scholarly journals Mathematics applied to the climate system: outstanding challenges and recent progress

2013 ◽  
Vol 371 (1991) ◽  
pp. 20120518 ◽  
Author(s):  
Paul D. Williams ◽  
Michael J. P. Cullen ◽  
Michael K. Davey ◽  
John M. Huthnance
Keyword(s):  
General Circulation ◽  
Recent Progress ◽  
Initial Conditions ◽  
Global Climate ◽  
Climate Science ◽  
General Circulation Models ◽  
Climate System ◽  
Future Research ◽  
Theme Issue ◽  
Physically Based

The societal need for reliable climate predictions and a proper assessment of their uncertainties is pressing. Uncertainties arise not only from initial conditions and forcing scenarios, but also from model formulation. Here, we identify and document three broad classes of problems, each representing what we regard to be an outstanding challenge in the area of mathematics applied to the climate system. First, there is the problem of the development and evaluation of simple physically based models of the global climate. Second, there is the problem of the development and evaluation of the components of complex models such as general circulation models. Third, there is the problem of the development and evaluation of appropriate statistical frameworks. We discuss these problems in turn, emphasizing the recent progress made by the papers presented in this Theme Issue. Many pressing challenges in climate science require closer collaboration between climate scientists, mathematicians and statisticians. We hope the papers contained in this Theme Issue will act as inspiration for such collaborations and for setting future research directions.

scholarly journals Two Exploratory Uses for General Circulation Models in Climate Science

2021 ◽  
Vol 29 (4) ◽  
pp. 493-509
Author(s):  
Joseph Wilson
Keyword(s):  
General Circulation ◽  
Circulation Model ◽  
Climate Science ◽  
Dynamic Structure ◽  
General Circulation Models ◽  
Climate System ◽  
Earth Systems ◽  
Systems Model ◽  
Complex Models ◽  
Earth’S Climate

Abstract In this paper I present two ways in which climate modelers use general circulation models for exploratory purposes. The complexity of Earth’s climate system makes it difficult to predict precisely how lower-order climate dynamics will interact over time to drive higher-order dynamics. The same issues arise for complex models built to simulate climate behavior like the Community Earth Systems Model (CESM). I argue that as a result of system complexity, climate modelers use general circulation models to perform model dynamic exploration (MDE) and climate dynamic exploration (CDE). MDE and CDE help climate modelers to better understand the dynamic structure of the general circulation model system and the actual climate system, respectively.

4. Modelling future climate

2014 ◽  
pp. 46-67
Author(s):  
Mark Maslin
Keyword(s):  
Carbon Emissions ◽  
General Circulation ◽  
Climate Models ◽  
Global Climate ◽  
Three Dimensional ◽  
General Circulation Models ◽  
Future Climate ◽  
Climate System ◽  
Global Mean Sea Level ◽  
Global Mean

‘Modelling future climate’ is about understanding the fundamental physical processes of the climate system. Modelling future climate considers the carbon cycle, cooling effects, carbon emissions, and the complex three-dimensional general circulation models that examine and further our understanding of the global climate system and which are used to predict future global climate. Over 40 climate models were used in developing the IPCC projections for the 2013 report. The three main realistic carbon emissions pathways suggest the global mean surface temperature could rise by between 2.8°C and 5.4°C by 2100 and predict an increase in global mean sea level of between 52 cm and 98 cm in this timeframe.

scholarly journals Evaluating climate emulation: fundamental impulse testing of simple climate models

2019 ◽  
Vol 10 (4) ◽  
pp. 729-739 ◽  
Author(s):  
Adria K. Schwarber ◽  
Steven J. Smith ◽  
Corinne A. Hartin ◽  
Benjamin Aaron Vega-Westhoff ◽  
Ryan Sriver
Keyword(s):  
General Circulation ◽  
Climate Models ◽  
Climate Model ◽  
Chemical Species ◽  
Co2 Concentration ◽  
General Circulation Models ◽  
Climate System ◽  
Physically Based ◽  
Mean Climate ◽  
The Impact

