scholarly journals Half a degree Additional warming, Projections, Prognosis and Impacts (HAPPI): Background and Experimental Design

2016 ◽  
Author(s):  
Daniel Mitchell ◽  
Krishna AchutaRao ◽  
Myles Allen ◽  
Ingo Bethke ◽  
Piers Forster ◽  
...  
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Greenhouse Gas Emission ◽  
Coupled Model ◽  
Climate Data ◽  
Intergovernmental Panel ◽  
Internal Climate Variability ◽  
Large Ensembles ◽  
Half Degree ◽  
The Impact

Abstract. The Intergovernmental Panel on Climate Change (IPCC) has accepted the invitation from the UNFCCC to provide a special report on the impacts of global warming of 1.5 °C above pre-industrial levels and related global greenhouse gas emission pathways. Many current experiments in, for example, the Coupled Model Inter-comparison Project (CMIP), are not specifically designed for informing this report. Here, we document the design of the Half a degree Additional warming, Projections, Prognosis and Impacts (HAPPI) experiment. HAPPI provides a framework for the generation of climate data describing how the climate, and in particular extreme weather, might differ from the present day in worlds that are 1.5 °C and 2.0 °C warmer than pre-industrial conditions. Output from participating climate models includes variables frequently used by a range of integrated assessment models. The key challenge is to separate the impact of an additional approximately half degree of warming from uncertainty in climate model responses and internal climate variability that dominate CMIP-style experiments. Large ensembles of simulations (> 50 members) of atmosphere-only models for three time slice experiments are proposed, each a decade in length; the first being the most recent observed 10-year period (2006–2015), the second two being estimates of the a similar decade but under 1.5 and 2 °C conditions a century in the future. We use the Representative Concentration Pathways 2.6 (RCP2.6) to provide the model boundary conditions for the 1.5 °C scenario, and a weighted combination of RCP2.6 and RCP4.5 for the 2 °C scenario.

scholarly journals Half a degree additional warming, prognosis and projected impacts (HAPPI): background and experimental design

2017 ◽  
Vol 10 (2) ◽  
pp. 571-583 ◽  
Author(s):  
Daniel Mitchell ◽  
Krishna AchutaRao ◽  
Myles Allen ◽  
Ingo Bethke ◽  
Urs Beyerle ◽  
...  
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Greenhouse Gas Emission ◽  
Coupled Model ◽  
Climate Data ◽  
Intergovernmental Panel ◽  
Internal Climate Variability ◽  
Low Emission ◽  
Half Degree ◽  
The Impact

Abstract. The Intergovernmental Panel on Climate Change (IPCC) has accepted the invitation from the UNFCCC to provide a special report on the impacts of global warming of 1.5 °C above pre-industrial levels and on related global greenhouse-gas emission pathways. Many current experiments in, for example, the Coupled Model Inter-comparison Project (CMIP), are not specifically designed for informing this report. Here, we document the design of the half a degree additional warming, projections, prognosis and impacts (HAPPI) experiment. HAPPI provides a framework for the generation of climate data describing how the climate, and in particular extreme weather, might differ from the present day in worlds that are 1.5 and 2.0 °C warmer than pre-industrial conditions. Output from participating climate models includes variables frequently used by a range of impact models. The key challenge is to separate the impact of an additional approximately half degree of warming from uncertainty in climate model responses and internal climate variability that dominate CMIP-style experiments under low-emission scenarios.Large ensembles of simulations (>  50 members) of atmosphere-only models for three time slices are proposed, each a decade in length: the first being the most recent observed 10-year period (2006–2015), the second two being estimates of a similar decade but under 1.5 and 2 °C conditions a century in the future. We use the representative concentration pathway 2.6 (RCP2.6) to provide the model boundary conditions for the 1.5 °C scenario, and a weighted combination of RCP2.6 and RCP4.5 for the 2 °C scenario.

Influence of Ocean and Atmosphere Components on Simulated Climate Sensitivities

2013 ◽  
Vol 26 (1) ◽  
pp. 231-245 ◽  
Author(s):  
Michael Winton ◽  
Alistair Adcroft ◽  
Stephen M. Griffies ◽  
Robert W. Hallberg ◽  
Larry W. Horowitz ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Climate Model ◽  
Model Simulation ◽  
Coupled Model ◽  
Ocean Model ◽  
Historical Simulation ◽  
Model Version ◽  
Salinity Response ◽  
The Impact

