scholarly journals Performance of Pattern-Scaled Climate Projections under High-End Warming. Part I: Surface Air Temperature over Land

2018 ◽  
Vol 31 (14) ◽  
pp. 5667-5680 ◽  
Author(s):  
Timothy J. Osborn ◽  
Craig J. Wallace ◽  
Jason A. Lowe ◽  
Dan Bernie
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
General Circulation ◽  
Surface Air Temperature ◽  
Circulation Model ◽  
Climate Change Impacts ◽  
Climate Change Signal ◽  
Climate Projections ◽  
Actual Performance ◽  
Mean Square Errors

Pattern scaling is widely used to create climate change projections to investigate future impacts. We consider the performance of pattern scaling for emulating the HadGEM2-ES general circulation model (GCM) paying particular attention to “high end” warming scenarios and to different choices of GCM simulations used to diagnose the climate change patterns. We demonstrate that evaluating pattern-scaling projections by comparing them with GCM simulations containing unforced variability gives a significantly less favorable view of the actual performance of pattern scaling. Using a four-member initial-condition ensemble of HadGEM2-ES simulations, we infer that the root-mean-square errors of pattern-scaled monthly temperature changes over land are less than 0.25°C for global warming up to approximately 3.5°C. Some regional errors are larger than this and, for this GCM, there is a tendency for pattern scaling to underestimate warming over land. For warming above 3.5°C, the pattern-scaled projection errors grow but remain small relative to the climate change signal. We investigate whether patterns diagnosed by pooling GCM experiments from several scenarios are suitable for emulating the GCM under a high-end warming scenario. For global warming up to 3.5°C, pattern scaling using this pooled pattern closely emulates GCM simulations. For warming beyond 3.5°C, pattern-scaling performance is notably improved by using patterns diagnosed only from the high-forcing representative concentration pathway 8.5 (RCP8.5) scenario. Assessments of climate change impacts under high-end warming using pattern-scaling projections could be improved by using change patterns diagnosed from pooled scenarios for projections up to 3.5°C above preindustrial levels and patterns diagnosed from only strong forcing simulations for projecting beyond that. Similar findings are obtained for five other GCMs.

scholarly journals Estimating the Continental Response to Global Warming Using Pattern-Scaled Sea Surface Temperatures and Sea Ice

2016 ◽  
Vol 29 (24) ◽  
pp. 9125-9139 ◽  
Author(s):  
Adeline Bichet ◽  
Paul J. Kushner ◽  
Lawrence Mudryk
Keyword(s):  
Global Warming ◽  
Sea Ice ◽  
General Circulation ◽  
Circulation Model ◽  
Tropical Indian Ocean ◽  
Sea Surface ◽  
Climate Projections ◽  
Western Boundary ◽  
Sea Ice Concentration ◽  
Continental Climate

Abstract Better constraining the continental climate response to anthropogenic forcing is essential to improve climate projections. In this study, pattern scaling is used to extract, from observations, the patterned response of sea surface temperature (SST) and sea ice concentration (SICE) to anthropogenically dominated long-term global warming. The SST response pattern includes a warming of the tropical Indian Ocean, the high northern latitudes, and the western boundary currents. The SICE pattern shows seasonal variations of the main locations of sea ice loss. These SST–SICE response patterns are used to drive an ensemble of an atmospheric general circulation model, the National Center for Atmospheric Research (NCAR) Community Atmosphere Model, version 5 (CAM5), over the period 1980–2010 along with a standard AMIP ensemble using observed SST—SICE. The simulations enable attribution of a variety of observed trends of continental climate to global warming. On the one hand, the warming trends observed in all seasons across the entire Northern Hemisphere extratropics result from global warming, as does the snow loss observed over the northern midlatitudes and northwestern Eurasia. On the other hand, 1980–2010 precipitation trends observed in winter over North America and in summer over Africa result from the recent decreasing phase of the Pacific decadal oscillation and the recent increasing phase of the Atlantic multidecadal oscillation, respectively, which are not part of the global warming signal. The method holds promise for near-term decadal climate prediction but as currently framed cannot distinguish regional signals associated with oceanic internal variability from aerosol forcing and other sources of short-term forcing.

