Browse
Abstract
Constraining unforced and forced climate variability impacts interpretations of past climate variations and predictions of future warming. However, comparing general circulation models (GCMs) and last millennium Holocene hydroclimate proxies reveals significant mismatches between simulated and reconstructed low-frequency variability at multidecadal and longer time scales. This mismatch suggests that existing simulations underestimate either external or internal drivers of climate variability. In addition, large differences arise across GCMs in both the magnitude and spatial pattern of low-frequency climate variability. Dynamical understanding of forced and unforced variability is expected to contribute to improved interpretations of paleoclimate variability. To that end, we develop a framework for fingerprinting spatiotemporal patterns of temperature variability in forced and unforced simulations. This framework relies on two frequency-dependent metrics: 1) degrees of freedom (≡N) and 2) spatial coherence. First, we use N and spatial coherence to characterize variability across a suite of both preindustrial control (unforced) and last-millennium (forced) GCM simulations. Overall, we find that, at low frequencies and when forcings are added, regional independence in the climate system decreases, reflected in fewer N and higher coherence between local and global mean surface temperature. We then present a simple three-box moist-static-energy-balance model for temperature variability, which is able to emulate key frequency-dependent behavior in the GCMs. This suggests that temperature variability in the GCM ensemble can be understood through Earth’s energy budget and downgradient energy transport, and allows us to identify sources of polar-amplified variability. Finally, we discuss insights the three-box model can provide into model-to-model GCM differences.
Significance Statement
Forced and unforced temperature variability are poorly constrained and understood, particularly that at time scales longer than a decade. Here, we identify key differences in the time scale–dependent behavior of forced and unforced temperature variability using a combination of numerical climate models and principles of downgradient energy transport. This work, and the spatiotemporal characterizations of forced and unforced temperature variability that we generate, will aid in interpretations of proxy-based paleoclimate reconstructions and improve mechanistic understanding of variability.
Abstract
Constraining unforced and forced climate variability impacts interpretations of past climate variations and predictions of future warming. However, comparing general circulation models (GCMs) and last millennium Holocene hydroclimate proxies reveals significant mismatches between simulated and reconstructed low-frequency variability at multidecadal and longer time scales. This mismatch suggests that existing simulations underestimate either external or internal drivers of climate variability. In addition, large differences arise across GCMs in both the magnitude and spatial pattern of low-frequency climate variability. Dynamical understanding of forced and unforced variability is expected to contribute to improved interpretations of paleoclimate variability. To that end, we develop a framework for fingerprinting spatiotemporal patterns of temperature variability in forced and unforced simulations. This framework relies on two frequency-dependent metrics: 1) degrees of freedom (≡N) and 2) spatial coherence. First, we use N and spatial coherence to characterize variability across a suite of both preindustrial control (unforced) and last-millennium (forced) GCM simulations. Overall, we find that, at low frequencies and when forcings are added, regional independence in the climate system decreases, reflected in fewer N and higher coherence between local and global mean surface temperature. We then present a simple three-box moist-static-energy-balance model for temperature variability, which is able to emulate key frequency-dependent behavior in the GCMs. This suggests that temperature variability in the GCM ensemble can be understood through Earth’s energy budget and downgradient energy transport, and allows us to identify sources of polar-amplified variability. Finally, we discuss insights the three-box model can provide into model-to-model GCM differences.
Significance Statement
Forced and unforced temperature variability are poorly constrained and understood, particularly that at time scales longer than a decade. Here, we identify key differences in the time scale–dependent behavior of forced and unforced temperature variability using a combination of numerical climate models and principles of downgradient energy transport. This work, and the spatiotemporal characterizations of forced and unforced temperature variability that we generate, will aid in interpretations of proxy-based paleoclimate reconstructions and improve mechanistic understanding of variability.
