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Abstract
Atmospheric macroturbulence transports energy down the equator-to-pole gradient. This is represented by diffusion in energy balance models (EBMs), and EBMs have proven valuable for understanding and quantifying the pattern of surface temperature change. They typically assume climate-state-independent diffusivity, chosen to well represent the current climate, and find that this is sufficient to emulate warming response in general circulation models (GCMs). Meanwhile, model diagnoses of GCM simulations have shown that the diffusivity changes with climate. There is also ongoing development for diffusivity theories based on atmospheric dynamics. Here, we examine the role that changes in diffusivity play in the large-scale equator-to-pole contrast in surface warming in EBMs, building on previous analytic EBM theories for polar-amplified warming. New analytic theories for two formulations of climate-state-dependent diffusivity capture the results of numerical EBM solutions. For reasonable choices of parameter values, the success of the new analytic theories reveals why the change of diffusivity is limited in response to radiative forcing and does not eliminate polar-amplified warming.
Abstract
Atmospheric macroturbulence transports energy down the equator-to-pole gradient. This is represented by diffusion in energy balance models (EBMs), and EBMs have proven valuable for understanding and quantifying the pattern of surface temperature change. They typically assume climate-state-independent diffusivity, chosen to well represent the current climate, and find that this is sufficient to emulate warming response in general circulation models (GCMs). Meanwhile, model diagnoses of GCM simulations have shown that the diffusivity changes with climate. There is also ongoing development for diffusivity theories based on atmospheric dynamics. Here, we examine the role that changes in diffusivity play in the large-scale equator-to-pole contrast in surface warming in EBMs, building on previous analytic EBM theories for polar-amplified warming. New analytic theories for two formulations of climate-state-dependent diffusivity capture the results of numerical EBM solutions. For reasonable choices of parameter values, the success of the new analytic theories reveals why the change of diffusivity is limited in response to radiative forcing and does not eliminate polar-amplified warming.
Abstract
This study first developed a comprehensive semiautomatic data homogenization procedure to produce gap-infilled and homogenized monthly precipitation data series for 425 long-term/critical stations in Canada, which were then used to assess Canadian historical precipitation trends. Data gaps in the 425 series were infilled by advanced spatial interpolation of a much larger dataset. The homogenization procedure repeatedly used multiple homogeneity tests without and with reference series to identify changepoints/inhomogeneities, the results from which were finalized by manual analysis using metadata and visual inspection of the multiphase regression fits. As a result, 298 out of the 425 data series were found to be inhomogeneous. These series were homogenized using quantile matching adjustments. The homogenized dataset shows better spatial consistency of trends than does the raw dataset. The improved gridding and regional mean trend estimation methods also provide more realistic trend estimates. With these improvements, Canadian historical precipitation trends were found to be dominantly positive and significant, except in central-south Canada where the trends are generally insignificant and small with mixed directions. For annual precipitation, the largest increases are seen in southeastern Canada and along the Pacific coast; however, the largest relative increases (in percent of the 1961–90 mean) are seen in northern Canada. The largest trend difference between northern and southern Canada is seen in winter, in which significant increases in the north were matched with significant decreases in the south.
Significance Statement
This study aims to produce a homogenized long-term monthly precipitation dataset for Canada, which is then used to assess Canadian historical precipitation trends. The work is important because it developed a comprehensive algorithm for homogenization of precipitation data, and the results provide better representation of precipitation climate and more robust estimates of precipitation trends. It also identified the causes for large biases in the published estimates of precipitation trends over Canada.
