scholarly journals Headline Indicators for Global Climate Monitoring

2021 ◽  
Vol 102 (1) ◽  
pp. E20-E37
Author(s):  
Blair Trewin ◽  
Anny Cazenave ◽  
Stephen Howell ◽  
Matthias Huss ◽  
Kirsten Isensee ◽  
...  
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
Ocean Acidification ◽  
Mass Balance ◽  
Global Climate ◽  
Global Ocean ◽  
Sea Ice Extent ◽  
Climate Monitoring ◽  
Global Mean Surface Temperature ◽  
Global Mean

AbstractThe World Meteorological Organization has developed a set of headline indicators for global climate monitoring. These seven indicators are a subset of the existing set of essential climate variables (ECVs) established by the Global Climate Observing System and are intended to provide the most essential parameters representing the state of the climate system. These indicators include global mean surface temperature, global ocean heat content, state of ocean acidification, glacier mass balance, Arctic and Antarctic sea ice extent, global CO2 mole fraction, and global mean sea level. This paper describes how well each of these indicators are currently monitored, including the number and quality of the underlying datasets; the health of those datasets; observation systems used to estimate each indicator; the timeliness of information; and how well recent values can be linked to preindustrial conditions. These aspects vary widely between indicators. While global mean surface temperature is available in close to real time and changes from preindustrial levels can be determined with relatively low uncertainty, this is not the case for many other indicators. Some indicators (e.g., sea ice extent) are largely dependent on satellite data only available in the last 40 years, while some (e.g., ocean acidification) have limited underlying observational bases, and others (e.g., glacial mass balance) with data only available a year or more in arrears.

scholarly journals Faster Arctic Sea Ice Retreat in CMIP5 than in CMIP3 due to Volcanoes

2016 ◽  
Vol 29 (24) ◽  
pp. 9179-9188 ◽  
Author(s):  
Erica Rosenblum ◽  
Ian Eisenman
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Arctic Sea Ice ◽  
Sea Ice Extent ◽  
Arctic Sea ◽  
Volcanic Forcing ◽  
Global Mean Surface Temperature ◽  
Ice Retreat ◽  
Sea Ice Retreat ◽  
Global Mean

Abstract The downward trend in Arctic sea ice extent is one of the most dramatic signals of climate change during recent decades. Comprehensive climate models have struggled to reproduce this trend, typically simulating a slower rate of sea ice retreat than has been observed. However, this bias has been widely noted to have decreased in models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5) compared with the previous generation of models (CMIP3). Here simulations are examined from both CMIP3 and CMIP5. It is found that simulated historical sea ice trends are influenced by volcanic forcing, which was included in all of the CMIP5 models but in only about half of the CMIP3 models. The volcanic forcing causes temporary simulated cooling in the 1980s and 1990s, which contributes to raising the simulated 1979–2013 global-mean surface temperature trends to values substantially larger than observed. It is shown that this warming bias is accompanied by an enhanced rate of Arctic sea ice retreat and hence a simulated sea ice trend that is closer to the observed value, which is consistent with previous findings of an approximately linear relationship between sea ice extent and global-mean surface temperature. Both generations of climate models are found to simulate Arctic sea ice that is substantially less sensitive to global warming than has been observed. The results imply that much of the difference in Arctic sea ice trends between CMIP3 and CMIP5 occurred because of the inclusion of volcanic forcing, rather than improved sea ice physics or model resolution.

scholarly journals Simulations of Southern Hemisphere warming and Antarctic sea-ice changes using global climate models

1999 ◽  
Vol 29 ◽  
pp. 61-65 ◽  
Author(s):  
Xingren Wu ◽  
W. F. Budd ◽  
T. H. Jacka
Keyword(s):  
Sea Ice ◽  
Greenhouse Gases ◽  
Surface Temperature ◽  
Global Climate ◽  
Coupled Model ◽  
Sea Surface ◽  
Sea Ice Extent ◽  
Antarctic Sea Ice ◽  
The Antarctic ◽  
Ice Model