Abstract
Explosive cyclones (ECs), defined as extratropical cyclones that experience normalized pressure drops of at least 24 hPa in 24 h, are impactful weather events in the North Atlantic sector, but year-to-year changes in the frequency and impacts of these storms are sizeable. To analyze the sources of this interannual variability, we track cases of ECs and dissect them into two spatial groups: those that formed near the east coast of North America (coastal) and those in the north central Atlantic (high latitude). The frequency of high-latitude ECs is strongly correlated with the North Atlantic Oscillation, a well-known feature, whereas coastal EC frequency is statistically linked with an atmospheric wave train emanating from the North Pacific in the last 30 years. This wave train pattern of alternating high and low pressure is associated with heightened upper-level divergence and Eady growth rates along the east coast of North America, likely resulting in a stronger correspondence between the atmospheric wave train and coastal EC frequency. Using coupled model experiments, we show that the tropical and North Pacific oceans are an important factor for this atmospheric wave train and the subsequent enhancement of seasonal baroclinicity in the North Atlantic.
Abstract
Explosive cyclones (ECs), defined as extratropical cyclones that experience normalized pressure drops of at least 24 hPa in 24 h, are impactful weather events in the North Atlantic sector, but year-to-year changes in the frequency and impacts of these storms are sizeable. To analyze the sources of this interannual variability, we track cases of ECs and dissect them into two spatial groups: those that formed near the east coast of North America (coastal) and those in the north central Atlantic (high latitude). The frequency of high-latitude ECs is strongly correlated with the North Atlantic Oscillation, a well-known feature, whereas coastal EC frequency is statistically linked with an atmospheric wave train emanating from the North Pacific in the last 30 years. This wave train pattern of alternating high and low pressure is associated with heightened upper-level divergence and Eady growth rates along the east coast of North America, likely resulting in a stronger correspondence between the atmospheric wave train and coastal EC frequency. Using coupled model experiments, we show that the tropical and North Pacific oceans are an important factor for this atmospheric wave train and the subsequent enhancement of seasonal baroclinicity in the North Atlantic.
Abstract
In recent years, the Southern Ocean has experienced unprecedented surface warming and sea ice loss—a stark reversal of the sea ice expansion and surface cooling that prevailed over the preceding decades. Here, we examine the mechanisms that led to the abrupt circumpolar surface warming events that occurred in late 2016 and 2019 and assess the role of internal climate variability. A mixed layer heat budget analysis reveals that these recent circumpolar surface warming events were triggered by a weakening of the circumpolar westerlies, which decreased northward Ekman transport and accelerated the seasonal shoaling of the mixed layer. We emphasize the underappreciated effect of the latter mechanism, which played a dominant role and amplified the warming effect of air–sea heat fluxes during months of peak solar insolation. An examination of the CESM1 large ensemble demonstrates that these recent circumpolar warming events are consistent with the internal variability associated with the Southern Annular Mode (SAM), whereby negative SAM in austral spring favors shallower mixed layers and anomalously high summertime SST. A key insight from this analysis is that the seasonal phasing of springtime mixed layer depth shoaling is an important contributor to summertime SST variability in the Southern Ocean. Thus, future Southern Ocean summertime SST extremes will depend on the coevolution of mixed layer depth and surface wind variability.
Significance Statement
This study examines how reductions in the strength of the circumpolar westerlies can produce abrupt and extreme surface warming across the Southern Ocean. A key insight is that the mixed layer temperature is most sensitive to surface wind perturbations in late austral spring, when the regional mixed layer depth and solar insolation approach their respective seasonal minimum and maximum. This heightened surface temperature response to surface wind variability was realized during the austral spring of 2016 and 2019, when a dramatic weakening of the circumpolar westerlies triggered unprecedented warming across the Southern Ocean. In both cases, the anomalously weak circumpolar winds reduced the northward Ekman transport of cool subpolar waters and caused the mixed layer to shoal more rapidly in the spring, with the latter mechanism being more dominant. Using results from an ensemble of coupled climate simulations, we demonstrate that the 2016 and 2019 Southern Ocean warming events are consistent with the internal variability associated with the Southern Annular Mode (SAM). These results suggest that future Southern Ocean surface warming extremes will depend on both the evolution of regional mixed layer depths and interannual wind variability.
