scholarly journals Multi-thousand member ensemble atmospheric simulations with global 60km resolution using climateprediction.net

2020 ◽  
Author(s):  
Peter Watson ◽  
Sarah Sparrow ◽  
William Ingram ◽  
Simon Wilson ◽  
Drouard Marie ◽  
...  
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Atmospheric Model ◽  
Computing System ◽  
Extreme Weather ◽  
Global Climate Models ◽  
Extreme Weather Events ◽  
Weather Events ◽  
The Impact

<p>Multi-thousand member climate model simulations are highly valuable for showing how extreme weather events will change as the climate changes, using a physically-based approach. However, until now, studies using such an approach have been limited to using models with a resolution much coarser than the most modern systems. We have developed a global atmospheric model with 5/6°x5/9° resolution (~60km in middle latitudes) that can be run in the climateprediction.net distributed computing system to produce such large datasets. This resolution is finer than that of many current global climate models and sufficient for good simulation of extratropical synoptic features such as storms. It will also allow many extratropical extreme weather events to be simulated without requiring regional downscaling. We will show that this model's simulation of extratropical weather is competitive with that in other current models. We will also present results from the first multi-thousand member ensembles produced at this resolution, showing the impact of 1.5°C and 2°C global warming on extreme winter rainfall and extratropical cyclones in Europe.</p>

scholarly journals Assessing the impact of global warming on worldwide open field tomato cultivation through CSIRO-Mk3·0 global climate model

2016 ◽  
Vol 155 (3) ◽  
pp. 407-420 ◽  
Author(s):  
R. S. SILVA ◽  
L. KUMAR ◽  
F. SHABANI ◽  
M. C. PICANÇO
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Open Field ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Current Model ◽  
Global Climate Models ◽  
The Impact

SUMMARYTomato (Solanum lycopersicum L.) is one of the most important vegetable crops globally and an important agricultural sector for generating employment. Open field cultivation of tomatoes exposes the crop to climatic conditions, whereas greenhouse production is protected. Hence, global warming will have a greater impact on open field cultivation of tomatoes rather than the controlled greenhouse environment. Although the scale of potential impacts is uncertain, there are techniques that can be implemented to predict these impacts. Global climate models (GCMs) are useful tools for the analysis of possible impacts on a species. The current study aims to determine the impacts of climate change and the major factors of abiotic stress that limit the open field cultivation of tomatoes in both the present and future, based on predicted global climate change using CLIMatic indEX and the A2 emissions scenario, together with the GCM Commonwealth Scientific and Industrial Research Organisation (CSIRO)-Mk3·0 (CS), for the years 2050 and 2100. The results indicate that large areas that currently have an optimum climate will become climatically marginal or unsuitable for open field cultivation of tomatoes due to progressively increasing heat and dry stress in the future. Conversely, large areas now marginal and unsuitable for open field cultivation of tomatoes will become suitable or optimal due to a decrease in cold stress. The current model may be useful for plant geneticists and horticulturalists who could develop new regional stress-resilient tomato cultivars based on needs related to these modelling projections.

scholarly journals Assessing Future Spatio-Temporal Changes in Crop Suitability and Planting Season over West Africa: Using the Concept of Crop-Climate Departure

Climate ◽  
2019 ◽  
Vol 7 (9) ◽  
pp. 102 ◽  
Author(s):  
Temitope S. Egbebiyi ◽  
Chris Lennard ◽  
Olivier Crespo ◽  
Phillip Mukwenha ◽  
Shakirudeen Lawal ◽  
...  
Keyword(s):  
West Africa ◽  
Linear Correlation ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Models ◽  
Crop Suitability ◽  
Suitable Area ◽  
The Impact ◽  
Planting Season

