Mesoscale Observing
Challenges:
One Perspective with
Emphasis on the Urban Zone
presentation to the:
NSF Observing Facilities
Users Workshop
24-26 September 2007
NCAR
Boulder, CO
Walt Dabberdt
Director, Strategic Research
Vaisala - Boulder, Colorado
Presentation Outline
• Urban Demographics & Challenges
• Importance of the PBL
• Measurement Systems
• Mesoscale Networks and Testbeds
©Vaisala | date | Ref. code | Page 2
Presentation Outline
• Urban Demographics & Challenges
• Importance of the PBL
• Measurement Systems
• Mesoscale Networks and Testbeds
©Vaisala | date | Ref. code | Page 3
Ten(10) Largest Cities in 1000A.D. (M-Inhabitants)
Cordova
Spain
0.450
Kaifeng
China
0.400
Constantinople
Turkey
0.300
Angkor
Cambodia
0.200
Kyoto
Japan
0.175
Cairo
Egypt
0.135
Baghdad
Iraq
0.125 (1.25???)
Nishapur
Iran
0.125
Al-Hasa
Saudi Arabia
0.110
Patan
India
0.100
Source: Tertius Chandler: “4,000 Years of Urban Growth” (1987)
©Vaisala | date | Ref. code | Page 4
2015
2000
1950
©Vaisala | date | Ref. code | Page 5
Growth of Mega-Cities
blue = coastal city
green = inland city
City-2015
Tokyo
Mumbai
Lagos
Dhaka
Sao Paulo
Karachi
Mexico City
Shanghai
New York
Jakarta
Kolkata
Delhi
Metro Manila
Los Angeles
Buenos Aires
Cairo
Istanbul
Beijing
Rio de Janeiro
Osaka
Tianjin
Hyderabad
Bangkok
Source: UN Population Division, March 2000
©Vaisala | date | Ref. code | Page 6
Population
26.4
26.1
23.2
21.1
20.4
19.2
19.2
19.1
17.4
17.3
17.3
16.8
14.8
14.1
14.1
13.8
12.5
12.3
11.9
11.0
10.7
10.5
10.1
379.3 (23)
most mega-cities
are in the less
developed regions
(16)
The March of Urbanization in the World (% global population)
World
MDR
LDR
Today,
54.9 1.3 million
17.8
people are moving to
the cities every week!
1950
29.8
1975
37.9
70.0
26.8
2000
47.2
75.4
40.4
2030
60.2
82.6
56.4
MDR = more developed regions
LDR = less developed regions
©Vaisala | date | Ref. code | Page 7
source: UNPD, 2001
Growth by City Size
Contrary to
popular belief, the
bulk of urban
population growth
is likely to occur in
smaller cities and
towns of less than
500,000.
©Vaisala | date | Ref. code | Page 8
Some Relevant City Factoids (source: Arnulf Gruber, 2004)
• ~50% world population (~2007)
• > 80(?)% world GDP (few data)
• > 80(?)% world electricity
[wfd: ~ CO2 eq. emissions?; no good data]
• ~ 95% world internet sites and internet traffic (good data)
•
78% mega-cities are coastal [wfd]
•
70% mega-cities are in less-developed regions [wfd]
©Vaisala | date | Ref. code | Page 9
Examples of Mesoscale Events That Impact Human WellBeing and/or Have Major Economic Impacts
Warm Season Events
•
•
•
•
•
•
•
•
•
•
Tornadoes
Mesoscale boundaries
Mesoscale systems
Convection (localized)
Hurricanes/Tropical storms
Flash floods and main-stem
flooding
Fire weather events
Air quality episodes (O3)
Heat waves
Toxic plumes
©Vaisala | date | Ref. code | Page 10
Winter Season Events
•
•
•
•
•
•
•
•
•
Fronts/short-waves
Liquid/freezing/frozen boundaries
Ice storms
Orographic (e.g., lake effect
storms)
Blizzards/Wind chill
Coastal Gales
Air quality episodes (PM)
Cold air outbreaks
Toxic plumes
Tornado – Ft. Worth, TX
March 28, 2000
Path Length: Approximately 3 miles
Path Width: 1/4 mile
F-Scale: F1 (73-112mph) to F2 (113-157mph)
simulation
©Vaisala | date | Ref. code | Page 11
Source: North Central Texas Council of Governments
MODIS Imagery: France Heat Wave -- August 13-28, 2003
Solid lines demarcate conventional climate zones.