Abstract The influence of alternative ocean and atmosphere subcomponents on climate model simulation of transient sensitivities is examined by comparing three GFDL climate models used for phase 5 of the Coupled Model Intercomparison Project (CMIP5). The base model ESM2M is closely related to GFDL’s CMIP3 climate model version 2.1 (CM2.1), and makes use of a depth coordinate ocean component. The second model, ESM2G, is identical to ESM2M but makes use of an isopycnal coordinate ocean model. The authors compare the impact of this “ocean swap” with an “atmosphere swap” that produces the GFDL Climate Model version 3 (CM3) by replacing the AM2 atmospheric component with AM3 while retaining a depth coordinate ocean model. The atmosphere swap is found to have much larger influence on sensitivities of global surface temperature and Northern Hemisphere sea ice cover. The atmosphere swap also introduces a multidecadal response time scale through its indirect influence on heat uptake. Despite significant differences in their interior ocean mean states, the ESM2M and ESM2G simulations of these metrics of climate change are very similar, except for an enhanced high-latitude salinity response accompanied by temporarily advancing sea ice in ESM2G. In the ESM2G historical simulation this behavior results in the establishment of a strong halocline in the subpolar North Atlantic during the early twentieth century and an associated cooling, which are counter to observations in that region. The Atlantic meridional overturning declines comparably in all three models.

scholarly journals An Investigation of Parameter Sensitivity of Minimum Complexity Earth Simulator

Atmosphere ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 95
Author(s):  
Jiewei Chen ◽  
Huijuan Cui ◽  
Yangyang Xu ◽  
Quansheng Ge
Keyword(s):  
Climate Change ◽  
Sensitivity Analysis ◽  
Climate Models ◽  
Climate Model ◽  
Greenhouse Gas Emission ◽  
Parameter Sensitivity ◽  
Parameter Sensitivity Analysis ◽  
Output Measurement ◽  
Sensitivity Analysis Method ◽  
The Impact

Climate change, induced by human greenhouse gas emission, has already influenced the environment and society. To quantify the impact of human activity on climate change, scientists have developed numerical climate models to simulate the evolution of the climate system, which often contains many parameters. The choice of parameters is of great importance to the reliability of the simulation. Therefore, parameter sensitivity analysis is needed to optimize the parameters for the model so that the physical process of nature can be reasonably simulated. In this study, we analyzed the parameter sensitivity of a simple carbon-cycle energy balance climate model, called the Minimum Complexity Earth Simulator (MiCES), in different periods using a multi-parameter sensitivity analysis method and output measurement method. The results show that the seven parameters related to heat and carbon transferred are most sensitive among all 37 parameters. Then uncertainties of the above key parameters are further analyzed by changing the input emission and temperature, providing reference bounds of parameters with 95% confidence intervals. Furthermore, we found that ocean heat capacity will be more sensitive if the simulation time becomes longer, indicating that ocean influence on climate is stronger in the future.

scholarly journals Atmospheric Tides in the Latest Generation of Climate Models*

2014 ◽  
Vol 71 (6) ◽  
pp. 1905-1913 ◽  
Author(s):  
Curt Covey ◽  
Aiguo Dai ◽  
Richard S. Lindzen ◽  
Daniel R. Marsh
Keyword(s):  
Climate Models ◽  
Wave Reflection ◽  
Climate Model ◽  
Middle Atmosphere ◽  
Coupled Model ◽  
Atmospheric Tides ◽  
Free Atmosphere ◽  
Intergovernmental Panel ◽  
Model Simulations ◽  
Numerical Experimentation

Abstract For atmospheric tides driven by solar heating, the database of climate model output used in the most recent assessment report of the Intergovernmental Panel on Climate Change (IPCC) confirms and extends the authors’ earlier results based on the previous generation of models. Both the present study and the earlier one examine the surface pressure signature of the tides, but the new database removes a shortcoming of the earlier study in which model simulations were not strictly comparable to observations. The present study confirms an approximate consistency among observations and all model simulations, despite variation of model tops from 31 to 144 km. On its face, this result is surprising because the dominant (semidiurnal) component of the tides is forced mostly by ozone heating around 30–70-km altitude. Classical linear tide calculations and occasional numerical experimentation have long suggested that models with low tops achieve some consistency with observations by means of compensating errors, with wave reflection from the model top making up for reduced ozone forcing. Future work with the new database may confirm this hypothesis by additional classical calculations and analyses of the ozone heating profiles and wave reflection in Coupled Model Intercomparison Project (CMIP) models. The new generation of models also extends CMIP's purview to free-atmosphere fields including the middle atmosphere and above.

scholarly journals Global exposure to flooding from the new CMIP6 climate model projections

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yukiko Hirabayashi ◽  
Masahiro Tanoue ◽  
Orie Sasaki ◽  
Xudong Zhou ◽  
Dai Yamazaki
Keyword(s):  
Spatial Patterns ◽  
Flood Risk ◽  
Climate Models ◽  
Climate Model ◽  
Model Development ◽  
Coupled Model ◽  
Model Intercomparison ◽  
Internal Climate Variability ◽  
Intercomparison Project ◽  
New Generation

