Browse
Abstract
Supercell thunderstorms develop low-level rotation via tilting of environmental horizontal vorticity ( ω h ) by the updraft. This rotation induces dynamic lifting that can stretch near-surface vertical vorticity into a tornado. Low-level updraft rotation is generally thought to scale with 0–500 m storm-relative helicity (SRH): the combination of storm-relative flow, |SRF|, | ω h |, and cosϕ (where ϕ is the angle between SRF and ω h ). It is unclear how much influence each component of SRH has in intensifying the low-level mesocyclone. This study surveys these three components using self-organizing maps (SOMs) to distill 15 906 proximity soundings for observed right-moving supercells. Statistical analyses reveal the component most highly correlated to SRH and to streamwise vorticity (ωs ) in the observed profiles is | ω h |. Furthermore, | ω h | and |SRF| are themselves highly correlated due to their shared dependence on the hodograph length. The representative profiles produced by the SOMs were combined with a common thermodynamic profile to initialize quasi-realistic supercells in a cloud model. The simulations reveal that, across a range of real-world profiles, intense low-level mesocyclones are most closely linked to ω h and SRF, while the angle between them appears to be mostly inconsequential.
Significance Statement
About three-fourths of all tornadoes are produced by rotating thunderstorms (supercells). When the part of the storm near cloud base (approximately 1 km above the ground) rotates more strongly, the chance of a tornado dramatically increases. The goal of this study is to identify the simplest characteristic(s) of the environmental wind profile that can be used to forecast the likelihood of strong cloud-base rotation. This study concludes that the most important ingredients for storm rotation are the magnitudes of the horizontal vertical wind shear between the surface and 500 m and the storm inflow wind, irrespective of their relative directions. This finding may lead to improved operational identification of environments favoring tornado formation.
Abstract
Supercell thunderstorms develop low-level rotation via tilting of environmental horizontal vorticity ( ω h ) by the updraft. This rotation induces dynamic lifting that can stretch near-surface vertical vorticity into a tornado. Low-level updraft rotation is generally thought to scale with 0–500 m storm-relative helicity (SRH): the combination of storm-relative flow, |SRF|, | ω h |, and cosϕ (where ϕ is the angle between SRF and ω h ). It is unclear how much influence each component of SRH has in intensifying the low-level mesocyclone. This study surveys these three components using self-organizing maps (SOMs) to distill 15 906 proximity soundings for observed right-moving supercells. Statistical analyses reveal the component most highly correlated to SRH and to streamwise vorticity (ωs ) in the observed profiles is | ω h |. Furthermore, | ω h | and |SRF| are themselves highly correlated due to their shared dependence on the hodograph length. The representative profiles produced by the SOMs were combined with a common thermodynamic profile to initialize quasi-realistic supercells in a cloud model. The simulations reveal that, across a range of real-world profiles, intense low-level mesocyclones are most closely linked to ω h and SRF, while the angle between them appears to be mostly inconsequential.
Significance Statement
About three-fourths of all tornadoes are produced by rotating thunderstorms (supercells). When the part of the storm near cloud base (approximately 1 km above the ground) rotates more strongly, the chance of a tornado dramatically increases. The goal of this study is to identify the simplest characteristic(s) of the environmental wind profile that can be used to forecast the likelihood of strong cloud-base rotation. This study concludes that the most important ingredients for storm rotation are the magnitudes of the horizontal vertical wind shear between the surface and 500 m and the storm inflow wind, irrespective of their relative directions. This finding may lead to improved operational identification of environments favoring tornado formation.
Comparison of ADCP and ECCOv4r4 Currents in the Pacific Equatorial UndercurrentAbstract
The Pacific Equatorial Undercurrent (EUC) flows eastward across the Pacific at the equator in the thermocline. Its variability is related to El Niño. Moored acoustic Doppler current profiler (ADCP) measurements recorded at four widely separated sites along the equator in the EUC were compared to currents generated by version 4 release 4 of the Estimating the Circulation and Climate of the Ocean (ECCOv4r4) global model–data synthesis product. We are interested to learn how well ECCOv4r4 currents could complement sparse in situ current measurements. ADCP measurements were not assimilated in ECCOv4r4. Comparisons occurred at 5-m depth intervals at 165°E, 170°W, 140°W, and 110°W over time intervals of 10–14 years from 1995 to 2010. Hourly values of ECCOv4r4 and ADCP EUC core speeds were strongly correlated, similar for the EUC transport per unit width (TPUW). Correlations were substantially weaker at 110°W. Although we expected means and standard deviations of ECCOv4r4 currents to be smaller than ADCP values because of ECCOv4r4’s grid representation error, the large differences were unforeseen. The appearance of ECCOv4r4 diurnal-period current oscillations was surprising. As the EUC moved eastward from 170° to 140°W, the ECCOv4r4 TPUW exhibited a much smaller increase compared to the ADCP TPUW. A consequence of smaller ECCOv4r4 EUC core speeds was significantly fewer instances of gradient Richardson number (Ri) less than 1/4 above and below the depth of the core speed compared to Ri computed with ADCP observations. We present linear regression analyses to use monthly-mean ECCOv4r4 EUC core speeds and TPUWs as proxies for ADCP measurements.
