scholarly journals AMOC-emulator M-AMOC1.0 for uncertainty assessment of future projections

2016 ◽  
Author(s):  
Pepijn Bakker ◽  
Andreas Schmittner
Keyword(s):  
Global Warming ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Uncertainty Assessment ◽  
Global Climate Models ◽  
Meridional Overturning Circulation

Abstract. State-of-the-science global climate models show that global warming is likely to weaken the Atlantic Meridional Overturning Circulation (AMOC). While such models are arguably the best tools to perform AMOC projections, they do not allow a comprehensive uncertainty assessment because of limited computational resources. Here we present an AMOC-emulator, a box model with a number of free parameters that can be tuned to mimic the sensitivity of the AMOC to climate change of a specific global climate model. The AMOC-emulator (M-AMOC1.0) is applied to simulations of global warming and melting of the Greenland Ice Sheet, performed with an intermediate complexity model. Predictive power of the AMOC-emulator is shown by comparison with a number of additional warming and Greenland Ice Sheet melt scenario that have not been used in the tuning of the AMOC-emulator, highlighting the potential of the AMOC-emulator to assess the uncertainty in AMOC projections.

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 Future rainfall and temperature changes in Brazil under global warming levels of 1.5ºC, 2ºC and 4ºC

2020 ◽  
Vol 11 (3) ◽  
pp. 57-90
Author(s):  
Diego Jatobá dos Santos ◽  
George Ulguim Pedra ◽  
Marcelo Guatura Barbosa da Silva ◽  
Carlos Augusto Guimarães Júnior ◽  
Lincoln Muniz Alves ◽  
...  
Keyword(s):  
Global Warming ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Climate Impacts ◽  
Global Climate Models ◽  
Northeastern Brazil ◽  
Climate Indices ◽  
Sea Ice Concentration

The present study analyzes the impacts of global warming of 1.5ºC, 2ºC, and 4ºC above pre-industrial levels in the Brazilian territory. Climate change projected among the different global warming levels has been analyzed for rainfall, temperature and extreme climate indices. The projections are derived from the global climate model HadGEM3-A, from the High-End cLimate Impacts and eXtremes (HELIX) international project, from the United Kingdom, forced by sea surface temperature and sea ice concentration of a subset of six CMIP5 (Coupled Model Intercomparison Project phase 5) global climate models and considering the RCP 8.5 (Representative Concentration Pathways) emissions scenario throughout the 21st century. Projections indicate robust differences in regional climate characteristics. These differences include changes: in the minimum and maximum air temperature close to the surface to all the country’s regions, in extremes of heat, particularly in northern Brazil, in the occurrence of heavy rainfall (Southern and Southeastern regions), and in the probability of droughts and rain deficits in some regions (Northern and Northeastern Brazil).

The MJO-QBO Relationship in a GCM with Stratospheric Nudging

2021 ◽  
pp. 1-69
Author(s):  
Zane Martin ◽  
Clara Orbe ◽  
Shuguang Wang ◽  
Adam Sobel
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Global Climate Models ◽  
Boreal Winter ◽  
Quasi Biennial Oscillation ◽  
Meridional Winds ◽  
Goddard Institute ◽  
Minimal Bias

AbstractObservational studies show a strong connection between the intraseasonal Madden-Julian oscillation (MJO) and the stratospheric quasi-biennial oscillation (QBO): the boreal winter MJO is stronger, more predictable, and has different teleconnections when the QBO in the lower stratosphere is easterly versus westerly. Despite the strength of the observed connection, global climate models do not produce an MJO-QBO link. Here the authors use a current-generation ocean-atmosphere coupled NASA Goddard Institute for Space Studies global climate model (Model E2.1) to examine the MJO-QBO link. To represent the QBO with minimal bias, the model zonal mean stratospheric zonal and meridional winds are relaxed to reanalysis fields from 1980-2017. The model troposphere, including the MJO, is allowed to freely evolve. The model with stratospheric nudging captures QBO signals well, including QBO temperature anomalies. However, an ensemble of nudged simulations still lacks an MJO-QBO connection.

scholarly journals Fidelity of the Observational/Reanalysis Datasets and Global Climate Models in Representation of Extreme Precipitation in East China

2018 ◽  
Vol 32 (1) ◽  
pp. 195-212 ◽  
Author(s):  
Sicheng He ◽  
Jing Yang ◽  
Qing Bao ◽  
Lei Wang ◽  
Bin Wang
Keyword(s):  
Extreme Precipitation ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Yangtze River Basin ◽  
Global Climate Model ◽  
Global Climate Models ◽  
Global Ocean ◽  
East China ◽  
Cmip5 Models

