scholarly journals Comparison of Local, Regional, and Scaling Models for Rainfall Intensity–Duration–Frequency Analysis

2020 ◽  
Vol 59 (9) ◽  
pp. 1519-1536
Author(s):  
Giuseppe Mascaro
Keyword(s):  
Monte Carlo ◽  
High Resolution ◽  
Annual Rainfall ◽  
Return Periods ◽  
Rain Gauges ◽  
Scaling Models ◽  
Simple Scaling ◽  
Daily Scale ◽  
Intensity Duration Frequency ◽  
Rainfall Statistics

AbstractIntensity–duration–frequency (IDF) analyses of rainfall extremes provide critical information to mitigate, manage, and adapt to urban flooding. The accuracy and uncertainty of IDF analyses depend on the availability of historical rainfall records, which are more accessible at daily resolution and, quite often, are very sparse in developing countries. In this work, we quantify performances of different IDF models as a function of the number of available high-resolution (Nτ) and daily (N24h) rain gauges. For this aim, we apply a cross-validation framework that is based on Monte Carlo bootstrapping experiments on records of 223 high-resolution gauges in central Arizona. We test five IDF models based on (two) local, (one) regional, and (two) scaling frequency analyses of annual rainfall maxima from 30-min to 24-h durations with the generalized extreme value (GEV) distribution. All models exhibit similar performances in simulating observed quantiles associated with return periods up to 30 years. When Nτ > 10, local and regional models have the best accuracy; bias correcting the GEV shape parameter for record length is recommended to estimate quantiles for large return periods. The uncertainty of all models, evaluated via Monte Carlo experiments, is very large when Nτ ≤ 5; however, if N24h ≥ 10 additional daily gauges are available, the uncertainty is greatly reduced and accuracy is increased by applying simple scaling models, which infer estimates on subdaily rainfall statistics from information at daily scale. For all models, performances depend on the ability to capture the elevation control on their parameters. Although our work is site specific, its results provide insights to conduct future IDF analyses, especially in regions with sparse data.

scholarly journals Effects of record length and resolution on the derived distribution of annual precipitation

2015 ◽  
Vol 12 (12) ◽  
pp. 12987-13018
Author(s):  
C. I. Meier ◽  
J. S. Moraga ◽  
G. Pranzini ◽  
P. Molnar
Keyword(s):  
High Resolution ◽  
Interannual Variability ◽  
Probability Model ◽  
Annual Precipitation ◽  
Annual Rainfall ◽  
Precipitation Data ◽  
Return Periods ◽  
Record Length ◽  
High Return ◽  
Log Normal

Abstract. Traditional frequency analysis of annual precipitation requires the fitting of a probability model to yearly precipitation totals. There are three potential problems with this approach: a long record (at least 25 ~ 30 years) is required in order to fit the model, years with missing data cannot be used, and the data need to be homogeneous. To overcome these limitations, we test an alternative methodology proposed by Eagleson (1978), based on the derived distribution approach (DDA). This allows for better estimation of the probability density function (pdf) of annual rainfall without requiring long records, provided that high-resolution precipitation data are available to derive external storm properties. The DDA combines marginal pdfs for storm depth and inter-arrival time to arrive at an analytical formulation of the distribution of annual precipitation under the assumption of independence between events. We tested the DDA at two temperate locations in different climates (Concepción, Chile, and Lugano, Switzerland), quantifying the effects of record length. Our results show that, as compared to the fitting of a normal or log-normal distribution, the DDA significantly reduces the uncertainty in annual precipitation estimates (especially interannual variability) when only short records are available. The DDA also reduces the bias in annual precipitation quantiles with high return periods. We also show that using precipitation data aggregated every 24 h, as commonly available at most weather stations, introduces a noticeable bias in the DDA. Our results point to the tangible benefits of installing high-resolution (hourly or less) precipitation gauges at previously ungauged locations. We show that the DDA, in combination with high resolution gauging, provides more accurate and less uncertain estimates of long-term precipitation statistics such as interannual variability and quantiles of annual precipitation with high return periods even for records as short as 5 years.