Abstract
This study first developed a comprehensive semiautomatic data homogenization procedure to produce gap-infilled and homogenized monthly precipitation data series for 425 long-term/critical stations in Canada, which were then used to assess Canadian historical precipitation trends. Data gaps in the 425 series were infilled by advanced spatial interpolation of a much larger dataset. The homogenization procedure repeatedly used multiple homogeneity tests without and with reference series to identify changepoints/inhomogeneities, the results from which were finalized by manual analysis using metadata and visual inspection of the multiphase regression fits. As a result, 298 out of the 425 data series were found to be inhomogeneous. These series were homogenized using quantile matching adjustments. The homogenized dataset shows better spatial consistency of trends than does the raw dataset. The improved gridding and regional mean trend estimation methods also provide more realistic trend estimates. With these improvements, Canadian historical precipitation trends were found to be dominantly positive and significant, except in central-south Canada where the trends are generally insignificant and small with mixed directions. For annual precipitation, the largest increases are seen in southeastern Canada and along the Pacific coast; however, the largest relative increases (in percent of the 1961–90 mean) are seen in northern Canada. The largest trend difference between northern and southern Canada is seen in winter, in which significant increases in the north were matched with significant decreases in the south.
Significance Statement
This study aims to produce a homogenized long-term monthly precipitation dataset for Canada, which is then used to assess Canadian historical precipitation trends. The work is important because it developed a comprehensive algorithm for homogenization of precipitation data, and the results provide better representation of precipitation climate and more robust estimates of precipitation trends. It also identified the causes for large biases in the published estimates of precipitation trends over Canada.
Abstract
Summer rainfall trends in southeastern South America (SE-SA) have received attention in recent decades because of their importance for climate impacts. More than one driving mechanism has been identified for the trends, some of which have opposing effects. It is still not clear how much each mechanism has contributed to the observed trends or how their combined influence will affect future changes. Here, we address the second question and study how the CMIP6 summer SE-SA rainfall response to greenhouse warming can be explained by mechanisms related to large-scale extratropical circulation responses in the Southern Hemisphere to remote drivers (RDs) of regional climate change. We find that the regional uncertainty is well represented by combining the influence of four RDs: tropical upper-tropospheric amplification of surface warming, the delay in the stratospheric polar vortex breakdown date, and two RDs characterizing recognized tropical Pacific SST warming patterns. Applying a storyline framework, we identify the combination of RD responses that lead to the most extreme drying and wetting scenarios. Although most scenarios involve wetting, SE-SA drying can result if high upper-tropospheric tropical warming and early stratospheric polar vortex breakdown conditions are combined with low central and eastern Pacific warming. We also show how the definition of the SE-SA regional box can impact the results since the spatial patterns characterizing the dynamical influences are complex and the rainfall changes can be averaged out if these are not considered when aggregating. This article’s perspective and the associated methodology are applicable to other regions of the globe.
Significance Statement
Summer rainfall in southeastern South America (SE-SA) affects an area where around 200 million people live. The observed trends suggest long-term wetting, and most climate models predict a wetting response to greenhouse warming. However, in this work, we find that there is a physically plausible combination of large-scale circulation changes that can promote drying, which means SE-SA drying is a possibility that cannot be ignored. We also show that the definition of the SE-SA regional box can impact regional rainfall analysis since the spatial patterns characterizing the dynamical influences are complex and the changes can be averaged out if these are not considered when aggregating. This perspective and the associated methodology are applicable to other regions of the globe.
Abstract
Summer rainfall trends in southeastern South America (SE-SA) have received attention in recent decades because of their importance for climate impacts. More than one driving mechanism has been identified for the trends, some of which have opposing effects. It is still not clear how much each mechanism has contributed to the observed trends or how their combined influence will affect future changes. Here, we address the second question and study how the CMIP6 summer SE-SA rainfall response to greenhouse warming can be explained by mechanisms related to large-scale extratropical circulation responses in the Southern Hemisphere to remote drivers (RDs) of regional climate change. We find that the regional uncertainty is well represented by combining the influence of four RDs: tropical upper-tropospheric amplification of surface warming, the delay in the stratospheric polar vortex breakdown date, and two RDs characterizing recognized tropical Pacific SST warming patterns. Applying a storyline framework, we identify the combination of RD responses that lead to the most extreme drying and wetting scenarios. Although most scenarios involve wetting, SE-SA drying can result if high upper-tropospheric tropical warming and early stratospheric polar vortex breakdown conditions are combined with low central and eastern Pacific warming. We also show how the definition of the SE-SA regional box can impact the results since the spatial patterns characterizing the dynamical influences are complex and the rainfall changes can be averaged out if these are not considered when aggregating. This article’s perspective and the associated methodology are applicable to other regions of the globe.
