Beyond mean climate change: what climate models tell us about future climate extremes

2009 ◽  
pp. 99-119
Author(s):  
Claudia Tebaldi ◽  
Gerald A. Meehl
Climate ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 16
Author(s):  
Suzanna Meeussen ◽  
Anouschka Hof

Climate change is expected to have an impact on the geographical distribution ranges of species. Endemic species and those with a restricted geographic range may be especially vulnerable. The Persian jird (Meriones persicus) is an endemic rodent inhabiting the mountainous areas of the Irano-Turanian region, where future desertification may form a threat to the species. In this study, the species distribution modelling algorithm MaxEnt was used to assess the impact of future climate change on the geographic distribution range of the Persian jird. Predictions were made under two Representative Concentration Pathways and five different climate models for the years 2050 and 2070. It was found that both bioclimatic variables and land use variables were important in determining potential suitability of the region for the species to occur. In most cases, the future predictions showed an expansion of the geographic range of the Persian jird which indicates that the species is not under immediate threat. There are however uncertainties with regards to its current range. Predictions may therefore be an over or underestimation of the total suitable area. Further research is thus needed to confirm the current geographic range of the Persian jird to be able to improve assessments of the impact of future climate change.


2021 ◽  
Author(s):  
Giovanni Di Virgilio ◽  
Jason P. Evans ◽  
Alejandro Di Luca ◽  
Michael R. Grose ◽  
Vanessa Round ◽  
...  

<p>Coarse resolution global climate models (GCM) cannot resolve fine-scale drivers of regional climate, which is the scale where climate adaptation decisions are made. Regional climate models (RCMs) generate high-resolution projections by dynamically downscaling GCM outputs. However, evidence of where and when downscaling provides new information about both the current climate (added value, AV) and projected climate change signals, relative to driving data, is lacking. Seasons and locations where CORDEX-Australasia ERA-Interim and GCM-driven RCMs show AV for mean and extreme precipitation and temperature are identified. A new concept is introduced, ‘realised added value’, that identifies where and when RCMs simultaneously add value in the present climate and project a different climate change signal, thus suggesting plausible improvements in future climate projections by RCMs. ERA-Interim-driven RCMs add value to the simulation of summer-time mean precipitation, especially over northern and eastern Australia. GCM-driven RCMs show AV for precipitation over complex orography in south-eastern Australia during winter and widespread AV for mean and extreme minimum temperature during both seasons, especially over coastal and high-altitude areas. RCM projections of decreased winter rainfall over the Australian Alps and decreased summer rainfall over northern Australia are collocated with notable realised added value. Realised added value averaged across models, variables, seasons and statistics is evident across the majority of Australia and shows where plausible improvements in future climate projections are conferred by RCMs. This assessment of varying RCM capabilities to provide realised added value to GCM projections can be applied globally to inform climate adaptation and model development.</p>


2017 ◽  
Vol 30 (17) ◽  
pp. 6701-6722 ◽  
Author(s):  
Daniel Bannister ◽  
Michael Herzog ◽  
Hans-F. Graf ◽  
J. Scott Hosking ◽  
C. Alan Short

The Sichuan basin is one of the most densely populated regions of China, making the area particularly vulnerable to the adverse impacts associated with future climate change. As such, climate models are important for understanding regional and local impacts of climate change and variability, like heat stress and drought. In this study, climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) are validated over the Sichuan basin by evaluating how well each model can capture the phase, amplitude, and variability of the regionally observed mean, maximum, and minimum temperature between 1979 and 2005. The results reveal that the majority of the models do not capture the basic spatial pattern and observed means, trends, and probability distribution functions. In particular, mean and minimum temperatures are underestimated, especially during the winter, resulting in biases exceeding −3°C. Models that reasonably represent the complex basin topography are found to generally have lower biases overall. The five most skillful climate models with respect to the regional climate of the Sichuan basin are selected to explore twenty-first-century temperature projections for the region. Under the CMIP5 high-emission future climate change scenario, representative concentration pathway 8.5 (RCP8.5), the temperatures are projected to increase by approximately 4°C (with an average warming rate of +0.72°C decade−1), with the greatest warming located over the central plains of the Sichuan basin, by 2100. Moreover, the frequency of extreme months (where mean temperature exceeds 28°C) is shown to increase in the twenty-first century at a faster rate compared to the twentieth century.


2020 ◽  
Vol 33 (19) ◽  
pp. 8315-8337 ◽  
Author(s):  
Lawrence S. Jackson ◽  
Declan L. Finney ◽  
Elizabeth J. Kendon ◽  
John H. Marsham ◽  
Douglas J. Parker ◽  
...  

