Estimating climate extreme indices and the related uncertainties using U.S. Climate Reference Network (USCRN) near-surface temperatures.

Changes in the frequency of temperature extremes are often attributed to global warming. The availability of near-surface temperature records from reference networks enables the quantification of measurement uncertainties. In this communication, four climate extreme indices (Frost Days, Summer Days, Ice Days, Tropical Nights) and the related uncertainties are calculated for the period 2006--2020 from U.S. Climate Reference Network (USCRN) and compared with traditional indices. Moreover, the asymmetric USCRN uncertainties are propagated to estimate the uncertainties of climate indices. The result shows expanded uncertainties homogeneously distributed with the latitude. Positive uncertainties are larger than negative ones for all the indices. The values of Frost Days and Ice Days with the related uncertainties for USCRN have also been compared with the corresponding values calculated from reanalysis data, showing differences within 60 days for median values, quite often smaller than USCRN and inconsistent within the related uncertainties. Overall, the results show that USCRN measurement uncertainties increase confidence in the estimation of climate extreme indices and decisions for adaptation.