Precipitation downscaling under climate change: Recent developments to bridge the gap between dynamical models and the end user

Maraun, Douglas; Wetterhall, F.; Ireson, A. M.; Chandler, Richard E.; Kendon, Elizabeth J.; Widmann, Martin; Brienen, Susanne; Rust, Henning W.; Sauter, Tobias; Themeßl, Matthias; Venema, Victor; Chun, Kwok Pan; Goodess, C. M.; Jones, R. G.; Onof, Christian; Vrac, Mathieu; Thiele-Eich, Insa

doi:10.1029/2009rg000314

Cited by 1,450 publications

(1,350 citation statements)

References 278 publications

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“…Consequently, it is assumed that the observed biases in the mean and variability of those climate parameters are systematic and will be the same in the future, but it remains to be determined whether the climate model errors are static over time (Maraun et al, 2010). Use of bias correction methods leads to a better fit of the hydrological model output, narrower variability bounds, and improved observed runoff regimes compared to uncorrected climate model data (Bosshard, 2011;Teutschbein and Seibert, 2012).…”

Section: Downscaling and Bias Correctionmentioning

confidence: 99%

Climate impact on floods: changes in high flows in Sweden in the past and the future (1911–2100)

Arheimer

Lindström

2015

Hydrol. Earth Syst. Sci.

130

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Abstract. There is an ongoing discussion whether floods occur more frequently today than in the past, and whether they will increase in number and magnitude in the future. To explore this issue in Sweden, we merged observed time series for the past century from 69 gauging sites throughout the country (450 000 km 2 ) with high-resolution dynamic model projections of the upcoming century. The results show that the changes in annual maximum daily flows in Sweden oscillate between dry and wet periods but exhibit no significant trend over the past 100 years. Temperature was found to be the strongest climate driver of changes in river high flows, which are related primarily to snowmelt in Sweden. Annual daily high flows may decrease by on average −1 % per decade in the future, mainly due to lower peaks from snowmelt in the spring (−2 % per decade) as a result of higher temperatures and a shorter snow season. In contrast, autumn flows may increase by +3 % per decade due to more intense rainfall. This indicates a shift in floodgenerating processes in the future, with greater influence of rain-fed floods. Changes in climate may have a more significant impact on some specific rivers than on the average for the whole country. Our results suggest that the temporal pattern in future daily high flow in some catchments will shift in time, with spring floods in the northern-central part of Sweden occurring about 1 month earlier than today. High flows in the southern part of the country may become more frequent. Moreover, the current boundary between snow-driven floods in northern-central Sweden and rain-driven floods in the south may move toward higher latitudes due to less snow accumulation in the south and at low altitudes. The findings also indicate a tendency in observations toward the modeled projections for timing of daily high flows over the last 25 years. Uncertainties related to both the observed data and the complex model chain of climate impact assessments in hydrology are discussed.

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Section: Downscaling and Bias Correctionmentioning

confidence: 99%

Climate impact on floods: changes in high flows in Sweden in the past and the future (1911–2100)

Arheimer

Lindström

2015

Hydrol. Earth Syst. Sci.

130

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“…Forecast verification requires good observational data (Maraun et al, 2010) and robust verification methodologies. Over East Africa, a sparse climatological station network limits use of pure in situ observations to verify gridded forecast products.…”

Section: Data Descriptionmentioning

confidence: 99%

Skill of ECMWF system‐4 ensemble seasonal climate forecasts for East Africa

Ogutu

Franssen

Supit

et al. 2016

Intl Journal of Climatology

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This study evaluates the potential use of the ECMWF System-4 seasonal forecasts (S4) for impact analysis over East Africa. For use, these forecasts should have skill and small biases. We used the 15-member ensemble of 7-month forecasts initiated every month, and tested forecast skill of precipitation (tp), near-surface air temperature (tas) and surface downwelling shortwave radiation (rsds). We validated the 30-year (1981-2010) hindcast version of S4 against the WFDEI reanalysis (WATCH Forcing Data ERA-Interim) and to independent relevant observational data sets. Probabilistic skill is assessed using anomaly correlation, ranked probability skill score (RPSS) and the relative operating curve skill score (ROCSS) at both grid cell and over six distinct homogeneous rainfall regions for the three growing seasons of East Africa (i.e. MAM, JJA and OND).S4 exhibits a wet bias in OND, a dry bias in MAM and a mix of both in JJA. Temperature biases are similar in all seasons, constant with lead-time and correlate with elevation. Biases in rsds correlate with cloud/rain patterns. Bias correction clears biases but does not affect probabilistic skills.Predictability of the three variables varies with season, location and lead-time. The choice of validating dataset plays little role in the regional patterns and magnitudes of probabilistic skill scores. The OND tp forecasts show skill over a larger area up to 3 months lead-time compared to MAM and JJA. Upper-and lower-tercile tp forecasts are 20-80% better than climatology. Temperature forecasts are skillful for at least 3 months lead-time and they are 40-100% better than climatology. The rsds is less skillful than tp and tas in all seasons when verified against WFDEI but higher in all lead months against the alternative datasets. The forecast system captures El-Niño Southern Oscillation (ENSO)-related anomalous years with region-dependent skill.

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“…Bavarian Adaptation Strategy in 2009) level. Before taking the step of impact-modeling -using regional climate projections to drive hydrological models (Fowler et al, 2007;Maraun et al, 2010) -a first approach in assessing possible changes in runoff is to analyze measured runoff time series (e.g. Mudelsee et al, 2006;Kundzewicz et al, 2005).…”

Section: Introductionmentioning

confidence: 99%

Changes in runoff time series in Thuringia, Germany – Mann-Kendall trend test and extreme value analysis

Danneberg

2012

Adv. Geosci.

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Abstract. Qualified knowledge about the impacts of climate change on hydrology is needed for the derivation of adaptation measures in the water sector. As temperature and precipitation time series in Thuringia, Germany of the last 50 years reveal that the climate is becoming warmer and drier in summer and wetter in winter, the question of changes in runoff time series arises. In the presented study, simple robust analysis approaches to detect changes in runoff characteristics are applied. A selection of 19 anthropogenically undisturbed Thuringian catchments with daily runoff time series of up to 78 years without gaps, covering different landscapes and climatic conditions in Thuringia, is made. Indicators of mean, high, and low runoff in the hydrological year, winter and summer are derived and tested for trends, using the non-

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Precipitation downscaling under climate change: Recent developments to bridge the gap between dynamical models and the end user

Cited by 1,450 publications

References 278 publications

Climate impact on floods: changes in high flows in Sweden in the past and the future (1911–2100)

Climate impact on floods: changes in high flows in Sweden in the past and the future (1911–2100)

Skill of ECMWF system‐4 ensemble seasonal climate forecasts for East Africa

Changes in runoff time series in Thuringia, Germany – Mann-Kendall trend test and extreme value analysis

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