AbstractThe Hadley circulation and tropical rain belt are dominant features of African climate. Moist convection provides ascent within the rain belt, but must be parameterized in climate models, limiting predictions. Here, we use a pan-African convection-permitting model (CPM), alongside a parameterized convection model (PCM), to analyze how explicit convection affects the rain belt under climate change. Regarding changes in mean climate, both models project an increase in total column water (TCW), a widespread increase in rainfall, and slowdown of subtropical descent. Regional climate changes are similar for annual mean rainfall but regional changes of ascent typically strengthen less or weaken more in the CPM. Over a land-only meridional transect of the rain belt, the CPM mean rainfall increases less than in the PCM (5% vs 14%) but mean vertical velocity at 500 hPa weakens more (17% vs 10%). These changes mask more fundamental changes in underlying distributions. The decrease in 3-hourly rain frequency and shift from lighter to heavier rainfall are more pronounced in the CPM and accompanied by a shift from weak to strong updrafts with the enhancement of heavy rainfall largely due to these dynamic changes. The CPM has stronger coupling between intense rainfall and higher TCW. This yields a greater increase in rainfall contribution from events with greater TCW, with more rainfall for a given large-scale ascent, and so favors slowing of that ascent. These findings highlight connections between the convective-scale and larger-scale flows and emphasize that limitations of parameterized convection have major implications for planning adaptation to climate change.


2021 ◽  
Author(s):  
Antoine Doury ◽  
Samuel Somot ◽  
Sébastien Gadat ◽  
Aurélien Ribes ◽  
Lola Corre

Abstract Providing reliable information on climate change at local scale remains a challenge of first importance for impact studies and policymakers. Here, we propose a novel hybrid downscaling method combining the strengths of both empirical statistical downscaling methods and Regional Climate Models (RCMs). The aim of this tool is to enlarge the size of high-resolution RCM simulation ensembles at low cost.We build a statistical RCM-emulator by estimating the downscaling function included in the RCM. This framework allows us to learn the relationship between large-scale predictors and a local surface variable of interest over the RCM domain in present and future climate. Furthermore, the emulator relies on a neural network architecture, which grants computational efficiency. The RCM-emulator developed in this study is trained to produce daily maps of the near-surface temperature at the RCM resolution (12km). The emulator demonstrates an excellent ability to reproduce the complex spatial structure and daily variability simulated by the RCM and in particular the way the RCM refines locally the low-resolution climate patterns. Training in future climate appears to be a key feature of our emulator. Moreover, there is a huge computational benefit in running the emulator rather than the RCM, since training the emulator takes about 2 hours on GPU, and the prediction is nearly instantaneous. However, further work is needed to improve the way the RCM-emulator reproduces some of the temperature extremes, the intensity of climate change, and to extend the proposed methodology to different regions, GCMs, RCMs, and variables of interest.


2006 ◽  
Vol 2 (2) ◽  
pp. 145-165 ◽  
Author(s):  
V. Masson-Delmotte ◽  
G. Dreyfus ◽  
P. Braconnot ◽  
S. Johnsen ◽  
J. Jouzel ◽  
...  

Abstract. Ice cores provide unique archives of past climate and environmental changes based only on physical processes. Quantitative temperature reconstructions are essential for the comparison between ice core records and climate models. We give an overview of the methods that have been developed to reconstruct past local temperatures from deep ice cores and highlight several points that are relevant for future climate change. We first analyse the long term fluctuations of temperature as depicted in the long Antarctic record from EPICA Dome C. The long term imprint of obliquity changes in the EPICA Dome C record is highlighted and compared to simulations conducted with the ECBILT-CLIO intermediate complexity climate model. We discuss the comparison between the current interglacial period and the long interglacial corresponding to marine isotopic stage 11, ~400 kyr BP. Previous studies had focused on the role of precession and the thresholds required to induce glacial inceptions. We suggest that, due to the low eccentricity configuration of MIS 11 and the Holocene, the effect of precession on the incoming solar radiation is damped and that changes in obliquity must be taken into account. The EPICA Dome C alignment of terminations I and VI published in 2004 corresponds to a phasing of the obliquity signals. A conjunction of low obliquity and minimum northern hemisphere summer insolation is not found in the next tens of thousand years, supporting the idea of an unusually long interglacial ahead. As a second point relevant for future climate change, we discuss the magnitude and rate of change of past temperatures reconstructed from Greenland (NorthGRIP) and Antarctic (Dome C) ice cores. Past episodes of temperatures above the present-day values by up to 5°C are recorded at both locations during the penultimate interglacial period. The rate of polar warming simulated by coupled climate models forced by a CO2 increase of 1% per year is compared to ice-core-based temperature reconstructions. In Antarctica, the CO2-induced warming lies clearly beyond the natural rhythm of temperature fluctuations. In Greenland, the CO2-induced warming is as fast or faster than the most rapid temperature shifts of the last ice age. The magnitude of polar temperature change in response to a quadrupling of atmospheric CO2 is comparable to the magnitude of the polar temperature change from the Last Glacial Maximum to present-day. When forced by prescribed changes in ice sheet reconstructions and CO2 changes, climate models systematically underestimate the glacial-interglacial polar temperature change.


