Abstract
Current climate models project that Antarctic sea ice will decrease by the end of 21st century. Previous studies have suggested that Antarctic sea ice change have impacts on atmospheric circulation and the mean state of the Southern Hemisphere. However, little is known whether Antarctic sea ice loss may have a tangible impact on climate extremes over southern continents and whether ocean-atmosphere coupling plays an important role in changes of climate extremes over southern continents. In this study, we conduct a set of fully coupled and atmosphere-only model experiments forced by present and future Antarctic sea ice cover. It is found that the projected Antarctic sea ice loss by the end of 21st century leads to increase in the frequency and duration of warm extremes (especially warm nights) over southern continents, and decrease in cold extremes over most regions. The frequency and duration of wet extremes are projected to increase over South America and Antarctica, whereas changes in dry days and longest dry spell vary with regions. Further Antarctic sea ice loss under a quadrupling of CO2 leads to similar but larger changes. Comparison between the coupled and atmosphere-only model experiments suggests that ocean dynamics and their interactions with the atmosphere induced by Antarctic sea ice loss plays a key role in driving the identified changes in temperature and precipitation extremes over southern continents. By comparing with global warming experiments, we find that Antarctic sea ice loss may affect temperature and precipitation extremes for some regions under greenhouse warming, especially for Antarctica.
Abstract
Current climate models project that Antarctic sea ice will decrease by the end of 21st century. Previous studies have suggested that Antarctic sea ice change have impacts on atmospheric circulation and the mean state of the Southern Hemisphere. However, little is known whether Antarctic sea ice loss may have a tangible impact on climate extremes over southern continents and whether ocean-atmosphere coupling plays an important role in changes of climate extremes over southern continents. In this study, we conduct a set of fully coupled and atmosphere-only model experiments forced by present and future Antarctic sea ice cover. It is found that the projected Antarctic sea ice loss by the end of 21st century leads to increase in the frequency and duration of warm extremes (especially warm nights) over southern continents, and decrease in cold extremes over most regions. The frequency and duration of wet extremes are projected to increase over South America and Antarctica, whereas changes in dry days and longest dry spell vary with regions. Further Antarctic sea ice loss under a quadrupling of CO2 leads to similar but larger changes. Comparison between the coupled and atmosphere-only model experiments suggests that ocean dynamics and their interactions with the atmosphere induced by Antarctic sea ice loss plays a key role in driving the identified changes in temperature and precipitation extremes over southern continents. By comparing with global warming experiments, we find that Antarctic sea ice loss may affect temperature and precipitation extremes for some regions under greenhouse warming, especially for Antarctica.
Abstract
Which processes control the mean amounts of precipitation received by tropical land and ocean? Do large-scale constraints exist on the ratio between the two? We address these questions using a conceptual box model based on water balance equations. With empirical but physically motivated parametrizations of the water balance components, we construct a set of coupled differential equations which describe the dynamical behavior of the water vapor content over land and ocean as well as the land’s soil moisture content. For a closed model configuration with one ocean and one land box, we compute equilibrium solutions across the parameter space and analyze their sensitivity to parameter choices. The precipitation ratio χ, defined as the ratio between mean land and ocean precipitation rates, quantifies the land-sea precipitation contrast. We find that χ is bounded between zero and one as long as the presence of land does not affect the relationship between water vapor path and precipitation. However, for the tested parameter values, 95% of the obtained χ values are even larger than 0.75. The sensitivity analysis reveals that χ is primarily controlled by the efficiency of atmospheric moisture transport rather than by land surface parameters. We further investigate under which conditions precipitation enhancement over land (χ > 1) would be possible. An open model configuration with an island between two ocean boxes and nonzero external advection into the domain can yield χ values larger than one, but only for a small subset of parameter choices, characterized by small land fractions and a sufficiently large moisture influx through the windward boundary.