Significance Statement
Summer rainfall in southeastern South America (SE-SA) affects an area where around 200 million people live. The observed trends suggest long-term wetting, and most climate models predict a wetting response to greenhouse warming. However, in this work, we find that there is a physically plausible combination of large-scale circulation changes that can promote drying, which means SE-SA drying is a possibility that cannot be ignored. We also show that the definition of the SE-SA regional box can impact regional rainfall analysis since the spatial patterns characterizing the dynamical influences are complex and the changes can be averaged out if these are not considered when aggregating. This perspective and the associated methodology are applicable to other regions of the globe.
Abstract
The impacts of the Madden–Julian oscillation (MJO) on the subseasonal-to-seasonal (S2S) prediction in the Northern Hemisphere extratropics are examined using the reforecasts from the S2S Project and Subseasonal Experiment Project (SubX). When forecasts are initialized during an active MJO, extratropical prediction skill becomes significantly higher at 3–4-week windows compared to inactive MJO. Such prediction skill improvement is evident in the 500-hPa geopotential height over the Pacific–North America region and the North Atlantic and in surface temperature over North America, especially when the model is initialized during the MJO phases 6–7 and 8–1. However, the extratropical prediction skill is not modulated by the MJO phases 2–3 and 4–5. This phase dependency is likely determined by the arrival time of the MJO at the Maritime Continent (MC) barrier that substantially enhances the MJO amplitude error. This result suggests that only MJO phases whose convection lies east of the MC are a source of wintertime S2S predictability in the extratropics.
Abstract
The impacts of the Madden–Julian oscillation (MJO) on the subseasonal-to-seasonal (S2S) prediction in the Northern Hemisphere extratropics are examined using the reforecasts from the S2S Project and Subseasonal Experiment Project (SubX). When forecasts are initialized during an active MJO, extratropical prediction skill becomes significantly higher at 3–4-week windows compared to inactive MJO. Such prediction skill improvement is evident in the 500-hPa geopotential height over the Pacific–North America region and the North Atlantic and in surface temperature over North America, especially when the model is initialized during the MJO phases 6–7 and 8–1. However, the extratropical prediction skill is not modulated by the MJO phases 2–3 and 4–5. This phase dependency is likely determined by the arrival time of the MJO at the Maritime Continent (MC) barrier that substantially enhances the MJO amplitude error. This result suggests that only MJO phases whose convection lies east of the MC are a source of wintertime S2S predictability in the extratropics.
Abstract
Human heat stress depends jointly on atmospheric temperature and humidity. Wetter soils reduce temperature but also raise humidity, making the collective impact on heat stress unclear. To better understand these interactions, we use ERA5 to examine the coupling between daily average soil moisture and wet-bulb temperature (Tw ) and its seasonal and diurnal cycle at global scale. We identify a global soil moisture–Tw coupling pattern with both widespread negative and positive correlations in contrast to the well-established cooling effect of wet soil on dry-bulb temperature. Regions showing positive correlations closely resemble previously identified land–atmosphere coupling hotspots where soil moisture effectively controls surface energy partition. Soil moisture–Tw coupling varies seasonally closely tied to monsoon development, and the positive coupling is slightly stronger and more widespread during nighttime. Local-scale analysis demonstrates a nonlinear structure of soil moisture–Tw coupling with stronger coupling under relatively dry soils. Hot days with high Tw values show wetter-than-normal soil, anomalous high latent and low sensible heat flux from a cooler surface, and a shallower boundary layer. This supports the hypothesis that wetter soil increases Tw by concentrating surface moist enthalpy flux within a shallower boundary layer and reducing free-troposphere-air entrainment. We identify areas of particular interest for future studies on the physical mechanisms of soil moisture–heat stress coupling. Our findings suggest that increasing soil moisture might amplify heat stress over large portions of the world including several densely populated areas. These results also raise questions about the effectiveness of evaporative cooling strategies in ameliorating urban heat stress.