The changing climate is posing significant threats to agriculture, the most vulnerable sector, and the main source of livelihood in West Africa. This study assesses the impact of the climate-departure on the crop suitability and planting month over West Africa. We used 10 CMIP5 Global climate models bias-corrected simulations downscaled by the CORDEX regional climate model, RCA4 to drive the crop suitability model, Ecocrop. We applied the concept of the crop-climate departure (CCD) to evaluate future changes in the crop suitability and planting month for five crop types, cereals, legumes, fruits, root and tuber and horticulture over the historical and future months. Our result shows a reduction (negative linear correlation) and an expansion (positive linear correlation) in the suitable area and crop suitability index value in the Guinea-Savanna and Sahel (southern Sahel) zone, respectively. The horticulture crop was the most negatively affected with a decrease in the suitable area while cereals and legumes benefited from the expansion in suitable areas into the Sahel zone. In general, CCD would likely lead to a delay in the planting season by 2–4 months except for the orange and early planting dates by about 2–3 months for cassava. No projected changes in the planting month are observed for the plantain and pineapple which are annual crops. The study is relevant for a short and long-term adaptation option and planning for future changes in the crop suitability and planting month to improve food security in the region.

scholarly journals Comparison of warming trends over the last century around Antarctica from three coupled models

1998 ◽  
Vol 27 ◽  
pp. 565-570 ◽  
Author(s):  
William M. Connolley ◽  
Siobhan P. O'Farrell
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Atmospheric Model ◽  
Global Climate Models ◽  
Large Temperature ◽  
Coupled Models ◽  
Temperature Changes ◽  
Model Variability ◽  
The Antarctic

We compare observed temperature variations in Antarctica with climate-model runs over the last century. The models used are three coupled global climate models (GCMs) — the UKMO, the CSIRO and the MPI forced by the CO2 increases observed over the last century, and an atmospheric model experiment forced with observed sea-surface temperatures and sea-ice extents over the last century. Despite some regions of agreement, in general the GCM runs appear to be incompatible with each other and with the observations, although the short observational record and high natural variability make verification difficult. One of the best places for a more detailed study is the Antarctic Peninsula where the density of stations is higher and station records are longer than elsewhere in Antarctica. Observations show that this area has seen larger temperature rises than anywhere else in Antarctica. None of the three GCMs simulate such large temperature changes in the Peninsula region, in either climate-change runs radiatively forced by CO2 increases or control runs which assess the level of model variability.

Dust Aerosol Important for Snowball Earth Deglaciation

2010 ◽  
Vol 23 (15) ◽  
pp. 4121-4132 ◽  
Author(s):  
Dorian S. Abbot ◽  
Itay Halevy
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Atmospheric Model ◽  
Dust Aerosol ◽  
Snowball Earth ◽  
Dust Aerosols ◽  
Co2 Levels ◽  
The Impact

Abstract Most previous global climate model simulations could only produce the termination of Snowball Earth episodes at CO2 partial pressures of several tenths of a bar, which is roughly an order of magnitude higher than recent estimates of CO2 levels during and shortly after Snowball events. These simulations have neglected the impact of dust aerosols on radiative transfer, which is an assumption of potentially grave importance. In this paper it is argued, using the Dust Entrainment and Deposition (DEAD) box model driven by GCM results, that atmospheric dust aerosol concentrations may have been one to two orders of magnitude higher during a Snowball Earth event than today. It is furthermore asserted on the basis of calculations using NCAR’s Single Column Atmospheric Model (SCAM)—a radiative–convective model with sophisticated aerosol, cloud, and radiative parameterizations—that when the surface albedo is high, such increases in dust aerosol loading can produce several times more surface warming than an increase in the partial pressure of CO2 from 10−4 to 10−1 bar. Therefore the conclusion is reached that including dust aerosols in simulations may reconcile the CO2 levels required for Snowball termination in climate models with observations.

scholarly journals On the attribution of the impacts of extreme weather events to anthropogenic climate change

2021 ◽  
Author(s):  
Sarah E Perkins-Kirkpatrick ◽  
Daithi Stone ◽  
Dann M. Mitchell ◽  
Suzanne M. Rosier ◽  
Andrew David King ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Anthropogenic Impacts ◽  
Extreme Weather ◽  
Anthropogenic Climate Change ◽  
Extreme Weather Events ◽  
Climate Change Signal ◽  
Care Needs ◽  
Weather Events ◽  
The Impact

