREE) and the daily composite-drought index (CI) of the 101 stations in southwestern China including Sichuan, Yunnan, Guizhou and Chongqing were used to investigate the southwestern China regional meteorological drought events during 1960-2010. The values of the parameters of the OITREE method were determined. 87 events were identified, including 9 extreme events in which the 2009/2010 severe drought in southwestern China is the most serious meteorological drought event for the past 50 years. Further analysis reveals that: The durations are generally between 10-80 d, with the longest period being 231 d. November to April is the dry season in southwestern China. As far as the regional distribution is concerned, Yunnan and southern Sichuan have the highest drought frequency and intensity, and strong (extreme and severe) southwestern China regional meteorological drought events could be divided into five types, with the Southern type occurring more frequently. During the past 50 years, the southwestern China regional meteorological drought events show a significant increase trend in frequency and an obvious increase trend in intensity, for which the main reason may be the significant decrease of the annual precipitation in this region, with a contribution by the significant increase trend in temperature.

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Liu Shiyin, Yao Xiaojun, Guo Wanqinet al., 2015. The contemporary glaciers in China based on the second Chinese glacier inventory.Acta Geographica Sinica, 70(1): 3-16. (in Chinese)lt;p>The Second Chinese Glacier Inventory (SCGI) was compiled based on remote sensing images after 2004 including Landsat TM/ETM+ and ASTER images, and the digital elevation models (DEMs) from SRTM. The SCGI shows that there are 48,571 glaciers with a total area of 5.18&#x000D7;10<sup>4</sup> km<sup>2</sup> and ice volume of 4.3&#x000D7;10<sup>3</sup>-4.7&#x000D7;10<sup>3</sup> km<sup>3</sup> in China (including glaciers measured from 1:50,000 or 1:100,000 topographic maps made from the 1960s to the 1980s because of no high quality remote sensing images for the contemporary glacier inventories). The number of glaciers with the area below 0.5 km<sup>2</sup> reaches 33,061 and accounts for the majority part (66.07%) of glaciers in China. Glaciers with areas between 1.0 km<sup>2</sup> and 50.0 km<sup>2</sup> are totaled as ~3.40&#x000D7;10<sup>4</sup> km<sup>2</sup> (~2.65&#x000D7;10<sup>3</sup> km<sup>3</sup> in ice volume) and constitute the main part of glaciers in China. The Yengisogat Glacier (359.05 km<sup>2</sup>), located in the Shaksgam Valley, north slope of the Karakoram Mountain, is the largest glacier in China. The glaciers are spatially distributed in 14 mountains and plateaus in western China. The Kunlun Mountains has the largest number of glaciers in China, followed by Tianshan Mountains, Nyainq&#x000ea;ntanglha Range, the Himalayas and Karakoram. Glaciers in the above five mountains account for 72.26% of the total glacier number in China, however, over 55% of the total area of glaciers and 59% of the total ice storage in China are concentrated in the Kunlun Mountains, Nyainq&#x000ea;ntanglha Range and Tianshan Mountains. The number and area of glaciers in Karakoram Mountains are less than those in the Himalayas, but the volume of the former is more than that of the latter because the glaciers in the Karakoram are generally larger. Some 4/5 of the total area of glaciers in China is mainly distributed in an altitudinal band between 4500-6500 m a.s.l. with regional differences depending on the general elevations of various mountains. Analogously, there is an obvious difference of glaciers in basins. The first level basin having the most glaciers is the East Asia interior drainage area (5Y) which occupies ~40% of glaciers in China. The Yellow River basin (5J) has the fewest glaciers where only 164 with an area of 126.72 km<sup>2</sup> are distributed. Xinjiang and Xizang autonomous regions are the two provincial units rich in glaciers, with ~9/10 of the total area and ice storage of glaciers in China.</p>

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Ma Zhuguo, Hua Lijuan, Ren Xiaobo, 2003. The extreme dry/wet events in Northern China during recent 100 years.Acta Geographica Sinica, 58(Suppl.): 69-74. (in Chinese)Using monthly precipitation and monthly mean temperature, a surface humid index was suggested. According to the index, the distribution characteristics of extreme dryness has been deeply analyzed. The results indicated that there is an obvious increasing trend of extreme dryness in the central part of North China and Northeast China in the last 10 years, which is a high frequent period of extreme dryness; and a low frequent period in the regions during the last 100 years. To compare with variation trend of the temperature in these regions, the high frequent extreme dryness region is consistent with the warming trend in the same region.