Reevaluation of Design Waves Off the Western Indian Coast Considering Climate Change

2016 ◽  
Vol 50 (1) ◽  
pp. 88-98 ◽  
Author(s):  
Pentapati Satyavathi ◽  
Makarand C. Deo ◽  
Jyoti Kerkar ◽  
Ponnumony Vethamony
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
General Circulation ◽  
Generalized Pareto Distribution ◽  
Circulation Model ◽  
Offshore Structures ◽  
Future Climate Change ◽  
Extreme Value Analysis ◽  
Value Analysis ◽  
Wave Data

AbstractKnowledge of design waves with long return periods forms an essential input to many engineering applications, including structural design and analysis. Such extreme or long-term waves are conventionally evaluated using observed or hindcast historical wave data. Globally, waves are expected to undergo future changes in magnitude and behavior as a result of climate change induced by global warming. Considering future climate change, this study attempts to reevaluate significant wave height (Hs) as well as average spectral wave period (Tz) with a return period of 100 years for a series of locations along the western Indian coastline. Historical waves are simulated using a numerical wave model forced by wind data extracted from the archives of the National Center for Environmental Prediction and the National Center for Atmospheric Research, while future wave data are generated by a state-of-the-art Canadian general circulation model. A statistical extreme value analysis of past and projected wave data carried out with the help of the generalized Pareto distribution showed an increase in 100-year Hs and Tz along the Indian coastline, pointing out the necessity to reconsider the safety of offshore structures in the light of global warming.

scholarly journals Regional aspects of global climate change simulations : Validation and assessment of climate response over Indian monsoon region to transient increase of greenhouse gases and sulfate aerosols

MAUSAM ◽  
2021 ◽  
Vol 52 (1) ◽  
pp. 229-244
Author(s):  
K. RUPA KUMAR ◽  
R. G. ASHRIT
Keyword(s):  
Climate Change ◽  
Greenhouse Gases ◽  
General Circulation ◽  
Regional Scale ◽  
Circulation Model ◽  
Ocean General Circulation Model ◽  
Change Scenario ◽  
Climate Projections ◽  
Sulfate Aerosols ◽  
Monsoon Climate

The regional climatic impacts associated with global climatic change and their assessment are very important since agriculture, water resources, ecology etc., are all vulnerable to climatic changes on regional scale. Coupled Atmosphere-Ocean general circulation model (AOGCM) simulations provide a range of scenarios, which can be used, for the assessment of impacts and development of adaptive or mitigative strategies. Validation of the models against the observations and establishing the sensitivity to climate change forcing are essential before the model projections are used for assessment of possible impacts. Moreover model simulated climate projections are often of coarse resolution while the models used for impact assessment, (e.g. crop simulation models, or river runoff models etc.) operate on a higher spatial resolution. This spatial mismatch can be overcome by adopting an appropriate strategy of downscaling the GCM output.   This study examines two AOGCM (ECHAM4/OPYC3 and HadCM2) climate change simulations for their performance in the simulation of monsoon climate over India and the sensitivity of the simulated monsoon climate to transient changes in the atmospheric concentrations of greenhouse gases and sulfate aerosols. The results show that the two models simulate the gross features of climate over India reasonably well. However the inter-model differences in simulation of mean characteristics, sensitivity to forcing and in the simulation of climate change suggest need for caution. Further an empirical downscaling approach in used to assess the possibility of using GCM projections for preparation of regional climate change scenario for India.

scholarly journals Set-up and preliminary results of mid-Pliocene climate simulations with CAM3.1

2011 ◽  
Vol 4 (4) ◽  
pp. 3339-3361 ◽  
Author(s):  
Q. Yan ◽  
Z. Zhang ◽  
H. Wang ◽  
Y. Gao ◽  
W. Zheng
Keyword(s):  
Global Warming ◽  
General Circulation ◽  
Atmospheric General Circulation Model ◽  
Surface Air Temperature ◽  
Circulation Model ◽  
High Latitudes ◽  
Atmospheric General Circulation ◽  
Climate Simulations ◽  
Low Latitudes ◽  
Set Up

