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- Author or Editor: Richard Thoman x
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Abstract
During the early winter of 2002 and late winter of 2007, the Alaskan sector of the North Pacific Ocean region experienced record-breaking temperature anomalies. The duration of these episodes was unusually long, with each lasting more than 1 month: 55 days for the warm anomaly of October–December 2002 and 37 days for the cold anomaly of February–March 2007. Temperature departures over each respective period were the largest for the continental climate of interior Alaska (>10°C) and the smallest for the maritime regions of Alaska (<4°C). Mean temperatures over the event periods in 2002 and 2007 easily ranked as the record warmest and coldest, respectively, for many surface observing stations. In addition, heating degree-day anomalies were on the order of 700 units for these periods. Atmospheric circulation patterns at the surface and upper levels for the circum-Arctic proved to be the driver for these persistent events. The 2002 warm anomaly was driven by enhanced southerly advection associated with an unusually strong Aleutian low and a positive Pacific decadal oscillation index, which resulted in a large area of anomalous temperatures in Alaska and northern Canada. The 2007 cold anomaly was driven by a weakening of the circulation pattern in the subpolar Pacific sector and a strengthening of the Siberian high, with the strongest temperature anomalies in Alaska and northwestern Canada.
Abstract
During the early winter of 2002 and late winter of 2007, the Alaskan sector of the North Pacific Ocean region experienced record-breaking temperature anomalies. The duration of these episodes was unusually long, with each lasting more than 1 month: 55 days for the warm anomaly of October–December 2002 and 37 days for the cold anomaly of February–March 2007. Temperature departures over each respective period were the largest for the continental climate of interior Alaska (>10°C) and the smallest for the maritime regions of Alaska (<4°C). Mean temperatures over the event periods in 2002 and 2007 easily ranked as the record warmest and coldest, respectively, for many surface observing stations. In addition, heating degree-day anomalies were on the order of 700 units for these periods. Atmospheric circulation patterns at the surface and upper levels for the circum-Arctic proved to be the driver for these persistent events. The 2002 warm anomaly was driven by enhanced southerly advection associated with an unusually strong Aleutian low and a positive Pacific decadal oscillation index, which resulted in a large area of anomalous temperatures in Alaska and northern Canada. The 2007 cold anomaly was driven by a weakening of the circulation pattern in the subpolar Pacific sector and a strengthening of the Siberian high, with the strongest temperature anomalies in Alaska and northwestern Canada.
Abstract
By extending the record of Alaskan divisional temperature and precipitation back in time, regional variations and trends of temperature and precipitation over 1920–2012 are documented. The use of the divisional framework highlights the greater spatial coherence of temperature variations relative to precipitation variations.
The divisional time series of temperature are characterized by large interannual variability superimposed upon low-frequency variability, as well as by an underlying trend. Low-frequency variability corresponding to the Pacific decadal oscillation (PDO) includes Alaska’s generally warm period of the 1920s and 1930s, a cold period from the late 1940s through the mid-1970s, a warm period from the late 1970s through the early 2000s, and a cooler period in the most recent decade. An exception to the cooling of the past decade is the North Slope climate division, which has continued to warm. There has been a gradual upward trend of Alaskan temperatures relative to the PDO since 1920, resulting in a statewide average warming of about 1°C.
In contrast to temperature, variations of precipitation are less consistent across climate divisions and have much less multidecadal character. Thirty-year trends of both variables are highly sensitive to the choice of the subperiod within the overall 93-yr period. The trends also vary seasonally, with winter and spring contributing the most to the annual trends.
Abstract
By extending the record of Alaskan divisional temperature and precipitation back in time, regional variations and trends of temperature and precipitation over 1920–2012 are documented. The use of the divisional framework highlights the greater spatial coherence of temperature variations relative to precipitation variations.
The divisional time series of temperature are characterized by large interannual variability superimposed upon low-frequency variability, as well as by an underlying trend. Low-frequency variability corresponding to the Pacific decadal oscillation (PDO) includes Alaska’s generally warm period of the 1920s and 1930s, a cold period from the late 1940s through the mid-1970s, a warm period from the late 1970s through the early 2000s, and a cooler period in the most recent decade. An exception to the cooling of the past decade is the North Slope climate division, which has continued to warm. There has been a gradual upward trend of Alaskan temperatures relative to the PDO since 1920, resulting in a statewide average warming of about 1°C.
In contrast to temperature, variations of precipitation are less consistent across climate divisions and have much less multidecadal character. Thirty-year trends of both variables are highly sensitive to the choice of the subperiod within the overall 93-yr period. The trends also vary seasonally, with winter and spring contributing the most to the annual trends.
