Streamflow variability over the 1881–2011 period in northern Québec: comparison of hydrological
reconstructions based on tree rings and geopotential height
field reanalysis

Brigode, Pierre; Brissette, François; Nicault, Antoine; Perreault, Luc; Kuentz, Anna; Mathevet, Thibault; Gailhard, Joël

doi:10.5194/cp-12-1785-2016

Cited by 26 publications

(32 citation statements)

References 60 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…(; ) for more details). D TW focuses on air flows since this distance involves gradients of absolute values of geopotential heights (Woodcock, ; Obled et al, ; Bontron, ; Wetterhall et al, ; Brigode et al, ). The formula for estimating D TW between two synoptic situations (Z1) and (Z2) characterized by geopotential height fields on a gridded domain oriented south–north (index i ) and west–east (index j ) is

D_{TW} = \frac{\sum_{i, j} (||, e_{G}^{i}) + \sum_{i, j} (||, e_{G}^{j})}{\sum_{i, j} (||, G_{L}^{i}) + \sum_{i, j} (||, G_{L}^{j})} \times 100,

where e G is the difference, around a given grid point, between the Z1 and Z2 geopotential gradients, while G L is the maximum of these two gradients in the direction considered ( i or j ),

(||, e_{G}^{i}) = (||, ((), normalZ 1_{i, j} - normalZ 1_{i + 1, 1}) - ((), normalZ 2_{i, j} - normalZ 2_{i + 1, 1})),

(||, e_{G}^{j}) = (||, ((), normalZ 1_{i, j} - normalZ 1_{i, j + 1}) - ((), normalZ 2_{i, j} - normalZ 2_{i, j + 1})),

(||, G_{L}^{i}) = max ((),, |Z 1_{i, j} - Z 1_{i + 1, 1}|, |Z 2_{i, j ...}|)

…”

Section: Methodsmentioning

confidence: 99%

“…Teweles and Wobus (1954) distances (noted D TW hereafter) are calculated to find the closest WP to each considered day (see Brigode et al (2013a;2013b) for more details). D TW focuses on air flows since this distance involves gradients of absolute values of geopotential heights (Woodcock, 1980;Obled et al, 2002;Bontron, 2004;Wetterhall et al, 2005;Brigode et al, 2016). The formula for estimating D TW between two synoptic situations (Z1) and (Z2) characterized by geopotential height fields on a gridded domain oriented south-north (index i) and westeast (index j) is…”

Section: Classification Of the Historical Periodmentioning

confidence: 99%

See 1 more Smart Citation

Changes in French weather pattern seasonal frequencies projected by a CMIP5 ensemble

Brigode

Gérardin

Bernardara

et al. 2018

Intl Journal of Climatology

Self Cite

View full text Add to dashboard Cite

Over the last decades, general circulation model (GCM) simulations have been regularly evaluated in terms of their ability to reproduce the historical frequency of significantly recurrent weather patterns (WP) observed at the regional scale. Thus, a good simulation of the frequency of these particular WP by the GCM is generally conditioning the good representation of the regional statistics of surface variables such as temperature and precipitation. In this paper, the seasonal frequency of eight particular WP have been calculated using the daily geopotential height fields simulated by an ensemble of 26 Coupled Model Intercomparison Project Phase 5 (CMIP5) GCM. These WP are known as significantly influencing the French regional hydro‐climatology in terms of both frequency of low‐flows and high‐precipitation events. Four different bias correction methods have been applied on the simulated geopotential height fields before the calculation of the seasonal WP frequencies. The GCM ensemble showed overall good performances in terms of the simulation of WP seasonal frequencies. The application of a spatially and temporally non‐homogenous correction of simulated geopotential height fields improved significantly the simulation of WP frequencies for the four seasons. Finally, the evolution of the WP frequencies over the next century has been quantified. Three WP (WP2, WP4 and WP8) have pronounced seasonal changes, with WP2 and WP4 being less frequent in summer and autumn seasons, respectively, while WP8 being more frequent over spring, summer and autumn seasons. The strong simulated frequency evolution of WP2 and WP8 is an interesting result, which predicts the climate to be drier with time for France. Thus, WP2 (western oceanic circulation), grouping rainy days over the northern France region, is simulated as less frequent in future summers, while WP8 (anticyclonic situations), which groups non‐rainy days over France, is simulated as more frequent in future summers.

show abstract

D_{TW} = \frac{\sum_{i, j} (||, e_{G}^{i}) + \sum_{i, j} (||, e_{G}^{j})}{\sum_{i, j} (||, G_{L}^{i}) + \sum_{i, j} (||, G_{L}^{j})} \times 100,

where e G is the difference, around a given grid point, between the Z1 and Z2 geopotential gradients, while G L is the maximum of these two gradients in the direction considered ( i or j ),

