Winter hydrometeorological extreme events modulated by 1 large scale atmospheric circulation in southern Ontario 2

Extreme events are widely studied across the world because of their major implications for many 8 aspects of society and especially floods. These events are generally studied in terms of precipitation or temperature 9 extreme indices that are often not adapted for regions affected by floods caused by snowmelt. Rain on Snow index 10 has been widely used, but it neglects rain only events which are expected to be more frequent in the future. In this 11 study, we identified a new winter compound index and assessed how large-scale atmospheric circulation controls 12 the past and future evolution of these events in the Great Lakes region. The future evolution of this index was 13 projected using temperature and precipitation from the Canadian Regional Climate Model Large Ensemble 14 (CRCM5-LE). These climate data were used as input in PRMS hydrological model to simulate the future evolution 15 of high flows in three watersheds in Southern Ontario. We also used five recurrent large-scale atmospheric 16 circulation patterns in north-eastern North America and identified how they control the past and future variability 17 of the newly created index and high flows. The results show that daily precipitation higher than 10mm and 18 temperature higher than 5°C were necessary historical conditions to produce high flows in these three watersheds. 19 In the historical period, the occurrences of these heavy rain and warm events as well as high flows were associated 20 with two main patterns characterized by high Z500 anomalies centred on eastern Great Lakes (regime HP) and 21 the Atlantic Ocean (regime South). These hydrometeorological extreme events will still be associated with the 22 same atmospheric patterns in the near future. The future evolution of the index will be modulated by the internal 23 variability of the climate system as higher Z500 in the east coast will amplify the increase in the number of events, 24 especially the warm events. The relationship between the extreme weather index and high flows will be modified 25 in the future as the snowpack reduces and rain becomes the main component of high flows generation. This study 26 shows the value of the CRCM5-LE dataset to simulate hydrometeorological extreme events in Eastern Canada 27 and to better understand the uncertainties associated with internal variability of climate. 28


Introduction 96
According to the actual pathway of greenhouse gases emissions, temperature will continue to rise in the future 97 with serious implications for society (Hoegh-Guldberg et al., 2018). The amount of precipitation, especially for 98 extreme events, is also projected to increase globally (Kharin et al., 2013), due to the acceleration of the 99 hydrological cycle (Trenberth, 1999). Because extreme precipitation has a great societal impact across the world, 100 internationally coordinated climate indices, built from precipitation and temperature data, are widely used to 101 step trial-and-error calibration approach applied to each watershed showed satisfactory results (Champagne et al., 213 2019a). The streamflow was simulated for each member of the ensemble in the 1957-2055 period using CRCM5-214 LE bias corrected data described in the section 2.1. 215 To quantify the winter change in number of high flows due to a change in number of weather extreme events, the 216 theoretical high flows frequency change due to the occurrence change in number of heavy rain and warm events 217 (OCC) have been calculated. For each member of the ensemble, the simulated historical number of high flows 218 events (99 th percentile) associated with each weather regime has been multiplied by the change factor between 219 number of rain and warm events in the historical period   Lakes. The regime South was characterized by positive Z500 anomalies in the Atlantic Ocean and negative 230 anomalies in the north-west part of the domain and was associated with southerly winds. The regime North-West 231 had low geopotential height on the Gulf of Saint-Lawrence together with winds from the northwest over the Great 232 Lakes region. Finally, the regime North-East was associated with low geopotential height in the Atlantic Ocean 233 but high geopotential height close to the Arctic that drove north-eastern winds over the Great Lakes. The weather 234 regimes calculated with CanESM2-LE data, using the k-means centroids identified with 20thCR anomalies, have 235 very similar patterns in the historical period   (Figure 3). CanESM2 50 members average Z500 236 anomalies were generally less strong than the 20thCR weather regimes and the anomalies were slightly shifted to 237 the south. Over the Great Lakes, 20thCR and CanESM2-LE Z500 anomalies were similar for most of the regimes 238 excepted for regime South showing higher Z500 anomalies with CanESM2-LE. In the 2026-2055 period the 239 weather regimes show meteorological systems in similar locations, but the anomalies are clearly weaker ( Figure  240 3). 241