Abstract
In recent years, the Southern Ocean has experienced unprecedented surface warming and sea ice loss—a stark reversal of the sea ice expansion and surface cooling that prevailed over the preceding decades. Here, we examine the mechanisms that led to the abrupt circumpolar surface warming events that occurred in late 2016 and 2019 and assess the role of internal climate variability. A mixed layer heat budget analysis reveals that these recent circumpolar surface warming events were triggered by a weakening of the circumpolar westerlies, which decreased northward Ekman transport and accelerated the seasonal shoaling of the mixed layer. We emphasize the underappreciated effect of the latter mechanism, which played a dominant role and amplified the warming effect of air–sea heat fluxes during months of peak solar insolation. An examination of the CESM1 large ensemble demonstrates that these recent circumpolar warming events are consistent with the internal variability associated with the Southern Annular Mode (SAM), whereby negative SAM in austral spring favors shallower mixed layers and anomalously high summertime SST. A key insight from this analysis is that the seasonal phasing of springtime mixed layer depth shoaling is an important contributor to summertime SST variability in the Southern Ocean. Thus, future Southern Ocean summertime SST extremes will depend on the coevolution of mixed layer depth and surface wind variability.
Significance Statement
This study examines how reductions in the strength of the circumpolar westerlies can produce abrupt and extreme surface warming across the Southern Ocean. A key insight is that the mixed layer temperature is most sensitive to surface wind perturbations in late austral spring, when the regional mixed layer depth and solar insolation approach their respective seasonal minimum and maximum. This heightened surface temperature response to surface wind variability was realized during the austral spring of 2016 and 2019, when a dramatic weakening of the circumpolar westerlies triggered unprecedented warming across the Southern Ocean. In both cases, the anomalously weak circumpolar winds reduced the northward Ekman transport of cool subpolar waters and caused the mixed layer to shoal more rapidly in the spring, with the latter mechanism being more dominant. Using results from an ensemble of coupled climate simulations, we demonstrate that the 2016 and 2019 Southern Ocean warming events are consistent with the internal variability associated with the Southern Annular Mode (SAM). These results suggest that future Southern Ocean surface warming extremes will depend on both the evolution of regional mixed layer depths and interannual wind variability.
Abstract
Weather regimes defined through cluster analysis concisely categorize the anomalous regional circulation pattern on any given day. Owing to their persistence and low dimensionality, regimes are increasingly used in subseasonal-to-seasonal prediction and in analysis of climate variability and change. However, a limitation of existing regime classifications for North America is their seasonal dependence, with most existing studies defining regimes for winter only. Here, we normalize the seasonal cycle in daily geopotential height variance and use empirical orthogonal function analysis combined with k-means clustering to define a new set of year-round North American weather regimes: the Pacific Trough, Pacific Ridge, Alaskan Ridge, and Greenland High regimes. We additionally define a “No Regime” state to represent conditions close to climatology. To demonstrate the robustness of the classification, a thorough assessment of the sensitivity of the clustering solution to various methodological choices is provided. The median persistence of all four regimes, obtained without imposing a persistence criterion, is found to be one week, approximately 3 times longer than the median persistence of the No Regime state. Regime-associated temperature and precipitation anomalies are reported, together with the relationship between the regimes and modes of climate variability. We also quantify historical trends in the frequency of the regimes since 1979, finding a decrease in the annual frequency of the Pacific Trough regime and an increase in the summertime frequency of the Greenland High regime. This study serves as a foundation for the future use of these regimes in a variety of weather and climate applications.
Significance Statement
Weather regimes provide a simple way of classifying daily large-scale regional weather patterns into a few predefined types. Existing methods usually define regimes for a specific season (typically winter), which limits their use, or provides only a minimal assessment of their robustness. In this study, we objectively quantify four weather regimes for use year-round over North America, while we classify near-normal conditions as No Regime. The four regimes represent persistent large-scale weather types that last for about a week and occasionally much longer. Our new classification can be applied to subseasonal-to-seasonal forecasts and climate model output to diagnose recurrent weather types across the North American continent.
