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Abstract
The ability of six CMIP6 models to reproduce the observed cold season teleconnection between tropical Indo-Pacific sea surface temperatures (SSTs) and precipitation in Southwest Asia, the coastal Middle East (CME), and northern Pakistan and India (NPI) is examined. The 1979–2014 period is analyzed to maximize observations over both the tropical ocean and the regions. Nine historical simulations for the same period are examined for each model to account for the internal variability of the coupled system. The teleconnection is examined in terms of SSTs, precipitation, 200-hPa geopotential heights, and derived quantities. All the models capture some of the broadest features of the teleconnections, but there is a wide range in the ability of the models to reproduce the magnitude and details. The differences appear related to both the models’ ability to capture the details of the tropical variability, including the position and strength of the precipitation anomalies in the Indo-west Pacific, and the models’ ability to accurately propagate the tropically forced response into the region. The teleconnections to the CME and NPI regions on the eastern and western margins, respectively, of the strongest signal are very similar in structure and have similar results, except that the models’ ability to reproduce the strength and details of the teleconnection is even more limited, consistent with their marginal locations and known influence of other modes of variability. For all three areas, the wide range in model ability to capture the leading teleconnection suggests caution in interpreting climate regional projections.
Abstract
The ability of six CMIP6 models to reproduce the observed cold season teleconnection between tropical Indo-Pacific sea surface temperatures (SSTs) and precipitation in Southwest Asia, the coastal Middle East (CME), and northern Pakistan and India (NPI) is examined. The 1979–2014 period is analyzed to maximize observations over both the tropical ocean and the regions. Nine historical simulations for the same period are examined for each model to account for the internal variability of the coupled system. The teleconnection is examined in terms of SSTs, precipitation, 200-hPa geopotential heights, and derived quantities. All the models capture some of the broadest features of the teleconnections, but there is a wide range in the ability of the models to reproduce the magnitude and details. The differences appear related to both the models’ ability to capture the details of the tropical variability, including the position and strength of the precipitation anomalies in the Indo-west Pacific, and the models’ ability to accurately propagate the tropically forced response into the region. The teleconnections to the CME and NPI regions on the eastern and western margins, respectively, of the strongest signal are very similar in structure and have similar results, except that the models’ ability to reproduce the strength and details of the teleconnection is even more limited, consistent with their marginal locations and known influence of other modes of variability. For all three areas, the wide range in model ability to capture the leading teleconnection suggests caution in interpreting climate regional projections.
Abstract
The links between daily ozone levels in Southern California and atmospheric circulation at regional and large scales are examined for July–September 1994–2001. The monitoring station in Pasadena is used as the primary basis for ozone analysis; comparison with other stations validates its representativeness for Southern California. Comparing the 10% of highest-ozone days with the 10% of lowest-ozone days for Pasadena reveals a large regional difference in 700-hPa vertical velocity over Southern California, consistent with changes to the ventilation and depth of the boundary layer. Analysis of the associated changes in midlevel (500 hPa) circulation reveals near-continental-scale differences, with very large modifications in the strength and position of the North American anticyclone. These links between daily ozone levels and regional and large-scale atmospheric circulation features suggest the potential for using currently available medium-range weather forecasts in ozone prediction.
Abstract
The links between daily ozone levels in Southern California and atmospheric circulation at regional and large scales are examined for July–September 1994–2001. The monitoring station in Pasadena is used as the primary basis for ozone analysis; comparison with other stations validates its representativeness for Southern California. Comparing the 10% of highest-ozone days with the 10% of lowest-ozone days for Pasadena reveals a large regional difference in 700-hPa vertical velocity over Southern California, consistent with changes to the ventilation and depth of the boundary layer. Analysis of the associated changes in midlevel (500 hPa) circulation reveals near-continental-scale differences, with very large modifications in the strength and position of the North American anticyclone. These links between daily ozone levels and regional and large-scale atmospheric circulation features suggest the potential for using currently available medium-range weather forecasts in ozone prediction.
