Stochastic Tropical Cyclone Precipitation Field Generation

11/19/2020
by   William Kleiber, et al.
0

Tropical cyclones are important drivers of coastal flooding which have severe negative public safety and economic consequences. Due to the rare occurrence of such events, high spatial and temporal resolution historical storm precipitation data are limited in availability. This paper introduces a statistical tropical cyclone space-time precipitation generator given limited information from storm track datasets. Given a handful of predictor variables that are common in either historical or simulated storm track ensembles such as pressure deficit at the storm's center, radius of maximal winds, storm center and direction, and distance to coast, the proposed stochastic model generates space-time fields of quantitative precipitation over the study domain. Statistically novel aspects include that the model is developed in Lagrangian coordinates with respect to the dynamic storm center that uses ideas from low-rank representations along with circular process models. The model is trained on a set of tropical cyclone data from an advanced weather forecasting model over the Gulf of Mexico and southern United States, and is validated by cross-validation. Results show the model appropriately captures spatial asymmetry of cyclone precipitation patterns, total precipitation as well as the local distribution of precipitation at a set of case study locations along the coast.

READ FULL TEXT
POST COMMENT

Comments

There are no comments yet.

Authors

page 15

10/01/2019

Point Pattern Processes and Models

In recent years there has been a substantial increase in the availabilit...
06/25/2019

New approach for stochastic downscaling and bias correction of daily mean temperatures to a high-resolution grid

In applications of climate information, coarse-resolution climate projec...
06/15/2021

Learning Incident Prediction Models Over Large Geographical Areas for Emergency Response Systems

Principled decision making in emergency response management necessitates...
01/13/2022

Space-time extremes of severe US thunderstorm environments

Severe thunderstorms cause substantial economic and human losses in the ...
12/04/2019

Simulating space-time random fields with nonseparable Gneiting-type covariance functions

Two algorithms are proposed to simulate space-time Gaussian random field...
05/01/2018

A Discrete View of the Indian Monsoon to Identify Spatial Patterns of Rainfall

We propose a representation of the Indian summer monsoon rainfall in ter...
12/27/2020

Prediction Model Evaluation for Space-Time Data

Evaluation metrics for prediction error, model selection and model avera...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.