Significance Statement
The purpose of this study is to provide a global picture of the relationship between soil moisture anomalies and a heat stress metric that includes the joint effects of temperature and humidity. This is important because a better understanding of this relationship will help improve the prediction of extreme heat stress events and inform strategies for ameliorating heat stress. We find a widespread positive correlation between soil moisture and heat stress, in contrast to studies relying on temperature alone. This raises the possibility that, over much of the world, and in the most populous regions, strategies like irrigation or “greening” that can reduce temperature might be ineffective or even harmful in reducing heat stress with humidity incorporated.
Abstract
Human heat stress depends jointly on atmospheric temperature and humidity. Wetter soils reduce temperature but also raise humidity, making the collective impact on heat stress unclear. To better understand these interactions, we use ERA5 to examine the coupling between daily average soil moisture and wet-bulb temperature (Tw ) and its seasonal and diurnal cycle at global scale. We identify a global soil moisture–Tw coupling pattern with both widespread negative and positive correlations in contrast to the well-established cooling effect of wet soil on dry-bulb temperature. Regions showing positive correlations closely resemble previously identified land–atmosphere coupling hotspots where soil moisture effectively controls surface energy partition. Soil moisture–Tw coupling varies seasonally closely tied to monsoon development, and the positive coupling is slightly stronger and more widespread during nighttime. Local-scale analysis demonstrates a nonlinear structure of soil moisture–Tw coupling with stronger coupling under relatively dry soils. Hot days with high Tw values show wetter-than-normal soil, anomalous high latent and low sensible heat flux from a cooler surface, and a shallower boundary layer. This supports the hypothesis that wetter soil increases Tw by concentrating surface moist enthalpy flux within a shallower boundary layer and reducing free-troposphere-air entrainment. We identify areas of particular interest for future studies on the physical mechanisms of soil moisture–heat stress coupling. Our findings suggest that increasing soil moisture might amplify heat stress over large portions of the world including several densely populated areas. These results also raise questions about the effectiveness of evaporative cooling strategies in ameliorating urban heat stress.
Significance Statement
The purpose of this study is to provide a global picture of the relationship between soil moisture anomalies and a heat stress metric that includes the joint effects of temperature and humidity. This is important because a better understanding of this relationship will help improve the prediction of extreme heat stress events and inform strategies for ameliorating heat stress. We find a widespread positive correlation between soil moisture and heat stress, in contrast to studies relying on temperature alone. This raises the possibility that, over much of the world, and in the most populous regions, strategies like irrigation or “greening” that can reduce temperature might be ineffective or even harmful in reducing heat stress with humidity incorporated.
Abstract
Summer precipitation over the Tibetan Plateau (TP) has experienced obvious changes in recent decades, with significantly increased trends observed over the northern and western regions during 1961–2020. Results indicate that there are two pathways linking them to the reduced Arctic sea ice from late spring (April and May) to early summer (June and July). First, decreased sea ice in late spring favors wet and dry soil over the eastern Caspian Sea and northeastern TP by stimulating anomalous wavelike patterns and modulating snow melting. Furthermore, the soil moisture anomalies during late spring could maintain to July because of memory effects, strengthen the midlatitude Silk Road pattern, and contribute to the formation of a dipole mode around TP, characterized by a west cyclone and an east anticyclone. Second, through exciting an anomalous Rossby wave directly spreading from the Arctic to TP, a similar dipole pattern on 500-hPa geopotential height could be associated with the decline of sea ice in early summer. Consequently, enhanced southwesterly winds shown with the west cyclone cause more water vapor input to the western TP, while easterly anomalies along with the east anticyclone inhibit climatological westerly winds and prevent water vapor from outputting. This dipole pattern finally brings more moisture accumulated in the western and northern TP and increases the precipitation. This study links heterogeneous changes in summer precipitation over TP to Arctic sea ice changes and provides insights for further investigation into whether the TP could serve as a bridge connecting the Arctic and tropical climates.
