Negative Values of Moisture -------- ------ -- -------- The relative humidity can have negative values and values greater than 100%. Some causes are: Gibb's Phenomenon The Reanalysis forecast model is spectral with a quadratic grid. This means that quadratic quantities can be calculated exactly for the resolved spherical harmonics. This is considered important as this helps preserve kinetic energy in a adiabatic model. One drawback of the quadratic grid is that it is prone to "Gibb-ing". Sharp gradients gradients tend to produce "over-shoots" or "ringing" after a transformation from grid to spectral and back to the grid representations. It is not uncommon to have negative humidity in regions of large moisture gradients. Humidity Advection Traditionally GCMs use a time step which is slightly shorter than what would cause an instability. It is possible that a too large time step could cause an overestimate of |dq/dt| from the moisture advection term in regions of a large gradient. Finite Precision of Grib GRIB data has a finite precision and the precision for specific humidity was set at a too low value. During winter over the polar regions, saturated q may have, for example, a value of 0.28 g/kg. In converting to GRIB, the moisture is converted to the nearest 0.1 g/kg. Thus it possible for the GRIB file to have a value of 0.3 g/kg which would be super-saturated. This quantization also plays havoc with the variance estimates. Effects of Negative Humidity (1) Radiation code uses RH = 0 whenever RH < 0 (2) pressure level data: 0 <= RH <= 100 (3) precipitable water uses negative RH to preserve water budget