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TZUNTIL:20191027T010000Z
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DTSTART:20171029T030000
TZOFFSETFROM:+0200
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RDATE:20181028T030000
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DTSTART:20170326T020000
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UID:www.bayceer.uni-bayreuth.de-bayceer-t140257id
DTSTAMP:20260805T124226Z
DESCRIPTION:When studying the earth’s surface\, we largely rely on surface 
 observations\, remote sensing\, and modeling\, which form a three-legged s
 tool. Each of these methods can only provide a partial confirmation of rea
 lity and requires the support of the other two. As part of this triad\, la
 nd models are a necessary tool for understanding the earth system\, yet mo
 dels are largely unconstrained: process representations vary between model
 s and parameter values are unknown. As a result\, when land models are int
 ercompared\, there is large divergence in simulated values\, eroding the v
 alue of one of the crucial tools for understanding the earth’s surface.\nW
 e demonstrate how observed surface temperature (Ts) can inform model evalu
 ation and development. Ts is the diagnostic variable of the modeled surfac
 e energy balance and is an ideal supplement to typical model evaluations\,
  which lack information on the surface energy balance. This study focuses 
 on modeling seasonal snow packs\, but many of the lessons learned are tran
 sferable to land modeling in general.\nUsing Ts\, we identify different ty
 pes of errors in the surface energy balance for future use in model develo
 pment and evaluation. Many of the modeled Ts responses are governed by fee
 dbacks between radiative and turbulent fluxes. Based on these results we r
 ecommend the inclusion of surface temperature observations in future studi
 es\, as these types of observations are cheap\, robust\, and provide criti
 cal missing information on the surface energy balance.
DTSTART;TZID=Europe/Berlin:20171130T120000
DTEND;TZID=Europe/Berlin:20171130T133000
SUMMARY:Dr. Karl Lapo\, Micrometeorology\, BayCEER\, University of Bayreuth
  (Homepage): Improving land models through the use of surface temperature 
 evaluations
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