Abstract
Hydrometeorological links to high streamflow events (HSFEs), 1950–2014, for the Mystic and Charles watersheds in the Metro Boston region of Massachusetts are examined. HSFEs are defined as one or more continuous days of streamflow above the mean annual maxima for a selected gauge in each basin. There are notable differences in the HSFEs for these two basins. HSFEs last from 1 to 3 days in the Mystic basin, while HSFEs for the Charles can last from 3 to 9 days. The majority of Mystic HSFEs are immediately preceded by extreme precipitation (occurring within 24 h), while only half of those for the Charles are preceded by extreme precipitation (in this case occurring 2–5 days earlier). While extreme precipitation events are often linked to HSFEs, other factors are often necessary in generating high streamflow, particularly for the Charles, as more than 50% of HSFEs occur at times when streamflow, soil moisture, and total precipitation are statistically above average for a period of at least 2 weeks before the HSFE. Approximately 52% and 80% of HSFEs occur from February to June for the Mystic and Charles, respectively, and these HSFEs are frequently linked to the passage of strong coastal lows, which produce extreme precipitation in the form of both rain and snow. For these coastal lows, Mystic HSFEs are linked to a strong moisture feed along the Massachusetts coastline and intense precipitation, while Charles HSFEs are linked to strong cyclones located off the Mid-Atlantic and longer-duration precipitation.
Abstract
Hydrometeorological links to high streamflow events (HSFEs), 1950–2014, for the Mystic and Charles watersheds in the Metro Boston region of Massachusetts are examined. HSFEs are defined as one or more continuous days of streamflow above the mean annual maxima for a selected gauge in each basin. There are notable differences in the HSFEs for these two basins. HSFEs last from 1 to 3 days in the Mystic basin, while HSFEs for the Charles can last from 3 to 9 days. The majority of Mystic HSFEs are immediately preceded by extreme precipitation (occurring within 24 h), while only half of those for the Charles are preceded by extreme precipitation (in this case occurring 2–5 days earlier). While extreme precipitation events are often linked to HSFEs, other factors are often necessary in generating high streamflow, particularly for the Charles, as more than 50% of HSFEs occur at times when streamflow, soil moisture, and total precipitation are statistically above average for a period of at least 2 weeks before the HSFE. Approximately 52% and 80% of HSFEs occur from February to June for the Mystic and Charles, respectively, and these HSFEs are frequently linked to the passage of strong coastal lows, which produce extreme precipitation in the form of both rain and snow. For these coastal lows, Mystic HSFEs are linked to a strong moisture feed along the Massachusetts coastline and intense precipitation, while Charles HSFEs are linked to strong cyclones located off the Mid-Atlantic and longer-duration precipitation.
Abstract
This study examines U.S. Northeast daily precipitation and extreme precipitation characteristics for the 1979–2008 period, focusing on daily station data. Seasonal and spatial distribution, time scale, and relation to large-scale factors are examined. Both parametric and nonparametric extreme definitions are considered, and the top 1% of wet days is chosen as a balance between sample size and emphasis on tail distribution. The seasonal cycle of daily precipitation exhibits two distinct subregions: inland stations characterized by frequent precipitation that peaks in summer and coastal stations characterized by less frequent but more intense precipitation that peaks in late spring as well as early fall. For both subregions, the frequency of extreme precipitation is greatest in the warm season, while the intensity of extreme precipitation shows no distinct seasonal cycle. The majority of Northeast precipitation occurs as isolated 1-day events, while most extreme precipitation occurs on a single day embedded in 2–5-day precipitation events. On these extreme days, examination of hourly data shows that 3 h or less account for approximately 50% of daily accumulation. Northeast station precipitation extremes are not particularly spatially cohesive: over 50% of extreme events occur at single stations only, and 90% occur at only 1–3 stations concurrently. The majority of extreme days (75%–100%) are related to extratropical storms, except during September, when more than 50% of extremes are related to tropical storms. Storm tracks on extreme days are farther southwest and more clustered than for all storm-related precipitation days.
