Canadian RCM projected climate-change signal and its sensitivity to model errors

Despite the importance of surface water in Manitoba, Canada, there has been relatively little investigation of the impact of climate change on the hydrology of the province. This study examines streamflow characteristics in northern Manitoba basins (Taylor and Burntwood River basins) under climate scenarios generated by global climate models (GCM) from 2 agencies (the UK Hadley Centre and the Canadian Centre for Climate Modelling and Analysis). The hydrological model SLURP (Semi-distributed Land Use-based Runoff Processes) was run with perturbed meteorological data based on the GCM simulations under 2 greenhouse gas emission scenarios (A2 and B2) for 2 future periods (2041-2070 and 2071-2099). A method to incorporate the changed variability in future temperature and precipitation to the climate scenarios was also tested. All scenarios project wetter and warmer climates, and simulation results show that the mean annual runoff is likely to increase in every scenario. The largest seasonal increase occurs in late spring and the least in winter and summer. The daily flow exceeded by 80% of the total records is also projected to substantially increase, resulting in much fewer days with extreme low flow compared to the control period. Results indicate that the combination of a hydrological model with simple GCM-based scenarios can produce results comparable to those obtained from regional climate modelling. Explicit incorporation of changed variability in climate scenarios results in higher runoff than consideration of only changes in means. KEY WORDS: Climate change impact · Runoff · Statistical downscaling · SLURP · ManitobaResale or republication not permitted without written consent of the publisher Clim Res 40: 89-102, 2009 mate models (GCMs) consistently project mean temperature increases of several degrees in northern Manitoba by the second half of the 21st century (Boer et al. 2000, Johns et al. 2003, it is imperative to assess the related effects on water resources.Few studies have addressed the effect of past or potential climate change on the hydrological cycle in Manitoba. This is in contrast to other areas in Canada where extensive studies have been undertaken, including British Columbia (see Merritt et al. 2006 for a review on B.C. studies), Ontario (e.g. Cunderlik & Simonovic 2005), and Quebec (e.g. Roy et al. 2001). Westmacott & Burn (1997) and Yulianti & Burn (1998) investigated links between climatic warming and hydrologic characteristics of river basins in the Canadian Prairies, including portions of Alberta, Saskatchewan, and Manitoba, by analysing past streamflow and temperature data. While they discovered a clear relationship between stream flow and temperature, they did not provide explicit projection of future climatic and hydrological characteristics. Sushama et al. (2006) investigated the Churchill and the Nelson River basins using 2 different versions of the Canadian Regional Climate Model (v3.6 and v3.7). Both of these rivers flow through Manitoba to Hudson Bay. The simulations ...

Section: Runoff Changes From the Standard Delta Methodsmentioning

confidence: 65%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Simulating streamflow response to climate scenarios in central Canada using a simple statistical downscaling method

Choi¹,

Rasmussen²,

Moore³

et al. 2009

“…In order to make future climate simulations with confidence, it is essential that models are able to adequately simulate the present climate (Sushama et al 2006, Engelbrecht et al 2009), as well as long-term mean circulation patterns and surface fields, and also particularly variability on all time scales (Battisti et al 1995, Renwick & Revell 1999, Engelbrecht et al 2009). …”

Section: Model Evaluationmentioning

confidence: 99%

Climate model simulation of the South Indian Ocean Convergence Zone: mean state and variability

Lazenby

Todd²,

Wang³

2016

Evaluation of climate model performance at regional scales is essential in determining confidence in simulations of present and future climate. Here we developed a process-based approach focussing on the South Indian Ocean Convergence Zone (SIOCZ), a large-scale, austral summer rainfall feature extending across southern Africa into the southwest Indian Ocean. Simulation of the SIOCZ was evaluated for the Coupled Model Intercomparison Project (CMIP5).Comparison was made between CMIP5 and Atmospheric Model Intercomparison Project (AMIP) models to diagnose sources of biases associated with coupled ocean−atmosphere processes. Models were assessed in terms of mean SIOCZ characteristics and processes of interannual variability. Most models simulated a SIOCZ feature, but were typically too zonally oriented. A systematic bias of excessive precipitation was found over southern Africa and the Indian Ocean, but not particularly along the SIOCZ. Excessive precipitation over the continent may be associated with excessively high low-level moisture flux around the Angola Low found in most models, which is almost entirely due to circulation biases in models. AMIP models represented precipitation more realistically over the Indian Ocean, implying a potential coupling error. Interannual variability in the SIOCZ was evaluated through empirical orthogonal function analysis, where results showed a clear dipole pattern, indicative of a northeast−southwest movement of the SIOCZ. The drivers of this shift were significantly related to the El Niño Southern Oscillation and the subtropical Indian Ocean dipole in observations. However, the models did not capture these teleconnections well, limiting our confidence in model representation of variability.KEY WORDS: CMIP5 · ENSO · Ensemble · Teleconnection · Model evaluation · South Indian Ocean Convergence Zone · SIOCZ · Southern Africa · December-January-February · DJF OPEN PEN ACCESS CCESS

“…Frei et al 2003, Kusunoki & Mizuta 2013. However, such systematic biases in the underlying model can be partly cancelled when taking the difference between REF simulation and RCP future projection, even though such a model bias could affect the magnitude of changes in response to emission forcing (Sushama et al 2006, Hagemann & Jacob 2007, Im et al 2008b). In addition, Giorgi & Coppola (2010) demonstrate that East Asia might be a region in which the model regional bias is not a dominant factor in determining the projected regional change.…”

Section: Long-term Trends Of Temperature and Precipitationmentioning

confidence: 99%

Regional climate projection over South Korea simulated by the HadGEM2-AO and WRF model chain under RCP emission scenarios

Im¹,

Ahn²,

Jo³

2015

This study assesses the regional climate projection newly generated within the framework of the national downscaling project in South Korea. To obtain fine-scale climate information (12.5 km), dynamical downscaling of the HadGEM2-AO global projections forced by the representative concentration pathway (RCP4.5 and RCP8.5) scenarios is performed using the Weather Research and Forecasting (WRF) modeling system. Changes in temperature and precipitation in terms of long-term trends, daily characteristics and extremes are presented by comparing two 30 yr periods (2041−2070 vs. 2071−2100) in which increasing rates of emission forcing between the RCP4.5 and RCP8.5 scenarios are relatively similar and quite different, respectively. The temperature increase presents a relevant trend, but the degree of warming varies in different periods and emission scenarios. While the temperature distribution from the RCP8.5 projection is continuously shifted toward warmer conditions by the end of the 21st century, the RCP4.5 projection appears to stabilize warming in accordance with emission forcing. This shift in distribution directly affects the magnitude of extremes, which enhances extreme hot days but reduces extreme cold days. Precipitation changes, however, do not respond monotonically to emission forcing, as they exhibit less sensitivity to different emission scenarios. An enhancement of high intensity precipitation and a reduction of weak intensity precipitation are discernible, implying an intensified hydrologic cycle. Changes in return levels of annual maximum precipitation suggest an increased probability of extreme precipitation with 20 yr and 50 yr return periods.