Should we believe model predictions of future climate change?

2008 ◽  
Vol 366 (1885) ◽  
pp. 4647-4664 ◽  
Author(s):  
Reto Knutti
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Computer Models ◽  
Future Climate ◽  
Future Climate Change ◽  
Climate Modelling ◽  
Policy Makers ◽  
The Public ◽  
Numerical Computer ◽  
Model Predictions

Predictions of future climate are based on elaborate numerical computer models. As computational capacity increases and better observations become available, one would expect the model predictions to become more reliable. However, are they really improving, and how do we know? This paper discusses how current climate models are evaluated, why and where scientists have confidence in their models, how uncertainty in predictions can be quantified, and why models often tend to converge on what we observe but not on what we predict. Furthermore, it outlines some strategies on how the climate modelling community may overcome some of the current deficiencies in the attempt to provide useful information to the public and policy-makers.

scholarly journals Predicted Future Benefits for an Endemic Rodent in the Irano-Turanian Region

Climate ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 16
Author(s):  
Suzanna Meeussen ◽  
Anouschka Hof
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Species Distribution Modelling ◽  
Geographic Range ◽  
Future Climate ◽  
Future Climate Change ◽  
Distribution Ranges ◽  
Bioclimatic Variables ◽  
Suitable Area ◽  
The Impact

Climate change is expected to have an impact on the geographical distribution ranges of species. Endemic species and those with a restricted geographic range may be especially vulnerable. The Persian jird (Meriones persicus) is an endemic rodent inhabiting the mountainous areas of the Irano-Turanian region, where future desertification may form a threat to the species. In this study, the species distribution modelling algorithm MaxEnt was used to assess the impact of future climate change on the geographic distribution range of the Persian jird. Predictions were made under two Representative Concentration Pathways and five different climate models for the years 2050 and 2070. It was found that both bioclimatic variables and land use variables were important in determining potential suitability of the region for the species to occur. In most cases, the future predictions showed an expansion of the geographic range of the Persian jird which indicates that the species is not under immediate threat. There are however uncertainties with regards to its current range. Predictions may therefore be an over or underestimation of the total suitable area. Further research is thus needed to confirm the current geographic range of the Persian jird to be able to improve assessments of the impact of future climate change.

scholarly journals An Assessment of Recent and Future Temperature Change over the Sichuan Basin, China, Using CMIP5 Climate Models

2017 ◽  
Vol 30 (17) ◽  
pp. 6701-6722 ◽  
Author(s):  
Daniel Bannister ◽  
Michael Herzog ◽  
Hans-F. Graf ◽  
J. Scott Hosking ◽  
C. Alan Short
Keyword(s):  
Climate Change ◽  
Sichuan Basin ◽  
Climate Models ◽  
Distribution Functions ◽  
Future Climate ◽  
First Century ◽  
Future Climate Change ◽  
Change Scenario ◽  
The Sichuan Basin ◽  
Twenty First Century

The Sichuan basin is one of the most densely populated regions of China, making the area particularly vulnerable to the adverse impacts associated with future climate change. As such, climate models are important for understanding regional and local impacts of climate change and variability, like heat stress and drought. In this study, climate models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) are validated over the Sichuan basin by evaluating how well each model can capture the phase, amplitude, and variability of the regionally observed mean, maximum, and minimum temperature between 1979 and 2005. The results reveal that the majority of the models do not capture the basic spatial pattern and observed means, trends, and probability distribution functions. In particular, mean and minimum temperatures are underestimated, especially during the winter, resulting in biases exceeding −3°C. Models that reasonably represent the complex basin topography are found to generally have lower biases overall. The five most skillful climate models with respect to the regional climate of the Sichuan basin are selected to explore twenty-first-century temperature projections for the region. Under the CMIP5 high-emission future climate change scenario, representative concentration pathway 8.5 (RCP8.5), the temperatures are projected to increase by approximately 4°C (with an average warming rate of +0.72°C decade−1), with the greatest warming located over the central plains of the Sichuan basin, by 2100. Moreover, the frequency of extreme months (where mean temperature exceeds 28°C) is shown to increase in the twenty-first century at a faster rate compared to the twentieth century.

scholarly journals Past temperature reconstructions from deep ice cores: relevance for future climate change

