- T.A. Buishand (1)
- D. Clark (1)
- S. Folwell (1)
- W.H.P. Franssen (1)
- D. Gerten (1)
- S. Gomes (1)
- S. Gosling (1)
- I. Haddeland (1)
- S. Hagemann (1)
- N. Hanasaki (1)
- R. Harding (1)
- W. Hazeleger (1)
- J. Heinke (1)
- B.J.J.M. Hurk van den (1)
- P. Kabat (1)
- C.A. Katsman (1)
- S. Koirala (1)
- R. Leemans (1)
- E.C. Linden van der (1)
- F. Ludwig (1)
- T. Oki (1)
- S.C. Pelt van (1)
- A.J. Pitman (1)
- J. Polcher (1)
- J. Schellekens (1)
- T. Stacke (1)
- P. Viterbo (1)
- F. Voss (1)
- H. Wang (1)
- G.P. Weedon (1)
- P. Yeh (1)
- M. Zhao (1)
Uncertainty in the future change of extreme precipitation over the Rhine basin: the role of internal climate variability
Pelt, S.C. van; Beersma, J.J. ; Buishand, T.A. ; Hurk, B.J.J.M. van den; Schellekens, J. - \ 2015
Climate Dynamics 44 (2015)7. - ISSN 0930-7575 - p. 1789 - 1800.
klimaatverandering - neerslag - hydrologie van stroomgebieden - risicoanalyse - rijn - climatic change - precipitation - catchment hydrology - risk analysis - river rhine - local precipitation - change simulations - model - temperature - quantification - frequency - ensemble - version - gcm
Future changes in extreme multi-day precipitation will influence the probability of floods in the river Rhine basin. In this paper the spread of the changes projected by climate models at the end of this century (2081–2100) is studied for a 17-member ensemble of a single Global Climate Model (GCM) and results from the Coupled Model Intercomparison Project Phase 3 (CMIP3) ensemble. All climate models were driven by the IPCC SRES A1B emission scenario. An analysis of variance model is formulated to disentangle the contributions from systematic differences between GCMs and internal climate variability. Both the changes in the mean and characteristics of extremes are considered. To estimate variances due to internal climate variability a bootstrap method was used. The changes from the GCM simulations were linked to the local scale using an advanced non-linear delta change approach. This approach uses climate responses of the GCM to transform the daily precipitation of 134 sub-basins of the river Rhine. The transformed precipitation series was used as input for the hydrological Hydrologiska Byråns Vattenbalansavdelning model to simulate future river discharges. Internal climate variability accounts for about 30 % of the total variance in the projected climate trends of average winter precipitation in the CMIP3 ensemble and explains a larger fraction of the total variance in the projected climate trends of extreme precipitation in the winter half-year. There is a good correspondence between the direction and spread of the changes in the return levels of extreme river discharges and extreme 10-day precipitation over the Rhine basin. This suggests that also for extreme discharges a large fraction of the total variance can be attributed to internal climate variability.
The Role of the Mean State of Arctic Sea Ice on Near-Surface Temperature Trends
Linden, E.C. van der; Bintanja, R. ; Hazeleger, W. ; Katsman, C.A. - \ 2014
Journal of Climate 27 (2014)8. - ISSN 0894-8755 - p. 2819 - 2841.
climate model sensitivity - albedo feedback - amplification - future - predictability - variability - inversion - thickness - extent - gcm
Century-scale global near-surface temperature trends in response to rising greenhouse gas concentrations in climate models vary by almost a factor of 2, with greatest intermodel spread in the Arctic region where sea ice is a key climate component. Three factors contribute to the intermodel spread: 1) model formulation, 2) control climate state, and 3) internal climate variability. This study focuses on the influence of Arctic sea ice in the control climate on the intermodel spread in warming, using idealized 1% yr(-1) CO2 increase simulations of 33 state-of-the-art global climate models, and combining sea ice-temperature relations on local to large spatial scales. On the Arctic mean scale, the spread in temperature trends is only weakly related to ice volume or area in the control climate, and is probably not dominated by internal variability. This suggests that other processes, such as ocean heat transport and meteorological conditions, play a more important role in the spread of long-term Arctic warming than control sea ice conditions. However, on a local scale, sea ice-warming relations show that in regions with more sea ice, models generally simulate more warming in winter and less warming in summer. The local winter warming is clearly related to control sea ice and universal among models, whereas summer sea ice-warming relations are more diverse, and are probably dominated by differences in model formulation. To obtain a more realistic representation of Arctic warming, it is recommended to simulate control sea ice conditions in climate models so that the spatial pattern is correct.
