| 1. |
- Kauffeldt, Anna, et al.
(författare)
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Imbalanced land surface water budgets in a numerical weather prediction system
- 2015
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Ingår i: Geophysical Research Letters. - 0094-8276 .- 1944-8007. ; 42:11, s. 4411-4417
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Tidskriftsartikel (refereegranskat)abstract
- There has been a significant increase in the skill and resolution of numerical weather prediction models (NWPs) in recent decades, extending the time scales of useful weather predictions. The land surface models (LSMs) of NWPs are often employed in hydrological applications, which raises the question of how hydrologically representative LSMs really are. In this paper, precipitation (P), evaporation (E), and runoff (R) from the European Centre for Medium-Range Weather Forecasts global models were evaluated against observational products. The forecasts differ substantially from observed data for key hydrological variables. In addition, imbalanced surface water budgets, mostly caused by data assimilation, were found on both global (P-E) and basin scales (P-E-R), with the latter being more important. Modeled surface fluxes should be used with care in hydrological applications, and further improvement in LSMs in terms of process descriptions, resolution, and estimation of uncertainties is needed to accurately describe the land surface water budgets.
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| 3. |
- Quesada Montano, Beatriz, et al.
(författare)
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Characterising droughts in Central America with uncertain hydro-meteorological data
- 2019
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Ingår i: Journal of Theoretical and Applied Climatology. - : Springer Science and Business Media LLC. - 0177-798X .- 1434-4483. ; 137:3-4, s. 2125-2138
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Tidskriftsartikel (refereegranskat)abstract
- Central America is frequently affected by droughts that cause significant socio-economic and environmental problems. Drought characterisation, monitoring and forecasting are potentially useful to support water resource management. Drought indices are designed for these purposes, but their ability to characterise droughts depends on the characteristics of the regional climate and the quality of the available data. Local comprehensive and high-quality observational networks of meteorological and hydrological data are not available, which limits the choice of drought indices and makes it important to assess available datasets. This study evaluated which combinations of drought index and meteorological dataset were most suitable for characterising droughts in the region. We evaluated the standardised precipitation index (SPI), a modified version of the deciles index (DI), the standardised precipitation evapotranspiration index (SPEI) and the effective drought index (EDI). These were calculated using precipitation data from the Climate Hazards Group Infra-Red Precipitation with Station (CHIRPS), the CRN073 dataset, the Climate Research Unit (CRU), ECMWF Reanalysis (ERA-Interim) and a regional station dataset, and temperature from the CRU and ERA-Interim datasets. The gridded meteorological precipitation datasets were compared to assess how well they captured key features of the regional climate. The performance of all the drought indices calculated with all the meteorological datasets was then evaluated against a drought index calculated using river discharge data. Results showed that the selection of database was more important than the selection of drought index and that the best combinations were the EDI and DI calculated with CHIRPS and CRN073. Results also highlighted the importance of including indices like SPEI for drought assessment in Central America.
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| 4. |
- Quesada-Montano, Beatriz, 1984-
(författare)
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Hydro-Climatic Variability and Change in Central America : Supporting Risk Reduction Through Improved Analyses and Data
- 2017
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Floods and droughts are frequent in Central America and cause large social, economic and environmental impacts. A crucial step in disaster risk reduction is to have a good understanding of the causing mechanisms of extreme events and their spatio-temporal characteristics. For this, a key aspect is access to a dense network of long and good-quality hydro-meteorological data. Unfortunately, such ideal data are sparse or non-existent in Central America. In addition, the existing methods for hydro-climatic studies need to be revised and/or improved to find the most suitable for the region’s climate, geography and hydro-climatic data situation. This work has the ultimate goal to support the reduction of risks associated with hydro-climatic-induced disasters in Central America. This was sought by developing ways to reduce data-related uncertainties and by improving the available methods to study and understand hydro-climatic variability processes. In terms of data-uncertainty reduction, this thesis includes the development of a high resolution air temperature dataset and a methodology to reduce uncertainties in a hydrological model at ungauged basins. The dataset was able to capture the spatial patterns with a detail not available with existing datasets. The methodology significantly reduced uncertainties in an assumed-to-be ungauged catchment. In terms of methodological improvements, this thesis includes an assessment of the most suitable combination of (available) meteorological datasets and drought indices to characterise droughts in Central America. In addition, a methodology was developed to analyse drought propagation in a tropical catchment, in an automated, objective way. Results from the assessment and the drought propagation analysis contributed with improving the understanding of drought patterns and generating processes in the region. Finally, a methodology was proposed for assessing changes in both hydrological extremes in a consistent way. This contrasts with most commonly used frameworks that study each extreme individually. The method provides important characteristics (frequency, duration and magnitude), information that can be useful for decisions within risk reduction and water management. The results presented in this thesis are a contribution, in terms of hydro-climatic data and assessment methods, for supporting risk reduction of disasters related with hydro-climatic extremes in Central America.
