Most megawatt-scale wind turbines align themselves into the wind as defined by the wind speed at or near the center of the rotor (hub height). However, both wind speed and wind direction can change with height across the area swept by the turbine blades. A turbine aligned to hub-height winds might experience suboptimal or superoptimal power production, depending on the changes in the vertical profile of wind, also known as shear. Using observed winds and power production over 6 months at a site in the high plains of North America, we quantify the sensitivity of a wind turbine's power production to wind speed shear and directional veer as well as atmospheric stability. We measure shear using metrics such as <
span class="inline-formula">
<
i>
?<
/i>
<
/span>
(the log-law wind shear exponent), <
span class="inline-formula">
<
i>
?<
/i>
<
sub>
bulk<
/sub>
<
/span>
(a measure of bulk rotor-disk-layer veer), <
span class="inline-formula">
<
i>
?<
/i>
<
sub>
total<
/sub>
<
/span>
(a measure of total rotor-disk-layer veer), and rotor-equivalent wind speed (REWS
a measure of actual momentum encountered by the turbine by accounting for shear). We also consider the REWS with the inclusion of directional veer, <
span class="inline-formula">
REWS<
sub>
<
i>
?<
/i>
<
/sub>
<
/span>
, although statistically significant differences in power production do not occur between REWS and <
span class="inline-formula">
REWS<
sub>
<
i>
?<
/i>
<
/sub>
<
/span>
at our site. When REWS differs from the hub-height wind speed (as measured by either the lidar or a transfer function-corrected nacelle anemometer), the turbine power generation also differs from the mean power curve in a statistically significant way. This change in power can be more than 70 <
span class="inline-formula">
kW<
/span>
or up to 5 % of the rated power for a single 1.5 <
span class="inline-formula">
MW<
/span>
utility-scale turbine. Over a theoretical 100-turbine wind farm, these changes could lead to instantaneous power prediction gains or losses equivalent to the addition or loss of multiple utility-scale turbines. At this site, REWS is the most useful metric for segregating the turbine's power curve into high and low cases of power production when compared to the other shear or stability metrics. Therefore, REWS enables improved forecasts of power production.