Abstract
Weather regimes defined through cluster analysis concisely categorize the anomalous regional circulation pattern on any given day. Owing to their persistence and low dimensionality, regimes are increasingly used in subseasonal-to-seasonal prediction and in analysis of climate variability and change. However, a limitation of existing regime classifications for North America is their seasonal dependence, with most existing studies defining regimes for winter only. Here, we normalize the seasonal cycle in daily geopotential height variance and use empirical orthogonal function analysis combined with k-means clustering to define a new set of year-round North American weather regimes: the Pacific Trough, Pacific Ridge, Alaskan Ridge, and Greenland High regimes. We additionally define a “No Regime” state to represent conditions close to climatology. To demonstrate the robustness of the classification, a thorough assessment of the sensitivity of the clustering solution to various methodological choices is provided. The median persistence of all four regimes, obtained without imposing a persistence criterion, is found to be one week, approximately 3 times longer than the median persistence of the No Regime state. Regime-associated temperature and precipitation anomalies are reported, together with the relationship between the regimes and modes of climate variability. We also quantify historical trends in the frequency of the regimes since 1979, finding a decrease in the annual frequency of the Pacific Trough regime and an increase in the summertime frequency of the Greenland High regime. This study serves as a foundation for the future use of these regimes in a variety of weather and climate applications.
Significance Statement
Weather regimes provide a simple way of classifying daily large-scale regional weather patterns into a few predefined types. Existing methods usually define regimes for a specific season (typically winter), which limits their use, or provides only a minimal assessment of their robustness. In this study, we objectively quantify four weather regimes for use year-round over North America, while we classify near-normal conditions as No Regime. The four regimes represent persistent large-scale weather types that last for about a week and occasionally much longer. Our new classification can be applied to subseasonal-to-seasonal forecasts and climate model output to diagnose recurrent weather types across the North American continent.
Abstract
The Pacific–North American (PNA) teleconnection pattern is one of the prominent atmospheric circulation modes in the extratropical Northern Hemisphere, and its seasonal to interannual predictability is suggested to originate from El Niño–Southern Oscillation (ENSO). Intriguingly, the PNA teleconnection pattern exhibits variance at near-annual frequencies, which is related to a rapid phase reversal of the PNA pattern during ENSO years, whereas the ENSO sea surface temperature (SST) anomalies in the tropical Pacific are evolving much slower in time. This distinct seasonal feature of the PNA pattern can be explained by an amplitude modulation of the interannual ENSO signal by the annual cycle (i.e., the ENSO combination mode). The ENSO-related seasonal phase transition of the PNA pattern is reproduced well in an atmospheric general circulation model when both the background SST annual cycle and ENSO SST anomalies are prescribed. In contrast, this characteristic seasonal evolution of the PNA pattern is absent when the tropical Pacific background SST annual cycle is not considered in the modeling experiments. The background SST annual cycle in the tropical Pacific modulates the ENSO-associated tropical Pacific convection response, leading to a rapid enhancement of convection anomalies in winter. The enhanced convection results in a fast establishment of the large-scale PNA teleconnection during ENSO years. The dynamics of this ENSO–annual cycle interaction fills an important gap in our understanding of the seasonally modulated PNA teleconnection pattern during ENSO years.
Abstract
The Pacific–North American (PNA) teleconnection pattern is one of the prominent atmospheric circulation modes in the extratropical Northern Hemisphere, and its seasonal to interannual predictability is suggested to originate from El Niño–Southern Oscillation (ENSO). Intriguingly, the PNA teleconnection pattern exhibits variance at near-annual frequencies, which is related to a rapid phase reversal of the PNA pattern during ENSO years, whereas the ENSO sea surface temperature (SST) anomalies in the tropical Pacific are evolving much slower in time. This distinct seasonal feature of the PNA pattern can be explained by an amplitude modulation of the interannual ENSO signal by the annual cycle (i.e., the ENSO combination mode). The ENSO-related seasonal phase transition of the PNA pattern is reproduced well in an atmospheric general circulation model when both the background SST annual cycle and ENSO SST anomalies are prescribed. In contrast, this characteristic seasonal evolution of the PNA pattern is absent when the tropical Pacific background SST annual cycle is not considered in the modeling experiments. The background SST annual cycle in the tropical Pacific modulates the ENSO-associated tropical Pacific convection response, leading to a rapid enhancement of convection anomalies in winter. The enhanced convection results in a fast establishment of the large-scale PNA teleconnection during ENSO years. The dynamics of this ENSO–annual cycle interaction fills an important gap in our understanding of the seasonally modulated PNA teleconnection pattern during ENSO years.
