Nathalie Schaller

Impact of hindcast length on estimates of seasonal climate predictability

It has recently been argued that single-model seasonal forecast ensembles are overdispersive, implying that the real world is more predictable than indicated by estimates of so-called perfect model predictability, particularly over the North Atlantic. However, such estimates are based on relatively short forecast data sets comprising just 20 years of seasonal predictions. Here we study longer 40 year seasonal forecast data sets from multimodel seasonal forecast ensemble projects and show that sampling uncertainty due to the length of the hindcast periods is large. The skill of forecasting the North Atlantic Oscillation during winter varies within the 40 year data sets with high levels of skill found for some subperiods. It is demonstrated that while 20 year estimates of seasonal reliability can show evidence of overdispersive behavior, the 40 year estimates are more stable and show no evidence of overdispersion. Instead, the predominant feature on these longer time scales is underdispersion, particularly in the tropics. Key Points Predictions can appear overdispersive due to hindcast length sampling error Longer hindcasts are more robust and underdispersive, especially in the tropics Twenty hindcasts are an inadequate sample size to assess seasonal forecast skill

Atmospheric seasonal forecasts of the twentieth century: multi-decadal variability in predictive skill of the winter North Atlantic Oscillation (NAO) and their potential value for extreme event attribution

Based on skill estimates from hindcasts made over the last couple of decades, recent studies have suggested that considerable success has been achieved in forecasting winter climate anomalies over the Euro‐Atlantic area using current‐generation dynamical forecast models. However, previous‐generation models had shown that forecasts of winter climate anomalies in the 1960s and 1970s were less successful than forecasts of the 1980s and 1990s. Given that the more recent decades have been dominated by the North Atlantic Oscillation (NAO) in its positive phase, it is important to know whether the performance of current models would be similarly skilful when tested over periods of a predominantly negative NAO. To this end, a new ensemble of atmospheric seasonal hindcasts covering the period 1900–2009 has been created, providing a unique tool to explore many aspects of atmospheric seasonal climate prediction. In this study we focus on two of these: multi‐decadal variability in predicting the winter NAO, and the potential value of the long seasonal hindcast datasets for the emerging science of probabilistic event attribution. The existence of relatively low skill levels during the period 1950s–1970s has been confirmed in the new dataset. The skill of the NAO forecasts is larger, however, in earlier and later periods. Whilst these inter‐decadal differences in skill are, by themselves, only marginally statistically significant, the variations in skill strongly co‐vary with statistics of the general circulation itself suggesting that such differences are indeed physically based. The mid‐century period of low forecast skill coincides with a negative NAO phase but the relationship between the NAO phase/amplitude and forecast skill is more complex than linear. Finally, we show how seasonal forecast reliability can be of importance for increasing confidence in statements of causes of extreme weather and climate events, including effects of anthropogenic climate change.

Multiannual Ocean–Atmosphere Adjustments to Radiative Forcing

AbstractIn radiative forcing and climate feedback frameworks, the initial stratospheric and tropospheric adjustments to a forcing agent can be treated as part of the forcing and not as a feedback, as long as the average global surface temperature response is negligible. Here, a very large initial condition ensemble of the Community Earth System Model is used to analyze how the ocean shapes the fast response to radiative forcing. It is shown that not only the stratosphere and troposphere but also the ocean adjusts. This oceanic adjustment includes meridional ocean heat transport convergence anomalies, which are locally as large as the surface heat flux anomalies, and an increase of the Atlantic meridional overturning circulation. These oceanic adjustments set the lower boundary condition for the atmospheric response of the first few years, in particular, the shortwave cloud radiative effect. This cloud adjustment causes a nonlinear relationship between global energy imbalance and temperature. It proceeds w...

