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  • Source Publication: Climate Dynamics, doi:10.1007/s00382-016-3148-x Authors: Whan, K. and F.W. Zwiers Publication Date: Jul 2016

    The relationship between winter precipitation in North America and indices of the North Atlantic Oscillation (NAO) and El Niño–Southern Oscillation (ENSO) is evaluated using non-stationary generalized extreme value distributions with the indices as covariates. Both covariates have a statistically significant influence on precipitation that is well simulated by two regional climate models (RCMs), CanRCM4 and CRCM5. The observed influence of the NAO on extreme precipitation is largest in eastern North America, with the likelihood of a negative phase extreme rainfall event decreased in the north and increased in the south under the positive phase of the NAO. This pattern is generally well simulated by the RCMs although there are some differences in the extent of influence, particularly south of the Great Lakes. A La Niña-magnitude extreme event is more likely to occur under El Niño conditions in California and the southern United States, and less likely in most of Canada and a region south of the Great Lakes. This broad pattern is also simulated well by the RCMs but they do not capture the increased likelihood in California. In some places the extreme precipitation response in the RCMs to external forcing from a covariate is of the opposite sign, despite use of the same lateral boundary conditions and dynamical core. This demonstrates the importance of model physics for teleconnections to extreme precipitation.

  • Authors: T. Q. MURDOCK, A. J. CANNON, AND S.R. SOBIE Publication Date: Jun 2016

    The need for future projections of extremes is growing, particularly as users planning to adapt to climate change continue to experience record-breaking events (Figure 1). Decision-making demands that such projections possess high spatial resolution. Downscaling has been carried out for Canada by the Pacic Climate Impacts Consortium for the newest Global Climate Model (GCM) and Regional Climate Model (RCM) projections.

  • Authors: G. Bürger, T. Q. Murdock, A. T. Werner, S. R. Sobie Publication Date: Jun 2016

    Empirical downscaling is based in a statistical analysis of present climatic conditions for an area, usually recorded by a number of variables from weather stations. The result of this analysis is a set of recipes (algorithms) and parameters from which the present climate, or at least some of its crucial aspects, such as extreme temperature values, can be recovered.

  • Authors: S.R. Sobie, A.J. Cannon, T.Q. Murdock Publication Date: Jun 2016

    For terrestrial British Columbia, precipitation averages and extremes can be simulated more accurately within individual regions by using gridded downscaling to increase the resolution of regional climate models. In locations where the difference between observations and RCMs is large, bias correction tends to inflate the magnitude of projected extremes. Differences in projections between the RCMs and downscaled simulations can be large enough to affect the PIEVC Risk Assessment process, leading to higher risk values. Future work will focus on correcting the inflation of extremes in the downscaling method and extending the analysis to additional regions.

  • Authors: S.R. Sobie, A.J. Cannon, T.Q. Murdock Publication Date: Jun 2016

    For terrestrial British Columbia, precipitation averages and extremes can be simulated more accurately within individual regions by using gridded downscaling to increase the resolution of both global and regional climate models. In locations where the difference between observations and model simulations is large, bias correction tends to inflate the magnitude of high resolution projected extremes. The effect is minimal for average indices but is statistically significant in a subset of models for projected changes of 10 and 20-year return periods. Future work will focus on correcting the inflation of extremes in the downscaling method and extending the analysis to additional regions.

  • Authors: T. Q. MURDOCK, S.R. SOBIE, A. J. CANNON, AND F.W. ZWIERS Publication Date: Jun 2016

    The main effect of statistical downscaling on projected change in extremes is due to correction of historical bias. is does not necessarily mean downscaling is adding value. e coarse scale projected change in annual precipitation is retained but heavy precipitation (R95ptot) is somewhat amplied and extreme precipitation change (RP10) is considerably altered. Since it is these extremes that are needed for planning, further work is needed. In next steps we will compare results at a coarser scale (e.g. 5°) to reduce the inuence of bias correction on results and also separate into small and large scale explicitly as in Di Luca et al. (2013). Finally, we plan to compare projected changes from RCMs to that of their driving models in the same ways. Statistical downscaling methods that are explicitly designed to preserve coarse scale projected changes including extremes would be a welcome development for regional decision-making.

