and mesoscale modeling of thermal convection, internal waves and

99 Pages·2015·3.26 MB·English

Budapest University of Technology and
Economics
Micro- and mesoscale modeling of
thermal convection, internal waves
and cloud formation in the
atmosphere
Author: Supervisor:
Norbert Rácz Dr. Gergely Kristóf
A Thesis Submitted in partial fullfillment for the Degree
of Doctor of Philosophy
in the
Faculty of Mechanical Engineering
Department of Fluid Mechanics
June 8, 2015
Nyilatkozat
Alulírott Rácz Norbert kijelentem, hogy ezt a doktori értekezést magam
készítettem és abban csak a megadott forrásokat használtam fel. Minden olyan
részt, amelyet szó szerint, vagy azonos tartalomban, de átfogalmazva más
forrásból átvettem, egyértelműen, a forrás megadásával megjelöltem.
Aláírás:
Dátum:
i
Abstract
The present thesis is about the simulation of micro- and mesoscale flows using gen-
eral purpose pressure based computational fluid dynamical (CFD) solvers. CFD
solvers are already widely used in urban studies such as in the modeling of the ven-
tilation of urban areas, pollution transport studies, wind farm design or calculation
of wind loads on different human made constructions. These solvers are capable of
handling complex topography, building structures and they have wide variety of
turbulence and physical models, effective numerical techniques and parallelization
however. With a recent transormation method it is possible to further extend
the limits of such solvers to the simulation of micro- and mesoscale atmospheric
flows with arbitrary stratification. A novel approach was also proposed where the
extended CFD solver was coupled with a bulk microphysical model in order to
describe wet adiabatic processes in the atmosphere. The technical viability and
capabilities of the technique are demonstarted in this thesis through the modeling
of thermal convection, internal gravity waves and the formation of natural- and
human made clouds in and above the atmospheric boundary layer.
ii
Acknowledgments
I would like to express my appreciation and thanks to my supervisor Dr. Gergely
Kristóf, you have always helped and motivated me during the coarse of this work.
I would like to thank for the support of the Department of Fluid Mechanics (DFM),
especially Tamás Lajos and János Vad who gave me the possibility to finish this
project.
Special thanks goes to the members of DFM who were very kind to me and en-
coureged me during my PhD studies.
At the end I would like express appreciation to my beloved wife who pushed me
forward when I lost my motivation.
iii
Contents
Abstract ii
Acknowledgments iii
Contents v
List of Figures viii
List of Tables ix
1 Introduction 1
2 Modeling stratified atmospheric flows and thermal convection – prov-
ing the technical viability and accuracy of a new modeling approach 4
2.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2.2 Meteorological outlook, equations and numerical solution . . . . . . 5
2.2.1 Filtering of acoustic modes . . . . . . . . . . . . . . . . . . . 6
2.2.2 Planetary boundary layer (PBL) and surface-layer schemes,
turbulence, closure problem . . . . . . . . . . . . . . . . . . 7
2.2.3 First order closure . . . . . . . . . . . . . . . . . . . . . . . 8
2.2.4 Higher order closures . . . . . . . . . . . . . . . . . . . . . . 9
2.3 Adaption of general purpose CFD solvers . . . . . . . . . . . . . . . 10
2.3.1 Stratification and turbulence models . . . . . . . . . . . . . 12
2.3.2 System of transformations . . . . . . . . . . . . . . . . . . . 13
2.3.3 Reference profiles . . . . . . . . . . . . . . . . . . . . . . . . 14
2.3.4 Volume sources . . . . . . . . . . . . . . . . . . . . . . . . . 15
2.3.5 A simplified model version for water-tank experiments . . . 16
2.3.6 Nesting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
2.4 Validation of the dynamical core of the model . . . . . . . . . . . . 18
2.4.1 Geometry and mesh . . . . . . . . . . . . . . . . . . . . . . 19
2.4.2 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20
2.5 Validation on laboratory scale urban heat island circulation . . . . . 21
2.5.1 Geometry and mesh . . . . . . . . . . . . . . . . . . . . . . 21
2.5.2 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
v
2.6 Summary and conclusions . . . . . . . . . . . . . . . . . . . . . . . 24
3 Modeling internal gravity waves by using a pressure based CFD solver 26
3.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
3.2 Introduction and literature survey . . . . . . . . . . . . . . . . . . 27
3.3 Validation with the analytic solution of gravity wave propagation . 28
3.3.1 Geometry and mesh . . . . . . . . . . . . . . . . . . . . . . 28
3.3.2 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
3.4 Validation with laboratory scale gravity wave experiments . . . . . 31
3.4.1 Statistical performance measures . . . . . . . . . . . . . . . 32
3.4.2 Geometry and mesh . . . . . . . . . . . . . . . . . . . . . . 32
3.4.3 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33
3.5 Model comparison with a full scale event . . . . . . . . . . . . . . . 37
3.5.1 The Boulder windstorm case study . . . . . . . . . . . . . . 37
3.5.2 Geometry and mesh . . . . . . . . . . . . . . . . . . . . . . 39
3.5.3 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40
3.6 Summary and conclusions . . . . . . . . . . . . . . . . . . . . . . . 44
4 Modeling phase change and moisture transport with a bulk microphys-
ical model using a general purpose pressure based CFD solver 46
4.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
4.2 Literature survey . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
4.3 Overview of existing tools . . . . . . . . . . . . . . . . . . . . . . . 49
4.4 Description of the bulk microphysical model . . . . . . . . . . . . . 51
4.4.1 Transport equaitons . . . . . . . . . . . . . . . . . . . . . . 51
4.4.2 Droplet growth by activation and diffusion . . . . . . . . . . 53
4.4.3 Partial and total evaporation of droplets . . . . . . . . . . . 54
4.5 Validation with a rising thermal in a dry stable atmosphere . . . . . 55
4.5.1 Geometry and mesh . . . . . . . . . . . . . . . . . . . . . . 56