Abstract
This study examines U.S. Northeast daily precipitation and extreme precipitation characteristics for the 1979–2008 period, focusing on daily station data. Seasonal and spatial distribution, time scale, and relation to large-scale factors are examined. Both parametric and nonparametric extreme definitions are considered, and the top 1% of wet days is chosen as a balance between sample size and emphasis on tail distribution. The seasonal cycle of daily precipitation exhibits two distinct subregions: inland stations characterized by frequent precipitation that peaks in summer and coastal stations characterized by less frequent but more intense precipitation that peaks in late spring as well as early fall. For both subregions, the frequency of extreme precipitation is greatest in the warm season, while the intensity of extreme precipitation shows no distinct seasonal cycle. The majority of Northeast precipitation occurs as isolated 1-day events, while most extreme precipitation occurs on a single day embedded in 2–5-day precipitation events. On these extreme days, examination of hourly data shows that 3 h or less account for approximately 50% of daily accumulation. Northeast station precipitation extremes are not particularly spatially cohesive: over 50% of extreme events occur at single stations only, and 90% occur at only 1–3 stations concurrently. The majority of extreme days (75%–100%) are related to extratropical storms, except during September, when more than 50% of extremes are related to tropical storms. Storm tracks on extreme days are farther southwest and more clustered than for all storm-related precipitation days.
Abstract
A k-means clustering method is applied to daily ERA5 500-hPa heights, sea level pressure, and 850-hPa winds, 1979–2008, to identify characteristic weather types (WTs) for September–November for the northeast United States. The resulting WTs are analyzed in terms of structure, frequency of occurrence, typical progressions, precipitation and temperature characteristics, and relation to teleconnections. The WTs are used to make a daily circulation-based distinction between early and late autumn and consider shifts in seasonality. Seven WTs are identified for the autumn season, representing a range of trough and ridge patterns. The largest average values of precipitation and greatest likelihood of extremes occur in the Midwestern Trough and Atlantic Ridge patterns. The greatest likelihood of extreme temperatures occurs in the Northeast Ridge. Some WTs are strongly associated with the phase of the North Atlantic Oscillation and Pacific–North America pattern, with frequency of occurrence for several WTs changing by more than a factor of 2. The two most common progressions between the WTs are one most frequent in September, Mid-Atlantic Trough to Northeast Ridge to Mid-Atlantic Trough, and one most frequent in mid-October–November, Midwestern Trough to Northeast Trough to Midwestern Trough. This seasonality allows for a daily WT-based distinction between early and late season. A preliminary trend analysis indicates an increase in early season WTs later in the season and a decrease in late season WTs earlier in the season; that is, a shift toward a longer period of warm season patterns and a shorter, delayed period of cold season patterns.
Abstract
A k-means clustering method is applied to daily ERA5 500-hPa heights, sea level pressure, and 850-hPa winds, 1979–2008, to identify characteristic weather types (WTs) for September–November for the northeast United States. The resulting WTs are analyzed in terms of structure, frequency of occurrence, typical progressions, precipitation and temperature characteristics, and relation to teleconnections. The WTs are used to make a daily circulation-based distinction between early and late autumn and consider shifts in seasonality. Seven WTs are identified for the autumn season, representing a range of trough and ridge patterns. The largest average values of precipitation and greatest likelihood of extremes occur in the Midwestern Trough and Atlantic Ridge patterns. The greatest likelihood of extreme temperatures occurs in the Northeast Ridge. Some WTs are strongly associated with the phase of the North Atlantic Oscillation and Pacific–North America pattern, with frequency of occurrence for several WTs changing by more than a factor of 2. The two most common progressions between the WTs are one most frequent in September, Mid-Atlantic Trough to Northeast Ridge to Mid-Atlantic Trough, and one most frequent in mid-October–November, Midwestern Trough to Northeast Trough to Midwestern Trough. This seasonality allows for a daily WT-based distinction between early and late season. A preliminary trend analysis indicates an increase in early season WTs later in the season and a decrease in late season WTs earlier in the season; that is, a shift toward a longer period of warm season patterns and a shorter, delayed period of cold season patterns.
Abstract
The extratropical stratosphere in boreal winter is characterized by a strong circumpolar westerly jet, confining the coldest temperatures at high latitudes. The jet, referred to as the stratospheric polar vortex, is predominantly zonal and centered around the pole; however, it does exhibit large variability in wind speed and location. Previous studies showed that a weak stratospheric polar vortex can lead to cold-air outbreaks in the midlatitudes, but the exact relationships and mechanisms are unclear. Particularly, it is unclear whether stratospheric variability has contributed to the observed anomalous cooling trends in midlatitude Eurasia. Using hierarchical clustering, we show that over the last 37 years, the frequency of weak vortex states in mid- to late winter (January and February) has increased, which was accompanied by subsequent cold extremes in midlatitude Eurasia. For this region, 60% of the observed cooling in the era of Arctic amplification, that is, since 1990, can be explained by the increased frequency of weak stratospheric polar vortex states, a number that increases to almost 80% when El Niño–Southern Oscillation (ENSO) variability is included as well.