Abstract
Summer precipitation over the Tibetan Plateau (TP) has experienced obvious changes in recent decades, with significantly increased trends observed over the northern and western regions during 1961–2020. Results indicate that there are two pathways linking them to the reduced Arctic sea ice from late spring (April and May) to early summer (June and July). First, decreased sea ice in late spring favors wet and dry soil over the eastern Caspian Sea and northeastern TP by stimulating anomalous wavelike patterns and modulating snow melting. Furthermore, the soil moisture anomalies during late spring could maintain to July because of memory effects, strengthen the midlatitude Silk Road pattern, and contribute to the formation of a dipole mode around TP, characterized by a west cyclone and an east anticyclone. Second, through exciting an anomalous Rossby wave directly spreading from the Arctic to TP, a similar dipole pattern on 500-hPa geopotential height could be associated with the decline of sea ice in early summer. Consequently, enhanced southwesterly winds shown with the west cyclone cause more water vapor input to the western TP, while easterly anomalies along with the east anticyclone inhibit climatological westerly winds and prevent water vapor from outputting. This dipole pattern finally brings more moisture accumulated in the western and northern TP and increases the precipitation. This study links heterogeneous changes in summer precipitation over TP to Arctic sea ice changes and provides insights for further investigation into whether the TP could serve as a bridge connecting the Arctic and tropical climates.
Abstract
The Tibetan Plateau (TP), known as the “Third Pole,” profoundly affects weather and climate at regional and global scales. In this study, we investigate the characteristics of heat waves in China and their association with the TP heat source. The results show that during the summertime from 1980 to 2020, the frequency of heat wave days that hit eastern China and northwest China increased at rates of 0.09 and 0.24 days yr−1, respectively, accompanied by an increase in the atmospheric heat source (AHS) over the TP by over 2 W m−2 yr−1 under the background of global warming. The enhanced TP heat source induces an anomalous upper-tropospheric anticyclone, which caused the western Pacific subtropical high and South Asia high to be stronger and closer to each other, causing descending motions over eastern China and consequently more heat waves. At the same time, the enhanced TP heat source weakened the westerlies, thereby favoring the occurrence and maintenance of the anticyclone centered in northwest China and creating more heat waves due to strong descending motions. Therefore, the association between the TP heat source and heat waves in China provides relevant information for studying the mechanism and future changes of heat waves.
Significance Statement
The Tibetan Plateau significantly affects the surrounding weather and climate. We find that there are some linkages between the Tibetan heat source and heat waves in China. The stronger the Tibetan heat source is, the more heat waves hit China. The enhancement of the Tibetan heat source could induce an anomalous upper-tropospheric anticyclone by affecting the western Pacific subtropical high and South Asia high, consequently causing descending motions over eastern China and the resulting heat waves. The weaker westerly due to the enhanced Tibetan heat source favors the occurrence of the anticyclone centered in northwest China, leading to more heat waves by descending motions. This study reveals a potential contributor to heat waves in China, providing some clues for better prediction in the future.