Abstract. Simple climate models (SCMs) are numerical representations of the Earth's gas cycles and climate system. SCMs are easy to use and computationally inexpensive, making them an ideal tool in both scientific and decision-making contexts (e.g., complex climate model emulation, parameter estimation experiments, climate metric calculations, and probabilistic analyses). Despite their prolific use, the fundamental responses of SCMs are often not directly characterized. In this study, we use fundamental impulse tests of three chemical species (CO2, CH4, and black carbon – BC) to understand the fundamental gas cycle and climate system responses of several comprehensive (Hector v2.0, MAGICC 5.3, MAGICC 6.0) and idealized (FAIR v1.0, AR5-IR) SCMs. We find that while idealized SCMs are widely used, they fail to capture the magnitude and timescales of global mean climate responses under emissions perturbations, which can produce biased temperature results. Comprehensive SCMs, which have physically based nonlinear forcing and carbon cycle representations, show improved responses compared to idealized SCMs. Even the comprehensive SCMs, however, fail to capture the response timescales to BC emission perturbations seen recently in two general circulation models. Some comprehensive SCMs also generally respond faster than more complex models to a 4×CO2 concentration perturbation, although this was not evident for lower perturbation levels. These results suggest where improvements should be made to SCMs. Further, we demonstrate here a set of fundamental tests that we recommend as a standard evaluation suite for any SCM. Fundamental impulse tests allow users to understand differences in model responses and the impact of model selection on results.

scholarly journals Emerging Skill in Multi-Year Prediction of the Indian Ocean Dipole

2021 ◽  
Vol 3 ◽  
Author(s):  
F. Feba ◽  
Karumuri Ashok ◽  
Matthew Collins ◽  
Satish R. Shetye
Keyword(s):  
Indian Ocean ◽  
Indian Ocean Dipole ◽  
General Circulation ◽  
Global Climate ◽  
Climate Science ◽  
General Circulation Models ◽  
Prediction Skill ◽  
Ocean Prediction ◽  
The Indian Ocean ◽  
The Tropics

The Indian Ocean Dipole is a leading phenomenon of climate variability in the tropics, which affects the global climate. However, the best lead prediction skill for the Indian Ocean Dipole, until recently, has been limited to ~6 months before the occurrence of the event. Here, we show that multi-year prediction has made considerable advancement such that, for the first time, two general circulation models have significant prediction skills for the Indian Ocean Dipole for at least 2 years after initialization. This skill is present despite ENSO having a lead prediction skill of only 1 year. Our analysis of observed/reanalyzed ocean datasets shows that the source of this multi-year predictability lies in sub-surface signals that propagate from the Southern Ocean into the Indian Ocean. Prediction skill for a prominent climate driver like the Indian Ocean Dipole has wide-ranging benefits for climate science and society.

scholarly journals Contributors to linkage between Arctic warming and East Asian winter climate

2021 ◽  
Author(s):  
Xinping Xu ◽  
Shengping He ◽  
Yongqi Gao ◽  
Botao Zhou ◽  
Huijun Wang
Keyword(s):  
Sea Ice ◽  
General Circulation ◽  
Initial Conditions ◽  
Wave Train ◽  
East Asian ◽  
Surface Air Temperature ◽  
General Circulation Models ◽  
The Arctic ◽  
Winter Climate ◽  
Arctic Warming

AbstractPrevious modelling and observational studies have shown discrepancies in the interannual relationship of winter surface air temperature (SAT) between Arctic and East Asia, stimulating the debate about whether Arctic change can influence midlatitude climate. This study uses two sets of coordinated experiments (EXP1 and EXP2) from six different atmospheric general circulation models. Both EXP1 and EXP2 consist of 130 ensemble members, each of which in EXP1 (EXP2) was forced by the same observed daily varying sea ice and daily varying (daily climatological) sea surface temperature (SST) for 1982–2014 but with different atmospheric initial conditions. Large spread exists among ensemble members in simulating the Arctic–East Asian SAT relationship. Only a fraction of ensemble members can reproduce the observed deep Arctic warming–cold continent pattern which extends from surface to upper troposphere, implying the important role of atmospheric internal variability. The mechanisms of deep Arctic warming and shallow Arctic warming are further distinguished. Arctic warming aloft is caused primarily by poleward moisture transport, which in conjunction with the surface warming coupled with sea ice melting constitutes the surface-amplified deep Arctic warming throughout the troposphere. These processes associated with the deep Arctic warming may be related to the forcing of remote SST when there is favorable atmospheric circulation such as Rossby wave train propagating from the North Atlantic into the Arctic.

scholarly journals Simulation of Extreme Precipitation in Four Climate Regions in China by General Circulation Models (GCMs): Performance and Projections