Abstract
Which processes control the mean amounts of precipitation received by tropical land and ocean? Do large-scale constraints exist on the ratio between the two? We address these questions using a conceptual box model based on water balance equations. With empirical but physically motivated parametrizations of the water balance components, we construct a set of coupled differential equations which describe the dynamical behavior of the water vapor content over land and ocean as well as the land’s soil moisture content. For a closed model configuration with one ocean and one land box, we compute equilibrium solutions across the parameter space and analyze their sensitivity to parameter choices. The precipitation ratio χ, defined as the ratio between mean land and ocean precipitation rates, quantifies the land-sea precipitation contrast. We find that χ is bounded between zero and one as long as the presence of land does not affect the relationship between water vapor path and precipitation. However, for the tested parameter values, 95% of the obtained χ values are even larger than 0.75. The sensitivity analysis reveals that χ is primarily controlled by the efficiency of atmospheric moisture transport rather than by land surface parameters. We further investigate under which conditions precipitation enhancement over land (χ > 1) would be possible. An open model configuration with an island between two ocean boxes and nonzero external advection into the domain can yield χ values larger than one, but only for a small subset of parameter choices, characterized by small land fractions and a sufficiently large moisture influx through the windward boundary.
Abstract
A scale-dependent dynamic Smagorinsky model is implemented in the Met Office/NERC cloud model (MONC) using two averaging flavours, along Lagrangian pathlines and local moving averages. The dynamic approaches were compared against the conventional Smagorinsky-Lilly scheme in simulating the diurnal cycle of shallow cumulus convection. The simulations spanned from the LES to the near-grey-zone and grey-zone resolutions and revealed the adaptability of the dynamic model across the scales and different stability regimes. The dynamic model can produce a scale and stability dependent profile of the subfilter turbulence length-scale across the chosen resolution range. At grey-zone resolutions the adaptive length scales can better represent the early pre-cloud boundary layer leading to temperature and moisture profiles closer to the LES compared to the standard Smagorinsky. As a result the initialisation and general representation of the cloud field in the dynamic model is in good agreement with the LES. In contrast, the standard Smagorinsky produces a less well-mixed boundary-layer which fails to ventilate moisture from the boundary layer resulting in the delayed spin-up of the cloud layer. Moreover, strong down-gradient diffusion controls the turbulent transport of scalars in the cloud layer. However, the dynamic approaches rely on the resolved field to account for non-local transports, leading to over-energetic structures when the boundary layer is fully developed and the Lagrangian model is used. Introducing the local averaging version of the model or adopting a new Lagrangian time scale provides stronger dissipation without significantly affecting model behaviour.
Abstract
A scale-dependent dynamic Smagorinsky model is implemented in the Met Office/NERC cloud model (MONC) using two averaging flavours, along Lagrangian pathlines and local moving averages. The dynamic approaches were compared against the conventional Smagorinsky-Lilly scheme in simulating the diurnal cycle of shallow cumulus convection. The simulations spanned from the LES to the near-grey-zone and grey-zone resolutions and revealed the adaptability of the dynamic model across the scales and different stability regimes. The dynamic model can produce a scale and stability dependent profile of the subfilter turbulence length-scale across the chosen resolution range. At grey-zone resolutions the adaptive length scales can better represent the early pre-cloud boundary layer leading to temperature and moisture profiles closer to the LES compared to the standard Smagorinsky. As a result the initialisation and general representation of the cloud field in the dynamic model is in good agreement with the LES. In contrast, the standard Smagorinsky produces a less well-mixed boundary-layer which fails to ventilate moisture from the boundary layer resulting in the delayed spin-up of the cloud layer. Moreover, strong down-gradient diffusion controls the turbulent transport of scalars in the cloud layer. However, the dynamic approaches rely on the resolved field to account for non-local transports, leading to over-energetic structures when the boundary layer is fully developed and the Lagrangian model is used. Introducing the local averaging version of the model or adopting a new Lagrangian time scale provides stronger dissipation without significantly affecting model behaviour.