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| 5. |
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| 6. |
- Wetterhall, Fredrik, et al.
(författare)
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Daily precipitation-downscaling techniques in three Chinese regions
- 2006
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Ingår i: Water resources research. - 0043-1397 .- 1944-7973. ; 42:11, s. W11423-
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Tidskriftsartikel (refereegranskat)abstract
- Four methods of statistical downscaling of daily precipitation were evaluated on three catchments located in southern, eastern, and central China. The evaluation focused on seasonal variation of statistical properties of precipitation and indices describing the precipitation regime, e. g., maximum length of dry spell and maximum 5-day precipitation, as well as interannual and intra-annual variations of precipitation. The predictors used in this study were mean sea level pressure, geopotential heights at 1000, 850, 700, and 500 hPa, and specific humidity as well as horizontal winds at 850, 700, and 500 hPa levels from the NCEP/NCAR reanalysis with 2.5 degrees x 2.5 degrees resolution for 1961 - 2000. The predictand was daily precipitation from 13 stations. Two analogue methods, one using principal components analysis (PCA) and the other Teweles-Wobus scores (TWS), a multiregression technique with a weather generator producing precipitation (SDSM) and a fuzzy-rule-based weather-pattern-classification method (MOFRBC), were used. Temporal and spatial properties of the predictors were carefully evaluated to derive the optimum setting for each method, and MOFRBC and SDSM were implemented in two modes, with and without humidity as predictor. The results showed that ( 1) precipitation was most successfully downscaled in the southern and eastern catchments located close to the coast, ( 2) winter properties were generally better downscaled, ( 3) MOFRBC and SDSM performed overall better than the analogue methods, ( 4) the modeled interannual variation in precipitation was improved when humidity was added to the predictor set, and ( 5), the annual precipitation cycle was well captured with all methods.
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| 8. |
- Wetterhall, Fredrik, et al.
(författare)
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Seasonality properties of four statistical-downscaling methods in central Sweden
- 2007
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Ingår i: Journal of Theoretical and Applied Climatology. - : Springer Science and Business Media LLC. - 0177-798X .- 1434-4483. ; 87:1-4, s. 123-137
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Tidskriftsartikel (refereegranskat)abstract
- Daily precipitation in northern Europe has different statistical properties depending on season. In this study, four statistical downscaling methods were evaluated in terms of their ability to capture statistical properties of daily precipitation in different seasons. Two of the methods were analogue downscaling methods; one using principal component analysis (PCA) and one using gradients in the pressure field (Teweles-Wobus scores, TWS) to select the analogues in the predictor field. The other two methods were conditional-probability methods; one using classification of weather patterns (MOFRBC) and the other using a regression method conditioning a stochastic weather generator (SDSM). The two analogue methods were used as benchmark methods. The study was performed on seven precipitation stations in south-central Sweden and the large-scale predictor was gridded mean-sea-level pressure over Northern Europe. The four methods were trained and calibrated on 25 years of data (1961–1978, 1994–2000) and validated on 15 years (1979–1993). Temporal and spatial limitations were imposed on the methods to find the optimum predictor settings for the downscaling. The quality measures used for evaluating the downscaling methods were the residuals of a number of key statistical properties, and the ranked probability scores (RPS) for precipitation and maximum length of dry and wet spells. The results showed that (1) the MOFRBC and SDSM outperformed the other methods for the RPS, (2) the statistical properties for the analogue methods were better during winter and autumn; for SDSM and TWS during spring; and for MOFRBC during summer, (3) larger predictor areas were needed for summer and autumn precipitation than winter and spring, and (4) no method could well capture the difference between dry and wet summers.
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