Author(s):  
Pietro Croce ◽  
Paolo Formichi ◽  
Filippo Landi ◽  
Francesca Marsili

<p>As consequence of global warming extreme weather events might become more frequent and severe across the globe. The evaluation of the impact of climate change on extremes is then a crucial issue for the resilience of infrastructures and buildings and is a key challenge for adaptation planning. In this paper, a suitable procedure for the estimation of future trends of climatic actions is presented starting from the output of regional climate models and taking into account the uncertainty in the model itself. In particular, the influence of climate change on ground snow loads is discussed in detail and the typical uncertainty range is determined applying an innovative algorithm for weather generation. Considering different greenhouse gasses emission scenarios, some results are presented for the Italian Mediterranean region proving the ability of the method to define factors of change for climate extremes also allowing a sound estimate of the uncertainty range associated with different models.</p>


2013 ◽  
Vol 125 (1) ◽  
pp. 24
Author(s):  
Leanne Webb

p>Agricultural production in Victoria includes the dairy, lamb and mutton, grains and perennial and annual horticultural sectors, with Victorian farmers contributing a major proportion of the Australian production total in many of these sectors. All these industries are exposed in different ways to weather and climate extremes. With projected warming of approximately 0.8°C by 2030 and by 1.4–2.7°C by 2070 (emissions dependent), and most climate models indicating reduced rainfall for the Victorian region (median of model results projecting a reduction of 4% by 2030 and 6%–11% by 2070; emissions dependent), a range of sectorspecific impacts could result. Increases in extreme events, such as heatwaves (e.g. for Mildura, days >35°C could nearly double from 32 to 59 annually by 2070), bushfires and drought, as well as an increased chance of extreme rainfall are all anticipated. Increasing frequencies of extreme events have the potential to affect agricultural production more than changes to the mean climate. For example, the exceptional heatwave that occurred in south-eastern Australia during January and February 2009 resulted in unprecedented impacts, with significant heat-stress related crop losses reported at many sites. Flooding in 2011 was also very costly to Victorian farmers with many crops being lost in the floodwaters and reduced agricultural production costing an estimated Au$500–600 million. Responses to climate variability already practised by the farming sector will inform some adaptation options that will assist farmers to cope in an increasingly challenging environment. As well as taking advantage of their underlying resilience, initiatives aimed at increasing the adaptive capacity of farmers are being implemented at many levels in agricultural communities.


2006 ◽  
Vol 19 (20) ◽  
pp. 5058-5077 ◽  
Author(s):  
Gabriele C. Hegerl ◽  
Thomas R. Karl ◽  
Myles Allen ◽  
Nathaniel L. Bindoff ◽  
Nathan Gillett ◽  
...  

Abstract A significant influence of anthropogenic forcing has been detected in global- and continental-scale surface temperature, temperature of the free atmosphere, and global ocean heat uptake. This paper reviews outstanding issues in the detection of climate change and attribution to causes. The detection of changes in variables other than temperature, on regional scales and in climate extremes, is important for evaluating model simulations of changes in societally relevant scales and variables. For example, sea level pressure changes are detectable but are significantly stronger in observations than the changes simulated in climate models, raising questions about simulated changes in climate dynamics. Application of detection and attribution methods to ocean data focusing not only on heat storage but also on the penetration of the anthropogenic signal into the ocean interior, and its effect on global water masses, helps to increase confidence in simulated large-scale changes in the ocean. To evaluate climate change signals with smaller spatial and temporal scales, improved and more densely sampled data are needed in both the atmosphere and ocean. Also, the problem of how model-simulated climate extremes can be compared to station-based observations needs to be addressed.


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