scholarly journals Patterns of Extreme Precipitation and Characteristics of Related Systems in the Northern Xinjiang Region

Atmosphere ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 358
Author(s):  
Rui Xu ◽  
Jie Ming
Keyword(s):  
Water Vapor ◽  
Extreme Precipitation ◽  
Daily Precipitation ◽  
Principal Component ◽  
Reanalysis Data ◽  
Water Vapor Transport ◽  
Northern Xinjiang ◽  
The North ◽  
Western Tianshan ◽  
Daily Precipitation Data

Based on 40 years of daily precipitation, 272 extreme precipitation days in the Northern Xinjiang region are defined. Using the daily precipitation data on these days, four precipitation spatial patterns were obtained through principal component analysis. Then, daily-averaged reanalysis data were used to analyze the variations of synoptic systems on extreme precipitation days and the two days before and after. The rainfall centers shifted with the influential systems at 500 hPa. Water vapor of the western Tianshan type (Type WT) and the north of Northern Xinjiang type (Type NN) comes from the west, while vapor of the Central Tianshan type (Type CT) mainly comes from the east. In the east of Northern Xinjiang type (Type EN), water vapor converges from both sides. The centers of the upper-level jets are located west of 80° E in Type WT and CT. However, they are to the east of 80° E in the other types. This article summarizes the variations of the systems at 500 hPa, the South Asia High, the westerly jet, and the water vapor transport between the surface and 500 hPa in four types of patterns, and builds the conceptual model for each type. The models built can be applied to the heavy rainfall forecast of Northern Xinjiang.

Estimation of the precipitable water and water vapor flux using MAX-DOAS in two typical  cities of China

2021 ◽  
Author(s):  
Hongmei Ren ◽  
Ang Li ◽  
Pinhua Xie ◽  
Zhaokun Hu ◽  
Jin Xu ◽  
...  
Keyword(s):  
Water Vapor ◽  
Precipitable Water ◽  
Reanalysis Data ◽  
Vapor Transport ◽  
Water Vapor Transport ◽  
Optical Absorption Spectroscopy ◽  
Water Vapor Flux ◽  
Vapor Flux ◽  
The North ◽  
Two Cities

<p>      Water vapor transport affects regional precipitation and climate change. The measurement of precipitable water and water vapor flux is of great significance to the study of precipitation and water vapor transport. In the study, a new method of computing the precipitable water and estimating the water vapor transport flux using multi-axis differential optical absorption spectroscopy (MAX-DOAS) were presented. The calculated precipitable water and water vapor flux were compared to the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis data and the correlation coefficient of the precipitable water, the zonal and meridional water vapor flux and ECMWF are r≥0.92, r=0.77 and r≥0.89, respectively. The seasonal and diurnal climatologies of precipitable water and water vapor flux in the coastal (Qingdao) and inland (Xi’an) cities of China using this method were analyzed from June 1, 2019 to May 31, 2020. The results indicated that the seasonal and diurnal variation characteristics of the precipitable water in the two cities were similar. The zonal fluxes of the two cities were mainly transported from west to east, Qingdao's meridional flux was mainly transported to the south, and Xi'an was mainly transported to the north. The results also indicated that the water vapor flux transmitting belts appear near 2km and 1.4km above the surface in Qingdao and appeared around 2.8km, 1.6km and 1.0km in Xi'an. </p>

scholarly journals Anomalous Circulation Patterns in Association with Summertime Regional Daily Precipitation Extremes over Northeast China

2019 ◽  
Vol 2019 ◽  
pp. 1-9
Author(s):  
Chuanlei Chen ◽  
Zhaoyong Guan ◽  
Min Jiao ◽  
Pengyu Hu
Keyword(s):  
Water Vapor ◽  
Strong Convergence ◽  
Extreme Precipitation ◽  
Northeast China ◽  
Daily Precipitation ◽  
Cyclonic Circulation ◽  
Northwest Pacific ◽  
Convergence Zone ◽  
Anticyclonic Circulation ◽  
The North

