93 / 218
– there is also a critical need to seamlessly integrate data
from all of the disparate observation systems to extract
maximal information.
Projects like the Helsinki Testbed are a valuable interme-
diate step in designing networks and sampling strategies;
evaluating new observation systems; setting data-quality
standards; creating products that better meet user needs; and
testing the ability of the public, private, and academic sectors
to form effective partnerships to enable operational
mesoscale networks. Successful testbeds should meet the
following criteria:
• Address the detection, monitoring, and prediction of
regional phenomena
• Engage experts in the relevant phenomena
• Define expected products and outcomes, and establish
criteria for measuring success
• Provide specialised observation networks for pilot studies
and research
• Define strategies for achieving the expected outcomes
• Involve stakeholders in planning, operation, and evalua-
tion of the testbeds.
The implementation of advanced 3D mesoscale measurement
networks entails many practical issues in addition to the tech-
nical and scientific ones. A national collection of regional and
urban networks will require a significant commitment and a
major infusion of financial resources. In many countries, the
most viable model for developing and supporting operational
mesoscale networks leans toward a consortium of public,
private and academic partners. In the old paradigm of synop-
tic-scale networks, government took responsibility for all
aspects of the observational problem – design, testing, stan-
dard-setting, quality assurance, implementation, and operation.
But with the reduction in scale size demanding more and
improved observations, and improved sampling strategies and
modeling systems, a partnership approach may offer the great-
est likelihood of successful and timely implementation.
Establishing one or more end-to-end mesoscale testbeds is a
tangible first step in establishing the urban networks needed
by the world’s growing cities.
[
] 93
Table 2: PCC estimates of confidence in observed and projected changes in extreme weather and climate events
Changes in phenomena
Confidence in observed changes
Confidence in projected changes
(latter half of the 20th century)
(during the 21st century)
Higher maximum temperatures and more hot
Likely
Very Likely
days over nearly all land areas
Higher minimum temperatures, fewer cold days
Very Likely
Very Likely
and frost days over nearly all land areas
Reduced diurnal temperature range
Very Likely
Very Likely
over most land areas
Increase of heat index (a measure of human
Likely, over many areas
Very Likely, over most areas
discomfort) over land areas
More intense precipitation events
Likely, over many Northern Hemisphere
Very Likely, over many areas
mid- to high latitude land areas
Increased summer continental drying
Likely, in a few areas
Likely, over most midlatitude continental interiors
and associated risk of drought
(lack of consistent projections in other areas)
Increase in tropical cyclone peak wind intensities
Not observed in the few analyses available
Likely, over some areas
Increase in tropical cyclone mean and peak
Insufficient data for assessment
Likely, over some areas
precipitation intensities
Virtually certain: greater than 99% chance that a result is true; Very likely: 90–99% chance; Likely: 66–90% chance; Medium likelihood: 33–66% chance
Unlikely: 10-33% chance; Very unlikely: 1–10% chance; Exceptionally unlikely: less than 1% chance.
Source: McBean and Henstra, 2003
One example of urban smog – Kuala Lumpur, Malaysia
Photo: Vaisala