AbstractA combination of modelling techniques is used in conjunction with the limited available observational data to examine Antarctic sea-ice changes with global warming over the past century. Firstly a coupled global climate model is forced by prescribing the effect of increasing greenhouse gases from last century to the present. Secondly the GISST (U.K. Meteorological Office global sea-ice and sea surface temperature) observational dataset is used to force an atmosphere-sea-ice model to compute changes in the Antarctic sea ice from last century to the present. Thirdly the global sea-surface-temperature (SST) anomalies derived from the coupled model are used to force the atmosphere-sea-ice model over the same period. The change in the Southern Hemisphere annual mean surface temperature simulated by the coupled model with greenhouse-gas forcing is about 0.6°C, which is similar to the observed change. Over the Antarctic (poleward of 60° S) the corresponding simulated change is about 0.7°C, which also appears compatible with observations. The reduction in summer sea-ice extent simulated by the CSIRO (Commonwealth Scientific and Industrial Research Organisation) coupled model is 0.44° lat. which is, in general, less than the observed change. For the two SST forcing cases the changes are, in general, larger than indicated by the observations. It is concluded that future changes of reduced sea-ice extent from increasing greenhouse gases as simulated by the CSIRO coupled model are not expected to be overestimates.

Simulation and Projection of Global Mean Surface Temperature Using the Empirical Model of Global Climate and Comparison to CMIP6 GCMs

2021 ◽  
Author(s):  
Laura McBride ◽  
Austin Hope ◽  
Timothy Canty ◽  
Walter Tribett ◽  
Brian Bennett ◽  
...  
Keyword(s):  
Global Warming ◽  
Greenhouse Gases ◽  
Surface Temperature ◽  
Empirical Model ◽  
Global Climate ◽  
Volcanic Eruptions ◽  
Climate Record ◽  
Global Mean Surface Temperature ◽  
Global Mean ◽  
Human Component

<p>The Empirical Model of Global Climate (EM-GC) (Canty et al., ACP, 2013, McBride et al., ESDD, 2020) is a multiple linear regression, energy balance model that accounts for the natural influences on global mean surface temperature due to ENSO, the 11-year solar cycle, major volcanic eruptions, as well as the anthropogenic influence of greenhouse gases and aerosols and the efficiency of ocean heat uptake. First, we will analyze the human contribution of global warming from 1975-2014 based on the climate record, also known as the attributable anthropogenic warming rate (AAWR). We will compare the values of AAWR found using the EM-GC with values of AAWR from the CMIP6 multi-model ensemble. Preliminary analysis indicates that over the past three decades, the human component of global warming inferred from the CMIP6 GCMs is larger than the human component of warming from the climate record. Second, we will compare values of equilibrium climate sensitivity inferred from the historical climate record to those determined from CMIP6 GCMs using the Gregory et al., GRL, 2004 method. Third, we will use the future abundances of greenhouse gases and aerosols provided by the Shared Socioeconomic Pathways (SSPs) to project future global mean surface temperature change. We will compare the projections of future temperature anomalies from CMIP6 GCMs to those determined by the EM-GC. We will conclude by assessing the probability of the CMIP6 and EM-GC projections of achieving the Paris Agreement target (1.5°C) and upper limit (2.0°C) for several of the SSP scenarios.</p>

Holocene variability in sea surface temperature and sea ice extent in the northern Bering Sea: A multiple biomarker study

2017 ◽  
Vol 113 ◽  
pp. 1-9 ◽  
Author(s):  
Jiaping Ruan ◽  
Yuanhui Huang ◽  
Xuefa Shi ◽  
Yanguang Liu ◽  
Wenjie Xiao ◽  
...  
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Bering Sea ◽  
Sea Surface ◽  
Sea Ice Extent ◽  
Northern Bering Sea

scholarly journals Halogenated Greenhouse Gases Made Global Warming Primarily

2022 ◽  
Author(s):  
Qing-Bin Lu
Keyword(s):  
Sea Ice ◽  
Greenhouse Gases ◽  
Land Surface ◽  
Southern Oscillation ◽  
Theoretical Calculations ◽  
Global Climate ◽  
Surface Air Temperature ◽  
The Arctic ◽  
Sea Ice Extent ◽  
Snow Cover Extent

