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- Author or Editor: Nicholas J. Lutsko x
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Abstract
The impact of large-scale orography on wintertime near-surface (850 hPa) temperature variability on daily and synoptic time scales (from days to weeks) in the Northern Hemisphere is investigated. Using a combination of theory, idealized modeling work, and simulations with a comprehensive climate model, it is shown that large-scale orography reduces upstream temperature gradients, in turn reducing upstream temperature variability, and enhances downstream temperature gradients, enhancing downstream temperature variability. Hence, the presence of the Rockies on the western edge of the North American continent increases temperature gradients over North America and, consequently, increases North American temperature variability. By contrast, the presence of the Tibetan Plateau and the Himalayas on the eastern edge of the Eurasian continent damps temperature variability over most of Eurasia. However, Tibet and the Himalayas also interfere with the downstream development of storms in the North Pacific storm track, and thus damp temperature variability over North America, by approximately as much as the Rockies enhance it. Large-scale orography is also shown to impact the skewness of downstream temperature distributions, as temperatures to the north of the enhanced temperature gradients are more positively skewed while temperatures to the south are more negatively skewed. This effect is most clearly seen in the northwest Pacific, off the east coast of Japan.
Abstract
The impact of large-scale orography on wintertime near-surface (850 hPa) temperature variability on daily and synoptic time scales (from days to weeks) in the Northern Hemisphere is investigated. Using a combination of theory, idealized modeling work, and simulations with a comprehensive climate model, it is shown that large-scale orography reduces upstream temperature gradients, in turn reducing upstream temperature variability, and enhances downstream temperature gradients, enhancing downstream temperature variability. Hence, the presence of the Rockies on the western edge of the North American continent increases temperature gradients over North America and, consequently, increases North American temperature variability. By contrast, the presence of the Tibetan Plateau and the Himalayas on the eastern edge of the Eurasian continent damps temperature variability over most of Eurasia. However, Tibet and the Himalayas also interfere with the downstream development of storms in the North Pacific storm track, and thus damp temperature variability over North America, by approximately as much as the Rockies enhance it. Large-scale orography is also shown to impact the skewness of downstream temperature distributions, as temperatures to the north of the enhanced temperature gradients are more positively skewed while temperatures to the south are more negatively skewed. This effect is most clearly seen in the northwest Pacific, off the east coast of Japan.
Abstract
The fluctuation–dissipation theorem (FDT) provides a means of calculating the response of a dynamical system to a small force by constructing a linear operator that depends only on data from the internal variability of the unperturbed system. Here the FDT is used to estimate the response of a two-layer quasigeostrophic model to two zonally symmetric torques, both barotropic, with the same sign of the forcing in the two layers, and baroclinic, with opposite sign forcing in the two layers. The supercriticality of the model is also varied to test how the FDT fares, as this parameter is varied. To perform the FDT calculations the data are decomposed onto empirical orthogonal functions (EOFs) and only those EOFs that are well resolved are retained in the FDT calculations. In the barotropic case good qualitative estimates are obtained for all values of the supercriticality, though the FDT consistently overestimates the response, perhaps because of significant non-Gaussian behavior present in the model. Nevertheless, this adds to the evidence that the annular-mode time scale plays an important role in determining the response of the midlatitudes to small perturbations. The baroclinic case is more challenging for the FDT. However, by constructing different bases with which to calculate the EOFs, it is shown that the issue in this case is that the baroclinic variability is poorly sampled, not that the FDT fails. The strategies developed in order to generate these estimates may be applicable to situations in which the FDT is applied to larger systems.
Abstract
The fluctuation–dissipation theorem (FDT) provides a means of calculating the response of a dynamical system to a small force by constructing a linear operator that depends only on data from the internal variability of the unperturbed system. Here the FDT is used to estimate the response of a two-layer quasigeostrophic model to two zonally symmetric torques, both barotropic, with the same sign of the forcing in the two layers, and baroclinic, with opposite sign forcing in the two layers. The supercriticality of the model is also varied to test how the FDT fares, as this parameter is varied. To perform the FDT calculations the data are decomposed onto empirical orthogonal functions (EOFs) and only those EOFs that are well resolved are retained in the FDT calculations. In the barotropic case good qualitative estimates are obtained for all values of the supercriticality, though the FDT consistently overestimates the response, perhaps because of significant non-Gaussian behavior present in the model. Nevertheless, this adds to the evidence that the annular-mode time scale plays an important role in determining the response of the midlatitudes to small perturbations. The baroclinic case is more challenging for the FDT. However, by constructing different bases with which to calculate the EOFs, it is shown that the issue in this case is that the baroclinic variability is poorly sampled, not that the FDT fails. The strategies developed in order to generate these estimates may be applicable to situations in which the FDT is applied to larger systems.
