If I am looking for a day lighting analysis at a specific time; I believe DIVA gives me two options to do this.  The first is a point-in-time illuminance and the second is a grid based climate analysis using a modified schedule.  I'm wondering which of these two options will work better?  Will I lose accuracy using the point-in-time analysis or will the edited schedule take longer to compute?

I'll look forward to your recommendations.


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Hi Chris,

The climate-based methods use actual weather data where each month is the median month in some larger (~30 year) dataset. So for your specific time, using that method, might be super sunny, it might be overcast, it might be partly cloudy. Its as random as the weather, and the climate-based methodology really works well for an entire year where these random weather events become representative of the climate as a whole.

Using the point in time methods, you could choose a clear sky or an overcast sky depending on the condition you are trying to address (or run both). If you are trying to reproduce a /real/ daylit condition, its best to try to come by measured irradiance data from a weather station and use that as a seed to the so-called "Perez Sky" model via DIVA.

I recommend to not use the climate-based method for a single point in time for another reason too. There is a geometric loss of accuracy in the position of the sun (its interpolated from ~65 representative solar positions).

Best regards,


So does this mean if you had a climate based anaylsis that picked sunny and had point in time with sunny, that the two answers would not actually be the same (assuming they had the same weather .. which I know is a stretch from your response above)?

Hi Renna,

I'd expect them to be somewhat close, but not identical. Here is a pretty sunny sky definition from the Boston, MA, USA weather file.

> 7 15 10.500      863 131

That's 863 Wm-2 direct normal solar irrad and 131 Wm-2 diffuse horizontal solar irrad. on July 15th at 10:30. The 'clear sky' point in time simulations are based on an ideal model, not explicit measured data. To compare (and this is fun, because I've never made this comparison before), we can look at total illuminance on a horizontal unshaded plane from this model and the CIE clear sky ideal model.

"Perez" sky with measured weather data: 96,581 lx

CIE clear sky: 76,791 lx

So actually about a 20,000 lx difference. So indeed its not a perfect model. The clear sky model has a default 'turbidity' value of 2.45, which is possibly too high for this day in Boston.


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