The amplitude of decadal to multidecadal variability in precipitation simulated by state‐of‐the‐art climate models

Abstract

[1] We assess the magnitude of decadal to multidecadal (D2M) variability in Climate Model Intercomparison Project 5 (CMIP5) simulations that will be used to understand, and plan for, climate change as part of the Intergovernmental Panel on Climate Change's 5th Assessment Report. Model performance on D2M timescales is evaluated using metrics designed to characterize the relative and absolute magnitude of variability at these frequencies. In observational data, we find that between 10% and 35% of the total variance occurs on D2M timescales. Regions characterized by the high end of this range include Africa, Australia, western North America, and the Amazon region of South America. In these areas D2M fluctuations are especially prominent and linked to prolonged drought. D2M fluctuations account for considerably less of the total variance (between 5% and 15%) in the CMIP5 archive of historical (1850-2005) simulations. The discrepancy between observation and model based estimates of D2M prominence reflects two features of the CMIP5 archive. First, interannual components of variability are generally too energetic. Second, decadal components are too weak in several key regions. Our findings imply that projections of the future lack sufficient decadal variability, presenting a limited view of prolonged drought and pluvial risk. Citation: Ault, T. R., J. E. Cole, and S. St. George (2012),The amplitude of decadal to multidecadal variability in precipitation simulated by state-of-the-art climate models, Geophys. Res.

A large set of potential past, present and future hydro-meteorological time series for the UK

“…In addition, the application of a bias-correction technique to climate model output cannot correct for interannual to decadal climate variability, which is known to be poorly captured in current stateof-the-art climate models (e.g. Ault et al, 2012). This issue could potentially lead to an underestimation of the risk of multi-decadal droughts (Ault et al, 2014).…”

“…These results are encouraging for the MaRIUS project, as they suggest that the dataset may well represent precipitation accumulation over a long time period, which is the most critical aspect to British droughts. Noteworthy is a small overestimation of dryness at rare fre- quencies for long accumulation times (2 to 4 years), not present in the 1-year accumulated values, which suggests that in this case the climate model overestimates long-term precipitation persistence, unlike what has been shown for longer accumulation times (Ault et al, 2012). The next section goes into further details through validation on the regional scale.…”

“…Nonetheless, even in those cases there are individual time series which look similar to the CEH-GEAR dataset, suggesting that natural variability could explain some of those apparent biases. The difficulty for climate models to represent low-frequency variability (Ault et al, 2012), an aspect that is by definition not improved by bias correction, could also play a role in this feature. While short droughts do not usually pose a serious threat to Great Britain, prolonged periods of drought (e.g.…”

“…representation of UK-scale dynamical systems and thermodynamic processes, Schaller et al, 2016) but has more difficulties in representing longer-term persistence -a common feature of climate models (e.g. Ault et al, 2012). Therefore, we recommend the application of another bias-correction technique (e.g.…”

Persistent drying in the tropics linked to natural forcing

“…The discrepancy between our reconstruction and the simulations can be ascribed to general deficiencies still affecting the simulated representation of key chemical and physical processes related to aerosol forcing, and to the consequent large uncertainties in the simulated climate response to volcanic forcing 25,36 . Further possible explanations are the common model deficiencies concerning regional precipitation variability at the decadal and multi-decadal time ARTICLE scales 37 , which are linked to poor and hence less robustly simulated representation of dominant modes of large-scale climate variability and associated teleconnections including ENSO 38 and the AMO 39 . Large uncertainties also affect the reconstructed forcing 40 and we have very limited knowledge about the background climate conditions at the time of volcanic eruptions that occurred before the last half of the twentieth century 30 .…”