Evidence of Decadal Climate Prediction Skill Resulting from Changes in Anthropogenic Forcing

2006 ◽  
Vol 19 (20) ◽  
pp. 5305-5318 ◽  
Author(s):  
Terry C. K. Lee ◽  
Francis W. Zwiers ◽  
Xuebin Zhang ◽  
Min Tsao
Keyword(s):  
Twentieth Century ◽  
Radiative Forcing ◽  
Climate Models ◽  
Global Climate ◽  
Spatial Scales ◽  
Global Climate Models ◽  
Anthropogenic Forcing ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Global Mean

Abstract It is argued that simulations of the twentieth century performed with coupled global climate models with specified historical changes in external radiative forcing can be interpreted as climate hindcasts. A simple Bayesian method for postprocessing such simulations is described, which produces probabilistic hindcasts of interdecadal temperature changes on large spatial scales. Hindcasts produced for the last two decades of the twentieth century are shown to be skillful. The suggestion that skillful decadal forecasts can be produced on large regional scales by exploiting the response to anthropogenic forcing provides additional evidence that anthropogenic change in the composition of the atmosphere has influenced the climate. In the absence of large negative volcanic forcing on the climate system (which cannot presently be forecast), it is predicted that the global mean temperature for the decade 2000–09 will lie above the 1970–99 normal with a probability of 0.94. The global mean temperature anomaly for this decade relative to 1970–99 is predicted to be 0.35°C with a 5%–95% confidence range of 0.21°–0.48°C.

Heat stress indicators in CMIP6: Estimating future trends and exceedances of critical physiological thresholds

2020 ◽  
Author(s):  
Clemens Schwingshackl ◽  
Jana Sillmann ◽  
Marit Sandstad ◽  
Kristin Aunan
Keyword(s):  
Heat Stress ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Future Trends ◽  
Stress Indicators ◽  
Threshold Levels ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Global Mean

<p>Global warming is leading to increased heat stress in many regions around the world. An extensive number of heat stress indicators has been developed to measure the associated impacts on human health. Here we calculate eight heat stress indicators for global climate models participating in the Coupled Model Intercomparison Project phase 6 (CMIP6) and compare their future trends and exceedances of critical physiological thresholds with particular focus on highly populated regions. The heat stress indicators are selected to represent a range of different applications, such as extreme heat events, heat-related losses in worker productivity, heat warnings, and heat-related morbidity and mortality. Projections of the analyzed heat stress indicators reveal that they increase significantly in all considered regions as function of global mean temperature. Moreover, heat stress indicators reveal a substantial spread ranging from trends close to the rate of global mean temperature up to an amplification of more than a factor of two. Consistently, exceedances of critical physiological thresholds are strongly increasing globally, including in several densely populated regions, but also show substantial spread across the selected heat stress indicators. Additionally, the indicators with the highest exceedance vary for different threshold levels, suggesting that the large indicator spread is associated both to differences in trend magnitude and threshold levels. The usage of heat stress indicators that are suitable for each specific application is thus crucial for reliably assessing impacts of future heat stress, while inappropriate indicators might lead to substantial biases.</p>

scholarly journals Estimates of Uncertainty in Predictions of Global Mean Surface Temperature

2007 ◽  
Vol 20 (5) ◽  
pp. 843-855 ◽  
Author(s):  
J. A. Kettleborough ◽  
B. B. B. Booth ◽  
P. A. Stott ◽  
M. R. Allen
Keyword(s):  
Twentieth Century ◽  
Energy Balance ◽  
Temperature Change ◽  
Radiative Forcing ◽  
Balance Model ◽  
Future Climate Change ◽  
Model Parameters ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Global Mean

Abstract A method for estimating uncertainty in future climate change is discussed in detail and applied to predictions of global mean temperature change. The method uses optimal fingerprinting to make estimates of uncertainty in model simulations of twentieth-century warming. These estimates are then projected forward in time using a linear, compact relationship between twentieth-century warming and twenty-first-century warming. This relationship is established from a large ensemble of energy balance models. By varying the energy balance model parameters an estimate is made of the error associated with using the linear relationship in forecasts of twentieth-century global mean temperature. Including this error has very little impact on the forecasts. There is a 50% chance that the global mean temperature change between 1995 and 2035 will be greater than 1.5 K for the Special Report on Emissions Scenarios (SRES) A1FI scenario. Under SRES B2 the same threshold is not exceeded until 2055. These results should be relatively robust to model developments for a given radiative forcing history.

scholarly journals Mean precipitation change from a deepening troposphere

2018 ◽  
Vol 115 (45) ◽  
pp. 11465-11470 ◽  
Author(s):  
Nadir Jeevanjee ◽  
David M. Romps
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Precipitation Change ◽  
Global Climate Models ◽  
Simple Theory ◽  
Radiative Cooling ◽  
Free Troposphere ◽  
Global Mean