Abstract
The summer North American dipole (NAD) is a pattern of climate variability linked to variations in boreal forest seed production and migration of seed-eating birds. This is a modeling investigation of two teleconnections identified as drivers of the NAD in prior observational work: 1) tropically sourced atmospheric Rossby waves associated with anomalies in the phase distribution of the Madden–Julian oscillation (MJO) (i.e., phases 1 and 6 are anomalously prominent), and 2) a pan-Pacific atmospheric Rossby wave linked to East Asian monsoonal (EAM) convection. Sea surface temperature (SST) boundary forcing experiments were conducted with the Community Earth System Model 2 (CESM2) to trigger convection patterns that align with those observed during EAM and nonuniform phase distributions of MJO. For the EAM case, an El Niño–like SST dipole pattern combined with cool southern Japan SST forcing produced a convection and jet stream shift anomaly over East Asia and the northern Pacific with a positive NAD pattern downstream over North America, similar to the observed pattern when precipitation over East Asia (P EA) is relatively high. A companion experiment with only ENSO-like SST forcing also produced the NAD but featured a different structure over the Eurasian continent with a response resembling the summer east Atlantic (SEA) pattern over eastern North America and the eastern Atlantic. Simulation results suggest that the southern Japan SST forcing region has a secondary importance in triggering the NAD, producing only a somewhat NAD-like pattern by itself and only slightly improving the NAD produced by ENSO-like forcing. Simulations using SST forcing to induce seasonal convection anomalies with spatial patterns similar to anomalously frequent occurrence of MJO phase 1 (phase 6) produced circulation response patterns resembling the positive NAD (negative NAD).
Abstract
The summer North American dipole (NAD) is a pattern of climate variability linked to variations in boreal forest seed production and migration of seed-eating birds. This is a modeling investigation of two teleconnections identified as drivers of the NAD in prior observational work: 1) tropically sourced atmospheric Rossby waves associated with anomalies in the phase distribution of the Madden–Julian oscillation (MJO) (i.e., phases 1 and 6 are anomalously prominent), and 2) a pan-Pacific atmospheric Rossby wave linked to East Asian monsoonal (EAM) convection. Sea surface temperature (SST) boundary forcing experiments were conducted with the Community Earth System Model 2 (CESM2) to trigger convection patterns that align with those observed during EAM and nonuniform phase distributions of MJO. For the EAM case, an El Niño–like SST dipole pattern combined with cool southern Japan SST forcing produced a convection and jet stream shift anomaly over East Asia and the northern Pacific with a positive NAD pattern downstream over North America, similar to the observed pattern when precipitation over East Asia (P EA) is relatively high. A companion experiment with only ENSO-like SST forcing also produced the NAD but featured a different structure over the Eurasian continent with a response resembling the summer east Atlantic (SEA) pattern over eastern North America and the eastern Atlantic. Simulation results suggest that the southern Japan SST forcing region has a secondary importance in triggering the NAD, producing only a somewhat NAD-like pattern by itself and only slightly improving the NAD produced by ENSO-like forcing. Simulations using SST forcing to induce seasonal convection anomalies with spatial patterns similar to anomalously frequent occurrence of MJO phase 1 (phase 6) produced circulation response patterns resembling the positive NAD (negative NAD).