AbstractRealistic reproduction of historical extreme precipitation has been challenging for both reanalysis and global climate model (GCM) simulations. This work assessed the fidelities of the combined gridded observational datasets, reanalysis datasets, and GCMs [CMIP5 and the Chinese Academy of Sciences Flexible Global Ocean–Atmospheric Land System Model–Finite-Volume Atmospheric Model, version 2 (FGOALS-f2)] in representing extreme precipitation over East China. The assessment used 552 stations’ rain gauge data as ground truth and focused on the probability distribution function of daily precipitation and spatial structure of extreme precipitation days. The TRMM observation displays similar rainfall intensity–frequency distributions as the stations. However, three combined gridded observational datasets, four reanalysis datasets, and most of the CMIP5 models cannot capture extreme precipitation exceeding 150 mm day−1, and all underestimate extreme precipitation frequency. The observed spatial distribution of extreme precipitation exhibits two maximum centers, located over the lower-middle reach of Yangtze River basin and the deep South China region, respectively. Combined gridded observations and JRA-55 capture these two centers, but ERA-Interim, MERRA, and CFSR and almost all CMIP5 models fail to capture them. The percentage of extreme rainfall in the total rainfall amount is generally underestimated by 25%–75% in all CMIP5 models. Higher-resolution models tend to have better performance, and physical parameterization may be crucial for simulating correct extreme precipitation. The performances are significantly improved in the newly released FGOALS-f2 as a result of increased resolution and a more realistic simulation of moisture and heating profiles. This work pinpoints the common biases in the combined gridded observational datasets and reanalysis datasets and helps to improve models’ simulation of extreme precipitation, which is critically important for reliable projection of future changes in extreme precipitation.

scholarly journals Increased variability in Greenland Ice Sheet runoff from satellite observations

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Thomas Slater ◽  
Andrew Shepherd ◽  
Malcolm McMillan ◽  
Amber Leeson ◽  
Lin Gilbert ◽  
...  
Keyword(s):  
Ocean Circulation ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate Model ◽  
Regional Climate ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Model Simulations ◽  
Climate Model Simulations

AbstractRunoff from the Greenland Ice Sheet has increased over recent decades affecting global sea level, regional ocean circulation, and coastal marine ecosystems, and it now accounts for most of the contemporary mass imbalance. Estimates of runoff are typically derived from regional climate models because satellite records have been limited to assessments of melting extent. Here, we use CryoSat-2 satellite altimetry to produce direct measurements of Greenland’s runoff variability, based on seasonal changes in the ice sheet’s surface elevation. Between 2011 and 2020, Greenland’s ablation zone thinned on average by 1.4 ± 0.4 m each summer and thickened by 0.9 ± 0.4 m each winter. By adjusting for the steady-state divergence of ice, we estimate that runoff was 357 ± 58 Gt/yr on average – in close agreement with regional climate model simulations (root mean square difference of 47 to 60 Gt/yr). As well as being 21 % higher between 2011 and 2020 than over the preceding three decades, runoff is now also 60 % more variable from year-to-year as a consequence of large-scale fluctuations in atmospheric circulation. Because this variability is not captured in global climate model simulations, our satellite record of runoff should help to refine them and improve confidence in their projections.

scholarly journals Influence of albedo parameterization on surface mass balance in the perspective of Greenland ice sheet modelling in EC-Earth

2016 ◽  
Author(s):  
Michiel Helsen ◽  
Roderik Van de Wal ◽  
Thomas Reerink ◽  
Richard Bintanja ◽  
Marianne Sloth Madsen ◽  
...  
Keyword(s):  
Mass Balance ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Ice Sheets ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Surface Mass Balance ◽  
Surface Mass

Abstract. The albedo of the surface of ice sheets changes as a function of time, due to the effects of deposition of new snow, ageing of dry snow, melting and runoff. Currently, the calculation of the albedo of ice sheets is highly parameterized within the Earth System Model EC-Earth, by taking a constant value for areas with thick perennial snow cover. This is one of the reasons that the surface mass balance (SMB) of the Greenland ice sheet (GrIS) is poorly resolved in the model. To improve this, eight snow albedo schemes are evaluated here. The resulting SMB is downscaled from the lower resolution global climate model topography to the higher resolution ice sheet topography of the GrIS, such that the influence of these different SMB climatologies on the long-term evolution of the GrIS is tested by ice sheet model simulations. This results in an optimised albedo parameterization that can be used in future EC-Earth simulations with an interactive ice sheet component.

