Sentences with phrase «used climate models forced»

Published in the Journal of Climate, authors Richard Seager and Martin Hoerling cleverly used climate models forced by sea surface temperatures to separate how much of the past century's North American droughts have been caused by ocean temperatures, natural variability, and humans.

In this study we consider the impact of stratospheric ozone depletion on Antarctic sea ice extent using a climate model forced with observed stratospheric ozone depletion from 1979 to 2005.

Not exact matches

The team used the new scheme in five ice sheet models and forced them with climate warming conditions taken from two different climate models.

The new findings of successful multi-year drought / fire predictions are based on a series of computer modeling experiments, using the state - of - the - art earth system model, the most detailed data on current ocean temperature and salinity conditions, and the climate responses to natural and human - linked radiative forcing.

The researchers used a climate model, a so - called coupled ocean - atmosphere model, which they forced with the observed wind data of the last decades.

Indeed the estimate of aerosol forcing used in the calculation of transient climate response (TCR) in the paper does not come directly from climate models, but instead incorporates an adjustment to those models so that the forcing better matches the assessed estimates from the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change climate response (TCR) in the paper does not come directly from climate models, but instead incorporates an adjustment to those models so that the forcing better matches the assessed estimates from the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change climate models, but instead incorporates an adjustment to those models so that the forcing better matches the assessed estimates from the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change Climate Change (IPCC).

Model simulations of 20th century global warming typically use actual observed amounts of atmospheric carbon dioxide, together with other human (for example chloroflorocarbons or CFCs) and natural (solar brightness variations, volcanic eruptions,...) climate - forcing factors.

As we explain in our glossary item, climatologists use the concept of radiative forcing and climate sensitivity because it provides a very robust predictive tool for knowing what model results will be, given a change of forcing.

Pat argues that it is the general tendency of climate models when forced with exponentially increasing CO2 concentrations (as were the models used in Dr. Covey's CMIP project) to produce a nearly linear temperature rise into the future.

This was accomplished using a stochastic climate model based on the concept that ocean temperature variability is a slow dynamical system, a red noise signal, generated by integrating stochastic atmospheric forcing, or white noise71.

The differences between the «natural forcing» model predictions and measured global temperatures were used to determine AGHG forcing functions for their final climate prediction model.

Note that the old GISS model had a climate sensitivity that was a little higher (4.2 ºC for a doubling of CO2) than the best estimate (~ 3ºC) and as stated in previous years, the actual forcings that occurred are not the same as those used in the different scenarios.

Methods: To understand the effects of economic forces from climate policy on terrestrial carbon and land use changes, the researchers used the MiniCAM, an integrated assessment model developed by the PNNL team over the last two decades, to compare different scenarios.

However, in view of the fact that cloud feedbacks are the dominant contribution to uncertainty in climate sensitivity, the fact that the energy balance model used by Schmittner et al can not compute changes in cloud radiative forcing is particularly serious.

The figure below shows the lower stratospheric temperature results from climate models using both all forcings and natural forcings only from 1880 to 2012.

Using Mg / Ca paleothermometry from the planktonic foraminifera Globigerinoides ruber from the past 500 k.y. at Ocean Drilling Program (ODP) Site 871 in the western Pacific warm pool, we estimate the tropical Pacific climate sensitivity parameter (λ) to be 0.94 — 1.06 °C (W m − 2) − 1, higher than that predicted by model simulations of the Last Glacial Maximum or by models of doubled greenhouse gas concentration forcing.

Wigley et al. (1997) pointed out that uncertainties in forcing and response made it impossible to use observed global temperature changes to constrain ECS more tightly than the range explored by climate models at the time (1.5 °C to 4.5 °C), and particularly the upper end of the range, a conclusion confirmed by subsequent studies.

«[B] y making use of 21 CMIP5 coupled climate models, we study the contribution of external forcing to the Pacific Ocean regional sea level variability over 1993 — 2013, and show that according to climate models, externally forced and thereby the anthropogenic sea level fingerprint on regional sea level trends in the tropical Pacific is still too small to be observable by satellite altimetry.»

