Impact of dust radiative forcing in snow on accuracy of operational runoff prediction in the Upper Colorado River Basin

Accurate prediction of snowmelt runoff is critical in the US Intermountain West, where water demand is increasing and snow patterns are shifting. Here, we show that errors in the National Weather Service Colorado Basin River Forecast Center's operational streamflow predictions are correlated with the interannual variability of dust radiative forcing in snow. With data from 2000–2010, we show that errors in snowmelt period streamflow prediction for the southern Colorado Rockies are linearly related to melt period dust radiative forcing in snow as inferred from NASA Moderate Resolution Imaging Spectroradiometer data, which ranged interannually from 20 to 80 W m−2. Each 10 W m−2 change of melt period dust forcing resulted in a corresponding change in runoff prediction bias of 10.0% ± 1.5% and a 1.5 ± 0.6 day shift in runoff center of mass. Accounting for bias introduced by dust forcing could improve streamflow prediction in regions prone to dust deposition in the snowpack. Key Points Streamflow prediction errors are related to dust radiative forcing in snow Percent bias in predicted streamflow increased by 0.9% per W m‐2 dust forcing MODDRFS data could reduce prediction error in dust‐affected snowmelt systems