Numerical reconstruction of the intense precipitation and moisture transport fields for six tropical cyclones affecting the eastern United States

Mure-Ravaud, Mathieu; Ishida, Kei; Kavvas, M. L.; Yegorova, Elena; Kanney, Joseph

doi:10.1016/j.scitotenv.2019.02.185

Cited by 6 publications

(6 citation statements)

References 32 publications

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“…Sauvage et al (2020) investigated the air‐sea exchange mechanisms during a heavy precipitation in the Mediterranean, and found that the forecast of the heaviest precipitation could be modified when the realistic sea state was taken into account. Based on the Weather Research and Forecasting (WRF) model, Mure‐Ravaud, Ishida, et al (2019) reconstructed extreme precipitation and moisture transportation for six tropical cyclones affecting the eastern United States using the WRF numerical model, and found that horizontal moisture convergence played a key role in the generation of extreme precipitation in those tropical cyclones. However, the driving factors of the extreme rainfalls differ from one place to the other and can hardly be directly related to the outputs of GCMs.…”

Section: Urban Short‐duration Extreme Precipitationmentioning

confidence: 99%

“…Under changing environment, the physically‐based diagnostic methods can provide feasible schemes for identifying the physical mechanisms associated with extreme precipitation. In fact, there are a large body of scientific literature providing analysis and simulation of extreme precipitation to better comprehend the underlying key processes controlling extreme precipitation at regional scale (Couto, Ducrocq, Salgado, & Costa, 2016; Ducrocq et al, 2016; Mure‐Ravaud, Ishida, Kavvas, Yegorova, & Kanney, 2019; Mure‐Ravaud, Kavvas, & Dib, 2019; Sauvage, Brossier, Bouin, & Ducrocq, 2020; Yang, Smith, Yang, Baeck, & Ni, 2019; Zhang et al, 2018). Among them, Ducrocq et al (2016) highlighted the advances in process understanding of heavy precipitation in the Mediterranean in terms of initiation of deep convection, mesoscale convective systems dynamics and microphysics, and origin and transportation of water vapor.…”

Section: Urban Short‐duration Extreme Precipitationmentioning

confidence: 99%

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Updating intensity–duration–frequency curves for urban infrastructure design under a changing environment

et al. 2021

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The intensity and frequency of extreme precipitation have increased in many regions in the past century due to climate change. Many studies have revealed that short‐duration extreme precipitations are likely to become more and more severe in many areas, thus raising a question on whether our urban infrastructures have been designed adequately to cope with these changes. Currently, Intensity–duration–frequency (IDF) curves, which summarize the relationships between the intensity and frequency of extreme precipitation for different durations, are recommended as a criterion for urban infrastructure design and stormwater management. However, climate change is thought to have invalidated the stationary assumption in deriving IDF curves, that is, current IDF curves could misevaluate future extreme precipitation in many cases. Therefore, it is necessary to update the current IDF curves by considering possible changes of extreme precipitation. In this review, we first summarize observed changes in urban short‐duration extreme precipitation and explore the physical mechanisms associated with changes. Then, we introduce two major approaches for updating IDF curves, namely the covariate‐based nonstationary IDF curves and climate‐model‐based IDF curves. Advances in these two updating approaches for IDF curves are the focus of this review. These include the investigation of physically‐based covariates with nonstationary modeling of extreme precipitation; nonstationary precipitation design strategies; and the statistical downscaling and dynamic downscaling methods for projecting future short‐duration precipitation. Finally, we summarize some future research challenges and opportunities on providing reliable projections of future short‐duration extreme precipitation and better characterize the probabilistic behavior of short‐duration extreme precipitation for IDF design. This article is categorized under: Engineering Water > Engineering Water

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Section: Urban Short‐duration Extreme Precipitationmentioning

confidence: 99%

Section: Urban Short‐duration Extreme Precipitationmentioning

confidence: 99%

Updating intensity–duration–frequency curves for urban infrastructure design under a changing environment

et al. 2021

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“…Parameterization is the method of replacing process that are too small-scale or complex to be physically represented in the model by simplified process. WRF commonly parameterizes microphysical processes, cumulus physics, land surface processes, planetary boundary layer (PBL) processes, surface layer processes, and radiation physics [7]. The model performance is highly dependent on the choice of parameterization schemes.…”

Section: Wrf Model Configurationmentioning

confidence: 99%

“…Until now, the RCMs models have been widely used in the diverse community for regional process and sensitivity studies. Among the various NWP models, WRF, as one of the most popular mesoscale numerical weather predictions models, has been widely used to forecast and study TCs due to a flexible and computationally efficient platform for operational forecasting [6,7]. Nevertheless, TC's intense rainfall is time-dependent and spatially complex, therefore, the accuracy of TC precipitation prediction remains a challenge [4].…”

