Assessing Climatic Drivers of Spring Mean and Annual Maximum Flows in Western Canadian River Basins

Flows originating from cold and mountainous watersheds are highly dependent on temperature and precipitation patterns, and the resulting snow accumulation and melt conditions, affecting the magnitude and timing of annual peak flows. This study applied a multiple linear regression (MLR) modelling framework to investigate spatial variations and relative importance of hydroclimatic drivers of annual maximum flows (AMF) and mean spring flows (MAMJflow) in 25 river basins across western Canada. The results show that basin average maximum snow water equivalent (SWEmax), April 1st SWE and spring precipitation (MAMJprc) are the most important predictors of both AMF and MAMJflow, with the proportion of explained variance averaging 51.7%, 44.0% and 33.5%, respectively. The MLR models’ abilities to project future changes in AMF and MAMJflow in response to changes to the hydroclimatic controls are also examined using the Canadian Regional Climate Model (CanRCM4) output for RCP 4.5 and RCP8.5 scenarios. The results show considerable spatial variations depending on individual watershed characteristics with projected changes in AMF ranging from −69% to +126% and those of MAMJflow ranging from −48% to +81% by the end of this century. In general, the study demonstrates that the MLR framework is a useful approach for assessing the spatial variation in hydroclimatic controls of annual maximum and mean spring flows in the western Canadian river basins. However, there is a need to exercise caution in applying MLR models for projecting changes in future flows, especially for regulated basins.

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A regional climate model hindcast for Siberia – assessing the added value of snow water equivalent using ESA GlobSnow and reanalyses

The Cryosphere Discussions ◽

10.5194/tcd-6-4637-2012 ◽

2012 ◽

Vol 6 (6) ◽

pp. 4637-4671

Author(s):

K. Klehmet ◽

B. Geyer ◽

B. Rockel

Keyword(s):

Regional Climate Model ◽

Snow Cover ◽

Large Scale ◽

Snow Water Equivalent ◽

Climate Model ◽

Regional Climate ◽

Snow Accumulation ◽

Added Value ◽

Snow Cover Extent ◽

Snow Water

Abstract. This study analyzes the added value of a regional climate model hindcast of CCLM compared to global reanalyses in providing a reconstruction of recent past snow water equivalent (SWE) for Siberia. Consistent regional climate data in time and space is necessary due to lack of station data in that region. We focus on SWE since it represents an important snow cover parameter in a region where snow has the potential to feed back to the climate of the whole Northern Hemisphere. The simulation was performed in a 50 km grid spacing for the period 1948 to 2010 using NCEP Reanalysis 1 as boundary forcing. Daily observational reference data for the period of 1987–2010 was obtained by the satellite derived SWE product of ESA DUE GlobSnow that enables a large scale assessment. The analyses includes comparisons of the distribution of snow cover extent, example time series of monthly SWE for January and April, regional characteristics of long-term monthly mean, standard deviation and temporal correlation averaged over subregions. SWE of CCLM is compared against the SWE information of NCEP-R1 itself and three more reanalyses (NCEP-R2, NCEP-CFSR, ERA-Interim). We demonstrate a significant added value of the CCLM hindcast during snow accumulation period shown for January for many subregions compared to SWE of NCEP-R1. NCEP-R1 mostly underestimates SWE during whole snow season. CCLM overestimates SWE compared to the satellite-derived product during April – a month representing the beginning of snow melt in southern regions. We illustrate that SWE of the regional hindcast is more consistent in time than ERA-Interim and NCEP-R2 and thus add realistic detail.

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Evaluation of CLASS 2.7 and 3.5 Simulations of Snow Properties from the Canadian Regional Climate Model (CRCM4) over Québec, Canada*

Journal of Hydrometeorology ◽

10.1175/jhm-d-13-055.1 ◽

2014 ◽

Vol 15 (4) ◽

pp. 1325-1343 ◽

Cited By ~ 14

Author(s):

A. Langlois ◽

J. Bergeron ◽

R. Brown ◽

A. Royer ◽

R. Harvey ◽

...