  • Source Publication: Climate Dynamics, doi:0.1007/s00382-016-3239-8 Authors: Teufel, B., G.T. Diro, K. Whan, S.M. Milrad, D.I. Jeong, A. Ganji, O. Huziy, K. Winger, E. Montero, J.R. Gyakum, R. de Elia, F.W. Zwiers and L. Sushama Publication Date: Jun 2016

    During 19–21 June 2013 a heavy precipitation event affected southern Alberta and adjoining regions, leading to severe flood damage in numerous communities and resulting in the costliest natural disaster in Canadian history. This flood was caused by a combination of meteorological and hydrological factors, which are investigated from weather and climate perspectives with the fifth generation Canadian Regional Climate Model. Results show that the contribution of orographic ascent to precipitation was important, exceeding 30 % over the foothills of the Rocky Mountains. Another contributing factor was evapotranspiration from the land surface, which is found to have acted as an important moisture source and was likely enhanced by antecedent rainfall that increased soil moisture over the northern Great Plains. Event attribution analysis suggests that human induced greenhouse gas increases may also have contributed by causing evapotranspiration rates to be higher than they would have been under pre-industrial conditions. Frozen and snow-covered soils at high elevations are likely to have played an important role in generating record streamflows. Results point to a doubling of surface runoff due to the frozen conditions, while 25 % of the modelled runoff originated from snowmelt. The estimated return time of the 3-day precipitation event exceeds 50 years over a large region, and an increase in the occurrence of similar extreme precipitation events is projected by the end of the 21st century. Event attribution analysis suggests that greenhouse gas increases may have increased 1-day and 3-day return levels of May–June precipitation with respect to pre-industrial climate conditions. However, no anthropogenic influence can be detected for 1-day and 3-day surface runoff, as increases in extreme precipitation in the present-day climate are offset by decreased snow cover and lower frozen water content in soils during the May–June transition months, compared to pre-industrial climate.

  • Authors: Krosby, M., Michalak, J., Robbins, T.O., Morgan, H., Norheim, R., Mauger, G., and T. Murdock Publication Date: Jun 2016

    Plant and animal species have historically used movement to adapt to changes in the Earth’s climate, shifting their ranges across landscapes to stay within climatically suitable habitat. Species are using this strategy to adapt to present day climate change, but the current rate of change is so rapid that many species will have difficulty keeping pace. In addition, human land use (e.g., highways, cities, farms) presents significant barriers to wildlife movement across today’s landscapes. For this reason, enhancing habitat connectivity – the ability of species to move across the landscape – is a leading strategy for helping wildlife respond to climate change. And yet, significant challenges remain in translating this high-level strategy into specific, on-the-ground actions. The Washington-British Columbia Transboundary Climate-Connectivity Project was initiated to help address these challenges. The region spanning the border of Washington state, USA, and British Columbia, Canada, faces increasing development pressure and limited transboundary coordination of land and wildlife management, both of which may threaten habitat connectivity and limit the potential for wildlife movement in response to change. In addition, the effects of climate change may further reduce habitat connectivity, and species may need novel types of habitat connectivity to complete adaptive range shifts. This project paired scientists and practitioners from both sides of the border to collaboratively identify potential climate impacts and adaptation actions for transboundary habitat connectivity, using a diverse suite of case study species, a vegetation system, and a region. Case study assessments revealed that climate change is likely to have significant implications for transboundary habitat connectivity. The adaptation actions identified to address potential impacts varied by case study, but fell into two general categories: those addressing potential climate impacts on existing habitat connectivity and those addressing novel habitat connectivity needs for climate-induced shifts in species ranges. In addition, project partners identified priority spatial locations for implementing these actions, as well as additional research needed to improve assessment of climate impacts and adaptation actions for habitat connectivity. The project resulted in a suite of products designed in collaboration with project partners to ensure their relevance and ease of application to decision-making. These products include this project overview report, which describes the project’s rationale, partnerships, approach, key findings, lessons learned, and remaining needs; detailed, stand-alone appendices for each case study, which describe the assessment process and key findings for each, and include all materials used in the assessment; and an interactive project gallery on the online mapping platform, Data Basin, which includes project reports and associated assessment materials, including interactive and downloadable connectivity and climate datasets. In addition, project participants emerged with enhanced capacity and a transboundary community of practice for addressing climate change and habitat connectivity in their decisionmaking. However, ongoing support for transboundary capacity building, collaboration, and research will be needed to promote the future resilience of our shared species and ecosystems.