Abstract
Climate models and observations robustly agree that Earth’s clear-sky longwave feedback has a value of about −2 W m−2 K−1, suggesting that this feedback can be estimated from first principles. In this study, we derive an analytic model for Earth’s clear-sky longwave feedback. Our approach uses a novel spectral decomposition that splits the feedback into four components: a surface Planck feedback and three atmospheric feedbacks from CO2, H2O, and the H2O continuum. We obtain analytic expressions for each of these terms, and the model can also be framed in terms of Simpson’s law and deviations therefrom. We validate the model by comparing it against line-by-line radiative transfer calculations across a wide range of climates. Additionally, the model qualitatively matches the spatial feedback maps of a comprehensive climate model. For present-day Earth, our analysis shows that the clear-sky longwave feedback is dominated by the surface in the global mean and in the dry subtropics; meanwhile, atmospheric feedbacks from CO2 and H2O become important in the inner tropics. Together, these results show that a spectral view of Earth’s clear-sky longwave feedback elucidates not only its global-mean magnitude, but also its spatial pattern and its state dependence across past and future climates.
Significance Statement
The climate feedback determines how much our planet warms due to changes in radiative forcing. For more than 50 years scientists have been predicting this feedback using complex numerical models. Except for cloud effects the numerical models largely agree, lending confidence to global warming predictions, but nobody has yet derived the feedback from simpler considerations. We show that Earth’s clear-sky longwave feedback can be estimated using only pen and paper. Our results confirm that numerical climate models get the right number for the right reasons, and allow us to explain regional and state variations of Earth’s climate feedback. These variations are difficult to understand solely from numerical models but are crucial for past and future climates.
Abstract
Climate models and observations robustly agree that Earth’s clear-sky longwave feedback has a value of about −2 W m−2 K−1, suggesting that this feedback can be estimated from first principles. In this study, we derive an analytic model for Earth’s clear-sky longwave feedback. Our approach uses a novel spectral decomposition that splits the feedback into four components: a surface Planck feedback and three atmospheric feedbacks from CO2, H2O, and the H2O continuum. We obtain analytic expressions for each of these terms, and the model can also be framed in terms of Simpson’s law and deviations therefrom. We validate the model by comparing it against line-by-line radiative transfer calculations across a wide range of climates. Additionally, the model qualitatively matches the spatial feedback maps of a comprehensive climate model. For present-day Earth, our analysis shows that the clear-sky longwave feedback is dominated by the surface in the global mean and in the dry subtropics; meanwhile, atmospheric feedbacks from CO2 and H2O become important in the inner tropics. Together, these results show that a spectral view of Earth’s clear-sky longwave feedback elucidates not only its global-mean magnitude, but also its spatial pattern and its state dependence across past and future climates.
Significance Statement
The climate feedback determines how much our planet warms due to changes in radiative forcing. For more than 50 years scientists have been predicting this feedback using complex numerical models. Except for cloud effects the numerical models largely agree, lending confidence to global warming predictions, but nobody has yet derived the feedback from simpler considerations. We show that Earth’s clear-sky longwave feedback can be estimated using only pen and paper. Our results confirm that numerical climate models get the right number for the right reasons, and allow us to explain regional and state variations of Earth’s climate feedback. These variations are difficult to understand solely from numerical models but are crucial for past and future climates.
Abstract
The influence of the El Niño-Southern Oscillation (ENSO) in the Asian monsoon region can persist through the post-ENSO summer, after the Sea Surface Temperature (SST) anomalies in the tropical Pacific have dissipated. The long persistence of coherent post-ENSO anomalies is caused by a positive feedback due to interbasin ocean-atmospheric coupling, known as the Indo-Western Pacific Ocean Capacitor (IPOC) effect, though the feedback mechanism itself does not necessarily rely on the antecedence of ENSO events, suggesting the potential for substantial internal variability independent of ENSO. To investigate the respective role of ENSO forcing and non-ENSO internal variability, we conduct ensemble “forecast” experiments with a full-physics, globally coupled atmosphere-ocean model initialized from a multi-decadal tropical Pacific pacemaker simulation. The leading mode of internal variability as represented by the forecast-ensemble spread resembles the post-ENSO IPOC, despite the absence of antecedent ENSO forcing by design. The persistent atmospheric and oceanic anomalies in the leading mode highlight the positive feedback mechanism in the internal variability. The large sample size afforded by the ensemble spread allows us to identify robust non-ENSO precursors of summer IPOC variability, including a cool SST patch over the tropical Northwestern Pacific, a warming patch in the tropical Northern Atlantic, and downwelling oceanic Rossby waves in the tropical Indian Ocean south of the equator. The pathways by which the precursors develop into the summer IPOC mode and the implications for improved predictability are discussed.