Significance Statement
Hundreds of scientific papers have used ECCO data products generated with a continually evolving state-of-the-art ocean-model–data synthesis system. We ask, How representative is the latest version of ECCO equatorial ocean currents? We use independent in situ current measurements as the reference dataset to establish the accuracy of ECCO currents in the tropical Pacific. Attention is focused on the Pacific Equatorial Undercurrent (EUC) because it contributes to the formation of El Niño and La Niña events. ECCO EUC core speeds were smaller in magnitude and less variable in time compared to observations. As a consequence, ECCO currents generated smaller vertical mixing in the EUC compared to that inferred from current measurements. We developed a linear regression model to improve representation of monthly-mean ECCO currents.
Abstract
The Pacific Equatorial Undercurrent (EUC) flows eastward across the Pacific at the equator in the thermocline. Its variability is related to El Niño. Moored acoustic Doppler current profiler (ADCP) measurements recorded at four widely separated sites along the equator in the EUC were compared to currents generated by version 4 release 4 of the Estimating the Circulation and Climate of the Ocean (ECCOv4r4) global model–data synthesis product. We are interested to learn how well ECCOv4r4 currents could complement sparse in situ current measurements. ADCP measurements were not assimilated in ECCOv4r4. Comparisons occurred at 5-m depth intervals at 165°E, 170°W, 140°W, and 110°W over time intervals of 10–14 years from 1995 to 2010. Hourly values of ECCOv4r4 and ADCP EUC core speeds were strongly correlated, similar for the EUC transport per unit width (TPUW). Correlations were substantially weaker at 110°W. Although we expected means and standard deviations of ECCOv4r4 currents to be smaller than ADCP values because of ECCOv4r4’s grid representation error, the large differences were unforeseen. The appearance of ECCOv4r4 diurnal-period current oscillations was surprising. As the EUC moved eastward from 170° to 140°W, the ECCOv4r4 TPUW exhibited a much smaller increase compared to the ADCP TPUW. A consequence of smaller ECCOv4r4 EUC core speeds was significantly fewer instances of gradient Richardson number (Ri) less than 1/4 above and below the depth of the core speed compared to Ri computed with ADCP observations. We present linear regression analyses to use monthly-mean ECCOv4r4 EUC core speeds and TPUWs as proxies for ADCP measurements.
Significance Statement
Hundreds of scientific papers have used ECCO data products generated with a continually evolving state-of-the-art ocean-model–data synthesis system. We ask, How representative is the latest version of ECCO equatorial ocean currents? We use independent in situ current measurements as the reference dataset to establish the accuracy of ECCO currents in the tropical Pacific. Attention is focused on the Pacific Equatorial Undercurrent (EUC) because it contributes to the formation of El Niño and La Niña events. ECCO EUC core speeds were smaller in magnitude and less variable in time compared to observations. As a consequence, ECCO currents generated smaller vertical mixing in the EUC compared to that inferred from current measurements. We developed a linear regression model to improve representation of monthly-mean ECCO currents.
Abstract
The influence of meridional shift of the oceanic subtropical front (STF) on the Agulhas Current (AC) regime shifts is studied using satellite altimeter data and a 1.5-layer ocean model. The satellite observations suggest the northward shift of the STF leads to the AC leaping across the gap with little Agulhas leakage, and the southward shift of the STF mainly results in the AC intruding into the Atlantic Ocean in the forms of a loop current and an eddy-shedding path, while there are three flow patterns of AC for moderate latitude of the STF. The ocean model results suggest no hysteresis (associated with multiple equilibrium states) exists in the AC system. The model reproduces similar AC regimes depending on different gap widths as in the observations, and model results can be used to explain the observed Agulhas leakage well. We also present the parameter space of the critical AC strength that results in different AC flow patterns as a function of the gap width. The vorticity dynamics of the AC regime shift suggests that the β term is mainly balanced by the viscosity term for the AC in the leaping and loop current paths, while the β and instantaneous vorticity terms are mainly balanced by the advection and viscosity terms for the AC in the eddy-shedding path. These findings help explain the dynamics of the AC flowing across the gateway beyond the tip of Africa affected by the north–south shift of the STF in the leaping regime or penetrating regime.