Abstract
A new set of CMIP6 data downscaled using the Localized Constructed Analogs (LOCA) statistical method has been produced, covering central Mexico through Southern Canada at 6 km resolution. Output from 27 CMIP6 Earth System Models is included, with up to 10 ensemble members per model and 3 SSPs (245, 370, and 585). Improvements from the previous CMIP5 downscaled data result in higher daily precipitation extremes, which have significant societal and economic implications. The improvements are accomplished by using a precipitation training data set that better represents daily extremes and by implementing an ensemble bias correction that allows a more realistic representation of extreme high daily precipitation values in models with numerous ensemble members. Over Southern Canada and the CONUS exclusive of Arizona (AZ) and New Mexico (NM), seasonal increases in daily precipitation extremes are largest in winter (~25% in SSP370). Over Mexico, AZ, and NM, seasonal increases are largest in autumn (~15%). Summer is the outlier season, with low model agreement except in New England and little changes in 5-yr return values, but substantial increases in the CONUS and Canada in the 500-yr return value. 1-in-100 yr historical daily precipitation events become substantially more frequent in the future, as often as once in 30-40 years in the southeastern U.S. and Pacific Northwest by end of century under SSP 370. Impacts of the higher precipitation extremes in the LOCA version 2 downscaled CMIP6 product relative to LOCA-downscaled CMIP5 product, even for similar anthropogenic emissions, may need to be considered by end-users.
Abstract
A new set of CMIP6 data downscaled using the Localized Constructed Analogs (LOCA) statistical method has been produced, covering central Mexico through Southern Canada at 6 km resolution. Output from 27 CMIP6 Earth System Models is included, with up to 10 ensemble members per model and 3 SSPs (245, 370, and 585). Improvements from the previous CMIP5 downscaled data result in higher daily precipitation extremes, which have significant societal and economic implications. The improvements are accomplished by using a precipitation training data set that better represents daily extremes and by implementing an ensemble bias correction that allows a more realistic representation of extreme high daily precipitation values in models with numerous ensemble members. Over Southern Canada and the CONUS exclusive of Arizona (AZ) and New Mexico (NM), seasonal increases in daily precipitation extremes are largest in winter (~25% in SSP370). Over Mexico, AZ, and NM, seasonal increases are largest in autumn (~15%). Summer is the outlier season, with low model agreement except in New England and little changes in 5-yr return values, but substantial increases in the CONUS and Canada in the 500-yr return value. 1-in-100 yr historical daily precipitation events become substantially more frequent in the future, as often as once in 30-40 years in the southeastern U.S. and Pacific Northwest by end of century under SSP 370. Impacts of the higher precipitation extremes in the LOCA version 2 downscaled CMIP6 product relative to LOCA-downscaled CMIP5 product, even for similar anthropogenic emissions, may need to be considered by end-users.
Abstract
Numerous low-level vortices are initiated downwind of the Hoggar Mountains and progress towards the Atlantic coast on the northern path of African Easterly Waves (AEWs). These vortices occur mostly in July and August and more specifically when the northern position of the Saharan heat low (SHL) generates stronger and vertically expanded easterly winds over Hoggar mountains. At synoptic time-scales, a composite analysis reveals that vortex initiation and westward motion are also statistically triggered by a reinforcement of these easterly winds by a wide and persistent high-pressure anomaly developing around the Strait of Gibraltar and by a weak wave trough approaching from the east. The vortices are generated in the lee of the Hoggar, about 1000 km west of this approaching trough, and intensify rapidly. The evolution of the vortex perturbation is afterward comparable with the known evolution of the AEWs of the northern path and suggest a growth due to dry barotropic and baroclinic processes induced in particular by the strong cyclonic shear between the reinforced easterly winds and the monsoon flow. These results show that vortex genesis promoted by changes in orographic forcing due to the strengthening of easterly winds over Hoggar mountains is a source of intensification of the northern path of AEWs in July and August. These results also provide a possible mechanism to explain the role of the SHL and of particular mid-latitude intraseasonal disturbances on the intensity of these waves.
