scholarly journals Exploiting strength, discounting weakness: combining information from multiple climate simulators

2013 ◽  
Vol 371 (1991) ◽  
pp. 20120388 ◽  
Author(s):  
Richard E. Chandler
Keyword(s):  
Climate Change ◽  
Prior Knowledge ◽  
Bayesian Methods ◽  
Full Range ◽  
Internal Variability ◽  
Future Climate ◽  
Climate Modelling ◽  
Climate Change Projections ◽  
Statistical Framework ◽  
Combining Information

This paper presents and analyses a statistical framework for combining projections of future climate from different climate simulators. The framework recognizes explicitly that all currently available simulators are imperfect; that they do not span the full range of possible decisions on the part of the climate modelling community; and that individual simulators have strengths and weaknesses. Information from individual simulators is automatically weighted, alongside that from historical observations and from prior knowledge. The weights for a simulator depend on its internal variability, its expected consensus with other simulators, the internal variability of the real climate and the propensity of simulators collectively to deviate from reality. The framework demonstrates, moreover, that some subjective judgements are inevitable when interpreting multiple climate change projections: by clarifying precisely what those judgements are, it provides increased transparency in the ensuing analyses. Although the framework is straightforward to apply in practice by a user with some understanding of Bayesian methods, the emphasis here is on conceptual aspects illustrated with a simplified artificial example. A ‘poor man's version’ is also presented, which can be implemented straightforwardly in simple situations.

scholarly journals Regionalization of Climate Change Simulations over the Eastern Mediterranean

2009 ◽  
Vol 22 (8) ◽  
pp. 1944-1961 ◽  
Author(s):  
Bariş Önol ◽  
Fredrick H. M. Semazzi
Keyword(s):  
Climate Change ◽  
Regional Climate Model ◽  
Temperature Increase ◽  
Climate Model ◽  
Eastern Mediterranean ◽  
Regional Climate ◽  
Future Climate ◽  
Climate Change Projections ◽  
Model Simulations ◽  
The Future

Abstract In this study, the potential role of global warming in modulating the future climate over the eastern Mediterranean (EM) region has been investigated. The primary vehicle of this investigation is the Abdus Salam International Centre for Theoretical Physics Regional Climate Model version 3 (ICTP-RegCM3), which was used to downscale the present and future climate scenario simulations generated by the NASA’s finite-volume GCM (fvGCM). The present-day (1961–90; RF) simulations and the future climate change projections (2071–2100; A2) are based on the Intergovernmental Panel on Climate Change (IPCC) greenhouse gas (GHG) emissions. During the Northern Hemispheric winter season, the general increase in precipitation over the northern sector of the EM region is present both in the fvGCM and RegCM3 model simulations. The regional model simulations reveal a significant increase (10%–50%) in winter precipitation over the Carpathian Mountains and along the east coast of the Black Sea, over the Kackar Mountains, and over the Caucasus Mountains. The large decrease in precipitation over the southeastern Turkey region that recharges the Euphrates and Tigris River basins could become a major source of concern for the countries downstream of this region. The model results also indicate that the autumn rains, which are primarily confined over Turkey for the current climate, will expand into Syria and Iraq in the future, which is consistent with the corresponding changes in the circulation pattern. The climate change over EM tends to manifest itself in terms of the modulation of North Atlantic Oscillation. During summer, temperature increase is as large as 7°C over the Balkan countries while changes for the rest of the region are in the range of 3°–4°C. Overall the temperature increase in summer is much greater than the corresponding changes during winter. Presentation of the climate change projections in terms of individual country averages is highly advantageous for the practical interpretation of the results. The consistence of the country averages for the RF RegCM3 projections with the corresponding averaged station data is compelling evidence of the added value of regional climate model downscaling.

The future of European floodplain wetlands under a changing climate

2011 ◽  
Vol 2 (2-3) ◽  
pp. 106-122 ◽  
Author(s):  
Christof Schneider ◽  
Martina Flörke ◽  
Gertjan Geerling ◽  
Harm Duel ◽  
Mateusz Grygoruk ◽  
...  
Keyword(s):  
Climate Change ◽  
Global Scale ◽  
Future Climate Change ◽  
Anthropogenic Factors ◽  
Climate Modelling ◽  
Floodplain Wetlands ◽  
Potential Threat ◽  
Climate Change Projections ◽  
The Future ◽  
Floodplain Inundation

In the future, climate change may severely alter flood patterns over large regional scales. Consequently, besides other anthropogenic factors, climate change represents a potential threat to river ecosystems. The aim of this study is to evaluate the effect of climate change on floodplain inundation for important floodplain wetlands in Europe and to place these results in an ecological context. This work is performed within the Water Scenarios for Europe and Neighbouring States (SCENES) project considering three different climate change projections for the 2050s. The global scale hydrological model WaterGAP is applied to simulate current and future river discharges that are then used to: (i) estimate bankfull flow conditions, (ii) determine three different inundation parameters, and (iii) evaluate the hydrological consequences and their relation to ecology. Results of this study indicate that in snow-affected catchments (e.g. in Central and Eastern Europe) inundation may appear earlier in the year. Duration and volume of inundation are expected to decrease. This will lead to a reduction in habitat for fish, vertebrates, water birds and floodplain-specific vegetation causing a loss in biodiversity, floodplain productivity and fish production. Contradictory results occur in Spain, France, Southern England and the Benelux countries. This reflects the uncertainties of current climate modelling for specific seasons.

