Wednesday, October 26, 2011

6.2 - Evaporation model

1. As we have seen, our model of evaporation seems to produce less variability than the data (compare Evap_M and Hyd_evap_calc). Try to tweak the model parameters to increase the variability in model output.
All I did here was to augment the effect of cloudiness, and that seems to have brought the model's variability in line with the recorded data's. I changed SolRadGr from SolRad*(1-0.5*cloudy) to SolRad*(1-0.12*cloudy).

2. Check out the sensitivity of the model to changes in the parameter that describes the effect of cloudiness. What happens if the effect of clouds is increased quite dramatically (say, tripled)? How can we avoid some of the unrealistic behavior in the model that we observe in this case? 

By multiplying the parameter "cloudy" by three, we get hyper-dominance of cloudiness, such that on rather cloudy days, there's no evaporation:

We can avoid this behavior by not tripling the cloudy parameter. Just kidding. I think what he wants us to get at here is that by augmenting the effect of cloudiness within the SolRadGr function (as I did above), rather than augmenting the cloudy parameter itself, we can avoid the unrealistic behavior.

3. What is more important for the rate of evaporation: the latitude of the site, or the climatic conditions? What changes in climate can compensate the effect of the latitude and vice versa? 

Latitude has a relatively minor effect on evaopration:

LatDeg = 20 (model's minimum, in the tropics)

LatDeg = 64 (model's maximum, in the arctic)

On the other hand, we can see from the inter-dial and inter-seasonal variation that climatic conditions  exert a strong effect on evaporation. Although the following graph is crowded, it shows that air temperature is the primary driver of evaporation:

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