Abstract
The influence of meridional shift of the oceanic subtropical front (STF) on the Agulhas Current (AC) regime shifts is studied using satellite altimeter data and a 1.5-layer ocean model. The satellite observations suggest the northward shift of the STF leads to the AC leaping across the gap with little Agulhas leakage, and the southward shift of the STF mainly results in the AC intruding into the Atlantic Ocean in the forms of a loop current and an eddy-shedding path, while there are three flow patterns of AC for moderate latitude of the STF. The ocean model results suggest no hysteresis (associated with multiple equilibrium states) exists in the AC system. The model reproduces similar AC regimes depending on different gap widths as in the observations, and model results can be used to explain the observed Agulhas leakage well. We also present the parameter space of the critical AC strength that results in different AC flow patterns as a function of the gap width. The vorticity dynamics of the AC regime shift suggests that the β term is mainly balanced by the viscosity term for the AC in the leaping and loop current paths, while the β and instantaneous vorticity terms are mainly balanced by the advection and viscosity terms for the AC in the eddy-shedding path. These findings help explain the dynamics of the AC flowing across the gateway beyond the tip of Africa affected by the north–south shift of the STF in the leaping regime or penetrating regime.
Abstract
Measurements from the South Dakota School of Mines and Technology T-28 hail-penetrating aircraft are analyzed using recently developed data processing techniques with the goals of identifying where the large hail is found relative to vertical motion and improving the detection of hail microphysical properties from radar. Hail particle size distributions (PSD) and environmental conditions (temperature, relative humidity, liquid water content, air vertical velocity) were digitally collected by the T28 between 1995 and 2003 and synthesized by Detwiler et al. The PSD were forward modeled by Cecchini et al. to simulate the radar reflectivity of the PSD at multiple radar wavelengths. The T-28 penetrated temperatures primarily between 0° and −10°C. The largest hailstones were sampled near the updraft/downdraft interface. Liquid water contents were highest in the updraft cores, whereas total (liquid + frozen) water contents were highest near the updraft/downdraft interface. The fitted properties of the PSD (intercept and slope) are directly related to each other but do not show any dependence on the region of the hailstorm where sampled. The PSD measurements and the radar reflectivity calculations at multiple radar wavelengths facilitated the development of relationships between the PSD bulk properties—hail kinetic energy and kinetic energy flux—and the radar reflectivity. Rather than using the oft-assumed sphericity and solid ice physical properties, actual measurements of hail properties are used in the analysis. Results from the maximum estimated size of hail (MESH) and vertical integrated liquid water (VIL) algorithms are evaluated based on this analysis.
Significance Statement
Hailstorms in the United States have caused over $10 billion in damage for each of the last 14 years, according to insurance industry estimates (). Algorithms have been developed to identify the presence and size of hail from radar. Numerical simulations of hailstorms have improved significantly since the 1970s, and further improvements will provide better resolution and more accurate estimates of the sizes of hailstones falling to the ground. Measurements of the properties of hailstones—their mass and terminal velocities—have been improved in recent years but in general are not incorporated in the algorithms developed for radar estimates of hail sizes or for the properties of hail used in the model simulations. This study synthesizes in situ aircraft data, computed radar backscatter cross sections, together with recent estimates of the physical characteristics of hailstones to improve the representation of hail in numerical models and quantitative assessment hail properties in storms using weather radar.
Abstract
Measurements from the South Dakota School of Mines and Technology T-28 hail-penetrating aircraft are analyzed using recently developed data processing techniques with the goals of identifying where the large hail is found relative to vertical motion and improving the detection of hail microphysical properties from radar. Hail particle size distributions (PSD) and environmental conditions (temperature, relative humidity, liquid water content, air vertical velocity) were digitally collected by the T28 between 1995 and 2003 and synthesized by Detwiler et al. The PSD were forward modeled by Cecchini et al. to simulate the radar reflectivity of the PSD at multiple radar wavelengths. The T-28 penetrated temperatures primarily between 0° and −10°C. The largest hailstones were sampled near the updraft/downdraft interface. Liquid water contents were highest in the updraft cores, whereas total (liquid + frozen) water contents were highest near the updraft/downdraft interface. The fitted properties of the PSD (intercept and slope) are directly related to each other but do not show any dependence on the region of the hailstorm where sampled. The PSD measurements and the radar reflectivity calculations at multiple radar wavelengths facilitated the development of relationships between the PSD bulk properties—hail kinetic energy and kinetic energy flux—and the radar reflectivity. Rather than using the oft-assumed sphericity and solid ice physical properties, actual measurements of hail properties are used in the analysis. Results from the maximum estimated size of hail (MESH) and vertical integrated liquid water (VIL) algorithms are evaluated based on this analysis.
