1 / 8

Climate Analysis for Enhanced Resilience

Climate Analysis for Enhanced Resilience. Ben Zaitchik Johns Hopkins University. Projected Precipitation Changes. Change in Annual Precipitation: 2080s – present, Blue Nile Headwaters. NASA’s Project Nile. IPCC AR4. GCM-based Precipitation Maps. Spatially coarse Highly uncertain

leola
Télécharger la présentation

Climate Analysis for Enhanced Resilience

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Climate Analysis for Enhanced Resilience Ben Zaitchik Johns Hopkins University

  2. Projected Precipitation Changes Change in Annual Precipitation: 2080s – present, Blue Nile Headwaters NASA’s Project Nile IPCC AR4

  3. GCM-based Precipitation Maps • Spatially coarse • Highly uncertain • Underestimate extremes • Systematically wrong in some regions

  4. So: Are the GCMs Useless? • No: there is useful information in the projections • But: precipitation projections applied directly to food/water security planning can be worse than useless

  5. 1. Dynamical Downscaling • Physically-based predictions • Can handle non-stationarity • Requires extensive evaluation of RCM and GCM • Computer and time intensive

  6. 2. Statistical Downscaling • Data-based and not computer intensive • Does not rely directly on GCM atmospheric dynamics • Requires 30+ year meteorological station records • Assumes stationarity

  7. 3. Physiographic Interpolation • Physically based • Highly localized at low computational expense • Can utilize satellite data • Derived from a larger scale projection • Requires calibration and evaluation

  8. Summary • GCM projections require interpretation and downscaling • Dynamical downscaling is valuable but resource intensive, and it relies on GCM atmospheric boundary conditions • Much can be achieved with statistical methods, but data and understanding are required • Coordinated dynamical-statistical approaches are optimal

More Related