Vegetation index anomaly
Surface temperature anomaly
Source: Zaitchik et al., 2006
©Vaisala | date | Ref. code | Page 12
Three Recent Heat Waves
Event
Year
Location
Fatalities
Heat wave
1987
Athens
~900 deaths
Heat wave
1995
Chicago
~700 deaths
Heat wave
2003
France
~15,000 deaths
Source: Earth Science and Applications
from Space: National Imperatives for the
Next Decade and Beyond (2007)
©Vaisala | date | Ref. code | Page 13
Hurricane Katrina (2005) Tracks: Forecasts and Actual
Courtesy of
James
Franklin,
NHC
©Vaisala | date | Ref. code | Page 14
Mega-City Smog -- Beijing
©Vaisala | date | Ref. code | Page 15
Presentation Outline
• Urban Demographics & Challenges
• Importance of the PBL
• Measurement Systems
• Mesoscale Networks and Testbeds
©Vaisala | date | Ref. code | Page 16
City-Atmosphere Interactions
Bi-directional physical problem with feedbacks:
•Weather and Climate Impacts on the City
•Quality of life
•Economy
•Human health and mortality
•Urban effects on the atmosphere
Direct:
sensible heat
runoff and latent heat
thermal conductivity and heat capacity
aerodynamic roughness
zero-plane displacement
gaseous and particulate loading
sun shading
©Vaisala | date | Ref. code | Page 17
Indirect:
urban heat island
human heat stress
PBL & ML structure
cloud cover & precip.
insolation and radiation
balance
local circulations
Why the Planetary Boundary Layer?
Courtesy of Fed Carr, NAOS
PBL contains the
Convective events in
well mixed layer
during daytime heating
Fog and low clouds
under nocturnal
inversion
Layer of air
containing
the roots of
summertime
convection
Low-level jet
©Vaisala | date | Ref. code | Page 18
for weather
Depth of cold air in winter
to tops of stratocumulus
The Need for Mesoscale Observations -- as Reported by the
North American Observing System (NAOS) Study*
• Need to measure mesoscale phenomena at resolution that is high
enough to accurately represent these mesoscale features in the initial
conditions of a mesoscale model
• If using 6-8 grid points per wavelength criterion, then the needed
resolution can be estimated as follows:
– 20-30 km resolution for jet streams, IPV details, etc.
– But 0.1 – 1 km resolution to observe thunderstorm updrafts
and downdrafts
* Courtesy of: Fred Carr,
Univ. Oklahoma
©Vaisala | date | Ref. code | Page 19
What Additional Observations Are Needed? (source: NAOS)
Critical to get forcing
correct in PBL, and
short waves in troposphere
Satellite
imagery &
soundings
Tropopause
Tropopause (8~13 km)
• Jet Stream
Mid Troposphere (2~8 km)
• Location/intensity of short waves
PBL (Sfc~2 km)
• Ageostrophic
• Orographic
• Temp, Moisture, Wind, Precipitation
• Surface/sub-surface conditions
MidTroposphere
Planetary Boundary
Layer (PBL)
Courtesy of: Fred Carr,
Univ. Oklahoma
©Vaisala | date | Ref. code | Page 20
PBL has largest unmet need
for improved observations
(assuming that next-generation satellite sensors
measure V, T and q at needed resolutions and
precision above the PBL)
Why the PBL? (source: NAOS)
The greatest need in future mesoscale observing capability is high vertical
resolution of T, q and wind in the PBL.
Need
~2km 100-200m
resolution!
Slight variations in these values will have a major impact on:
thunderstorm vs. severe thunderstorm vs. squall line vs. MCC,
and subsequent forecasts of flooding, winds, temperatures, etc.,
and consequent impacts on health, safety, agriculture, transportation, energy, etc.