Another approach uses the response of climate models, most often simple climate models or Earth System Models of Intermediate Complexity (EMICs, Table 8.3) to explore the range of forcings and climate parameters that yield results consistent with observations (Andronova and Schlesinger, 2001; Forest et al., 2002; Harvey and Kaufmann, 2002; Knutti et al., 2002, 2003; Forest et al., models, most often simple climate models or Earth System Models of Intermediate Complexity (EMICs, Table 8.3) to explore the range of forcings and climate parameters that yield results consistent with observations (Andronova and Schlesinger, 2001; Forest et al., 2002; Harvey and Kaufmann, 2002; Knutti et al., 2002, 2003; Forest et al., models or Earth System Models of Intermediate Complexity (EMICs, Table 8.3) to explore the range of forcings and climate parameters that yield results consistent with observations (Andronova and Schlesinger, 2001; Forest et al., 2002; Harvey and Kaufmann, 2002; Knutti et al., 2002, 2003; Forest et al., Models of Intermediate Complexity (EMICs, Table 8.3) to explore the range of forcings and climate parameters that yield results consistent with observations (Andronova and Schlesinger, 2001; Forest et al., 2002; Harvey and Kaufmann, 2002; Knutti et al., 2002, 2003; Forest et al., 2006).

M2009 use a simplified carbon cycle and climate model to make a large ensemble of simulations in which principal uncertainties in the carbon cycle, radiative forcings, and climate response are allowed to vary, thus yielding a probability distribution for global warming as a function of time throughout the 21st century.

«We use a massive ensemble of the Bern2.5 D climate model of intermediate complexity, driven by bottom - up estimates of historic radiative forcing F, and constrained by a set of observations of the surface warming T since 1850 and heat uptake Q since the 1950s... Between 1850 and 2010, the climate system accumulated a total net forcing energy of 140 x 1022 J with a 5 - 95 % uncertainty range of 95 - 197 x 1022 J, corresponding to an average net radiative forcing of roughly 0.54 (0.36 - 0.76) Wm - 2.»

Several reconstructions are available for the last two millennia and have been used to force climate models (Section 6.6.3).

Response: < / b > von Storch et al purport to test statistical methods used to reconstruct past climate patterns from «noisy» proxy data by constructing false proxy records («pseudoproxy» records) based on adding noise to model gridbox temperature series taken from a climate simulation forced with estimated past radiative forcing changes.

Using models to distinguish between the forcing histories is thus likely to require a tighter focus on regional changes, or in climate patterns, more than the just the mean temperature.

That understanding will be advanced by new and more extensive data collection efforts, improvements to methods used to synthesise that data, and more extensive and collaborative use of climate model simulations over this period — both to understand the forcing / response of the climate, but also to serve as testbed for the various reconstruction methodologies.

And finally, the CMIP5 climate models used values of aerosol forcing that are now thought to be far too large.