Significance Statement
Hailstorms in the United States have caused over $10 billion in damage for each of the last 14 years, according to insurance industry estimates (). Algorithms have been developed to identify the presence and size of hail from radar. Numerical simulations of hailstorms have improved significantly since the 1970s, and further improvements will provide better resolution and more accurate estimates of the sizes of hailstones falling to the ground. Measurements of the properties of hailstones—their mass and terminal velocities—have been improved in recent years but in general are not incorporated in the algorithms developed for radar estimates of hail sizes or for the properties of hail used in the model simulations. This study synthesizes in situ aircraft data, computed radar backscatter cross sections, together with recent estimates of the physical characteristics of hailstones to improve the representation of hail in numerical models and quantitative assessment hail properties in storms using weather radar.
Abstract
We use a simple risk model for U.S. hurricane wind and surge economic damage to investigate the impact of projected changes in the frequencies of hurricanes of different intensities due to climate change. For average annual damage, we find that changes in the frequency of category-4 storms dominate. For distributions of annual damage, we find that changes in the frequency of category-4 storms again dominate for all except the shortest return periods. Sensitivity tests show that accounting for landfall, uncertainties, and correlations leads to increases in damage estimates. When we propagate the distributions of uncertain frequency changes to give a best estimate of the changes in damage, the changes are moderate. When we pick individual scenarios from within the distributions of frequency changes, we find a significant probability of much larger changes in damage. The inputs on which our study depends are highly uncertain, and our methods are approximate, leading to high levels of uncertainty in our results. Also, the damage changes we consider are only part of the total possible change in hurricane damage due to climate change. Total damage change estimates would also need to include changes due to other factors, including possible changes in genesis, tracks, size, forward speed, sea level, rainfall, and exposure. Nevertheless, we believe that our results give important new insights into U.S. hurricane risk under climate change.
Significance Statement
We investigate how changes in the frequencies of hurricanes of different intensities as a result of climate change may contribute to changes in U.S. economic damage due to wind and surge. We find that economic damage will likely increase as a result of projected increases in the frequency of landfalling hurricanes. Analysis of our results shows that increases in the frequency of category-4 storms are the main driver of the changes. Our best estimate results, based on a multimodel ensemble, give modest increases in damage, but within the ensemble there are individual scenarios that give much larger increases in damage. The large range of individual damage estimates is a motivation for continuing efforts to reduce the uncertainty around hurricane projections under climate change.
Abstract
We use a simple risk model for U.S. hurricane wind and surge economic damage to investigate the impact of projected changes in the frequencies of hurricanes of different intensities due to climate change. For average annual damage, we find that changes in the frequency of category-4 storms dominate. For distributions of annual damage, we find that changes in the frequency of category-4 storms again dominate for all except the shortest return periods. Sensitivity tests show that accounting for landfall, uncertainties, and correlations leads to increases in damage estimates. When we propagate the distributions of uncertain frequency changes to give a best estimate of the changes in damage, the changes are moderate. When we pick individual scenarios from within the distributions of frequency changes, we find a significant probability of much larger changes in damage. The inputs on which our study depends are highly uncertain, and our methods are approximate, leading to high levels of uncertainty in our results. Also, the damage changes we consider are only part of the total possible change in hurricane damage due to climate change. Total damage change estimates would also need to include changes due to other factors, including possible changes in genesis, tracks, size, forward speed, sea level, rainfall, and exposure. Nevertheless, we believe that our results give important new insights into U.S. hurricane risk under climate change.
Significance Statement
We investigate how changes in the frequencies of hurricanes of different intensities as a result of climate change may contribute to changes in U.S. economic damage due to wind and surge. We find that economic damage will likely increase as a result of projected increases in the frequency of landfalling hurricanes. Analysis of our results shows that increases in the frequency of category-4 storms are the main driver of the changes. Our best estimate results, based on a multimodel ensemble, give modest increases in damage, but within the ensemble there are individual scenarios that give much larger increases in damage. The large range of individual damage estimates is a motivation for continuing efforts to reduce the uncertainty around hurricane projections under climate change.
