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Abstract
Previous evaluations of model simulations of the cloud and water vapor feedbacks in response to El Niño warming have singled out two common biases in models from phase 3 of the Coupled Model Intercomparison Project (CMIP3): an underestimate of the negative feedback from the shortwave cloud radiative forcing (SWCRF) and an overestimate of the positive feedback from the greenhouse effect of water vapor. Here, the authors check whether these two biases are alleviated in the CMIP5 models. While encouraging improvements are found, particularly in the simulation of the negative SWCRF feedback, the biases in the simulation of these two feedbacks remain prevalent and significant. It is shown that bias in the SWCRF feedback correlates well with biases in the corresponding feedbacks from precipitation, large-scale circulation, and longwave radiative forcing of clouds (LWCRF). By dividing CMIP5 models into two categories—high score models (HSM) and low score models (LSM)—based on their individual skills of simulating the SWCRF feedback, the authors further find that ocean–atmosphere coupling generally lowers the score of the simulated feedbacks of water vapor and clouds but that the LSM is more affected by the coupling than the HSM. They also find that the SWCRF feedback is simulated better in the models that have a more realistic zonal extent of the equatorial cold tongue, suggesting that the continuing existence of an excessive cold tongue is a key factor behind the persistence of the feedback biases in models.
Abstract
Previous evaluations of model simulations of the cloud and water vapor feedbacks in response to El Niño warming have singled out two common biases in models from phase 3 of the Coupled Model Intercomparison Project (CMIP3): an underestimate of the negative feedback from the shortwave cloud radiative forcing (SWCRF) and an overestimate of the positive feedback from the greenhouse effect of water vapor. Here, the authors check whether these two biases are alleviated in the CMIP5 models. While encouraging improvements are found, particularly in the simulation of the negative SWCRF feedback, the biases in the simulation of these two feedbacks remain prevalent and significant. It is shown that bias in the SWCRF feedback correlates well with biases in the corresponding feedbacks from precipitation, large-scale circulation, and longwave radiative forcing of clouds (LWCRF). By dividing CMIP5 models into two categories—high score models (HSM) and low score models (LSM)—based on their individual skills of simulating the SWCRF feedback, the authors further find that ocean–atmosphere coupling generally lowers the score of the simulated feedbacks of water vapor and clouds but that the LSM is more affected by the coupling than the HSM. They also find that the SWCRF feedback is simulated better in the models that have a more realistic zonal extent of the equatorial cold tongue, suggesting that the continuing existence of an excessive cold tongue is a key factor behind the persistence of the feedback biases in models.
Abstract
The accurate representation of precipitation is a recurring issue in climate models. El Niño–Southern Oscillation (ENSO) precipitation teleconnections provide a test bed for comparison of modeled to observed precipitation. The simulation quality for the atmospheric component of models in the Coupled Model Intercomparison Project (CMIP) phase 5 (CMIP5) is assessed here, using the ensemble of runs driven by observed sea surface temperatures (SSTs). Simulated seasonal precipitation teleconnection patterns are compared to observations during 1979–2005 and to the ensemble of CMIP phase 3 (CMIP3). Within regions of strong observed teleconnections (equatorial South America, the western equatorial Pacific, and a southern section of North America), there is little improvement in the CMIP5 ensemble relative to CMIP3 in amplitude and spatial correlation metrics of precipitation. Spatial patterns within each region exhibit substantial departures from observations, with spatial correlation coefficients typically less than 0.5. However, the atmospheric models do considerably better in other measures. First, the amplitude of the precipitation response (root-mean-square deviation over each region) is well estimated by the mean of the amplitudes from the individual models. This is in contrast with the amplitude of the multimodel ensemble mean, which is systematically smaller (by about 30%–40%) in the selected teleconnection regions. Second, high intermodel agreement on teleconnection sign provides a good predictor for high model agreement with observed teleconnections. The ability of the model ensemble to yield amplitude and sign measures that agree with the observed signal for ENSO precipitation teleconnections lends supporting evidence for the use of corresponding measures in global warming projections.
Abstract
The accurate representation of precipitation is a recurring issue in climate models. El Niño–Southern Oscillation (ENSO) precipitation teleconnections provide a test bed for comparison of modeled to observed precipitation. The simulation quality for the atmospheric component of models in the Coupled Model Intercomparison Project (CMIP) phase 5 (CMIP5) is assessed here, using the ensemble of runs driven by observed sea surface temperatures (SSTs). Simulated seasonal precipitation teleconnection patterns are compared to observations during 1979–2005 and to the ensemble of CMIP phase 3 (CMIP3). Within regions of strong observed teleconnections (equatorial South America, the western equatorial Pacific, and a southern section of North America), there is little improvement in the CMIP5 ensemble relative to CMIP3 in amplitude and spatial correlation metrics of precipitation. Spatial patterns within each region exhibit substantial departures from observations, with spatial correlation coefficients typically less than 0.5. However, the atmospheric models do considerably better in other measures. First, the amplitude of the precipitation response (root-mean-square deviation over each region) is well estimated by the mean of the amplitudes from the individual models. This is in contrast with the amplitude of the multimodel ensemble mean, which is systematically smaller (by about 30%–40%) in the selected teleconnection regions. Second, high intermodel agreement on teleconnection sign provides a good predictor for high model agreement with observed teleconnections. The ability of the model ensemble to yield amplitude and sign measures that agree with the observed signal for ENSO precipitation teleconnections lends supporting evidence for the use of corresponding measures in global warming projections.