Based on the NCEP/NCAR daily reanalysis product, NOAA monthly sea surface temperature (SST) dataset, and daily precipitation data collected at observational stations provided by Meteorological Information Center of China Meteorological Administration, the present study analyzes characteristic circulation anomalies conducive to regional extreme daily precipitation in the summer over Northeast China. Results indicate that 26 extreme precipitation events occurred during the 36-year period of 1979–2014. The precipitation threshold for the 99th percentile is 22.2 mm/d, and the maximum extreme daily precipitation occurred in Liaoning Province. When extreme precipitation occurs, Northeast China is located to the southeast of an anomalous cyclonic circulation and northwest of an anomalous anticyclonic circulation, where a strong convergence zone is formed in the lower troposphere. The low-level convergence and upper-level divergence as well as the baroclinic circulation structure are favorable for the development of extreme daily precipitation. Meanwhile, there exist two symmetrical meridional circulations to the north and south of Northeast China. The two meridional circulations share the same ascending branch, which is conducive to the occurrence of precipitation. Located in the strong convergence zone to the southeast of the abnormal cyclonic circulation and northwest of the abnormal anticyclonic circulation, huge amounts of water vapor from the Inner Mongolia, Russia, the Japan Sea, and the mid-high latitudes of the Northwest Pacific are transported to Northeast China, providing sufficient water vapor condition for the occurrence of extreme daily precipitation in this region. In addition, daily extreme precipitation in Northeast China is also closely related to the accumulation and convergence of disturbance energy in Northeast China. It may also be related to the abnormal SST distribution that is high in the north and low in the south. Corresponding to extreme daily precipitation, SST anomaly in the Pacific Ocean is roughly characterized by the feature of “positive-north and negative- south” with the equator as the boundary.

scholarly journals Changes in Winter Atmospheric Rivers along the North American West Coast in CMIP5 Climate Models

2015 ◽  
Vol 16 (1) ◽  
pp. 118-128 ◽  
Author(s):  
Michael D. Warner ◽  
Clifford F. Mass ◽  
Eric P. Salathé
Keyword(s):  
Water Vapor ◽  
North American ◽  
West Coast ◽  
American West ◽  
Climate Models ◽  
Water Vapor Transport ◽  
The West ◽  
North American West ◽  
The North ◽  
Extreme Precipitation Events

Abstract Most extreme precipitation events that occur along the North American west coast are associated with winter atmospheric river (AR) events. Global climate models have sufficient resolution to simulate synoptic features associated with AR events, such as high values of vertically integrated water vapor transport (IVT) approaching the coast. From phase 5 of the Coupled Model Intercomparison Project (CMIP5), 10 simulations are used to identify changes in ARs impacting the west coast of North America between historical (1970–99) and end-of-century (2070–99) runs, using representative concentration pathway (RCP) 8.5. The most extreme ARs are identified in both time periods by the 99th percentile of IVT days along a north–south transect offshore of the coast. Integrated water vapor (IWV) and IVT are predicted to increase, while lower-tropospheric winds change little. Winter mean precipitation along the west coast increases by 11%–18% [from 4% to 6% (°C)−1], while precipitation on extreme IVT days increases by 15%–39% [from 5% to 19% (°C)−1]. The frequency of IVT days above the historical 99th percentile threshold increases as much as 290% by the end of this century.

scholarly journals Features of Extreme Precipitation at Progress Station, Antarctica

2018 ◽  
Vol 31 (22) ◽  
pp. 9087-9105 ◽  
Author(s):  
Lejiang Yu ◽  
Qinghua Yang ◽  
Timo Vihma ◽  
Svetlana Jagovkina ◽  
Jiping Liu ◽  
...  
Keyword(s):  
Water Vapor ◽  
Extreme Precipitation ◽  
Dynamic Processes ◽  
Annual Number ◽  
Positive Trend ◽  
Self Organizing Maps ◽  
Dipole Structure ◽  
Extreme Precipitation Events ◽  
Daily Precipitation Data ◽  
Precipitation Events

