scholarly journals Glacial runoff buffers droughts through the 21st century

2021 ◽  
Author(s):  
Lizz Ultee ◽  
Sloan Coats ◽  
Jonathan Mackay
Keyword(s):  
21St Century ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Global Climate Models ◽  
Comprehensive Picture ◽  
Glacial Runoff ◽  
Glacier Ice ◽  
Glacier Modeling

Abstract. Global climate model projections suggest that 21st century climate change will bring significant drying in the terrestrial midlatitudes. Recent glacier modeling suggests that runoff from glaciers will continue to provide substantial freshwater in many drainage basins, though the supply will generally diminish throughout the century. In the absence of dynamic glacier ice within global climate models (GCMs), a comprehensive picture of future drought conditions in glaciated regions has been elusive. Here, we leverage the results of existing GCM simulations and a global glacier model to evaluate glacial buffering of droughts in the Standardized Precipitation-Evapotranspiration Index (SPEI). We find that accounting for glacial runoff tends to increase multi-model ensemble mean SPEI and reduce drought frequency and severity, even in basins with relatively little glacier cover. Glacial drought buffering persists even as glacial runoff is projected to decline through the 21st century.

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 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 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.

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.

Model Uncertainty in Cloud–Circulation Coupling, and Cloud-Radiative Response to Increasing CO2, Linked to Biases in Climatological Circulation

2018 ◽  
Vol 31 (24) ◽  
pp. 10013-10020
Author(s):  
Bernard R. Lipat ◽  
Aiko Voigt ◽  
George Tselioudis ◽  
Lorenzo M. Polvani
Keyword(s):  
Model Uncertainty ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Global Climate Models ◽  
Hadley Cell ◽  
Temperature Structure ◽  
Climatological Circulation

Recent analyses of global climate models suggest that uncertainty in the coupling between midlatitude clouds and the atmospheric circulation contributes to uncertainty in climate sensitivity. However, the reasons behind model differences in the cloud–circulation coupling have remained unclear. Here, we use a global climate model in an idealized aquaplanet setup to show that the Southern Hemisphere climatological circulation, which in many models is biased equatorward, contributes to the model differences in the cloud–circulation coupling. For the same poleward shift of the Hadley cell (HC) edge, models with narrower climatological HCs exhibit stronger midlatitude cloud-induced shortwave warming than models with wider climatological HCs. This cloud-induced radiative warming results predominantly from a subsidence warming that decreases cloud fraction and is stronger for narrower HCs because of a larger meridional gradient in the vertical velocity. A comparison of our aquaplanet results with comprehensive climate models suggests that about half of the model uncertainty in the midlatitude cloud–circulation coupling stems from this impact of the circulation on the large-scale temperature structure of the atmosphere, and thus could be removed by improving the climatological circulation in models. This illustrates how understanding of large-scale dynamics can help reduce uncertainty in clouds and their response to climate change.

scholarly journals Characterizing Sources of Uncertainty from Global Climate Models and Downscaling Techniques

2017 ◽  
Vol 56 (12) ◽  
pp. 3245-3262 ◽  
Author(s):  
A. Wootten ◽  
A. Terando ◽  
B. J. Reich ◽  
R. P. Boyles ◽  
F. Semazzi
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Dynamical Downscaling ◽  
Global Climate ◽  
Global Climate Model ◽  
Global Climate Models ◽  
Model Experiments ◽  
Complete Set ◽  
Regional Adaptation ◽  
Model Ensembles

AbstractIn recent years, climate model experiments have been increasingly oriented toward providing information that can support local and regional adaptation to the expected impacts of anthropogenic climate change. This shift has magnified the importance of downscaling as a means to translate coarse-scale global climate model (GCM) output to a finer scale that more closely matches the scale of interest. Applying this technique, however, introduces a new source of uncertainty into any resulting climate model ensemble. Here a method is presented, on the basis of a previously established variance decomposition method, to partition and quantify the uncertainty in climate model ensembles that is attributable to downscaling. The method is applied to the southeastern United States using five downscaled datasets that represent both statistical and dynamical downscaling techniques. The combined ensemble is highly fragmented, in that only a small portion of the complete set of downscaled GCMs and emission scenarios is typically available. The results indicate that the uncertainty attributable to downscaling approaches ~20% for large areas of the Southeast for precipitation and ~30% for extreme heat days (>35°C) in the Appalachian Mountains. However, attributable quantities are significantly lower for time periods when the full ensemble is considered but only a subsample of all models is available, suggesting that overconfidence could be a serious problem in studies that employ a single set of downscaled GCMs. This article concludes with recommendations to advance the design of climate model experiments so that the uncertainty that accrues when downscaling is employed is more fully and systematically considered.

scholarly journals Cirrus clouds in a global climate model with a statistical cirrus cloud scheme

