Nathan Moore Research Associate Room 202, Manly Miles Building Department of Geography Michigan State University East Lansing, MI, 48823 (517)-355-1733 moorena@msu.edu Climate Change, the Water Cycle, Physical Geography,  Land Surface Interactions, Regional Climate Modeling Download my CV (.pdf)
	Ph.D. 2004 Earth and Ocean Sciences, Duke University  M.S. 1997 Physics, University of Oregon B.A. 1993 Physics, University of Virginia

East Africa. I am modeling and projecting climate trends and variability in Eastern Africa as part of the Climate-Land Interactions Project (CLIP) at Michigan State University. Using the RAMS atmospheric model we are investigating the potential impacts of land use change in Kenya, Tanzania, and Uganda. Economic, cultural, and natural drivers are being assessed via landscape models like LTM and MABEL. Once we understand how RAMS responds under current conditions, we will use landscape models in conjuction with GCM results to assess likely regional climate responses to different boundary conditions and land surface conditions. I am employing a variety of GIS tools and remote sensing data to compare model results with observed temperature, rainfall, and other variables.

The Amazon. I am exploring the range of uncertainty in Amazonian land-climate interactions by explicitly simulating 50 different "worst case scenario" landscapes and 50 "best case scenario" landscapes. A large portion of this research includes joining the work of human geographers (via GIS methods) with a physical representation of a land surface in terms of biophysical parameters like fractional cover and albedo.

Experimental Design. I am also interested in experimental design and how choices in the structure of an experiment can influence the
range of possible outcomes. Both projects, being interdisciplinary, lend themselves to this sort of analysis,
and both groups are studying what constraints (and uncertainties) we have introduced to the systems in question
by make the choices we have made in our modeling/measuring efforts.

PUBLICATIONS:

My Ph.D. focused on studying large hydrologic disturbances and how they affect climate, weather, and agriculture. Using AVHRR satellite images and Nexrad precipitation estimates from the Great Plains region, we determined variability in evapotranspiration and irrigation for the region. We have looked at monthly precipitation patterns with Principal Components Analysis which showed that monthly data were not adequate to detect perturbations on the order of an irrigation effect. Subsequent research using hourly precipitation images from NOAA (www.srh.noaa.gov/abrfc) suggests that irrigation adds 1-4cm or additional rain to the Texas Panhandle area, which corresponds to a ~15% increase that could possible be attributed to irrigation.

     The final phase of the research centered on modeling the physical processes that could lead to the formation of mesoscale circulations which produce rain. Using the Regional Atmospheric Modeling System (RAMS) we explored one month (July 1996) at 4 km resolution. Some physical quantities which are important in regional atmospheric forcing (e.g. latent heat flux, convective available potential energy) are not measured in the area, so we relied primarily on Nexrad estimates of precipitation, GOES satellite imagery, and radiosondes for validation. We found that modeling July 1996 with irrigation in the Texas Panhandle produced about 35% more precipitation than the unirrigated simulations. This difference was statisically significant, but the irrigation did not occur in precisely the same places and times as observed precipitation.

Skill scores, correlation indices, and many other statistical measures show that on the large scale (days/10s of kilometers), the model produced precipitation very similar to observation in terms of timing, amount and location. However, on finer scales (hourly/kilometers) the model's fidelity to observation fades. This is attributable in part to problems of convective parameterization and downscaling. Irrigation is clearly responsible to some extent for the elevated precipitation in and around the Texas panhandle, but the exact amount remains uncertain.

Updated on ... 17 December 2007