INSPIRE impact analysis on Meteorological Community: KNMI Example

W.J. Som de Cerff, R. Sluiter, J.W. Noteboom, G. H. J. van den Oord
(Royal Netherlands Meteorological Institute (KNMI), De Bilt, The Netherlands)

On May 15 th 2007, the INSPIRE directive (Infrastructure for Spatial Information in Europe) entered into force. The overall aim of the INSPIRE directive is to improve the way in which spatial data held by public authorities supports environmental policy, by improving the harmonization of data and the interoperability of spatial services, ensuring better sharing of the data between public authorities and on-line access by the public . Each member state has until 2009 the time to integrate the directive into national law. The INSPIRE directive addresses data and services for meteorology and related themes. Meteorological data and services belong to annex III, especially to themes 13 – Atmospheric conditions, 14 Meteorological geographical features, 15 - Oceanographic geographical features and 16 - Sea regions. In addition some other themes require meteorological data and services, in particular theme 5 - Human health and safety, 7 - Environmental monitoring facilities and 12 - Natural risk zones. What are the implications of INSPIRE for a meteorological institute like KNMI when the INSPIRE directive is adapted into national law? To find answers to this question KNMI, the national institute for weather, climate research and seismology in the Netherlands has formed a small team studying the implications and reviewing the INSPIRE guidelines and directives themselves. An impact analysis has been written that will be published as a technical report. KNMI is actively involved in INSPIRE as Legal Mandated Organization (LMO), to be able to comment on INSPIRE guidelines. Internationally, KNMI is part of INSPIMET, a working group set up by EUMETNET [R2] that considers the implications of INSPIRE to meteorological institutes. Nationally, KNMI aligns INSPIRE support with Geonovum, the National Spatial Data Infrastructure (NSDI) executive committee in the Netherlands [R3].

[R1] INSPIRE, Infrastructure for Spatial Information in the European Community
http://inspire.jrc.ec.europa.eu/

[R3] Geonovum, is the National Spatial Data Infrastructure (NSDI) executive committee in the Netherlands

An Investigation of Risk and Exposure to Extreme Heat in Phoenix, AZ: A Mixed Methods Analysis

Darren M. Ruddell (School of Geographical Sciences, Arizona State University), Sharon L. Harlan (School of Human Evolution and Social Change, Arizona State University), and Susanne Grossman-Clarke (Global Institute of Sustainability, Arizona State University).

As rapid urban development continues, the impacts of temperature extremes on human health and comfort are also expected to increase as threshold temperatures of human tolerance are crossed more frequently and for longer periods of time. To investigate changing urban climates, human decision-making that alters urban environments, and human illness associated with extreme heat, a research agenda designed to integrate multiple methodologies and data sources is required. GIS represents a unique platform that allows users to synthesize physical and social data. This study combines modeling output on heat variability for the summer of 2005 throughout the Phoenix metropolitan area with US Census data and two questions from the Phoenix Area Social Survey (PASS) 2006 regarding respondent perceptions of heat and reported symptoms of heat stress. Employing the mesoscale Weather Research and Forecast (WRF) climate model to simulate local temperature variability throughout the region, analyses compare resident perceptions of heat stress to scientifically measurable environmental conditions for selected heat events and explore human-environmental relationships.

Integrating Climatological Techniques and Geographic Information Systems to Assess Rocky Mountain Hydroclimatic Variability

Erika Wise (University of Arizona)

A multitude of activities and livelihoods depend on rivers systems that originate in the Rocky Mountains. This area experiences a high degree of hydroclimatic variability due to physiographic, meteorological, and teleconnection influences. The purpose of this study is to improve understanding of the spatial and temporal patterns of hydroclimatic variability in this region, as well as the underlying atmospheric processes controlling those patterns. Analysis of historical climatological and hydrological data were undertaken to provide better understanding of current hydroclimatic connections at the watershed scale. Monthly precipitation averages and anomalies were calculated using gridded precipitation data, and the precipitation anomalies were regionalized using empirical orthogonal function analysis. The resulting grid was incorporated into a Geographic Information Systems (GIS) database and re-gridded to a lower resolution for spatial analysis and the examination of linkages between precipitation patterns and controlling processes. Results of climate composites indicate strong synoptic controls on Snake and Yellowstone river streamflow in both high- and low-flow years. The strongest precipitation anomaly pattern is a north-south transition that is partially, but not entirely, explained by teleconnection influences. Lack of synchronicity in wet/dry years between adjacent watersheds across the continental divide may result from increased precipitation variability on the eastern side of the Rocky Mountains.