Abstract Time-series observations of global lower stratospheric temperature (GLST), global land surface air temperature (LSAT), global mean surface temperature (GMST), sea ice extent (SIE) and snow cover extent (SCE), together with observations reported in Paper I, combined with theoretical calculations of GLSTs and GMSTs, have provided strong evidence that ozone depletion and global climate changes are dominantly caused by human-made halogen-containing ozone-depleting substances (ODSs) and greenhouse gases (GHGs) respectively. Both GLST and SCE have become constant since the mid-1990s and GMST/LSAT has reached a peak since the mid-2000s, while regional continued warmings at the Arctic coasts (particularly Russia and Alaska) in winter and spring and at some areas of Antarctica are observed and can be well explained by a sea-ice-loss warming amplification mechanism. The calculated GMSTs by the parameter-free warming theory of halogenated GHGs show an excellent agreement with the observed GMSTs after the natural El Niño southern oscillation (ENSO) and volcanic effects are removed. These results provide a convincing mechanism of global climate change and will make profound changes in our understanding of atmospheric processes. This study also emphasizes the critical importance of continued international efforts in phasing out all anthropogenic halogenated ODSs and GHGs.

scholarly journals Experimental and diagnostic protocol for the physical component of the CMIP6 Ocean Model Intercomparison Project (OMIP)

2016 ◽  
Author(s):  
Stephen M. Griffies ◽  
Gokhan Danabasoglu ◽  
Paul J. Durack ◽  
Alistair J. Adcroft ◽  
V. Balaji ◽  
...  
Keyword(s):  
Sea Ice ◽  
Global Climate ◽  
Coupled Model ◽  
Companion Paper ◽  
Ocean Model ◽  
Global Ocean ◽  
Model Intercomparison ◽  
Experimental Protocol ◽  
Diagnostic Protocol ◽  
Intercomparison Project

Abstract. The Ocean Model Intercomparison Project (OMIP) aims to provide a framework for evaluating, understanding, and improving the ocean and sea-ice components of global climate and earth system models contributing to the Coupled Model Intercomparison Project Phase 6 (CMIP6). OMIP addresses these aims in two complementary manners: (A) by providing an experimental protocol for global ocean/sea-ice models run with a prescribed atmospheric forcing, (B) by providing a protocol for ocean diagnostics to be saved as part of CMIP6. We focus here on the physical component of OMIP, with a companion paper (Orr et al., 2016) offering details for the inert chemistry and interactive biogeochemistry. The physical portion of the OMIP experimental protocol follows that of the interannual Coordinated Ocean-ice Reference Experiments (CORE-II). Since 2009, CORE-I (Normal Year Forcing) and CORE-II have become the standard method to evaluate global ocean/sea-ice simulations and to examine mechanisms for forced ocean climate variability. The OMIP diagnostic protocol is relevant for any ocean model component of CMIP6, including the DECK (Diagnostic, Evaluation and Characterization of Klima experiments), historical simulations, FAFMIP (Flux Anomaly Forced MIP), C4MIP (Coupled Carbon Cycle Climate MIP), DAMIP (Detection and Attribution MIP), DCPP (Decadal Climate Prediction Project), ScenarioMIP (Scenario MIP), as well as the ocean-sea ice OMIP simulations. The bulk of this paper offers scientific rationale for saving these diagnostics.

scholarly journals Towards Reliable Probabilistic Time-Series Projections of Global Mean Surface Temperature

2021 ◽  
Author(s):  
Philip G. Sansom ◽  
Donald Cummins ◽  
Stefan Siegert ◽  
David B Stephenson
Keyword(s):  
Time Series ◽  
Global Warming ◽  
Surface Temperature ◽  
Climate Model ◽  
Future Projections ◽  
Perfect Model ◽  
Global Mean Surface Temperature ◽  
Time Series Approach ◽  
Energy Balance Models ◽  
Global Mean