  • Authors: T. Q. MURDOCK, D. NYLAND, S. SOBIE, AND J. WOLF Publication Date: Jun 2016

    Large scale infrastructure projects have long lifespans so planning them considers the long term. Highways in British Columbia are already experiencing extreme events beyond design capacity (see: photos at left). In 2008, the BC MOTI identied a pair of adaptation case studies, the results of which informed four streams of subsequent work (see timeline and other text boxes). A best practices summary of four years of adaptation work recommended MOTI produce a policy document. Following stakeholder and expert review, a ”Technical Circular” was published in 2015, requiring all projects for MOTI to consider climate. To assist with implementation, the Association of Professional Engineers and Geoscientists of BC is developing comprehensive guidelines for engineers to mainstream adaptation into their practice.

  • Source Publication: Climate Dynamics, doi:10.1007/s00382-016-3079-6 Authors: Ribes, A, F.W. Zwiers, Jean-Marc Azaïs and P. Naveau Publication Date: Apr 2016

    We propose here a new statistical approach to climate change detection and attribution that is based on additive decomposition and simple hypothesis testing. Most current statistical methods for detection and attribution rely on linear regression models where the observations are regressed onto expected response patterns to different external forcings. These methods do not use physical information provided by climate models regarding the expected response magnitudes to constrain the estimated responses to the forcings. Climate modelling uncertainty is difficult to take into account with regression based methods and is almost never treated explicitly. As an alternative to this approach, our statistical model is only based on the additivity assumption; the proposed method does not regress observations onto expected response patterns. We introduce estimation and testing procedures based on likelihood maximization, and show that climate modelling uncertainty can easily be accounted for. Some discussion is provided on how to practically estimate the climate modelling uncertainty based on an ensemble of opportunity. Our approach is based on the “models are statistically indistinguishable from the truth” paradigm, where the difference between any given model and the truth has the same distribution as the difference between any pair of models, but other choices might also be considered. The properties of this approach are illustrated and discussed based on synthetic data. Lastly, the method is applied to the linear trend in global mean temperature over the period 1951–2010. Consistent with the last IPCC assessment report, we find that most of the observed warming over this period (+0.65 K) is attributable to anthropogenic forcings (+0.67 ±± 0.12 K, 90 % confidence range), with a very limited contribution from natural forcings (−0.01±0.02−0.01±0.02 K).

  • Authors: T. Q. Murdock, S. R. Sobie, H. D. Eckstrand, E. Jackson Publication Date: Apr 2016

    Climate change projections have been provided in this report for Metro Vancouver and the Capital Regional District from several difference sources: Global Climate Models (GCMs) directly, high resolution elevation-corrected projections from GCMs, and Regional Climate Models. Historical climate information at selected stations of interest throughout the region is also provided for comparison.
    Projected annual warming by the 2050s (compared to 1961-1990) for the two regions is similar, according to a set of 30 commonly used Global Climate Models (GCMs). Projections are given for both the 2050s and 2080s periods. For the 2050s, the range of projected change in Metro Vancouver is +1.4°C to +2.8°C in summer, +0.8°C to +2.7°C in winter, -5% to +16% in winter precipitation, and -25% to +5% in summer precipitation. For the 2050s, the range of projected change in the Capital Regional District (CRD) is +1.3°C to +2.6°C in summer, +0.8°C to +2.4°C in winter, -5% to +17% in winter precipitation, and -30% to +1% in summer precipitation. Compared to the ranges, the projected differences between regions are minor.
    Maps of high resolution projections of change are provided for several variables of interest. Projections mid-century show changes in variables related to temperature: increased growing degree days, cooling degree days, and frost free period along with decreased heating degree days and precipitation as snow. The projected 2080s maps illustrate a future climate that does not resemble the present-day for most of these variables.
    Regional Climate Models projections are used to provide projections of changes in temperature, precipitation, and indices of extremes. Extreme temperatures so warm that in the past they would be exceeded on average once every ten years (corresponding to about 32°C to 35°C) are projected to occur on average over twice as often in future in Metro Vancouver and almost four times as often in future in the CRD.
    The amount of precipitation falling during very wet days is projected to increase by 21% in Metro Vancouver and 20% in CRD, while precipitation during extremely wet days is projected to increase by 28% in Metro Vancouver and 25% in CRD. More extreme precipitation events (with 3-hour duration) so intense than in the past they would be exceeded on average only once every 10 years are projected to occur on average three times as often in future in Metro Vancouver and about three and a half times as often in future in CRD.
    The implications of these projected changes are briefly discussed for physical, social, economic, and ecological systems, and the ICLEI Canada climate adaptation planning methodology is described. This process, outlined in Changing Climate, Changing Communities: Guide and Workbook for Municipal Climate Adaptation is currently being undertaken by communities in Metro Vancouver and CRD. The information contained within this report supports Milestone Two of that process as is intended to assist with adaptation planning.