Global climate models robustly predict that global mean precipitation should increase at roughly 2–3%K−1, but the origin of these values is not well understood. Here we develop a simple theory to help explain these values. This theory combines the well-known radiative constraint on precipitation, which says that condensation heating from precipitation is balanced by the net radiative cooling of the free troposphere, with an invariance of radiative cooling profiles when expressed in temperature coordinates. These two constraints yield a picture in which mean precipitation is controlled primarily by the depth of the troposphere, when measured in temperature coordinates. We develop this theory in idealized simulations of radiative–convective equilibrium and also demonstrate its applicability to global climate models.

scholarly journals Robust increase of Indian monsoon rainfall and its variability under future warming in CMIP-6 models

2020 ◽  
Author(s):  
Anja Katzenberger ◽  
Jacob Schewe ◽  
Julia Pongratz ◽  
Anders Levermann
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Climate Models ◽  
Monsoon Rainfall ◽  
Global Climate ◽  
Coupled Model ◽  
Global Climate Models ◽  
Future Climate Change ◽  
Global Mean Temperature ◽  
Almost All

Abstract. The Indian summer monsoon is an integral part of the global climate system. As its seasonal rainfall plays a crucial role in India's agriculture and shapes many other aspects of life, it affects the livelihood of a fifth of the world's population. It is therefore highly relevant to assess its change under potential future climate change. Global climate models within the Coupled Model Intercomparison Project Phase 5 (CMIP-5) indicated a consistent increase in monsoon rainfall and its variability under global warming. Since the range of the results of CMIP-5 was still large and the confidence in the models was limited due to partly poor representation of observed rainfall, the updates within the latest generation of climate models in CMIP-6 are of interest. Here, we analyse 32 models of the latest CMIP-6 exercise with regard to their annual mean monsoon rainfall and its variability. All of these models show a substantial increase in June-to-September (JJAS) mean rainfall under unabated climate change (SSP5-8.5) and most do also for the other three Shared Socioeconomic Pathways analyzed (SSP1-2.6, SSP2-4.5, SSP3-7.0). Moreover, the simulation ensemble indicates a linear dependence of rainfall on global mean temperature with high agreement between the models and independent of the SSP; the multi-model mean for JJAS projects an increase of 0.33 mm/day and 5.3 % per degree of global warming. This is significantly higher than in the CMIP-5 projections. Most models project that the increase will contribute to the precipitation especially in the Himalaya region and to the northeast of the Bay of Bengal, as well as the west coast of India. Interannual variability is found to be increasing in the higher-warming scenarios by almost all models. The CMIP-6 simulations largely confirm the findings from CMIP-5 models, but show an increased robustness across models with reduced uncertainties and updated magnitudes towards a stronger increase in monsoon rainfall.

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 An Equatorial Ocean Bottleneck in Global Climate Models

2012 ◽  
Vol 25 (1) ◽  
pp. 343-349 ◽  
Author(s):  
Kristopher B. Karnauskas ◽  
Gregory C. Johnson ◽  
Raghu Murtugudde
Keyword(s):  
Ocean Circulation ◽  
Radiative Forcing ◽  
Climate Models ◽  
Global Climate ◽  
Critical Role ◽  
Tropical Pacific ◽  
Global Climate Models ◽  
Momentum Balance ◽  
Equatorial Ocean ◽  
The Tropical Pacific

Abstract The Equatorial Undercurrent (EUC) is a major component of the tropical Pacific Ocean circulation. EUC velocity in most global climate models is sluggish relative to observations. Insufficient ocean resolution slows the EUC in the eastern Pacific where nonlinear terms should dominate the zonal momentum balance. A slow EUC in the east creates a bottleneck for the EUC to the west. However, this bottleneck does not impair other major components of the tropical circulation, including upwelling and poleward transport. In most models, upwelling velocity and poleward transport divergence fall within directly estimated uncertainties. Both of these transports play a critical role in a theory for how the tropical Pacific may change under increased radiative forcing, that is, the ocean dynamical thermostat mechanism. These findings suggest that, in the mean, global climate models may not underrepresent the role of equatorial ocean circulation, nor perhaps bias the balance between competing mechanisms for how the tropical Pacific might change in the future. Implications for model improvement under higher resolution are also discussed.

scholarly journals Evaluating Climate Model Simulations of the Radiative Forcing and Radiative Response at Earth’s Surface

2019 ◽  
Vol 32 (13) ◽  
pp. 4089-4102 ◽  
Author(s):  
Ryan J. Kramer ◽  
Brian J. Soden ◽  
Angeline G. Pendergrass
Keyword(s):  
Radiative Forcing ◽  
Climate Models ◽  
Climate Model ◽  
Hydrological Cycle ◽  
Global Climate ◽  
Global Climate Models ◽  
Lapse Rate ◽  
Radiation Budget ◽  
Model Simulations ◽  
Climate Model Simulations