Keyword(s):

Regional Climate Model ◽

Land Surface ◽

Snow Water Equivalent ◽

Climate Model ◽

Regional Climate ◽

Snow Accumulation ◽

Canadian Regional Climate Model ◽

Surface Areas ◽

Snow Properties ◽

Surface Scheme

Abstract Snow cover simulations from versions 2.7 and 3.5 of the Canadian Land Surface Scheme (CLASS) coupled to the Canadian Regional Climate Model, version 4 (CRCM4), are evaluated over northern Québec and the larger Québec domain using in situ and remotely sensed datasets. Version 2.7 of CLASS has been used in the operational version of CRCM4 at Ouranos since 2006. Version 3.5 includes a number of improvements to the snow processes as well as a more realistic parameterization of snow thermal conductivity. The evaluation shows that version 3.5 provides improved simulations of snow water equivalent, density, depth, and snowpack temperature values. However, snowpack density still contains systematic biases during the snow season that need to be addressed. The snow albedo parameterization in CLASS was found to be very sensitive to an empirical snowfall rate threshold for albedo refreshment and does not keep track of the snow accumulation history in estimating the snow surface albedo. A modified albedo scheme based on snow-specific surface areas is proposed to address this problem.

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Comparison of Methods to Estimate Snow Water Equivalent at the Mountain Range Scale: A Case Study of the California Sierra Nevada

Journal of Hydrometeorology ◽

10.1175/jhm-d-16-0246.1 ◽

2017 ◽

Vol 18 (4) ◽

pp. 1101-1119 ◽

Cited By ~ 29

Author(s):

Melissa L. Wrzesien ◽

Michael T. Durand ◽

Tamlin M. Pavelsky ◽

Ian M. Howat ◽

Steven A. Margulis ◽

...

Keyword(s):

Sierra Nevada ◽

Snow Water Equivalent ◽

Climate Model ◽

Regional Climate ◽

Wrf Model ◽

Snow Accumulation ◽

Energy Budgets ◽

Mountain Range ◽

Order Of Magnitude ◽

Snow Water

Abstract Despite the importance of snow in global water and energy budgets, estimates of global mountain snow water equivalent (SWE) are not well constrained. Two approaches for estimating total range-wide SWE over Sierra Nevada, California, are assessed: 1) global/hemispherical models and remote sensing and models available for continental United States (CONUS) plus southern Canada (CONUS+) available to the scientific community and 2) regional climate model simulations via the Weather Research and Forecasting (WRF) Model run at 3, 9, and 27 km. As no truth dataset provides total mountain range SWE, these two approaches are compared to a “reference” SWE consisting of three published, independent datasets that utilize/validate against in situ SWE measurements. Model outputs are compared with the reference datasets for three water years: 2005 (high snow accumulation), 2009 (average), and 2014 (low). There is a distinctive difference between the reference/WRF datasets and the global/CONUS+ daily estimates of SWE, with the former suggesting up to an order of magnitude more snow. Results are qualitatively similar for peak SWE and 1 April SWE for all three years. Analysis of SWE time series indicates that lower SWE for global and CONUS+ datasets is likely due to precipitation, rain/snow partitioning, and ablation parameterization differences. It is found that WRF produces reasonable (within 50%) estimates of total mountain range SWE in the Sierra Nevada, while the global and CONUS+ datasets underestimate SWE.

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Heterogeneous snowpack response and snow drought occurrence across river basins of northwestern North America under 1.0°C to 4.0°C global warming

Climatic Change ◽

10.1007/s10584-021-02968-7 ◽

2021 ◽

Vol 164 (3-4) ◽

Cited By ~ 1

Author(s):

Rajesh R. Shrestha ◽

Barrie R. Bonsal ◽

James M. Bonnyman ◽

Alex J. Cannon ◽

Mohammad Reza Najafi

Keyword(s):