Mike's work, like that of previous award winners, is diverse, and includes pioneering and highly cited work in time series analysis (an elegant use of Thomson's multitaper spectral analysis approach to detect spatiotemporal oscillations in the climate record and methods for smoothing temporal data), decadal climate variability (the term «Atlantic Multidecadal Oscillation» or «AMO» was coined by Mike in an interview with Science's Richard Kerr about a paper he had published with Tom Delworth of GFDL showing evidence in both climate model simulations and observational data for a 50 - 70 year oscillation in the climate system; significantly Mike also published work with Kerry Emanuel in 2006 showing that the AMO concept has been overstated as regards its role in 20th century tropical Atlantic SST changes, a finding recently reaffirmed by a study published in Nature), in showing how changes in radiative forcing from volcanoes can affect ENSO, in examining the role of solar variations in explaining the pattern of the Medieval Climate Anomaly and Little Ice Age, the relationship between the climate changes of past centuries and phenomena such as Atlantic tropical cyclones and global sea level, and even a bit of work in atmospheric chemistry (an analysis of beryllium - 7 measureclimate record and methods for smoothing temporal data), decadal climate variability (the term «Atlantic Multidecadal Oscillation» or «AMO» was coined by Mike in an interview with Science's Richard Kerr about a paper he had published with Tom Delworth of GFDL showing evidence in both climate model simulations and observational data for a 50 - 70 year oscillation in the climate system; significantly Mike also published work with Kerry Emanuel in 2006 showing that the AMO concept has been overstated as regards its role in 20th century tropical Atlantic SST changes, a finding recently reaffirmed by a study published in Nature), in showing how changes in radiative forcing from volcanoes can affect ENSO, in examining the role of solar variations in explaining the pattern of the Medieval Climate Anomaly and Little Ice Age, the relationship between the climate changes of past centuries and phenomena such as Atlantic tropical cyclones and global sea level, and even a bit of work in atmospheric chemistry (an analysis of beryllium - 7 measureclimate variability (the term «Atlantic Multidecadal Oscillation» or «AMO» was coined by Mike in an interview with Science's Richard Kerr about a paper he had published with Tom Delworth of GFDL showing evidence in both climate model simulations and observational data for a 50 - 70 year oscillation in the climate system; significantly Mike also published work with Kerry Emanuel in 2006 showing that the AMO concept has been overstated as regards its role in 20th century tropical Atlantic SST changes, a finding recently reaffirmed by a study published in Nature), in showing how changes in radiative forcing from volcanoes can affect ENSO, in examining the role of solar variations in explaining the pattern of the Medieval Climate Anomaly and Little Ice Age, the relationship between the climate changes of past centuries and phenomena such as Atlantic tropical cyclones and global sea level, and even a bit of work in atmospheric chemistry (an analysis of beryllium - 7 measureclimate model simulations and observational data for a 50 - 70 year oscillation in the climate system; significantly Mike also published work with Kerry Emanuel in 2006 showing that the AMO concept has been overstated as regards its role in 20th century tropical Atlantic SST changes, a finding recently reaffirmed by a study published in Nature), in showing how changes in radiative forcing from volcanoes can affect ENSO, in examining the role of solar variations in explaining the pattern of the Medieval Climate Anomaly and Little Ice Age, the relationship between the climate changes of past centuries and phenomena such as Atlantic tropical cyclones and global sea level, and even a bit of work in atmospheric chemistry (an analysis of beryllium - 7 measureclimate system; significantly Mike also published work with Kerry Emanuel in 2006 showing that the AMO concept has been overstated as regards its role in 20th century tropical Atlantic SST changes, a finding recently reaffirmed by a study published in Nature), in showing how changes in radiative forcing from volcanoes can affect ENSO, in examining the role of solar variations in explaining the pattern of the Medieval Climate Anomaly and Little Ice Age, the relationship between the climate changes of past centuries and phenomena such as Atlantic tropical cyclones and global sea level, and even a bit of work in atmospheric chemistry (an analysis of beryllium - 7 measureClimate Anomaly and Little Ice Age, the relationship between the climate changes of past centuries and phenomena such as Atlantic tropical cyclones and global sea level, and even a bit of work in atmospheric chemistry (an analysis of beryllium - 7 measureclimate changes of past centuries and phenomena such as Atlantic tropical cyclones and global sea level, and even a bit of work in atmospheric chemistry (an analysis of beryllium - 7 measurements).

Using Mg / Ca paleothermometry from the planktonic foraminifera Globigerinoides ruber from the past 500 k.y. at Ocean Drilling Program (ODP) Site 871 in the western Pacific warm pool, we estimate the tropical Pacific climate sensitivity parameter (λ) to be 0.94 — 1.06 °C (W m − 2) − 1, higher than that predicted by model simulations of the Last Glacial Maximum or by models of doubled greenhouse gas concentration forcing.

Some of them are optimal fingerprint detection studies (estimating the magnitude of fingerprints for different external forcing factors in observations, and determining how likely such patterns could have occurred in observations by chance, and how likely they could be confused with climate response to other influences, using a statistically optimal metric), some of them use simpler methods, such as comparisons between data and climate model simulations with and without greenhouse gas increases / anthropogenic forcing, and some are even based only on observations.

We used it heavily as part of a Global Climate Processes course at UW - Madison for later undergrad and grad students, so it has a good deal of flexibility in what you can test (though the model blows up for extreme forcings like snowball Earth, I used CO2 at about 140 ppm and couldn't get much lower than that).