  • Source Publication: Environmental Research Letters, 11, 4, doi:10.1088/1748-9326/11/4/044011 Authors: B. Mueller, X. Zhang and F.W. Zwiers Publication Date: Apr 2016

    e project that within the next two decades, half of the world's population will regularly (every second summer on average) experience regional summer mean temperatures that exceed those of the historically hottest summer, even under the moderate RCP4.5 emissions pathway. This frequency threshold for hot temperatures over land, which have adverse effects on human health, society and economy, might be broached in little more than a decade under the RCP8.5 emissions pathway. These hot summer frequency projections are based on adjusted RCP4.5 and 8.5 temperature projections, where the adjustments are performed with scaling factors determined by regularized optimal fingerprinting analyzes that compare historical model simulations with observations over the period 1950–2012. A temperature reconstruction technique is then used to simulate a multitude of possible past and future temperature evolutions, from which the probability of a hot summer is determined for each region, with a hot summer being defined as the historically warmest summer on record in that region. Probabilities with and without external forcing show that hot summers are now about ten times more likely (fraction of attributable risk 0.9) in many regions of the world than they would have been in the absence of past greenhouse gas increases. The adjusted future projections suggest that the Mediterranean, Sahara, large parts of Asia and the Western US and Canada will be among the first regions for which hot summers will become the norm (i.e. occur on average every other year), and that this will occur within the next 1–2 decades.

  • Source Publication: Nature Climate Change 6, 706–709, doi:10.1038/NCLIMATE2956. Authors: Sun, Y., X, Zhang, G. Ren, F.W. Zwiers and T. Hu Publication Date: Mar 2016

    China has warmed rapidly over the past half century and has experienced widespread concomitant impacts on water availability, agriculture and ecosystems. Although urban areas occupy less than 1% of China’s land mass, the majority of China’s observing stations are situated in proximity to urban areas, and thus some of the recorded warming is undoubtedly the consequence of rapid urban development, particularly since the late 1970s. Here, we quantify the separate contributions of urbanization and other external forcings to the observed warming. We estimate that China’s temperature increased by 1.44 °C (90% confidence interval 1.22–1.66 °C) over the period 1961–2013 and that urban warming influences account for about a third of this observed warming, 0.49 °C (0.12–0.86 °C). Anthropogenic and natural external forcings combined explain most of the rest of the observed warming, contributing 0.93 °C (0.61–1.24 °C). This is close to the warming of 1.09 °C (0.86–1.31 °C) observed in global mean land temperatures over the period 1951–2010, which, in contrast to China’s recorded temperature change, is only weakly affected by urban warming influences. Clearly the effects of urbanization have considerably exacerbated the warming experienced by the large majority of the Chinese population in comparison with the warming that they would have experienced as a result of external forcing alone.

  • Authors: Anslow, F.S. and Y. Wang Publication Date: Mar 2016

    This document details the exploratory efforts to create a high quality, homogenized set of monthly mean of daily minimum and maximum temperatures for the Williston Basin and Campbell River regions of British Columbia. Data from BC Hydro, the Ministry of Transportation and Infrastructure, and the Ministry of Forests Lands and Natural Resource Operation Wildfire Management Branch are used. The data records are of various lengths, from as many as 50 years to as few as a single year. A set of quality control procedures is applied to the data and then the data are subject to a two step statistical homogenization process. The quality control work revealed that the data are of high quality overall. Inconsistencies were set as missing. Homogenization efforts revealed that fewer than 50% of stations contained any discontinuities with the data in the Williston region being of greater homogeneity than that in the Campbell River region. The outlook for homogenizing daily temperature and monthly precipitation totals is also discussed. Appendices detail station metadata as well as changepoint occurrence for each station. This report will be accompanied by an archive of the results of this project including the homogenized datasets.