Validation of heavy rain and warm index and high flows simulated by CRCM5-LE 242
The ability of the bias corrected CRCM5-LE data to recreate the number of heavy rain and warm events relative 243 to the number of occurrences of each weather regime is assessed in this section. For the heavy precipitation events 244 the observations show higher number of events during the occurrence of regime HP (10% of all HP days) 245 compared to other regimes, especially in the southern parts of the region (13% of all HP days) (Figure 4). The 246 regime South shows the second largest occurrence of heavy precipitation events (7% of all South days) while the 247 regime North-West was associated with the least number of observed heavy precipitation events (2% of all North-248 West days). The number of precipitation events associated with a regime LP is spatially variable with a large 249 number of events limited to the Lake Huron shoreline (12% of all LP days). The number of heavy precipitation 250 events per winter was generally well recreated by the regional ensemble in the historical period ( Figure 4). The 251 regime South is the exception with much more events with the 50 members average (11% of all South days) 252 compared to the observations (7% of all South days). In southern areas the simulations were also slightly 253 overestimating the number of heavy precipitation events during regime North-West while underestimating during 254 regime HP (Figure 4). 255 Figure 5 shows that the observed number of warm events (7.5% of all days) were overall more frequent than the 256 number of heavy precipitation events (5% of all days, Figure 4). The number of warm events occurred more 257 frequently in southern areas, particularly in the Niagara peninsula between Lake Erie and Lake Ontario, where 258 12-14% of all days were considered as warm days ( Figure 5). The observed warm events occurred mostly during 259 regime HP (23% of all HP days) while they were non-existent during regime LP ( Figure 5). The number of warm 260 events was similar between regimes North-West, North-East and South in a large part of the area. In the Niagara 261 peninsula more events were occurring during a regime South (15% of all South days). The simulated number of 262 warm events averaged for all members overestimated the observations and represented 11% of all days ( Figure  263 5). This discrepancy was due to an overestimation during regimes North-West and South ( Figure 5). Specifically, 264 the number of events per occurrence of regime South for the 50 members average (19% of all South days) was 265 twice the number of events calculated with the observations (9%). 266 The number of compound events, heavy rain and warm temperature was more frequent in the area close to Lake 267 Erie in both observations and simulations if we consider all weather regimes together ( Figure 6). The number of 268 events was overestimated by the ensemble mean in the northern parts of the region. In this region, many grid 269 points show all members of the ensemble overestimating the number of events. Close to Lake Erie the 270 overestimation was lower and even non-existent in the Niagara peninsula. These compound index heavy rain and 271 warm events were more frequent during a regime HP in both observations and simulations (4.5% of all HP days). 272 The simulations show a similar number of events during a regime South (4.5% of all South days) but the results 273 largely overestimated the observations (1.5% of all Souths days). Finally, the occurrences of events were very low 274 for LP and North-West ( Figure 6). 275 The historical distribution of streamflow associated with heavy rain and warm events for the observed streamflow 276 (OBS), streamflow simulated with NRCANmet (CTL) and streamflow simulated for all CRCM5-LE members 277 (ENS) are depicted in Figure 7. The results show an observed streamflow frequently higher than the high flows 278 threshold when the heavy rain and warm events occurred during a regime HP. The streamflow simulated with 279 NRCANmet weather data (CTL) is underestimated but show a similar inter-regime variability with higher 280 streamflow during HP heavy rain and warm events compared to events associated with other weather regimes. 281 The 50 simulations from CRCM5-LE show a less strong variability between weather regimes but again higher 282 streamflow when heavy rain and warm events correspond to regimes HP. High flows are also occurring for other 283 weather regimes especially regime South (Figure 7). 284

