Abstract. A methodology for estimating and downscaling the probability associated with
the duration of heatwaves is presented and applied as a case study for Indian
wheat crops. These probability estimates make use of empirical-statistical
downscaling and statistical modelling of probability of occurrence and streak
length statistics, and we present projections based on large multi-model
ensembles of global climate models from the Coupled Model Intercomparison
Project Phase 5 and three different emissions scenarios: Representative Concentration Pathways (RCPs) 2.6, 4.5, and
8.5. Our objective was to estimate the probabilities for heatwaves with more
than 5 consecutive days with daily maximum temperature above
35 ∘C, which represent a condition that limits wheat yields. Such
heatwaves are already quite frequent under current climate conditions, and downscaled
estimates of the probability of occurrence in 2010 is in the range of
20 %–84 % depending on the location. For the year 2100, the
high-emission scenario RCP8.5 suggests more frequent occurrences, with a
probability in the range of 36 %–88 %. Our results also point to
increased probabilities for a hot day to turn into a heatwave lasting more
than 5 days, from roughly 8 %–20 % at present to
9 %–23 % in 2100 assuming future emissions according to the RCP8.5
scenario; however, these estimates were to a greater extent subject to
systematic biases. We also demonstrate a downscaling methodology based on
principal component analysis that can produce reasonable results even when
the data are sparse with variable quality.