Engineering topics

Xi, Dazhi

Publications and source records attributed to Xi, Dazhi.

5 records

DOE OSTI2023

Assessing North Atlantic Tropical Cyclone Rainfall Hazard Using Engineered-Synthetic Storms and a Physics-Based Tropical Cyclone Rainfall Model

In this study, we design a statistical method to couple observations with a physics-based tropical cyclone (TC) rainfall model (TCR) and engineered-synthetic storms for assessing TC rainfall hazard. We first propose a bias-correction method to minimize the errors induced by TCR via matching the probability distribution of TCR-simulated historical TC rainfall with gauge observations. Then we assign occurrence probabilities to engineered-synthetic storms to reflect local climatology, through a resampling method that matches the probability distribution of a newly proposed storm parameter named rainfall potential (POT) in the synthetic dataset with that in the observation. POT is constructed to include several important storm parameters for TC rainfall such as TC intensity, duration, and distance and environmental humidity near landfall, and it is shown to be correlated with TCR-simulated rainfall. The proposed method has a satisfactory performance in reproducing the rainfall hazard curve in various locations in the continental United States; it is an improvement over the traditional joint probability method (JPM) for TC rainfall hazard assessment.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Increasing sequential tropical cyclone hazards along the US East and Gulf coasts

Two tropical cyclones (TCs) that make landfall close together can induce sequential hazards to coastal areas. Here we investigate the change in sequential TC hazards in the historical and future projected climates. We find that the chance of sequential TC hazards has been increasing over the past several decades at many US locations. Under the high (moderate) emission scenario, the chance of hazards from two TCs impacting the same location within 15 days may substantially increase, with the return period decreasing over the century from 10–92 years to ~1–2 (1–3) years along the US East and Gulf coasts, due to sea-level rise and storm climatology change. Climate change can also cause unprecedented compounding of extreme hazards at the regional level. A Katrina-like TC and a Harvey-like TC impacting the United States within 15 days of each other, which is non-existent in the control simulation for over 1,000 years, is projected to have an annual occurrence probability of more than 1% by the end of the century under the high emission scenario.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Analyzing Relationships between Tropical Cyclone Intensity and Rain Rate over the Ocean Using Numerical Simulations

In this study, the relationship between tropical cyclone (TC) intensity and rain rate over the ocean is investigated using a full-physics numerical model (WRF) and a physics-based TC rainfall model (TCR). TC intensity is found to be nearly linearly correlated with the average rain rate in the inner core [~0.97 (mm h –1 m –2 )/(m s –1 )], while the correlation is weak at outer radii. This difference is induced because TC intensity is significantly correlated with both the vertical velocity and specific humidity in the inner core but is not significantly correlated with the vertical velocity in the outer radii. Further investigation shows that the intensity–rain-rate relationship at the outer radii is influenced by the TC evolution stage. The rain rate for the outer radii is positively correlated with TC intensity for nondecaying TCs, while this correlation is reduced for decaying TCs due to systematic downdrafts in the outer radii. In the context of climate change, the sensitivity of the TC rain rate to sea surface temperature (SST) is found to be +9% per 1 K increase of SST, roughly the product of the sensitivity of TC intensity to SST (+3%) and the Clausius-Clapeyron scaling (+7%). Coupled with synthetic storms, evolution of the TC rain rate over the twenty-first century under the SSP5-8.5 scenario is projected by the TCR (calibrated with the WRF simulations). The annual increase rates of averaged TC rain rate are 0.17% and 0.20% for the inner core and outer radii, respectively, larger than the annual increase rate of TC intensity (0.046%) but comparable to that of cube of intensity (0.18%).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Investigating the Physical Drivers for the Increasing Tropical Cyclone Rainfall Hazard in the United States

In this study, we investigate both the changes of tropical cyclone (TC) rainfall hazard in the United States under climate change and the relative importance of the factors that cause the changes. We find that under the SSP5 8.5 scenario, the 100-year TC rainfall level can increase by up to 320% along the U.S. coastline by the end of this century. The influence of TC rainfall-producing ability increase is more significant than the influence of TC frequency increase on the increase of the 100-year TC rainfall level (up to 180% vs. 60% increase). Among the different physical drivers for the increase in storm rainfall-producing ability, the increase of TC intensity is the leading factor, followed by changes in TC duration and atmospheric temperature. The projected increase of TC rainfall hazard is robust against the uncertainty in the TC frequency projection.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Understanding Uncertainties in Tropical Cyclone Rainfall Hazard Modeling Using Synthetic Storms

Tropical cyclone (TC) rainfall hazard assessment is subject to the bias in TC climatology estimation from climate simulations or synthetic downscaling. In this study, we investigate the uncertainty in TC rainfall hazard assessment induced by this bias using both rain gauge and radar observations and synthetic-storm-model-coupled TC rainfall simulations. We identify the storm’s maximum intensity, impact duration, and minimal distance to the site to be the three most important storm parameters for TC rainfall hazard, and the relationship between the important storm parameters and TC rainfall can be well captured by a physics-based TC rainfall model. The uncertainty in the synthetic rainfall hazard induced by the bias in TC climatology can be largely explained by the bias in the important storm parameters simulated by the synthetic storm model. Correcting the distribution of the most biased parameter may significantly improve rainfall hazard estimation. Bias correction based on the joint distribution of the important parameters may render more accurate rainfall hazard estimations; however, the general technical difficulties in resampling from high-dimensional joint probability distributions prevent more accurate estimations in some cases. The results of the study also support future investigation of the impact of climate change on TC rainfall hazards through the lens of future changes in the identified important storm parameters.

54 ENVIRONMENTAL SCIENCES↗