Abstract
Streamwise vorticity currents (SVCs) have been hypothesized to enhance low-level mesocyclones within supercell thunderstorms and perhaps increase the likelihood of tornadogenesis. Recent observational studies have confirmed the existence of SVCs in supercells and numerical simulations have allowed for further investigation of SVCs. A suite of 19 idealized supercell simulations with varying midlevel shear orientations is analyzed to determine how SVC formation and characteristics may differ between storms. In our simulations, SVCs develop on the cold side of left-flank convergence boundaries and their updraft-relative positions are partially dependent on downdraft location. The magnitude, duration, and mean depth of SVCs do not differ significantly between simulations or between SVCs that precede tornado-like vortices (TLVs) and those that do not. Trajectories initialized within SVCs reveal two primary airstreams, one that flows through an SVC for the majority of its length, and another that originates in the modified inflow in the forward flank and then merges with the SVC. Vorticity budgets calculated along trajectories reveal that the first airstream exhibits significantly greater maximum streamwise vorticity magnitudes than the second airstream. The vorticity budgets also indicate that stretching of horizontal streamwise vorticity is the dominant contributor to the large values of streamwise vorticity within the SVCs. TLV formation does not require the development of an SVC beforehand; 44% of TLVs in the simulations are preceded by SVCs. When an SVC occurs, it is followed by a TLV 53% of the time, indicating not all SVCs lead to TLV formation.
Significance Statement
Streamwise vorticity currents (SVCs) are features within thunderstorms hypothesized to strengthen updraft rotation and increase the likelihood of tornado formation. SVCs in a suite of 19 thunderstorm simulations are analyzed to investigate how they develop, if their characteristics differ between storms, and how often they precede tornado production. The rotation in an SVC is amplified as air accelerates toward the updraft, which is the main process contributing to SVC formation. The likelihood of SVCs may vary with differences in the winds 3–6 km above the ground. These findings may aid in developing strategies for better observing SVCs.
Abstract
Streamwise vorticity currents (SVCs) have been hypothesized to enhance low-level mesocyclones within supercell thunderstorms and perhaps increase the likelihood of tornadogenesis. Recent observational studies have confirmed the existence of SVCs in supercells and numerical simulations have allowed for further investigation of SVCs. A suite of 19 idealized supercell simulations with varying midlevel shear orientations is analyzed to determine how SVC formation and characteristics may differ between storms. In our simulations, SVCs develop on the cold side of left-flank convergence boundaries and their updraft-relative positions are partially dependent on downdraft location. The magnitude, duration, and mean depth of SVCs do not differ significantly between simulations or between SVCs that precede tornado-like vortices (TLVs) and those that do not. Trajectories initialized within SVCs reveal two primary airstreams, one that flows through an SVC for the majority of its length, and another that originates in the modified inflow in the forward flank and then merges with the SVC. Vorticity budgets calculated along trajectories reveal that the first airstream exhibits significantly greater maximum streamwise vorticity magnitudes than the second airstream. The vorticity budgets also indicate that stretching of horizontal streamwise vorticity is the dominant contributor to the large values of streamwise vorticity within the SVCs. TLV formation does not require the development of an SVC beforehand; 44% of TLVs in the simulations are preceded by SVCs. When an SVC occurs, it is followed by a TLV 53% of the time, indicating not all SVCs lead to TLV formation.
Significance Statement
Streamwise vorticity currents (SVCs) are features within thunderstorms hypothesized to strengthen updraft rotation and increase the likelihood of tornado formation. SVCs in a suite of 19 thunderstorm simulations are analyzed to investigate how they develop, if their characteristics differ between storms, and how often they precede tornado production. The rotation in an SVC is amplified as air accelerates toward the updraft, which is the main process contributing to SVC formation. The likelihood of SVCs may vary with differences in the winds 3–6 km above the ground. These findings may aid in developing strategies for better observing SVCs.
