Karin van der Wiel, Sarah B. Kapnick, Gabriel A. Vecchi, William F Cooke, Thomas L Delworth, Liwei Jia, Hiroyuki Murakami, Seth Underwood, Fanrong Zeng. 2016. The resolution dependence of contiguous US precipitation extremes in response to CO forcing. Journal of Climate, doi:10.1175/JCLI-D-16-0307.1
Precipitation extremes have a widespread impact on societies and ecosystems; it is therefore important to understand current and future patterns of extreme precipitation. Here, a set of new global coupled climate models with varying atmospheric resolution has been used to investigate the ability of these models to reproduce observed patterns of precipitation extremes and to investigate changes in these extremes in response to increased atmospheric CO2 concentrations. The atmospheric resolution was increased from 2°×2° grid cells (typical resolution in the CMIP5 archive) to 0.25°×.25° (tropical cyclone-permitting). Analysis has been confined to the contiguous United States (CONUS). It is shown that, for these models, integrating at higher atmospheric resolution improves all aspects of simulated extreme precipitation: spatial patterns, intensities and seasonal timing. In response to 2×CO2concentrations, all models show a mean intensification of precipitation rates during extreme events of approximately 3-4% K−1. However, projected regional patterns of changes in extremes are dependent on model resolution. For example, the highest-resolution models show increased precipitation rates during extreme events in the hurricane season in the CONUS southeast, this increase is not found in the low-resolution model. These results emphasize that, for the study of extreme precipitation there is a minimum model resolution that is needed to capture the weather phenomena generating the extremes. Finally, the observed record and historical model experiments were used to investigate changes in the recent past. In part because of large intrinsic variability, no evidence was found for changes in extreme precipitation attributable to climate change in the available observed record.
Mallakpour, I. and Villarini, G. Analysis of changes in the magnitude, frequency, and seasonality of heavy precipitation over the contiguous USA
Theoretical and Applied Climatology (2016). doi:10.1007/s00704-016-1881-z
Gridded daily precipitation observations over the contiguous USA are used to investigate the past observed changes in the frequency and magnitude of heavy precipitation, and to examine its seasonality. Analyses are based on the Climate Prediction Center (CPC) daily precipitation data from 1948 to 2012. We use a block maxima approach to identify changes in the magnitude of heavy precipitation and a peak-over-threshold (POT) approach for the changes in the frequency. The results of this study show that there is a stronger signal of change in the frequency rather than in the magnitude of heavy precipitation events. Also, results show an increasing trend in the frequency of heavy precipitation over large areas of the contiguous USA with the most notable exception of the US Northwest. These results indicate that over the last 65 years, the stronger storms are not getting stronger, but a larger number of heavy precipitation events have been observed. The annual maximum precipitation and annual frequency of heavy precipitation reveal a marked seasonality over the contiguous USA. However, we could not find any evidence suggesting shifting in the seasonality of annual maximum precipitation by investigating whether the day of the year at which the maximum precipitation occurs has changed over time. Furthermore, we examine whether the year-to-year variations in the frequency and magnitude of heavy precipitation can be explained in terms of climate variability driven by the influence of the Atlantic and Pacific Oceans. Our findings indicate that the climate variability of both the Atlantic and Pacific Oceans can exert a large control on the precipitation frequency and magnitude over the contiguous USA. Also, the results indicate that part of the spatial and temporal features of the relationship between climate variability and heavy precipitation magnitude and frequency can be described by one or more of the climate indices considered here.
Climate models are known to be very poor predictors of precipitation.