Observed daily precipitation data were used to investigate the characteristics of precipitation at Antarctic Progress Station and synoptic patterns associated with extreme precipitation events during the period 2003–16. The annual precipitation, annual number of extreme precipitation events, and amount of precipitation during the extreme events have positive trends. The distribution of precipitation at Progress Station is heavily skewed with a long tail of extreme dry days and a high peak of extreme wet days. The synoptic pattern associated with extreme precipitation events is a dipole structure of negative and positive height anomalies to the west and east of Progress Station, respectively, resulting in water vapor advection to the station. For the first time, we apply self-organizing maps (SOMs) to examine thermodynamic and dynamic perspectives of trends in the frequency of occurrence of Antarctic extreme precipitation events. The changes in thermodynamic (noncirculation) processes explain 80% of the trend, followed by the changes in the interaction between thermodynamic and dynamic processes, which account for nearly 25% of the trend. The changes in dynamic processes make a negative (less than 5%) contribution to the trend. The positive trend in total column water vapor over the Southern Ocean explains the change of thermodynamic term.

scholarly journals Identifying the Ideal Number Components of the Bayesian Principal Component Analysis Model for Missing Daily Precipitation Data Treatment

2018 ◽  
Vol 7 (4.30) ◽  
pp. 5 ◽  
Author(s):  
Zun Liang Chuan ◽  
Azlyna Senawi ◽  
Wan Nur Syahidah Wan Yusoff ◽  
Noriszura Ismail ◽  
Tan Lit Ken ◽  
...  
Keyword(s):  
Time Series ◽  
Daily Precipitation ◽  
Principal Component ◽  
Precipitation Data ◽  
Analysis Model ◽  
Principal Component Analysis Model ◽  
Data Treatment ◽  
Daily Precipitation Data ◽  
Ideal Number ◽  
The Ideal

The grassroots of the presence of missing precipitation data are due to the malfunction of instruments, error of recording and meteorological extremes. Consequently, an effective imputation algorithm is indeed much needed to provide a high quality complete time series in assessing the risk of occurrence of extreme precipitation tragedy. In order to overcome this issue, this study desired to investigate the effectiveness of various Q-components of the Bayesian Principal Component Analysis model associates with Variational Bayes algorithm (BPCAQ-VB) in missing daily precipitation data treatment, which the ideal number of Q-components is identified by using The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) algorithm. The effectiveness of BPCAQ-VB algorithm in missing daily precipitation data treatment is evaluated by using four distinct precipitation time series, including two monitoring stations located in inland and coastal regions of Kuantan district, respectively. The analysis results rendered the BPCA5-VB is superior in missing daily precipitation data treatment for the coastal region time series compared to the single imputation algorithms proposed in previous studies. Contrarily, the single imputation algorithm is superior in missing daily precipitation data treatment for an inland region time series rather than the BPCAQ-VB algorithm.   

scholarly journals Response of Extreme Precipitation to Urbanization over the Netherlands

2019 ◽  
Vol 58 (4) ◽  
pp. 645-661 ◽  
Author(s):  
Vahid Rahimpour Golroudbary ◽  
Yijian Zeng ◽  
Chris M. Mannaerts ◽  
Zhongbo Su
Keyword(s):  
The Netherlands ◽  
Extreme Precipitation ◽  
Large Scale ◽  
Daily Precipitation ◽  
Atmospheric Air ◽  
The North ◽  
Circulation Types ◽  
Return Levels ◽  
Air Temperatures ◽  
The North Atlantic Oscillation

AbstractKnowledge of the response of extreme precipitation to urbanization is essential to ensure societal preparedness for the extreme events caused by climate change. To quantify this response, this study scales extreme precipitation according to temperature using the statistical quantile regression and binning methods for 231 rain gauges during the period of 1985–2014. The positive 3%–7% scaling rates were found at most stations. The nonstationary return levels of extreme precipitation are investigated using monthly blocks of the maximum daily precipitation, considering the dependency of precipitation on the dewpoint, atmospheric air temperatures, and the North Atlantic Oscillation (NAO) index. Consideration of Coordination of Information on the Environment (CORINE) land-cover types upwind of the stations in different directions classifies stations as urban and nonurban. The return levels for the maximum daily precipitation are greater over urban stations than those over nonurban stations especially after the spring months. This discrepancy was found by 5%–7% larger values in August for all of the classified station types. Analysis of the intensity–duration–frequency curves for urban and nonurban precipitation in August reveals that the assumption of stationarity leads to the underestimation of precipitation extremes due to the sensitivity of extreme precipitation to the nonstationary condition. The study concludes that nonstationary models should be used to estimate the return levels of extreme precipitation by considering the probable covariates such as the dewpoint and atmospheric air temperatures. In addition to the external forces, such as large-scale weather modes, circulation types, and temperature changes that drive extreme precipitation, urbanization could impact extreme precipitation in the Netherlands, particularly for short-duration events.