Future evolution of hydrometeorological extreme events 285
The number of heavy precipitation events simulated by CRCM5-LE is expected to increase between 1961-1990 286 and 2026-2055, with a maximum increase between 1 and 2 events per winter expected close to the Georgian Bay 287 ( Figure 8). The increase in the number of events is mainly expected during the regime South but also for the 288 regime LP near Lake Huron. The increased frequency of warm events is expected to be even higher reaching a 289 total increase of about 10 events per winter close to Lake Erie. The highest increase is expected for HP and South 290 regimes and at a lower rate for regimes North-East and North-West. The number of compound events is expected 291 to increase by 1 or 2 events per winter with a maximal increase between Lake Erie and Huron. The increase in the 292 number of heavy rain and warm events is expected to concern mainly the regime South and HP (Figure 8). 293 The contribution of the trend in heavy rain and warm events to the trend in number of high flows has been 294 investigated ( Figure 9). Taking all weather regimes events together, the total change in number of high flows 295 simulated by PRMS (TOT) is expected to increase in the future. The theoretical high flows frequency change due 296 to the occurrence change in number of heavy rain and warm events (OCC) is slightly lower than the increase in 297 TOT for most of the weather regimes (DIF positive, Figure 9). Regime HP shows an opposite result with higher 298 OCC compared to TOT on average (DIF negative, Figure 9). 299 The 50-members distribution change in rainfall and snowfall amounts corresponding to all compound events 300 simulated by PRMS at each watershed outlet have been investigated ( Figure 10). The amount of snowmelt and 301 rainfall taken together is generally decreasing but a large difference between members was simulated. Many 302 members show an increase in amount of rain and snowmelt especially during regime LP. The change in amount 303 of snowmelt follows a similar decreasing trend for most of the cases but an increase in snowmelt during LP 304 extreme days is expected, especially in Grand River. The amount of rainfall is slightly increasesing for most of 305 the members especially for LP in Thames river and Big Creek river.  (Table 1). Concerning the compound index, the number of heavy rain and warm 327 events is positively correlated wihto a combination of regime South-HP (significant at 95% confidence interval) 328 and negatively correlated withto a combination of North-East-LP and North-East-LP (significant at 90% 329 confidence interval). 330 The correlations with the change in number of high flows in each watershed have also been investigated (Table  331 2) and shows significance in the Big Creek and Grand River watersheds. In both watersheds, LP and a combination 332 LP-North-West are negatively correlated withto high flows while a combination North-West-South is positively 333 correlated withto high flows. In Grand River the number of high flows is also negatively correlated withto a 334 combination of regime HP-LP. 335 The change of heavy precipitation, warm and compound events frequency in respect to change in occurrence of 336 regimes South, HP, LP and North-East for each member of the ensemble is shown in Figure 12. The 337 correspondence between change in number of heavy precipitations events and change in number of occurrences 338 of weather regimes is not clear, confirming the low correlations in Figure 11 and Table 1 3). This pattern also brings warm temperature events even though the regime HP brings even more warm events 371 in both the observations and the ensemble average ( Figure 5). Regime HP has similarities with the positive phase 372 of the NAO, previously associated with warm winter temperature in the Great Lakes region (Ning and Bradley, 373 2015). The other weather regimes bring generally fewer heavy precipitation or warm events apart from regime LP 374 bringing heavy precipitation close to Lake Huron (Figure 4). LP is not associated with warm events (Figure 5) 375 suggesting that these extreme precipitations are in form of snow and likely from lake effect snow. Suriano and 376 Leathers (2017) show that low pressure anomalies north-east from Great lakes bring major lake effects snow in 377 the eastern shores of Lake Huron due to less zonal wind and cold outbreaks from the Arctic. The regime LP shows 378 low geopotential height anomalies right on the Great lakes and the associated north-west winds on the Lake Huron 379 are likely to bring lake effect snowfall in this area. consider snowpack and is expecting to be more frequent in the future (Figure 8). The increase of heavy rain and 390 warm events is likely driven by warmer temperature shown by the increase of the compound events and warm 391 events both occurring at a higher extent close to Lake Erie (Figure 8). The increase in extreme precipitation events 392 is less significant than the increase in warm events and is occurring mostly in the Northern parts of the area (Figure  393 8). 394 The future evolution of ROS or heavy rain and warm events corresponding to different weather patterns have not 395 been yet investigated in previous literature. It is interesting to note that the future increase in the number of heavy 396 rain and warm events are expected to occur only for the regimes HP and South, the number of events remaining 397 very low for the other regimes (Figure 8). This result suggests that the global increase of mean temperature and 398 precipitation is not sufficient to reach the 10 mm and 5°C threshold for LP, North-West and North-East regimes. 399 More precipitation events are expected during regime LP but the temperature stays too low to increase the numbers 400 of heavy rain and warm events (Figure 8). Regime North-West and North-East show an increase of warm events 401 but not an increase in precipitation events and therefore the number of rain and warm events is not expected to 402 increase. 403

Change in frequency of heavy rain and warm events partially modulated by the occurrence of weather 404 regimes 405
Despite clear association between regimes HP/South and occurrences of rain and warm events, the uncertainties 406 linked to internal variability of climate are not fully drivenapprehended by the frequency of weather regimes. 407 Members of the ensemble associated with a simultaneous high increase of regime HP and South frequencies are 408 generally associated with higher increase in rainfall and warm events (Table 1), but the association is less 409 straightforward than suggested by the correlation values ( Figure 12) probably due to poor association between 410 precipitation extremes and occurrence of weather regimes (Table 1 and