Courtesy of: Fred Carr,
Univ. Oklahoma
©Vaisala | date | Ref. code | Page 21
Diurnal Boundary-Layer Evolution (after Stull)
©Vaisala | date | Ref. code | Page 22
Urban Boundary Layer: Scales & Layers
©Vaisala | date | Ref. code | Page 24
Near-Surface Layer: Scales & Layers
©Vaisala | date | Ref. code | Page 25
Measurement Capabilities: Transport & Diffusion Scales
Rawinsondes
Daytime Boundary Layer
RADAR
ACARS
Modeling
Gap
Sfc
Obs
Surface Layer
Building
1 mm
1 cm
1m
Slide courtesy Walter Bach, ARO
©Vaisala | date | Ref. code | Page 29
Urban
10 m
100 m
Storm
1 km
Fronts
10 km
Synoptic
100 km
1000 km
Horizontal grid spacing
Nocturnal
Boundary Layer
Rawinsondes
Measurement Capabilities: Transport & Diffusion Scales
RADAR
ACARS
Modeling
Gap
Sfc
Obs
Surface Layer
Building
1 mm
1 cm
1m
Slide modified after Walter Bach, ARO
©Vaisala | date | Ref. code | Page 30
Urban
10 m
100 m
Storm
1 km
Fronts
10 km
Synoptic
100 km
1000 km
Horizontal grid spacing
Mixing Depth – Spatial and Temporal Variability
SCOS-97 mixing depths,
September 4, 1997
0300LST
L.A. Basin
(Plate, 2004)
1400LST
(MacDonald et al., 2001)
©Vaisala | date | Ref. code | Page 31
Emergence of Urban-Based Mesoscale Initiatives
•
U.S. Weather Research Program PDT-10 on Urban Forecasting (1998)
•
U.S. Weather Research Program PDT-11 on Air Quality Forecasting (2001) and
subsequent AQF Workshop (2003)
•
U.S. Weather Research Program Community Workshop on Multifunctional Mesoscale
Observing Systems (2003)
•
U.S. Environmental Protection Agency Recommendations on Air Quality Forecasting and
the Role of Urban Testbeds (2004)
•
Helsinki Mesoscale Testbed (in operation since 2005)
•
U.S. National Academies’ Panel on Multi-Functional Mesoscale Networks (midway through
an 18-month study; completion 1Q 2008)
•
U.S. Multi-Agency New Study of Urban Meteorological Testbeds (ongoing; completion 1Q
2008)
•
American Meteorological Society’s New Panel on Partnerships and Mesoscale Networks
(midway through an 18-month study; no completion target as yet)
•
Canadian Research on Improved Urban Weather and Air Quality Forecasting (started in
2006 a 3-Year Study)
•
U.S. National Science Foundation Study on Urban Meteorology (started a 5-year study in
2006)
•
Beijing Mesoscale Network (in advanced implementation stage)
•
London Mesoscale Network (in early planning stage)
©Vaisala | date | Ref. code | Page 32
Common Themes from Four USWRP Workshops & PDTs
Themes
Impacts of visibility & icing on transportation
Improved understanding & forecasting of winter storms
Improved understanding & forecasting of convective storms
Improved understanding & measurement of clouds &cloud processes
Intense/severe lightning
PBL understanding and measurement
Land surface processes
Mesoscale weather forecasting for emergency response
Mesoscale weather forecasting for air quality forecasting
Hydrological modeling
Optimized observing system design for urban needs
Data assimilation
Uncertainty and predictability
Tailor forecast and data products to user needs
Improved access to data and forecast products
Need for testbeds
Develop strong outreach programs to end users
©Vaisala | date | Ref. code | Page 33
PDT-10
FUZ
X
X
X
PDT-11 WKSHOP WKSHOP
AQF
AQF MESOMS
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
One Very Relevant Study of the US Weather Research Program
BAMS 86(7), 2005
©Vaisala | date | Ref. code | Page 34
Observational Recommendations from the Modeling &
Recommendations
Data
Modeling
Assimilation
& Data Assimilation
Community
re: Modeling
Community
(mesoscale
& Data Assimilation
workshop)
 Current observations are not sufficient for mesoscale applications.