scholarly journals Bias Correction of Zero-Inflated RCM Precipitation Fields: A Copula-Based Scheme for Both Mean and Extreme Conditions

2019 ◽  
Vol 20 (4) ◽  
pp. 595-611 ◽  
Author(s):  
Rajib Maity ◽  
Mayank Suman ◽  
Patrick Laux ◽  
Harald Kunstmann
Keyword(s):  
Climate Change ◽  
Bias Correction ◽  
Extreme Precipitation ◽  
Joint Distribution ◽  
Daily Precipitation ◽  
Extreme Values ◽  
Entire Study ◽  
Daily Precipitation Data ◽  
Zero Values ◽  
The Mean

Abstract Changes in extreme precipitation due to climate change often require the application of methods to bias correct simulated atmospheric fields, including extremes. Most existing bias correction techniques (i) only focus on the bias in the mean value or on the extreme values separately, and (ii) exclude zero values from analysis, even though their presence is significant in daily precipitation. We developed a copula-based bias correction scheme that is suitable for zero-inflated daily precipitation data to correct the bias in mean as well as in extreme precipitation at any specific statistical quantile. In considering the whole of Germany as a test bed, the proposed scheme is found to work well across the entire study area, including the German Alpine regions. The joint distribution between observed and regional climate model (RCM)-derived precipitation is developed through copulas. In particular, the joint distribution is modified to make it discrete at zero in order to account for zero values. The benefit of considering zero precipitation values is revealed through the improved performance of bias correction both in the mean and extreme values. Second, the quantile that best captures the bias (whether in the mean or any extreme value) is determined for a specific location and varies spatially and seasonally. This relaxation in selecting the location-specific optimal quantile renders the proposed methodology spatially transferable. By acknowledging possible changes in extreme precipitation due to climate change, the proposed scheme is expected to be suitable for climate change impact assessments for extreme events worldwide.

scholarly journals Development of a Pressure–Precipitation Transmitter

2019 ◽  
Vol 58 (11) ◽  
pp. 2453-2468
Author(s):  
Masaru Inatsu ◽  
Tamaki Suematsu ◽  
Yuta Tamaki ◽  
Naoto Nakano ◽  
Kao Mizushima ◽  
...  
Keyword(s):  
Regression Model ◽  
Daily Precipitation ◽  
Reanalysis Data ◽  
Precipitation Pattern ◽  
Multilevel Regression ◽  
Extreme Statistics ◽  
Spatial Continuity ◽  
Daily Precipitation Data ◽  
Multilevel Regression Model

AbstractA novel method is proposed to create very long term daily precipitation data for the extreme statistics by computing very long term daily sea level pressure (SLP) with the SLP emulator (a statistical multilevel regression model) and then converting the SLP into precipitation by combining statistical downscaling methods of the analog ensemble and singular value decomposition (SVD). After a review of the SLP emulator, we present a multilevel regression model constructed for each month that is based on a time series of 1000 principal components of SLPs on global reanalysis data. Simple integration of the SLP emulator provides 100-yr daily SLP data, which are temporally interpolated into a 6-h interval. Next, the pressure–precipitation transmitter (PPT) is developed to convert 6-hourly SLP to daily precipitation. The PPT makes its first-guess estimate from a composite of time frames with analogous SLP transition patterns in the learning period. The departure of SLPs from the analog ensemble is then corrected with an SVD relationship between SLPs and precipitation. The final product showed a fairly realistic precipitation pattern, displaying temporal and spatial continuity. The annual-maximum precipitation of the estimated 100-yr data extended the tail of probability distribution of the 8-yr learning data.

