IP2.1 Climate Change and Extreme Events in the Marine Environment. Bill Merryfield Environment Canada/University of Victoria

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1 IP2.1 Climate Change and Extreme Events in the Marine Environment Bill Merryfield Environment Canada/University of Victoria

2 MEOPAR Initial Project 2.1 Status June, 2014 compiled by G. Flato with input from all project leads. Theme 2: Reducing the Impact of Emerging and Changing Marine Risks IP2.1 : Climate Change and Extreme Events in the Marine Environment Global Predictions/ Projections Validation Value added Changes in Extremes Changes in Risk Preparedness and Adaptation Downscaled Predictions/ Projections Modelling Analysis Assessment Planning EC/UVic UQAM DFO/Dal UVic/PCIC Dal MemU Western Global/RCM RCM Ocean/Wave Fisheries Communities Policies Flato,Boer Laprise Sheng Zwiers Pelot Neis McBean Merryfield Monahan

3 Marine Applications & Downscaling of Seasonal Climate Predictions Bill Merryfield, Woo-Sung Lee, George Boer, Greg Flato CCCma(EC)/U.Vic (with John Scinocca, Slava Kharin and Yanjun Jiao) Activities: Evaluate performance of CanSIPS (Canadian Seasonal to Interannual Prediction System) marine-relevant predictions: subsurface ocean temps, NAO/PNA/PDO Develop methods for dynamical downscaling of CanSIPS predictions to 25 km resolution for North America and surrounding ocean regions, using CCCma s CanRCM4 regional model. Outcome: Improved ability to provide regionally-downscaled seasonal climate predictions of relevance to Canada s maritime areas.

4 Downscaling CanSIPS using CanRCM4 regional model CORDEX North America grid at km resolution First step: run in assimilation mode to generate forecast initial conditions Example: Maritimes storm surge of Dec 2010 (maps valid 12Z 21 Dec): NOAA surface analysis Model sea level pressure Storm Surge Escuminac, N.B. Model surface wind (u) Model surface wind (v) Sustained onshore winds at Escuminac ~ 100 km/h Although not a forecast, this illustrates the level of detail that will be available in CanRCM4 downscaled forecasts

5 Future Plans Production of CanRCM4-downscaled seasonal hindcasts for 1979-present will begin this year. Model output potentially includes 3-hourly fields at 25 km horizontal resolution suitable for driving coastal ocean models, e.g. IOS/DFO BC coastal model If you are interested in using this output to drive a coastal model please let us know soon: - of your interest - data requirements (driving variables, frequency) Masson & Fine, JGR 2012 A goal is to demonstrate value added by RCM for predicting probabilities of coastal wind extremes, etc. RCM is designed to run in tandem with global model potential for CanRCM downscaling of seasonal forecasts to become operational

6 Empirical correction of CGCM-simulated SSTs for driving RCM projections René Laprise -ESCER-UQAM Activities: Design bias correction strategy for use in downscaling with CRCM5 [completed] Implement bias correction strategy and test over CORDEX Africa domain [in progress] Bias-corrected CRCM5 simulation at 15km resolution for East Coast North America, for , driven by 1 CGCM for 1 RCP climate change scenario [next] Multiple simulations driven by several CGCMs and for several RCPs [later] Outcome: Improved ability to provide regionally-downscaled climate information by reducing biases inherited from the global model providing lateral and sea-surface boundary conditions.

7 Traditional two-stage dynamical downscaling Cgcm$ Low%Res.*! Atmosphere!! Lat.!BC! Rcm$ High%Res.*! Atmosphere!! Global coupled model results used directly as RCM boundary conditions. SIC!! SST! Lower!BC! (Oc.!Sfc)!! Ocean!! SIC *! SST! Proposed three-stage dynamical downscaling Cgcm% Low'Res.+ ) Atmosphere) ) Agcm% Medium'Res.+ ) Atmosphere) ) Lat.)BC) Empirical) SIC) ) SST) Correc-on) SIC * Lower)BC) ) SST) (Oc.)Sfc)) ) Ocean) ) Rcm% High'Res.+ ) Atmosphere) ) SIC * ) SST) * Sea1ice)concentra-on)(SIC))and)sea1surface)temperature)(SST)) are)specified,)but)sea1ice)thickness)and)sea1ice)temperature) are)calculated) Empirical bias correction applied to global coupled model SST, then medium resolution atmosphereonly model driven by these bias-corrected SSTs. Output from AGCM used to provide RCM boundary conditions.