  • Source Publication: Wiley Interdisciplinary Reviews: Climate Change, 7, 1, pages 23–41, doi:10.1002/wcc.380. Authors: Stott, P.A., N. Christidis, F. Otto, Y. Sun, J.-P. Vanderlinden, G.J. van Oldenborgh, R. Vautard, P. Walton, P. Yiou, F.W. Zwiers Publication Date: Jan 2016

    Extreme weather and climate-related events occur in a particular place, by definition, infrequently. It is therefore challenging to detect systematic changes in their occurrence given the relative shortness of observational records. However, there is a clear interest from outside the climate science community in the extent to which recent damaging extreme events can be linked to human-induced climate change or natural climate variability. Event attribution studies seek to determine to what extent anthropogenic climate change has altered the probability or magnitude of particular events. They have shown clear evidence for human influence having increased the probability of many extremely warm seasonal temperatures and reduced the probability of extremely cold seasonal temperatures in many parts of the world. The evidence for human influence on the probability of extreme precipitation events, droughts, and storms is more mixed. Although the science of event attribution has developed rapidly in recent years, geographical coverage of events remains patchy and based on the interests and capabilities of individual research groups. The development of operational event attribution would allow a more timely and methodical production of attribution assessments than currently obtained on an ad hoc basis. For event attribution assessments to be most useful, remaining scientific uncertainties need to be robustly assessed and the results clearly communicated. This requires the continuing development of methodologies to assess the reliability of event attribution results and further work to understand the potential utility of event attribution for stakeholder groups and decision makers.

  • Source Publication: Climate Dynamics, doi:10.1007/s00382-015-2807-7 Authors: Whan, K., and F.W. Zwiers Publication Date: Jan 2016

    We assess the ability of two Canadian regional climate models (RCMs), CanRCM4 and CRCM5, to simulate North American climate extremes over the period 1989–2009. Both RCMs use lateral boundary conditions derived from the ERA-Interim reanalysis and share the same dynamical core but use different nesting strategies, land-surface and physics schemes. The annual cycle and spatial patterns of extreme temperature indices are generally well reproduced in both models but the magnitude varies. In central and southern North America, maximum temperature extremes are up to 7 °C warmer in CanRCM4. There is a cool bias in minimum temperature extremes in both RCMs. The shape of the annual cycle of extreme rainfall varies between simulations. There is a wet bias in CRCM5 extreme rainfall on the west coast throughout the year and in winter rainfall elsewhere. In summer both RCMs have precipitation biases in the south-east. These rainfall and temperature biases are likely associated with differences in the physical parameterisation of rainfall. CanRCM4 simulates too little convective rainfall, while over-estimating large-scale rainfall; nevertheless, cloud cover is well simulated. CRCM5 simulates more large-scale rainfall throughout the year on the west coast and in winter in other regions. The spatial extent, intensity and location of atmospheric river (AR) landfall are well reproduced by the RCMs, as is the fraction of winter rainfall from AR days. Spectral nudging improves agreement on landfall latitude between the RCM and the driving model without greatly diminishing the intensity of the rainfall extreme.

  • Source Publication: Geophysical Research Letters, 42, 24, 10,867–10,875, doi:10.1002/2015GL066858. Authors: Kumar, S., R.P. Allan, F.W. Zwiers, D.M. Lawrence and P.A. Dirmeyer Publication Date: Dec 2015

    A theoretically expected consequence of the intensification of the hydrological cycle under global warming is that on average, wet regions get wetter and dry regions get drier (WWDD). Recent studies, however, have found significant discrepancies between the expected pattern of change and observed changes over land. We assess the WWDD theory in four climate models. We find that the reported discrepancy can be traced to two main issues: (1) unforced internal climate variability strongly affects local wetness and dryness trends and can obscure underlying agreement with WWDD, and (2) dry land regions are not constrained to become drier by enhanced moisture divergence since evaporation cannot exceed precipitation over multiannual time scales. Over land, where the available water does not limit evaporation, a “wet gets wetter” signal predominates. On seasonal time scales, where evaporation can exceed precipitation, trends in wet season becoming wetter and dry season becoming drier are also found.