Abstract
Doppler-lidar wind-profile measurements at three sites were used to evaluate NWP model errors from two versions of NOAA’s 3-km-grid HRRR model, to see whether updates in the latest version 4 reduced errors when compared against the original version 1. Nested (750-m grid) versions of each were also tested to see how grid spacing affected forecast skill. The measurements were part of the field phase of the Second Wind Forecasting Improvement Project (WFIP2), an 18-month deployment into central Oregon–Washington, a major wind-energy-producing region. This study focuses on errors in simulating marine intrusions, a summertime, 600–800-m-deep, regional sea-breeze flow found to generate large errors. HRRR errors proved to be complex and site dependent. The most prominent error resulted from a premature drop in modeled marine-intrusion wind speeds after local midnight, when lidar-measured winds of greater than 8 m s−1 persisted through the next morning. These large negative errors were offset at low levels by positive errors due to excessive mixing, complicating the interpretation of model “improvement,” such that the updates to the full-scale versions produced mixed results, sometimes enhancing but sometimes degrading model skill. Nesting consistently improved model performance, with version 1’s nest producing the smallest errors overall. HRRR’s ability to represent the stages of sea-breeze forcing was evaluated using radiation budget, surface-energy balance, and near-surface temperature measurements available during WFIP2. The significant site-to-site differences in model error and the complex nature of these errors mean that field-measurement campaigns having dense arrays of profiling sensors are necessary to properly diagnose and characterize model errors, as part of a systematic approach to NWP model improvement.
Significance Statement
Dramatic increases in NWP model skill will be required over the coming decades. This paper describes the role of major deployments of accurate profiling sensors in achieving that goal and presents an example from the Second Wind Forecast Improvement Program (WFIP2). Wind-profile data from scanning Doppler lidars were used to evaluate two versions of HRRR, the original and an updated version, and nested versions of each. This study focuses on the ability of updated HRRR versions to improve upon predicting a regional sea-breeze flow, which was found to generate large errors by the original HRRR. Updates to the full-scale HRRR versions produced mixed results, but the finer-mesh versions consistently reduced model errors.
Abstract
Doppler-lidar wind-profile measurements at three sites were used to evaluate NWP model errors from two versions of NOAA’s 3-km-grid HRRR model, to see whether updates in the latest version 4 reduced errors when compared against the original version 1. Nested (750-m grid) versions of each were also tested to see how grid spacing affected forecast skill. The measurements were part of the field phase of the Second Wind Forecasting Improvement Project (WFIP2), an 18-month deployment into central Oregon–Washington, a major wind-energy-producing region. This study focuses on errors in simulating marine intrusions, a summertime, 600–800-m-deep, regional sea-breeze flow found to generate large errors. HRRR errors proved to be complex and site dependent. The most prominent error resulted from a premature drop in modeled marine-intrusion wind speeds after local midnight, when lidar-measured winds of greater than 8 m s−1 persisted through the next morning. These large negative errors were offset at low levels by positive errors due to excessive mixing, complicating the interpretation of model “improvement,” such that the updates to the full-scale versions produced mixed results, sometimes enhancing but sometimes degrading model skill. Nesting consistently improved model performance, with version 1’s nest producing the smallest errors overall. HRRR’s ability to represent the stages of sea-breeze forcing was evaluated using radiation budget, surface-energy balance, and near-surface temperature measurements available during WFIP2. The significant site-to-site differences in model error and the complex nature of these errors mean that field-measurement campaigns having dense arrays of profiling sensors are necessary to properly diagnose and characterize model errors, as part of a systematic approach to NWP model improvement.
Significance Statement
Dramatic increases in NWP model skill will be required over the coming decades. This paper describes the role of major deployments of accurate profiling sensors in achieving that goal and presents an example from the Second Wind Forecast Improvement Program (WFIP2). Wind-profile data from scanning Doppler lidars were used to evaluate two versions of HRRR, the original and an updated version, and nested versions of each. This study focuses on the ability of updated HRRR versions to improve upon predicting a regional sea-breeze flow, which was found to generate large errors by the original HRRR. Updates to the full-scale HRRR versions produced mixed results, but the finer-mesh versions consistently reduced model errors.
Abstract
Air–sea coupling system in the southwestern Indian Ocean (SWIO; 35°–55°S, 40°–75°E) exhibits predominant multidecadal variability that is the strongest during austral summer. It is characterized by an equivalent barotropic atmospheric high (low) pressure over warm (cold) sea surface temperature (SST) anomalies and a poleward (equatorward) shift of the westerlies during the positive (negative) phase. In this study, physical processes of this multidecadal variability are investigated by using observations/reanalysis and CMIP6 model simulations. Results suggest that the multidecadal fluctuation can be explained by the modulation of the Atlantic meridional overturning circulation (AMOC) and the local air–sea positive feedback in the SWIO. In both observations/reanalysis and CMIP6 model simulations, the AMOC fluctuation presents a significantly negative correlation with the multidecadal SST variation in the SWIO when the AMOC is leading by about a decade. The mechanisms are that the preceding AMOC variation can cause an interhemispheric dipolar pattern of SST anomalies in the Atlantic Ocean. Subsequently, the SST anomalies in the midlatitudes of the South Atlantic can propagate to the SWIO by the oceanic Rossby wave under the influence of the Antarctic Circumpolar Current (ACC). Once the SST anomalies reach the SWIO, these SST anomalies in the oceanic front can affect the baroclinicity in the lower troposphere to influence the synoptic transient eddy and then cause the atmospheric circulation anomaly via the eddy–mean flow interaction. Subsequently, the anomalous atmospheric circulation over the SWIO can significantly strengthen the SST anomalies through modifying the oceanic meridional temperature advection and latent and sensible heat flux.