Tipping bucket mechanical errors and their influence on rainfall statistics and extremes

2002 ◽  
Vol 45 (2) ◽  
pp. 1-9 ◽  
Author(s):  
P. La Barbera ◽  
L.G. Lanza ◽  
L. Stagi
Keyword(s):  
Sample Size ◽  
Engineering Design ◽  
Laboratory Tests ◽  
Return Periods ◽  
Climate Trends ◽  
Data Set ◽  
Rain Gauges ◽  
Simple Index ◽  
Rainfall Extremes ◽  
Rainfall Statistics

Based on the error figures obtained after laboratory tests over a wide set of operational rain gauges from the network of the Liguria region, the bias introduced by systematic mechanical errors of tipping bucket rain gauges in the estimation of return periods and other statistics of rainfall extremes is quantified. An equivalent sample size is defined as a simple index that can be easily employed by practitioner engineers to measure the influence of systematic mechanical errors on common hydrological practice and the derived hydraulic engineering design. A few consequences of the presented results are discussed, with reference to data set reconstruction issues and the risk of introducing artificial climate trends in the observed rain records.

scholarly journals Exploring the robustness of Keplerian signals to the removal of active and telluric features

2020 ◽  
Vol 500 (1) ◽  
pp. 548-557
Author(s):  
M Lisogorskyi ◽  
H R A Jones ◽  
F Feng ◽  
R P Butler ◽  
S Vogt
Keyword(s):  
Monte Carlo ◽  
High Resolution ◽  
Monte Carlo Simulations ◽  
Large Amplitude ◽  
Absorption Cell ◽  
Stellar Rotation ◽  
Long Period ◽  
Active Line ◽  
Low Amplitude ◽  
Rotation Signal

ABSTRACT We examine the influence of activity- and telluric-induced radial velocity (RV) signals on high-resolution spectra taken with an iodine absorption cell. We exclude 2-$\mathring{\rm A}$ spectral chunks containing active and telluric lines based on the well-characterized K1V star α Centauri B and illustrate the method on Epsilon Eridani – an active K2V star with a long-period, low-amplitude planetary signal. After removal of the activity- and telluric-sensitive parts of the spectrum from the RV calculation, the significance of the planetary signal is increased and the stellar rotation signal disappears. In order to assess the robustness of the procedure, we perform Monte Carlo simulations based on removing random chunks of the spectrum. Simulations confirm that the removal of lines impacted by activity and tellurics provides a method for checking the robustness of a given Keplerian signal. We also test the approach on HD 40979, which is an active F8V star with a large-amplitude planetary signal. Our Monte Carlo simulations reveal that the significance of the Keplerian signal in the F star is much more sensitive to wavelength. Unlike the K star, the removal of active lines from the F star greatly reduces the RV precision. In this case, our removal of a K star active line from an F star does not a provide a simple useful diagnostic because it has far less RV information and heavily relies on the strong active lines.

scholarly journals 92 Years of the Ising Model: A High Resolution Monte Carlo Study

2018 ◽  
Vol 1012 ◽  
pp. 012002 ◽  
Author(s):  
Jiahao Xu ◽  
Alan M. Ferrenberg ◽  
David P. Landau
Keyword(s):  
Monte Carlo ◽  
Ising Model ◽  
High Resolution ◽  
Monte Carlo Study

scholarly journals Quantification of southwest China rainfall during the 8.2 ka BP event with response to North Atlantic cooling

2016 ◽  
Vol 12 (7) ◽  
pp. 1583-1590 ◽  
Author(s):  
Yuhui Liu ◽  
Chaoyong Hu
Keyword(s):  
High Resolution ◽  
Southwest China ◽  
East Asian Monsoon ◽  
Moving Average ◽  
Ice Core ◽  
Scale Model ◽  
Annual Rainfall ◽  
Transport Pathway ◽  
Mean Annual Rainfall ◽  
Monsoon Area

