scholarly journals Reanalysis Product-Based Nonstationary Frequency Analysis for Estimating Extreme Design Rainfall

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 191
Author(s):  
Dong-IK Kim ◽  
Dawei Han ◽  
Taesam Lee
Keyword(s):  
South Korea ◽  
20Th Century ◽  
Frequency Analysis ◽  
Systematic Errors ◽  
Quantile Mapping ◽  
Reanalysis Product ◽  
Rainfall Analysis ◽  
Future Evolution ◽  
Design Rainfall ◽  
Nonstationary Frequency

Nonstationarity is one major issue in hydrological models, especially in design rainfall analysis. Design rainfalls are typically estimated by annual maximum rainfalls (AMRs) of observations below 50 years in many parts of the world, including South Korea. However, due to the lack of data, the time-dependent nature may not be sufficiently identified by this classic approach. Here, this study aims to explore design rainfall with nonstationary condition using century-long reanalysis products that help one to go back to the early 20th century. Despite its useful representation of the past climate, the reanalysis products via observational data assimilation schemes and models have never been tested in representing the nonstationary behavior in extreme rainfall events. We used daily precipitations of two century-long reanalysis datasets as the ERA-20c by the European Centre for Medium-Range Weather Forecasts (ECMWF) and the 20th century reanalysis (20CR) by the National Oceanic and Atmospheric Administration (NOAA). The AMRs from 1900 to 2010 were derived from the grids over South Korea. The systematic errors were downgraded through quantile delta mapping (QDM), as well as conventional stationary quantile mapping (SQM). The evaluation result of the bias-corrected AMRs indicated the significant reduction of the errors. Furthermore, the AMRs present obvious increasing trends from 1900 to 2010. With the bias-corrected values, we carried out nonstationary frequency analysis based on the time-varying location parameters of generalized extreme value (GEV) distribution. Design rainfalls with certain return periods were estimated based on the expected number of exceedance (ENE) interpretation. Although there is a significant range of uncertainty, the design quantiles by the median parameters showed the significant relative difference, from −30.8% to 42.8% for QDM, compared with the quantiles by the multi-decadal observations. Even though the AMRs from the reanalysis products are challenged by various errors such as quantile mapping (QM) and systematic errors, the results from the current study imply that the proposed scheme with employing the reanalysis product might be beneficial to predict the future evolution of extreme precipitation and to estimate the design rainfall accordingly.

Diagnosing and Debunking Korean Pseudohistory

2019 ◽  
pp. 37-80
Author(s):  
Andrew Logie
Keyword(s):  
South Korea ◽  
East Asia ◽  
20Th Century ◽  
Inner Mongolia ◽  
Political Influence ◽  
The Core ◽  
Early State

In current day South Korea pseudohistory pertaining to early Korea and northern East Asia has reached epidemic proportions. Its advocates argue the early state of Chosŏn to have been an expansive empire centered on mainland geographical Manchuria. Through rationalizing interpretations of the traditional Hwan’ung- Tan’gun myth, they project back the supposed antiquity and pristine nature of this charter empire to the archaeological Hongshan Culture of the Neolithic straddling Inner Mongolia and Liaoning provinces of China. Despite these blatant spatial and temporal exaggerations, all but specialists of early Korea typically remain hesitant to explicitly label this conceptualization as “pseudohistory.” This is because advocates of ancient empire cast themselves as rationalist scholars and claim to have evidential arguments drawn from multiple textual sources and archaeology. They further wield an emotive polemic defaming the domestic academic establishment as being composed of national traitors bent only on maintaining a “colonial view of history.” The canon of counterevidence relied on by empire advocates is the accumulated product of 20th century revisionist and pseudo historiography, but to willing believers and non-experts, it can easily appear convincing and overwhelming. Combined with a postcolonial nationalist framing and situated against the ongoing historiography dispute with China, their conceptualization of a grand antiquity has gained bipartisan political influence with concrete ramifications for professional scholarship. This paper seeks to introduce and debunk the core, seemingly evidential, canon of arguments put forward by purveyors of Korean pseudohistory and to expose their polemics, situating the phenomenon in a broader diagnostic context of global pseudohistory and archaeology.

scholarly journals Nonstationary Frequency Analysis of Censored Data: A Case Study of the Floods in the Yangtze River From 1470 to 2017

2020 ◽  
Vol 56 (8) ◽  
Author(s):  
Bin Xiong ◽  
Lihua Xiong ◽  
Shenglian Guo ◽  
Chong‐Yu Xu ◽  
Jun Xia ◽  
...  
Keyword(s):  
Censored Data ◽  
Frequency Analysis ◽  
Yangtze River ◽  
The Yangtze River ◽  
Nonstationary Frequency