AbstractEstimates of future flood risk rely on projections from climate models. The relatively few climate models used to analyze future flood risk cannot easily quantify of their associated uncertainties. In this study, we demonstrated that the projected fluvial flood changes estimated by a new generation of climate models, the collectively known as Coupled Model Intercomparison Project Phase 6 (CMIP6), are similar to those estimated by CMIP5. The spatial patterns of the multi-model median signs of change (+ or −) were also very consistent, implying greater confidence in the projections. The model spread changed little over the course of model development, suggesting irreducibility of the model spread due to internal climate variability, and the consistent projections of models from the same institute suggest the potential to reduce uncertainties caused by model differences. Potential global exposure to flooding is projected to be proportional to the degree of warming, and a greater threat is anticipated as populations increase, demonstrating the need for immediate decisions.

scholarly journals The transient sensitivity of sea level rise

Ocean Science ◽  
2021 ◽  
Vol 17 (1) ◽  
pp. 181-186
Author(s):  
Aslak Grinsted ◽  
Jens Hesselbjerg Christensen
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Carbon Dioxide Emissions ◽  
Radiative Forcing ◽  
Climate Models ◽  
Climate Model ◽  
Greenhouse Gas Emission ◽  
Rate Of Change ◽  
Intergovernmental Panel ◽  
Global Mean

Abstract. Recent assessments from the Intergovernmental Panel on Climate Change (IPCC) imply that global mean sea level is unlikely to rise more than about 1.1 m within this century but will increase further beyond 2100. Even within the most intensive future anthropogenic greenhouse gas emission scenarios, higher levels are assessed to be unlikely. However, some studies conclude that considerably greater sea level rise could be realized, and a number of experts assign a substantially higher likelihood of such a future. To understand this discrepancy, it would be useful to have scenario-independent metrics that can be compared between different approaches. The concept of a transient climate sensitivity has proven to be useful to compare the global mean temperature response of climate models to specific radiative forcing scenarios. Here, we introduce a similar metric for sea level response. By analyzing the mean rate of change in sea level (not sea level itself), we identify a nearly linear relationship with global mean surface temperature (and therefore accumulated carbon dioxide emissions) both in model projections and in observations on a century scale. This motivates us to define the “transient sea level sensitivity” as the increase in the sea level rate associated with a given warming in units of meters per century per kelvin. We find that future projections estimated on climate model responses fall below extrapolation based on recent observational records. This comparison suggests that the likely upper level of sea level projections in recent IPCC reports would be too low.

scholarly journals Controls on the Diversity in Climate Model Projections of Early Summer Drying over Southern Africa

2019 ◽  
Vol 32 (12) ◽  
pp. 3707-3725 ◽  
Author(s):  
C. Munday ◽  
R. Washington
Keyword(s):  
Climate Change ◽  
Southern Africa ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Atmospheric Stability ◽  
Coupled Model ◽  
Early Summer ◽  
Intergovernmental Panel ◽  
Surface Temperature Change

Abstract Ninety-five percent of climate models contributing to phase 5 of the Coupled Model Intercomparison Project (CMIP5) project early summer [October–December (OND)] rainfall declines over subtropical southern Africa by the end of the century, under all emissions forcing pathways. The intermodel consensus underlies the Intergovernmental Panel on Climate Change (IPCC) assessment that rainfall declines are “likely” and implies that significant climate change adaptation is needed. However, model consensus is not necessarily a good indicator of confidence, especially given that there is an order of magnitude difference in the scale of rainfall decline among models in OND (from <10 mm season−1 to ~100 mm season−1), and that the CMIP5 ensemble systematically overestimates present-day OND precipitation over subtropical southern Africa (in some models by a factor of 2). In this paper we investigate the uncertainty in the OND drying signal by evaluating the climate mechanisms that underlie the diversity in model rainfall projections. Models projecting the highest-magnitude drying simulate the largest increases in tropospheric stability over subtropical southern Africa associated with anomalous upper-level subsidence, reduced evaporation, and amplified surface temperature change. Intermodel differences in rainfall projections are in turn related to the large-scale adjustment of the tropical atmosphere to emissions forcing: models with the strongest relative warming of the northern tropical sea surface temperatures compared to the tropical mean warming simulate the largest rainfall declines. The models with extreme rainfall declines also tend to simulate large present-day biases in rainfall and in atmospheric stability, leading the authors to suggest that projections of high-magnitude drying require further critical attention.

scholarly journals Impacts of Climate Change on Rainfall Indices Estimation in Some of Subbasins West of Iran

2017 ◽  
Author(s):  
Hadi Nazaripouya
Keyword(s):  
Climate Change ◽  
Heavy Rainfall ◽  
Climate Models ◽  
Greenhouse Gas Emission ◽  
Coupled Model ◽  
Impact Of Climate Change ◽  
Intensity Index ◽  
Hamedan Province ◽  
Relative Change ◽  
The Impact