The following observations are needed to most effectively address
deficiencies in current observing networks:


















More accurate precipitation rates with good quality control;
Three-dimensional hydrometeor fields;
Three-dimensional mass, wind, and moisture fields
10-km horizontal resolution in the lower troposphere
10-100 km in the upper troposphere;
Three-dimensional cloud fields and cloud diabatic heating rate profiles;
Daily land (sea) surface features
Soil moisture and temperature profiles,
Snow cover and depth,
Land and sea-surface temperature (SST),
Emissivity
Vegetation type and state;
Turbulent flow, fluxes, and stability measured from Earth’s surface to 2 km
15 min. intervals and 100-200m vertical resolution;
PBL height and characteristics of convective rolls;
Tropopause topology with 10 km horizontal resolution;
O3, CO2, water vapor, & cloud distributions req’d for radiative transfer models;
Aerosols and chemical tracer concentrations
©Vaisala | date | Ref. code | Page 36
Observational Recommendations from the
Recommendations
Nowcasting
Nowcasting
Community
Community
re: Nowcasting
(from the
(mesoscale
Mesoscale
workshop)
Workshop)
Top mesonet recommendation:
Establish a national mesonetwork of surface stations.
NOAA
should take the lead to establish this network, and set standards for
data quality. Resolution needed: <10-25km and 5-15min.
Remote sensing recommendations:
 Addition of dual polarization capability to the WSR-88D network.
 Pursue integration of other radars into the national radar network.
 Investigate improving boundary-layer coverage through the use of
closely spaced X-band radars.
 Vigorously pursue national expansion of the NOAA Profiler Network
with emphasis on boundary-layer observations.
 Test the utility of radar refractivity measurements to improve
nowcasting.
©Vaisala | date | Ref. code | Page 37
Observational Recommendations from the
Recommendations
Nowcasting
Nowcasting
Community
Community
re: Nowcasting
(from the
(mesoscale
Mesoscale
workshop)
Workshop)
Other priority recommendations:
 Conduct research aimed at using total lightning data to improve
severe weather warnings and nowcasts.
 Demonstrate added value of high-resolution water vapor fields for
improve nowcasting.
 Establish testbeds for very short period forecasting (0-6 hr, nowcasting)
of high-impact weather. Tasks should include:






siting recommendations;
identification of leveraged funding sources;
identification of public/private partners;
specification of nowcasting systems and products;
involvement of potential clients and users; and
conducting impact and benefits studies.
©Vaisala | date | Ref. code | Page 38
Recent
Two
Other
Supporting
RelevantStudies
USWRPofStudies
the USWRP
on AQF
BAMS 87(2), 2006
©Vaisala | date | Ref. code | Page 39
Organization
ofRecommendations
Recommendations
Scope
of AQF Workshop
Research Theme:
Boundary-Layer Structure & Modeling
Surface-Atm. Interface & Emissions
Clouds & Aerosol Microphysics
Establish AQ Regional Testbeds
Instrumentation & Measurements
Data Assimilation
Models & Modeling
Forecaster & End-User Products
Outreach
BLD
2
1
2
5
4
1
-
BLD = Boundary-layer Dynamics WG
C&A = Clouds and Aerosols WG
M&M = Measurements and Modeling WG
OAQF = Operational Air Quality Forecasting WG
S&SI = Stakeholders and Societal Impacts WG
©Vaisala | date | Ref. code | Page 40
Recommendations per Working Group
C&A
M&M
OAQF
S&SI
1
1
2
3
1
3
2
2
3
2
3
5
2
2
2
1
9
8
4
2
1
1
10
Recommendations
focus equally on
measurement &
modeling
Total
4
7
9
10
14
6
21
3
11
85
U+
U
U+
U+
U
U+
U+
U
U