Abstract. The mid-Pliocene warm period (~3.3 to 3.0 Ma BP) is a potential analogue for future climate under global warming. In this study, we use an atmospheric general circulation model (AGCM) called CAM3.1 to simulate the mid-Pliocene climate with the PRISM3D boundary conditions. The simulations show that the global annual mean surface air temperature (SAT) increases by 2.0 °C in the mid-Pliocene compared with the pre-industrial temperature. The greatest warming mainly occurs in the high latitudes of both hemispheres, with little change in SAT at low latitudes. The equator-to-pole SAT gradient is reduced in the mid-Pliocene simulation. The annual mean precipitation is enhanced by 3.6% of the pre-industrial value. However, the changes in precipitation are greater in low latitudes than high latitudes.

scholarly journals Calibrating Climate Change Time-Slice Projections with Estimates of Seasonal Forecast Reliability

2016 ◽  
Vol 29 (10) ◽  
pp. 3831-3840 ◽  
Author(s):  
M. Matsueda ◽  
A. Weisheimer ◽  
T. N. Palmer
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Circulation Model ◽  
Seasonal Forecast ◽  
Time Slice ◽  
Climate Change Signal ◽  
Seasonal Forecasts ◽  
Low Resolution ◽  
Climate Change Projections ◽  
Resolution Model

Abstract In earlier work, it was proposed that the reliability of climate change projections, particularly of regional rainfall, could be improved if such projections were calibrated using quantitative measures of reliability obtained by running the same model in seasonal forecast mode. This proposal is tested for fast atmospheric processes (such as clouds and convection) by considering output from versions of the same atmospheric general circulation model run at two different resolutions and forced with prescribed sea surface temperatures and sea ice. Here output from the high-resolution version of the model is treated as a proxy for truth. The reason for using this approach is simply that the twenty-first-century climate change signal is not yet known and, hence, no climate change projections can be verified using observations. Quantitative assessments of reliability of the low-resolution model, run in seasonal hindcast mode, are used to calibrate climate change time-slice projections made with the same low-resolution model. Results show that the calibrated climate change probabilities are closer to the proxy truth than the uncalibrated probabilities. Given that seasonal forecasts are performed operationally already at several centers around the world, in a seamless forecast system they provide a resource that can be used without cost to help calibrate climate change projections and make them more reliable for users.

An Examination of Climate Change on Extreme Heat Events and Climate–Mortality Relationships in Large U.S. Cities

2011 ◽  
Vol 3 (4) ◽  
pp. 281-292 ◽  
Author(s):  
Scott Greene ◽  
Laurence S. Kalkstein ◽  
David M. Mills ◽  
Jason Samenow
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Large Scale ◽  
Circulation Model ◽  
The United States ◽  
Attributable Mortality ◽  
Climate Projections ◽  
Synoptic Classification ◽  
The Impact ◽  
Related Mortality

Abstract This study examines the impact of a changing climate on heat-related mortality in 40 large cities in the United States. A synoptic climatological procedure, the spatial synoptic classification, is used to evaluate present climate–mortality relationships and project how potential climate changes might affect these values. Specifically, the synoptic classification is combined with downscaled future climate projections for the decadal periods of 2020–29, 2045–55, and 2090–99 from a coupled atmospheric–oceanic general circulation model. The results show an increase in excessive heat event (EHE) days and increased heat-attributable mortality across the study cities with the most pronounced increases projected to occur in the Southeast and Northeast. This increase becomes more dramatic toward the end of the twenty-first century as the anticipated impact of climate change intensifies. The health impact associated with different emissions scenarios is also examined. These results suggest that a “business as usual” approach to greenhouse gas emissions mitigation could result in twice as many heat-related deaths by the end of the century than a lower emissions scenario. Finally, a comparison of future estimates of heat-related mortality during EHEs is presented using algorithms developed during two different, although overlapping, time periods, one that includes some recent large-scale significant EHE intervention strategies (1975–2004), and one without (1975–95). The results suggest these public health responses can significantly decrease heat-related mortality.