Abstract
This study reveals a close relation between the Mascarene high (MH), atmospheric transient eddies (hereafter transient eddies or eddies for short), and the sea surface temperature (SST) front over the southern Indian Ocean in austral winter. Climatologically, the subpolar westerly jet couples well with transient eddies via eddy–mean flow interaction and the anticyclonic vorticity to its north helps with anchoring the MH. On the interannual time scale, the MH exhibits a dominant meridional variation accompanied by intensity variability. When the MH moves poleward and intensifies, positive quasi-barotropic geopotential height anomalies associated with a warm temperature feature the southern flank of MH. As a result of the modified mean temperature gradient, the subpolar jet and transient eddies’ activity are enhanced near the jet exit; in contrast, the subtropical westerly jet and eddies are weakened over the jet entrance, mainly via the baroclinic energy conversion. As feedback, the anomalous transient eddies can trigger the poleward shift of MH by diverging the extended Eliassen–Palm (E-P) flux from subpolar to subtropical region and thus the intensification of subpolar jet and weakness of subtropical jet. Such positive feedback between the meridional variation of MH and transient eddies could be attributed to the underlying SST anomalies. Early SST warming appears over the southwestern Indian Ocean 3 months prior and shifts the Agulhas SST front poleward. The poleward Agulhas SST front could further induce a southward displacement of the activity of transient eddies by changing the low-level atmospheric baroclinicity. Hence, the SST anomalies over the southern Indian Ocean may trigger the meridional variation of MH via the positive eddies–mean flow feedback.
Abstract
This study reveals a close relation between the Mascarene high (MH), atmospheric transient eddies (hereafter transient eddies or eddies for short), and the sea surface temperature (SST) front over the southern Indian Ocean in austral winter. Climatologically, the subpolar westerly jet couples well with transient eddies via eddy–mean flow interaction and the anticyclonic vorticity to its north helps with anchoring the MH. On the interannual time scale, the MH exhibits a dominant meridional variation accompanied by intensity variability. When the MH moves poleward and intensifies, positive quasi-barotropic geopotential height anomalies associated with a warm temperature feature the southern flank of MH. As a result of the modified mean temperature gradient, the subpolar jet and transient eddies’ activity are enhanced near the jet exit; in contrast, the subtropical westerly jet and eddies are weakened over the jet entrance, mainly via the baroclinic energy conversion. As feedback, the anomalous transient eddies can trigger the poleward shift of MH by diverging the extended Eliassen–Palm (E-P) flux from subpolar to subtropical region and thus the intensification of subpolar jet and weakness of subtropical jet. Such positive feedback between the meridional variation of MH and transient eddies could be attributed to the underlying SST anomalies. Early SST warming appears over the southwestern Indian Ocean 3 months prior and shifts the Agulhas SST front poleward. The poleward Agulhas SST front could further induce a southward displacement of the activity of transient eddies by changing the low-level atmospheric baroclinicity. Hence, the SST anomalies over the southern Indian Ocean may trigger the meridional variation of MH via the positive eddies–mean flow feedback.
Abstract
The intense and moist winds in a tropical cyclone (TC) environment can produce strong mountain waves and enhanced precipitation over complex terrain, yet few studies have investigated how the orographic precipitation in a TC environment might respond to global warming. Here, we use large-eddy simulation to estimate the global warming–induced change in the precipitation near an idealized mountain (1 km maximum height) with pseudo global warming. Two regions exhibit enhanced precipitation, one over the mountain and the other in the downstream region 25–45 km away from the mountain. The enhanced precipitation in both regions is related to the seeder–feeder mechanism, although the enhancement in the downstream regions differs from the conventional definition and is referred to as the pseudo-seeder–feeder mechanism (PSF). In the PSF, mountain waves generate an intense cloud formation center in the midtroposphere above the lee slope, and the resulting hydrometeors drift downstream, intensifying downstream convection when they fall into proper locations. Under warming, the overmountain precipitation maximum exhibits minimal changes, while the downstream precipitation maximum exhibits a large sensitivity of 18% K−1. The small sensitivity of the first precipitation peak is due to the canceling effects of thermodynamic and dynamic changes. The large sensitivity in the downstream region is mainly due to the strengthening of the wave-induced midtroposphere cloud formation center, which supplies more hydrometeors to the downstream region and enhances precipitation efficiency through the enhanced PSF mechanism. However, the downstream precipitation sensitivity varies with mountain geometry. Higher mountain height enhances precipitation but lowers the sensitivity to warming.
