Regional signatures of future fire weather over eastern Australia from global climate models

2011 ◽  
Vol 20 (4) ◽  
pp. 550 ◽  
Author(s):  
Hamish G. Clarke ◽  
Peter L. Smith ◽  
Andrew J. Pitman
Keyword(s):  
20Th Century ◽  
Climate Models ◽  
Global Climate ◽  
Summer Rainfall ◽  
Global Climate Models ◽  
Fire Season ◽  
Future Climate Change ◽  
Fire Weather ◽  
Winter Rainfall ◽  
Eastern Australia

Skill-selected global climate models were used to explore the effect of future climate change on regional bushfire weather in eastern Australia. Daily Forest Fire Danger Index (FFDI) was calculated in four regions of differing rainfall seasonality for the 20th century, 2050 and 2100 using the A2 scenario from the Special Report on Emissions Scenarios. Projected changes in FFDI vary along a latitudinal gradient. In summer rainfall-dominated tropical north-east Australia, mean and extreme FFDI are projected to decrease or remain close to 20th century levels. In the uniform and winter rainfall regions, which occupy south-east continental Australia, FFDI is projected to increase strongly by 2100. Projections fall between these two extremes for the summer rainfall region, which lies between the uniform and summer tropical rainfall zones. Based on these changes in fire weather, the fire season is projected to start earlier in the uniform and winter rainfall regions, potentially leading to a longer overall fire season.

scholarly journals Future Australian Severe Thunderstorm Environments. Part II: The Influence of a Strongly Warming Climate on Convective Environments

2014 ◽  
Vol 27 (10) ◽  
pp. 3848-3868 ◽  
Author(s):  
John T. Allen ◽  
David J. Karoly ◽  
Kevin J. Walsh
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Convective Available Potential Energy ◽  
Vertical Wind Shear ◽  
Atmospheric Model ◽  
Global Climate Models ◽  
Historical Period ◽  
Severe Thunderstorm ◽  
Warming Climate ◽  
Eastern Australia

Abstract The influence of a warming climate on the occurrence of severe thunderstorm environments in Australia was explored using two global climate models: Commonwealth Scientific and Industrial Research Organisation Mark, version 3.6 (CSIRO Mk3.6), and the Cubic-Conformal Atmospheric Model (CCAM). These models have previously been evaluated and found to be capable of reproducing a useful climatology for the twentieth-century period (1980–2000). Analyzing the changes between the historical period and high warming climate scenarios for the period 2079–99 has allowed estimation of the potential convective future for the continent. Based on these simulations, significant increases to the frequency of severe thunderstorm environments will likely occur for northern and eastern Australia in a warmed climate. This change is a response to increasing convective available potential energy from higher continental moisture, particularly in proximity to warm sea surface temperatures. Despite decreases to the frequency of environments with high vertical wind shear, it appears unlikely that this will offset increases to thermodynamic energy. The change is most pronounced during the peak of the convective season, increasing its length and the frequency of severe thunderstorm environments therein, particularly over the eastern parts of the continent. The implications of this potential increase are significant, with the overall frequency of potential severe thunderstorm days per year likely to rise over the major population centers of the east coast by 14% for Brisbane, 22% for Melbourne, and 30% for Sydney. The limitations of this approach are then discussed in the context of ways to increase the confidence of predictions of future severe convection.

scholarly journals Robust increase of Indian monsoon rainfall and its variability under future warming in CMIP-6 models

2020 ◽  
Author(s):  
Anja Katzenberger ◽  
Jacob Schewe ◽  
Julia Pongratz ◽  
Anders Levermann
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Climate Models ◽  
Monsoon Rainfall ◽  
Global Climate ◽  
Coupled Model ◽  
Global Climate Models ◽  
Future Climate Change ◽  
Global Mean Temperature ◽  
Almost All

