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

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, and comparisons of our method against well-known weather simulation results and systems.

[1]  Louis J. Wicker,et al.  Numerical solutions of a non‐linear density current: A benchmark solution and comparisons , 1993 .

[2]  Jun Wang,et al.  Compute Unified Device Architecture (CUDA)-based parallelization of WRF Kessler cloud microphysics scheme , 2011, Remote Sensing.

[3]  Kevin W. Manning,et al.  The Integrated WRF/Urban Modeling System: Development, Evaluation, and Applications to Urban Environmental Problems , 2010 .

[4]  Jun Wang,et al.  Compute unified device architecture (CUDA)-based parallelization of WRF Kessler cloud microphysics scheme , 2013, Comput. Geosci..

[5]  Terry Lucke,et al.  The pollution removal and stormwater reduction performance of street-side bioretention basins after ten years in operation. , 2015, The Science of the total environment.

[6]  Daniel G. Aliaga,et al.  A Survey of Urban Reconstruction , 2013, Comput. Graph. Forum.

[7]  Louis J. Wicker,et al.  Time-Splitting Methods for Elastic Models Using Forward Time Schemes , 2002 .

[8]  Xiangao Xia,et al.  Impacts of urban expansion and future green planting on summer precipitation in the Beijing metropolitan area , 2009 .

[9]  R. Stull,et al.  Meteorology for Scientists and Engineers , 1999 .

[10]  Anselmo Lastra,et al.  Real‐Time Cloud Rendering , 2001, Comput. Graph. Forum.

[11]  David D. Parrish,et al.  NORTH AMERICAN REGIONAL REANALYSIS , 2006 .

[12]  Radomír Mech,et al.  Metropolis procedural modeling , 2011, TOGS.

[13]  D. Niyogi,et al.  Impact of city size on precipitation‐modifying potential , 2013 .

[14]  Lily Parshall,et al.  Mitigation of the heat island effect in urban New Jersey , 2005 .

[15]  Christopher Wojtan,et al.  A stream function solver for liquid simulations , 2015, ACM Trans. Graph..

[16]  O. Tetens,et al.  Uber einige meteorologische begriffe , 1930 .

[17]  F. Nebeker.  Calculating the weather : meteorology in the 20th century , 1997 .

[18]  R. J. Purser,et al.  A Semi-Implicit, Semi-Lagrangian Finite-Difference Scheme Using Hligh-Order Spatial Differencing on a Nonstaggered Grid , 1988 .

[19]  Akio Arakawa,et al.  Computational Design of the Basic Dynamical Processes of the UCLA General Circulation Model , 1977 .

[20]  R. Pielke.  Mesoscale Meteorological Modeling , 1984 .

[21]  J. Marshall,et al.  THE DISTRIBUTION OF RAINDROPS WITH SIZE , 1948 .

[22]  George Drettakis,et al.  Image-guided weathering: A new approach applied to flow phenomena , 2011, TOGS.

[23]  Shree K. Nayar,et al.  Photorealistic rendering of rain streaks , 2006, SIGGRAPH '06.

[24]  Yoshimitsu Ogura,et al.  A Comparison Between Axisymmetric and Slab-Symmetric Cumulus Cloud Models , 1973 .

[25]  N. Metropolis,et al.  Equation of State Calculations by Fast Computing Machines , 1953, Resonance.

[26]  Masanori Kakimoto,et al.  Real-time rendering of physically based optical effects in theory and practice , 2015, SIGGRAPH Courses.

[27]  Howard B. Bluestein,et al.  A Synoptic and Photographic Climatology of Low-Precipitation Severe Thunderstorms in the Southern Plains , 1983 .

[28]  M. Caramia,et al.  Multi-objective Management in Freight Logistics: Increasing Capacity, Service Level and Safety with Optimization Algorithms , 2008 .

[29]  J. Dudhia,et al.  Coupling an Advanced Land Surface–Hydrology Model with the Penn State–NCAR MM5 Modeling System. Part I: Model Implementation and Sensitivity , 2001 .

[30]  S. Arya.  Air Pollution Meteorology and Dispersion , 1998 .

[31]  J. Monteith,et al.  Boundary Layer Climates. , 1979 .

[32]  Nash'at Ahmad,et al.  Euler solutions using flux‐based wave decomposition , 2007 .

[33]  Westone,et al.  Home Page , 2004, 2022 2nd International Conference on Intelligent Cybernetics Technology & Applications (ICICyTA).

[34]  E. Lorenz.  Atmospheric Predictability as Revealed by Naturally Occurring Analogues , 1969 .

[35]  S. Arya,et al.  Urban modification of thunderstorms - An observational storm climatology and model case study for the Indianapolis urban region , 2011 .

[36]  David S. Ebert,et al.  Texturing and Modeling: A Procedural Approach , 1994 .

[37]  A. Monin,et al.  Basic laws of turbulent mixing in the surface layer of the atmosphere , 2009 .

[38]  W. Cotton,et al.  RAMS 2001: Current status and future directions , 2003 .

[39]  Roger A. Pielke,et al.  The impact of land cover change on storms in the Sydney Basin, Australia , 2006 .

[40]  David S. Ebert,et al.  Texturing & modeling : a procedural approach : 日本語版 , 2009 .

[41]  R. Stull.  An Introduction to Boundary Layer Meteorology , 1988 .