The asymmetry of the climate system's response to solar forcing changes and its implications for geoengineering scenarios

Motivated by proposals to compensate CO2-induced warming with a decrease in solar radiation, this study investigates how single-forcing simulations should be combined to best represent the spatial patterns of surface temperature and precipitation of idealized geoengineering scenarios. Using instantaneous and transient simulations with changing CO2 and solar forcings, we show that a geoengineering scenario, i.e., a scenario where the solar constant is reduced as CO2 concentrations are increased, is better represented by subtracting the response pattern of a solar forcing increase simulation from the response pattern of a CO2 forcing increase simulation, than by adding the response pattern of a solar forcing decrease simulation to a CO2 forcing increase simulation. The reason is a asymmetric response of the climate system to a forcing increase or decrease between both hemispheres. In particular, the Atlantic meridional overturning circulation responds faster to a solar forcing decrease compared to a solar forcing increase. Further, the climate feedbacks are state and region dependent, which is particularly apparent in the polar regions due to the sea ice-albedo feedback. The importance of understanding the local response of the climate system to geoengineering and single-forcing scenarios is highlighted, since these aspects are hardly discernible when only global mean values are considered.

Real-time extreme weather event attribution with forecast seasonal SSTs

Within the last decade, extreme weather event attribution has emerged as a new field of science and garnered increasing attention from the wider scientific community and the public. Numerous methods have been put forward to determine the contribution of anthropogenic climate change to individual extreme weather events. So far nearly all such analyses were done months after an event has happened. Here we present a new method which can assess the fraction of attributable risk of a severe weather event due to an external driver in real-time. The method builds on a large ensemble of atmosphere-only general circulation model simulations forced by seasonal forecast sea surface temperatures (SSTs). Taking the England 2013/14 winter floods as an example, we demonstrate that the change in risk for heavy rainfall during the England floods due to anthropogenic climate change, is of similar magnitude using either observed or seasonal forecast SSTs. Testing the dynamic response of the model to the anomalous ocean state for January 2014, we find that observed SSTs are required to establish a discernible link between a particular SST pattern and an atmospheric response such as a shift in the jetstream in the model. For extreme events occurring under strongly anomalous SST patterns associated with known low-frequency climate modes, however, forecast SSTs can provide sufficient guidance to determine the dynamic contribution to the event.

Dependence of Present and Future European Temperature Extremes on the Location of Atmospheric Blocking

Abstract The impact of atmospheric blocking on European heat waves (HWs) and cold spells (CSs) is investigated for present and future conditions . A 50‐member ensemble of the second generation Canadian Earth System Model is used to quantify the role of internal variability in the response to blocking. We find that the present blocking‐extreme temperature link is well represented compared to ERA‐Interim, despite a significant underestimation of blocking frequency in most ensemble members. Our results show a strong correlation of blocking with northern European HWs in summer, spring, and fall. However, we also find a strong anticorrelation between blocking and HW occurrence in southern Europe in all seasons. Blocking increases the CS frequency particularly in southern Europe in fall, winter, and spring but reduces it in summer. For the future we find that blocking will continue to play an important role in the development of both CSs and HWs in all seasons.

Extreme heat-related mortality avoided under Paris Agreement goals

In key European cities, stabilizing climate warming at 1.5 °C would decrease extreme heat-related mortality by 15–22% per summer compared with stabilization at 2 °C.

Ensemble of European regional climate simulations for the winter of 2013 and 2014 from HadAM3P-RM3P

Large data sets used to study the impact of anthropogenic climate change on the 2013/14 floods in the UK are provided. The data consist of perturbed initial conditions simulations using the Weather@Home regional climate modelling framework. Two different base conditions, Actual, including atmospheric conditions (anthropogenic greenhouse gases and human induced aerosols) as at present and Natural, with these forcings all removed are available. The data set is made up of 13 different ensembles (2 actual and 11 natural) with each having more than 7500 members. The data is available as NetCDF V3 files representing monthly data within the period of interest (1st Dec 2013 to 15th February 2014) for both a specified European region at a 50 km horizontal resolution and globally at N96 resolution. The data is stored within the UK Natural and Environmental Research Council Centre for Environmental Data Analysis repository.