Procedure of iterations in estimation of Sensible Heat Flux in SEBAL?

I am stuck trying to figure out how to estimate this value.

According to the literature the Sensible heat flux (H) at the cold Pixel for Metric and Sebal Models is 

H=Rn-G-1.05λ ETr 

where Rn is net radiation (w/m2), G is soil heat flux (W/m2), λ is latent heat of vaporization (aprox. 2,264,760 J/Kg) and ET (mm/hr) is Penman Monteith reference evapotranspiration. My problem is that the value that I get is way too high because of the value of the latent heat of vaporization.

For the people that have worked with these kind of models, am I doing something wrong? I have compared my results with the SEBAL manual (appendix 8), and clearly there is something that isn't working as it should.

Regards

In each iteration, I get the same value of H for different values of aerodynamic resistance and the temperature difference between two heights. Do the results make sense? Is it necessary to adjust the air density value for each step?

Evapotranspiration estimation

Crop coefficients can be greater than 1.00.

Ex: Corn 1.15

Then ETa=Kc *ETo, it seems to be ETa greater than ETo.

But ETo is the evaporative power of the amosphere. is it possible to go over that value?

I am working on SEBAL algorithm by using Landsat images in order to calculate evapotranspiration. i should find cold and hot pixels but I don't know how i can work out a and b in the said equation and of course sensible heat flux.

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I downloaded the latent heat flux from fluxnet, the latent heat flux is per hour in W m-2. I summed each value per hour of the day to get the daily sum.

Now I have the daily sum of latent heat flux in W m-2 and want to daily evapotranspiration in mm.

You can calculate this with the formula ET= λ LE/λ. First you calculate the heat of vaporization; λ = 2.501 – (2.361 x 10^-3) x Ta. Where Ta is temperature air in celcius, I also have this daily data.

My calculations in my code (df stands just for dataframe and double ** is ^):

df['heat_of_vaporization'] = 2.501-(2.361*10**-3)*df['TA_daily_average']

df['ET'] = df['LE_daily_sum']/(df['heat_of_evaporation']*1000 *1000)*3600

Is the calculation right? It think I get the good data. I did * 3600 because of the seconds in an hour, added all the hours so not 3600*24 I think. Are the *1000 *1000 also right?

Thanks a lot!

I have computed the evapotranspiration in MATLAB using the FAO PM method and found negative values especially in January month. The study site was in Sicily, Italy ( very rare for snow and uncommon the temperature less than 0 degree temperature) Could yo suggest me why the value is negative, please?