[42]  S. Planton,et al.  A Simple Parameterization of Land Surface Processes for Meteorological Models , 1989 .

[43]  Yoshinori Dobashi,et al.  A method for modeling clouds based on atmospheric fluid dynamics , 2001, Proceedings Ninth Pacific Conference on Computer Graphics and Applications. Pacific Graphics 2001.

[44]  M. Santamouris.  Cooling the cities – A review of reflective and green roof mitigation technologies to fight heat island and improve comfort in urban environments , 2014 .

[45]  Yoshinori Dobashi,et al.  A Modeling and Rendering Method for Snow by Using Metaballs , 1997, Comput. Graph. Forum.

[46]  Roger A. Pielke,et al.  Satellite-Based Model Parameterization of Diabatic Heating , 2007 .

[47]  W. K. Hastings,et al.  Monte Carlo Sampling Methods Using Markov Chains and Their Applications , 1970 .

[48]  J. Holton.  An introduction to dynamic meteorology , 2004 .

[49]  Joe Michael Kniss,et al.  A Model for Volume Lighting and Modeling , 2003, IEEE Trans. Vis. Comput. Graph..

[50]  Yoshinori Dobashi,et al.  Display of clouds taking into account multiple anisotropic scattering and sky light , 1996, SIGGRAPH.

[51]  Greg Humphreys,et al.  A spatial data structure for fast Poisson-disk sample generation , 2006, ACM Trans. Graph..

[52]  George J. Huffman,et al.  A stochastic model of cumulus clumping , 1980 .

[53]  Michael Wimmer,et al.  Instant architecture , 2003, ACM Trans. Graph..

[54]  T. Lucke,et al.  A review of benefits and challenges in growing street trees in paved urban environments , 2015 .

[55]  Hujun Bao,et al.  Visual simulation of weathering by γ-ton tracing , 2005, ACM Trans. Graph..

[56]  Kazufumi Kaneda,et al.  A simple, efficient method for realistic animation of clouds , 2000, SIGGRAPH.

[57]  James T. Kajiya,et al.  Ray tracing volume densities , 1984, SIGGRAPH.

[58]  Yong-Run Guo,et al.  The Weather Research and Forecasting Model's Community Variational/Ensemble Data Assimilation System: WRFDA , 2012 .

[59]  D. Durran.  Numerical methods for wave equations in geophysical fluid dynamics , 1999 .

[60]  Qinping Zhao,et al.  Modelling Cumulus Cloud Shape from a Single Image , 2014, Comput. Graph. Forum.

[61]  Daniel G. Aliaga,et al.  Designing large‐scale interactive traffic animations for urban modeling , 2014, Comput. Graph. Forum.

[62]  H. Seidel,et al.  A connection between partial symmetry and inverse procedural modeling , 2010, ACM Trans. Graph..

[63]  M. Doyle,et al.  What is a stream? , 2011, Environmental science & technology.

[64]  Daniel G. Aliaga,et al.  Modelling the Appearance and Behaviour of Urban Spaces , 2010, Comput. Graph. Forum.

[65]  D. Durran.  Improving the Anelastic Approximation , 1989 .

[66]  Daniel G. Aliaga,et al.  Inverse design of urban procedural models , 2012, ACM Trans. Graph..

[67]  Scott J. Goetz,et al.  Designing and implementing a regional urban modeling system using the SLEUTH cellular urban model , 2010, Comput. Environ. Urban Syst..

[68]  Nelson L. Max,et al.  Interactive multiple anisotropic scattering in clouds , 2008, I3D '08.

[69]  Stéphanie Perron,et al.  The connection. , 2012, Canadian family physician Medecin de famille canadien.

[70]  Manish Vachharajani,et al.  GPU acceleration of numerical weather prediction , 2008, 2008 IEEE International Symposium on Parallel and Distributed Processing.

[71]  James F. Blinn,et al.  Light reflection functions for simulation of clouds and dusty surfaces , 1982, SIGGRAPH.

[72]  Ming C. Lin,et al.  Interactive hybrid simulation of large-scale traffic , 2011, ACM Trans. Graph..

[73]  John Hart,et al.  ACM Transactions on Graphics , 2004, SIGGRAPH 2004.

[74]  E. Kessler.  On the distribution and continuity of water substance in atmospheric circulations , 1969 .

[75]  Jordan G. Powers,et al.  A Description of the Advanced Research WRF Version 2 , 2005 .

[76]  J. Steinhoff,et al.  Modification of the Euler equations for ‘‘vorticity confinement’’: Application to the computation of interacting vortex rings , 1994 .

[77]  Christopher D. Kulla,et al.  Production volume rendering: SIGGRAPH 2017 course , 2017, SIGGRAPH Courses.

[78]  Dinesh Manocha,et al.  Interactive Large-Scale Crowd Simulation , 2012 .

[79]  Miles Macklin,et al.  Position based fluids , 2013, ACM Trans. Graph..

[80]  Anselmo Lastra,et al.  Simulation of cloud dynamics on graphics hardware , 2003, HWWS '03.

[81]  Yoshinori Dobashi,et al.  Feedback control of cumuliform cloud formation based on computational fluid dynamics , 2008, ACM Trans. Graph..

[82]  Ronald Fedkiw,et al.  Visual simulation of smoke , 2001, SIGGRAPH.

[83]  Pascal Müller,et al.  Procedural modeling of cities , 2001, SIGGRAPH.