Abstract Investigations into the role of anthropogenic climate change in extreme weather events are now starting to extend into analysis of anthropogenic impacts on non-climate (e.g. socio-economic) systems. However, care needs to be taken when making this extension, because methodological choices regarding extreme weather attribution can become crucial when considering the events’ impacts. The fraction of attributable risk (FAR) method, useful in extreme weather attribution research, has a very specific interpretation concerning a class of events, and there is potential to misinterpret results from weather event analyses as being applicable to specific events and their impact outcomes. Using two case studies of meteorological extremes and their impacts, we argue that FAR is not generally appropriate when estimating the magnitude of the anthropogenic signal behind a specific impact. Attribution assessments on impacts should always be carried out in addition to assessment of the associated meteorological event, since it cannot be assumed that the anthropogenic signal behind the weather is equivalent to the signal behind the impact because of lags and nonlinearities in the processes through which the impact system reacts to weather. Whilst there are situations where employing FAR to understand the climate change signal behind a class of impacts is useful (e.g. “system breaking” events), more useful results will generally be produced if attribution questions on specific impacts are reframed to focus on changes in the impact return value and magnitude across large samples of factual and counterfactual climate model and impact simulations. We advocate for constant interdisciplinary collaboration as essential for effective and robust impact attribution assessments.

Impact of a quasi-stochastic cellular automaton backscatter scheme on the systematic error and seasonal prediction skill of a global climate model

2008 ◽  
Vol 366 (1875) ◽  
pp. 2559-2577 ◽  
Author(s):  
J Berner ◽  
F.J Doblas-Reyes ◽  
T.N Palmer ◽  
G Shutts ◽  
A Weisheimer
Keyword(s):  
Cellular Automaton ◽  
Systematic Error ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Seasonal Prediction ◽  
Global Climate Models ◽  
Seasonal Forecasts ◽  
The Impact

The impact of a nonlinear dynamic cellular automaton (CA) model, as a representation of the partially stochastic aspects of unresolved scales in global climate models, is studied in the European Centre for Medium Range Weather Forecasts coupled ocean–atmosphere model. Two separate aspects are discussed: impact on the systematic error of the model, and impact on the skill of seasonal forecasts. Significant reductions of systematic error are found both in the tropics and in the extratropics. Such reductions can be understood in terms of the inherently nonlinear nature of climate, in particular how energy injected by the CA at the near-grid scale can backscatter nonlinearly to larger scales. In addition, significant improvements in the probabilistic skill of seasonal forecasts are found in terms of a number of different variables such as temperature, precipitation and sea-level pressure. Such increases in skill can be understood both in terms of the reduction of systematic error as mentioned above, and in terms of the impact on ensemble spread of the CA's representation of inherent model uncertainty.

scholarly journals Process-oriented analysis of aircraft soot-cirrus interactions constrains the climate impact of aviation

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Bernd Kärcher ◽  
Fabian Mahrt ◽  
Claudia Marcolli
Keyword(s):  
Radiative Forcing ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Climate Impact ◽  
Global Climate Models ◽  
Soot Particles ◽  
Cloud Ice ◽  
The Impact

AbstractFully accounting for the climate impact of aviation requires a process-level understanding of the impact of aircraft soot particle emissions on the formation of ice clouds. Assessing this impact with the help of global climate models remains elusive and direct observations are lacking. Here we use a high-resolution cirrus column model to investigate how aircraft-emitted soot particles, released after ice crystals sublimate at the end of the lifetime of contrails and contrail cirrus, perturb the formation of cirrus. By allying cloud simulations with a measurement-based description of soot-induced ice formation, we find that only a small fraction (<1%) of the soot particles succeeds in forming cloud ice alongside homogeneous freezing of liquid aerosol droplets. Thus, soot-perturbed and homogeneously-formed cirrus fundamentally do not differ in optical depth. Our results imply that climate model estimates of global radiative forcing from interactions between aircraft soot and large-scale cirrus may be overestimates. The improved scientific understanding reported here provides a process-based underpinning for improved climate model parametrizations and targeted field observations.