Water ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1509
Author(s):  
Mengru Zhang ◽  
Xiaoli Yang ◽  
Liliang Ren ◽  
Ming Pan ◽  
Shanhu Jiang ◽  
...  
Keyword(s):  
Extreme Precipitation ◽  
General Circulation ◽  
Global Climate ◽  
Summer Precipitation ◽  
General Circulation Models ◽  
Cumulative Distribution ◽  
Extreme Precipitation Events ◽  
Increasing Trend ◽  
The Future ◽  
Semi Arid

In the context of global climate change, it is important to monitor abnormal changes in extreme precipitation events that lead to frequent floods. This research used precipitation indices to describe variations in extreme precipitation and analyzed the characteristics of extreme precipitation in four climatic (arid, semi-arid, semi-humid and humid) regions across China. The equidistant cumulative distribution function (EDCDF) method was used to downscale and bias-correct daily precipitation in eight Coupled Model Intercomparison Project Phase 5 (CMIP5) general circulation models (GCMs). From 1961 to 2005, the humid region had stronger and longer extreme precipitation compared with the other regions. In the future, the projected extreme precipitation is mainly concentrated in summer, and there will be large areas with substantial changes in maximum consecutive 5-day precipitation (Rx5) and precipitation intensity (SDII). The greatest differences between two scenarios (RCP4.5 and RCP8.5) are in semi-arid and semi-humid areas for summer precipitation anomalies. However, the area of the four regions with an increasing trend of extreme precipitation is larger under the RCP8.5 scenario than that under the RCP4.5 scenario. The increasing trend of extreme precipitation in the future is relatively pronounced, especially in humid areas, implying a potential heightened flood risk in these areas.

scholarly journals Boundary conditions for the Middle Miocene Climate Transition (MMCT v1.0)

2017 ◽  
Author(s):  
Amanda Frigola ◽  
Matthias Prange ◽  
Michael Schulz
Keyword(s):  
Boundary Conditions ◽  
General Circulation ◽  
Middle Miocene ◽  
Climate Models ◽  
Global Climate ◽  
Co2 Concentration ◽  
General Circulation Models ◽  
Global Climate Models ◽  
Ice Volume ◽  
Climate Transition

Abstract. The Middle Miocene Climate Transition was characterized by major Antarctic ice-sheet expansion and global cooling during the interval ~ 15–13 Ma. Here we present two sets of boundary conditions for global general circulation models characterizing the periods before (Middle Miocene Climatic Optimum; MMCO) and after (Middle Miocene Glaciation; MMG) the transition. These boundary conditions include Middle Miocene global topography, bathymetry and vegetation. Additionally, Antarctic ice volume and geometry, sea-level and atmospheric CO2 concentration estimates for the MMCO and the MMG are reviewed. The boundary-condition files are available for use as input in a wide variety of global climate models and constitute a valuable tool for modeling studies with a focus on the Middle Miocene.

scholarly journals An ensemble of AMIP simulations with prescribed land surface temperatures

2018 ◽  
Author(s):  
Duncan Ackerley ◽  
Robin Chadwick ◽  
Dietmar Dommenget ◽  
Paola Petrelli
Keyword(s):  
Surface Temperature ◽  
Land Surface ◽  
General Circulation ◽  
Global Climate ◽  
General Circulation Models ◽  
Solar Constant ◽  
Surface Temperatures ◽  
Co2 Concentrations ◽  
Land Surface Temperatures ◽  
Intercomparison Project

