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  • 1. Anderson, C J
    et al.
    Arritt, R W
    Takle, E S
    Pan, Z T
    Gutowski, W J
    Otieno, F O
    da Silva, R
    Caya, D
    Christensen, J H
    Luthi, D
    Gaertner, M A
    Gallardo, C
    Giorgi, F
    Hong, S Y
    Jones, Colin
    SMHI, Research Department, Climate research - Rossby Centre.
    Juang, H M H
    Katzfey, J J
    Lapenta, W M
    Laprise, R
    Larson, J W
    Liston, G E
    McGregor, J L
    Pielke, R A
    Roads, J O
    Taylor, J A
    Hydrological processes in regional climate model simulations of the central United States flood of June-July 19932003In: Journal of Hydrometeorology, ISSN 1525-755X, E-ISSN 1525-7541, Vol. 4, no 3, p. 584-598Article in journal (Refereed)
    Abstract [en]

    Thirteen regional climate model(RCM) simulations of June - July 1993 were compared with each other and observations. Water vapor conservation and precipitation characteristics in each RCM were examined for a 108 x 10degrees subregion of the upper Mississippi River basin, containing the region of maximum 60-day accumulated precipitation in all RCMs and station reports. All RCMs produced positive precipitation minus evapotranspiration ( P - E > 0), though most RCMs produced P - E below the observed range. RCM recycling ratios were within the range estimated from observations. No evidence of common errors of E was found. In contrast, common dry bias of P was found in the simulations. Daily cycles of terms in the water vapor conservation equation were qualitatively similar in most RCMs. Nocturnal maximums of P and C ( convergence) occurred in 9 of 13 RCMs, consistent with observations. Three of the four driest simulations failed to couple P and C overnight, producing afternoon maximum P. Further, dry simulations tended to produce a larger fraction of their 60-day accumulated precipitation from low 3-h totals. In station reports, accumulation from high ( low) 3-h totals had a nocturnal ( early morning) maximum. This time lag occurred, in part, because many mesoscale convective systems had reached peak intensity overnight and had declined in intensity by early morning. None of the RCMs contained such a time lag. It is recommended that short-period experiments be performed to examine the ability of RCMs to simulate mesoscale convective systems prior to generating long-period simulations for hydroclimatology.

  • 2.
    Bosshard, Thomas
    et al.
    SMHI, Research Department, Hydrology.
    Kotlarski, Sven
    Zappa, Massimiliano
    Schaer, Christoph
    Hydrological Climate-Impact Projections for the Rhine River: GCM-RCM Uncertainty and Separate Temperature and Precipitation Effects2014In: Journal of Hydrometeorology, ISSN 1525-755X, E-ISSN 1525-7541, Vol. 15, no 2, p. 697-713Article in journal (Refereed)
    Abstract [en]

    Climate change is expected to affect the hydrological cycle, with considerable impacts on water resources. Climate-induced changes in the hydrology of the Rhine River (Europe) are of major importance for the riparian countries, as the Rhine River is the most important European waterway, serves as a freshwater supply source, and is prone to floods and droughts. Here regional climate model data from the Ensemble-Based Predictions of Climate Changes and their Impacts (ENSEMBLES) project is used to drive the hydrological model Precipitation-Runoff-Evapotranspiration-Hydrotope (PREVAH) and to assess the impact of climate change on the hydrology in the Rhine basin. Results suggest increases in monthly mean runoff during winter and decreases in summer. At the gauge Cologne and for the period 2070-99 under the A1B scenario of the Special Report on Emissions Scenarios, projected decreases in summer vary between -9% and -40% depending on the climate model used, while increases in winter are in the range of +4% to +51%. These projected changes in mean runoff are generally consistent with earlier studies, but the derived spread in the runoff projections appears to be larger. It is demonstrated that temperature effects (e.g., through altered snow processes) dominate in the Alpine tributaries, while precipitation effects dominate in the lower portion of the Rhine basin. Analyses are also presented for selected extreme runoff indices.

  • 3.
    Lucas-Picher, Philippe
    et al.
    SMHI, Research Department, Climate research - Rossby Centre.
    Boberg, Fredrik
    Christensen, Jens H.
    Berg, Peter
    SMHI, Research Department, Climate research - Rossby Centre.
    Dynamical Downscaling with Reinitializations: A Method to Generate Finescale Climate Datasets Suitable for Impact Studies2013In: Journal of Hydrometeorology, ISSN 1525-755X, E-ISSN 1525-7541, Vol. 14, no 4, p. 1159-1174Article in journal (Refereed)
    Abstract [en]