Abstract
Numerous low-level vortices are initiated downwind of the Hoggar Mountains and progress towards the Atlantic coast on the northern path of African Easterly Waves (AEWs). These vortices occur mostly in July and August and more specifically when the northern position of the Saharan heat low (SHL) generates stronger and vertically expanded easterly winds over Hoggar mountains. At synoptic time-scales, a composite analysis reveals that vortex initiation and westward motion are also statistically triggered by a reinforcement of these easterly winds by a wide and persistent high-pressure anomaly developing around the Strait of Gibraltar and by a weak wave trough approaching from the east. The vortices are generated in the lee of the Hoggar, about 1000 km west of this approaching trough, and intensify rapidly. The evolution of the vortex perturbation is afterward comparable with the known evolution of the AEWs of the northern path and suggest a growth due to dry barotropic and baroclinic processes induced in particular by the strong cyclonic shear between the reinforced easterly winds and the monsoon flow. These results show that vortex genesis promoted by changes in orographic forcing due to the strengthening of easterly winds over Hoggar mountains is a source of intensification of the northern path of AEWs in July and August. These results also provide a possible mechanism to explain the role of the SHL and of particular mid-latitude intraseasonal disturbances on the intensity of these waves.
Abstract
Modeled global warming is often quantified using global near-surface air temperature (T as). Meanwhile, long-term temperature datasets combine observations of T as over land with sea surface temperature (SST) over ocean. Modeled ocean T as warms more than SST, which can bias model–observation comparisons. Skin temperature (Ts ), which is typically warmer than T as, follows SST changes so the ocean surface temperature discontinuity δTs = Ts − T as decreases with warming. Here I show that under CO2 forcing, decreased δTs is consistently simulated for nonpolar ocean within ±60°S/N, but not for other regions. I investigate the causes of oceanic δTs decrease using a LongRunMIP climate simulation, radiative kernels, and standard methods for diagnosing forcing and feedbacks from the CMIP5 ensemble. CO2 forcing establishes longwave heating of the lower atmosphere and subsequent adjustments that result in a small T as increase, and therefore a δTs decrease. During the subsequent warming in response to CO2 forcing, the model-mean surface evaporation feedback is 3.6 W m−2 °C−1 over oceans, which reduces Ts warming relative to T as and further shrinks δTs . Present-day forcing and feedback contributions are of similar magnitude, and both contribute to small differences in model–observation comparisons of global warming rates when these differences are not accounted for.
Significance Statement
Earth’s surface skin temperature is generally warmer than that of the air just above, and this discontinuity drives upward turbulent heat fluxes. Under global warming, climate models consistently show that over oceans, the air above warms more than the water below. This causes issues when comparing model output and observational temperature records, since observational records blend land air and ocean water temperature. It also affects understanding of how surface energy and moisture fluxes will change with warming. Observational data are currently too uncertain to confidently support or refute this model behavior, and the IPCC recently noted that “there is no simple explanation based on physical grounds alone for how this difference responds to climate change.” This study provides such an explanation for changes over ocean, and shows that this result applies only to nonpolar oceans.
Abstract
Modeled global warming is often quantified using global near-surface air temperature (T as). Meanwhile, long-term temperature datasets combine observations of T as over land with sea surface temperature (SST) over ocean. Modeled ocean T as warms more than SST, which can bias model–observation comparisons. Skin temperature (Ts ), which is typically warmer than T as, follows SST changes so the ocean surface temperature discontinuity δTs = Ts − T as decreases with warming. Here I show that under CO2 forcing, decreased δTs is consistently simulated for nonpolar ocean within ±60°S/N, but not for other regions. I investigate the causes of oceanic δTs decrease using a LongRunMIP climate simulation, radiative kernels, and standard methods for diagnosing forcing and feedbacks from the CMIP5 ensemble. CO2 forcing establishes longwave heating of the lower atmosphere and subsequent adjustments that result in a small T as increase, and therefore a δTs decrease. During the subsequent warming in response to CO2 forcing, the model-mean surface evaporation feedback is 3.6 W m−2 °C−1 over oceans, which reduces Ts warming relative to T as and further shrinks δTs . Present-day forcing and feedback contributions are of similar magnitude, and both contribute to small differences in model–observation comparisons of global warming rates when these differences are not accounted for.