Global Warming ◽

North America ◽

Snow Water Equivalent ◽

Climate Model ◽

Regional Climate ◽

River Basins ◽

Large River ◽

Ecological Impacts ◽

Temperature And Precipitation ◽

Northwestern North America

AbstractAnthropogenic climate change is affecting the snowpack freshwater storage, with socioeconomic and ecological impacts. We present an assessment of maximum snow water equivalent (SWEmax) change in large river basins of the northwestern North America region using the Canadian Regional Climate Model 50-member ensemble under 1.0 °C to 4.0 °C global warming thresholds above the pre-industrial period. The projections indicate steep SWEmax decline in the warmer coastal/southern basins (i.e., Skeena, Fraser and Columbia), moderate decline in the milder interior basins (i.e., Peace, Athabasca and Saskatchewan), and either a small increase or decrease in the colder northern basins (i.e., Yukon, Peel, and Liard). A key factor for these spatial differences is the proximity of winter mean temperature to the freeze/melt threshold, with larger SWEmax declines for the basins closer to the threshold. Using the random forests machine-learning model, we find that the SWEmax change is primarily temperature controlled, especially for warmer basins. Further, under a categorical framework of below-normal SWEmax defined as snow drought (SD), we find that above-normal temperature and precipitation are the dominant conditions for SD occurrences under higher global warming thresholds. This implies a limited capacity of precipitation increase to compensate the temperature-driven snowpack decline. Additionally, the frequency and severity of SD occurrences are projected to be most extreme in the southern basins where current water demands are highest. Overall, the results of this study, including insights on snowpack changes, their climatic controls, and the framework for SD classification, are applicable for basins spanning a range of hydro-climatological regimes.

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Observationally constrained surface mass balance of Larsen C ice shelf, Antarctica

The Cryosphere ◽

10.5194/tc-11-2411-2017 ◽

2017 ◽

Vol 11 (6) ◽

pp. 2411-2426 ◽

Cited By ~ 7

Author(s):

Peter Kuipers Munneke ◽

Daniel McGrath ◽

Brooke Medley ◽

Adrian Luckman ◽

Suzanne Bevan ◽

...

Keyword(s):

Mass Balance ◽

Climate Model ◽

Regional Climate ◽

Snow Accumulation ◽

Airborne Radar ◽

Surface Mass Balance ◽

Spatial And Temporal Patterns ◽

Ice Shelf ◽

The West ◽

Surface Mass

Abstract. The surface mass balance (SMB) of the Larsen C ice shelf (LCIS), Antarctica, is poorly constrained due to a dearth of in situ observations. Combining several geophysical techniques, we reconstruct spatial and temporal patterns of SMB over the LCIS. Continuous time series of snow height (2.5–6 years) at five locations allow for multi-year estimates of seasonal and annual SMB over the LCIS. There is high interannual variability in SMB as well as spatial variability: in the north, SMB is 0.40 ± 0.06 to 0.41 ± 0.04 m w.e. year−1, while farther south, SMB is up to 0.50 ± 0.05 m w.e. year−1. This difference between north and south is corroborated by winter snow accumulation derived from an airborne radar survey from 2009, which showed an average snow thickness of 0.34 m w.e. north of 66° S, and 0.40 m w.e. south of 68° S. Analysis of ground-penetrating radar from several field campaigns allows for a longer-term perspective of spatial variations in SMB: a particularly strong and coherent reflection horizon below 25–44 m of water-equivalent ice and firn is observed in radargrams collected across the shelf. We propose that this horizon was formed synchronously across the ice shelf. Combining snow height observations, ground and airborne radar, and SMB output from a regional climate model yields a gridded estimate of SMB over the LCIS. It confirms that SMB increases from north to south, overprinted by a gradient of increasing SMB to the west, modulated in the west by föhn-induced sublimation. Previous observations show a strong decrease in firn air content toward the west, which we attribute to spatial patterns of melt, refreezing, and densification rather than SMB.

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Precipitation and snow cover in the Himalaya: from reanalysis to regional climate simulations

Hydrology and Earth System Sciences ◽

10.5194/hess-17-3921-2013 ◽

2013 ◽

Vol 17 (10) ◽

pp. 3921-3936 ◽

Cited By ~ 70

Author(s):

M. Ménégoz ◽

H. Gallée ◽

H. W. Jacobi

Keyword(s):