(||, e_{G}^{i}) = (||, ((), normalZ 1_{i, j} - normalZ 1_{i + 1, 1}) - ((), normalZ 2_{i, j} - normalZ 2_{i + 1, 1})),

(||, e_{G}^{j}) = (||, ((), normalZ 1_{i, j} - normalZ 1_{i, j + 1}) - ((), normalZ 2_{i, j} - normalZ 2_{i, j + 1})),

(||, G_{L}^{i}) = max ((),, |Z 1_{i, j} - Z 1_{i + 1, 1}|, |Z 2_{i, j ...}|)

…”

Section: Methodsmentioning

confidence: 99%

Section: Classification Of the Historical Periodmentioning

confidence: 99%

Changes in French weather pattern seasonal frequencies projected by a CMIP5 ensemble

Brigode

Gérardin

Bernardara

et al. 2018

Intl Journal of Climatology

Self Cite

View full text Add to dashboard Cite

show abstract

“…Kuentz et al (2013) reconstructed the 20th century hydrological variability of the Durance catchment (southern French Alps) based on an analogue downscaling method (Kuentz et al, 2015) and a lumped conceptual hydrological model. More recently, Brigode et al (2016) applied the same downscaling method and a hydrological model to reconstruct streamflow variability in a northern Québec catchment. Few studies have been performed at a country scale, with the exception of Dayon (2015), who used a deterministic statistical downscaling approach combined with a physically based hydrological model to reconstruct hydrometeorological data in France.…”

Section: Introductionmentioning

confidence: 99%

Reply to Referee #1

Caillouet¹

2016

View full text Add to dashboard Cite

show abstract

“…It derives from the widely used GR4J model (Perrin et al, 2003) -which has been used recently in a reconstruction context by Brigode et al (2016) -with a fifth parameter added to better model exchanges between surface and groundwater (Le Moine, 2008) and a sixth parameter added to better model low-flow periods (Pushpalatha et al, 2011). GR6J has been intensively used in France, in particular for low-flow studies (see Pushpalatha et al, 2012).…”

Section: Hydrological Modellingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Ensemble reconstruction of spatio-temporal extreme low-flow events in France since 1871

Caillouet¹,

Vidal²,

Sauquet³

et al. 2017

Hydrol. Earth Syst. Sci.

View full text Add to dashboard Cite

Abstract. The length of streamflow observations is generally limited to the last 50 years even in data-rich countries like France. It therefore offers too small a sample of extreme low-flow events to properly explore the long-term evolution of their characteristics and associated impacts. To overcome this limit, this work first presents a daily 140-year ensemble reconstructed streamflow dataset for a reference network of near-natural catchments in France. This dataset, called SCOPE Hydro (Spatially COherent Probabilistic Extended Hydrological dataset), is based on (1) a probabilistic precipitation, temperature, and reference evapotranspiration downscaling of the Twentieth Century Reanalysis over France, called SCOPE Climate, and (2) continuous hydrological modelling using SCOPE Climate as forcings over the whole period. This work then introduces tools for defining spatio-temporal extreme low-flow events. Extreme low-flow events are first locally defined through the sequent peak algorithm using a novel combination of a fixed threshold and a daily variable threshold. A dedicated spatial matching procedure is then established to identify spatiotemporal events across France. This procedure is furthermore adapted to the SCOPE Hydro 25-member ensemble to characterize in a probabilistic way unrecorded historical events at the national scale. Extreme low-flow events are described and compared in a spatially and temporally homogeneous way over 140 years on a large set of catchments. Results highlight well-known recent events like 1976 or 1989-1990, but also older and relatively forgotten ones like the 1878 and 1893 events. These results contribute to improving our knowledge of historical events and provide a selection of benchmark events for climate change adaptation purposes. Moreover, this study allows for further detailed analyses of the effect of climate variability and anthropogenic climate change on low-flow hydrology at the scale of France.

show abstract

Streamflow variability over the 1881–2011 period in northern Québec: comparison of hydrological reconstructions based on tree rings and geopotential height field reanalysis

Cited by 26 publications

References 60 publications

Changes in French weather pattern seasonal frequencies projected by a CMIP5 ensemble

Changes in French weather pattern seasonal frequencies projected by a CMIP5 ensemble

Reply to Referee #1

Ensemble reconstruction of spatio-temporal extreme low-flow events in France since 1871

Contact Info

Product

Resources

About