Search

We have created a performance-based assessment of CMIP6 models for Europe that can be used to inform the sub-selection of models for this region. Our assessment covers criteria indicative of the ability of individual models to capture a range of large-scale processes that are important for the representation of present-day European climate. We use this study to provide examples of how this performance-based assessment may be applied to a multi-model ensemble of CMIP6 models to (a) filter the ensemble for performance against these climatological and processed-based criteria and (b) create a smaller subset of models based on performance that also maintains model diversity and the filtered projection range as far as possible. Filtering by excluding the least-realistic models leads to higher-sensitivity models remaining in the ensemble as an emergent consequence of the assessment. This results in both the 25th percentile and the median of the projected temperature range being shifted towards greater warming for the filtered set of models. We also weight the unfiltered ensemble against global trends. In contrast, this shifts the distribution towards less warming. This highlights a tension for regional model selection in terms of selection based on regional climate processes versus the global mean warming trend. [ABSTRACT FROM AUTHOR]

We have created a performance-based assessment of CMIP6 models for Europe that can be used to inform the subselection of models for this region. Our assessment covers criteria indicative of the ability of individual models to capture range of large-scale processes that are important for the representation of present-day European climate. We use this study to provide examples of how this performance-based assessment may be applied to multi-model ensemble of CMIP6 models to a) filter the ensemble for performance against these climatological/processed-based criteria and, b) create a smaller sub-set of models based on performance, that also maintains model diversity and the filtered projection range as far as possible. Filtering by excluding the least realistic models leads to higher sensitivity models remaining in the ensemble as an emergent consequence of the assessment. This results in both the 25th percentile and the median of the projected temperature range being shifted toward greater warming for the filtered set of models. We also weight the unfiltered ensemble against global trends. In contrast this shifts both the distribution of towards less warming. This highlights a tension for regional model selection in terms of selection based on regional climate processes versus the global mean warming trend. [ABSTRACT FROM AUTHOR]

The regional climate modelling system PRECIS, was run at 25 km horizontal resolution for 150 years (1949-2099) using global driving data from a five member perturbed physics ensemble (based on the coupled global climate model HadCM3). Output from these simulations was used to investigate projected changes in tropical cyclones (TCs) over Vietnam and the South China Sea due to global warming (under SRES scenario A1B). Thirty year climatological mean periods were used to look at projected changes in future (2069-2098) TCs compared to a 1961-1990 baseline. Present day results were compared qualitatively with IBTrACS observations and found to be reasonably realistic. Future projections show a 20-44 % decrease in TC frequency, although the spatial patterns of change differ between the ensemble members, and an increase of 27-53 % in the amount of TC associated precipitation. No statistically significant changes in TC intensity were found, however, the occurrence of more intense TCs (defined as those with a maximum 10 m wind speed >35 m/s) was found to increase by 3-9 %. Projected increases in TC associated precipitation are likely caused by increased evaporation and availability of atmospheric water vapour, due to increased sea surface and atmospheric temperature. The mechanisms behind the projected changes in TC frequency are difficult to link explicitly; changes are most likely due to the combination of increased static stability, increased vertical wind shear and decreased upward motion, which suggest a decrease in the tropical overturning circulation. [ABSTRACT FROM AUTHOR]

The Met Office Hadley Centre's PRECIS regional climate modelling system has been used to generate a five member ensemble of climate projections for Africa over the 50 km resolution Coordinated Regional climate Downscaling Experiment-Africa domain. The ensemble comprises the downscaling of a subset of the Hadley Centre's perturbed physics global climate model (GCM) ensemble chosen to exclude ensemble members unable to represent the African climate realistically and then to capture the spread in outcomes from the projections of the remaining models. The PRECIS simulations were run from December 1949 to December 2100. The regional climate model (RCM) ensemble captures the annual cycle of temperatures well both for Africa as a whole and the sub-regions. It slightly overestimates precipitation over Africa as a whole and captures the annual cycle of rainfall for most of the African regions. The RCM ensemble substantially improve the patterns and magnitude of precipitation simulation compared to their driving GCM which is particularly noticeable in the Sahel for both the magnitude and timing of the wet season. Present-day simulations of the RCM ensemble are more similar to each other than those of the driving GCM ensemble which indicates that their climatologies are influenced significantly by the RCM formulation and less so by their driving GCMs. Consistent with this, the spread and magnitudes of the large-scale responses of the RCMs are often different than the driving GCMs and arguably more credible given the improved performance of the RCM. This also suggests that local climate forcing will be a significant driver of the regional response to climate change over Africa. [ABSTRACT FROM AUTHOR]

