Overpredicting temperature in the surface layer

Question

To whom it may concern

I'm having an issue where the model is over predicting surface temperatures by around 3°C within a month of simulation, there also seems to be too much heat penetrating into the hypolimnion. Looking at the results it seems to be the model is retaining too much heat which is have a culminative effect.

The forcing data is gathered on site, though longwave radiation is estimated from the other recorded weather, due to this atmospheric stability is assumed. Light extinction is based on secchi depth taken from the site. Otherwise, the model is, as far as I aware, using the basic model parameters. I've tired playing around a lot with the various parameters but to no avail.

Any help or suggestions would be appreciated

David

Answer 1

Hi David,

Atmospheric stability should only be switched on if the data collected in the lake within 2m of the surface.

Is there any nearby cloud data you could use instead of estimating longwave?

Are the WIND_SPEED_HEIGHT and  SCALAR_HEIGHT values correct for the measurements?

Do inflows have much impact on the thermal structure?

Chris

Comments

Hi Chris

Ah ok I'll turn that off.

Regrettably not really, there are a few nearby weather stations but those have only about four values for cloud cover (0 33%, 66%, 100%), which seemed to me to be less useful than estimation of longwave radiation.

WIND_SPEED_HEIGHT and SCALAR_HEIGHT values are correct.

We’ve not used inflows within the model, but I will include them.

I’ll try turning Atmospheric stability off and incorporating any inflows to see if model performance is improved.

Thanks for the very quick reply!

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Are you estimating LW_RAD_IN or LW_RAD_NET?

It would be best to use IN rather than NET and let the model calculate out.

I would try with measured cloud as well if turning off stability doesn't work

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We're estimating LW_RAD_IN  and thanks i'll try using the cloud cover as well.