GIS in Meteorology and Climate Science

Transcription

1 GIS in Meteorology and Climate Science Olga Wilhelmi and Jennifer Boehnert NCAR / Research Applications Program African Weather and Climate: Unique Challenges and Application of New Knowledge 25 July 5 August 2011, NCAR, Boulder, Colorado

2 Outline NCAR GIS program Introduction to GIS GIS in meteorology and climatology Data interoperability Science applications

3 NCAR Science Climate Earth's past climate, greenhouse effect and global warming, Earth's future, El Niño & La Niña, drought and wildfires. Meteorology/Weather Short-term forecasts, weather forecasting and predictability, weather's effect on climate, training meteorologists, severe storms, physical processes. Societal Impacts, vulnerability and adaptation Effects of weather & climate on society, human health, urban water management, national security, risk perceptions, integrated assessments, economics Pollution & Air Chemistry Air pollution, chemistry of our atmosphere, tracking plumes, ozone. The Whole Earth System Oceans effects on climate and weather, the effects of land use on climate and weather, cryosphere/ice, the water cycle. Sun & Space Weather Solar furnace, suns effect on weather and climate, the solar

4 web: Interdisciplinary effort to foster collaborative science, spatial data interoperability, and knowledge sharing with GIS. Goals: Support the use of GIS as both an analysis, and an infrastructure tool at NCAR; Conduct research integrating atmospheric, the Earth system and social sciences through spatial analysis and interoperability of georeferenced information; Improve usable science through data sharing; and Address issues of spatial data management, interoperability, and geoinformatics within the geosciences.

5 NCAR GIS Program Partnerships OGC Esri Atmo/GIS-Community Standards Unidata (Ben Domenico) netcdf Analysis tools OGC-NCAR MOU Development of OGC technology within the atmospheric sciences and to extend OpenGIS specifications to include the geospatial processing needs of the atmospheric community Outcome: CF-netCDF is an OGC standard Esri NCAR MOU Advancing GIS technical methods and technologies; Exploring the development of atmospheric information and models within GIS domains Outcome: netcdf CF in ArcGIS Atmo-GIS community workshops

6 Program elements and current priority areas GIScience Research enabled by GIS Data distribution Building community Education, Training & User Support Coupling natural and social sciences through integration of quantitative and qualitative data Improving spatial accuracy and usability of atmospheric models for terrestrial and societal applications Building capacity through GIS-focused education, usable GIS lab, community workshops and enabling interdisciplinary research

7 Geographic Information Systems GIS is a science and a technology that includes elements of Computer visualization Database management Query, spatial analysis and modeling Web services Powerful information management tool

8 GIS Overlays Geographical referencing allows for mapping spatial and non-spatial data together to reach a common interpretation GIS overlay (data integration) allows to create or identify spatial relationships

9 A broader perspective of GIS Theories Applications Thematic domains COMMUNITY Data, Information, and Communication Systems Computation and Algorithms Communication and Decision Support Source: May Yuan (U. Oklahoma) Society

10 Diverse atmospheric data

11 Data challenges Spatially and/or temporally structured quantitative (e.g., surveys), qualitative (e.g., interviews, images), often context-specific pieces of information Social Sciences Data Integration/ Spatial Analysis GIS Earth Sciences

12 NetCDF in ArcGIS Atmospheric community ESRI collaboration Since 2006 release of ArcGIS 9.2 NetCDF CF format can be read in GIS

13 Mesoscale Weather Models (WRF) Interactive web mapping application which integrates WRF forecast with socio-economic and infrastructure data Dynamically adds netcdf WRF Hurricane model through ArcGIS Server Symbolized based on hurricane wind scale (Saffir-Simpson Wind Scale) and accumulated rain User-defined query about possible impacts (population density, schools, critical infrastructure) From J. Boehnert (NCAR)

14 Operational meteorology Radar Warnings

15 Monitoring Rainfall in the IRI Map Room Source: IRI, P. Cecatto

16 Rainfall estimation Source: IRI, P. Cecatto

17 Global Climate Models (CCSM) Distributing outputs from NCAR Community Climate System Model (CCSM), generated for IPCC AR4, in a GIS format Monthly averages Global CCSM runs Downscaled USA projections Dynamic converter from netcdf to shapefile ~3700 users from 133 countries; ~49K downloads

18 Climate products Temperature and Precipitation Annual and seasonal averages Anomalies from present climate ( ) Near-term ( ) Mid-century ( ) End of 21 st Century ( )» Special subset ( ) Pilot for distributing these products as OGC Web Mapping Service and Web Coverage Service Challenges due to multidimensional nature of data Data description metadata

19 Future scenarios and uncertainty

20 Spatial analysis and GIS applications Visualization of information Spatial analysis Location (Where is it...) Condition (What is it...) Trend (What has changed...) Pattern (What is the pattern...) Modeling and Prediction (What if...) Why? (linking spatial and non-spatial data) Data sharing

21 Rate of change: extreme heat events and urban population Majority of cities with greatest rate of change are located in mid- and high latitude countries (e.g., US, Russia, Norway, Canada, Ireland, Chile), but also include Spain, Argentina, Nepal and Iran Majority of cities with greatest rate of change in urban population are in low-latitude countries (e.g., Iraq, Egypt, Oman, Brazil, Venezuela, Libya, Rwanda, Papua New Guinea, Yemen), but also include Iceland.

22 Climate indices Source: CIESIN, A. de Sherbinin. The Biophysical and Geographical Correlates of Child Malnutrition in Africa (2009)

23 Integration of atmospheric and social data Wilhelmi and Hayden (ERL, 2010)

24 Role of scale Impacts, risk and vulnerability are spatially differentiated National and regional assessments can mask communities living in marginal conditions Hazard mitigation and climate change adaptation measures have to be adjusted for local ecology and appropriate level of decision making O Brien et al Local-level assessment ensures more targeted intervention, response, adaptation. Borden et al Top down/bottom up approach is essential

25 System for Integrated Modeling of Metropolitan Extreme heat Risk (SIMMER) RAL CGD IMAGe NASA ROSES (09-IDS09-34) FY10-13

26 SIMMER Tools and Data Local Scale Models Weather Research and Forecasting Model (WRF) Noah Land Surface Model (Noah LSM) w/ Urban Canopy Model (UCM) Regional Scale Models Community Earth System Model (CESM/CCSM; atmosphere, ocean, land, sea ice, ) Urban Community Land Model (CLMU) Urban Datasets Local land cover / urban heat island (Houston) Regional (U.S., Southern Canada) (based on Landscan USA or similar) NASA Satellite Data Demographic Datasets US Census Household Survey

27 Remaining challenges and research directions Availability of spatial data at the local scale Input into atmospheric models Societal data (proxy) Multidimensional GIS Data interoperability across disciplines (data, semantics, scales) Representation of uncertainty Integration of physical and social sciences requires further research on methods and tools for working with multidimensional data, across spatial and temporal scales, and including both quantitative and qualitative information.

28 Summary GIS is critical to integrating data sources from different disciplines. Significant progress has been made in linking GIS and meteorology but few challenges remain. Growing interest among practitioners in GIS- compatible atmospheric data Growing recognition among researchers and organizations that GIS is appropriate tool for research, climate change adaptation and science communication. Ongoing research in GIScience and developments in geospatial technology may further increase the use of GIS in meteorology and climate science.

29 Thank you!