U+
U
U
U+
U
©Vaisala | date | Ref. code | Page 44
S&SI
OAQF
M&M
C&A
BLD
Some Specific Recommendations from the USWRP
AQF Workshop (29 April - 1 May 2003)
Recommendations:
Instrumentation & Measurements
develop new met instruments/techniques for
volumetric sampling of PBL (see BLS&M)
develop methods for assimilating new PBL
met measurements (see DA)
improved microphysical characterization techniques
for clouds and aerosols in urban areas
specify method for routine CCN measurements in
urban areas (see testbeds)
develop an "aerosol-sonde"
develop low-cost, easily deployable techniques for
real-time aerosol characterization
explore innovative approaches to upper-air measurements
design optimal chem monitoring networks for gases, PM and UV radiance
develop improved vertical profiling methods for O3 & aerosols
improve methods for using satellite chem measurements
develop ACARS-like system for chem and PM measurements
U+ extremely urgent
U urgent
I
important
Presentation Outline
• Urban Demographics & Challenges
• Importance of the PBL
• Measurement Systems
• Mesoscale Networks and Testbeds
©Vaisala | date | Ref. code | Page 45
Measurement Technology & Environmental Prediction
Observations
Improved atmospheric
measurements are
central to improved
environmental analyses
and forecasts
Science
Computing
Modeling
©Vaisala | date | Ref. code | Page 46
Candidate Measurement Systems
• Weather radar:
• Wind profilers:
• Thermodynamic soundings:
• Lightning detection:
• Radiometers:
Space and Ground-based Profiling
• GPS receivers:
A (GPS)
·
A (GPS)
·
B (LEO)
·
a
jth layer
xa
jth layer
a
Space-based profiling
• Surface mesonets:
¥
a (a ) = 2a ò
a
d ln n / dx
x2  a2
dx
¥
a (a ) =  ò
xa
d ln n / dx
x2  a2
dx
Onion-peeling one layer at a time
All layers affect each observation
Total phase effect ~ 2 km (geometric
amplification)
Total phase effect ~ 0.2 km
Takes 1-2 minutes for entire profile
• Satellites:
Ground-based profiling
Takes 30 minutes for GPS to set 15 degrees
Ill-posed problem with low signal to noise
Well behaved with high signal-to-noise
Printed 4/5/00
©Vaisala | date | Ref. code | Page 47
UCAR COSMIC Project Office
reflectivity; velocity, polarization;
refractivity
radar, sodar; lidar;
tethersondes; aircraft
RAOBS, aircraft; tethersondes;
lidar
CG; total
microwave -- scanning;
multi-wavelength
precipitable water vapor -column integrated;
maybe slant path and 3D
PTU; V; LW, SW, net radiation;
energy & momentum fluxes
geostationary; POES; LEO
WSR-88D Radar Network Coverage – PBL Limitations
• Elevation angles between 0.5 and 20 degrees
• Earth surface curvature effect
• “Cone of silence” & “pyramid of silence”
• Much less coverage at the low levels/in PBL where features such as
thunderstorm outflows, convergence boundaries are crucially important
• Resolution degrades further away from radar
• ~75-85% of PBL is not observed
PYRAMID
OF
SILENCE
CONE OF
SILENCE
20deg
0.5deg
Courtesy of: Fred Carr,
Univ. Oklahoma
©Vaisala | date | Ref. code | Page 48
CASA
Price target equivalent
to a mid-to-high-end
automobile
©Vaisala | date | Ref. code | Page 49
©Vaisala | date | Ref. code | Page 50
Mixing Depth – Radar
Data and
Wind
Methods
Profiler
Estimating Mixing Depth
Cn2
Vertical
Velocity
Spectral
Width
0
©Vaisala | date | Ref. code | Page 51
local time
24
Mixing Depth – Ceilometer vs. RAOB Sounding (2000)
CT25K Backscatter 28-29-Mar-2000
3000
2000
1500
1000
500
12
14
16
18
20
22
0
CT25K Backscatter 29-Mar-2000 @ 11:44
2000
1800
1600
1400
1200
1000
800
600
400
200
0 2
10
10 3
10 4
©Vaisala | date | Ref. code Backscatter
| Page 52
(a.u.)