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Ren Zhengguo, Zhang Mingjun, Wang Shengjie et al., 2015. Changes in daily extreme precipitation events in South China from 1961 to 2011.Journal of Geographical Sciences, 2015, 25(1): 58-68.lt;p>Based on the daily precipitation from a 0.5&deg;&times;0.5&deg; gridded dataset and meteorological stations during 1961-2011 released by National Meteorological Information Center, the reliability of this gridded precipitation dataset in South China was evaluated. Five precipitation indices recommended by the World Meteorological Organization (WMO) were selected to investigate the changes in precipitation extremes of South China. The results indicated that the bias between gridded data interpolated to given stations and the corresponding observed data is limited, and the proportion of the number of stations with bias between -10% and 0 is 50.64%. The correlation coefficients between gridded data and observed data are generally above 0.80 in most parts. The average of precipitation indices shows a significant spatial difference with drier northwest section and wetter southeast section. The trend magnitudes of the maximum 5-day precipitation (RX5day), very wet day precipitation (R95), very heavy precipitation days (R20mm) and simple daily intensity index (SDII) are 0.17 mm&middot;a<sup>-1</sup> 1.14 mm&middot;a<sup>-1</sup> 0.02 d&middot;a<sup>-1</sup> and 0.01 mm&middot;d<sup>-1</sup>&middot;a<sup>-1</sup> respectively, while consecutive wet days (CWD) decrease by -0.05 d&middot;a<sup>-1</sup> during 1961-2011. There is spatial disparity in trend magnitudes of precipitation indices, and approximate 60.85%, 75.32% and 75.74% of the grid boxes show increasing trends for RX5day, SDII and R95, respectively. There are high correlations between precipitation indices and total precipitation, which is statistically significant at the 0.01 level.</p>

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Sen P K, 1968. Estimates of the regression coefficient based on Kendall’s tau.Journal of the American Association, 39: 1379-1389.

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Shen Yan, Xiong Anyuan, Wang Yinget al., 2010. Performance of high-resolution satellite precipitation products over China.Journal of Geophysical Research: Atmospheres, 115(D2): 355-365.A gauge-based analysis of hourly precipitation is constructed on a 0.25 latitude/ longitude grid over China for a 3 year period from 2005 to 2007 by interpolating gauge reports from ~2000 stations (fig.1) collected and quality controlled by the National Meteorological Information Center of the China Meteorological Administration. Gauge-based precipitation analysis is applied to examine the performance of six high-resolution satellite precipitation estimates, including Joyce et al. (2004) Climate Prediction Center Morphing Technique (CMORPH) and the arithmetic mean of the microwave estimates used in CMORPH; Huffman et al. (2007) Tropical Rainfall Measuring Mission (TRMM) precipitation product 3B42 and its real-time version 3B42RT; Turk et al. (2004) Naval Research Laboratory blended product; and Hsu et al. (1997) Precipitation Estimation From Remotely Sensed Information Using Artificial Neural Network (PERSIANN). Our results showed the following: (1) all six satellite products are capable of capturing the overall spatial distribution and temporal variations of precipitation reasonably well; (2) performance of the satellite products varies for different regions and different precipitation regimes, with better comparison statistics observed over wet regions and for warm seasons; (3) products based solely on satellite observations present regionally and seasonally varying biases, while the gauge-adjustment procedures applied in TRMM 3B42 remove the large-scale bias almost completely; (4) CMORPH exhibits the best performance in depicting the spatial pattern and temporal variations of precipitation; and (5) both the relative magnitude and the phase of the warm season precipitation over China are estimated quite well, but the early morning peak associated with the Mei-Yu rainfall over central eastern China is substantially under-estimated by all satellite products. The work reported in this paper is an integral part of our efforts to construct an analysis of hourly merged precipitation analysis in the future (Shen et al., 2010). Further work is to extend its temporal coverage and to improve the quality of the CPAP. The dataset for the period of 1900-1952 with only ~100 gauge reports available over mainland China is under consideration for development. Gauge network is an important element to determine the quality of the dataset, while the gauge distribution is very sparse over the northwestern China and the Tibetan Plateau, the effective tool to improve the quality of the dataset over these areas is to merge the gauge observations with the satellite precipitation products which is under way. Figure 1 Number of Chinese stations reporting hourly precipitation over a three-year period from January 2005 to December 2007

