The evolving distribution of relative humidity conditional upon daily
maximum temperature in a warming climate
Abstract
The impacts of heat waves in a warming climate depend not just on
changing temperatures but also on changing humidity. Using 35
simulations from the Community Earth System Model Large Ensemble (CESM
LENS), we investigate the long-term evolution of the joint distribution
of summer relative humidity (RH) and daily maximum temperature () in
four U.S. cities (New York City, Chicago, Phoenix, New Orleans) under
the high-emissions Representative Concentration Pathway (RCP) 8.5. We
estimate the conditional quantiles of RH given by quantile regression
models, using functions of temperature for each month and city for three
time periods (1990-2005, 2026-2035, and 2071-2080). Quality of fit
diagnostics indicate that these models accurately estimate conditional
quantiles for each city. As expected, each quantile of increases from
1990-2005 to 2071-2080, while mean RH decreases modestly. For a fixed ,
the high quantiles of RH (and thus of heat index and dew point) increase
from 1990-2005 to 2071-2080 in all four cities. This result suggests
that the health impacts of a day of a given will increase in a warming
climate due to the increase of RH. Conditional upon a fixed quantile of
, the median and high quantiles of RH decrease, while those of heat
index and dew point both increase. This result suggests that, despite a
modest decrease in median relative humidity, heat stress impacts in a
warming climate will increase faster than temperatures alone would
indicate.