Multimodel estimate of the global terrestrial water balance: Setup and first results
Haddeland, I. ; Clark, D. ; Franssen, W.H.P. ; Ludwig, F. ; Voss, F. ; Arnell, N.W. ; Bertrand, N. ; Best, M. ; Folwell, S. ; Gerten, D. ; Gomes, S. ; Gosling, S. ; Hagemann, S. ; Hanasaki, N. ; Harding, R. ; Heinke, J. ; Kabat, P. ; Koirala, S. ; Oki, T. ; Polcher, J. ; Stacke, T. ; Viterbo, P. ; Weedon, G.P. ; Yeh, P. - \ 2011
Journal of Hydrometeorology 12 (2011)5. - ISSN 1525-755X - p. 869 - 884.
land-surface scheme - space-time climate - parameterization schemes - integrated model - project - simulation - resources - runoff - gcm - precipitation
Six land surface models and five global hydrological models participate in a model intercomparison project [Water Model Intercomparison Project (WaterMIP)], which for the first time compares simulation results of these different classes of models in a consistent way. In this paper, the simulation setup is described and aspects of the multimodel global terrestrial water balance are presented. All models were run at 0.5° spatial resolution for the global land areas for a 15-yr period (1985–99) using a newly developed global meteorological dataset. Simulated global terrestrial evapotranspiration, excluding Greenland and Antarctica, ranges from 415 to 586 mm yr-1 (from 60 000 to 85 000 km3 yr-1), and simulated runoff ranges from 290 to 457 mm yr-1 (from 42 000 to 66 000 km3 yr-1). Both the mean and median runoff fractions for the land surface models are lower than those of the global hydrological models, although the range is wider. Significant simulation differences between land surface and global hydrological models are found to be caused by the snow scheme employed. The physically based energy balance approach used by land surface models generally results in lower snow water equivalent values than the conceptual degree-day approach used by global hydrological models. Some differences in simulated runoff and evapotranspiration are explained by model parameterizations, although the processes included and parameterizations used are not distinct to either land surface models or global hydrological models. The results show that differences between models are a major source of uncertainty. Climate change impact studies thus need to use not only multiple climate models but also some other measure of uncertainty (e.g., multiple impact models).
The impact of land-cover modification on the June meteorology of China since 1700, simulated using a regional climate model
Wang, H. ; Pitman, A.J. ; Zhao, M. ; Leemans, R. - \ 2003
International Journal of Climatology 23 (2003)5. - ISSN 0899-8418 - p. 511 - 527.
global climate - amazonian deforestation - tropical deforestation - vegetation - sensitivity - ecosystems - weather - gcm
A series of simulations was conducted using a regional climate model with a domain covering mainland China. Simulations were conducted for a single June using estimated land cover for 1700, 1750, 1800, 1850, 1900, 1950, 1970 and 1990. The conversion of land cover between these periods was extensive over mainland China, where large areas were altered from natural forests to either grass or crops, or from natural grasslands to crops. These land-cover modifications affect various characteristics of the land surface, which lead to changes in the way available energy and water are partitioned. Over areas where land cover was modified, substantial changes are simulated. The conversion from forests to grasses or crops leads to warming and to reductions in root zone soil moisture and latent heat fluxes. Regionally, the conversion from forest to grasses and crops leads to significant warming over large areas of China, but there is an area of cooling present that is coincident with the main location of a land-use change from short grass to crops. The changes in temperature propagate to about 1500 m above the surface and affect specific humidity throughout this part of the atmosphere. An analysis of daily average results shows a consistent impact of land-cover modification on temperature, latent heat flux and soil moisture. Therefore, we find large and consistent impacts over China resulting from historical land-cover modification that are sufficiently important to the regional-scale climate to warrant inclusion in future modelling efforts. Our results suggest that efforts to attribute warming patterns over China to any particular cause need to take into account the conversion of the land cover that has taken place over China over the last 300 years