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Shi Yafeng, Shen Yongping, Kang Ersiet al., 2007. Recent and future climate change in northwest China.Climatic Change, 80(3/4): 379-393.As a consequence of global warming and an enhanced water cycle, the climate changed in northwest China, most notably in the Xinjiang area in the year 1987. Precipitation, glacial melt water and river runoff and air temperature increased continuously during the last decades, as did also the water level of inland lakes and the frequency of flood disasters. As a result, the vegetation cover is improved, number of days with sand-dust storms reduced. From the end of the 19th century to the 1970s, the climate was warm and dry, and then changed to warm and wet. The effects on northwest China can be classified into three classes by using the relation between precipitation and evaporation increase. If precipitation increases more than evaporation, runoff increases and lake water levels rise. We identify regions with: (1) notable change, (2) slight change and (3) no change. The future climate for doubled COconcentration is simulated in a nested approach with the regional climate model-RegCM2. The annual temperature will increase by 2.7 ^ C and annual precipitation by 25%. The cooling effect of aerosols and natural factors will reduce this increase to 2.0 ^C and 19% of precipitation. As a consequence, annual runoff may increase by more than 10%.

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Shi Yuguang, Sun Zhaobo, Yang Qing, 2008. Characteristics of area precipitation in Xinjiang region with its variations.Journal of Applied Meteorological Science, 19(3): 325-332. (in Chinese)Using the data of precipitation including 144 meteorological and hydrological stations in Xinjiang from 1961 to 2005, annual and seasonal distributing features and its variations of area precipitation in Xinjiang are discussed by empirical orthogonal function(EOF), multiple regression analysis, maximum entropy analysis and so on, combining with 1 km 1 km gridding data of digital elevation model (DEM). Results show that mean annual area precipitation in Xinjiang region is 2724.6 108t and mean annual precipitation is 165.5 mm. For space distribution, area precipitation of Tianshan Mountains, Northern Xinjiang and Southern Xinjiang respectively occupy about 40.4%, 34.3% and 25.3% of all regions, and its mean annual precipitation are 409.1 mm, 277.3 mm and 66.2 mm, respectively. Area precipitation in summer is the most one about 54.4% of all year, 23.6% in spring, 16.5% in autumn, and the least 5.5% in winter. In the last 45 years area precipitation in Xinjiang presents clear annual variations and increasing trend, especially since 1987.

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Stocker T F, Qin D, Plattner G-K et al., 2013. Climate Change 2013: The Physical Science Basis. Cambridge: Cambridge University Press.

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Tian Hongzhen, Yang Taibao, Liu Qinping, 2014. Climate change and glacier area shrinkage in the Qilian Mountains, China, from 1956 to 2010.Annals of Glaciology, 55(66): 187-197.Glaciers in the Qilian mountains, located in the northeastern part of the Tibetan Plateau, constitute an important freshwater resource for downstream populations and natural systems. To enhance our understanding of the variability of the glaciers, temporally and spatially comprehensive information on them is needed. In this study, the glacier outlines of ~1990, ~2000 and ~2010 for the whole area were delineated in a semi-automated manner using band TM3/TM5 ratio images of Landsat ETM+ or TM scenes with the help of a merged ASTER GDEM/SRTM v4.1 digital elevation model. Combining our own results with those of previously published studies that span the period back to 1956, we found that the glacier area shrank by 30 8% from 1956 to 2010 and the shrinkage accelerated remarkably in the past two decades. The linear trends of annual air temperature and precipitation measured at weather stations within the glacierized areas were 0.03-0.058C a-1 (significant only after 2000) and 0.37-1.58mm a-1 (not significant) respectively from 1961 to 2010. Glaciers shrank mainly due to the increasing temperature. Glaciers in the Qilian mountains are very unlikely to have experienced positive mass balance over the past decade. Moreover, given the trend toward higher temperatures, the glaciers in this region will continue to shrink.