2
4
6
8
10
12 14
16
18
20
22
0
Local Time (h)
Radiosonde Sounding 29-Mar-2000 @ 11:44
2000
1800
1600
1400
1200
1000
800
600
400
200
CT25K BSL
0
0
5
10
Potential Temperature (°C)
Altitude (m)
0
10
Altitude (m)
Altitude (m)
2500
1m
Mixing Depth – Ceilometer vs. RAOB Sounding (2006)
©Vaisala | date | Ref. code | Page 54
Summary of Selected Mesoscale/Urban Challenges

PBL observations with high vertical and temporal resolution




radar wind profilers
lidars & laser ceilometers
x-band radars
aircraft

Dynamic characterization of land surface

Acquire & assimilate 4D meteorological and chemical data

High-resolution surface networks: <10km and 5min resolution

Augmentation of weather radar network





dual polarization
radars of opportunity
high-density, low-power radar networks
total lightning observations – merge with radar data
adaptive radar calibration
 Testbeds -- a vehicle to evaluate alternative measurement, modeling
and implementation strategies
©VaisalaOptimal
network
design
| date | Ref. code | Page
59
Presentation Outline
• Urban Demographics & Challenges
• Importance of the PBL
• Measurement Systems
• Mesoscale Networks and Testbeds
©Vaisala | date | Ref. code | Page 60
Some Definitions
Mesoscale networks measure the three-dimensional,
time-dependent structure of the lower atmosphere
using an integrated observing system that incorporates
in situ and
remote sensing systems, deployed on/from
APPLICATION
the ground and aloft.
“Mesonets” are a subset of mesoscale networks that
consist of high-density surface stations.
©Vaisala | date | Ref. code | Page 61
General applications
• Analysis/description of current atmospheric state – research or ops
• Nowcasting/very short-range forecasting
(0+ to ~2 hrs)
• Short-range mesoscale prediction
(~3 to 48 hrs)
Area (rel.)
mesoscale
prediction
As the timescale of the prediction
increases, so does the commonality of
the observing systems needed to make
the prediction (i.e. they become less
application-specific).
nowcasting
Site of
interest
©Vaisala | date | Ref. code | Page 62
analysis
As the timescale of the prediction
decreases -- toward analysis and shortterm nowcasting – the observing
requirements become more applicationTimespecific
(rel.)
Mesoscale Weather Forecasting -- Testbeds
Testbed Definition: “A working relationship in quasi-operational
framework among forecasters, researchers, private-sector, and
government agencies aimed at solving operational and practical
regional problems with a strong connection to end-users.”
©Vaisala | date | Ref. code | Page 63
Testbed Criteria
A successful testbed must satisfy the following criteria:
 Address the detection, monitoring, and prediction of regional
phenomena of particular interest
 Define expected outcomes
 Provide special observing networks needed for pilot studies and
research
 Define strategies for achieving the expected outcomes
 Engage experts in the phenomena of interest
 Involve stakeholders in planning, operation, and evaluation of the
testbeds
 Expedite R2O: transitioning research to operations
©Vaisala | date | Ref. code | Page 65
Testbed Concept
Obs. Sys. Priorities for
R&D
• Exploratory
• Higher Resolution
• Multi-Sensor
• New Variables
• Exploratory Analysis
R&D
©Vaisala | date | Ref. code | Page 66
Obs. Sys. Priorities for
Operations
• Reliability
• Efficiency
• Cost Effectiveness
• COTS
• Continuity
Testbed
Functions
Operations
Testbeds provide the
infrastructure for
transitioning from R&D to
operations. Testbeds need
the flexibility to test many
new ideas, the expertise to
judge which of them are
viable, and the
infrastructure to harden the
sensors, algorithms and
models that will generate
new products for
operations.
Status of some Mesoscale Testbeds
• Helsinki Testbed Phase I (observations) started August 2005;
II (applications) started August 2007
Phase
• Beijing Olympics 2008 enhanced mesoscale observing-andforecasting underway
• Shanghai 2010 World Expo enhanced meso- and micro-scale multifunctional observing-and-forecasting system in advanced planning
• U.S. preparations/planning underway
• DHS – Homeland Security limited urban nets in New York and WDC
• OFCM urban testbeds under consideration
• Multi-agency planning in early stage – NRC/BASC study (completion early
2008)
©Vaisala | date | Ref. code | Page 67
Two Approaches to Designing Networks
Designing
Mesoscale
Meteorological
Observing
Empirical
Networks
Methods
Analytical
(current
Methods
state-of-the-art)
(in development)
Team of experts (Wx & AQ):
• Forecasters
• Modelers
• Observationalists
• Other ‘stakeholders’
©Vaisala | date | Ref. code | Page 68
Numerical tools:
• OSSEs
• OSEs
• Data denial experiments
• Observational testbeds
©Vaisala | date | Ref. code | Page 69