Fast Weather Simulation for Inverse Procedural Design of 3D Urban Models

Ignacio Garcia-Dorado1,2    Daniel G. Aliaga1    Saiprasanth Bhalachandran1    Paul Schmid1    Dev Niyogi1

1 Purdue University   2 Google Research

ACM Transactions on Graphics 2017

Teaser image

Abstract

We present the first realistic, physically-based, fully coupled, real-time weather design tool for use in urban procedural modeling. We merge designing of a 3D urban model with a controlled long-lasting spatiotemporal interactive simulation of weather. Starting from the fundamental dynamical equations similar to those used in state-of-the-art weather models, we present a novel simplified urban weather model for interactive graphics. Control of physically-based weather phenomena is accomplished via an inverse modeling methodology. In our results, we present several scenarios of forward design, inverse design with high-level and detailed-level weather control and optimization, as well as comparisons of our method against well-known weather simulation results and systems.

PDF PDF (Supplemental) Video Code

Code

We provide the C++ code of our weather simulation. This code contains all the elements necassary to simulate weather: 1. loads an initial weather sounding, 2. randomly generates a terrain configuration, 3. runs our 3D weather simulation for any given number of simulation steps. For more details, please refer to the github and code documentation.

Images & Video

Citation

Ignacio Garcia-Dorado, Daniel Aliaga, Saiprasanth Bhalachandran, Paul Schmid, Dev Niyogi. 2017. Fast Weather Simulation for Inverse Procedural Design of 3D Urban Models. ACM Trans. Graph., 19 pages.

@article{GDA*2017,
	author = {Garcia-Dorado, Ignacio and Aliaga, Daniel and Bhalachandran, Saiprasanth, and Schmid, Paul, 
                  and Niyogi, Dev},
	title = {Fast Weather Simulation for Inverse Procedural Design of 3D Urban Models},
	journal = {ACM Trans. Graph.},
	year = {2017},
	publisher = {ACM},
	address = {New York, NY, USA},
	keywords = {design, dynamical systems, inverse modeling, weather forecasting, urban climate design}
}