scholarly journals Precipitation and Water Vapor Transport in the Southern Hemisphere with Emphasis on the South American Region

2009 ◽  
Vol 48 (9) ◽  
pp. 1902-1912 ◽  
Author(s):  
Josefina Moraes Arraut ◽  
Prakki Satyamurty
Keyword(s):  
Water Vapor ◽  
South America ◽  
North Atlantic ◽  
Vapor Transport ◽  
Water Vapor Transport ◽  
The South ◽  
Meridional Transport ◽  
Moisture Flow ◽  
The North ◽  
The North Atlantic

Abstract December–March climatologies of precipitation and vertically integrated water vapor transport were analyzed and compared to find the main paths by which moisture is fed to high-rainfall regions in the Southern Hemisphere in this season. The southern tropics (20°S–0°) exhibit high rainfall and receive ample moisture from the northern trades, except in the eastern Pacific and the Atlantic Oceans. This interhemispheric flow is particularly important for Amazonian rainfall, establishing the North Atlantic as the main source of moisture for the forest during its main rainy season. In the subtropics the rainfall distribution is very heterogeneous. The meridional average of precipitation between 35° and 25°S is well modulated by the meridional water vapor transport through the 25°S latitude circle, being greater where this transport is from the north and smaller where it is from the south. In South America, to the east of the Andes, the moisture that fuels precipitation between 20° and 30°S comes from both the tropical South and North Atlantic Oceans whereas between 30° and 40°S it comes mostly from the North Atlantic after passing over the Amazonian rain forest. The meridional transport (across 25°S) curve exhibits a double peak over South America and the adjacent Atlantic, which is closely reproduced in the mean rainfall curve. This corresponds to two local maxima in the two-dimensional field of meridional transport: the moisture corridor from Amazonia into the continental subtropics and the moisture flow coming from the southern tropical Atlantic into the subtropical portion of the South Atlantic convergence zone. These two narrow pathways of intense moisture flow could be suitably called “aerial rivers.” Their longitudinal positions are well defined. The yearly deviations from climatology for moisture flow and rainfall correlate well (0.75) for the continental peak but not for the oceanic peak (0.23). The structure of two maxima is produced by the effect of transients in the time scale of days.

scholarly journals Characteristics and Changes of Extreme Precipitation in the Yellow–Huaihe and Yangtze–Huaihe Rivers Basins, China

2011 ◽  
Vol 24 (14) ◽  
pp. 3781-3795 ◽  
Author(s):  
Quan Dong ◽  
Xing Chen ◽  
Tiexi Chen
Keyword(s):  
Monte Carlo ◽  
Spatial Distribution ◽  
Extreme Precipitation ◽  
Daily Precipitation ◽  
Poyang Lake ◽  
Yellow River ◽  
Statistical Significance ◽  
Monte Carlo Experiment ◽  
Huaihe River ◽  
Daily Precipitation Data

Abstract Many works suggest that the intensity of extreme precipitation might be changing under the background of global warming. Because of the importance of extreme precipitation in the Yellow–Huaihe and Yangtze–Huaihe River basins of China and to compare the spatial difference, the generalized Pareto distribution (GPD) function is used to fit the daily precipitation series in these basins and an estimate of the extreme precipitation spatial distribution is presented. At the same time, its long-term trends are estimated for the period between 1951 and 2004 by using a generalized linear model (GLM), which is based on GPD. High quality daily precipitation data from 215 observation stations over the area are used in this study. The statistical significance of the trend fields is tested with a Monte Carlo experiment based on a two-dimensional Hurst coefficient, H2. The spatial distribution of the shape parameter of GPD indicates that the upper reaches of the Huaihe River (HuR) basin have the largest probability of extreme rainfall events, which is consistent with most historical flood records in this region. Spatial variations in extreme precipitation trends are found and show significant positive trends in the upper reaches of Poyang Lake in the Yangtze River (YaR) basin and a significant negative trend in the mid- to lower reaches of the Yellow River (YeR) and Haihe River (HaR) basins. The trends in the HuR basin and the lower reaches of Poyang Lake in the YaR basin are nearly neutral. All trend fields are significant at the 5% level of significance from the Monte Carlo experiments.

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