Call for Papers: "Regional Climate Modeling to Improve Climate Variability and Change Projections at the Local Scale" at AMS (USA)
We would like to encourage you to submit an abstract to our session at the AMS 2013 Fall meeting to be held in Austin, TX, Jan 6-10, 2013. Session title : "Regional Climate Modeling to Improve Climate Variability and Change Projections at the Local Scale"
We would like to encourage you to submit an abstract to our session at
the AMS 2013 Fall meeting to be held in Austin, TX, Jan 6-10, 2013.
Session title : "Regional Climate Modeling to Improve Climate
Variability and Change Projections at the Local Scale " Please refer to
the session abstract below. Abstract submission is open and the deadline
is August 1st. Looking forward to see you in Austin.
<http://annual.ametsoc.org/2013/>
Best regards,
Francina Dominguez (University of Arizona, <francina@atmo.arizona.edu>)
Ruby Leung (Pacific Northwest National Laboratory, <Ruby.Leung@pnnl.gov>
Om Tripathi (University of Arizona, <tripathi@atmo.arizona.edu>)
Hsin-I Chang (University of Arizona, <hchang@atmo.arizona.edu>)
Christopher Castro (University of Arizona, <castro@atmo.arizona.edu>)
Session: Regional Climate Modeling to Improve Climate Variability and
Change Projections at the Local Scale
Abstract: While climate variability and change are largely governed by
global phenomena adaptation to climate phenomena is primarily a regional
and local problem. Regional climate models (RCMs) play an important role
in downscaling global climate model information to the regional and
local scale - at which local stakeholders and decision makers operate.
In this session, we solicit talks related to the development and
application of RCMs. We welcome talks focusing on diagnosis and
evaluation of RCMs with in situ and remote sensing observations,
improved physical parameterizations, and the relationship between
large-scale climate variability and change with local phenomena.
Application of RCMs to hydrological, ecological, agricultural and water
resources management problems, including the prediction of hydrologic
extremes, are also welcome.
Hsin-I Chang
Research Associate
Department of Atmospheric Sciences
University of Arizona