Abstract We analyze the radiative forcing and radiative response at Earth’s surface, where perturbations in the radiation budget regulate the atmospheric hydrological cycle. By applying a radiative kernel-regression technique to CMIP5 climate model simulations where CO2 is instantaneously quadrupled, we evaluate the intermodel spread in surface instantaneous radiative forcing, radiative adjustments to this forcing, and radiative responses to surface warming. The cloud radiative adjustment to CO2 forcing and the temperature-mediated cloud radiative response exhibit significant intermodel spread. In contrast to its counterpart at the top of the atmosphere, the temperature-mediated cloud radiative response at the surface is found to be positive in some models and negative in others. Also, the compensation between the temperature-mediated lapse rate and water vapor radiative responses found in top-of-atmosphere calculations is not present for surface radiative flux changes. Instantaneous radiative forcing at the surface is rarely reported for model simulations; as a result, intermodel differences have not previously been evaluated in global climate models. We demonstrate that the instantaneous radiative forcing is the largest contributor to intermodel spread in effective radiative forcing at the surface. We also find evidence of differences in radiative parameterizations in current models and argue that this is a significant, but largely overlooked, source of bias in climate change simulations.

Monitoring the Martian Weather with Areostationary SmallSats

2020 ◽  
Author(s):  
Luca Montabone ◽  
Bruce Cantor ◽  
Michel Capderou ◽  
Robin Fergason ◽  
Lorenzo Feruglio ◽  
...  
Keyword(s):  
Radiative Forcing ◽  
Climate Models ◽  
Spatial Scales ◽  
Low Cost ◽  
Dust Storms ◽  
Global Climate Models ◽  
Machine Learning Algorithms ◽  
Dust Particles ◽  
Martian Surface ◽  
Wide Range

<p>The Martian atmosphere (from the surface up to the outer layers) is a very dynamic system, quickly responding to strong radiative forcing coming from the absorption of solar radiation from dust particles lofted during dust storms. So far, such dynamical phenomena at short time scales and large spatial scales have been observed mainly from spacecraft in polar or quasi-polar orbits, which cannot provide continuous and simultaneous observations over fixed, large regions. This limitation can be bypassed using spacecraft in equatorial, circular, planet-synchronous (i.e. areostationary) orbit at an altitude of 17,031.5 km above the Martian surface. Besides their possible use as communication relays for ground-based assets, for space weather monitoring (they orbit outside Mars' bow shock), and for the study of surface properties (e.g. thermal inertia and albedo), the unique scientific advantages of areostationary satellites for weather monitoring are comparable to those provided by geostationary satellites. These platforms greatly increase the temporal resolution and coverage of single events, and are ideally suited for data assimilation in global climate models. Thanks to NASA PSDS3 program, we have elaborated a mission concept to put a low-cost, low-weight, ESPA-class SmallSat in areostationary orbit, which is capable of supporting various tank sizes in order to provide a wide range of ΔV for three different Mars arrival scenarios. ExoTerra Resource LLC adapted its "Electrically Propelled Interplanetary CubeSat" bus as part of the mission design. Despite the optimization of the flight trajectories and the use of machine learning algorithms to prioritize data downlink, the conclusions of the concept study clearly point towards the current challenges represented by propulsion, communication, and possibly radiation tolerance for scientific SmallSat missions to Mars. Such conclusions are generally common among all low-cost interplanetary SmallSat concepts. Furthermore, a single areostationary satellite is enough to provide a full-disk view to monitor regional dust storms and water ice clouds at specific locations, but cannot provide the global coverage required to understand extreme phenomena such as Martian planetary-scale dust events. For this reason, we have recently started to study a more advanced mission concept involving the use of at least three areostationary satellites. This new study is carried out in collaboration with the Jet Propulsion Laboratory within the scope of a wider NASA-funded project (PMCS program) looking at a constellation concept. The challenge is to keep the areostationary satellite configuration within the ESPA class limits, in order to take advantage of possible future rideshare opportunities.</p>

scholarly journals Observing regional-scale pack-ice decay processes with helicopter-borne sensors and moored upward-looking sonars

2011 ◽  
Vol 52 (57) ◽  
pp. 35-42 ◽  
Author(s):  
Simon J. Prinsenberg ◽  
Ingrid K. Peterson
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Spatial Scales ◽  
Regional Scale ◽  
Global Climate Models ◽  
First Year ◽  
Coarse Scale ◽  
Interaction Processes ◽  
Pack Ice ◽  
Ice Floes

AbstractThe variability of Arctic pack-ice parameters (e.g. extent and ice type) has been monitored by satellite-borne sensors since the early 1960s, and information on ice thickness is now becoming available from satellite altimeters. However, the spatial resolution of satellite-derived ice properties is too coarse to validate fine-scale ice variability generated by regional-scale interaction processes that affect the coarse-scale pack-ice albedo, strength and decay. To understand these regional processes, researchers rely on other data-monitoring platforms such as moored upward-looking sonars and helicopter-borne sensors. Backed by observations, two such regional-scale pack-ice decay processes are discussed: the break-up of large pack-ice floes by long-period waves generated by distant storms, and the spring decay of first-year-ice ridges in a diverging pack-ice environment. These two processes, although occurring on regional spatial scales, are important contributors to the evolution of the total pack ice and need to be included in global climate models, especially as the conditions for their occurrence will alter due to climate change.

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