scholarly journals Scaling Characteristics of Storm-Centered ARF Using Radar Rainfall

10.29007/hmzf ◽  
2018 ◽  
Author(s):  
Eunji Kim ◽  
Boosik Kang
Keyword(s):  
Return Period ◽  
Reduction Factor ◽  
Exceedance Probability ◽  
Storm Events ◽  
Reference Area ◽  
Radar Rainfall ◽  
Areal Reduction Factor ◽  
Fixed Area ◽  
Spatio Temporal ◽  
Areal Rainfall

In the hydraulic design practices, it is necessary to apply areal reduction factor to convert the point rainfall into the areal rainfall in the reference area. The fixed-area ARF (ARFf), which is commonly used, can be considered unrealistic because it is estimated through independent frequency analysis of the point rainfall and the areal rainfall. In this study, storm-centred ARF (ARFs) was estimated using radar rainfall data to reflect the spatial distribution characteristics of storm events effectively. ARFs representing the duration and the return period was extracted by 95% non-exceedance probability of the Weibull distribution to derive envelope covering all values from various storm events. ARFs has a correlation with not only the reference area but also the duration and the return period. Their relationships are defined as the scaling factors. A new ARFs equation that reflects the spatio-temporal characteristics of actual rainfall is presented.

scholarly journals On the use of radar reflectivity for estimation of the areal reduction factor

2006 ◽  
Vol 6 (3) ◽  
pp. 377-386 ◽  
Author(s):  
F. Lombardo ◽  
F. Napolitano ◽  
F. Russo
Keyword(s):  
Reduction Factor ◽  
Radar Reflectivity ◽  
Medium Size ◽  
Small Scale ◽  
Natural Phenomena ◽  
Radar Rainfall ◽  
Areal Reduction Factor ◽  
Empirical Relations ◽  
Urban Catchments ◽  
Areal Rainfall

Abstract. In order to estimate the rainfall fields over an entire basin raingauge, pointwise measurements need to be interpolated and the small-scale variability of rainfall fields can lead to biases in the rain rate estimation over an entire basin, above all for small or medium size mountainous and urban catchments. For these reasons, several raingauges should be installed in different places in order to determine the spatial rainfall distribution during the evolution of the natural phenomena over the selected area. In technical applications, many empirical relations are used in order to deduce heavy areal rainfall, when just one raingauge is available. In this work, we studied the areal reduction factor (ARF) using radar reflectivity maps collected with the Polar 55C, a C-band Doppler dual polarized coherent weather radar with polarization agility and with a 0.9° beamwidth. The radar rainfall estimates, for an area of 1 km2, were integrated for heavy rainfall with an upscaling process, until we had rainfall estimate for an area of 900 km2. The results obtained for a significant amount of data by using this technique are compared with the most important relations of the areal reduction factor reported in the literature.

Intercomparison of selected fixed-area areal reduction factor methods

2016 ◽  
Vol 537 ◽  
pp. 419-430 ◽  
Author(s):  
Sandra Pavlovic ◽  
Sanja Perica ◽  
Michael St Laurent ◽  
Alfonso Mejía
Keyword(s):  
Reduction Factor ◽  
Areal Reduction Factor ◽  
Fixed Area

Evaluation of areal versus point rainfall with sparse data

1981 ◽  
Vol 8 (2) ◽  
pp. 173-178 ◽  
Author(s):  
Van-Thanh-Van Nguyen ◽  
Jean Rousselle ◽  
M. B. McPherson
Keyword(s):  
Fixed Point ◽  
Distribution Function ◽  
Exponential Distribution ◽  
Correction Factor ◽  
Return Period ◽  
Specific Area ◽  
Sparse Data ◽  
Exceedance Probability ◽  
Fixed Area

A theoretical methodology is proposed to establish a relationship between the rainfall at a fixed point and the associated mean rainfall over a geographically fixed area. The distribution relation for mean rainfall over a specific area was derived using an exponential distribution function for hourly point rainfall. Values of the areal correction factor were estimated at equal levels of exceedance probability for point and areal mean rainfalls. Contrary to previous indications for a moving point, it was found that the areal correction factor for a fixed point and fixed area was not always equal to or less than unity. Furthermore, the areal correction factor was found to vary with the return period.

From point to areal rainfall: linking the different approaches for the frequency characterisation of rainfalls in urban areas

2006 ◽  
Vol 54 (6-7) ◽  
pp. 33-40 ◽  
Author(s):  
M.H. Ramos ◽  
E. Leblois ◽  
J.-D. Creutin
Keyword(s):  
Frequency Analysis ◽  
Return Period ◽  
Urban Areas ◽  
Urban Water ◽  
Storm Events ◽  
Unified Approach ◽  
Rainfall Frequency ◽  
Rainfall Frequency Analysis ◽  
Areal Rainfall ◽  
The City

In urban water design and management, many hydrologic problems involve the frequency characterisation of rainfalls. Hydrologists are commonly asked to evaluate rainfall intensities for given recurrence frequencies or to indicate how rare an observed event is by estimating its return period. This study aims to improve the characterisation of rainfall hazard over a city by linking point to areal rainfall frequency analysis. We use a stochastic rainfall field generator based on the turning-bands method directly to assess areal rainfall distributions and to illustrate the link between different approaches. The simulating algorithm is applied to rainfall data from the city of Marseilles. The frequency analysis of simulated fields provides the elements to deal with the notions of return period and severity of observed storm events. The study concludes on the importance of a unified approach to assess rainfall better.