Abstract
The Tibetan Plateau (TP), known as the “Third Pole,” profoundly affects weather and climate at regional and global scales. In this study, we investigate the characteristics of heat waves in China and their association with the TP heat source. The results show that during the summertime from 1980 to 2020, the frequency of heat wave days that hit eastern China and northwest China increased at rates of 0.09 and 0.24 days yr−1, respectively, accompanied by an increase in the atmospheric heat source (AHS) over the TP by over 2 W m−2 yr−1 under the background of global warming. The enhanced TP heat source induces an anomalous upper-tropospheric anticyclone, which caused the western Pacific subtropical high and South Asia high to be stronger and closer to each other, causing descending motions over eastern China and consequently more heat waves. At the same time, the enhanced TP heat source weakened the westerlies, thereby favoring the occurrence and maintenance of the anticyclone centered in northwest China and creating more heat waves due to strong descending motions. Therefore, the association between the TP heat source and heat waves in China provides relevant information for studying the mechanism and future changes of heat waves.
Significance Statement
The Tibetan Plateau significantly affects the surrounding weather and climate. We find that there are some linkages between the Tibetan heat source and heat waves in China. The stronger the Tibetan heat source is, the more heat waves hit China. The enhancement of the Tibetan heat source could induce an anomalous upper-tropospheric anticyclone by affecting the western Pacific subtropical high and South Asia high, consequently causing descending motions over eastern China and the resulting heat waves. The weaker westerly due to the enhanced Tibetan heat source favors the occurrence of the anticyclone centered in northwest China, leading to more heat waves by descending motions. This study reveals a potential contributor to heat waves in China, providing some clues for better prediction in the future.
Abstract
The Indian Ocean is a frequent site for the initiation of the Madden–Julian oscillation (MJO). The evolution of convection during MJO initiation is intimately linked to the subcloud atmospheric mixed layer (ML). Much of the air entering developing cumulus clouds passes through the cloud base; hence, the properties of the ML are critical in determining the nature of cloud development. The properties and depth of the ML are influenced by horizontal advection, precipitation-driven cold pools, and vertical motion. To address ML behavior during the initiation of the MJO, data from the 2011/12 Dynamics of the MJO Experiment (DYNAMO) are utilized. Observations from the research vessel Revelle are used to document the ML and its modification during the time leading up to the onset phase of the October MJO. The mixed layer depth increased from ∼500 to ∼700 m during the 1–12 October suppressed period, allowing a greater proportion of boundary layer thermals to reach the lifting condensation level and hence promote cloud growth. The ML heat budget defines an equilibrium mixed layer depth that accurately diagnoses the mixed layer depth over the DYNAMO convectively suppressed period, provided that horizontal advection is included. The advection at the Revelle is significantly influenced by low-level convective outflows from the southern ITCZ. The findings also demonstrate a connection between cirrus clouds and their remote impact on ML depth and convective development through a reduction in the ML radiative cooling rate. The emergent behavior of the equilibrium mixed layer has implications for simulating the MJO with models with parameterized cloud and turbulent-scale motions.
Abstract
The Indian Ocean is a frequent site for the initiation of the Madden–Julian oscillation (MJO). The evolution of convection during MJO initiation is intimately linked to the subcloud atmospheric mixed layer (ML). Much of the air entering developing cumulus clouds passes through the cloud base; hence, the properties of the ML are critical in determining the nature of cloud development. The properties and depth of the ML are influenced by horizontal advection, precipitation-driven cold pools, and vertical motion. To address ML behavior during the initiation of the MJO, data from the 2011/12 Dynamics of the MJO Experiment (DYNAMO) are utilized. Observations from the research vessel Revelle are used to document the ML and its modification during the time leading up to the onset phase of the October MJO. The mixed layer depth increased from ∼500 to ∼700 m during the 1–12 October suppressed period, allowing a greater proportion of boundary layer thermals to reach the lifting condensation level and hence promote cloud growth. The ML heat budget defines an equilibrium mixed layer depth that accurately diagnoses the mixed layer depth over the DYNAMO convectively suppressed period, provided that horizontal advection is included. The advection at the Revelle is significantly influenced by low-level convective outflows from the southern ITCZ. The findings also demonstrate a connection between cirrus clouds and their remote impact on ML depth and convective development through a reduction in the ML radiative cooling rate. The emergent behavior of the equilibrium mixed layer has implications for simulating the MJO with models with parameterized cloud and turbulent-scale motions.
