Call for Abstracts: AGU Session on Integrated Observations and Modeling of Water Cycle (Variability) Extremes (WCEs)
Extremes in the water cycle are becoming more frequent and intense as the climate changes. Many of the impacts of these climate-related extremes are mediated through the water cycle. They are particularly important because of their large impacts on socio-economic structures/activities and on natural ecosystems. WCEs are at the center of changes in the water-food-energy-health-ecosystem nexus. They provide a cross-cutting focus for water cycle research and applications. Adequately characterizing WCEs (in space/time) is a challenge to both space-based and in-situ observing systems, and data assimilation/modeling systems. These topics will be discussed in a session at the AGU Conference taking place 14-18 December 2015 in San Francisco, CA, USA.
Papers are invited to review the capabilities/limitations of space-based and in-situ observing/monitoring systems and assimilation and modeling systems to characterize extremes and variability for: Precipitation (Droughts/Floods); Evapotranspiration; Soil Moisture (Near surface and Root-Zone); Surface Water (Run-Off, River Flow/River Discharge, Lakes/Reservoirs); Snow/Ice; and Ground Water Storages (Aquifers, Discharge/Re-Charge) and their implications for other terrestrial process. It is anticipated that results from this session could be beneficial for addressing several of the recommendations in the GEOSS Water Strategy report. If you are planning on being at the fall AGU and you have something to contribute on this topic we would encourage you to submit an abstract to this session.Primary Convener
: Sushel Unninayar, NASA/GSFC, GESTAR/MSU, Greenbelt, MD, United StatesConveners
: Richard G Lawford, Morgan State University, Greenbelt, MD, United States and Paul Houser, George Mason University, Fairfax, VA, United StatesWhere to Submit
: https://agu.confex.com/agu/fm15/preliminaryview.cgi/Session7884Abstract Submission Deadline
: 5 August 23:59 EDT/03:59 +1 GMT.