Abstract
The influence of the El Niño-Southern Oscillation (ENSO) in the Asian monsoon region can persist through the post-ENSO summer, after the Sea Surface Temperature (SST) anomalies in the tropical Pacific have dissipated. The long persistence of coherent post-ENSO anomalies is caused by a positive feedback due to interbasin ocean-atmospheric coupling, known as the Indo-Western Pacific Ocean Capacitor (IPOC) effect, though the feedback mechanism itself does not necessarily rely on the antecedence of ENSO events, suggesting the potential for substantial internal variability independent of ENSO. To investigate the respective role of ENSO forcing and non-ENSO internal variability, we conduct ensemble “forecast” experiments with a full-physics, globally coupled atmosphere-ocean model initialized from a multi-decadal tropical Pacific pacemaker simulation. The leading mode of internal variability as represented by the forecast-ensemble spread resembles the post-ENSO IPOC, despite the absence of antecedent ENSO forcing by design. The persistent atmospheric and oceanic anomalies in the leading mode highlight the positive feedback mechanism in the internal variability. The large sample size afforded by the ensemble spread allows us to identify robust non-ENSO precursors of summer IPOC variability, including a cool SST patch over the tropical Northwestern Pacific, a warming patch in the tropical Northern Atlantic, and downwelling oceanic Rossby waves in the tropical Indian Ocean south of the equator. The pathways by which the precursors develop into the summer IPOC mode and the implications for improved predictability are discussed.
Abstract
The precise mechanisms driving Arctic amplification are still under debate. Previous attribution methods compute the vertically uniform temperature change required to balance the top-of-atmosphere energy imbalance caused by each forcing and feedback, with any departures from vertically uniform warming collected into the lapse-rate feedback. We propose an alternative attribution method using a single-column model that accounts for the forcing dependence of high-latitude lapse-rate changes. We examine this method in an idealized general circulation model (GCM), finding that, even though the column-integrated carbon dioxide (CO2) forcing and water vapor feedback are stronger in the tropics, they contribute to polar-amplified surface warming as they produce bottom-heavy warming in high latitudes. A separation of atmospheric temperature changes into local and remote contributors shows that, in the absence of polar surface forcing (e.g., sea ice retreat), changes in energy transport are primarily responsible for the polar-amplified pattern of warming. The addition of surface forcing substantially increases polar surface warming and reduces the contribution of atmospheric dry static energy transport to the warming. This physically based attribution method can be applied to comprehensive GCMs to provide a clearer view of the mechanisms behind Arctic amplification.
Abstract
The precise mechanisms driving Arctic amplification are still under debate. Previous attribution methods compute the vertically uniform temperature change required to balance the top-of-atmosphere energy imbalance caused by each forcing and feedback, with any departures from vertically uniform warming collected into the lapse-rate feedback. We propose an alternative attribution method using a single-column model that accounts for the forcing dependence of high-latitude lapse-rate changes. We examine this method in an idealized general circulation model (GCM), finding that, even though the column-integrated carbon dioxide (CO2) forcing and water vapor feedback are stronger in the tropics, they contribute to polar-amplified surface warming as they produce bottom-heavy warming in high latitudes. A separation of atmospheric temperature changes into local and remote contributors shows that, in the absence of polar surface forcing (e.g., sea ice retreat), changes in energy transport are primarily responsible for the polar-amplified pattern of warming. The addition of surface forcing substantially increases polar surface warming and reduces the contribution of atmospheric dry static energy transport to the warming. This physically based attribution method can be applied to comprehensive GCMs to provide a clearer view of the mechanisms behind Arctic amplification.