8 Initial Results Africa chosen for initial tests because of strong sensitivity of West African monsoon to cold tongue in Gulf of Guinea SST bias in global coupled model Mean ( ) annual cycle of precipitation (mm/day) RCM driven by raw global coupled model boundary conditions (green) RCM driven by bias-corrected AGCM boundary conditions (blue) RCM driven by reanalysis boundary conditions (red) Observational estimates (dashed lines) Three-stage downscaling approach corrects large bias in precip annual cycle.

9 Estimation of extreme wave statistics off the east coast of Canada and their future change Jinyu Sheng and Lanli Guo Dalhousie U. Activities: Apply third-generation ocean wave model (WAVEWATCH III) to the northwest Atlantic Ocean with a horizontal resolution of 0.25 degree. Wind forcing is taken from the Climate Forecast System Reanalysis (CFSR) with a horizontal resolution of about 38 km. The spatial resolution of the CFSR, however, is still not fine to enough to represent winds associated with a tropical storm or hurricane, which affects simulation accuracy of ocean waves, particularly extreme waves. Outcome: Improved ability to simulate extreme wave statistics (e.g. return period) and their response to a changing climate.

10 Initial Results Ocean wave simulation during Hurricane Juan (2003) Arrows denote wind velocities in m/s) Colours represent significant wave height in m Driving is by CFSR winds, plus a vortex to simulate small-scale influence of Hurricane Juan Simulated wave heights near Halifax Greatly improved when vortex representing Hurricane Juan is added to CFSR winds Peak significant wave height is then 8-9 m as observed, vs 5-6 m without vortex

11 Progress 30-year wave simulation over the northwest Atlantic completed. A parameterized hurricane effect has been inserted into the wind field to improve the wind field during a tropical storm or hurricane. The accuracy of the wave model is improved using the modified wind field for Hurricane Juan. Waves in different hurricane cases will be simulated. Model results will be used to estimate extreme wave statistics. Future work will include impact of climate change on the return period of extreme waves

12 Coastal Storm Activity Francis Zwiers, Christian Seiler, Katie Pingree-Shippee U.Victoria Activities: Analysis of wind speed and sea-level pressure as simulated by global coupled climate models to assess their ability to reproduce storm tracks and related storm intensity statistics Outcome: Quantitative evaluation of contemporary global climate models in terms of their ability to simulate coastal storms. Quantitative information regarding future change in coastal storm activity under a changing climate.

13 Representation of Storm Activity in Reanalyses (K. Pingree-Shippee) Current work: Evaluating the representation of coastal storm activity in commonlyused global reanalyses (NCEP-1, NCEP-2, ERA-Interim, 20CR), using station-based MSLP proxies. 20CR ERA- Interim NCEP- 2 NCEP- 1 Initial results: ERA-Interim provides best representation of coastal storm activity for a range of West and East coast sites Future work: Evaluate seasonal predictability of coastal storm activity in CCCma seasonal forecasting system.

14 Meteorological Bombs - rapidly intensifying extratropical cyclones How well do CMIP5 reproduce meteorological bombs? (Christian Seiler) Reasonable bomb evolution Most models underestimate bomb frequency, vorticity, wind speed Most models overestimate bomb sea level pressure Too few bombs E of Japan, southward shift in north Atlantic Models tend to underestimate bomb intensity

15 The link between SST anomalies and wind speed Adam Monahan and Johannes Gemmrich U.Vic Activities: Analysis of sea-surface temperature (SST) and near-surface wind speed data Outcome: Improved understanding of processes relating wind speed and surface temperature Improved ability to represent these processes in climate prediction models, and resulting improvement in ability to predict wind speed and wind extremes.