Abstract
Human influence has been robustly detected throughout many parts of the climate system. Pattern-based methods have been used extensively to estimate the strength of model-predicted “fingerprints,” both human and natural, in observational data. However, individual studies using different analysis methods and time periods yield inconsistent estimates of the magnitude of the influence of anthropogenic aerosols, depending on whether they examined the troposphere, surface, or ocean. Reducing the uncertainty of the impact of aerosols on the climate system is crucial for understanding past climate change and obtaining more reliable estimates of climate sensitivity. To reconcile divergent estimates of aerosol effects obtained in previous studies, we apply the same regression-based detection and attribution method to three different variables: mid-to-upper-tropospheric temperature, surface temperature, and ocean heat content. We find that quantitative estimates of human influence in observations are consistent across these three independently monitored components of the climate system. Combining the troposphere, surface, and ocean data into a single multivariate fingerprint results in a small (∼10%) reduction of uncertainty of the magnitude of the greenhouse gas fingerprint, but a large (∼40%) reduction for the anthropogenic aerosol fingerprint. This reduction in uncertainty results in a substantially earlier time of detection of the multivariate aerosol fingerprint when compared to aerosol fingerprint detection time in each of the three individual variables. Our results highlight the benefits of analyzing data across the troposphere, surface, and ocean in detection and attribution studies, and motivate future work to further constrain uncertainties in aerosol effects on climate.
Significance Statement
Fingerprints of human influence have been detected separately across the troposphere, surface, and ocean. Previous studies examining the different parts of the climate system are difficult to compare quantitatively, however, because they use different methods and cover differ timespans. Here we find consistent estimates of the human influence on the troposphere, surface, and ocean over recent decades when the same fingerprint method and analysis period is used. When we combine the three variables into a single fingerprint, the uncertainty of the influence of anthropogenic aerosols is substantially reduced and the signal is detectable considerably earlier in the observational record. Our results highlight the benefits of performing analysis across different variables instead of focusing on one variable only.
Abstract
Human influence has been robustly detected throughout many parts of the climate system. Pattern-based methods have been used extensively to estimate the strength of model-predicted “fingerprints,” both human and natural, in observational data. However, individual studies using different analysis methods and time periods yield inconsistent estimates of the magnitude of the influence of anthropogenic aerosols, depending on whether they examined the troposphere, surface, or ocean. Reducing the uncertainty of the impact of aerosols on the climate system is crucial for understanding past climate change and obtaining more reliable estimates of climate sensitivity. To reconcile divergent estimates of aerosol effects obtained in previous studies, we apply the same regression-based detection and attribution method to three different variables: mid-to-upper-tropospheric temperature, surface temperature, and ocean heat content. We find that quantitative estimates of human influence in observations are consistent across these three independently monitored components of the climate system. Combining the troposphere, surface, and ocean data into a single multivariate fingerprint results in a small (∼10%) reduction of uncertainty of the magnitude of the greenhouse gas fingerprint, but a large (∼40%) reduction for the anthropogenic aerosol fingerprint. This reduction in uncertainty results in a substantially earlier time of detection of the multivariate aerosol fingerprint when compared to aerosol fingerprint detection time in each of the three individual variables. Our results highlight the benefits of analyzing data across the troposphere, surface, and ocean in detection and attribution studies, and motivate future work to further constrain uncertainties in aerosol effects on climate.