Abstract. General circulation models (GCMs) are routinely run under Atmospheric Modelling Intercomparison Project (AMIP) conditions with prescribed sea surface temperatures (SSTs) and sea ice concentrations (SICs) from observations. These AMIP simulations are often used to evaluate the role of the land and/or atmosphere in causing the development of systematic errors in such GCMs. Extensions to the original AMIP experiment have also been developed to evaluate the response of the global climate to increased SSTs (prescribed) and carbon-dioxide (CO2) as part of the Cloud Feedback Model Intercomparison Project (CFMIP). None of these international modelling initiatives has undertaken a set of experiments where the land conditions are also prescribed, which is the focus of the work presented in this paper. Experiments are performed initially with freely varying land conditions (surface temperature and, soil temperature and mositure) under five different configurations (AMIP, AMIP with uniform 4 K added to SSTs, AMIP SST with quadrupled CO2, AMIP SST and quadrupled CO2 without the plant stomata response, and increasing the solar constant by 3.3 %). Then, the land surface temperatures from the free-land experiments are used to perform a set of “AMIP-prescribed land” (PL) simulations, which are evaluated against their free-land counterparts. The PL simulations agree well with the free-land experiments, which indicates that the land surface is prescribed in a way that is consistent with the original free-land configuration. Further experiments are also performed with different combinations of SSTs, CO2 concentrations, solar constant and land conditions. For example, SST and land conditions are used from the AMIP simulation with quadrupled CO2 in order to simulate the atmospheric response to increased CO2 concentrations without the surface temperature changing. The results of all these experiments have been made publicly available for further analysis. The main aims of this paper are to provide a description of the method used and an initial validation of these AMIP-prescribed land experiments.

Forecast skill of autumn snow for European winter climate during the 20th century: A multi member seasonal prediction experiment

2021 ◽  
Author(s):  
Martin Wegmann ◽  
Yvan Orsolini ◽  
Antje Weisheimer ◽  
Bart van den Hurk ◽  
Gerrit Lohmann
Keyword(s):  
Snow Cover ◽  
General Circulation ◽  
Initial Conditions ◽  
Internal Variability ◽  
Seasonal Prediction ◽  
General Circulation Models ◽  
Reanalysis Data ◽  
Winter Climate ◽  
European Continent ◽  
Near Surface

<p>As the leading climate mode to explain wintertime climate variability over Europe, the North Atlantic Oscillation (NAO) has been extensively studied over the last decades. Recently, studies highlighted the state of the Northern Hemispheric cryosphere as possible predictor for the wintertime NAO (Cohen et al. 2014). Although several studies could find seasonal prediction skill in reanalysis data (Orsolini et al. 2016, Duville et al. 2017,Han & Sun 2018), experiments with ocean-atmosphere general circulation models (AOGCMs) still show conflicting results (Furtado et al. 2015, Handorf et al. 2015, Francis 2017, Gastineau et al. 2017). </p><p>Here we use two kinds ECMWF seasonal prediction ensembles starting with November initial conditions taken from the long-term reanalysis ERA-20C and forecasting the following three winter months. Besides the 110-year ensemble of 50 members representing internal variability of the atmosphere, we investigate a second ensemble of 20 members where initial conditions are split between low and high snow cover years for the Northern Hemisphere. We compare two recently used Eurasian snow cover indices for their skill in predicting winter climate for the European continent. Analyzing the two forecast experiments, we found that prediction runs starting with high snow index values in November result in significantly more negative NAO states in the following winter (DJF), which in turn modulates near surface temperatures. We track the atmospheric anomalies triggered by the high snow index through the tropo- and stratosphere as well as for the individual winter months to provide a physical explanation for the formation of this particular climate state.</p><p> </p>

Efficient estimation and ensemble generation in climate modelling

2007 ◽  
Vol 365 (1857) ◽  
pp. 2077-2088 ◽  
Author(s):  
J.D Annan ◽  
J.C Hargreaves
Keyword(s):  
Monte Carlo ◽  
Particle Filtering ◽  
General Circulation ◽  
Climate Models ◽  
General Circulation Models ◽  
Monte Carlo Sampling ◽  
Efficient Estimation ◽  
Future Research ◽  
Great Promise ◽  
Climate Modelling

In this paper, we review progress towards efficiently estimating parameters in climate models. Since the general problem is inherently intractable, a range of approximations and heuristic methods have been proposed. Simple Monte Carlo sampling methods, although easy to implement and very flexible, are rather inefficient, making implementation possible only in the very simplest models. More sophisticated methods based on random walks and gradient-descent methods can provide more efficient solutions, but it is often unclear how to extract probabilistic information from such methods and the computational costs are still generally too high for their application to state-of-the-art general circulation models (GCMs). The ensemble Kalman filter is an efficient Monte Carlo approximation which is optimal for linear problems, but we show here how its accuracy can degrade in nonlinear applications. Methods based on particle filtering may provide a solution to this problem but have yet to be studied in any detail in the realm of climate models. Statistical emulators show great promise for future research and their computational speed would eliminate much of the need for efficient sampling techniques. However, emulation of a full GCM has yet to be achieved and the construction of such represents a substantial computational task in itself.

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