Impact of bias correction techniques on an ensemble of seasonal discharge forecast for the Danube upstream of Vienna

2021 ◽  
Author(s):  
Ignacio Martin Santos ◽  
Mathew Herrnegger ◽  
Hubert Holzmann
Keyword(s):  
Bias Correction ◽  
Hydrological Model ◽  
Systematic Errors ◽  
Seasonal Forecasts ◽  
Scaling Factors ◽  
Quantile Mapping ◽  
Forecasting System ◽  
Mapping Techniques ◽  
Seasonal Discharge

<p>The skill of seasonal hydro-meteorological forecasts with a lead time of up to six months is currently limited, since they frequently exhibit random but also systematic errors. Bias correction algorithms can be applied and provide an effective approach in removing historical biases relative to observations. Systematic errors in hydrology model outputs can be consequence of different sources: i) errors in meteorological data used as input data, ii) errors in the hydrological model response to climate forcings, iii) unknown/unobservable internal states and iv) errors in the model parameterizations, also due to unresolved subgrid scale variability.</p><p>Normally, bias correction techniques are used to correct meteorological, e.g. precipitation data, provided by climate models. Only few studies are available applying these techniques to hydrological model outputs. Standard bias correction techniques used in literature can be classified into scaling-, and distributional-based methods. The former consists of using multiplicative or additive scaling factors to correct the modeled simulations, while the later methods are quantile mapping techniques that fit the distribution of the simulation to fit to the observations. In this study, the impact of different bias correction techniques on the seasonal discharge forecasts skill is assessed.</p><p>As a case study, a seasonal discharge forecasting system developed for the Danube basin upstream of Vienna, is used. The studied basin covers an area of around 100 000 km<sup>2</sup> and is subdivided in 65 subbasins, 55 of them gauged with a long historical record of observed discharge. The forecast system uses the calibrated hydrological model, COSERO, which is fed with an ensemble of seasonal temperature and precipitation forecasts. The output of the model provides an ensemble of seasonal discharge forecasts for each of the (gauged) subbasins. Seasonal meteorological forecasts for the past (hindcast), together with historical discharge observations, allow to assess the quality of the seasonal discharge forecasting system, also including the effects of different bias correction methods. The corrections applied to the discharge simulations allow to eliminate potential systematic errors between the modeled and observed values.</p><p>Our findings generally suggest that the quality of the seasonal forecasts improve when applying bias correction. Compared to simpler methods, which use additive or multiplicative scaling factors, quantile mapping techniques tend to be more appropriate in removing errors in the ensemble seasonal forecasts.</p>

scholarly journals A Bivariate Frequency Analysis of Extreme Wave Heights and Periods Using a Copula Function in South Korea

2018 ◽  
Vol 85 ◽  
pp. 566-570
Author(s):  
Yong-Tak Kim ◽  
Jong-Hyeon Park ◽  
Byoung-Han Choi ◽  
Dong Ho Kim ◽  
Hyun-Han Kwon
Keyword(s):  
South Korea ◽  
Frequency Analysis ◽  
Copula Function ◽  
Extreme Wave ◽  
Wave Heights ◽  
Bivariate Frequency Analysis

scholarly journals The world population and its expected future evolution

2010 ◽  
Vol 58 (3) ◽  
pp. 197-206 ◽  
Author(s):  
Marie Prášilová ◽  
Pavla Hošková
Keyword(s):  
20Th Century ◽  
World Population ◽  
African Countries ◽  
Future Evolution ◽  
Smoothing Methods ◽  
Statistical Procedures ◽  
Adaptive Procedures ◽  
The World ◽  
The Relationship ◽  
Population Numbers

Population numbers on Planet Earth grow steadily. The most rapid increase took place over the 20th century when the number of world population rose from 1.6 billion up to 6 billion. Demographic revolution affect the process of changes. The paper has paid attention to the relationship between natality and mortality in various parts of the world. It indicates the differing behaviour in the African countries where the demographic revolution has not been finished so far. Population numbers on the Planet Earth are being forecast for 2050 applying the exponential smoothing methods. The outcomes of statistical procedures are being compared with the UN prognoses and they do not indicate large differences in confidence intervals predictions. The adaptive procedures selected have been found suitable and satisfying for the population numbers forecasting purposes. Most rapidly the population of Africa numbers will grow until 2050, the number of Europeans will cover 7.55 % of the world population only.

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