scholarly journals Set-up and preliminary results of mid-Pliocene climate simulations with CAM3.1

2012 ◽  
Vol 5 (2) ◽  
pp. 289-297 ◽  
Author(s):  
Q. Yan ◽  
Z. S. Zhang ◽  
H. J. Wang ◽  
Y. Q. Gao ◽  
W. P. Zheng
Keyword(s):  
Global Warming ◽  
General Circulation ◽  
Atmospheric General Circulation Model ◽  
Surface Air Temperature ◽  
Circulation Model ◽  
High Latitudes ◽  
Atmospheric General Circulation ◽  
Climate Simulations ◽  
Low Latitudes ◽  
Set Up

Abstract. The mid-Pliocene warm period ~3.264 to 3.025 Ma) is a potential analogue for future climate under global warming. In this study, we use an atmospheric general circulation model (AGCM) called CAM3.1 to simulate the mid-Pliocene climate with the PRISM3D boundary conditions. The simulations show that the global annual mean surface air temperature (SAT) increases by 2.0 °C in the mid-Pliocene compared with the pre-industrial temperature. The greatest warming occurs at high latitudes of both hemispheres, with little change in SAT at low latitudes. The equator-to-pole SAT gradient is reduced in the mid-Pliocene simulation. The annual mean precipitation is enhanced by 3.6% of the pre-industrial value. However, the changes in precipitation are greater at low latitudes than at high latitudes.

scholarly journals Quantifying uncertainty in the impacts of climate change on river discharge in sub-catchments of the River Yangtze and Yellow Basins, China

2010 ◽  
Vol 7 (5) ◽  
pp. 6823-6850 ◽  
Author(s):  
H. Xu ◽  
R. G. Taylor ◽  
Y. Xu
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Air Temperature ◽  
River Discharge ◽  
Climate Change Impacts ◽  
Dry Season ◽  
Climate Projections ◽  
Emission Scenarios ◽  
Global Mean ◽  
Impacts Of Climate Change

Abstract. Quantitative evaluations of the impacts of climate change on water resources are primarily constrained by uncertainty in climate projections from GCMs. In this study we assess uncertainty in the impacts of climate change on river discharge in two catchments of the River Yangtze and Yellow Basins that feature contrasting climate regimes (humid and semi-arid). Specifically we quantify uncertainty associated with GCM structure from a subset of CMIP3 AR4 GCMs (HadCM3, HadGEM1, CCSM3.0, IPSL, ECHAM5, CSIRO, CGCM3.1), SRES emissions scenarios (A1B, A2, B1, B2) and prescribed increases in global mean air temperature (1 °C to 6 °C). Climate projections, applied to semi-distributed hydrological models (SWAT 2005) in both catchments, indicate trends toward warmer and wetter conditions. For prescribed warming scenarios of 1 °C to 6 °C, linear increases in mean annual river discharge, relative to baseline (1961–1990), for the River Xiangxi and River Huangfuchuan are +9% and 11% per +1 °C, respectively. Intra-annual changes include increases in flood (Q05) discharges for both rivers as well as a shift in the timing of flood discharges from summer to autumn and a rise (24 to 93%) in dry season (Q95) discharge for the River Xiangxi. Differences in projections of mean annual river discharge between SRES emission scenarios using HadCM3 are comparatively minor for the River Xiangxi (13% to 17% rise from baseline) but substantial (73% to 121%) for the River Huangfuchuan. With one minor exception of a slight (−2%) decrease in river discharge projected using HadGEM1 for the River Xiangxi, mean annual river discharge is projected to increase in both catchments under both the SRES A1B emission scenario and 2° rise in global mean air temperature using all AR4 GCMs on the CMIP3 subset. For the River Xiangxi, there is great uncertainty associated with GCM structure in the magnitude of the rise in flood (Q05) discharges (−1% to 41% under SRES A1B and −3% to 41% under 2° global warming) and dry season (Q95) discharges (2% to 55% under SRES A1B and 2% to 39% under 2° global warming). For the River Huangfuchuan, all GCMs project a rise in the Q05 flow but there is substantial uncertainty in the magnitude of this rise (7% to 70% under SRES A1B and 2% to 57% under 2° global warming). Greatest differences in the projected hydrologic changes are associated with GCMs in both catchments than emission scenarios and climate sensitivity. Critically, estimated uncertainty in projections of mean annual flows is less than that calculated for extreme (Q05, Q95) flows. This research suggest that the common approach of reporting of climate change impacts on river in terms of mean annual flows may mask the magnitude of uncertainty in flows of most importance to water managers.

