Showing papers by "Viatcheslav Kharin published in 2017"

Half a degree additional warming, prognosis and projected impacts (HAPPI): background and experimental design

Abstract: . The Intergovernmental Panel on Climate Change (IPCC) has accepted the invitation from the UNFCCC to provide a special report on the impacts of global warming of 1.5 °C above pre-industrial levels and on related global greenhouse-gas emission pathways. Many current experiments in, for example, the Coupled Model Inter-comparison Project (CMIP), are not specifically designed for informing this report. Here, we document the design of the half a degree additional warming, projections, prognosis and impacts (HAPPI) experiment. HAPPI provides a framework for the generation of climate data describing how the climate, and in particular extreme weather, might differ from the present day in worlds that are 1.5 and 2.0 °C warmer than pre-industrial conditions. Output from participating climate models includes variables frequently used by a range of impact models. The key challenge is to separate the impact of an additional approximately half degree of warming from uncertainty in climate model responses and internal climate variability that dominate CMIP-style experiments under low-emission scenarios. Large ensembles of simulations (> 50 members) of atmosphere-only models for three time slices are proposed, each a decade in length: the first being the most recent observed 10-year period (2006–2015), the second two being estimates of a similar decade but under 1.5 and 2 °C conditions a century in the future. We use the representative concentration pathway 2.6 (RCP2.6) to provide the model boundary conditions for the 1.5 °C scenario, and a weighted combination of RCP2.6 and RCP4.5 for the 2 °C scenario.

Rapid adjustments cause weak surface temperature response to increased black carbon concentrations

Abstract: We investigate the climate response to increased concentrations of black carbon (BC), as part of the Precipitation Driver Response Model Intercomparison Project (PDRMIP). A tenfold increase in BC is simulated by nine global coupled‐climate models, producing a model median effective radiative forcing of 0.82 (ranging from 0.41 to 2.91) W m⁻², and a warming of 0.67 (0.16 to 1.66) K globally and 1.24 (0.26 to 4.31) K in the Arctic. A strong positive instantaneous radiative forcing (median of 2.10 W m⁻² based on five of the models) is countered by negative rapid adjustments (−0.64 W m⁻² for the same five models), which dampen the total surface temperature signal. Unlike other drivers of climate change, the response of temperature and cloud profiles to the BC forcing is dominated by rapid adjustments. Low‐level cloud amounts increase for all models, while higher‐level clouds are diminished. The rapid temperature response is particularly strong above 400 hPa, where increased atmospheric stabilization and reduced cloud cover contrast the response pattern of the other drivers. In conclusion, we find that this substantial increase in BC concentrations does have considerable impacts on important aspects of the climate system. However, some of these effects tend to offset one another, leaving a relatively small median global warming of 0.47 K per W m⁻²—about 20% lower than the response to a doubling of CO₂. Translating the tenfold increase in BC to the present‐day impact of anthropogenic BC (given the emissions used in this work) would leave a warming of merely 0.07 K.

PDRMIP: A Precipitation Driver and Response Model Intercomparison Project, Protocol and preliminary results.

Abstract: As the global temperature increases with changing climate, precipitation rates and patterns are affected through a wide range of physical mechanisms. The globally averaged intensity of extreme precipitation also changes more rapidly than the globally averaged precipitation rate. While some aspects of the regional variation in precipitation predicted by climate models appear robust, there is still a large degree of inter-model differences unaccounted for. Individual drivers of climate change initially alter the energy budget of the atmosphere leading to distinct rapid adjustments involving changes in precipitation. Differences in how these rapid adjustment processes manifest themselves within models are likely to explain a large fraction of the present model spread and needs better quantifications to improve precipitation predictions. Here, we introduce the Precipitation Driver and Response Model Intercomparison Project (PDRMIP), where a set of idealized experiments designed to understand the role of different climate forcing mechanisms were performed by a large set of climate models. PDRMIP focuses on understanding how precipitation changes relating to rapid adjustments and slower responses to climate forcings are represented across models. Initial results show that rapid adjustments account for large regional differences in hydrological sensitivity across multiple drivers. The PDRMIP results are expected to dramatically improve our understanding of the causes of the present diversity in future climate projections.

Remarkable separability of circulation response to Arctic sea ice loss and greenhouse gas forcing

Abstract: Arctic sea ice loss may influence midlatitude climate by changing large-scale circulation. The extent to which climate change can be understood as greenhouse gas-induced changes that are modulated by this loss depends on how additive the responses to the separate influences are. A novel sea ice nudging methodology in a fully coupled climate model reveals that the separate effects of doubled atmospheric carbon dioxide (CO2) concentrations and associated Arctic sea ice loss are remarkably additive and insensitive to the mean climate state. This separability is evident in several fields throughout most of the year, from hemispheric to synoptic scales. The extent to which the regional response to sea ice loss sometimes agrees with and sometimes cancels the response to CO2 is quantified. The separability of the responses might provide a means to better interpret the diverse array of modeling and observational studies of Arctic change and influence.

Changes in extremely hot days under stabilized 1.5 and 2.0 °c global warming scenarios as simulated by the HAPPI multi-model ensemble

Abstract: . The half a degree additional warming, prognosis and projected impacts (HAPPI) experimental protocol provides a multi-model database to compare the effects of stabilizing anthropogenic global warming of 1.5 ∘ C over preindustrial levels to 2.0 ∘ C over these levels. The HAPPI experiment is based upon large ensembles of global atmospheric models forced by sea surface temperature and sea ice concentrations plausible for these stabilization levels. This paper examines changes in extremes of high temperatures averaged over three consecutive days. Changes in this measure of extreme temperature are also compared to changes in hot season temperatures. We find that over land this measure of extreme high temperature increases from about 0.5 to 1.5 ∘ C over present-day values in the 1.5 ∘ C stabilization scenario, depending on location and model. We further find an additional 0.25 to 1.0 ∘ C increase in extreme high temperatures over land in the 2.0 ∘ C stabilization scenario. Results from the HAPPI models are consistent with similar results from the one available fully coupled climate model. However, a complicating factor in interpreting extreme temperature changes across the HAPPI models is their diversity of aerosol forcing changes.

A Postprocessing Method for Seasonal Forecasts Using Temporally and Spatially Smoothed Statistics

Abstract: A statistical postprocessing method for seasonal forecasts based on temporally and spatially smoothed climate statistics is introduced. The method uses information available from seasonal hindcasts initialized at the beginning of 12 calendar months. The performance of the method is tested within both deterministic and probabilistic frameworks using output from the ensemble of seasonal hindcasts produced by the Canadian Seasonal to Interannual Prediction System for the 30-yr period 1981–2010. Forecast skill improvements are found to be greater when forecast adjustment parameters estimated for individual seasons and at individual grid points are temporally and spatially smoothed. The greatest skill improvements are typically achieved for seasonally invariant parameters while skill improvements due to additional spatial smoothing are modest.

Towards the prediction of multi-year to decadal climate variability in the Southern Hemisphere

Abstract: Multi-year (2-7 years) and decadal climate variability (MDCV) can have a profound influence on lives, livelihoods and economies. Consequently, learning more about the causes of this variability, the extent to which it can be predicted, and the greater the clarity that we can provide on the climatic conditions that will unfold over coming years and decades is a high priority for the research community. This importance is reflected in new initiatives by WCRP, CLIVAR, and in the Decadal Climate Prediction Project (Boer et al., 2016) that target this area of research. Here we briefly examine some of the things we know, and have recently learnt, about the causes and predictability of Southern Hemisphere MDCV (SH MDCV), and current skill in its prediction.