不会被任何冬季降水专家拉伸(我们在佛罗里达避免这样的愚蠢!),我认为关键可能是“* *湿度很低(40%)* *”部分。当冬季降水通过热空气,它加热的空气。但如果空气干燥,一些外边缘的降水会融化\升华,从而冷却片,并帮助它存活更长时间。http://www.sciencebits.com/SnowAboveFreezing似乎有一个很伟大的有关细节的详细页面。有时它可能是温暖的层就像只有几百英尺,所以确实没有花长下降通过这一层。当然降水在寒冷的温度下开始给它一个小垫子。低导电性和高比热容是很重要的。但升华热超过10倍的比热容,显示,失去一个小冰表面上可以抵消相当多的温暖。<人力资源>然而重要的是要注意,即使如此,计算器Sciencebits网站上并没有给予任何希望的雪在你给的温度和湿度。但是不远了(30%和7°C或40%和6°C,你会开始变得值)。 It's quite reasonable that there would be some degree of error in the values you're getting from their site, most likely due to elevation or older data. Many sites will give the reading at the closest weather station, which may be at a different elevation or even in a different airmass on occasion. And weather observations are usually updated once an hour, so they may not reflect the changes since then. Even if their site employs a weighted average of nearby temperatures to try to better approximate yours, as many apps do, this won't include elevation effects on temperature. And if they employ a finer resolution of analysis such as using [weather models][1] to fill in the gaps and estimate for your location, the resolution (and initial data) is often still poor enough to not match entirely. Plus temperature often naturally varies by a couple degrees over local areas anyways, with a similar spread in humidity, so unless the observation site is right where you're at, expect your values may differ slightly! A very high lapse rate would likely have deep convection, and is more connected with large hail and lightning\severe weather than with shallow mediocris snow suggesting limited vertical development, so I'm tending to doubt that has too much bearing. [1]: https://www.pivotalweather.com/model.php?fh=loop&dpdt=&mc=&r=uk&p=sfct_b&m=gfs