Global hydrology modelling and uncertainty: running multiple ensembles with a campus grid

2010 ◽  
Vol 368 (1926) ◽  
pp. 4005-4021 ◽  
Author(s):  
Simon N. Gosling ◽  
Dan Bretherton ◽  
Keith Haines ◽  
Nigel W. Arnell
Keyword(s):  
Climate Change ◽  
Water Resource ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Models ◽  
Resource Stress ◽  
Runoff Changes ◽  
Campus Grid ◽  
The Impact

Uncertainties associated with the representation of various physical processes in global climate models (GCMs) mean that, when projections from GCMs are used in climate change impact studies, the uncertainty propagates through to the impact estimates. A complete treatment of this ‘climate model structural uncertainty’ is necessary so that decision-makers are presented with an uncertainty range around the impact estimates. This uncertainty is often underexplored owing to the human and computer processing time required to perform the numerous simulations. Here, we present a 189-member ensemble of global river runoff and water resource stress simulations that adequately address this uncertainty. Following several adaptations and modifications, the ensemble creation time has been reduced from 750 h on a typical single-processor personal computer to 9 h of high-throughput computing on the University of Reading Campus Grid. Here, we outline the changes that had to be made to the hydrological impacts model and to the Campus Grid, and present the main results. We show that, although there is considerable uncertainty in both the magnitude and the sign of regional runoff changes across different GCMs with climate change, there is much less uncertainty in runoff changes for regions that experience large runoff increases (e.g. the high northern latitudes and Central Asia) and large runoff decreases (e.g. the Mediterranean). Furthermore, there is consensus that the percentage of the global population at risk to water resource stress will increase with climate change.

scholarly journals Summer Season Squall-Line Simulations: Sensitivity of Gravity Waves to Physics Parameterization and Implications for Their Parameterization in Global Climate Models

2014 ◽  
Vol 71 (9) ◽  
pp. 3376-3391 ◽  
Author(s):  
Claudia Stephan ◽  
M. Joan Alexander
Keyword(s):  
Gravity Waves ◽  
Momentum Flux ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Middle Atmosphere ◽  
Global Climate ◽  
Global Climate Models ◽  
Squall Line ◽  
The Impact

Abstract Gravity waves have important effects on the middle atmosphere circulation, and those generated by convection are prevalent in the tropics and summer midlatitudes. Numerous case studies have been carried out to investigate their characteristics in high-resolution simulations. Here, the impact of the choice of physics parameterizations on the generation and spectral properties of these waves in models is investigated. Using the Weather Research and Forecasting Model (WRF) a summertime squall line over the Great Plains is simulated in a three-dimensional, nonlinear, and nonhydrostatic mesoscale framework. The distributions of precipitation strength and echo tops in the simulations are compared with radar data. Unsurprisingly, those storm features are most sensitive to the microphysics scheme. However, it is found that these variations in storm morphology have little influence on the simulated stratospheric momentum flux spectra. These results support the fundamental idea behind climate model parameterizations: that the large-scale storm conditions can be used to predict the spectrum of gravity wave momentum flux above the storm irrespective of the convective details that coarse-resolution models cannot capture. The simulated spectra are then contrasted with those obtained from a parameterization used in global climate models. The parameterization reproduces the shape of the spectra reasonably well but their magnitudes remain highly sensitive to the peak heating rate within the convective cells.

scholarly journals Connection of Quasi-Resonant Amplification to the Delay in Atmospheric Residence Times Over India

2021 ◽  
Vol 9 ◽  
Author(s):  
T. V. Lakshmi Kumar ◽  
G. Purna Durga ◽  
K. Koteswara Rao ◽  
Humberto Barbosa ◽  
Ashwini Kulkarni ◽  
...  
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Monsoon Season ◽  
Coupled Model ◽  
Southwest Monsoon ◽  
Global Climate Models ◽  
Extreme Weather Events ◽  
Residence Times ◽  
Tropical Country ◽  
Weather Events

Mean monthly Atmospheric Residence Times (ART), deduced from the global climate models of Coupled Model Intercomparison Project 5 (CMIP5) under RCP4.5 and RCP8.5 emission scenarios over Indian landmass, show a perceptible increase by the end of the 21st century. India, being a tropical country, faces prolonged ART, particularly during the June month of Southwest monsoon season (June to September) which will be an indicative measure of the increased frequency of extreme weather events. Here we show a possible connection of quasi-resonant amplification (QRA) to the recent (August 2018) Kerala heavy rains that resulted in severe floods and claimed more than 400 mortalities. Remarkable delay in residence times over India during June is shown to have an association with QRA evidenced by the higher magnitudes of amplitudes at the wavenumbers six and seven from the 19 global climate models of CMIP5 under the RCP4.5 and RCP8.5 scenarios.

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