Snow Cover ◽

Climate Model ◽

Regional Climate ◽

Rain Gauge ◽

Snow Accumulation ◽

The Tibetan Plateau ◽

Monsoon Period ◽

Medium Range Weather Forecast ◽

Snow Cover Extent ◽

The Himalaya

Abstract. We applied a Regional Climate Model (RCM) to simulate precipitation and snow cover over the Himalaya, between March 2000 and December 2002. Due to its higher resolution, our model simulates a more realistic spatial variability of wind and precipitation than those of the reanalysis of the European Centre of Medium range Weather Forecast (ECMWF) used as lateral boundaries. In this region, we found very large discrepancies between the estimations of precipitation provided by reanalysis, rain gauges networks, satellite observations, and our RCM simulation. Our model clearly underestimates precipitation at the foothills of the Himalaya and in its eastern part. However, our simulation provides a first estimation of liquid and solid precipitation in high altitude areas, where satellite and rain gauge networks are not very reliable. During the two years of simulation, our model resembles the snow cover extent and duration quite accurately in these areas. Both snow accumulation and snow cover duration differ widely along the Himalaya: snowfall can occur during the whole year in western Himalaya, due to both summer monsoon and mid-latitude low pressure systems bringing moisture into this region. In Central Himalaya and on the Tibetan Plateau, a much more marked dry season occurs from October to March. Snow cover does not have a pronounced seasonal cycle in these regions, since it depends both on the quite variable duration of the monsoon and on the rare but possible occurrence of snowfall during the extra-monsoon period.

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Evaluating the ability of NA-CORDEX to simulate the seasonal modes of precipitation variability across the Western United States: Does resolution matter?

10.5194/egusphere-egu21-6999 ◽

2021 ◽

Author(s):

Jonathan Meyer ◽

Shih-Yu (Simon) Wang ◽

Robert Gillies ◽

Jin-Ho Yoon

Keyword(s):

Performance Metrics ◽

Climate Model ◽

Regional Climate ◽

Storm Track ◽

Model Performance ◽

Precipitation Variability ◽

Future Trend ◽

Spring Precipitation ◽

Precipitation Patterns ◽

The North

The western U.S. precipitation climatology simulated by the NA-CORDEX regional climate model ensembles are examined to evaluate the capability of the 0.44&#176; and 0.22&#176; resolutionensembles to reproduce 1) the annual and semi-annual precipitation cycle of several hydrologically important western U.S. regions and 2) localized seasonality in the amount and timing of precipitation. Collectively, when compared against observation-based gridded precipitation, NA-CORDEX RCMs driven by ERA-Interim reanalysis at the higher resolution 0.22&#176; domain resolution dramatically outperformed the 0.44&#176; ensemble over the 1950-2005 historical periods. Furthermore, the ability to capture the annual and semi-annual modes of variability was starkly improved in the higher resolution 0.22&#176; ensemble. The higher resolution members reproduced more consistent spatial patterns of variance featuring lower errors in magnitude&#8212;especially with respect to the winter-summer and spring-fall seasonality. A great deal of spread in model performance was found for the semi-annual cycles, although the higher-resolution ensemble exhibited a more coherent clustering of performance metrics. In general, model performance was a function of which RCM was used, while future trend scenarios seem to cluster around which GCM was downscaled. Future projections of precipitation patterns from the 0.22&#176; NA-CORDEX RCMs driven by the RCP4.5 &#8220;stabilization scenario&#8221; and the RCP8.5 &#8220;high emission&#8221; scenario were analyzed to examine trends to the &#8220;end of century&#8221; (i.e. 2050-2099) precipitation patterns. Except for the Desert Southwest&#8217;s spring season, the RCP4.5 and RCP8.5 scenarios show a consensus change towards an increase in winter and spring precipitation throughout all regions of interest with the RCP8.5 scenario containing a greater number of ensemble members simulating greater wetting trends. The future winter-summer mode of variability exhibited a general consensus towards increasing variability with greatest change found over the region&#8217;s terrain suggesting a greater year-to-year variability of the region&#8217;s orographic response to the strength and location of the mid-latitude jet streams and storm track. Increasing spring-fall precipitation variability suggests an expanding influence of tropical moisture advection associated with the North American Monsoon, although we note that like many future monsoon projections, a spring &#8220;convective barrier&#8221; was also apparent in the NA-CORDEX ensembles.

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Development and implementation of river-routing process module in a regional climate model and its evaluation in Korean river basins

Journal of Geophysical Research Atmospheres ◽

10.1002/2014jd022698 ◽

2015 ◽

Vol 120 (10) ◽

pp. 4613-4629 ◽

Cited By ~ 5

Author(s):

Ji-Woo Lee ◽

Song-You Hong ◽

Jung-Eun Esther Kim ◽

Kei Yoshimura ◽

Suryun Ham ◽

...

