scholarly journals Dissecting Performances of PERSIANN-CDR Precipitation Product over Huai River Basin, China

2019 ◽  
Vol 11 (15) ◽  
pp. 1805 ◽  
Author(s):  
Sun ◽  
Zhou ◽  
Shen ◽  
Chai ◽  
Chen ◽  
...  
Keyword(s):  
River Basin ◽  
Daily Precipitation ◽  
Poor Performance ◽  
Rain Gauge ◽  
Probability Of Detection ◽  
Climate Data ◽  
Rainfall Events ◽  
Huai River Basin ◽  
Daily Precipitation Data ◽  
Huai River

Satellite-based precipitation products, especially those with high temporal and spatial resolution, constitute a potential alternative to sparse rain gauge networks for multidisciplinary research and applications. In this study, the validation of the 30-year Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) daily precipitation dataset was conducted over the Huai River Basin (HRB) of China. Based on daily precipitation data from 182 rain gauges, several continuous and categorical validation statistics combined with bias and error decomposition techniques were employed to quantitatively dissect the PERSIANN-CDR performance on daily, monthly, and annual scales. With and without consideration of non-rainfall data, this product reproduces adequate climatologic precipitation characteristics in the HRB, such as intra-annual cycles and spatial distributions. Bias analyses show that PERSIANN-CDR overestimates daily, monthly, and annual precipitation with a regional mean percent total bias of 11%. This is related closely to the larger positive false bias on the daily scale, while the negative non-false bias comes from a large underestimation of high percentile data despite overestimating lower percentile data. The systematic sub-component (error from high precipitation), which is independent of timescale, mainly leads to the PERSIANN-CDR total Mean-Square-Error (TMSE). Moreover, the daily TMSE is attributed to non-false error. The correlation coefficient (R) and Kling–Gupta Efficiency (KGE) respectively suggest that this product can well capture the temporal variability of precipitation and has a moderate-to-high overall performance skill in reproducing precipitation. The corresponding capabilities increase from the daily to annual scale, but decrease with the specified precipitation thresholds. Overall, the PERSIANN-CDR product has good (poor) performance in detecting daily low (high) rainfall events on the basis of Probability of Detection, and it has a False Alarm Ratio of above 50% for each precipitation threshold. The Equitable Threat Score and Heidke Skill Score both suggest that PERSIANN-CDR has a certain ability to detect precipitation between the second and eighth percentiles. According to the Hanssen–Kuipers Discriminant, this product can generally discriminate rainfall events between two thresholds. The Frequency Bias Index indicates an overestimation (underestimation) of precipitation totals in thresholds below (above) the seventh percentile. Also, continuous and categorical statistics for each month show evident intra-annual fluctuations. In brief, the comprehensive dissection of PERSIANN-CDR performance reported herein facilitates a valuable reference for decision-makers seeking to mitigate the adverse impacts of water deficit in the HRB and algorithm improvements in this product.

A 33-yr Mei-Yu-Season Climatology of Shear Lines over the Yangtze–Huai River Basin in Eastern China

2020 ◽  
Vol 59 (6) ◽  
pp. 1125-1137
Author(s):  
Xiuping Yao ◽  
Jiali Ma ◽  
Da-Lin Zhang ◽  
Lizhu Yan
Keyword(s):  
River Basin ◽  
Heavy Rainfall ◽  
Eastern China ◽  
Rain Gauge ◽  
Reanalysis Data ◽  
Central Basin ◽  
The South ◽  
South Central ◽  
Huai River Basin ◽  
Huai River

AbstractA 33-yr climatology of shear lines occurring over the Yangtze–Huai River basin (YHSLs) of eastern China during the mei-yu season (i.e., June and July) of 1981–2013 is examined using the daily ERA-Interim reanalysis data and daily rain gauge observations. Results show that (i) nearly 75% of the heavy-rainfall days (i.e., >50 mm day−1) are accompanied by YHSLs, (ii) about 66% of YHSLs can produce heavy rainfall over the Yangtze–Huai River basin, and (iii) YHSL-related heavy rainfall occurs frequently in the south-central basin. The statistical properties of YHSLs are investigated by classifying them into warm, cold, quasi-stationary, and vortex types based on their distinct flow and thermal patterns as well as orientations and movements. Although the warm-type rainfall intensity is the weakest among the four, it has the highest number of heavy-rainfall days, making it the largest contributor (33%) to the total mei-yu rainfall amounts associated with YHSLs. By comparison, the quasi-stationary type has the smallest number of heavy-rainfall days, contributing about 19% to the total rainfall, whereas the vortex type is the more frequent extreme-rain producer (i.e., >100 mm day−1). The four types of YHSLs are closely related to various synoptic-scale low-to-midtropospheric disturbances—such as the southwest vortex, low-level jets, and midlatitude traveling perturbations that interact with mei-yu fronts over the basin and a subtropical high to the south—that provide favorable lifting and the needed moisture supply for heavy-rainfall production. The results have important implications for the operational rainfall forecasts associated with YHSLs through analog pattern recognition.