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Wang Puyu, Li Zhongqin, Gao Wenyu, 2011. Rapid shrinking of glaciers in the Middle Qilian Mountain region of Northwest China during the last 50 years.Journal of Earth Science, 22(4): 539-548.During the past five decades, fluctuations of glaciers were reconstructed from historical documents, aerial photographs, and remote sensing data. From 1956 to 2003, 910 glaciers investigated had reduced in area by 21.7% of the 1956 value, with a mean reduction for the individual glacier of 0.10 km(2). The relative area reductions of small glaciers were usually higher than those of large ones, which exhibited larger absolute loss, indicating that the small glaciers were more sensitive to climate change than large ones. Over the past similar to 50 years, glacier area decreased by 29.6% in the Heihe (sic) River basin and 18.7% in the Beidahe (sic) River basin, which were the two regions investigated in the Middle Qilian (sic) Mountain region. Compared with other areas of the Qilian Mountain region, the most dramatic glacier shrinkage had occurred in the Middle Qilian Mountain region, mainly resulting from rapid rising temperatures. Regional differences in glacier area changes are related to local climate conditions, the relative proportion of glaciers in different size classes, and other factors.

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Wang Shengjie, Zhang Mingjun, Sun Meipinget al., 2013. Changes in precipitation extremes in alpine areas of the Chinese Tianshan Mountains, Central Asia, 1961-2011.Quaternary International, 311(11): 97-107.Based on the gridded and observed daily precipitation datasets from 1961 to 2011, changes in daily precipitation extremes in alpine areas of the Chinese Tianshan Mountains are discussed. Four indices that represent extreme precipitation events are selected and calculated. Maximum 5-day precipitation, simple daily intensity index and very wet day precipitation have increased significantly by 1.18mm, 0.09mm/d, and 6.75mm per decade, respectively, while consecutive dry days have decreased at a rate of 5.83 days per decade during the study period. Changes in probability distribution functions of precipitation indices before and after the detected abrupt year also indicate a wetting trend. Generally, the linear trends of precipitation indices are spatially coherent. Approximately 79.0%, 83.8%, and 98.1% of the grid boxes show increasing trends for maximum 5-day precipitation, simple daily intensity index and very wet day precipitation, respectively, and the proportion of decreasing trends for consecutive dry days is 95.2%. Trends in most precipitation indices (except consecutive dry days) are highly correlated with total precipitation trends ( p <0.0001). Significant correlations between precipitation indices and Northern Hemisphere Annular Mode Index (also referred as Arctic Oscillation Index) in wintertime indicate that precipitation extremes in the study area are related to the Arctic Oscillation.

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Wei Jie, Ma Zhuguo, 2003. Comparison of palmer drought severity index, percentage of precipitation anomaly and surface humid index.Acta Geographica Sinica, 58(Suppl.): 117-124. (in Chinese)The monthly PDSI, surface moisture index and percentage of precipitation anomaly are calculated for the past 49 years with data from 160 stations in China. The result shows that PDSI and surface moisture index can grasp rainfall, a decisive factor of drought. Moreover, they reflect the process of drought on a greater space and time scale. In the region with more actual evaporation, PDSI describes the severity of drought more precisely than percentage of precipitation anomaly. In North China, before the 1980s, the rainfall was more sufficient, the temperature was higher and the potential evaporation was lower. It was a relatively moist period. Since the 1980s, the rainfall has been less sufficient together with higher temperature, the drought in North China has become more and more severe.

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Yang Qing, Sun Churong, Shi Yuguanget al., 2006. Estimation of areal precipitation series and its relation to runoff in Aksu river basin.Acta Geographica Sinica, 61(7): 697-704. (in Chinese)<p>Based on Digital Elevation Model with a spatial resolution of 1 km&times;1 km, the data of annual precipitation obtained from 12 meteorological and 2 hydrological stations (1961-2000) in the Aksu river catchment was filtered using Empirical Orthogonal Function (EOF). Through regression analysis, an interpolation model between the main characteristic vectors of EOF and geographical parameters was established. The annual areal precipitation was calculated from this model, and it is proved to be an efficient scheme to establish areal mean series of climate element. As a result, the annual areal precipitation and its spatial distribution are calculated on the grids that covered the basin. Point estimates were verified against meteorological or hydrological station data. The ratio (R/P) of the runoff of the Aksu river and calculated areal precipitation is 0.43 on average, the maximum is 0.69 (1997) and the minimum 0.30 (1963). The rates of changing trends of calculated areal precipitation and the observed runoff of Aksu river were 5.79&times;10<sup>8</sup> m<sup>3</sup>/10a and 4.29&times;10<sup>8</sup> m<sup>3</sup>/10a respectively, and both of them presented an increasing trend. The annual changing trend and extent of the areal precipitation are higher than those of the runoff. Both of their coefficients of variation (Cv) are 0.17 and 0.13, respectively. There is a close relationship between the annual runoff and annual areal precipitation and 0<sup>o</sup>C level height in summer. So the climate change after the 1990s in Xinjiang was the main cause for stable runoff increase in the Aksu river basin.</p>