Abstract
Southern Ocean (SO) surface winds are essential for ventilating the upper ocean by bringing heat and CO2 to the ocean interior. The relationships between mixed layer ventilation, the southern annular mode (SAM), and the storm tracks remain unclear because processes can be governed by short-term wind events as well as long-term means. In this study, observed time-varying 5-day probability density functions (PDFs) of ERA5 surface winds and stresses over the SO are used in a singular value decomposition to derive a linearly independent set of empirical basis functions. The first modes of wind (72% of the total wind variance) and stress (74% of the total stress variance) are highly correlated with a standard SAM index (r = 0.82) and reflect the SAM’s role in driving cyclone intensity and, in turn, extreme westerly winds. The joint PDFs of zonal and meridional wind show that southerly and less westerly winds associated with strong mixed layer ventilation are more frequent during short and distinct negative SAM phases. The probability of these short-term events might be related to midlatitude atmospheric circulation. The second mode describes seasonal changes in the wind variance (16% of the total variance) that are uncorrelated with the first mode. The analysis produces similar results when repeated using 5-day PDFs from a suite of scatterometer products. Differences between wind product PDFs resemble the first mode of the PDFs. Together, these results show a strong correlation between surface stress PDFs and the leading modes of atmospheric variability, suggesting that empirical modes can serve as a novel pathway for understanding differences and variability of surface stress PDFs.
Abstract
Southern Ocean (SO) surface winds are essential for ventilating the upper ocean by bringing heat and CO2 to the ocean interior. The relationships between mixed layer ventilation, the southern annular mode (SAM), and the storm tracks remain unclear because processes can be governed by short-term wind events as well as long-term means. In this study, observed time-varying 5-day probability density functions (PDFs) of ERA5 surface winds and stresses over the SO are used in a singular value decomposition to derive a linearly independent set of empirical basis functions. The first modes of wind (72% of the total wind variance) and stress (74% of the total stress variance) are highly correlated with a standard SAM index (r = 0.82) and reflect the SAM’s role in driving cyclone intensity and, in turn, extreme westerly winds. The joint PDFs of zonal and meridional wind show that southerly and less westerly winds associated with strong mixed layer ventilation are more frequent during short and distinct negative SAM phases. The probability of these short-term events might be related to midlatitude atmospheric circulation. The second mode describes seasonal changes in the wind variance (16% of the total variance) that are uncorrelated with the first mode. The analysis produces similar results when repeated using 5-day PDFs from a suite of scatterometer products. Differences between wind product PDFs resemble the first mode of the PDFs. Together, these results show a strong correlation between surface stress PDFs and the leading modes of atmospheric variability, suggesting that empirical modes can serve as a novel pathway for understanding differences and variability of surface stress PDFs.
Abstract
In Earth’s atmosphere eddy momentum fluxes (EMFs) are largest in the upper troposphere, but EMFs in the lower troposphere, although modest in amplitude, have an intriguing structure. To document this structure, the EMFs in the lower tropospheres of a two-layer quasigeostrophic model, a primitive equation model, and the Southern Hemisphere of a reanalysis dataset are investigated. The lower-tropospheric EMFs are very similar in the cores of the jets in both models and the reanalysis data, with EMF divergence (opposing the upper-tropospheric convergence) due to relatively long waves with slow eastward phase speeds and EMF divergence (as in the upper troposphere) due to shorter waves with faster eastward phase speeds.
As the two-layer model is able to capture the EMF divergence by long waves, a qualitative picture of the underlying dynamics is proposed that relies on the negative potential vorticity gradient in the lower layer of the model. Eddies excited by baroclinic instability mix efficiently through a wide region in the lower layer, centered on the latitude of maximum westerlies and encompassing the lower-layer critical latitudes. Near these critical latitudes, the mixing is enhanced, resulting in increased EMF convergence, with compensating EMF divergence in the center of the jet. The EMF convergence at faster phase speeds is due to deep eddies that propagate on the upper-tropospheric potential vorticity gradient.
Abstract
In Earth’s atmosphere eddy momentum fluxes (EMFs) are largest in the upper troposphere, but EMFs in the lower troposphere, although modest in amplitude, have an intriguing structure. To document this structure, the EMFs in the lower tropospheres of a two-layer quasigeostrophic model, a primitive equation model, and the Southern Hemisphere of a reanalysis dataset are investigated. The lower-tropospheric EMFs are very similar in the cores of the jets in both models and the reanalysis data, with EMF divergence (opposing the upper-tropospheric convergence) due to relatively long waves with slow eastward phase speeds and EMF divergence (as in the upper troposphere) due to shorter waves with faster eastward phase speeds.