Significance Statement
Earth’s surface skin temperature is generally warmer than that of the air just above, and this discontinuity drives upward turbulent heat fluxes. Under global warming, climate models consistently show that over oceans, the air above warms more than the water below. This causes issues when comparing model output and observational temperature records, since observational records blend land air and ocean water temperature. It also affects understanding of how surface energy and moisture fluxes will change with warming. Observational data are currently too uncertain to confidently support or refute this model behavior, and the IPCC recently noted that “there is no simple explanation based on physical grounds alone for how this difference responds to climate change.” This study provides such an explanation for changes over ocean, and shows that this result applies only to nonpolar oceans.
Abstract
Several studies have reported a significant negative correlation between the tropical cyclone (TC) frequency affecting South Korea (KOR TC frequency) and the Pacific decadal oscillation (PDO), which is accompanied by the weak negative correlation between the TC intensity when TCs enter Korean coastal seas (KOR TC intensity) and PDO. However, the weak negative relationship between KOR TC intensity and PDO contradicts results from other related studies regarding the relationship between TC activity in the western North Pacific and PDO. Thus, we reexamined the PDO relationships with both KOR TC frequency and intensity and their mechanisms. Although a negative correlation between KOR TC frequency and PDO was consistently found, in contrast to previous studies, we found a significant positive correlation between KOR TC intensity and PDO. According to our analyses, during the negative phase, anomalous southeasterly winds over the Korean Peninsula and the northwestward shift in the mean TC genesis location favor the increase in KOR TC frequency. The northwestward mean TC genesis location migrates, which shortens the time spent over the warm ocean, weakening the lifetime maximum intensity and, consequently, the KOR TC intensity. We confirmed that our result is robust by performing various sensitivity tests examining the best track data, analysis period, TC season, and KOR TC definition.
Abstract
Several studies have reported a significant negative correlation between the tropical cyclone (TC) frequency affecting South Korea (KOR TC frequency) and the Pacific decadal oscillation (PDO), which is accompanied by the weak negative correlation between the TC intensity when TCs enter Korean coastal seas (KOR TC intensity) and PDO. However, the weak negative relationship between KOR TC intensity and PDO contradicts results from other related studies regarding the relationship between TC activity in the western North Pacific and PDO. Thus, we reexamined the PDO relationships with both KOR TC frequency and intensity and their mechanisms. Although a negative correlation between KOR TC frequency and PDO was consistently found, in contrast to previous studies, we found a significant positive correlation between KOR TC intensity and PDO. According to our analyses, during the negative phase, anomalous southeasterly winds over the Korean Peninsula and the northwestward shift in the mean TC genesis location favor the increase in KOR TC frequency. The northwestward mean TC genesis location migrates, which shortens the time spent over the warm ocean, weakening the lifetime maximum intensity and, consequently, the KOR TC intensity. We confirmed that our result is robust by performing various sensitivity tests examining the best track data, analysis period, TC season, and KOR TC definition.
Abstract
The western-central equatorial Pacific (WCEP) zonal wind affects El Niño-Southern Oscillation (ENSO) by involving a series of multi-scale air-sea interactions. Its interannual variation contributes the most to ENSO amplitude. Thus, understanding the predictability of the WCEP interannual wind is of great importance for better predictions of ENSO. Here we show that the North Pacific Oscillation (NPO) and the South Pacific Oscillation (SPO) alternate in fueling this interannual wind from late boreal winter to austral winter in the presence of background trade winds in different hemispheres. During the boreal winter-spring, the NPO registers footprints in the tropics by benefiting from the Pacific meridional mode and modulating the northwestern Pacific intertropical convergence zone (NITCZ). However, as austral winter approaches, the SPO takes over the role of the NPO in maintaining the anomalous NITCZ. Moreover, the interannual wind is further driven to the east in the positive phase of the SPO, by intensified central-eastern equatorial Pacific convection resulting from tropical-extratropical heat flux adjustments. A reconstructed WCEP interannual wind index involving only the NPO and the SPO processes a long lead time for ENSO prediction by nearly one year. These two extratropical boosters enhance the viability of equatorial Pacific zonal wind anomalies associated with the large growth rate of ENSO, and the one in the winter hemisphere seems to be more efficient in forcing the tropics. Our result further indicates that the NPO benefits a long-lead prediction of the WCEP interannual wind and ENSO, while the SPO is the dominant extratropical predictor of ENSO amplitude.