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Zhang Liang, Zhang Qiang, Feng Jianyinget al., 2014. A study of atmospheric water cycle over the Qilian Mountains (I): Variation of annual water vapor transport.Journal of Glaciology and Geocryology, 36(5): 1079-1091. (in Chinese)In this paper, reanalysis data (NCEP Ⅰ, NCEP Ⅱ and ECMWF) were comparing with radiosonde data. NCEP Ⅰ reanalysis data, together with observational meteorological data, were used to study the characteristics of water vapor transport over the Qilian Mountains for the period of 1960-2010. The reason of water vapor transport changing was analyzed. The relationships between summer precipitation and the East Asian Monsoon, the South Asian Monsoon, South China Sea Monsoon, zonal wind and subtropical anticyclone were also investigated. The results show that the precipitable water showed an obvious downward trend in the 1960s, and then has basically remained stable from the 1970s to present. As a whole, it is a decline trend. The remained water vapor has decreased and the net water balance has obviously gone down. Hereinto, the whole meridional water vapor transport, i.e., north wind transport, has appeared positive value, resulting in positive contribution to net moisture budget. The whole zonal water vapor transport, i.e., westerly transport, has appeared negative value, resulting in negative contribution to net moisture budget. Moreover, wind speed decreasing has resulted directly in water vapor transport decreasing and has further decreased net moisture budget. The change in wind speed averaged from ground surface to 300 hPa height shows that zonal wind speed decreased by 13.2% in the 1990s as compared to that in the 1960s, and meridional wind speed decreased by 10.5%. The correlation coefficients between summer precipitation and summer monsoon indices show that the correlations are poor in western part, middle part and eastern part of the Qilian Mountains, which are mainly caused by the effects of special terrain, condition of circulation, researching season and time scale.

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Zhang Qiang, Yu Yaxun, Zhang Jie, 2008. Characteristics of water cycle in the Qilian Mountains and the oases in Hexi inland river basins.Journal of Glaciology and Geocryology, 30(6): 907-913. (in Chinese)

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Zhang Qiang, Zhang Cunjie, Bai Huzhiet al., 2010. New development of climate change in northwest China and its impact on arid environment.Journal of Arid Meteorology, 28(1): 1-7. (in Chinese)Over the past 50 years,temperature in the Northwest China presented a significant rising trend,while precipitation change was different in different place.Warming and drying trend is evident in the whole Northwest China,but the local appears warming and wetting phenomenon.With the global warming,glaciers retreat and snow line rises,permafrost melts,wetlands degradation,lakes shrink,river flows decrease,water resource becomes scarcer,and eco-environmental degradation.According to IPCC forecast results,the climate warming trend in this region in the future will be more pronounced.The countermeasures to protect the ecological environment,improve the comprehensive climate change monitoring system,launch specific research on the key regional climate change processes,and other suggestions were put forward.