Abstract Quantifying the risk of global warming exceeding critical targets such as 2.0 ◦ C requires reliable projections of uncertainty as well as best estimates of Global Mean Surface Temperature (GMST). However, uncertainty bands on GMST projections are often calculated heuristically and have several potential shortcomings. In particular, the uncertainty bands shown in IPCC plume projections of GMST are based on the distribution of GMST anomalies from climate model runs and so are strongly determined by model characteristics with little influence from observations of the real-world. Physically motivated time-series approaches are proposed based on fitting energy balance models (EBMs) to climate model outputs and observations in order to constrain future projections. It is shown that EBMs fitted to one forcing scenario will not produce reliable projections when different forcing scenarios are applied. The errors in the EBM projections can be interpreted as arising due to a discrepancy in the effective forcing felt by the model. A simple time-series approach to correcting the projections is proposed based on learning the evolution of the forcing discrepancy so that it can be projected into the future. This approach gives reliable projections of GMST when tested in a perfect model setting. When applied to observations this leads to projected warming of 2.2 ◦ C (1.7 ◦ C to 2.9 ◦ C) in 2100 compared to pre-industrial conditions, 0.4 ◦ C lower than a comparable IPCC anomaly estimate. The probability of staying below the critical 2.0 ◦ C warming target in 2100 more than doubles to 0.28 compared to only 0.11 from a comparably IPCC estimate.

scholarly journals Modeled Arctic sea ice evolution through 2300 in CMIP5 extended RCPs

2014 ◽  
Vol 8 (1) ◽  
pp. 1383-1406 ◽  
Author(s):  
P. J. Hezel ◽  
T. Fichefet ◽  
F. Massonnet
Keyword(s):  
Sea Ice ◽  
Radiative Forcing ◽  
Climate Models ◽  
Global Climate ◽  
Arctic Sea Ice ◽  
Global Climate Models ◽  
The Arctic ◽  
Sea Ice Extent ◽  
Arctic Sea ◽  
Arctic Sea Ice Extent

Abstract. Almost all global climate models and Earth system models that participated in the Coupled Model Intercomparison Project 5 (CMIP5) show strong declines in Arctic sea ice extent and volume under the highest forcing scenario of the Radiative Concentration Pathways (RCPs) through 2100, including a transition from perennial to seasonal ice cover. Extended RCP simulations through 2300 were completed for a~subset of models, and here we examine the time evolution of Arctic sea ice in these simulations. In RCP2.6, the summer Arctic sea ice extent increases compared to its minimum following the peak radiative forcing in 2044 in all 9 models. RCP4.5 demonstrates continued summer Arctic sea ice decline due to continued warming on longer time scales. These two scenarios imply that summer sea ice extent could begin to recover if and when radiative forcing from greenhouse gas concentrations were to decrease. In RCP8.5 the Arctic Ocean reaches annually ice-free conditions in 7 of 9 models. The ensemble of simulations completed under the extended RCPs provide insight into the global temperature increase at which sea ice disappears in the Arctic and reversibility of declines in seasonal sea ice extent.

scholarly journals Projected Changes in the Seasonal Cycle of Surface Temperature

2012 ◽  
Vol 25 (18) ◽  
pp. 6359-6374 ◽  
Author(s):  
John G. Dwyer ◽  
Michela Biasutti ◽  
Adam H. Sobel
Keyword(s):  
Heat Capacity ◽  
Sea Ice ◽  
Surface Temperature ◽  
Seasonal Cycle ◽  
Phase Delay ◽  
First Century ◽  
Effective Heat Capacity ◽  
Effective Heat ◽  
Twenty First Century ◽  
Global Mean

Abstract When forced with increasing greenhouse gases, global climate models project a delay in the phase and a reduction in the amplitude of the seasonal cycle of surface temperature, expressed as later minimum and maximum annual temperatures and greater warming in winter than in summer. Most of the global mean changes come from the high latitudes, especially over the ocean. All 24 Coupled Model Intercomparison Project phase 3 models agree on these changes and, over the twenty-first century, average a phase delay of 5 days and an amplitude decrease of 5% for the global mean ocean surface temperature. Evidence is provided that the changes are mainly driven by sea ice loss: as sea ice melts during the twenty-first century, the previously unexposed open ocean increases the effective heat capacity of the surface layer, slowing and damping the temperature response. From the tropics to the midlatitudes, changes in phase and amplitude are smaller and less spatially uniform than near the poles but are still prevalent in the models. These regions experience a small phase delay but an amplitude increase of the surface temperature cycle, a combination that is inconsistent with changes to the effective heat capacity of the system. The authors propose that changes in this region are controlled by changes in surface heat fluxes.

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