Section: Introductionmentioning

confidence: 99%

Data Assimilation of High-Resolution Satellite Rainfall Product Improves Rainfall Simulation Associated with Landfalling Tropical Cyclones in the Yangtze River Delta

Wang

Yang

et al. 2020

Remote Sensing

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Floods caused by heavy rainfall events associated with landfalling tropical cyclones (TCs) represent a major risk for the Yangtze River Delta (YRD) region of China. Accurate extreme precipitation forecasting, at long lead times, is crucial for the improvement of flood prevention and warning. However, accurate prediction of timing, location, and intensity of the heavy rainfall events is a major challenge for the Numerical Weather Prediction (NWP). In this study, high-resolution satellite precipitation products like Global Precipitation Measurement (GPM) are evaluated at the hourly timescale, and the optimal Integrated Multi-satellite Retrievals for GPM (IMERG) precipitation product is selected and applied to directly assimilate into the Weather Research and Forecasting (WRF) model via the four-dimensional variational (4D-Var) method. The TC Jondari and Rumbia events of August 2018 are evaluated to analyze the performance of the WRF model with the 4D-Var method assimilated IMERG precipitation product (DA-IMERG) and the conventional observation (DA-CONV) for real-time heavy rainfall forecasting. The results indicate that (1) IMERG precipitation products were larger and wetter than the observed precipitation values over YRD. By comparison, the performance of “late” run precipitation product (IMERG-L) was the closest to the observation data with lower deviation and higher detection capability; (2) DA-IMERG experiment substantially affected the magnitude of the WRF model primary variables, which changed the precipitation pattern of the TC heavy rain. (3) DA-IMERG experiment further improved the forecast of heavy rainbands and relatively reduced erroneous detection rate than CTL and DA-CONV experiments at the grid scale. Meanwhile, the DA-IMERG experiment has a better fractions skill score (FSS) value (especially in the threshold of 10 mm/h) than DA-CONV for TC Jondari and Rumbia at the spatial scale, while it shows a lower performance than CTL and DA-CONV experiments when the threshold is lower than the 5 mm/h for the TC Rumbia.

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“…A physically based modeling methodology has been introduced as part of an effort to provide reliable investigation and estimation of PMP and PMF values (Chen et al, 2016;Ishida et al, 2014Ishida et al, , 2015Ishida et al, 2018;Mure-Ravaud et al, 2019;Ohara et al, 2011;Toride et al, 2019;Trinh et al, 2021). Ishida et al (2014) introduced a numerical modeling approach to objectively estimate the maximum precipitation during a storm event by altering atmospheric boundary conditions and maximizing moisture conditions without any statistical assumptions.…”

mentioning

confidence: 99%

A numerical coupled atmospheric–hydrologic modeling system for probable maximum flood estimation with application to California's southern Sierra Nevada foothills watersheds

Trinh

Díaz

Iseri

et al. 2022

J Flood Risk Management

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Estimation of probable maximum flood (PMF) is a crucial process in water resources management and in the design of large hydraulic structures. However, there are uncertainties in the estimation of hydrologic conditions that contribute to extreme floods. In particular, this is the case in snow‐dominated regions, as surface air temperature and wind speed are understood to have a substantial effect on the magnitude of a flood during a storm event. Motivated by the development of a new approach to investigate and estimate reliable PMF values and in an attempt to resolve the uncertainty issues, this study introduces a physically based modeling approach. For the case study, seven watersheds located in the Sierra‐Nevada mountain range of California, including Cosumnes, Mokelumne, Stanislaus, Tuolumne, Merced, Upper San Joaquin, and Upper Kings were selected. The hydroclimate model was first implemented over the physical boundaries of the study region, and then utilized to simulate possible maximum flood conditions with input from 10 extreme precipitation scenarios. The study results provide evidence of a nonlinear atmospheric–hydrologic system; the extreme 72‐h basin‐averaged precipitation depth was found not to be linearly proportional to 72‐h flow volume equivalent depth. It can also be concluded that a large precipitation depth may not be the sole reason for a large flood event. Temperature and other atmospheric variables also contribute significantly to the production of snowfall and liquid water available for runoff, and to the resulting hydrologic response, such as the flood peak discharge and volume.

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Numerical reconstruction of the intense precipitation and moisture transport fields for six tropical cyclones affecting the eastern United States

Cited by 6 publications

References 32 publications

Updating intensity–duration–frequency curves for urban infrastructure design under a changing environment

Updating intensity–duration–frequency curves for urban infrastructure design under a changing environment

Data Assimilation of High-Resolution Satellite Rainfall Product Improves Rainfall Simulation Associated with Landfalling Tropical Cyclones in the Yangtze River Delta

A numerical coupled atmospheric–hydrologic modeling system for probable maximum flood estimation with application to California's southern Sierra Nevada foothills watersheds

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