Abstract. The 8.2 ka BP event could provide important information for predicting abrupt climate change in the future. Although published records show that the East Asian monsoon area responded to the 8.2 ka BP event, there is no high-resolution quantitative reconstructed climate record in this area. In this study, a reconstructed 10-year moving average annual rainfall record in southwest China during the 8.2 ka BP event is presented by comparing two high-resolution stalagmite δ18O records from Dongge cave and Heshang cave. This decade-scale rainfall reconstruction is based on a central-scale model and is confirmed by inter-annual monitoring records, which show a significant positive correlation between the regional mean annual rainfall and the drip water annual average δ18O difference from two caves along the same monsoon moisture transport pathway from May 2011 to April 2014. Similar trends between the reconstructed rainfall and the stalagmite Mg ∕ Ca record, another proxy of rainfall, during the 8.2 ka BP period further increase the confidence of the quantification of the rainfall record. The reconstructed record shows that the mean annual rainfall in southwest China during the central 8.2 ka BP event is less than that of present (1950–1990) by  ∼  200 mm and decreased by  ∼  350 mm in  ∼  70 years experiencing an extreme drying period lasting for  ∼  50 years. Comparison of the reconstructed rainfall record in southwest China with Greenland ice core δ18O and δ15N records suggests that the reduced rainfall in southwest China during the 8.2 ka BP period was coupled with Greenland cooling with a possible response rate of 110 ± 30 mm °C−1.

scholarly journals Impacts of Spatial Heterogeneity and Temporal Non-Stationarity on Intensity-Duration-Frequency Estimates—A Case Study in a Mountainous California-Nevada Watershed

Water ◽  
2019 ◽  
Vol 11 (6) ◽  
pp. 1296 ◽  
Author(s):  
Huiying Ren ◽  
Z. Jason Hou ◽  
Mark Wigmosta ◽  
Ying Liu ◽  
L. Ruby Leung
Keyword(s):  
High Resolution ◽  
Spatial Heterogeneity ◽  
Time Windows ◽  
Exceedance Probability ◽  
Extreme Precipitation Events ◽  
Climate Simulations ◽  
Engineering Standards ◽  
Intensity Duration Frequency ◽  
Using Data

Changes in extreme precipitation events may require revisions of civil engineering standards to prevent water infrastructures from performing below the designated guidelines. Climate change may invalidate the intensity-duration-frequency (IDF) computation that is based on the assumption of data stationarity. Efforts in evaluating non-stationarity in the annual maxima series are inadequate, mostly due to the lack of long data records and convenient methods for detecting trends in the higher moments. In this study, using downscaled high resolution climate simulations of the historical and future periods under different carbon emission scenarios, we tested two solutions to obtain reliable IDFs under non-stationarity: (1) identify quasi-stationary time windows from the time series of interest to compute the IDF curves using data for the corresponding time windows; (2) introduce a parameter representing the trend in the means of the extreme value distributions. Focusing on a mountainous site, the Walker Watershed, the spatial heterogeneity and variability of IDFs or extremes are evaluated, particularly in terms of the terrain and elevation impacts. We compared observations-based IDFs that use the stationarity assumption with the two approaches that consider non-stationarity. The IDFs directly estimated based on the traditional stationarity assumption may underestimate the 100-year 24-h events by 10% to 60% towards the end of the century at most grids, resulting in significant under-designing of the engineering infrastructure at the study site. Strong spatial heterogeneity and variability in the IDF estimates suggest a preference for using high resolution simulation data for the reliable estimation of exceedance probability over data from sparsely distributed weather stations. Discrepancies among the three IDFs analyses due to non-stationarity are comparable to the spatial variability of the IDFs, underscoring a need to use an ensemble of non-stationary approaches to achieve unbiased and comprehensive IDF estimates.

scholarly journals Application of Enhanced Sampling Monte Carlo Methods for High-Resolution Protein-Protein Docking in Rosetta

PLoS ONE ◽  
2015 ◽  
Vol 10 (6) ◽  
pp. e0125941 ◽  
Author(s):  
Zhe Zhang ◽  
Christina E. M. Schindler ◽  
Oliver F. Lange ◽  
Martin Zacharias
Keyword(s):  
Monte Carlo ◽  
High Resolution ◽  
Monte Carlo Methods ◽  
Protein Docking ◽  
Enhanced Sampling
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