Abstract
The ability of phase 5 of the Coupled Model Intercomparison Project (CMIP5) climate models to simulate the twentieth-century “warming hole” over North America is explored, along with the warming hole’s relationship with natural climate variability. Twenty-first-century warming hole projections are also examined for two future emission scenarios, the 8.5 and 4.5 W m−2 representative concentration pathways (RCP8.5 and RCP4.5). Simulations from 22 CMIP5 climate models were analyzed, including all their ensemble members, for a total of 192 climate realizations. A nonparametric trend detection method was employed, and an alternative perspective emphasizing trend variability. Observations show multidecadal variability in the sign and magnitude of the trend, where the twentieth-century temperature trend over the eastern United States appears to be associated with low-frequency (multidecadal) variability in the North Atlantic temperatures. Most CMIP5 climate models simulate significantly lower “relative power” in the North Atlantic multidecadal oscillations than observed. Models that have relatively higher skill in simulating the North Atlantic multidecadal oscillation also are more likely to reproduce the warming hole. It was also found that the trend variability envelope simulated by multiple CMIP5 climate models brackets the observed warming hole. Based on the multimodel analysis, it is found that in the twenty-first-century climate simulations the presence or absence of the warming hole depends on future emission scenarios; the RCP8.5 scenario indicates a disappearance of the warming hole, whereas the RCP4.5 scenario shows some chance (10%–20%) of the warming hole’s reappearance in the latter half of the twenty-first century, consistent with CO2 stabilization.
Abstract
The ability of phase 5 of the Coupled Model Intercomparison Project (CMIP5) climate models to simulate the twentieth-century “warming hole” over North America is explored, along with the warming hole’s relationship with natural climate variability. Twenty-first-century warming hole projections are also examined for two future emission scenarios, the 8.5 and 4.5 W m−2 representative concentration pathways (RCP8.5 and RCP4.5). Simulations from 22 CMIP5 climate models were analyzed, including all their ensemble members, for a total of 192 climate realizations. A nonparametric trend detection method was employed, and an alternative perspective emphasizing trend variability. Observations show multidecadal variability in the sign and magnitude of the trend, where the twentieth-century temperature trend over the eastern United States appears to be associated with low-frequency (multidecadal) variability in the North Atlantic temperatures. Most CMIP5 climate models simulate significantly lower “relative power” in the North Atlantic multidecadal oscillations than observed. Models that have relatively higher skill in simulating the North Atlantic multidecadal oscillation also are more likely to reproduce the warming hole. It was also found that the trend variability envelope simulated by multiple CMIP5 climate models brackets the observed warming hole. Based on the multimodel analysis, it is found that in the twenty-first-century climate simulations the presence or absence of the warming hole depends on future emission scenarios; the RCP8.5 scenario indicates a disappearance of the warming hole, whereas the RCP4.5 scenario shows some chance (10%–20%) of the warming hole’s reappearance in the latter half of the twenty-first century, consistent with CO2 stabilization.
Abstract
As a key component of tropical atmospheric variability, intraseasonal variability (ISV) over the eastern North Pacific Ocean (ENP) exerts pronounced influences on regional weather and climate. Since general circulation models (GCMs) are essential tools for prediction and projection of future climate, current model deficiencies in representing this important variability leave us greatly disadvantaged in studies and prediction of climate change. In this study, the authors have assessed model fidelity in representing ENP ISV by analyzing 16 GCMs participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5). Among the 16 CMIP5 GCMs examined in this study, only seven GCMs capture the spatial pattern of the leading ENP ISV mode relatively well, although even these GCMs exhibit biases in simulating ISV amplitude. Analyses indicate that model fidelity in representing ENP ISV is closely associated with the ability to simulate a realistic summer mean state. The presence of westerly or weak mean easterly winds over the ENP warm pool region could be conducive to more realistic simulations of the ISV. One hypothesis to explain this relationship is that a realistic mean state could produce the correct sign of surface flux anomalies relative to the ISV convection, which helps to destabilize local intraseasonal disturbances. The projected changes in characteristics of ENP ISV under the representative concentration pathway 8.5 (RCP8.5) projection scenario are also explored based on simulations from three CMIP5 GCMs. Results suggest that, in a future climate, the amplitude of ISV could be enhanced over the southern part of the ENP while reduced over the northern ENP off the coast of Mexico/Central America and the Caribbean.
Abstract
As a key component of tropical atmospheric variability, intraseasonal variability (ISV) over the eastern North Pacific Ocean (ENP) exerts pronounced influences on regional weather and climate. Since general circulation models (GCMs) are essential tools for prediction and projection of future climate, current model deficiencies in representing this important variability leave us greatly disadvantaged in studies and prediction of climate change. In this study, the authors have assessed model fidelity in representing ENP ISV by analyzing 16 GCMs participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5). Among the 16 CMIP5 GCMs examined in this study, only seven GCMs capture the spatial pattern of the leading ENP ISV mode relatively well, although even these GCMs exhibit biases in simulating ISV amplitude. Analyses indicate that model fidelity in representing ENP ISV is closely associated with the ability to simulate a realistic summer mean state. The presence of westerly or weak mean easterly winds over the ENP warm pool region could be conducive to more realistic simulations of the ISV. One hypothesis to explain this relationship is that a realistic mean state could produce the correct sign of surface flux anomalies relative to the ISV convection, which helps to destabilize local intraseasonal disturbances. The projected changes in characteristics of ENP ISV under the representative concentration pathway 8.5 (RCP8.5) projection scenario are also explored based on simulations from three CMIP5 GCMs. Results suggest that, in a future climate, the amplitude of ISV could be enhanced over the southern part of the ENP while reduced over the northern ENP off the coast of Mexico/Central America and the Caribbean.