Abstract
Frozen rivers in the Arctic serve as critical highways because of the lack of roads; therefore, it is important to understand the key mechanisms that control the timing of river ice breakup. The relationships between springtime Interior Alaska river ice breakup date and the large-scale climate are investigated for the Yukon, Tanana, Kuskokwim, and Chena Rivers for the 1949–2008 period. The most important climate factor that determines breakup is April–May surface air temperatures (SATs). Breakup tends to occur earlier when Alaska April–May SATs and river flow are above normal. Spring SATs are influenced by storms approaching the state from the Gulf of Alaska, which are part of large-scale climate anomalies that compare favorably with ENSO. During the warm phase of ENSO fewer storms travel into the Gulf of Alaska during the spring, resulting in a decrease of cloud cover over Alaska, which increases surface solar insolation. This results in warmer-than-average springtime SATs and an earlier breakup date. The opposite holds true for the cold phase of ENSO. Increased wintertime precipitation over Alaska has a secondary impact on earlier breakup by increasing spring river discharge. Improved springtime Alaska temperature predictions would enhance the ability to forecast the timing of river ice breakup.
Abstract
Frozen rivers in the Arctic serve as critical highways because of the lack of roads; therefore, it is important to understand the key mechanisms that control the timing of river ice breakup. The relationships between springtime Interior Alaska river ice breakup date and the large-scale climate are investigated for the Yukon, Tanana, Kuskokwim, and Chena Rivers for the 1949–2008 period. The most important climate factor that determines breakup is April–May surface air temperatures (SATs). Breakup tends to occur earlier when Alaska April–May SATs and river flow are above normal. Spring SATs are influenced by storms approaching the state from the Gulf of Alaska, which are part of large-scale climate anomalies that compare favorably with ENSO. During the warm phase of ENSO fewer storms travel into the Gulf of Alaska during the spring, resulting in a decrease of cloud cover over Alaska, which increases surface solar insolation. This results in warmer-than-average springtime SATs and an earlier breakup date. The opposite holds true for the cold phase of ENSO. Increased wintertime precipitation over Alaska has a secondary impact on earlier breakup by increasing spring river discharge. Improved springtime Alaska temperature predictions would enhance the ability to forecast the timing of river ice breakup.
Abstract
Alaska experienced record-setting warmth during the 2015/16 cold season (October–April). Statewide average temperatures exceeded the period-of-record mean by more than 4°C over the 7-month cold season and by more than 6°C over the 4-month late-winter period, January–April. The record warmth raises two questions: 1) Why was Alaska so warm during the 2015/16 cold season? 2) At what point in the future might this warmth become typical if greenhouse warming continues? On the basis of circulation analogs computed from sea level pressure and 850-hPa geopotential height fields, the atmospheric circulation explains less than half of the anomalous warmth. The warming signal forced by greenhouse gases in climate models accounts for about 1°C of the anomalous warmth. A factor that is consistent with the seasonal and spatial patterns of the warmth is the anomalous surface state. The surface anomalies include 1) above-normal ocean surface temperatures and below-normal sea ice coverage in the surrounding seas from which air advects into Alaska and 2) the deficient snowpack over Alaska itself. The location of the maximum of anomalous warmth over Alaska and the late-winter–early-spring increase of the anomalous warmth unexplained by the atmospheric circulation implicates snow cover and its albedo effect, which is supported by observational measurements in the boreal forest and tundra biomes. Climate model simulations indicate that warmth of this magnitude will become the norm by the 2050s if greenhouse gas emissions follow their present scenario.
Abstract
Alaska experienced record-setting warmth during the 2015/16 cold season (October–April). Statewide average temperatures exceeded the period-of-record mean by more than 4°C over the 7-month cold season and by more than 6°C over the 4-month late-winter period, January–April. The record warmth raises two questions: 1) Why was Alaska so warm during the 2015/16 cold season? 2) At what point in the future might this warmth become typical if greenhouse warming continues? On the basis of circulation analogs computed from sea level pressure and 850-hPa geopotential height fields, the atmospheric circulation explains less than half of the anomalous warmth. The warming signal forced by greenhouse gases in climate models accounts for about 1°C of the anomalous warmth. A factor that is consistent with the seasonal and spatial patterns of the warmth is the anomalous surface state. The surface anomalies include 1) above-normal ocean surface temperatures and below-normal sea ice coverage in the surrounding seas from which air advects into Alaska and 2) the deficient snowpack over Alaska itself. The location of the maximum of anomalous warmth over Alaska and the late-winter–early-spring increase of the anomalous warmth unexplained by the atmospheric circulation implicates snow cover and its albedo effect, which is supported by observational measurements in the boreal forest and tundra biomes. Climate model simulations indicate that warmth of this magnitude will become the norm by the 2050s if greenhouse gas emissions follow their present scenario.