scholarly journals Evaluation of High-Resolution Gridded Precipitation Data in Arid and Semiarid Regions: Heihe River Basin, Northwest China

2017 ◽  
Vol 18 (12) ◽  
pp. 3075-3101 ◽  
Author(s):  
Yi Yang ◽  
Jianping Tang ◽  
Zhe Xiong ◽  
Xinning Dong
Keyword(s):  
High Resolution ◽  
River Basin ◽  
Warm Season ◽  
Poor Performance ◽  
Northwest China ◽  
Rain Gauge ◽  
Probability Of Detection ◽  
Heihe River Basin ◽  
Heihe River ◽  
China Meteorological Administration

Abstract The reliability of three satellite-derived precipitation products, Tropical Rainfall Measuring Mission (TRMM) 3B42 V7 and the Climate Prediction Center morphing technique (CMORPH) satellite-only (CMORPH-RAW) and gauge-corrected versions (CMORPH-CRT), and three gauge-based precipitation datasets, Asian Precipitation–Highly Resolved Observational Data Integration Toward Evaluation of Water Resources (APHRODITE), National Climate Center of China Meteorological Administration (CN05.1), and Institute of Tibetan Plateau Research, Chinese Academy of Sciences (ITPCAS), is evaluated via comparisons with rain gauge observations from stations over the Heihe River basin (HRB) for the period from 1998 to 2012. The results show that the observed climatology, interannual variability, the detection of precipitation events, and probability density functions (PDFs) are reasonably well represented by the high-resolution precipitation products (HRPPs), with APHRODITE presenting the best performance, CN05.1 and ITPCAS exhibiting similar performances, and CMORPH-CRT showing a poor performance. The bias-correction algorithms applied in CMORPH-CRT improve the accuracy of CMORPH-RAW slightly but fail to improve the rainfall detection skill. TRMM consistently outperforms CMORPH-CRT at various scales, whereas CMORPH-CRT is comparable to TRMM in summer. The spatial correlations, normalized root-mean-square error (NRMSE), and probability of detection (POD) show that all datasets perform better in summer than in winter. Except for CMORPH-RAW, the HRPPs could adequately reproduce the unimodal characteristics of annual cycle, although they overestimate the magnitude of the warm season precipitation. The HRPPs could capture the overall spatial distribution and decadal trend of extreme precipitation indices. However, the satellite-derived products overestimate the wet day precipitation and underestimate the consecutive dry days, although the TRMM generates relatively better results.

scholarly journals Capacity of the PERSIANN-CDR Product in Detecting Extreme Precipitation over Huai River Basin, China

2021 ◽  
Vol 13 (9) ◽  
pp. 1747
Author(s):  
Shanlei Sun ◽  
Jiazhi Wang ◽  
Wanrong Shi ◽  
Rongfan Chai ◽  
Guojie Wang
Keyword(s):  
River Basin ◽  
Extreme Precipitation ◽  
Precipitation Amount ◽  
Climate Data ◽  
Validation Metrics ◽  
Huai River Basin ◽  
Huai River ◽  
Precipitation Estimation ◽  
Precipitation Changes ◽  
Linear Trends

Assessing satellite-based precipitation product capacity for detecting precipitation and linear trends is fundamental for accurately knowing precipitation characteristics and changes, especially for regions with scarce and even no observations. In this study, we used daily gauge observations across the Huai River Basin (HRB) during 1983–2012 and four validation metrics to evaluate the Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) capacity for detecting extreme precipitation and linear trends. The PERSIANN-CDR well captured climatologic characteristics of the precipitation amount- (PRCPTOT, R85p, R95p, and R99p), duration- (CDD and CWD), and frequency-based indices (R10mm, R20mm, and Rnnmm), followed by moderate performance for the intensity-based indices (Rx1day, R5xday, and SDII). Based on different validation metrics, the PERSIANN-CDR capacity to detect extreme precipitation varied spatially, and meanwhile the validation metric-based performance differed among these indices. Furthermore, evaluation of the PERSIANN-CDR linear trends indicated that this product had a much limited and even no capacity to represent extreme precipitation changes across the HRB. Briefly, this study provides a significant reference for PERSIANN-CDR developers to use to improve product accuracy from the perspective of extreme precipitation, and for potential users in the HRB.

scholarly journals Spatiotemporal Changes and Frequency Analysis of Multiday Extreme Precipitation in the Huai River Basin during 1960 to 2014

