Sensitivity Analysis of an Off-the-Shelf Land Surface Model
Changes in land surface energy fluxes, due to different land cover types, can induce changes in local weather patterns. Surface meteorological conditions are influenced in large part by the land-surface boundary. Therefore, land surface heat and water fluxes are important input components to meteorological models used to predict weather and climate. The land surface model (LSM) used in this project is called Noah. Noah is an off-the-shelf open source model
Knowing the sensitivity of Noah to each input parameter (wind speed, air temperature, solar radiation, downwelling longwave radiation, pressure, humidity, albedo, and vegetation fraction) allows for proper allocation of resources in acquiring input parameter data. This results in a more cost-effective method to calibrate and validate the land surface model.
Materials and Methods
For each simulation, one input variable was modified using set intervals while keeping the rest of the variables constant. Noah’s output variables were then compared with input variables to assess the model’s degree of sensitivity to each input variable. This process was repeated for all 8 input variables resulting in 111 simulations.
Conclusions
• The results presented here allows one to derive empirical equations relating Noah’s sensitivity of the state variables to the input variables.
• The empirical equations could then be used to assess required input precision given needed output accuracy.
Author: Chinedu T.J. Ekwueme, Ecology Emphasis Group, SLSTP Trainee 2004
Norfolk State University
Principal Investigator: Manuel Gimond, Dynamac Corporation
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