  • Source Publication: Hydrological Processes, 28, 4294–4310, doi: 10.1002/hyp.9997 Authors: Shrestha, R.R., D.L. Peters and M.A. Schnorbus Publication Date: Nov 2015

    It is a common practice to employ hydrologic models for assessing alterations to streamflow as a result of anthropogenically driven changes, such as riverine, land use, and climate change. However, the ability of the models to replicate different components of the hydrograph simultaneously is not clear. Hence, this study evaluates the ability of a standard hydrologic model set-up: Variable Infiltration Capacity (VIC) hydrologic model for two headwater sub-basins in the Fraser River (Salmon and Willow), British Columbia, Canada, with climate inputs derived from observations and statistically downscaled global climate models (GCMs); to simulate six general water resource indicators (WRIs) and 32 ecologically relevant indicators of hydrologic alterations (IHA). The results show a generally good skill of the observation-driven VIC model in replicating most of the WRIs and IHAs. Although the WRIs, including annual volume, centre of timing, and seasonal flows, and the IHAs, including maximum and minimum flows, were reasonably well replicated, statistically significant differences in some of the monthly flows, number and duration of flow pulses, rise and fall rates, and reversals were noted. In the case of GCM-driven results, additional monthly, maximum, and minimum flow indicators produced statistically significant differences. A number of issues with the model input/output data, hydrologic model parametrization and structure as well as downscaling methods were identified, which lead to such discrepancies. Therefore, there is a need to exercise caution in the use of model-simulated indicators. Overall, the WRIs and IHAs can be useful tools for evaluating changes in an altered hydrologic system, provided the skill and limitations of the model in replicating these indicators are understood.

  • Source Publication: Weather and Climate Extremes, 9, 57-67, doi:10.1016/j.wace.2015.05.001 Authors: Whan, K., J. Zscheischler, R., Orth, M. Shongwe, M., Rahimi, E.O. Asare and S.I. Seneviratne Publication Date: Nov 2015

    Land-atmosphere interactions play an important role for hot temperature extremes in Europe. Dry soils may amplify such extremes through feedbacks with evapotranspiration. While previous observational studies generally focused on the relationship between precipitation deficits and the number of hot days, we investigate here the influence of soil moisture (SM) on summer monthly maximum temperatures (TXx) using water balance model-based SM estimates (driven with observations) and temperature observations. Generalized extreme value distributions are fitted to TXx using SM as a covariate. We identify a negative relationship between SM and TXx, whereby a 100 mm decrease in model-based SM is associated with a 1.6 °C increase in TXx in Southern-Central and Southeastern Europe. Dry SM conditions result in a 2–4 °C increase in the 20-year return value of TXx compared to wet conditions in these two regions. In contrast with SM impacts on the number of hot days (NHD), where low and high surface-moisture conditions lead to different variability, we find a mostly linear dependency of the 20-year return value on surface-moisture conditions. We attribute this difference to the non-linear relationship between TXx and NHD that stems from the threshold-based calculation of NHD. Furthermore the employed SM data and the Standardized Precipitation Index (SPI) are only weakly correlated in the investigated regions, highlighting the importance of evapotranspiration and runoff for resulting SM. Finally, in a case study for the hot 2003 summer we illustrate that if 2003 spring conditions in Southern-Central Europe had been as dry as in the more recent 2011 event, temperature extremes in summer would have been higher by about 1 °C, further enhancing the already extreme conditions which prevailed in that year.

  • Source Publication: Earth’s Future, 2, 3, 152‐160, doi: 10.1002/2013EF000159 Authors: Kumar, S., D. Lawrence, P. Dirmeyer and J. Sheffield Publication Date: Nov 2015

    The temporal variability of river and soil water affects society at time scales ranging from hourly to decadal. The available water (AW), i.e., precipitation minus evapotranspiration, represents the total water available for runoff, soil water storage change, and ground water recharge. The reliability of AW is defined as the annual range of AW between local wet and dry seasons. A smaller annual range represents greater reliability and a larger range denotes less reliability. Here we assess the reliability of AW in the 21st century climate projections by 20 climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5). The multimodel consensus suggests less reliable AW in the 21st century than in the 20th century with generally decreasing AW in local dry seasons and increasing AW in local wet seasons. In addition to the canonical perspective from climate models that wet regions will get wetter, this study suggests greater dryness during dry seasons even in regions where the mean climate becomes wetter. Lower emission scenarios show significant advantages in terms of minimizing impacts on AW but do not eliminate these impacts altogether.

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