Advancing the Understanding of Human-Environment Interactions Using Fine Resolution Socioeconomic Data

Alex de Sherbinin (CIESIN, The Earth Institute at Columbia University)

This poster describes three applications of fine resolution gridded socioeconomic data to understand human-environment interactions in the context of global assessments. These applications reveal how human population and welfare are related to a variety of environmental variables, and how future environmental change such as increased drought or sea-level rise is likely to affect well being. Applications 1 and 3 uncover vulnerabilities in dryland regions, whereas application 2 demonstrates the vulnerabilities of the coastal zone to sea-level rise.

NARCCAP: Regional Climate Change Modeling for Impacts & Analysis

Seth McGinnis (ISSE - NCAR)

The North American Regional Climate Change Assessment Program (NARCCAP) is an international program to produce high resolution climate change scenarios and investigate uncertainties in regional scale projections of future climate by nesting multiple regional climate models (RCMs) within multiple atmosphere-ocean general circulation models (AOGCMs) forced with the A2 SRES scenario and with historical data over a domain covering the conterminous United States, Northern Mexico, and most of Canada. The resulting 60+ TB of data will be archived for distributed storage and made available to global change impacts researchers worldwide via the Earth System Grid (ESG). To ensure that the final product is usable by the impacts community, GIS practitioners, climate analysts, modelers, policy-makers, and other end users, data is stored in NetCDF format adhering to the CF metadata standard, making it fully compatible with many popular analysis programs, including ArcGIS, Matlab, IDL, and R.

Studying the potential impacts of climate changes on Wyoming vegetation coverage using GIS, statistics and spatial data mining

ZongBo Shang (University of Wyoming)

Factor analysis, classification and regression tree analysis (CART), discriminant analysis and classification analysis were applied to study land cover in Wyoming, to explore: 1) how environmental variables are related to one another; 2) whether land cover types (forest, grass, shrub and un-vegetated) are differentiated from one another in term of abiotic conditions; and 3) how to predicate vegetation covers based on environmental variables. A factor analysis indicated that environmental variables were characterized by three dominant conditions: 1) harsh condition for survival, 2) suitable condition during growing season, and 3) harsh condition caused by high altitude. A discriminant analysis indicated that: 1) forests and grasses required wet climate with relatively cool summers, while shrub could bear drought; 2) quite different to forests, grasses required dry winters and relatively wet and warm summers. CART and classification analysis both indicated that, by using Precipitation in July, Maximum Annual Temperature and Average Annual Precipitation, we had a fair accuracy in predicting vegetation covers in Wyoming. Based on 6 pre-specified climate change scenarios, we used this model to study the potential impacts of climate change on vegetation coverage in Wyoming.

GIS Analysis of Impacts from Sea Level Rise

X. Li (1), R.J. Rowley (2), J.C. Kostelnick (3), D. Braaten (1), J. Meisel (2) and K. Hulbutta (2)
(1) Dept. of Geography and CReSIS, University of Kansas,
(2) College of Mathematics and Natural Sciences, Haskell Indian Nations University,
(3) Dept. of Geography-Geology, Illinois State University

Precipitation Events—its Dynamics and Movement

X. Li and D. Tucker (Dept. of Geography, University of Kansas)

A precipitation event in this study is defined as a contiguous precipitation object in space and time. It consists of a set of connected precipitation cells delineated from stacked hourly NEXRAD precipitation raster layers. The method used to identify contiguous regions in space and time is based on the component labeling algorithm in digital image processing. Three parameters, the minimum hourly precipitation ( MHP ) in a cell, the minimum time span (MTS) of an event, and the definition of spatial and temporal connectivity, were used to control event delineation. Each event is represented as a directed spatio-temporal graph which the nodes are precipitation areas during the life span of the event. Based on this representation, precipitation events, their statistics, movement, and path can be visualized, queried, and analyzed.