Future Climate Change Projections of the Kabul River Basin Using a Multi-model Ensemble of High-Resolution Statistically Downscaled Data

2018 ◽  
Vol 2 (3) ◽  
pp. 477-497 ◽  
Author(s):  
Syed Ahsan Ali Bokhari ◽  
Burhan Ahmad ◽  
Jahangir Ali ◽  
Shakeel Ahmad ◽  
Haris Mushtaq ◽  
...  
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
River Basin ◽  
Future Climate ◽  
Future Climate Change ◽  
Model Ensemble ◽  
Climate Change Projections ◽  
Kabul River

Downscaling future climate change projections over Puerto Rico using a non-hydrostatic atmospheric model

2018 ◽  
Vol 147 (1-2) ◽  
pp. 133-147 ◽  
Author(s):  
Amit Bhardwaj ◽  
Vasubandhu Misra ◽  
Akhilesh Mishra ◽  
Adrienne Wootten ◽  
Ryan Boyles ◽  
...  
Keyword(s):  
Climate Change ◽  
Puerto Rico ◽  
Atmospheric Model ◽  
Future Climate ◽  
Future Climate Change ◽  
Climate Change Projections

Recent and near future climate change in the Antarctic Peninsula

2020 ◽  
Author(s):  
Deniz Bozkurt ◽  
David H. Bromwich ◽  
Roberto Rondanelli
Keyword(s):  
Climate Change ◽  
Sea Ice ◽  
Antarctic Peninsula ◽  
Future Climate ◽  
Future Climate Change ◽  
Climate Change Projections ◽  
Domain Configuration ◽  
Increasing Trend ◽  
The Antarctic ◽  
Near Future

<p>This study assesses the recent (1990-2015) and near future (2020-2045) climate change in the Antarctic Peninsula. For the recent period, we make the use of available observations, ECMWF’s ERA5 and its predecessor ERA-Interim, as well as regional climate model simulations. Given the different climate characteristics at each side of the mountain barrier, we principally assess the results considering the windward and leeward sides. We use hindcast simulations performed with Polar-WRF over the Antarctic Peninsula on a nested domain configuration at 45 km (PWRF-45) and 15 km (PWRF-15) spatial resolutions for the period 1990-2015. In addition, we include hindcast simulations of KNMI-RACMO21P obtained from the CORDEX-Antarctica domain (~ 50 km) for further comparisons. For the near future climate change evaluation, we principally use historical simulations and climate change projections (until 2050s, RCP85) performed with PWRF (forced with NCAR-CESM1) on the same domain configuration of the hindcast simulations. Recent observed trends show contrasts between summer and autumn. Annual warming (cooling) trend is notable on the windward (leeward) coasts of the peninsula. Unlike the reanalysis, numerical simulations indicate a clear pattern of windward warming and leeward cooling at annual time-scale. These temperature changes are accompanied by a decreasing and increasing trend in sea ice on the windward and leeward coasts, respectively. An increasing trend of precipitation is notable on the central and northern peninsula. High resolution climate change projections (PWRF-15, RCP85) indicate that the recent warming trend on the windward coasts tends to continue in the near future (2020-2045) and the projections exhibit an increase in temperature by ~ 1.5°C and 0.5°C on the windward and leeward coasts, respectively. In the same period, the projections show an increase in precipitation over the peninsula (5% to 10%). The more notable warming projected on the windward side causes more increases in surface melting (~ +20% to +80%) and more sea ice loss (-4% to -20%) on this side. Results show that the windward coasts of central and northern Antarctic Peninsula can be considered as "hotspots" with notable increases in temperature, surface melting and sea ice loss.</p>

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.

Chaos in Estimates of Climate Change Impacts

2020 ◽  
Author(s):  
Emanuele Massetti ◽  
Emanuele Di Lorenzo
Keyword(s):  
Climate Change ◽  
Large Scale ◽  
Initial Conditions ◽  
Climate Change Impacts ◽  
Internal Variability ◽  
Future Climate ◽  
Climate System ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Exogenous Forcing

<p>Estimates of physical, social and economic impacts of climate change are less accurate than usually thought because the impacts literature has largely neglected the internal variability of the climate system. Climate change scenarios are highly sensitive to the initial conditions of the climate system due the chaotic dynamics of weather. As the initial conditions of the climate system are unknown with a sufficiently high level of precision, each future climate scenario – for any given model parameterization and level of exogenous forcing – is only one of the many possible future realizations of climate. The impacts literature usually relies on only one realization randomly taken out of the full distribution of future climates. Here we use one of the few available large scale ensembles produced to study internal variability and an econometric model of climate change impacts on United States (US) agricultural productivity to show that the range of impacts is much larger than previously thought. Different ensemble members lead to significantly different impacts. Significant sign reversals are frequent. Relying only on one ensemble member leads to incorrect conclusions on the effect of climate change on agriculture in most of the US counties. Impacts studies should start using large scale ensembles of future climate change to predict damages. Climatologists should ramp-up efforts to run large ensembles for all GCMs, for at least the most frequently used scenarios of exogenous forcing.</p>

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