Abstract. The Indian summer monsoon is an integral part of the global climate system. As its seasonal rainfall plays a crucial role in India's agriculture and shapes many other aspects of life, it affects the livelihood of a fifth of the world's population. It is therefore highly relevant to assess its change under potential future climate change. Global climate models within the Coupled Model Intercomparison Project Phase 5 (CMIP-5) indicated a consistent increase in monsoon rainfall and its variability under global warming. Since the range of the results of CMIP-5 was still large and the confidence in the models was limited due to partly poor representation of observed rainfall, the updates within the latest generation of climate models in CMIP-6 are of interest. Here, we analyse 32 models of the latest CMIP-6 exercise with regard to their annual mean monsoon rainfall and its variability. All of these models show a substantial increase in June-to-September (JJAS) mean rainfall under unabated climate change (SSP5-8.5) and most do also for the other three Shared Socioeconomic Pathways analyzed (SSP1-2.6, SSP2-4.5, SSP3-7.0). Moreover, the simulation ensemble indicates a linear dependence of rainfall on global mean temperature with high agreement between the models and independent of the SSP; the multi-model mean for JJAS projects an increase of 0.33 mm/day and 5.3 % per degree of global warming. This is significantly higher than in the CMIP-5 projections. Most models project that the increase will contribute to the precipitation especially in the Himalaya region and to the northeast of the Bay of Bengal, as well as the west coast of India. Interannual variability is found to be increasing in the higher-warming scenarios by almost all models. The CMIP-6 simulations largely confirm the findings from CMIP-5 models, but show an increased robustness across models with reduced uncertainties and updated magnitudes towards a stronger increase in monsoon rainfall.

scholarly journals 20th-century sea-ice variations from observational data

2001 ◽  
Vol 33 ◽  
pp. 444-448 ◽  
Author(s):  
John E. Walsh ◽  
William L. Chapman
Keyword(s):  
Sea Ice ◽  
20Th Century ◽  
North Atlantic ◽  
Climate Models ◽  
Global Climate ◽  
Arctic Sea Ice ◽  
Empirical Orthogonal Functions ◽  
Global Climate Models ◽  
The Past ◽  
Ice Coverage

AbstractIn order to extend diagnoses of recent sea-ice variations beyond the past few decades, a century-scale digital dataset of Arctic sea-ice coverage has been compiled. For recent decades, the compilation utilizes satellite-derived hemispheric datasets. Regional datasets based primarily on ship reports and aerial reconnaissance are the primary inputs for the earlier part of the 20th century. While the various datasets contain some discrepancies, they capture the same general variations during their period of overlap. The outstanding feature of the time series of total hemispheric ice extent is a decrease that has accelerated during the past several decades. The decrease is greatest in summer and weakest in winter, contrary to the seasonality of the greenhouse changes projected by most global climate models. The primary spatial modes of sea-ice variability diagnosed in terms of empirical orthogonal functions, also show a strong seasonality. The first winter mode is dominated by an opposition of anomalies in the western and eastern North Atlantic, corresponding to the well-documented North Atlantic Oscillation. The primary summer mode depicts an anomaly of the same sign over nearly the entire Arctic and captures the recent trend of sea-ice coverage.

scholarly journals Impacts of future climate change on potential yields of major crops in China

2014 ◽  
Vol 5 (1) ◽  
pp. 617-647
Author(s):  
Y. Yin ◽  
Q. Tang ◽  
X. Liu
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Future Climate ◽  
Future Climate Change ◽  
Yield Reduction ◽  
Climate Data ◽  
Potential Yield ◽  
Crop Models

Abstract. Climate change may affect crop development and yield, and consequently cast a shadow of doubt over China's food self-sufficiency efforts. In this study we used the model projections of a couple of global gridded crop models (GGCMs) to assess the effects of future climate change on the potential yields of the major crops (i.e. wheat, rice, maize and soybean) over China. The GGCMs were forced with the bias-corrected climate data from 5 global climate models (GCMs) under the Representative Concentration Pathways (RCP) 8.5 which were made available by the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP). The results show that the potential yields of rice may increase over a large portion of China. Climate change may benefit food productions over the high-altitude and cold regions where are outside current main agricultural area. However, the potential yield of maize, soybean and wheat may decrease in a large portion of the current main crop planting areas such as North China Plain. Development of new agronomic management strategy may be useful for coping with climate change in the areas with high risk of yield reduction.

scholarly journals ENSO Teleconnection to Eastern African Summer Rainfall in Global Climate Models: Role of the Tropical Easterly Jet

2021 ◽  
Vol 34 (1) ◽  
pp. 293-312
Author(s):  
Amandeep Vashisht ◽  
Benjamin Zaitchik ◽  
Anand Gnanadesikan
Keyword(s):  
Climate Variability ◽  
Climate Models ◽  
Southern Oscillation ◽  
Global Climate ◽  
Summer Rainfall ◽  
Global Climate Models ◽  
Eastern Africa ◽  
Climate Variability And Change ◽  
Tropical Easterly Jet ◽  
Interannual Rainfall Variability

