Intercomparison of different uncertainty sources in hydrological climate change projections for an alpine catchment (upper Clutha River, New Zealand)

Jobst, Andreas M.; Kingston, Daniel G.; Cullen, Nicolas J.; Schmid, Josef

doi:10.5194/hess-22-3125-2018

Cited by 28 publications

(18 citation statements)

References 51 publications

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“…In some of them, the GCM structure is identified as the dominant source of uncertainty, e.g., [42][43][44]. A common finding for other studies is that in the hydrological model, uncertainty is less important than other sources but cannot be ignored [45][46][47]. Ideally, the analysis of hydrologic change in future studies should comprehend the full suite of uncertainties associated with global climate modeling, climate downscaling, hydrologic modeling, and natural climate variability.…”

Section: Discussionmentioning

confidence: 99%

Projected Changes in the Water Budget for Eastern Colombia Due to Climate Change

Molina

Luong

Bernhofer

2019

Water

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There is a lack of information about the effect of climate change on the water budget for the eastern side of Colombia, which is currently experiencing an increased pressure on its water resources due to the demand for food, industrial use, and human demand for drinking and hygiene. In this study, the lumped model BROOK90 was utilized with input based on the available historical and projected meteorological data, as well as land use and soil information. With this data, we were able to determine the changes in the water balance components in four different regions, representing four different water districts in Eastern Colombia. These four regions reflect four different sets of climate and geographic conditions. The projected data were obtained using the Statistical Downscaling Model (SDSM), in which two global climate models were used in addition to two different climate scenarios from each. These are the Representative Concentration Pathways (RCP) RCP 2.6 and RCP 8.5. Results showed that the temporal and spatial distribution of water balance components were considerably affected by the changing climate. A reduction in the generated streamflow for all of the studied regions is shown and changes in the evapotranspiration and stored water were varied for each region according to both the climate scenario as well as the characteristics of soil and land use for each area. The results of spatial change of the water balance components showed a direct link to the geography of each region. Soil moisture was reduced considerably in the next decades, and the percentage of decrease varied for each scenario.

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Section: Discussionmentioning

confidence: 99%

Projected Changes in the Water Budget for Eastern Colombia Due to Climate Change

Molina

Luong

Bernhofer

2019

Water

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“…Precipitation was also interpolated using a trivariate spline, with a 30-year normal surface included as a covariate (Jobst, 2017 3. Global gridded (2.5 • ) NCEP/NCAR meteorological reanalysis data (Kalnay et al, 1996), used as input fields for the HYSPLIT (version 4) model. Data were acquired from the Climate Data Center (CDC) via the FTP module within the HYSPLIT software.…”

Section: Climatic Influences On Snow Cover Variabilitymentioning

confidence: 99%

Characterising spatio-temporal variability in seasonal snow cover at a regional scale from MODIS data: the Clutha Catchment, New Zealand

Redpath

Sirguey

Cullen

2019

Hydrol. Earth Syst. Sci.

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Abstract. A 16-year series of daily snow-covered area (SCA) for 2000–2016 is derived from MODIS imagery to produce a regional-scale snow cover climatology for New Zealand's largest catchment, the Clutha Catchment. Filling a geographic gap in observations of seasonal snow, this record provides a basis for understanding spatio-temporal variability in seasonal snow cover and, combined with climatic data, provides insight into controls on variability. Seasonal snow cover metrics including daily SCA, mean snow cover duration (SCD), annual SCD anomaly and daily snowline elevation (SLE) were derived and assessed for temporal trends. Modes of spatial variability were characterised, whilst also preserving temporal signals by applying raster principal component analysis (rPCA) to maps of annual SCD anomaly. Sensitivity of SCD to temperature and precipitation variability was assessed in a semi-distributed way for mountain ranges across the catchment. The influence of anomalous winter air flow, as characterised by HYSPLIT back-trajectories, on SCD variability was also assessed. On average, SCA peaks in late June, at around 30 % of the catchment area, with 10 % of the catchment area sustaining snow cover for > 120 d yr−1. A persistent mid-winter reduction in SCA, prior to a second peak in August, is attributed to the prevalence of winter blocking highs in the New Zealand region. In contrast to other regions globally, no significant decrease in SCD was observed, but substantial spatial and temporal variability was present. rPCA identified six distinct modes of spatial variability, characterising 77 % of the observed variability in SCD. This analysis of SCD anomalies revealed strong spatio-temporal variability beyond that associated with topographic controls, which can result in snow cover conditions being out of phase across the catchment. Furthermore, it is demonstrated that the sensitivity of SCD to temperature and precipitation variability varies significantly across the catchment. While two large-scale climate modes, the SOI and SAM, fail to explain observed variability, specific spatial modes of SCD are favoured by anomalous airflow from the NE, E and SE. These findings illustrate the complexity of atmospheric controls on SCD within the catchment and support the need to incorporate atmospheric processes that govern variability of the energy balance, as well as the re-distribution of snow by wind in order to improve the modelling of future changes in seasonal snow.