Keyword(s):

Regional Climate Model ◽

Climate Model ◽

Regional Climate ◽

River Basins ◽

River Routing

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Evaluation of CLASS Snow Simulation over Eastern Canada

Journal of Hydrometeorology ◽

10.1175/jhm-d-16-0153.1 ◽

2017 ◽

Vol 18 (5) ◽

pp. 1205-1225 ◽

Cited By ~ 19

Author(s):

Diana Verseghy ◽

Ross Brown ◽

Libo Wang

Keyword(s):

Snow Cover ◽

Land Surface ◽

Snow Water Equivalent ◽

Climate Model ◽

Regional Climate ◽

Eastern Canada ◽

Fractional Snow Cover ◽

Forest Regions ◽

Snow Water ◽

Snow Model

Abstract The Canadian Land Surface Scheme (CLASS), version 3.6.1, was run offline for the period 1990–2011 over a domain centered on eastern Canada, driven by atmospheric forcing data dynamically downscaled from ERA-Interim using the Canadian Regional Climate Model. The precipitation inputs were adjusted to replicate the monthly average precipitation reported in the CRU observational database. The simulated fractional snow cover and the surface albedo were evaluated using NOAA Interactive Multisensor Snow and Ice Mapping System and MODIS data, and the snow water equivalent was evaluated using CMC, Global Snow Monitoring for Climate Research (GlobSnow), and Hydro-Québec products. The modeled fractional snow cover agreed well with the observational estimates. The albedo of snow-covered areas showed a bias of up to −0.15 in boreal forest regions, owing to neglect of subgrid-scale lakes in the simulation. In June, conversely, there was a positive albedo bias in the remaining snow-covered areas, likely caused by neglect of impurities in the snow. The validation of the snow water equivalent was complicated by the fact that the three observation-based datasets differed widely. Also, the downward adjustment of the forcing precipitation clearly resulted in a low snow bias in some regions. However, where the density of the observations was high, the CLASS snow model was deemed to have performed well. Sensitivity tests confirmed the satisfactory behavior of the current parameterizations of snow thermal conductivity, snow albedo refreshment threshold, and limiting snow depth and underlined the importance of snow interception by vegetation. Overall, the study demonstrated the necessity of using a wide variety of observation-based datasets for model validation.

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Southeast Greenland high accumulation rates derived from firn cores and ground-penetrating radar

Annals of Glaciology ◽

10.3189/2013aog63a358 ◽

2013 ◽

Vol 54 (63) ◽

pp. 322-332 ◽

Cited By ~ 35

Author(s):

Clément Miège ◽

Richard R. Forster ◽

Jason E. Box ◽

Evan W. Burgess ◽

Joseph R. McConnell ◽

...

Keyword(s):

Ground Penetrating Radar ◽

Climate Model ◽

Regional Climate ◽

Elevation Gradient ◽

Greenland Ice Sheet ◽

Snow Accumulation ◽

Internal Layers ◽

Accumulation Rates ◽

High Accumulation ◽

Ground Penetrating

AbstractDespite containing only 14% of the Greenland ice sheet by area, the southeastern sector has the highest accumulation rates, and hence receives ∼30% of the total snow accumulation. We present accumulation rates obtained during our 2010 Arctic Circle Traverse derived from three 50 m firn cores dated using geochemical analysis. We tracked continuous internal reflection horizons between the firn cores using a 400 MHz ground-penetrating radar (GPR). GPR data combined with depth-age scales from the firn cores provide accumulation rates along a 70 km transect. We followed an elevation gradient from ∼2350 to ∼1830m to understand how progressive surface melt may affect the ability to chemically date the firn cores and trace the internal layers with GPR. From the firn cores, we find a 52% (∼0.43 m w.e. a-1) increase in average snow accumulation and greater interannual variability at the lower site than the upper site. The GPR profiling reveals that accumulation rates are influenced by topographic undulations on the surface, with up to 23% variability over 7 km. These measurements confirm the presence of high accumulation rates in the southeast as predicted by the calibrated regional climate model Polar MM5.

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