Areal reduction factor: The effect of the return period

2019 ◽  
Author(s):  
C. Mineo ◽  
E. Ridolfi ◽  
A. Neri ◽  
F. Russo
Keyword(s):  
Return Period ◽  
Reduction Factor ◽  
Areal Reduction Factor

scholarly journals Development and Assessment of High-Resolution Radar-Based Precipitation Intensity-Duration-Curve (IDF) Curves for the State of Texas

2021 ◽  
Vol 13 (15) ◽  
pp. 2890
Author(s):  
Dawit T. Ghebreyesus ◽  
Hatim O. Sharif
Keyword(s):  
High Resolution ◽  
Return Period ◽  
Extreme Values ◽  
Stage Iv ◽  
Radar Data ◽  
The State ◽  
Storm Events ◽  
High Resolution Radar ◽  
Idf Curves ◽  
Spatio Temporal

Conventionally, in situ rainfall data are used to develop Intensity Duration Frequency (IDF) curves, which are one of the most effective tools for modeling the probability of the occurrence of extreme storm events at different timescales. The rapid recent technological advancements in precipitation sensing, and the finer spatio-temporal resolution of data have made the application of remotely sensed precipitation products more dominant in the field of hydrology. Some recent studies have discussed the potential of remote sensing products for developing IDF curves. This study employs a 19-year NEXRAD Stage-IV high-resolution radar data (2002–2020) to develop IDF curves over the entire state of Texas at a fine spatial resolution. The Annual Maximum Series (AMS) were fitted to four widely used theoretical Extreme Value statistical distributions. Gumble distribution, a unique scenario of the Generalized Extreme Values (GEV) family, was found to be the best model for more than 70% of the state’s area for all storm durations. Validation of the developed IDFs against the operational Atlas 14 IDF values shows a ±27% difference in over 95% of the state for all storm durations. The median of the difference stays between −10% and +10% for all storm durations and for all return periods in the range of (2–100) years. The mean difference ranges from −5% for the 100-year return period to 8% for the 10-year return period for the 24-h storm. Generally, the western and northern regions of the state show an overestimation, while the southern and southcentral regions show an underestimation of the published values.

Commercial microwave links instead of rain gauges: fiction or reality?

2014 ◽  
Vol 71 (1) ◽  
pp. 31-37 ◽  
Author(s):  
Martin Fencl ◽  
Jörg Rieckermann ◽  
Petr Sýkora ◽  
David Stránský ◽  
Vojtěch Bareš
Keyword(s):  
Rainfall Variability ◽  
A Priori ◽  
Rain Gauges ◽  
Precipitation Estimates ◽  
Spatio Temporal ◽  
Areal Rainfall ◽  
Quantitative Precipitation Estimates ◽  
Commercial Microwave Links ◽  
Unique Dataset

Commercial microwave links (MWLs) were suggested about a decade ago as a new source for quantitative precipitation estimates (QPEs). Meanwhile, the theory is well understood and rainfall monitoring with MWLs is on its way to being a mature technology, with several well-documented case studies, which investigate QPEs from multiple MWLs on the mesoscale. However, the potential of MWLs to observe microscale rainfall variability, which is important for urban hydrology, has not been investigated yet. In this paper, we assess the potential of MWLs to capture the spatio-temporal rainfall dynamics over small catchments of a few square kilometres. Specifically, we investigate the influence of different MWL topologies on areal rainfall estimation, which is important for experimental design or to a priori check the feasibility of using MWLs. In a dedicated case study in Prague, Czech Republic, we collected a unique dataset of 14 MWL signals with a temporal resolution of a few seconds and compared the QPEs from the MWLs to reference rainfall from multiple rain gauges. Our results show that, although QPEs from most MWLs are probably positively biased, they capture spatio-temporal rainfall variability on the microscale very well. Thus, they have great potential to improve runoff predictions. This is especially beneficial for heavy rainfall, which is usually decisive for urban drainage design.

scholarly journals Space–Time Characteristics of Areal Reduction Factors and Rainfall Processes

2020 ◽  
Vol 21 (4) ◽  
pp. 671-689 ◽  
Author(s):  
Korbinian Breinl ◽  
Hannes Müller-Thomy ◽  
Günter Blöschl
Keyword(s):  
Return Period ◽  
Lightning Activity ◽  
Convective Activity ◽  
Convective Rainfall ◽  
The West ◽  
Rain Gauges ◽  
Fixed Area ◽  
Relationship Of ◽  
The Relationship ◽  
Reduction Factors

AbstractWe estimate areal reduction factors (ARFs; the ratio of catchment rainfall and point rainfall) varying in space and time using a fixed-area method for Austria and link them to the dominating rainfall processes in the region. We particularly focus on two subregions in the west and east of the country, where stratiform and convective rainfall processes dominate, respectively. ARFs are estimated using a rainfall dataset of 306 rain gauges with hourly resolution for five durations between 1 h and 1 day. Results indicate that the ARFs decay faster with area in regions of increased convective activity than in regions dominated by stratiform processes. Low ARF values occur where and when lightning activity (as a proxy for convective activity) is high, but some areas with reduced lightning activity exhibit also rather low ARFs as, in summer, convective rainfall can occur in any part of the country. ARFs tend to decrease with increasing return period, possibly because the contribution of convective rainfall is higher. The results of this study are consistent with similar studies in humid climates and provide new insights regarding the relationship of ARFs and dominating rainfall processes.

scholarly journals The derivation of areal reduction factor of storm rainfall from its scaling properties

2001 ◽  
Vol 37 (12) ◽  
pp. 3247-3252 ◽  
Author(s):  
Carlo De Michele ◽  
Nathabandu T. Kottegoda ◽  
Renzo Rosso
Keyword(s):  
Reduction Factor ◽  
Scaling Properties ◽  
Areal Reduction Factor ◽  
Storm Rainfall
Sign in / Sign up

Export Citation Format

Share Document