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 Large sensitivity of a Greenland ice sheet model to atmospheric forcing fields

2012 ◽  
Vol 6 (2) ◽  
pp. 1037-1083 ◽  
Author(s):  
A. Quiquet ◽  
H. J. Punge ◽  
C. Ritz ◽  
X. Fettweis ◽  
M. Kageyama ◽  
...  
Keyword(s):  
General Circulation ◽  
Climate Models ◽  
Climate Model ◽  
Ice Sheets ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Global Climate Models ◽  
Near Surface ◽  
Temperature And Precipitation ◽  
The Impact

Abstract. The prediction of future climate and ice sheet evolution requires coupling of ice sheet and climate models. Before proceeding to a coupled setup, we propose to analyze the impact of model simulated climate on an ice sheet. Here, we undertake this exercise for a set of regional and global climate models. Modelled near surface air temperature and precipitation are provided as upper boundary condition to the GRISLI (GRenoble Ice Shelf and Land Ice model) hybrid ice sheet model (ISM) in its Greenland configuration. After 20 kyr of simulation, the resulting ice sheets highlight the differences between the climate models. While modelled ice sheet sizes are generally comparable to the observed ones, there are considerable deviations among the ice sheets on regional scales. These can be explained by difficulties in modelling local temperature and precipitation near the coast. This is especially true in the case of global models. But the deviations of each climate model are also due to the differences in the atmospheric general circulation. In the context of coupling ice sheet and climate models, we conclude that appropriate downscaling methods will be needed and systematic corrections of the climatic variables at the interface may be required in some cases to obtain realistic results for the Greenland ice sheet (GIS).

A regional atmospheric warming threshold for irreversible Greenland ice sheet mass loss

2020 ◽  
Author(s):  
Michiel van den Broeke ◽  
Brice Noël ◽  
Leo van Kampenhout ◽  
Willem-Jan van de Berg
Keyword(s):  
Mass Loss ◽  
Mass Balance ◽  
Sea Level Rise ◽  
Sea Level ◽  
Climate Models ◽  
Climate Model ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Global Climate Models ◽  
The Future

<p>The mass balance of the Greenland ice sheet (GrIS, units Gt per year) equals the surface mass balance (SMB) minus solid ice discharge across the grounding line. As the latter is definite positive, an important threshold for irreversible GrIS mass loss occurs when long-term average SMB becomes negative. For this to happen, runoff (mainly meltwater, some rain) must exceed mass accumulation (mainly snowfall minus sublimation). Even for a single year, this threshold has not been passed since at least 1958, the first year with reliable estimates of SMB components, although recent years with warm summers (e.g. 2012 and 2019) came close. Simply extrapolating the recent (1991-present) negative SMB trend into the future suggests that the SMB = 0 threshold could be reached before ~2040, but such predictions are extremely uncertain given the very large interannual SMB variability, the relative brevity of the time series and the uncertainty in future warming. In this study we use a cascade of models, extensively evaluated with in-situ and remotely sensed (GRACE) SMB observations, to better constrain the future regional warming threshold for the 5-year average GrIS SMB to become negative. To this end, a 1950-2100 climate change run with the global model CESM2 (app. 100 km resolution) was dynamically downscaled using the regional climate model RACMO2 (app. 11 km), which in turn was statistically downscaled to 1 km resolution. The result is a threshold regional Greenland warming of close to 4 degrees. We then use a range of CMIP5 and CMIP6 global climate models to translate the regional value into a global warming threshold for various warming scenarios, including its timing this century. We find substantial differences, ranging from stabilization before the threshold is reached in the RCP/SSP2.6 scenarios with a limited but still significant sea-level rise contribution (< 5 cm by 2100) to an imminent crossing of the warming threshold for the RCP/SSP8.5 scenarios with substantial and ever-growing contributions to sea level rise (> 10 cm by 2100). These results stress the need for strong mitigation to avoid irreversible GrIS mass loss. We finish by discussing the caveats and uncertainties of our approach.</p>

scholarly journals High-end climate change impact on European runoff and low flows – exploring the effects of forcing biases

2016 ◽  
Vol 20 (5) ◽  
pp. 1785-1808 ◽  
Author(s):  
Lamprini V. Papadimitriou ◽  
Aristeidis G. Koutroulis ◽  
Manolis G. Grillakis ◽  
Ioannis K. Tsanis
Keyword(s):  
Global Warming ◽  
Bias Correction ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Data Set ◽  
Low Flows ◽  
The Impact ◽  
Selection Of

Abstract. Climate models project a much more substantial warming than the 2 °C target under the more probable emission scenarios, making higher-end scenarios increasingly plausible. Freshwater availability under such conditions is a key issue of concern. In this study, an ensemble of Euro-CORDEX projections under RCP8.5 is used to assess the mean and low hydrological states under +4 °C of global warming for the European region. Five major European catchments were analysed in terms of future drought climatology and the impact of +2 °C versus +4 °C global warming was investigated. The effect of bias correction of the climate model outputs and the observations used for this adjustment was also quantified. Projections indicate an intensification of the water cycle at higher levels of warming. Even for areas where the average state may not considerably be affected, low flows are expected to reduce, leading to changes in the number of dry days and thus drought climatology. The identified increasing or decreasing runoff trends are substantially intensified when moving from the +2 to the +4° of global warming. Bias correction resulted in an improved representation of the historical hydrology. It is also found that the selection of the observational data set for the application of the bias correction has an impact on the projected signal that could be of the same order of magnitude to the selection of the Global Climate Model (GCM).

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