Abstract
The western-central equatorial Pacific (WCEP) zonal wind affects El Niño-Southern Oscillation (ENSO) by involving a series of multi-scale air-sea interactions. Its interannual variation contributes the most to ENSO amplitude. Thus, understanding the predictability of the WCEP interannual wind is of great importance for better predictions of ENSO. Here we show that the North Pacific Oscillation (NPO) and the South Pacific Oscillation (SPO) alternate in fueling this interannual wind from late boreal winter to austral winter in the presence of background trade winds in different hemispheres. During the boreal winter-spring, the NPO registers footprints in the tropics by benefiting from the Pacific meridional mode and modulating the northwestern Pacific intertropical convergence zone (NITCZ). However, as austral winter approaches, the SPO takes over the role of the NPO in maintaining the anomalous NITCZ. Moreover, the interannual wind is further driven to the east in the positive phase of the SPO, by intensified central-eastern equatorial Pacific convection resulting from tropical-extratropical heat flux adjustments. A reconstructed WCEP interannual wind index involving only the NPO and the SPO processes a long lead time for ENSO prediction by nearly one year. These two extratropical boosters enhance the viability of equatorial Pacific zonal wind anomalies associated with the large growth rate of ENSO, and the one in the winter hemisphere seems to be more efficient in forcing the tropics. Our result further indicates that the NPO benefits a long-lead prediction of the WCEP interannual wind and ENSO, while the SPO is the dominant extratropical predictor of ENSO amplitude.
Abstract
“Supermodeling” climate by allowing different models to assimilate data from one another in run time has been shown to give results superior to those of any one model and superior to any weighted average of model outputs. The only free parameters, connection strengths between corresponding variables in each pair of models, are determined using some form of machine learning. It is demonstrated that supermodeling succeeds because near critical states, inter-scale interactions are important but unresolved processes cannot be effectively represented diagnostically in any single parameterization scheme. In two examples, a pair of toy quasigeostrophic (QG) channel models of the mid-latidtudes and a pair of ECHAM5 models of the Tropical Pacific atmosphere with a common ocean, supermodels dynamically combine parameterization schemes so as to capture criticality, associated critical structures, and the supporting scale interactions. The QG supermodeling scheme extends a previous configuration in which two such models synchronize with inter-model connections only between medium-scale components of the flow; here the connections are trained against a third “real” model. Intermittent blocking patterns characterize the critical behavior thus obtained, even where such patterns are missing in the constituent models. In the ECHAM-based climate supermodel, the corresponding critical structure is the single ITCZ pattern, a pattern that occurs in neither of the constituent models. For supermodels of both types, power spectra indicate enhanced inter-scale interactions in frequency or energy ranges of physical interest, in agreement with observed data, and supporting a generalized form of the self-organized criticality hypothesis.
Abstract
“Supermodeling” climate by allowing different models to assimilate data from one another in run time has been shown to give results superior to those of any one model and superior to any weighted average of model outputs. The only free parameters, connection strengths between corresponding variables in each pair of models, are determined using some form of machine learning. It is demonstrated that supermodeling succeeds because near critical states, inter-scale interactions are important but unresolved processes cannot be effectively represented diagnostically in any single parameterization scheme. In two examples, a pair of toy quasigeostrophic (QG) channel models of the mid-latidtudes and a pair of ECHAM5 models of the Tropical Pacific atmosphere with a common ocean, supermodels dynamically combine parameterization schemes so as to capture criticality, associated critical structures, and the supporting scale interactions. The QG supermodeling scheme extends a previous configuration in which two such models synchronize with inter-model connections only between medium-scale components of the flow; here the connections are trained against a third “real” model. Intermittent blocking patterns characterize the critical behavior thus obtained, even where such patterns are missing in the constituent models. In the ECHAM-based climate supermodel, the corresponding critical structure is the single ITCZ pattern, a pattern that occurs in neither of the constituent models. For supermodels of both types, power spectra indicate enhanced inter-scale interactions in frequency or energy ranges of physical interest, in agreement with observed data, and supporting a generalized form of the self-organized criticality hypothesis.