2009 ◽  
Vol 9 (4) ◽  
pp. 16607-16682 ◽  
Author(s):  
M. Wang ◽  
J. E. Penner
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Circulation Model ◽  
Global Climate Models ◽  
Cirrus Clouds ◽  
Cirrus Cloud ◽  
Ice Crystal ◽  
Low Level

Abstract. A statistical cirrus cloud scheme that accounts for mesoscale temperature perturbations is implemented into a coupled aerosol and atmospheric circulation model to better represent both cloud fraction and subgrid-scale supersaturation in global climate models. This new scheme is able to better simulate the observed probability distribution of relative humidity than the scheme that was implemented in an older version of the model. Heterogeneous ice nuclei (IN) are shown to affect not only high level cirrus clouds through their effect on ice crystal number concentration but also low level liquid clouds through the moistening effect of settling and evaporating ice crystals. As a result, the change in the net cloud forcing is not very sensitive to the change in ice crystal concentrations associated with heterogeneous IN because changes in high cirrus clouds and low level liquid clouds tend to cancel. Nevertheless, the change in the net radiative flux at the top of the atmosphere due to changes in IN is still large because of changes in the greenhouse effect of water vapor caused by the changes in ice crystal number concentrations. Changes in the magnitude of the assumed mesoscale temperature perturbations by 25% alter the ice crystal number concentrations and radiative fluxes by an amount that is similar to that from a factor of 10 change in the heterogeneous IN number concentrations.

scholarly journals Response of extreme precipitation to uniform surface warming in quasi-global aquaplanet simulations at high resolution

2021 ◽  
Vol 379 (2195) ◽  
pp. 20190543
Author(s):  
P. A. O’Gorman ◽  
Z. Li ◽  
W. R. Boos ◽  
J. Yuval
Keyword(s):  
High Resolution ◽  
Climate Models ◽  
Climate Model ◽  
Flash Flood ◽  
Global Climate ◽  
Global Climate Model ◽  
Global Climate Models ◽  
Precipitation Extremes ◽  
Coarse Grained ◽  
The Tropics

Projections of precipitation extremes in simulations with global climate models are very uncertain in the tropics, in part because of the use of parameterizations of deep convection and model deficiencies in simulating convective organization. Here, we analyse precipitation extremes in high-resolution simulations that are run without a convective parameterization on a quasi-global aquaplanet. The frequency distributions of precipitation rates and precipitation cluster sizes in the tropics of a control simulation are similar to the observed distributions. In response to climate warming, 3 h precipitation extremes increase at rates of up to 9 %   K − 1 in the tropics because of a combination of positive thermodynamic and dynamic contributions. The dynamic contribution at different latitudes is connected to the vertical structure of warming using a moist static stability. When the precipitation rates are first averaged to a daily timescale and coarse-grained to a typical global climate-model resolution prior to calculating the precipitation extremes, the response of the precipitation extremes to warming becomes more similar to what was found previously in coarse-resolution aquaplanet studies. However, the simulations studied here do not exhibit the high rates of increase of tropical precipitation extremes found in projections with some global climate models. This article is part of a discussion meeting issue ‘Intensification of short-duration rainfall extremes and implications for flash flood risks’.

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.

Climate Feedbacks in CCSM3 under Changing CO2 Forcing. Part I: Adapting the Linear Radiative Kernel Technique to Feedback Calculations for a Broad Range of Forcings

2012 ◽  
Vol 25 (15) ◽  
pp. 5260-5272 ◽  
Author(s):  
Alexandra K. Jonko ◽  
Karen M. Shell ◽  
Benjamin M. Sanderson ◽  
Gokhan Danabasoglu
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Global Climate Models ◽  
Climate Feedbacks ◽  
Radiative Fluxes ◽  
Co2 Concentrations ◽  
Climate Model Simulations ◽  
Linear Technique

Abstract Climate feedbacks vary strongly among climate models and continue to represent a major source of uncertainty in estimates of the response of climate to anthropogenic forcings. One method to evaluate feedbacks in global climate models is the radiative kernel technique, which is well suited for model intercomparison studies because of its computational efficiency. However, the usefulness of this technique is predicated on the assumption of linearity between top-of-atmosphere (TOA) radiative fluxes and feedback variables, limiting its application to simulations of small climate perturbations, where nonlinearities can be neglected. This paper presents an extension of the utility of this linear technique to large forcings, using global climate model simulations forced with CO2 concentrations ranging from 2 to 8 times present-day values. Radiative kernels depend on the model’s radiative transfer algorithm and climate base state. For large warming, kernels based on the present-day climate significantly underestimate longwave TOA flux changes and somewhat overestimate shortwave TOA flux changes. These biases translate to inaccurate feedback estimates. It is shown that a combination of present-day kernels and kernels computed using a large forcing climate base state leads to significant improvement in the approximation of TOA flux changes and increased reliability of feedback estimates. While using present-day kernels results in a climate sensitivity that remains constant, using the new kernels shows that sensitivity increases significantly with each successive doubling of CO2 concentrations.

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