4.5.2 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
4.6 Validation with the rise of a moist thermal . . . . . . . . . . . . . . 57
4.6.1 Geometry and mesh . . . . . . . . . . . . . . . . . . . . . . 57
4.6.2 results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 58
4.7 Validation with the Bugey 1980 field campaign . . . . . . . . . . . . 60
4.7.1 Geometry and mesh . . . . . . . . . . . . . . . . . . . . . . 61
4.7.2 Boundary conditions . . . . . . . . . . . . . . . . . . . . . . 61
4.7.3 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
4.8 Summary and conclusions . . . . . . . . . . . . . . . . . . . . . . . 65
5 Summary, conclusions and outlook 67
5.1 Summary and conclusions . . . . . . . . . . . . . . . . . . . . . . . 67
vi
5.2 Outlook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
6 Thesis points 71
1. Thesis: Modeling stratified atmospheric flows and thermal convection
– proving the technical viability and accuracy of a new modeling
approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71
2. Thesis: Modeling internal gravity waves by using a pressure based
CFD solver . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
3. Thesis: Modeling phase change and moisture transport with a bulk
microphysical model using a general purpose pressure based CFD
solver . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
Bibliography 75
vii
List of Figures
2.1 Nesting of domains . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
2.2 Nonlinear density current . . . . . . . . . . . . . . . . . . . . . . . . 20
2.3 Validation with laboratory scale urban heat island circulation, mean
flow field . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
2.4 Validation with laboratory scale urban heat island circulation, u
and w velocity components . . . . . . . . . . . . . . . . . . . . . . . 23
2.5 Validation with laboratory scale urban heat island circulation, T
profiles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
3.1 Validation with gravity wave propagation, the analytic solution . . 31
3.2 Laboratory scale gravity waves, elongation of waves . . . . . . . . . 33
3.3 Validation with gravity wave propagation, normalized wave length
and amplitude data . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
3.4 Validation with gravity wave propagation, mean flow field Nh/U =
0.69 and Nh/U = 3.33 . . . . . . . . . . . . . . . . . . . . . . . . . 36
3.5 The Boulder windstorm field survey . . . . . . . . . . . . . . . . . . 38
3.6 Validation with the Boulder windstorm survey, mean flow field . . . 43
4.1 Rise of a dry thermal, mesh sensitivity of the solution . . . . . . . . 57
4.2 Rise of a dry thermal, sensitivity of the solution to the explicit
viscosity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
4.3 Rise of a moist thermal, time evolution . . . . . . . . . . . . . . . . 59
4.4 Rise of a wet thermal, mesh sensitivity of the solution . . . . . . . . 60
4.5 Rise of a wet thermal, sensitivity of the solution to the explicit
viscosity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
4.6 The Bugey 1980 field campaign, ambient conditions . . . . . . . . . 63
4.7 Validation with the Bugey 1980 field campaign, LWC field . . . . . 64
4.8 Validation with the Bugey 1980 field campaign, comparison with
aircraft data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
viii
List of Tables
2.1 Nonlinear density current, CFD and reference calculations . . . . . 20
3.1 Laboratory scale gravity waves, investigated cases . . . . . . . . . . 34
3.2 Validation with gravity waves, statistical metrics . . . . . . . . . . . 37
3.3 Validation with the Boulder windstorm survey, statistical measures 41
4.1 The Bugey 1980 field campaign, tower exit conditions . . . . . . . . 62
ix
1 Introduction
A clear trend can be seen in the development of mesoscale meteorological codes
towards the usage of higher resolution numerical models incorporating multiple
physical effects in order to better describe the atmosphere, to give higher resolution
models for urban environments or to give higher fidelity forecasting. This process
is well reflected in the “urbanization” of several mesoscale meteorological models
where more and more fine scale physical effects are introduced.
The urban heat island circulation, which largely affects the ventilation and ther-
mal comfort of large cities is a good example for the urbanization of such codes.
Many researchers investigated the phenomena numerically by different purpose
developed solvers and by mesoscale meteorological models, such as MM5, Meso-
NH and WRF, which utilize urbanized canopy models and surface energy bal-
ance calculations. An excellent agreement with temperature measurements can
be achieved by using fine tuned subgrid-scale surface parameterizations however,
these models still do not allow the exact analyses of contaminant transport in an
urban atmosphere as local immission levels are strongly dependent on fine flow
structures such as urban canyon effects, building-specific lofting, and eddies in the
wakes of buildings.
Boundary conditions for the CFD domain can be taken from mesoscale simulations
by utilizing one-way or two-way model nesting. The drawbacks of this approach
are the numerical errors and model uncertainties introduced by the sudden change
in physical description and interpolation of variables between grid interfaces with
different resolutions. When both close- and far-field flow features are important,
it may be more reasonable to use a single framework for the physical description
for the entire domain.
There is another potential approach however for going towards fine scale namely
when modern computational fluid dynamical (CFD) solvers are adapted to handle
mesoscale effects. General purpose CFD solvers are already widely used in urban
studies such as in the modeling of the ventilation of urban areas, pollution trans-
port studies, wind farm design or calculation of wind loads on different human
made constructions. These solvers are capable of handling complex topography,
building structures and they have wide variety of turbulence and physical models,
effective numerical techniques and parallelization.
1