Significance Statement
The combination of typhoon environment and orography can produce intense precipitation and thereby severe flooding risks. Here, we investigate the global warming response of orographic precipitation in a typhoon environment with idealized, high-resolution simulations. The experiments suggest that under warming, a precipitation maximum may emerge in the downstream region of a mountain or strengthen and shift upwind if it already exists in the current climate. This surprising amplification of downstream-region precipitation is related to the enhancement of the midtropospheric cloud generation caused by mountain waves and has critical implications for flooding risk management in mountainous regions.
Abstract
The intense and moist winds in a tropical cyclone (TC) environment can produce strong mountain waves and enhanced precipitation over complex terrain, yet few studies have investigated how the orographic precipitation in a TC environment might respond to global warming. Here, we use large-eddy simulation to estimate the global warming–induced change in the precipitation near an idealized mountain (1 km maximum height) with pseudo global warming. Two regions exhibit enhanced precipitation, one over the mountain and the other in the downstream region 25–45 km away from the mountain. The enhanced precipitation in both regions is related to the seeder–feeder mechanism, although the enhancement in the downstream regions differs from the conventional definition and is referred to as the pseudo-seeder–feeder mechanism (PSF). In the PSF, mountain waves generate an intense cloud formation center in the midtroposphere above the lee slope, and the resulting hydrometeors drift downstream, intensifying downstream convection when they fall into proper locations. Under warming, the overmountain precipitation maximum exhibits minimal changes, while the downstream precipitation maximum exhibits a large sensitivity of 18% K−1. The small sensitivity of the first precipitation peak is due to the canceling effects of thermodynamic and dynamic changes. The large sensitivity in the downstream region is mainly due to the strengthening of the wave-induced midtroposphere cloud formation center, which supplies more hydrometeors to the downstream region and enhances precipitation efficiency through the enhanced PSF mechanism. However, the downstream precipitation sensitivity varies with mountain geometry. Higher mountain height enhances precipitation but lowers the sensitivity to warming.
Significance Statement
The combination of typhoon environment and orography can produce intense precipitation and thereby severe flooding risks. Here, we investigate the global warming response of orographic precipitation in a typhoon environment with idealized, high-resolution simulations. The experiments suggest that under warming, a precipitation maximum may emerge in the downstream region of a mountain or strengthen and shift upwind if it already exists in the current climate. This surprising amplification of downstream-region precipitation is related to the enhancement of the midtropospheric cloud generation caused by mountain waves and has critical implications for flooding risk management in mountainous regions.
Abstract
This study examines the characteristics and phase evolution of the quasi-biweekly oscillation of surface sensible heating (SH) over the central-eastern Tibetan Plateau (CETP) during spring. The mechanism connecting CETP SH to spring rainfall in China on the quasi-biweekly time scale is further investigated. Results show that the dominant mode of quasi-biweekly CETP SH presents a monopole pattern, in which the peak leads the maximum of the quasi-biweekly rainfall in the middle and lower reaches of the Yangtze River (MLYR) and South China by approximately 5 and 7 days, respectively. As an upper-level Rossby wave train propagates eastward, an anomalous center of convergence moves to the CETP, which leads to a strong downdraft and reduced cloud cover. The resultant elevated shortwave radiation input and drier soil conditions are favorable for the CETP SH quasi-biweekly oscillation to enter a positive phase. When reaching its peak, the CETP SH efficiently heats the lower atmosphere, resulting in a local updraft. Due to the “SH-driven air pump” effect, abundant water vapor is transported from the oceans to China. A lower-layer southerly anomaly on the east side of the TP develops into an anomalous cyclonic circulation via the effect of topographic friction, which leads to the expansion of the positive potential vorticity anomaly and the maximum of the quasi-biweekly rainfall in the MLYR. Further southeastward propagation of the wave train leads to a shift in the rainfall anomaly center to South China. These findings suggest that the CETP monopole SH warming could be a good indicator for predicting intraseasonal variations in spring rainfall over China.