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“…Then, areas of mountain ranges above this elevation were manually digitised using a DEM (Columbus et al, 2011) and stream centreline vector data (Snelder et al, 2010) as guidance ( Figure 3). Since the Main Divide of the Southern Alps is considered to provide a baseline for climatic gradients in the east of the South Island, owing to predominant westerly air flow and the substantial orographic effects of the Southern Alps (Sinclair et al, 1997;Jobst et al, 2018), the distance from each range to the main divide of the Southern Alps was calculated using the Near tool in ArcGIS v10.3. Mean annual SCD anomalies for each range were then extracted from the maps calculated in Section 3.3.2.…”

Section: Mountain Range Analysismentioning

confidence: 99%

“…While water management is not a new concept in these areas, the role of snow in the hydrological cycle, and the impact of variability in the extent and duration of winter snow cover in the Central Otago mountain ranges, has received little attention. While modelling studies indicate that significant future changes in the snow hydrology of the Clutha Catchment are likely (e.g., Poyck et al, 2011;Jobst, 2017;Jobst et al, 2018), observational studies of snow hydrology have been discontinuous and mostly limited to small sub-catchments (e.g., Fitzharris et al, 1980;Fitzharris and Grimmond, 1982;Sims and Orwin, 2011).…”

mentioning

confidence: 99%

Charactersing spatio-temporal variability in seasonal snow cover at a regional scale from MODIS data: The Clutha Catchment, New Zealand

Redpath¹,

Sirguey²,

Cullen³

2019

Preprint

Self Cite

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Abstract. A 16-year series of daily snow covered area (SCA) for 2000–2016 is derived from MODIS imagery to produce a regional scale snow cover climatology for New Zealand's largest catchment, the Clutha Catchment. Filling a geographic gap in observations of seasonal snow, this record provides a basis for understanding spatio-temporal variability in seasonal snow cover, and combined with climatic data, provides insight into controls on variability. Metrics including daily SCA, mean snow cover duration (SCD), annual SCD anomaly and daily snowline elevation (SLE) were derived and assessed for temporal trends. Raster principal components analysis (rPCA) was applied to maps of annual SCD anomaly to characterise modes of spatial variability whilst preserving temporal signals. Semi-distributed analysis between SCD and temperature and precipitation anomalies allowed sensitivity of SCD to climatic forcings to be assessed spatially. The influence of anomalous winter air flow, as characterised by HYSPLIT back-trajectories, on SCD variability was also assessed. On average, SCA peaks in late June, at around 30 % of the catchment area, with 10 % of the catchment area sustaining snow cover for > 120 days per year. A reduction in SCA through mid-winter, prior to a second peak in August and persistent throughout the time series is attributed to the prevalence of winter blocking highs in the New Zealand region. In contrast to other regions globally, no significant decrease in SCD was observed. rPCA identified six distinct modes of spatial variability, characterising 77 % of the observed variability in SCD. rPCA and semi-distributed analysis of SCD anomalies reveal strong spatio-temporal variability beyond that associated with topographic controls, which can result in snow cover conditions being out of phase across the catchment. Furthermore, it is demonstrated that the sensitivity of SCD to temperature and precipitation variability varies significantly across the catchment. While two large scale climate modes, the SOI and SAM, fail to explain observed variability, specific spatial modes of SCD are favoured by anomalous airflow from the NE, E and SE. These findings illustrate the complexity of atmospheric controls on SCD within the catchment and support the need to incorporate atmospheric processes that govern variability of the energy balance, as well as the re-distribution of snow by wind in order to improve the modelling of future changes in seasonal snow.

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Intercomparison of different uncertainty sources in hydrological climate change projections for an alpine catchment (upper Clutha River, New Zealand)

Cited by 28 publications

References 51 publications

Projected Changes in the Water Budget for Eastern Colombia Due to Climate Change

Projected Changes in the Water Budget for Eastern Colombia Due to Climate Change

Characterising spatio-temporal variability in seasonal snow cover at a regional scale from MODIS data: the Clutha Catchment, New Zealand

Charactersing spatio-temporal variability in seasonal snow cover at a regional scale from MODIS data: The Clutha Catchment, New Zealand

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