Non stationarity in the relationship between weather extreme events and high flows 420
The projections show that the increase in number of high flows associated with a regime HP is expected to be 421 lower than the increase in number of heavy rain and warm events (negative DIF in Figure 9). This result suggests 422 that the conditions thatto produce high flows may change in the future. As the temperature increases, snowmelt is 423 expected to be a less important component in the generation of high flows in the region (Figure 10). In the 424 historical period regimes HP and South produce approximately the same number of high flows in the simulations 425 ( Figure 7), but are driving mostly by heavy precipitation for the regime South and warm events for the regime 426 HP (Figure 4 and 5). More importantly, HP shows a further increase of warm events in the future while South 427 show rather an increase of precipitation (Figure 8). In the context of less snow, the importance of precipitation to 428 drive high flows will be higher in the future because warmer conditions do not increase snowmelt in case of a 429 snowpack reduction ( Figure 10). Therefore, the increase of weather extreme events associated with the regime 430 South will generate an increase of high flows more strenuously than the increase of events associated with regime 431 HP (Figure 9). 432 The future change in number of high flows is associated with a large inter-member uncertainty (Figure 9). The 433 weather extreme events inter-member uncertainty was partly associated with the change in occurrence of weather 434 regimes especially for the warm component ( Figure 11,12 and Table 1). The association between occurrence of 435 weather regimes and high flows is less clear and shows opposite results (Table 1 and Table S2). In addition, as already stated in the previous 444 paragraph, regime HP will be less likely to produce a heavy rain event than a regime South in the future. Therefore, 445 members projecting an increase in the combination of the snowy regime North-West and wetter and warmer 446 regime South are more likely to project more high flow events. These results emphasize the need to study not only 447 each hydrometeorological extreme events and relationship with atmospheric circulation independently, but to also 448 focusing on the sequence of weather patterns preceding the high flows events. 449

Relevance of rain and warm events to explain future evolution of high flows 450
Our method The relevance of that usesing an index based on daily temperature and precipitation to study the future 451 evolution of high flows is questionable. Even if a heavy rain and warm event is a necessary condition to create a 452 high flow event (Figure 2), such event is not systematically followed by a high flow event (Figure 7). The previous 453 section suggests that snow falling days before the high flow event has an important role in the generation of high 454 flows. Other factors such as multi-days rain events could also contribute to increase the streamflow. This study 455 focused on single day events to introduce first results in the ability of CRCM5-LE to recreate extreme events in 456 southern Ontario, but future studies should investigate multi-day events. 457 Moreover, as stated in the previous section, the relationship between the extreme weather events index and high 458 flows is affected by non-stationarity. Applied in the past, the Rain and warm index works well to define the high 459 flows risk in Southern Ontario (Figure 2), the warm component of this index being a condition to trigger snowmelt. 460 In a warming climate, snowpack is reduced, and the rain to snow ratio is increasing (Jeong and Sushama, 2018), 461 changing the relationship between extreme weather events and high flows. 462 To integrate snow processes and reduce the uncertainties from non-stationarity of temperature, Rain on snow 463 index could be used in lieu of our heavy rain and warm index. However, this index is not projected to be more and take into consideration heavy rainfall whatever the amount of snow covering the ground. It is therefore a good 470 tool to assess the potential risk of high flows in Southern Ontario from all ranges of rain events, even though it is 471 important to keep in mind that the flood risk diminished as snowpack decreases. A rain only index could also be 472 used but the impact of snowpack on streamflow would be completely eradicated while snow will still play a role 473 in the future hydrology. ROS events, liquid precipitation events and our heavy rain and warm events, ideally with 474 multi-day events integrated, should be investigated together to fully understand the future evolution of the flood 475 risk due to a shift in weather extreme events. 476

Conclusion 477
The aim of this study was to assess the ability of the These results suggest that depending on the future evolution of natural variability of climate, the increase in the 497 number of events will be amplified or attenuated by the favoured positions of the pressure systems. The natural 498 variability of climate is not expected to greatly modulate the number of high flows due to an increase of the 499 importance of precipitation in generating high flows. The role of more localized processes such as impact of the 500 lakes on precipitation events needs to be further evaluated to improve the ability of the next versions of regional 501 climate models to recreate the precipitation events. The newly created weather index did not integrate snowpack 502 because the uncertainties in the ability of CRCM5-LE to recreate precipitation and temperature extremes at a daily 503 basis would be further increased in snowmelt estimates. However, snowpack variability will have a large impact 504 in the modulation of high flows in the region and future studies should investigate snow processes by taking 505 advantage of rapid improvements in climate regional modelling. Other regional climate models and different 506 scenarios should also be used to improve our understanding of the future evolution of hydrometeorological 507 extreme events in Southern Ontario. Despite these future possible improvements, our study gives a good 508 estimation of what to expect in term of change in number of hydrometeorological events in Southern Ontario and 509 will serve to better estimate the future flood risk in this populated region. 510

Authors contribution 511
ML furnished CRCM5-LE data. OC performed the analyses and made the figures. OC prepared the manuscript 512 with contributions from all co-authors. 513

Competing interest 514
The authors declare that they have no conflict of interest. 515

Acknowledgement 516
We are acknowledging the reviewers who gave constructive comments during the publication process.