Abstract
The extratropical stratosphere in boreal winter is characterized by a strong circumpolar westerly jet, confining the coldest temperatures at high latitudes. The jet, referred to as the stratospheric polar vortex, is predominantly zonal and centered around the pole; however, it does exhibit large variability in wind speed and location. Previous studies showed that a weak stratospheric polar vortex can lead to cold-air outbreaks in the midlatitudes, but the exact relationships and mechanisms are unclear. Particularly, it is unclear whether stratospheric variability has contributed to the observed anomalous cooling trends in midlatitude Eurasia. Using hierarchical clustering, we show that over the last 37 years, the frequency of weak vortex states in mid- to late winter (January and February) has increased, which was accompanied by subsequent cold extremes in midlatitude Eurasia. For this region, 60% of the observed cooling in the era of Arctic amplification, that is, since 1990, can be explained by the increased frequency of weak stratospheric polar vortex states, a number that increases to almost 80% when El Niño–Southern Oscillation (ENSO) variability is included as well.
Abstract
The method of k-means cluster analysis is applied to U.S. wintertime daily 850-hPa winds across the Northeast. The resulting weather patterns are analyzed in terms of duration, station, gridded precipitation, storm tracks, and climate teleconnections. Five distinct weather patterns are identified. Weather type (WT) 1 is characterized by a ridge over the western Atlantic and positive precipitation anomalies as far north as the Great Lakes; WT2, by a trough along the eastern United States and positive precipitation anomalies into southern New England; WT3, by a trough over the western Atlantic and negative precipitation anomalies along much of the U.S. East Coast; WT4, by a trough east of Newfoundland and negative precipitation anomalies along parts of the U.S. East Coast; and WT5, by a broad, shallow trough over southeastern Canada and negative precipitation anomalies over the entire U.S. East Coast. WT5 and WT1 are the most persistent, while WT2 typically progresses quickly to WT3 and then to WT4. Based on mean station precipitation in the northeastern United States, most precipitation occurs in WT2 and WT3, with the least in WT1 and WT4. Extreme precipitation occurs most frequently in WT2. Storm tracks show that WT2 and WT3 are associated with coastal storms, while WT2 is also associated with Great Lakes storms. Teleconnections are linked with a change in WT frequency by more than a factor of 2 in several cases: for the North Atlantic Oscillation (NAO) in WT1 and WT4 and for the Pacific–North American (PNA) pattern in WT1 and WT3.
Abstract
The method of k-means cluster analysis is applied to U.S. wintertime daily 850-hPa winds across the Northeast. The resulting weather patterns are analyzed in terms of duration, station, gridded precipitation, storm tracks, and climate teleconnections. Five distinct weather patterns are identified. Weather type (WT) 1 is characterized by a ridge over the western Atlantic and positive precipitation anomalies as far north as the Great Lakes; WT2, by a trough along the eastern United States and positive precipitation anomalies into southern New England; WT3, by a trough over the western Atlantic and negative precipitation anomalies along much of the U.S. East Coast; WT4, by a trough east of Newfoundland and negative precipitation anomalies along parts of the U.S. East Coast; and WT5, by a broad, shallow trough over southeastern Canada and negative precipitation anomalies over the entire U.S. East Coast. WT5 and WT1 are the most persistent, while WT2 typically progresses quickly to WT3 and then to WT4. Based on mean station precipitation in the northeastern United States, most precipitation occurs in WT2 and WT3, with the least in WT1 and WT4. Extreme precipitation occurs most frequently in WT2. Storm tracks show that WT2 and WT3 are associated with coastal storms, while WT2 is also associated with Great Lakes storms. Teleconnections are linked with a change in WT frequency by more than a factor of 2 in several cases: for the North Atlantic Oscillation (NAO) in WT1 and WT4 and for the Pacific–North American (PNA) pattern in WT1 and WT3.
