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Quantifying and separating different sources of uncertainty helps to improve the understanding of the projected effects of climate change and can inform decision‐making in adaptation planning. This paper (1) evaluated four process‐based crop models; (2) assessed the effects of climate change on maize yield using climate change outputs from seven global climate models (GCMs) under three representative concentration pathways (RCPs); and (3) disaggregated the contributions of multiple crop models, GCMs and RCPs to overall uncertainty. All four models captured more than 80% of the variation in days to silking, maturity and yield, indicating reasonably reproduced observations. Similarly, the root mean square errors were moderate for days to silking and maturity (fewer than 4 days) and yield (0.5–0.7 t/ha). Overall, the results indicate that the models could assess grain yield at the study sites reasonably well. The results of the multiple models ensemble indicate that the maize yield will decrease by 9–11% with a probability of 72–80% on average during the period 2010–2039 relative to the baseline (1976–2005). The uncertainty in the maize‐yield simulations might arise mostly from the GCM models, followed by the crop models and RCPs, the contribution of which could be neglected relative to the other factors. Therefore, the use of a multiple crop model and a GCM ensemble is advisable in order to account properly for uncertainties in crop assessments. The uncertainty in maize‐yield simulations might arise mostly from global climate models (GCMs), followed by crop models and representative concentration pathways (RCPs), the contribution of which could be neglected relative to the other factors. Therefore, the use of a multiple crop model and a GCM ensemble is advisable in order to account properly for uncertainties in crop assessments. [ABSTRACT FROM AUTHOR]

ABSTRACT Heavy rain events or rainstorms of various scales often occur in Hong Kong from April to September. In extremes cases, they lead to serious landslides and flash floods resulting in loss of life, and damage to property and infrastructure. With climate change, extreme rain events are projected to be more frequent and more intense in this region. A system to gauge and label the severity of rainstorms would be useful for identifying and communicating extreme conditions in warning and disaster prevention operations. In parallel, a better understanding of the characteristics of rainstorms would also be important for impact assessments and engineering design purposes. This paper formulates a practical framework to index the magnitude and severity of rainstorms in Hong Kong. An index termed as the Severity Index combining the magnitude of different rainstorm attributes is devised for quantifying the overall severity of rainstorms. This index is flexible to allow tuning for specific applications. [ABSTRACT FROM AUTHOR]

A weatherpatternbased multiple regression model to derive future possible changes in the level of the higher temporal resolution spectrum of heavy precipitation has been developed. The temporal spectrum was described using statistical precipitation amounts as a function of the events duration 1–24 h and return period once in 5 yr to once in 100 yr. The principle of the method consists in projecting a statistical relationship between the parameters of a transformed Gumbel distribution theoretical extreme value distribution and the distribution of classes of objective weather patterns to time slices in the near future of climate. Changes in distribution parameters were constructed in the model from changes in the distribution of weather patterns. Possible change signals were calculated for the catchment of the Weißeritz River Ore Mountains, Germany for the time slices centred around 2025 2011–2040 and 2050 2036–2065 as changes versusthe reanalyses of the reference period 1961–2000 May–September. For the climate conditions to be expected in the near future IPCC A1B scenario, increases in the amounts of heavy precipitation, i.e. decreases in the return periods of equal amounts of heavy precipitation from the reference period, were obtained for the entire temporal spectrum covered by this paper. Overall, the change signals derived on the basis of a concept of weather patterns seem plausible because they represent a possible continuation of the already observed increase in frequency and intensification of events of heavy precipitation in the extended study area. Copyright © 2009 Royal Meteorological Society [ABSTRACT FROM AUTHOR]