As a check of this, one could comparing the climate model simulations of temperature change using the historical forcing runs with the temperature change produced by the same models under CO2 - only forcing runs * at times of equivalent total forcing change *.

Result: NS 2) «In reviewing the results, the IPCC report concluded: «No climate model using natural forcings [i.e., natural warming factors] alone has reproduced the observed global warming trend in the second half of the twentieth century.

But questions remained concerning the degree of decadal variability, the length of the record and the balance in the models between aerosol forcing and climate sensitivity (which can't really be disentangled using this measure).

As we explain in our glossary item, climatologists use the concept of radiative forcing and climate sensitivity because it provides a very robust predictive tool for knowing what model results will be, given a change of forcing.

A detailed reanalysis is presented of a «Bayesian» climate parameter study (Forest et al., 2006) that estimates climate sensitivity (ECS) jointly with effective ocean diffusivity and aerosol forcing, using optimal fingerprints to compare multi-decadal observations with simulations by the MIT 2D climate model at varying settings of the three climate parameters.

I'm not sure whether statistical trend models would be sufficient, and in order to examine the «residuals» (the data after the trends have been removed), one really needs to use a fully - flegded climate model with all important forcings and feedback processes accounted for.

While the definition of a forcing may appear a little arbitrary, the reason why radiative forcing is used is because it (conveniently) gives quite good predictions of what happens in models to the global mean temperature once the climate system has fully responded to the change.

In fact, the logarithmic nature of the climate forcing due to CO2 is built into the radiative transfer used in all IPCC climate models, and has been taken into account in climate models at least since the late 1950's.

von Storch et al purport to test statistical methods used to reconstruct past climate patterns from «noisy» proxy data by constructing false proxy records («pseudoproxy» records) based on adding noise to model gridbox temperature series taken from a climate simulation forced with estimated past radiative forcing changes.

It is also robust to the use of different climate models, different methods for estimating the responses to external forcing and variations in the analysis technique.

Using the business - as - usual scenario for GHG radiative forcing (RCP8.5) and their novel estimate of Earth's warm - phase climate sensitivity the authors find that the resulting warming during the 21st century overlaps with the upper range of the Coupled Model Intercomparison Project Phase 5 (CMIP5) climate simulations.

Comparing different general circulation climate models these researchers find it is actually only the (often - used) Hadley Centre model that forces vegetation models to a biome switch:

At least with a model like the MIT one used in Forest 2006 one can (if the descriptions of it are correct) set the key climate sensitivity, effective ocean diffusivity and aerosol forcing levels independently and with some confidence (I'm not the person to ask how much) that the simulated results reflect those settings.

This graph shows the forcings (CO2, and other stuff) used by Hansen in the model runs for each of his three future scenarios, plotted alongside the actual climate forcings that were observed.

Due to the important role of ozone in driving temperature changes in the stratosphere as well as radiative forcing of surface climate, several different groups have provided databases characterizing the time - varying concentrations of this key gas that can be used to force global climate change simulations (particularly for those models that do not calculate ozone from photochemical principles).

Given the huge sums of money involved in funding climate research and the even larger sums being spent on the assumption that it gives us good guidance for practical decisions, it may be time for some very large experimental chambers to be constructed to test the presumptions of the device of using forcings as an tractable way of including changes in atmospheric composition in climate models.

There should be support for things that will better define climate response to forcing, like better quality aerosol data and better cloud data, but much less for duplicative modeling efforts, studies that use wildly uncertain models to make wildly uncertain predictions, and silly chicken - little scare - story studies of utter doom.

The scientific focus is on better understanding of climate variability and climate trends using paleo (past)- climate data, instrumental data, and numerical models and theory to assess the importance of internal and external forcing of past, present and future climate.

If only GHG forcing is used, without aerosols, the surface temperature in the last decade or so is about 0.3 - 0.4 C higher than observations; adding in aerosols has a cooling effect of about 0.3 - 0.4 C (and so cancelling out a portion of the GHG warming), providing a fairly good match between the climate model simulations and the observations.

Since climate models did not treat either CO2 or solar effects in a simple linear way, the models underestimated the total solar effects by a factor of six (using a climate forcing multiplier).