2006 ◽  
Vol 2 (2) ◽  
pp. 145-165 ◽  
Author(s):  
V. Masson-Delmotte ◽  
G. Dreyfus ◽  
P. Braconnot ◽  
S. Johnsen ◽  
J. Jouzel ◽  
...  
Keyword(s):  
Climate Change ◽  
Temperature Change ◽  
Climate Models ◽  
Ice Core ◽  
Ice Cores ◽  
Future Climate ◽  
Future Climate Change ◽  
Interglacial Period ◽  
Temperature Reconstructions

Abstract. Ice cores provide unique archives of past climate and environmental changes based only on physical processes. Quantitative temperature reconstructions are essential for the comparison between ice core records and climate models. We give an overview of the methods that have been developed to reconstruct past local temperatures from deep ice cores and highlight several points that are relevant for future climate change. We first analyse the long term fluctuations of temperature as depicted in the long Antarctic record from EPICA Dome C. The long term imprint of obliquity changes in the EPICA Dome C record is highlighted and compared to simulations conducted with the ECBILT-CLIO intermediate complexity climate model. We discuss the comparison between the current interglacial period and the long interglacial corresponding to marine isotopic stage 11, ~400 kyr BP. Previous studies had focused on the role of precession and the thresholds required to induce glacial inceptions. We suggest that, due to the low eccentricity configuration of MIS 11 and the Holocene, the effect of precession on the incoming solar radiation is damped and that changes in obliquity must be taken into account. The EPICA Dome C alignment of terminations I and VI published in 2004 corresponds to a phasing of the obliquity signals. A conjunction of low obliquity and minimum northern hemisphere summer insolation is not found in the next tens of thousand years, supporting the idea of an unusually long interglacial ahead. As a second point relevant for future climate change, we discuss the magnitude and rate of change of past temperatures reconstructed from Greenland (NorthGRIP) and Antarctic (Dome C) ice cores. Past episodes of temperatures above the present-day values by up to 5°C are recorded at both locations during the penultimate interglacial period. The rate of polar warming simulated by coupled climate models forced by a CO2 increase of 1% per year is compared to ice-core-based temperature reconstructions. In Antarctica, the CO2-induced warming lies clearly beyond the natural rhythm of temperature fluctuations. In Greenland, the CO2-induced warming is as fast or faster than the most rapid temperature shifts of the last ice age. The magnitude of polar temperature change in response to a quadrupling of atmospheric CO2 is comparable to the magnitude of the polar temperature change from the Last Glacial Maximum to present-day. When forced by prescribed changes in ice sheet reconstructions and CO2 changes, climate models systematically underestimate the glacial-interglacial polar temperature change.

Assessment of future climate change impacts on the hydrological regime of selected Greek areas with different climate conditions

2016 ◽  
Vol 48 (5) ◽  
pp. 1327-1342 ◽  
Author(s):  
Spyridon Paparrizos ◽  
Andreas Matzarakis
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Hydrological Cycle ◽  
Meteorological Data ◽  
Hydrological Regime ◽  
Future Climate ◽  
Future Climate Change ◽  
Water Losses ◽  
Climate Conditions ◽  
The Future

Assessment of future variations of streamflow is essential for research regarding climate and climate change. This study is focused on three agricultural areas widespread in Greece and aims to assess the future response of annual and seasonal streamflow and its impacts on the hydrological regime, in combination with other fundamental aspects of the hydrological cycle in areas with different climate classification. ArcSWAT ArcGIS extension was used to simulate the future responses of streamflow. Future meteorological data were obtained from various regional climate models, and analysed for the periods 2021–2050 and 2071–2100. In all the examined areas, streamflow is expected to be reduced. Areas characterized by continental climate will face minor reductions by the mid-century that will become very intense by the end and thus these areas will become more resistant to future changes. Autumn season will face the strongest reductions. Areas characterized by Mediterranean conditions will be very vulnerable in terms of future climate change and winter runoff will face the most significant decreases. Reduced precipitation is the main reason for decreased streamflow. High values of actual evapotranspiration by the end of the century will act as an inhibitor towards reduced runoff and partly counterbalance the water losses.

