Weather effects on Sunny F-16 rule

[debejyo]

<p>Hi Guys,<br /> I am planning to conduct a regression analysis on the variation from sunny F-16 rule as a function of weather. For this, I need a large volume of data and your contribution will be greatly appreciated.</p>

<p>On a clear sky day, take a typical picture with greens, and sky. On a clear sky, perfect visibility conditions, a metering on gray card (18%) will meter accurately to use the sunny f-16 rule (1/ISO seconds exposure at aperture f-16). Please note down the visibility from the internet of your location and report at f-16 what your shutter speed and ISO was. In other words, help me complete the table below:</p>

<table border="1">

<tbody>

<tr>

<td>visibility (%)</td>

<td>ISO or ASA</td>

<td>shutter speed (at aperture f-16) on 18% gray card in direct sunlight</td>

<td>distance of photographer from gray card</td>

</tr>

<tr>

<td>.</td>

<td>.</td>

<td>.</td>

<td>.</td>

</tr>

</tbody>

</table>

<p>Thanks, hope this is going to give us some information. I'll share my findings with all of you. Also, may be you can attach a picture that includes your gray card, with colorspace SRGB.</p>

[mark_sirota1]

<p>I don't understand what you're looking for here.</p>

<p>Sunny/16 works perfectly at EV 14.6439 (rounded) at ISO 100, which is when the illuminance is 69888 lux (again, rounded). It's not precisely 69888 lux in all "sunny" conditions, obviously.<br>

<br />What value are you expecting us to put in the "visibility" column?</p>

[richard_cochran]

<p>Maybe you're looking for the info that used to be included on the data sheet, packed with every roll of film?</p>

<p><img src="http://webs.lanset.com/rcochran/photonet/datasheet.gif" alt="" /></p>

<p>I find that this info is still pretty much accurate.</p>

[debejyo]

<p>Dear Mark Sirota,<br>

By visibility, I'm considering surface visibility as defined in http://www.weather.com/glossary/v.html (find the term here). For example, in Tempe, the visibility can be obtained from the weather.com page : http://www.wunderground.com/US/AZ/Tempe.html (look for visibility in the table on the left).<br>

I think I mislead you by putting '%' in the first column. It should have been distance (eg miles).<br>

Also, where can I find the illuminance information and the EV values? Do you know a document I can refer?<br>

Thanks.</p>

<p>TO Richard,<br>

Thanks for the table. Its surely very handy. However, my objective was to try to come up with a measure of estimating the exposure from the weather report data on visibility as described above.<br>

Thanks again for sharing the information.</p>

 

[andylynn]

<p>That seems like an overcomplicated way to work, and I don't think visibility correlates precisely to light levels. Visibility is haze at or near ground level. Light has more to do with time of day and cloud conditions.</p>

<p>There's an expanded version of a table like that at http://www.fredparker.com/ultexp1.htm - first read the part on Exposure Value because it explains the EV concept. Or just understand that Sunny 16 is at EV 15, so for each EV down from that you must make up the difference by adding one stop of shutter speed, aperture or film ISO.</p>

[mark_sirota1]

<p>And surface visibility doesn't mean much until you get to long distances. Are you only looking for data from photographs where the subject is at infinity?</p>

[mark_sirota1]

<p>And to answer your question, the Wikipedia entries on <a href="http://en.wikipedia.org/wiki/Lux">lux</a>, <a href="http://en.wikipedia.org/wiki/Illuminance">illuminance</a>, and <a href="http://en.wikipedia.org/wiki/Exposure_value">Exposure Value</a> are informative.</p>

[john_jennings2]

<p>Expand "weather" to include, time of day, season, and lattitude. The sun is hitting at different angles, depending on variables. But, for practical purposes, the old film data sheet that came from a roll of film is hard to beat.</p>

<p> </p>

[david_henderson]

<p>Regression analysis can be a very precise and useful tool. But it won't be if you don't control the variables, include those variables that account for the bulk of the variation you're seeking to explain, and the true meaning of the data you assemble. Seems to me that your brief has a number of shortcomings that will affect how many answers you get and the comparability of those answers. </p>