2019 ◽  
Vol 2019 ◽  
pp. 1-12
Author(s):  
Yixing Yin ◽  
Xin Pan ◽  
Xiuqin Yang ◽  
Xiaojun Wang ◽  
Guojie Wang ◽  
...  
Keyword(s):  
River Basin ◽  
Frequency Analysis ◽  
Extreme Precipitation ◽  
Abrupt Change ◽  
Upward Trend ◽  
Huai River Basin ◽  
Daily Precipitation Data ◽  
Significant Downward Trend ◽  
Huai River ◽  
The Huai River Basin

Floods and droughts are more closely related to the extreme precipitation over longer periods of time. The spatial and temporal changes and frequency analysis of 5-day and 10-day extreme precipitations (PX5D and PX10D) in the Huai River basin (HRB) are investigated by means of correlation analysis, trend and abrupt change analysis, EOF analysis, and hydrological frequency analysis based on the daily precipitation data from 1960 to 2014. The results indicate (1) PX5D and PX10D indices have a weak upward trend in HRB, and the weak upward trend may be due to the significant downward trend in the 21st century, (2) the multiday (5-day and 10-day) extreme precipitation is closely associated with flood/drought disasters in the HRB, and (3) for stations of nonstationary changes with significant upward trend after the abrupt change, if the whole extreme precipitation series are used for frequency analysis, the risk of future floods will be underestimated, and this effect is more pronounced for longer return periods.

Impact of Water Projects on River Flow Regimes and Water Quality in Huai River Basin

2009 ◽  
Vol 24 (5) ◽  
pp. 889-908 ◽  
Author(s):  
Yongyong Zhang ◽  
Jun Xia ◽  
Tao Liang ◽  
Quanxi Shao
Keyword(s):  
Water Quality ◽  
River Basin ◽  
River Flow ◽  
Flow Regimes ◽  
Water Projects ◽  
Huai River Basin ◽  
Huai River

scholarly journals Drought evolution characteristics and precipitation intensity changes during alternating dry-wet changes in the Huang-Huai-Hai River basin

2013 ◽  
Vol 10 (3) ◽  
pp. 2665-2696 ◽  
Author(s):  
D. H. Yan ◽  
D. Wu ◽  
R. Huang ◽  
L. N. Wang ◽  
G. Y. Yang
Keyword(s):  
River Basin ◽  
Inner Mongolia ◽  
Precipitation Intensity ◽  
Occurrence Frequency ◽  
Drought Frequency ◽  
Piedmont Plain ◽  
Daily Precipitation Data ◽  
Huai River ◽  
Increasing Trend ◽  
Frequency Changes

Abstract. According to the Chinese climate divisions and the Huang-Huai-Hai River basin digital elevation map, the basin is divided into seven sub-regions by means of cluster analysis of the basin meteorological stations using the self-organizing map (SOM) neural network method. Based on the daily precipitation data of 171 stations for the years 1961–2011, the drought frequency changes with different magnitudes are analyzed and the number of consecutive days without precipitation is used to identify the drought magnitudes. The first precipitation intensity after a drought period is analyzed with the Pearson-III frequency curve, then the relationship between rainfall intensity and different drought magnitudes is observed, as are the drought frequency changes for different years. The results of the study indicated the following: (1) the occurrence frequency of different drought level shows an overall increasing trend; there is no clear interdecadal change shown, but the spatial difference is significant. The occurrence frequencies of severe and extraordinary drought are higher on the North China Plain, Hetao Plains in Ningxia-Inner Mongolia, as well as on the Inner Mongolia and the Loess Plateaus, and in the Fen-Wei Valley basin. (2) As the drought level increases, the probability of extraordinary rainstorm becomes lower, and the frequency of occurrence of spatial changes in different precipitation intensities vary. In the areas surrounding Bo Sea, the Shandong Peninsula and the Huai River downstream, as the drought level increases, the occurrence frequency of different precipitation intensities first shows a decreasing trend, which becomes an increasing trend when extraordinary drought occurs. In the middle and upper reaches of the Huai River basin, on the Hai River basin piedmont plain and Hetao Plains in Ningxia-Inner Mongolia, Inner Mongolia and Loess Plateaus, and in the Fen-Wei Valley basin, the probability of the different precipitation intensities shows an overall decreasing trend. The mountains with high attitude and Tibetan Plateau are located at high altitudes where the variation of different precipitation intensities with the increase in drought level is relatively complex. (3) As the drought frequency increases, areas I, II and V which are located on the coastal and in the river basin are vulnerable to extreme precipitation processes; areas III, IV, VI and VII are located in the inland area where heavier precipitation is not likely to occur.

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