Abstract
Air–sea coupling system in the southwestern Indian Ocean (SWIO; 35°–55°S, 40°–75°E) exhibits predominant multidecadal variability that is the strongest during austral summer. It is characterized by an equivalent barotropic atmospheric high (low) pressure over warm (cold) sea surface temperature (SST) anomalies and a poleward (equatorward) shift of the westerlies during the positive (negative) phase. In this study, physical processes of this multidecadal variability are investigated by using observations/reanalysis and CMIP6 model simulations. Results suggest that the multidecadal fluctuation can be explained by the modulation of the Atlantic meridional overturning circulation (AMOC) and the local air–sea positive feedback in the SWIO. In both observations/reanalysis and CMIP6 model simulations, the AMOC fluctuation presents a significantly negative correlation with the multidecadal SST variation in the SWIO when the AMOC is leading by about a decade. The mechanisms are that the preceding AMOC variation can cause an interhemispheric dipolar pattern of SST anomalies in the Atlantic Ocean. Subsequently, the SST anomalies in the midlatitudes of the South Atlantic can propagate to the SWIO by the oceanic Rossby wave under the influence of the Antarctic Circumpolar Current (ACC). Once the SST anomalies reach the SWIO, these SST anomalies in the oceanic front can affect the baroclinicity in the lower troposphere to influence the synoptic transient eddy and then cause the atmospheric circulation anomaly via the eddy–mean flow interaction. Subsequently, the anomalous atmospheric circulation over the SWIO can significantly strengthen the SST anomalies through modifying the oceanic meridional temperature advection and latent and sensible heat flux.
Abstract
Recurving tropical cyclones (TCs) in the western North Pacific often cause heavy rainfall events (HREs) in East Asia. However, how their interactions with midlatitude flows alter the characteristics of HREs remains unclear. The present study examines the synoptic–dynamic characteristics of HREs directly resulting from TCs in South Korea with a focus on the role of midlatitude baroclinic condition. The HREs are categorized into two clusters based on midlatitude tropopause patterns: strongly (C1) and weakly (C2) baroclinic conditions. C1, which is common in late summer, is characterized by a well-defined trough–ridge couplet and jet streak at the tropopause. As TCs approach, the trough–ridge couplet amplifies, but is anchored by divergent TC outflow. This leads to phase locking of the upstream trough with TCs and thereby prompts substantial structural changes of TCs reminiscent of extratropical transition. The synergistic TC–midlatitude flow interactions allow for widely enhanced quasigeostrophic forcing for ascent to the north of the TC center. This allows HREs to occur even before TC landfall with more inland rainfall than C2 HREs. In contrast, C2, which is mainly observed in midsummer, does not accompany the undulating tropopause. In the absence of strong interactions with midlatitude flows, TCs rapidly dissipate after HREs while maintaining their tropical features. The upward motion is confined to the inherent TC convection, and thus HREs occur only when TCs are located in the vicinity of the country. These findings suggest that midlatitude baroclinic condition determines the spatial extent of TC rainfall and the timing of TC-induced HREs in South Korea.
Significance Statement
This study suggests that the midlatitude flows can substantially modulate heavy rainfall events directly caused by tropical cyclones. By analyzing the 42-yr tropical cyclone–induced heavy rainfall events in South Korea, it is found that tropical cyclones and midlatitude flows strongly interact with each other, especially when the midlatitude flows meander in conjunction with a strong jet stream. Their synergistic interactions result in a poleward expansion of the tropical cyclones’ precipitation shields, leading to heavy rainfall events even before they make landfall in the country. Consequently, it is advisable to carefully monitor the midlatitude conditions as well as tropical cyclones themselves as earlier heavy rainfall warnings may be necessary depending on the former.