As the two-layer model is able to capture the EMF divergence by long waves, a qualitative picture of the underlying dynamics is proposed that relies on the negative potential vorticity gradient in the lower layer of the model. Eddies excited by baroclinic instability mix efficiently through a wide region in the lower layer, centered on the latitude of maximum westerlies and encompassing the lower-layer critical latitudes. Near these critical latitudes, the mixing is enhanced, resulting in increased EMF convergence, with compensating EMF divergence in the center of the jet. The EMF convergence at faster phase speeds is due to deep eddies that propagate on the upper-tropospheric potential vorticity gradient.
Abstract
The northeastern United States (NEUS) is a densely populated region with a number of major cities along the climatological storm track. Despite its economic and social importance, as well as the area’s vulnerability to flooding, there is significant uncertainty around future trends in extreme precipitation over the region. Here, we undertake a regional study of the projected changes in extreme precipitation over the NEUS through the end of the twenty-first century using an ensemble of high-resolution, dynamically downscaled simulations from the North American Coordinated Regional Climate Downscaling Experiment (NA-CORDEX) project. We find that extreme precipitation increases throughout the region, with the largest changes in coastal regions and smaller changes inland. These increases are seen throughout the year, although the smallest changes in extreme precipitation are seen in the summer, in contrast to earlier studies. The frequency of heavy precipitation also increases such that there are relatively fewer days with moderate precipitation and relatively more days with either no or strong precipitation. Averaged over the region, extreme precipitation increases by +3%–5% °C−1 of local warming, with the largest fractional increases in southern and inland regions and occurring during the winter and spring seasons. This is lower than the +7% °C−1 rate expected from thermodynamic considerations alone and suggests that dynamical changes damp the increases in extreme precipitation. These changes are qualitatively robust across ensemble members, although there is notable intermodel spread associated with models’ climate sensitivity and with changes in mean precipitation. Together, the NA-CORDEX simulations suggest that this densely populated region may require significant adaptation strategies to cope with the increase in extreme precipitation expected at the end of the next century.
Significance Statement
Observations show that the northeastern United States has already experienced increases in extreme precipitation, and prior modeling studies suggest that this trend is expected to continue through the end of the century. Using high-resolution climate model simulations, we find that coastal regions will experience large increases in extreme precipitation (+6.0–7.5 mm day−1), although there is significant intermodel spread in the trends’ spatial distribution and in their seasonality. Regionally averaged, extreme precipitation will increase at a rate of ∼2% decade−1. Our results also suggest that the frequency of extreme precipitation will increase, with the strongest storms doubling in frequency per degree of warming. These results, taken with earlier studies, provide guidance to aid in resiliency preparation and planning by regional stakeholders.
Abstract
The northeastern United States (NEUS) is a densely populated region with a number of major cities along the climatological storm track. Despite its economic and social importance, as well as the area’s vulnerability to flooding, there is significant uncertainty around future trends in extreme precipitation over the region. Here, we undertake a regional study of the projected changes in extreme precipitation over the NEUS through the end of the twenty-first century using an ensemble of high-resolution, dynamically downscaled simulations from the North American Coordinated Regional Climate Downscaling Experiment (NA-CORDEX) project. We find that extreme precipitation increases throughout the region, with the largest changes in coastal regions and smaller changes inland. These increases are seen throughout the year, although the smallest changes in extreme precipitation are seen in the summer, in contrast to earlier studies. The frequency of heavy precipitation also increases such that there are relatively fewer days with moderate precipitation and relatively more days with either no or strong precipitation. Averaged over the region, extreme precipitation increases by +3%–5% °C−1 of local warming, with the largest fractional increases in southern and inland regions and occurring during the winter and spring seasons. This is lower than the +7% °C−1 rate expected from thermodynamic considerations alone and suggests that dynamical changes damp the increases in extreme precipitation. These changes are qualitatively robust across ensemble members, although there is notable intermodel spread associated with models’ climate sensitivity and with changes in mean precipitation. Together, the NA-CORDEX simulations suggest that this densely populated region may require significant adaptation strategies to cope with the increase in extreme precipitation expected at the end of the next century.
Significance Statement
Observations show that the northeastern United States has already experienced increases in extreme precipitation, and prior modeling studies suggest that this trend is expected to continue through the end of the century. Using high-resolution climate model simulations, we find that coastal regions will experience large increases in extreme precipitation (+6.0–7.5 mm day−1), although there is significant intermodel spread in the trends’ spatial distribution and in their seasonality. Regionally averaged, extreme precipitation will increase at a rate of ∼2% decade−1. Our results also suggest that the frequency of extreme precipitation will increase, with the strongest storms doubling in frequency per degree of warming. These results, taken with earlier studies, provide guidance to aid in resiliency preparation and planning by regional stakeholders.