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The observed summertime drying over Northern Central India (NCI) during the latter half of the twentieth century is not reproduced by the Coupled Model Intercomparison Project Phase 5 (CMIP5) model ensemble average. At the same time, the spread between precipitation trends from individual model realizations is large, indicating that internal variability potentially plays an important role in explaining the observed trend. Here we show that the drying is indeed related to the observed 1950–1999 positive trend of the Pacific Decadal Oscillation (PDO) index and that the relationship is even stronger for a simpler index (S1). Adjusting the CMIP5-simulated precipitation trends to account for the difference between the observed and simulated S1 trend increases the original multimodel average NCI drying trend from −0.09 ± 0.31 mm d−1 (50 years)−1 to −0.54 ± 0.40 mm d−1 (50 years)−1. Thus, our estimate of the 1950–1999 NCI drying associated with Pacific decadal variability is of similar magnitude as our previous CMIP5-based estimate of the drying due to anthropogenic aerosol. The drying (moistening) associated with increasing (decreasing) S1 can partially be attributed to a southeastward (northwestward) shift of the boundary between ascent and descent affecting NCI. This shift of the ascent region strongly affects NCI but not Southeast Asia and south China. The average spread between individual model realizations is only slightly reduced when adjusting for S1 as smaller-scale variability also plays an important role.

The observed summertime drying over Northern Central India (NCI) during the latter half of the twentieth century is not reproduced by the Coupled Model Intercomparison Project Phase 5 (CMIP5) model ensemble average. At the same time, the spread between precipitation trends from individual model realizations is large, indicating that internal variability potentially plays an important role in explaining the observed trend. Here we show that the drying is indeed related to the observed 1950–1999 positive trend of the Pacific Decadal Oscillation (PDO) index and that the relationship is even stronger for a simpler index (S1). Adjusting the CMIP5-simulated precipitation trends to account for the difference between the observed and simulated S1 trend increases the original multimodel average NCI drying trend from −0.09 ± 0.31 mm d−1 (50 years)−1 to −0.54 ± 0.40 mm d−1 (50 years)−1. Thus, our estimate of the 1950–1999 NCI drying associated with Pacific decadal variability is of similar magnitude as our previous CMIP5-based estimate of the drying due to anthropogenic aerosol. The drying (moistening) associated with increasing (decreasing) S1 can partially be attributed to a southeastward (northwestward) shift of the boundary between ascent and descent affecting NCI. This shift of the ascent region strongly affects NCI but not Southeast Asia and south China. The average spread between individual model realizations is only slightly reduced when adjusting for S1 as smaller-scale variability also plays an important role.

Flooding is a major concern for Canadian society as it is the costliest natural disaster type in Canada. Southern Ontario, which houses one-third of the Canadian population, is particularly affected by early spring floods following snowmelt. During the last three decades, there has been a shift in flooding events from March-April to earlier months due to earlier snowmelt coupled with extreme rain events. Hydrological models run with different scenarios of climate change suggest further enhancement of this shift in the future. These projections of streamflow are associated with a cascade of uncertainties due to the choice of Global Climate Models (GCM’s), climate change scenarios, downscaling methods or hydrological models. A large part of the uncertainty is also associated with internal variability of climate due to the chaotic nature of the climate system. Despite these uncertainties, little is known about the impact of atmospheric circulation on past streamflow in southern Ontario and how the internal variability of climate is expected to impact the overall uncertainties in the projections of the future hydrological processes. In this thesis, the Precipitation Runoff Modelling System (PRMS), a semi-distributed conceptual hydrological model, was established in four watersheds in southern Ontario to assess the impact of atmospheric circulation on the modulation of streamflow and number of high flows. Recurrent meteorological patterns (Or Weather regimes), based on 500hPa geopotential height (Z500), have been first identified in Northeastern North America using the k-means algorithm. The occurrences of these weather regimes patterns were used to create a regime-normalized hypothetical temperature and precipitation dataset that have been used as input in PRMS. Then, to investigate the future evolution of the hydrological processes, PRMS was forced with temperature and precipitation from the 50-members Canadian Regional Climate Model Large Ensemble (CRCM5-LE), a dynamically downscaled version of CanESM2-LE. The 50-members were classified into different classes of similar change in average temperature, precipitation and streamflow to identify the corresponding large-scale patterns. The specific focus of this analysis was on winter high flows, with the identification of a heavy rain and warm index, that can help to explain the generation of winter high flows in southern Ontario. The future evolution of these hydrometeorological extreme events, calculated for each member of CRCM5-LE, was analyzed with respect to the corresponding k-means weather regimes calculated for each member of CanESM2-LE. Finally, the uncertainties in the projections of the hydrometeorological extremes from the 50-members ensemble were compared to other sources of uncertainties using an analysis of variance applied to 504 simulations in the Big creek watershed. The high flows were projected using seven sets of PRMS parameters, 11 CMIP5 climate models forced with 2 scenarios of climate change and the 50 members of CRCM5-LE. The results, focusing on the winter season, showed that weather regimes High-Pressure (HP) and southerly winds (South) are associated with a higher average streamflow volume and high-flows frequency in the historical period. Regime HP is characterized by high geopotential height anomalies on top of the Great Lakes region together with higher temperature and precipitation amounts. Regime South is characterized by high Z500 anomalies in the Atlantic east coast and is associated with stronger southerly winds and higher precipitation amount in southern Ontario. The temporal increase in HP in the past contributed more than 40% of the increase in average streamflow in winter. In the future, all 50 members of CRCM5-LE ensemble produce an increase in January-February streamflow. 14% of the ensemble depict a larger streamflow increase due to increase in Z500 anomalies in the east coast. This pattern, well defined by the regimes South, is expected to become a major contributor in the generation of hydrometeorological extreme events in Southern Ontario in the future. Regime HP is expected to contribute less to the high-flows due to the disappearance of snow. Overall, the contribution of internal variability of climate to high flows will be stable through the 21st century, primarily due to an increase in rainfall as generators of high flow events. The results suggest that the regional representation of rainfall in the GCMs-RCMs chains will be a critical area to improve with great societal implications for floods. / Dissertation / Doctor of Science (PhD)