Abstract
Recurving tropical cyclones (TCs) in the western North Pacific often cause heavy rainfall events (HREs) in East Asia. However, how their interactions with midlatitude flows alter the characteristics of HREs remains unclear. The present study examines the synoptic–dynamic characteristics of HREs directly resulting from TCs in South Korea with a focus on the role of midlatitude baroclinic condition. The HREs are categorized into two clusters based on midlatitude tropopause patterns: strongly (C1) and weakly (C2) baroclinic conditions. C1, which is common in late summer, is characterized by a well-defined trough–ridge couplet and jet streak at the tropopause. As TCs approach, the trough–ridge couplet amplifies, but is anchored by divergent TC outflow. This leads to phase locking of the upstream trough with TCs and thereby prompts substantial structural changes of TCs reminiscent of extratropical transition. The synergistic TC–midlatitude flow interactions allow for widely enhanced quasigeostrophic forcing for ascent to the north of the TC center. This allows HREs to occur even before TC landfall with more inland rainfall than C2 HREs. In contrast, C2, which is mainly observed in midsummer, does not accompany the undulating tropopause. In the absence of strong interactions with midlatitude flows, TCs rapidly dissipate after HREs while maintaining their tropical features. The upward motion is confined to the inherent TC convection, and thus HREs occur only when TCs are located in the vicinity of the country. These findings suggest that midlatitude baroclinic condition determines the spatial extent of TC rainfall and the timing of TC-induced HREs in South Korea.
Significance Statement
This study suggests that the midlatitude flows can substantially modulate heavy rainfall events directly caused by tropical cyclones. By analyzing the 42-yr tropical cyclone–induced heavy rainfall events in South Korea, it is found that tropical cyclones and midlatitude flows strongly interact with each other, especially when the midlatitude flows meander in conjunction with a strong jet stream. Their synergistic interactions result in a poleward expansion of the tropical cyclones’ precipitation shields, leading to heavy rainfall events even before they make landfall in the country. Consequently, it is advisable to carefully monitor the midlatitude conditions as well as tropical cyclones themselves as earlier heavy rainfall warnings may be necessary depending on the former.
Abstract
Radiative feedbacks over interannual time scales can be potentially useful for global warming estimation. However, the diversity of the lead–lag relationships in global mean surface temperature (GMST) and net radiation flux at the top of the atmosphere (GMTOA) create uncertainty during the estimation of radiative feedbacks. In this study, key physical processes controlling lead–lag relationships were elucidated by categorizing preindustrial control simulations of CMIP6 into three groups based on cross correlation values of GMTOA against GMST at lag 0 and lag +1 year. The diversity in the lead–lag relationships was primarily caused by the climatological state difference of the atmosphere over the equatorial Pacific, which modulated the strength of convective activity and sensitivity of low-level clouds. Diminished atmospheric stability caused enhanced convective activity, more efficient energy release, and smaller lags. In addition, enhanced stability in the lower atmosphere rendered the low-level clouds more sensitive to sea surface temperature changes and considerably delayed the radiative response. The climatological state difference of the atmosphere resulted from model-inherent atmospheric conditions. These findings suggest that the diversity of lead–lag relationships of GMST and GMTOA over interannual time scales could represent the characteristics of general atmospheric circulation models and possible solutions of the actual atmosphere, which could also affect long-term feedback features.
Abstract
Radiative feedbacks over interannual time scales can be potentially useful for global warming estimation. However, the diversity of the lead–lag relationships in global mean surface temperature (GMST) and net radiation flux at the top of the atmosphere (GMTOA) create uncertainty during the estimation of radiative feedbacks. In this study, key physical processes controlling lead–lag relationships were elucidated by categorizing preindustrial control simulations of CMIP6 into three groups based on cross correlation values of GMTOA against GMST at lag 0 and lag +1 year. The diversity in the lead–lag relationships was primarily caused by the climatological state difference of the atmosphere over the equatorial Pacific, which modulated the strength of convective activity and sensitivity of low-level clouds. Diminished atmospheric stability caused enhanced convective activity, more efficient energy release, and smaller lags. In addition, enhanced stability in the lower atmosphere rendered the low-level clouds more sensitive to sea surface temperature changes and considerably delayed the radiative response. The climatological state difference of the atmosphere resulted from model-inherent atmospheric conditions. These findings suggest that the diversity of lead–lag relationships of GMST and GMTOA over interannual time scales could represent the characteristics of general atmospheric circulation models and possible solutions of the actual atmosphere, which could also affect long-term feedback features.