16 Consider 8 regions of distinctive ΔSST and ΔU 10 characteristics Data: Global SST (GHRSST_v2) and wind speed (QuikSCAT), 0.25 o resolution, daily, 06/ /

17 PDF of wind speed anomalies as function of SST anomalies ΔU 10 vs ΔSST and lead time Low wind speeds High SST ΔSST leads ΔU 10 ΔSST lags ΔU 10 High wind speeds Low SST ΔU 10 - ΔSST dependence vs lead time 2 competing processes: Largest effects when SST lags wind Enhanced wind mixing: Positive U 10 anomaly negative SST anomaly Modified boundary layer stability: Positive SST anomaly positive U 10 anomaly Next step: Basic, process oriented boundary layer model relating ΔU 10 vs. ΔSST

18 Climate Change and Marine Risk Ron Pelot, Joel Finnis, Sara Rezaee and Heather Read Dal & Memorial U. Activities: Risk Analysis model development Assess distribution and frequency (climatology) of environmental factors contributing to marine risk in Atlantic Canada Quantify the impact of climate change on environmental factors Outcome: Identify significant cyclone weather conditions associated with fishing incident occurrence, categorized spatially and temporally. Understand connection between cyclone weather conditions and the severity of fishing incidents, categorized spatially and temporally. Identify relationship between cyclone weather conditions and fishing traffic levels, categorized spatially and temporally. Link cyclone weather conditions to fishing vessel incidents associated with different fishing activities. Develop tools to predict future risk levels based on different climate change scenarios.

19 Initial Results Cyclone Weather Conditions and Fishing Vessel Incidents in Atlantic Canada Risk Analysis Risk Analysis Model Development 1. Multivariate Statistical Methods: Use statistical methods such as logistic and/or ordered regressions, classification and/or regression trees and neural networks to document patterns in incident occurrence, incident severity levels, and relative incident rate with respect to different extreme weather conditions. 2. Geostatistical Methods: Determine spatial variability of maritime risk due to weather conditions and traffic levels. Apply geostatistical interpolation methods such as geographically weighted regression to the analysis of 625 Incidents 312 Incidents 62 Incidents incident, traffic and weather data. 3. What-If Analysis: Apply various regional Climate Change predictive models to the data to anticipate impacts on future risk to fishing safety arising from possible weather changes. Fishing Vessel Incidents

20 Initial Results Impact of Climate Change on Marine Risk - Perform spatial analyses of environmental risk factors - Atmospheric & wave reanalyses/hindcasts - Satellite derived sea surface temperatures and sea ice cover - Identify ocean locations with similar risk factor climatology - Compare risk factors in climate projections to observations - North American Climate Change Assessment Project - Program for Climate Model Diagnosis & Intercomparison (IPCC/CMIP) - Quantify impact of climate change on marine risk, using risk prediction systems

21 Assessing and Reducing Risk and Vulnerability to Extreme Events in Newfoundland and Labrador Fisheries by Engaging Stakeholders and their Knowledge B. Neis, J. Finnis, R. Pelot, and James Shewmake Memorial U. Activities: Frame fishing safety within a social-ecological systems (SES) framework Use mixed methods (ethnography, participatory mapping and spatial analysis and linkages to other project components) to engage stakeholders in the fishing industry in documenting, mapping and assessing risk of injury and fatality associated with extreme events by season, species, gear and fleet sector and region Devise and model the effectiveness of different participatory interventions with the potential improve system resilience while reducing vulnerability to safety risks. Outcome: Improve occupational health and safety in commercial fishing by documenting high risk fishing scenarios in Newfoundland and Labrador associated with severe weather events and environmental change and developing risk reduction strategies.

22 Climate Impacts and Risk Assessment Gordon McBean U.Western Ontario (with Brennan Vogel and Jonathan Raikes) Activities: Municipalities & Climate Change: A Framework for Analyzing Local Climate Adaptation Policy Comparative case study & research approach: Nova Scotia Municipal Climate Change Action Planning (MCCAP) Outcome: Improved knowledge mobilization to guide preparedness of communities and industries Improved ability of government, private sector and coastal communities to prepare for and adapt to altered risk associate with climate change

