Sjoukje Philip

Significant atmospheric nonlinearities in the ENSO cycle.

Abstract The nonlinearities that cause El Nino events to deviate more from the mean state than La Nina events are still not completely understood. This paper investigates the contribution of one candidate mechanism: ENSO nonlinearities originating from the atmosphere. The initially linear intermediate complexity model of the equatorial Pacific Ocean, in which all couplings were fitted to observations, describes the ENSO cycle reasonably well. In this linear model, extra terms are systematically introduced in the atmospheric component: the nonlinear response of mean wind stress to SST anomalies, the skewness of the driving noise term in the atmosphere, and the relation of this noise term to the background SST or the ENSO phase. The nonlinear response of mean wind stress to SST in the ENSO region is found to be the dominant term influencing the ENSO cycle. However, this influence is only visible when noise fields are used that are fitted to observed patterns of prescribed standard deviation and spatial deco...

Climate change increases the probability of heavy rains in Northern England/Southern Scotland like those of storm Desmond—a real-time event attribution revisited

On 4–6 December 2015, storm Desmond caused very heavy rainfall in Northern England and Southern Scotland which led to widespread flooding. A week after the event we provided an initial assessment of the influence of anthropogenic climate change on the likelihood of one-day precipitation events averaged over an area encompassing Northern England and Southern Scotland using data and methods available immediately after the event occurred. The analysis was based on three independent methods of extreme event attribution: historical observed trends, coupled climate model simulations and a large ensemble of regional model simulations. All three methods agreed that the effect of climate change was positive, making precipitation events like this about 40% more likely, with a provisional 2.5%–97.5% confidence interval of 5%–80%. Here we revisit the assessment using more station data, an additional monthly event definition, a second global climate model and regional model simulations of winter 2015/16. The overall result of the analysis is similar to the real-time analysis with a best estimate of a 59% increase in event frequency, but a larger confidence interval that does include no change. It is important to highlight that the observational data in the additional monthly analysis does not only represent the rainfall associated with storm Desmond but also that of storms Eve and Frank occurring towards the end of the month.

Western US high June 2015 temperatures and their relation to global warming and soil moisture

The Western US states Washington (WA), Oregon (OR) and California (CA) experienced extremely high temperatures in June 2015. The temperature anomalies were so extreme that they cannot be explained with global warming alone. We investigate the hypothesis that soil moisture played an important role as well. We use a land surface model and a large ensemble from the weather@home modelling effort to investigate the coupling between soil moisture and temperature in a warming world. Both models show that May was anomalously dry, satisfying a prerequisite for the extreme heat wave, and they indicate that WA and OR are in a wet-to-dry transitional soil moisture regime. We use two different land surface–atmosphere coupling metrics to show that there was strong coupling between temperature, latent heat flux and the effect of soil moisture deficits on the energy balance in June 2015 in WA and OR. June temperature anomalies conditioned on wet/dry conditions show that both the mean and extreme temperatures become hotter for dry soils, especially in WA and OR. Fitting a Gaussian model to temperatures using soil moisture as a covariate shows that the June 2015 temperature values fit well in the extrapolated empirical temperature/drought lines. The high temperature anomalies in WA and OR are thus to be expected, given the dry soil moisture conditions and that those regions are in the transition from a wet to a dry regime. CA is already in the dry regime and therefore the necessity of taking soil moisture into account is of lower importance.