Significance Statement
Fingerprints of human influence have been detected separately across the troposphere, surface, and ocean. Previous studies examining the different parts of the climate system are difficult to compare quantitatively, however, because they use different methods and cover differ timespans. Here we find consistent estimates of the human influence on the troposphere, surface, and ocean over recent decades when the same fingerprint method and analysis period is used. When we combine the three variables into a single fingerprint, the uncertainty of the influence of anthropogenic aerosols is substantially reduced and the signal is detectable considerably earlier in the observational record. Our results highlight the benefits of performing analysis across different variables instead of focusing on one variable only.
Abstract
Tropical Pacific quasi-decadal (TPQD) climate variability is characterized by quasi-decadal sea surface temperature (SST) variations in the central Pacific (CP). This low-frequency climate variability is suggested to influence extreme regional weather and substantially impact global climate patterns and associated socioeconomics through teleconnections. Previous studies mostly attributed the TPQD climate variability to basin-scale air–sea coupling processes. However, due to the coarse resolution of the majority of the observations and climate models, the role of subbasin-scale processes in modulating the TPQD climate variability is still unclear. Using a long-term high-resolution global climate model, we find that energetic small-scale motions with horizontal scales from tens to hundreds of kilometers (loosely referred to as equatorial submesoscale eddies) act as an important damping effect to retard the TPQD variability. During the positive TPQD events, compound increasing precipitation and warming SST in the equatorial Pacific intensifies the upper ocean stratification and weakens the temperature fronts along the Pacific cold tongue. This suppresses submesoscale eddy growth as well as their associated upward vertical heat transport by inhibiting baroclinic instability (BCI) and frontogenesis; conversely, during the negative TPQD events, the opposite is true. Using a series of coupled global climate models that participated in phase 6 of the Coupled Model Intercomparison Project with different oceanic resolutions, we show that the amplitude of the TPQD variability becomes smaller as the oceanic resolution becomes finer, providing evidence for the impacts of submesoscale eddies on damping the TPQD variability. Our study suggests that explicitly simulating equatorial submesoscale eddies is necessary for gaining a more robust understanding of low-frequency tropical climate variability.
Significance Statement
Submesoscale ocean eddies inhibit the development of quasi-decadal climate variability in the equatorial central Pacific, according to a high-resolution global climate simulation.
Abstract
Tropical Pacific quasi-decadal (TPQD) climate variability is characterized by quasi-decadal sea surface temperature (SST) variations in the central Pacific (CP). This low-frequency climate variability is suggested to influence extreme regional weather and substantially impact global climate patterns and associated socioeconomics through teleconnections. Previous studies mostly attributed the TPQD climate variability to basin-scale air–sea coupling processes. However, due to the coarse resolution of the majority of the observations and climate models, the role of subbasin-scale processes in modulating the TPQD climate variability is still unclear. Using a long-term high-resolution global climate model, we find that energetic small-scale motions with horizontal scales from tens to hundreds of kilometers (loosely referred to as equatorial submesoscale eddies) act as an important damping effect to retard the TPQD variability. During the positive TPQD events, compound increasing precipitation and warming SST in the equatorial Pacific intensifies the upper ocean stratification and weakens the temperature fronts along the Pacific cold tongue. This suppresses submesoscale eddy growth as well as their associated upward vertical heat transport by inhibiting baroclinic instability (BCI) and frontogenesis; conversely, during the negative TPQD events, the opposite is true. Using a series of coupled global climate models that participated in phase 6 of the Coupled Model Intercomparison Project with different oceanic resolutions, we show that the amplitude of the TPQD variability becomes smaller as the oceanic resolution becomes finer, providing evidence for the impacts of submesoscale eddies on damping the TPQD variability. Our study suggests that explicitly simulating equatorial submesoscale eddies is necessary for gaining a more robust understanding of low-frequency tropical climate variability.
Significance Statement
Submesoscale ocean eddies inhibit the development of quasi-decadal climate variability in the equatorial central Pacific, according to a high-resolution global climate simulation.