    To retain the sequence of events of a regional climate model (RCM) simulation driven by a reanalysis, a method that has not been widely adopted uses an RCM with frequent reinitializations toward its driving field. In this regard, this study highlights the benefits of an RCM simulation with frequent (daily) reinitializations compared to a standard continuous RCM simulation. Both simulations are carried out with the RCM HIRHAM5, driven with the European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Re-Analysis (ERA-Interim) data, over the 12-km-resolution European Coordinated Regional Climate Downscaling Experiment (CORDEX) domain covering the period 1989-2009. The analysis of daily precipitation shows improvements in the sequence of events and the maintenance of the added value from the standard continuous RCM simulation. The validation of the two RCM simulations with observations reveals that the simulation with reinitializations indeed improves the temporal correlation. Furthermore, the RCM simulation with reinitializations has lower systematic errors compared to the continuous simulation, which has a tendency to be too wet. A comparison of the distribution of wet day precipitation intensities shows similar added value in the continuous and reinitialized simulations with higher variability and extremes compared to the driving field ERA-Interim. Overall, the results suggest that the finescale climate dataset of the RCM simulation with reinitializations better suits the needs of impact studies by providing a sequence of events matching closely the observations, while limiting systematic errors and generating reliable added value. Downsides of the method with reinitializations are increased computational costs and the introduction of temporal discontinuities that are similar to those of a reanalysis.

  • 4.
    Olsson, Jonas
    et al.
    SMHI, Research Department, Hydrology.
    Berg, Peter
    SMHI, Research Department, Hydrology.
    Kawamura, Akira
    Impact of RCM Spatial Resolution on the Reproduction of Local, Subdaily Precipitation2015In: Journal of Hydrometeorology, ISSN 1525-755X, E-ISSN 1525-7541, Vol. 16, no 2, p. 534-547Article in journal (Refereed)
    Abstract [en]

    Many hydrological hazards are closely connected to local precipitation (extremes), especially in small and urban catchments. The use of regional climate model (RCM) data for small-scale hydrological climate change impact assessment has long been nearly unfeasible because of the low spatial resolution. The RCM resolution is, however, rapidly increasing, approaching the size of small catchments and thus potentially increasing the applicability of RCM data for this purpose. The objective of this study is to explore to what degree subhourly temporal precipitation statistics in an RCM converge to observed point statistics when gradually increasing the resolution from 50 to 6 km. This study uses precipitation simulated by RCA3 at seven locations in southern Sweden during 1995-2008. A positive impact of higher resolution was most clearly manifested in 10-yr intensity-duration-frequency (IDF) curves. At 50 km the intensities are underestimated by 50%-90%, but at 6 km they are nearly unbiased, when averaged over all locations and durations. Thus, at 6 km, RCA3 apparently generates low-frequency subdaily extremes that resemble the values found in point observations. Also, the reproduction of short-term variability and less extreme maxima were overall improved with increasing resolution. For monthly totals, a slightly increased overestimation with increasing resolution was found. The bias in terms of wet fraction and wet spell characteristics was overall not strongly dependent on resolution. These metrics are, however, influenced by the cutoff threshold used to separate between wet and dry time steps as well as the wet spell definition.

  • 5. Ott, Irena
    et al.
    Duethmann, Doris
    Liebert, Joachim
    Berg, Peter
    SMHI, Research Department, Climate research - Rossby Centre.
    Feldmann, Hendrik
    Ihringer, Juergen
    Kunstmann, Harald
    Merz, Bruno
    Schaedler, Gerd
    Wagner, Sven
    High-Resolution Climate Change Impact Analysis on Medium-Sized River Catchments in Germany: An Ensemble Assessment2013In: Journal of Hydrometeorology, ISSN 1525-755X, E-ISSN 1525-7541, Vol. 14, no 4, p. 1175-1193Article in journal (Refereed)
    Abstract [en]

    The impact of climate change on three small- to medium-sized river catchments (Ammer, Mulde, and Ruhr) in Germany is investigated for the near future (2021-50) following the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) A1B scenario. A 10-member ensemble of hydrological model (HM) simulations, based on two high-resolution regional climate models (RCMs) driven by two global climate models (GCMs), with three realizations of ECHAM5 (E5) and one realization of the Canadian Centre for Climate Modelling and Analysis version 3 (CCCma3; C3) is established. All GCM simulations are downscaled by the RCM Community Land Model (CLM), and one realization of E5 is downscaled also with the RCM Weather Research and Forecasting Model (WRF). This concerted 7-km, high-resolution RCM ensemble provides a sound basis for runoff simulations of small catchments and is currently unique for Germany. The hydrology for each catchment is simulated in an overlapping scheme, with two of the three HMs used in the project. The resulting ensemble hence contains for each chain link (GCM-realization-RCM-HM) at least two members and allows the investigation of qualitative and limited quantitative indications of the existence and uncertainty range of the change signal. The ensemble spread in the climate change signal is large and varies with catchment and season, and the results show that most of the uncertainty of the change signal arises from the natural variability in winter and from the RCMs in summer.

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