There is a growing need for indicator-quality data which facilitate inter-comparison of environmental, economic, and social situations.  Applications of such data include comprehensive assessments of security/resilience vs impact/vulnerability, strategy development, and decision support toward mitigating challenges and improving outcomes for communities.  This may require a new breed of weather and climatic indicators, thematically focused on people and planning, and geographically tagged to detailed administrative units – as has been evolving in other fields for 10-20 years.

Three examples of strategic needs for such data/indicators:

Human Security Index: The global HSI (reference below) was first released in 2008, with version 2 posted in 2010.  Human Security Index USA (reference below) is in prototype.  Aimed to be more geographically and thematically comprehensive and perceptive than many socio-economic “well-being” indices, it looks at economic, environmental, and social fabric of individuals and communities.  Detail is to 232 countries, and ~3142 counties in the USA, with potential for partial extension to census tracts (of which there are ~65,000).  It is being developed as a decision-support and strategizing support tool, so is formulated as attributes assigned to administrative units (e.g. global=>230 countries; USA=~3142 counties). 

National Climate Assessments: The US Global Change Research Program is mandated to regularly produce National Climate Assessments (reference below).  A goal for upcoming NSAs is to craft societal indicators which may help in assessing situations (including possible impacts) related to climate change.  For this to be most useful meteorological, climatic, other environmental, and socio-economic data must be developed for enhanced comparability.

Quantifying Vulnerability to Climate Change: Implications for Adaptation Assistance: This effort (reference below) attempts to link vulnerability to extreme weather, sea level rise, and agricultural productivity change to vulnerability, determine costs, and to estimate apportioned adaptation assistance for 233 countries.  One could also imagine a parallel sub-national effort, such as at the municipal and county levels in the USA, possibly to complement and feed National Climate Assessments and Human Security Index development and application.

Challenges:

In order to stretch in such directions, how may meteorological and climatological indicators best be crafted for use in conjunction with other environmental and socio-economic data to (1) perceive societal situations (particularly security/resilience vs. vulnerability/impacts), and (2) provide a strategic and decision-support framework toward progress?

An example of such an attempt is the Natural Amenities Scale (reference below).  In an attempt to better understand possible causes for population loss in many rural counties, and contrasting gains in some other counties, the final Natural Amenities Scale looked at mean January temperature and hours of sunlight, mean July temperature and relative humidity, percent water area, and terrain characteristics for each county in the Conterminous USA.  These inputs were scaled and blended to form the Natural Amenities Scale.  A followup assessment by the author suggests that a more diverse design team might select different input parameters, and scale them differently, and then refine the process with a more rigorous comparison of other data (in addition to population change).  Indeed, the published Natural Amenities Scale might provide an excellent platform for (1) enhancement for use in the Human Security Index and/or National Climate Assessments societal indicators, and (2) a stimulus for assessment on the design and development of a new cadre of meteorological, climatic, and related environmental indicators tagged to counties for enhanced decision-support and strategy development.

Implications/Opportunities for Weather-Climate Indicator Developers?

Are the data selected for the Natural Amenities Scale, for the HSI, and for the Quantifying Vulnerability effort the best choices?  Could better data-indicators be crafted?  Could we formulate better scaling of the input data to associate with community socio-economic-environmental vulnerability and resilience? Do traditional weather-climate statistics, often focused on observing systems, best serve the needs of such assessments?  Could models of likely current or projected extreme events be improved?

Suggested options for improving the comparability of weather-climate, other environmental, and socio-economic data will be presented.