ABSTRACT This article presents an assessment of the skill of regional climate model PRECIS in simulating seasonal climate over Vietnam. The simulations were conducted at a horizontal resolution of 25 km × 25 km. The model simulations were forced by the ERA-Interim reanalysis and five members of the Hadley Centre's perturbed physics ensemble (PPE). CRU, APHRODITE, ERA40 datasets and observations recorded at 61 meteorological stations over Vietnam were used to validate the model. The analysis compared seasonal averages of observed and simulated precipitation, temperature, 850 hPa wind speed and direction, as well as the 99th percentile of daily precipitation and the 95th and 5th percentile of daily minimum and maximum temperatures. Annual cycles of temperature and precipitation, and the interannual variability of precipitation were also assessed. The reanalysis-driven simulation accurately reproduced most of the important characteristics of the observed spatial patterns and annual cycles of circulation rainfall and temperature as well as capturing key characteristics of interannual variability in rainfall and of extremes in precipitation and temperature. Some apparent systematic cool biases were found most likely to be an artefact of inadequacies in the CRU-gridded temperature observations. The regional model was found to introduce some systematic wet-biases in rainfall. The five GCM driven simulations demonstrated errors with similar characteristics to the ERA-Interim-driven simulations, although with diversity in the magnitude of those errors resulting from the differences in the characteristics of the different members of the HadCM3-based PPE. By assessing the skill of these models at producing realistic baseline simulations, we gain valuable contextual information to guide the application and interpretation of the future projections over Vietnam generated using these models. [ABSTRACT FROM AUTHOR]

Highlights: [•] Population changes is the main driver of increasing future global water stress. [•] Carbon dioxide effects on plant water-use is likely to increase runoff. [•] Climate change will lead to regional winners and losers in water resources. [•] Climate change may help alleviate the population driven increase in water stress. [•] In terms of water resources not all GHGs can be considered to be equal. [ABSTRACT FROM AUTHOR]

We examine the evidence for the possibility that 21st-century climate change may cause a large-scale "dieback" or degradation of Amazonian rainforest. We employ a new framework for evaluating the rainfall regime of tropical forests and from this deduce precipitation-based boundaries for current forest viability. We then examine climate simulations by 19 global climate models (GCMs) in this context and find that most tend to underestimate current rainfall. GCM5 also vary greatly in their projections of future climate change in Amazonia. We attempt to take into account the differences between GCM-simulated and observed rainfall regimes in the 20th century. Our analysis suggests that dry-season water stress is likely to increase in E. Amazonia over the 21st century, but the region tends toward a climate more appropriate to seasonal forest than to savanna. These seasonal forests may be resilient to seasonal drought but are likely to face intensified water stress caused by higher temperatures and to be vulnerable to fires, which are at present naturally rare in much of Amazonia. The spread of fire ignition associated with advancing deforestation, logging, and fragmentation may act as nucleation points that trigger the transition of these seasonal forests into fire-dominated, low biomass forests. Conversely, deliberate limitation of deforestation and fire may be an effective intervention to maintain Amazonian forest resilience in the face of imposed 21st-century climate change. Such intervention may be enough to navigate E. Amazonia away from a possible "tipping point," beyond which extensive rainforest would become unsustainable. [ABSTRACT FROM AUTHOR]