AbstractGlobal climate models (GCMs) are critical tools for understanding and projecting climate variability and change, yet the performance of these models is notoriously weak over much of tropical Africa. To improve this situation, process-based studies of African climate dynamics and their representation in GCMs are required. Here, we focus on summer rainfall of eastern Africa (SREA), which is crucial to the Ethiopian Highlands and feeds the flow of the Blue Nile River. The SREA region is highly vulnerable to droughts, with El Niño–Southern Oscillation (ENSO) being a leading cause of interannual rainfall variability. Adequate understanding and accurate representation of climate features that influence regional variability is an important but often neglected issue when evaluating models. We perform a process-based evaluation of GCMs, focusing on the upper-troposphere tropical easterly jet (TEJ), which has been hypothesized to link ENSO to SREA. We find that most models have an ENSO–TEJ coupling similar to observed, but the models diverge in their representation of TEJ–SREA coupling. Differences in the latter explain the majority (80%) of variability in ENSO teleconnection simulation across the models. This is higher than the variance explained by rainfall coupling with the Somali jet (44%) and African easterly jet (55%). However, our diagnostics of the leading hypothesized mechanism in the models—variability in divergence in the TEJ exit region—are not consistent across models and suggest that a deeper understanding of the mechanisms of TEJ–precipitation coupling should be a priority for studies of climate variability and change in the region.

scholarly journals Downscale of future climate change scenarios applied to Recife-PE

2020 ◽  
Vol 9 (6) ◽  
pp. 361
Author(s):  
Rafaela Lisboa Costa ◽  
Heliofábio Barros Gomes ◽  
Fabrício Daniel Dos Santos Silva ◽  
Rodrigo Lins Da Rocha Júnior
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Global Climate ◽  
Reanalysis Data ◽  
Global Climate Models ◽  
Future Climate ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
The Future ◽  
Maximum Temperatures

The objective of this work was to analyze and compare results from two generations of global climate models (GCMs) simulations for the city of Recife-PE: CMIP3 and CMIP5. Differences and similarities in historical and future climate simulations are presented for four GCMs using CMIP3 scenarios A1B and A2 and for seven CMIP5 scenarios RCP4.5 and RCP8.5. The scale reduction technique applied to GCMs scenarios is statistical downscaling, employing the same set of large-scale atmospheric variables as predictors for both sets of scenarios, differing only in the type of reanalysis data used to characterize surface variables precipitation, maximum and minimum temperatures. For CMIP3 scenarios the simulated historical climate is 1961-1990 and CMIP5 is 1979-2000, and the validation period is ten years, 1991-2000 for CMIP3 and 2001-2010 for CMIP5. However, for both the future period analyzed is 2021-2050 and 2051-2080. Validation metrics indicated superior results from the historical simulations of CMIP5 over those of CMIP3 for precipitation and minimum and similar temperatures for maximum temperatures. For the future, both CMIP3 and CMIP5 scenarios indicate reduced precipitation and increased temperatures. The potencial evapotranspiration was calculated, projected to increase in scenarios A1B and A2 of CMIP3 and with behavior similar to that observed historically in scenarios RCP4.5 and 8.5.

scholarly journals Peatlands and the carbon cycle: from local processes to global implications – a synthesis

2008 ◽  
Vol 5 (5) ◽  
pp. 1475-1491 ◽  
Author(s):  
J. Limpens ◽  
F. Berendse ◽  
C. Blodau ◽  
J. G. Canadell ◽  
C. Freeman ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Surface ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Trace Gas ◽  
Future Climate Change ◽  
Small Scale ◽  
Ecosystem Structure ◽  
Positive Feedbacks

Abstract. Peatlands cover only 3% of the Earth's land surface but boreal and subarctic peatlands store about 15–30% of the world's soil carbon (C) as peat. Despite their potential for large positive feedbacks to the climate system through sequestration and emission of greenhouse gases, peatlands are not explicitly included in global climate models and therefore in predictions of future climate change. In April 2007 a symposium was held in Wageningen, the Netherlands, to advance our understanding of peatland C cycling. This paper synthesizes the main findings of the symposium, focusing on (i) small-scale processes, (ii) C fluxes at the landscape scale, and (iii) peatlands in the context of climate change. The main drivers controlling C fluxes are largely scale dependent and most are related to some aspects of hydrology. Despite high spatial and annual variability in Net Ecosystem Exchange (NEE), the differences in cumulative annual NEE are more a function of broad scale geographic location and physical setting than internal factors, suggesting the existence of strong feedbacks. In contrast, trace gas emissions seem mainly controlled by local factors. Key uncertainties remain concerning the existence of perturbation thresholds, the relative strengths of the CO2 and CH4 feedback, the links among peatland surface climate, hydrology, ecosystem structure and function, and trace gas biogeochemistry as well as the similarity of process rates across peatland types and climatic zones. Progress on these research areas can only be realized by stronger co-operation between disciplines that address different spatial and temporal scales.

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