Future projections from climate models and recent studies shows impact of climate change on rainfall indices estimation. This study assesses the simulations of rainfall indices based on the Coupled Model Intercomparison Project CMIP5 and CMIP3 in the some of subbasin Hamedan Province West of Iran. The analysis of the rainfall indices are: simple rainfall intensity, very heavy rainfall days, maximum one-day rainfall and rainfall frequency has been carried out in this study to evaluating the impact of climate change on rainfall indices events. Relative change in three rainfall indices is investigated by GCMs under various greenhouse gas emission scenarious A1B and B1 and RCP8.5, RCP8.5 scenarios for the future periods 2020–2045 and 2045-2065. The final results show that each of rainfall indices differs in stations under the three GCMs model (GIAOM, MIHR, MPEH5) and emission scenarios A1B and B1, and RCP2.5, RCP8.5 scenarios. Relative change of daily intensity index varies from -9.93% - 25%, very heavy rainfall days 20.71% - 25.9% and yearly rainfall depth -15.71% - 13% can be observed at study area in 50y for future periods (2046–2065). Rainfall indices of sum wet days, nday >1mm and maximum one-day rainfall are projected to decrease under the senariuos B1,A1B and sum wet days, simple daily intensity and heavy Rainfall days>10 projected to decrease under the RCP2.6.

scholarly journals Impact of Climate Change on Rainfall Indices Estimation in Some of Subbasins West of Iran

2017 ◽  
Author(s):  
Hadi Nazaripouya
Keyword(s):  
Climate Change ◽  
Heavy Rainfall ◽  
Climate Models ◽  
Greenhouse Gas Emission ◽  
Coupled Model ◽  
Climate Extremes ◽  
Impact Of Climate Change ◽  
Model Ensembles ◽  
Hamedan Province ◽  
The Impact

Weather and climate extremes affect every facet of society, economies, environments and cultures. Future projections from climate models and recent studies shows impact of climate change on rainfall indices estimation.The purpose of this study is thus to document changes in indices that are calculated in a consistent manner as simulated in the CMIP3 and CMIP5 model ensembles for analyzing impacts of climate change on cachment rainfall indices the some of subbasin Hamedan Province West of Iran. This study assesses the simulations of rainfall indices based on the Coupled Model Intercomparison Project CMIP5 and CMIP3. The analysis of the rainfall indices are : simple rainfall intensity, very heavy rainfall days , maximum one-day rainfall and rainfall frequency has been carried out in this study to evaluating the impact of climate change on rainfall indices events. Relative change in three rainfall indices is investigated by GCMs under various greenhouse gas emission scenarious A1B and B1 and RCP8.5, RCP8.5 scenarios for the future periods 2020–2045 and 2045-2065. Rainfall indices of sum wet days , nday >1mm and maximum one-day rainfall are projected to decrease under the senariuos B1,A1B and sum wet days , simple daily intensity and heavy Rainfall days>10 projected to decrease under the RCP2.6 .

scholarly journals Connecting Climate Model Projections of Global Temperature Change with the Real World

2016 ◽  
Vol 97 (6) ◽  
pp. 963-980 ◽  
Author(s):  
Ed Hawkins ◽  
Rowan Sutton
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Coupled Model ◽  
Global Climate Models ◽  
Global Temperature ◽  
Climate Projections ◽  
Reference Period ◽  
Intergovernmental Panel ◽  
Temperature Levels

Abstract Current state-of-the-art global climate models produce different values for Earth’s mean temperature. When comparing simulations with each other and with observations, it is standard practice to compare temperature anomalies with respect to a reference period. It is not always appreciated that the choice of reference period can affect conclusions, both about the skill of simulations of past climate and about the magnitude of expected future changes in climate. For example, observed global temperatures over the past decade are toward the lower end of the range of the phase 5 of the Coupled Model Intercomparison Project (CMIP5) simulations irrespective of what reference period is used, but exactly where they lie in the model distribution varies with the choice of reference period. Additionally, we demonstrate that projections of when particular temperature levels are reached, for example, 2 K above “preindustrial,” change by up to a decade depending on the choice of reference period. In this article, we discuss some of the key issues that arise when using anomalies relative to a reference period to generate climate projections. We highlight that there is no perfect choice of reference period. When evaluating models against observations, a long reference period should generally be used, but how long depends on the quality of the observations available. The Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) choice to use a 1986–2005 reference period for future global temperature projections was reasonable, but a case-by-case approach is needed for different purposes and when assessing projections of different climate variables. Finally, we recommend that any studies that involve the use of a reference period should explicitly examine the robustness of the conclusions to alternative choices.

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