Abstract
This study examines the characteristics and phase evolution of the quasi-biweekly oscillation of surface sensible heating (SH) over the central-eastern Tibetan Plateau (CETP) during spring. The mechanism connecting CETP SH to spring rainfall in China on the quasi-biweekly time scale is further investigated. Results show that the dominant mode of quasi-biweekly CETP SH presents a monopole pattern, in which the peak leads the maximum of the quasi-biweekly rainfall in the middle and lower reaches of the Yangtze River (MLYR) and South China by approximately 5 and 7 days, respectively. As an upper-level Rossby wave train propagates eastward, an anomalous center of convergence moves to the CETP, which leads to a strong downdraft and reduced cloud cover. The resultant elevated shortwave radiation input and drier soil conditions are favorable for the CETP SH quasi-biweekly oscillation to enter a positive phase. When reaching its peak, the CETP SH efficiently heats the lower atmosphere, resulting in a local updraft. Due to the “SH-driven air pump” effect, abundant water vapor is transported from the oceans to China. A lower-layer southerly anomaly on the east side of the TP develops into an anomalous cyclonic circulation via the effect of topographic friction, which leads to the expansion of the positive potential vorticity anomaly and the maximum of the quasi-biweekly rainfall in the MLYR. Further southeastward propagation of the wave train leads to a shift in the rainfall anomaly center to South China. These findings suggest that the CETP monopole SH warming could be a good indicator for predicting intraseasonal variations in spring rainfall over China.
Abstract
Accurate representation of mesoscale scale convective systems (MCSs) in climate models is of vital importance to understanding global energy, water cycles, and extreme weather. In this study, we evaluate the simulated MCS features over the United States from the newly developed GFDL global high-resolution (∼50 km) AM4 model by comparing them with the observations during spring to early summer (April–June) and late summer (July–August). The results show that the spatial distribution and seasonality of occurrence and genesis frequency of MCSs are reasonably simulated over the central United States in both seasons. The model reliably reproduces the observed features of MCS duration, translation speed, and size over the central United States, as well as the favorable large-scale circulation pattern associated with MCS development over the central United States during spring and early summer. However, the model misrepresents the amplitude and the phase of the diurnal cycle of MCSs during both seasons. In addition, the spatial distribution of occurrence and genesis frequency of MCSs over the eastern United States is substantially overestimated, with larger biases in early spring and summer. Furthermore, while large-scale circulation patterns are reasonably simulated in spring and early summer, they are misrepresented in the model during summer. Finally, we examine MCS-related precipitation, finding that the model overestimates MCS-related precipitation during spring and early summer, but this bias is insufficient to explain the significant dry bias observed in total precipitation over the central United States. Nonetheless, the dry biases in MCS-associated precipitation during late summer likely contribute to the overall precipitation deficit in the model.
Abstract
Accurate representation of mesoscale scale convective systems (MCSs) in climate models is of vital importance to understanding global energy, water cycles, and extreme weather. In this study, we evaluate the simulated MCS features over the United States from the newly developed GFDL global high-resolution (∼50 km) AM4 model by comparing them with the observations during spring to early summer (April–June) and late summer (July–August). The results show that the spatial distribution and seasonality of occurrence and genesis frequency of MCSs are reasonably simulated over the central United States in both seasons. The model reliably reproduces the observed features of MCS duration, translation speed, and size over the central United States, as well as the favorable large-scale circulation pattern associated with MCS development over the central United States during spring and early summer. However, the model misrepresents the amplitude and the phase of the diurnal cycle of MCSs during both seasons. In addition, the spatial distribution of occurrence and genesis frequency of MCSs over the eastern United States is substantially overestimated, with larger biases in early spring and summer. Furthermore, while large-scale circulation patterns are reasonably simulated in spring and early summer, they are misrepresented in the model during summer. Finally, we examine MCS-related precipitation, finding that the model overestimates MCS-related precipitation during spring and early summer, but this bias is insufficient to explain the significant dry bias observed in total precipitation over the central United States. Nonetheless, the dry biases in MCS-associated precipitation during late summer likely contribute to the overall precipitation deficit in the model.