Abstract
Lightning is a key driver of wildfire activity in Alaska. Quantifying its historical variability and trends has been challenging because of changes in the observational network, but understanding historical and possible future changes in lightning activity is important for fire management planning. Dynamically downscaled reanalysis and global climate model (GCM) data were used to statistically assess lightning data in geographic zones used operationally by fire managers across Alaska. Convective precipitation was found to be a key predictor of weekly lightning activity through multiple regression analysis, along with additional atmospheric stability, moisture, and temperature predictor variables. Model-derived estimates of historical June–July lightning since 1979 showed increasing but lower-magnitude trends than the observed record, derived from the highly heterogeneous lightning sensor network, over the same period throughout interior Alaska. Two downscaled GCM projections estimate a doubling of lightning activity over the same June–July season and geographic region by the end of the twenty-first century. Such a substantial increase in lightning activity may have significant impacts on future wildfire activity in Alaska because of increased opportunities for ignitions, although the final outcome also depends on fire weather conditions and fuels.
Abstract
Lightning is a key driver of wildfire activity in Alaska. Quantifying its historical variability and trends has been challenging because of changes in the observational network, but understanding historical and possible future changes in lightning activity is important for fire management planning. Dynamically downscaled reanalysis and global climate model (GCM) data were used to statistically assess lightning data in geographic zones used operationally by fire managers across Alaska. Convective precipitation was found to be a key predictor of weekly lightning activity through multiple regression analysis, along with additional atmospheric stability, moisture, and temperature predictor variables. Model-derived estimates of historical June–July lightning since 1979 showed increasing but lower-magnitude trends than the observed record, derived from the highly heterogeneous lightning sensor network, over the same period throughout interior Alaska. Two downscaled GCM projections estimate a doubling of lightning activity over the same June–July season and geographic region by the end of the twenty-first century. Such a substantial increase in lightning activity may have significant impacts on future wildfire activity in Alaska because of increased opportunities for ignitions, although the final outcome also depends on fire weather conditions and fuels.
Abstract
The ice formed by cold-season rainfall or rain on snow (ROS) has striking impacts on the economy and ecology of Alaska. An understanding of the atmospheric drivers of ROS events is required to better predict them and plan for environmental change. The spatially/temporally sparse network of stations in Alaska makes studying such events challenging, and gridded reanalysis or remote sensing products are necessary to fill the gaps. Recently developed dynamically downscaled climate data provide a new suite of high-resolution variables for investigating historical and projected ROS events across all of Alaska from 1979 to 2100. The dynamically downscaled reanalysis data of ERA-Interim replicated the seasonal patterns of ROS events but tended to produce more rain events than in station observations. However, dynamical downscaling reduced the bias toward more rain events in the coarse reanalysis. ROS occurred most frequently over southwestern and southern coastal regions. Extreme events with the heaviest rainfall generally coincided with anomalous high pressure centered to the south/southeast of the locations receiving the event and warm-air advection from the resulting southwesterly wind flow. ROS events were projected to increase in frequency overall and for extremes across most of the region but were expected to decline over southwestern/southern Alaska. Increases in frequency were projected as a result of more frequent winter rainfall, but the number of ROS events may ultimately decline in some areas as a result of temperatures rising above the freezing threshold. These projected changes in ROS can significantly affect wildlife, vegetation, and human activities across the Alaska landscape.
Abstract
The ice formed by cold-season rainfall or rain on snow (ROS) has striking impacts on the economy and ecology of Alaska. An understanding of the atmospheric drivers of ROS events is required to better predict them and plan for environmental change. The spatially/temporally sparse network of stations in Alaska makes studying such events challenging, and gridded reanalysis or remote sensing products are necessary to fill the gaps. Recently developed dynamically downscaled climate data provide a new suite of high-resolution variables for investigating historical and projected ROS events across all of Alaska from 1979 to 2100. The dynamically downscaled reanalysis data of ERA-Interim replicated the seasonal patterns of ROS events but tended to produce more rain events than in station observations. However, dynamical downscaling reduced the bias toward more rain events in the coarse reanalysis. ROS occurred most frequently over southwestern and southern coastal regions. Extreme events with the heaviest rainfall generally coincided with anomalous high pressure centered to the south/southeast of the locations receiving the event and warm-air advection from the resulting southwesterly wind flow. ROS events were projected to increase in frequency overall and for extremes across most of the region but were expected to decline over southwestern/southern Alaska. Increases in frequency were projected as a result of more frequent winter rainfall, but the number of ROS events may ultimately decline in some areas as a result of temperatures rising above the freezing threshold. These projected changes in ROS can significantly affect wildlife, vegetation, and human activities across the Alaska landscape.