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Zhang Qiang, Zhang Jie, Sun Guowuet al., 2007. Research on atmospheric water-vapor distribution over Qilianshan Mountains.Acta Meteorologica Sinica, 65(4): 633-643. (in Chinese)

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Zhang Renhe, 2001. Relations of water vapor transports from Indian monsoon with those over East Asia and the summer rainfall in China.Advances in Atmospheric Sciences, 18(5): 1005-1017.A diagnostic study is made to investigate the relationship between water vapor transport from Indian monsoon and that over East Asia in Northern summer. It is found that water vapor transport from Indian monsoon is inverse to that over East Asia. More (less) Indian monsoon water vapor transport corresponds to less (more) water vapor transport over East Asia and less (more) rainfall in the middle and lower reaches of the Yangtze River valley. The Indian summer monsoon water vapor transport is closely related to the in tensity of the western Pacific subtropical high in its southwestern part. The stronger (weaker) the Indian sum mer monsoon water vapor transport, the weaker (stronger) the western Pacific subtropical high in its southwestern part, which leads to less (more) water vapor transport to East Asia, and thus less (more) rain fall in the middle and lower reaches of the Yangtze River valley. Analysis of the out-going longwave radia tion anomalies suggests that the convective heating anomalies over the Indian Ocean may have significant impact not only on the Indian monsoon, but also on the East Asian monsoon.

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Zhang Zhixian, Zhang Qiang, Zhang Qingyunet al., 2013. Radar quantitative precipitation inversion and its application to areal rainfall estimation in the northeastern marginal areas of the Tibetan Plateau.Journal of Glaciology and Geocryology, 35(3): 621-629. (in Chinese)<p>Using radar-rain gauge to estimate areal rainfall is one of the major ways to improve the application of radar, which has great advantages in both the wide coverage of radar scanning and high single-point precision of rain-gauge. Based on the correlation with radar echo and rainfall in northeastern marginal areas of the Tibetan Plateau, a regional heavy rain case on May 10, 2012, is compared and spatial calibrated by using average calibration, optimal interpolation and variational-Kalman filter. It is found that the <em>Z-I</em> relationship with terrain is very different. Compared with precipitation observation, one can see that the local <em>Z-I</em> relationship by method of optimization is better than the others in diverse bands or districts, which effectively changes the situation of estimating lowly. In the mean time, the variational-Kalman filter method has the advantage of radar areal scan, which nicely reflected the spatial distribution of rainfall, able to calibrate well. In addition, it will be more effective in spatial precipitation estimation if take correct mathematical measures through the equations with multi-elevation angles and multi variable.</p>

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Zhao Ling, Yang Qing, An Shazhou, 2013. Distribution and change characteristics of areal precipitation in Tianshan Mountains during 1961-2010.Desert and Oasis Meteorology, 7(2): 20-24. (in Chinese)This paper analysed annual and seasonal distribution and change characteristics of aeral precipitation if Tianshan mountains using 44 meteorological and hydrological stations during 19612009 and 1 km 1 km digital elevation model(DEM)data.The methodologies include EOF,multiregression analysis,maximum entropy analysis and Geographic Information System.In Tianshan mountains,annual mean areal precipitation is around 1 903.2 108 m3.To seasonal distributions,summer has the most areal precipitation.Over the past 50 years from 1961 to 2009,the inter annual variation range of precipitation in Tianshan mountains was relatively large and presented an increasing trend.Especially since 1987,precipitation had increased significantly.

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Zhao Yufei, Zhu Jiang, Xu Yan, 2014. Establishment and assessment of the grid precipitation datasets in China for recent 50 years.Journal of the Meteorological Sciences, 34(4): 414-420. (in Chinese)Based on the high-quality precipitation data from 2,400 stations over China through the ANUSPLIN software developed by Australian National University with thin plate smooth spline method,interpolation scheme adopting three variables( longitude,latitude,altitude),precipitation square pretreatment and three times spline was set up,then the digital altimetric data was introduced in order to weaken the effects of elevation on interpolation precision of precipitation square under the condition of Chinese special landscape,finally the datasets of daily and monthly 0. 5 0. 5 grid-based precipitation over China from 1961 to 2010 were established by interpolating the precipitation data. Cross-validation tests show that this gauge-based analysis worked quite well with annual interpolation error typically less than 0. 49 mm and the relation coefficient amounting to 0. 93; monthly error depended on period and region,it was more in summer than in winter,and it was more in the east and west than in other areas. The mean bias error of the most gauges was between- 10 mm /month and 10 mm /month. The relative bias error of 60%,82%,54% and77% gauges were between-10% and 10%. This kind of datasets is helpful to explore the spatial and temporal distributions of the precipitation,but it still ignores narrow-range rainfall extreme centers. It can be usedwidely in weather /climate monitoring,climate analysis,numerical model verifications,ecological assessment and hydrological studies.

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