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Hi, I have been struggling to get the attached formula to calculate correctly in Excel - I'm sure its dumbo issue - any help is much appreciated :-) The aim is to use a temperature value (C) and a Relative Humidity value (%) to give Dew Point Temperature. For example: T RH Dew 17.38 66.54 11.08
I am using the below formula but it gives wrong values in Fahrenheit unit. float Temp = [value floatValue]; float Humi = [[data humidity] floatValue]; float Td = Temp - ((100 - Humi)/3.6); return Td; I have the temperature (°C or °F) and humidity and need help in formula to calculate dew point in objective C.
"Computation of Vapour pressure, dew point and relative humidity from dry-and wet-bulb temperatures" by G.P.Sargent, was published in Meteorological Magazine, 109, 1980. Written in the days of programmable calculators, it gives all the formulae needed, and I did write my own routine for a Casio fx-7000G calculator.
This is the correct formula. The e(Td) and e(T) represent the actual vapor pressure and the saturation vapor pressure respectively. To calcualte the vapor pressure from temperature they use the following formula: e(T) = 6.112 e^(17.67T/(T + 243.5)) where T is the temperature in degree celsius.
I am trying to write a code to calculate the dew point. My code works, but the formula I was using was too simple and I wasn't able to get an accurate answer. I found a more advanced formula, which is quite lengthy, and it includes a few exponents.
Everything inside of a function, including comments, needs indented... def calc_wind_chill(f_temp, wind_speed): """ float, float -> float returns wind_chill_temperature (F) given farenheit temperature and wind_speed in miles per hour """ velocity = wind_speed ** 0.16 chill = 35.74 + (0.6215 * f_temp)-(35.75 * velocity) +(0.4275 * f_temp * velocity) return chill
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There is no free lunch though, this won't work at boundary UTM zones where each point lays on different UTM zone. Here are some test results, GcDistance uses the Haverstine formula, the test distance where generated with GeographicLib at 1,2,3,5,10,20,and 40 meters from point 100:
@stallingOne Good point, I shouldn't have included negative values in the example, I might change that later. Just for reference for people reading this, you don't need to create a custom divergent cmap with seaborn (although the one in the comment above looks pretty slick), you can also use the built-in divergent cmaps from matplotlib, e.g ...
p1 = longitude/latitude for point(s) p2 = longitude/latitude for point(s) # type of distance calculation fun = distCosine / distHaversine / distVincentySphere / distVincentyEllipsoid As the earth is not perfectly spherical, the Vincenty formula for ellipsoids is probably the best way to calculate distances.