32 knots in meters per second

Conversion

32 knots is equivalent to 16.4622222222222 meters per second.^[1]

Conversion in the opposite direction

The inverse of the conversion factor is that 1 meter per second is equal to 0.0607451403887689 times 32 knots.

It can also be expressed as: 32 knots is equal to $\frac{1}{0.0607451403887689}$ meters per second.

Approximation

An approximate numerical result would be: thirty-two knots is about sixteen point four six meters per second, or alternatively, a meter per second is about zero point zero six times thirty-two knots.

Units involved

This is how the units in this conversion are defined:

Knots

"The knot (/nɒt/) is a unit of speed equal to one nautical mile (1.852 km) per hour, approximately 1.151 mph. The ISO Standard symbol for the knot is kn. The same symbol is preferred by the IEEE; kt is also common. The knot is a non-SI unit that is accepted for use with the SI. Worldwide, the knot is used in meteorology, and in maritime and air navigation—for example, a vessel travelling at 1 knot along a meridian travels approximately one minute of geographic latitude in one hour. Etymologically, the term derives from counting the number of knots in the line that unspooled from the reel of a chip log in a specific time."

Wikipedia page of knots

Meters Per Second

"Meter per second is an SI derived unit of both speed (scalar) and velocity (vector quantity which specifies both magnitude and a specific direction), defined by distance in metres divided by time in seconds.The SI unit symbols are m·s−1, m s−1, m/s, or m/s, sometimes (unofficially) abbreviated as mps. Where metres per second are several orders of magnitude too slow to be convenient, such as in astronomical measurements, velocities may be given in kilometres per second, where 1 km/s is 1000 metres per second, sometimes unofficially abbreviated as kps."

Wikipedia page of meters per second

Footnotes

[1] The precision is 15 significant digits (fourteen digits to the right of the decimal point).

Results may contain small errors due to the use of floating point arithmetic.