<p>Global mean surface air temperature (GMST) is one of the most well-known and robust measures of global climate change both contemporarily as well as through deep time. In contemporary climate science, the most often discussed causes of GMST change are referred to as external radiative forcings, which are considered to be exogenous to the land-atmosphere-ocean system and which impose a radiative energy imbalance (N) at the top of the earth’s atmosphere. Examples of external radiative forcings include changes in well-mixed greenhouse gas concentrations, changes in volcanic or anthropogenic aerosol loading, anthropogenic changes in land use, and changes in incoming solar radiation. The climate system can also produce unforced variability in GMST that spontaneously emerges from the internal dynamics of the land-atmosphere-ocean system. Unforced GMST variability can emerge via a vertical redistribution of heat within the climate system. For example, there can be a net transport of energy from below the ocean’s mixed layer to the surface during an El-Niño event. Additionally, unforced GMST variability can be due to an unforced change in N. For example, an internally generated change in the strength of an ocean circulation could alter the extent of sea ice and thus change the Earth’s albedo.</p><p>Understanding the magnitude and mechanisms underlying unforced GMST variability is relevant for both the attribution of past climate change to various causes, as well to the prediction of future changes on policy-relevant timescales. However, the literature on unforced GMST variability, particularly at interdecadal and longer timescales, is inconsistent and there is significant disagreement on its magnitude, on its primary geographic origins, and on the physical mechanisms that are most responsible.</p><p>This dissertation seeks to advance the scientific understanding of unforced GMST variability by addressing seven primary scientific goals: 1) To identify the geographic locations (and by proxy modes of variability) that are most responsible for unforced GMST variability in both the instrumental record and in climate models. 2) To identify the primary reasons why AOGCMs disagree on the magnitude of interdecadal unforced GMST variability. 3) To quantify the magnitude of unforced GMST variability in observations over the instrumental record as well as in multi-proxy reconstructions over the past millennium. 4) To quantify the degree to which unforced GMST variability is influenced by internally generated N energy imbalances. 5) To understand how anomalous N fluxes can influence large scale modes of surface temperature variability that affect GMST, such as the Atlantic Multidecadal Oscillation (AMO). 6) To understand the nature of the restoring force responsible for returning a perturbed GMST anomaly back to equilibrium; and 7) To understand how the magnitude and mechanisms of GMST variability might change in the future as the climate warms. </p><p>This research relies on the analysis of coupled Atmosphere-Ocean general circulation models (AOGCMs) that participated in Phase 5 of the Coupled Model Intercomparison Project (CMIP5), satellite observations of the Earth’s energy budget from the Clouds and Earth’s Radiant Energy System (CERES), instrumental surface temperature observations from NASA GISS Surface Temperature Analysis (GISTEMP), atmospheric reanalysis data from the European Center for Medium-Range Weather Forecasts interim reanalysis (ERA-I) and surface temperature reconstructions over the past millennium from numerous multiproxy archives.</p><p>This work has yielded six primary conclusions: I) Dynamics over the tropical Pacific Ocean represent the primary contributor to unforced GMST variability at interdecadal and longer timescales with lesser contributions from dynamics in the subpolar north Atlantic and Southern Ocean. II) AOGCMs tend to underestimate the magnitude of unforced GMST variability at interdecadal and longer timescales relative to both instrumental and reconstructed surface temperature datasets. III) N imbalances can act to significantly enhance interdecadal GMST variability. IV) GMST is able to restore equilibrium after an internally generated perturbation via the transport of energy to high-latitude locations and via the rearrangement the atmospheric circulation; both of which allow for much more efficient release of outgoing longwave radiation (OLR) than would otherwise be expected. V) N imbalances can significantly enhance internal modes of variability such as the AMO; and VI) The magnitude of interdecadal GMST variability is likely to decline and the generating mechanisms of such variability may be fundamentally altered as climate warms over the 21st century. These results advance our understanding of unforced GMST variability and they have implications for attribution studies and may inform projections of climate change on interdecadal timescales.</p> / Dissertation