scholarly journals Comparison of uncertainty in multi-parameter and multi-model ensemble hydrologic analysis of climate change

2016 ◽  
Author(s):  
Younggu Her ◽  
Seung-Hwan Yoo ◽  
Chounghyun Seong ◽  
Jaehak Jeong ◽  
Jaepil Cho ◽  
...  
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Hydrological Modeling ◽  
Circulation Model ◽  
Climate Change Impacts ◽  
Ohio River ◽  
Hydrologic Simulation ◽  
Direct Runoff ◽  
Hydrologic Analysis ◽  
Selection Of

Abstract. Quantification of uncertainty in ensemble based predictions of climate change and the corresponding hydrologic impact is necessary for the development of robust climate change adaptation plans. Although the equifinality of hydrological modeling has been discussed for a long time, its impact on the hydrologic analysis of climate change has not been studied enough to provide clear ideas that represent the relative contributions of uncertainty contained in both multi-GCM (general circulation model) and multi-parameter ensembles toward the projections of hydrologic components. This study demonstrated that the uncertainty in multi-GCM (or multi-model) ensembles could be an order of magnitude larger than that of multi-parameter ensembles for predictions of direct runoff, suggesting that the selection of appropriate GCMs should be much more emphasized than the selection of a parameter set among behavioral ones when projecting direct runoff. When simulating soil moisture and groundwater, on the other hand, equifinality in hydrologic modeling was more influential than uncertainty in the multi-GCM ensemble. Also, uncertainty in a hydrologic simulation of climate change impact was much more closely associated with uncertainty in ensemble projections of precipitation than that in projected temperature, indicating a need to pay closer attention to the precipitation data for improvement of the reliability of hydrologic predictions. From among 35 GCMs incorporated, this study identified GCMs that contributed the most and least to uncertainty in an assessment of climate change impacts on the hydrology of 61 Ohio River watersheds, thereby exhibiting a framework to quantify contributions of individual GCMs to the overall uncertainty in climate change modeling.

Evaluation of climate change impacts on streamflow to a multiple reservoir system using a data-based mechanistic model

2014 ◽  
Vol 5 (4) ◽  
pp. 610-624 ◽  
Author(s):  
Sara Nazif ◽  
Mohammad Karamouz
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Mechanistic Model ◽  
Moving Average ◽  
Daily Rainfall ◽  
Circulation Model ◽  
Climate Change Impacts ◽  
Climate Change Scenarios ◽  
Daily Streamflow ◽  
Global Mean Temperature

Recent investigations have demonstrated scientists' consensus on the increase in global mean temperature and climate variability. These changes alter the hydro-climatic condition of regions. Investigation of surface water changes is an important issue in water resources planning as well as for the operation of reservoirs. In this study a data-based mechanistic (DBM) model has been used for daily streamflow simulation. This model is a data-driven statistical base simulation model that can take advantage of additional climate variables with time variable configurations. The model has been developed for simulation of streamflow to three reservoirs, located in central Iran, using the daily rainfall, temperature and streamflow data. Comparison of the DBM results with the autoregressive integrated moving average model, as an alternative model, shows its higher performance. To include climate change impacts in study, an artificial neural network-based statistical downscaling model is developed for rainfall and temperature downscaling. The downscaled temperature and rainfall data under climate change scenarios based on HadCM3 general circulation model outputs are used to evaluate the climate change impacts on streamflow for the 2000–2050 time horizon. The results demonstrate the considerable impact of climate change on streamflow variability with significantly different behaviour in the three adjacent basins.

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