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 Assessment of Future Climate Change Projections Using Multiple Global Climate Models

2019 ◽  
Vol 5 (10) ◽  
pp. 2152-2166 ◽  
Author(s):  
Han Thi Oo ◽  
Win Win Zin ◽  
Cho Cho Thin Kyi
Keyword(s):  
Climate Change ◽  
Temperature Rise ◽  
Climate Models ◽  
Hydrological Cycle ◽  
Winter Season ◽  
Future Climate ◽  
Maximum Temperature ◽  
Future Climate Change ◽  
Seasonal Temperature ◽  
Suitable Climate

Nowadays, the hydrological cycle which alters river discharge and water availability is affected by climate change. Therefore, the understanding of climate change is curial for the security of hydrologic conditions of river basins. The main purpose of this study is to assess the projections of future climate across the Upper Ayeyarwady river basin for its sustainable development and management of water sector for this area. Global Ten climate Models available from CMIP5 represented by the IPCC for its fifth Assessment Report were bias corrected using linear scaling method to generate the model error. Among the GCMs, a suitable climate model for each station is selected based on the results of performance indicators (R2 and RMSE). Future climate data are projected based on the selected suitable climate models by using future climate scenarios: RCP2.6, RCP4.5, and RCP8.5. According to this study, future projection indicates to increase in precipitation amounts in the rainy and winter season and diminishes in summer season under all future scenarios. Based on the seasonal temperature changes analysis for all stations,  the future temperature are  predicted to steadily increase with higher rates during summer than the other two seasons and it can also be concluded that the monthly minimum temperature rise is a bit larger than the maximum temperature rise in all seasons.

Simulation of the mid-Pliocene Warm Period using HadGEM3-GC31-LL: Pliocene climate relative to the pre-industrial era, previous model versions, other climate models and proxy data

2021 ◽  
Author(s):  
Charles Williams ◽  
Daniel Lunt ◽  
Alistair Sellar ◽  
William Roberts ◽  
Robin Smith ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Model ◽  
High Sensitivity ◽  
Warm Period ◽  
Future Climate ◽  
Future Climate Change ◽  
Last Interglacial ◽  
Proxy Data ◽  
Global Mean

<p>To better understand the processes contributing to future climate change, palaeoclimate model simulations are an important tool because they allow testing of the models’ ability to simulate very different climates than that of today.  As part of CMIP6/PMIP4, the latest version of the UK’s physical climate model, HadGEM3-GC31-LL (hereafter, for brevity, HadGEM3), was recently used to simulate the mid-Holocene (~6 ka) and Last Interglacial (~127 ka) simulations and the results were compared to the preindustrial era, previous versions of the same model and proxy data (see Williams et al. 2020, Climate of the Past).  Here, we use the same model to go further back in time, presenting the results from the mid-Pliocene Warm Period (~3.3 to 3 ma, hereafter the “Pliocene” for brevity).  This period is of particular interest when it comes to projections of future climate change under various scenarios of CO<sub>2</sub> emissions, because it is the most recent time in Earth’s history when CO<sub>2</sub> levels were roughly equivalent to today.  In response, albeit due to slower mechanisms than today’s anthropogenic fossil fuel driven-change, during the Pliocene global mean temperatures were 2-3°C higher than today, more so at the poles.</p><p> </p><p>Here, we present results from the HadGEM3 Pliocene simulation.  The model is responding to the Pliocene boundary conditions in a manner consistent with current understanding and existing literature.  When compared to the preindustrial era, global mean temperatures are currently ~5°C higher, with the majority of warming coming from high latitudes due to polar amplification from a lack of sea ice.  Relative to other models within the Pliocene Modelling Intercomparison Project (PlioMIP), this is the 2<sup>nd</sup> warmest model, with the majority of others only showing up to a 4.5°C increase and many a lot less.  This is consistent with the relatively high sensitivity of HadGEM3, relative to other CMIP6-class models.  When compared to a previous generation of the same UK model, HadCM3, similar patterns of both surface temperature and precipitation changes are shown (relative to preindustrial).  Moreover, when the simulations are compared to proxy data, the results suggest that the HadGEM3 Pliocene simulation is closer to the reconstructions than its predecessor.</p>

scholarly journals A mathematical approach to understanding emergent constraints

2018 ◽  
Vol 9 (3) ◽  
pp. 999-1012 ◽  
Author(s):  
Femke J. M. M. Nijsse ◽  
Henk A. Dijkstra
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Future Climate ◽  
Future Climate Change ◽  
Mathematical Approach ◽  
Empirical Relationships ◽  
Current Climate ◽  
Emergent Constraints

Abstract. One of the approaches to constrain uncertainty in climate models is the identification of emergent constraints. These are physically explainable empirical relationships between a particular simulated characteristic of the current climate and future climate change from an ensemble of climate models, which can be exploited using current observations. In this paper, we develop a theory to understand the appearance of such emergent constraints. Based on this theory, we also propose a classification for emergent constraints, and applications are shown for several idealized climate models.

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