23 Progress Brennan Vogel PhD Candidate- Western Topic: Adapting to Climate Change: The Case of Local Governance and Municipal Planning in Nova Scotia A comparative case study / policy evaluation of climate change adaptation planning and policy approaches in coastal municipalities of Nova Scotia, Canada. Highlights & Plans Research synthesis & journal article #1 completed 6 presentations including Ontario Climate Change Consortium, Coastal Zone Canada Federation of Canadian Municipalities MEOPAR representative and delegate Municipal Climate Change Action Plan (MCCAP) activities Research synthesis & journal article #2 Jonathan Raikes - MA candidate -Western Topic: Pathways of local responses to flooding in the Vancouver region Coastal city vulnerability and response to rising sea levels, examining hazard risk management strategies associated with changing climatic conditions by the private and government sectors Highlights & Plans Literature review and data analysis underway Edward G. Pleva Fellowship ( )---teaching excellence award Potentially working as an intern at the United Nations in New York

24 Lagos Bangkok Coastal Cities at Risk CCaR - Building Adaptive Capacity for Managing Climate Change in Coastal Megacities G.A. McBean, Canadian Principal Investigator Linked with MEOPAR - agreement on use of MEOPAR-PCIC climate model outputs - 10 conference presentations on coastal cities and climate change (last 12 months) Vancouver Manila

25 Timeline and key deliverables (First 3 years) Year 1: Atlantic Canada consultation workshop and report (McBean) Initial analysis of multi-season forecast skill for marine variables, making use of existing retrospective forecast output (Merryfield/Boer/Flato) Initial development of Atlantic coast wave model based on WAVEWATCHIII (Sheng) Year 2: British Columbia consultation workshop and report (McBean) Initial wave model runs and their validation using wave observations (Sheng) Initial implementation of bias correction strategy for use in subsequent downscaling (Laprise) Development of a coupled atmosphere/upper-ocean single column model underway (Monahan) Initial implementation of CanRCM downscaling of coupled climate prediction system and analysis of added value (Merryfield/Flato) Review of literature on impacts of weather extremes on fishing vessel accidents (Neis) Evaluation of observed and simulated coastal storm trends and variability (Zwiers) Year 3: Second Atlantic Canada consultation workshop and report (McBean) Initial version of spatial model of risks to fishing vessels (Pelot) Analysis of physical controls on extreme winds and nonlinear statistical downscaling method developed (Monahan) Bias-corrected regional downscaling completed at ~15km resolution, covering period , driven by CanESM2 global model and a single GHG scenario. (Laprise) CanRCM downscaling of seasonal hindcasts for 1979-present (Merryfield/Flato) Analysis of 20-year historical simulation of Atlantic wave conditions using wave model and bias-corrected regional downscaling model output (Sheng). Assessment of prospects for seasonal to interannual prediction of storm-related extreme events in the coastal environment (Zwiers).

26 Questions? Your name here How to reach you

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28 Prediction Core IP2.2: Biogeochemical Projections Under a Changing Climate Global Predictions/ Projections Validation Value added Changes in Extremes Changes in Risk Preparedness and Adaptation Downscaled Predictions/ Projections Modelling Analysis Assessment Planning EC/UVic UQAM DFO/Dal UVic/PCIC Dal MemU Western Global/RCM RCM Ocean/Wave Fisheries Communities Policies Flato,Boer Laprise Sheng Zwiers Pelot Neis McBean Merryfield Monahan

29 1) Performance of CanSIPS marine-relevant predictions Prediction of subsurface ocean temperatures DFO observations along Line P off the BC coast provide a unique long-term time series for verifying subsurface ocean temperature hindcasts CanSIPS hindcasts represent interannual to interdecadal subsurfce temperature variations reasonably well Predictions initialized in winter have higher skill than predictions initialized in summer 2005 Crawford et al Obs CanSIPS Observations and CanSIPS forecasts of subsurface ocean temperature anomalies averaged over m depth, along Line P, initialized from the start of February each year time Prediction of climate indices affecting Canada s coasts 1979 distance from shore Skill demonstrated for predicting North Atlantic Oscillation (NAO) and Pacific North America (PNA) patterns, especially in winter Skill for predicting seasonal mean Pacific Decadal Oscillation (PDO) index 9 months ahead is 0.64 (anomaly correlation, averaged over all seasons)