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The trajectory of land surface wetness is one of the most consequential unknowns in the Arctic climate system. The present analysis is intended to (1) document seasonal and interannual variations of surface moisture fluxes, (2) clarify the drivers of P-ET variations among Arctic vegetative types, and (3) evaluate the effects of wildfire disturbance on ET. The analysis is based on field measurements from sites in boreal forest and tundra ecosystems of Alaska. The surface moisture budget at boreal forest sites in permafrost areas generally shows a moisture deficit in late spring and early summer, followed by a moisture surplus from late summer into autumn. The annual net P-ET is generally positive but can vary interannually by more than an order of magnitude. The primary drivers of variations in evapotranspiration over weekly to monthly timescales are radiative fluxes, air temperature, relative humidity and wind speed. Overall, the ET at forest sites shows a stronger dependence on relative humidity and wind speed, while ET at tundra sites shows the stronger dependence on air temperature. These differences imply that tundra sites are more temperature-limited and forest sites are more humidity-dependent. Relative to a nearby unburned site, a burned forest site in interior Alaska shows an increase in ET for nearly a decade following the fire, while the recovery time for ET at a burned tundra site is only about three years.
Sarah M. Thunberg; John E. Walsh; Eugénie S. Euskirchen; Kyle Redilla; Adrian V. Rocha. Surface moisture budget of tundra and boreal ecosystems in Alaska: Variations and drivers. Polar Science 2021, 100685 .
AMA StyleSarah M. Thunberg, John E. Walsh, Eugénie S. Euskirchen, Kyle Redilla, Adrian V. Rocha. Surface moisture budget of tundra and boreal ecosystems in Alaska: Variations and drivers. Polar Science. 2021; ():100685.
Chicago/Turabian StyleSarah M. Thunberg; John E. Walsh; Eugénie S. Euskirchen; Kyle Redilla; Adrian V. Rocha. 2021. "Surface moisture budget of tundra and boreal ecosystems in Alaska: Variations and drivers." Polar Science , no. : 100685.
The late-season extreme fire activity in Southcentral Alaska during 2019 was highly unusual and consequential. Firefighting operations had to be extended by a month in 2019 due to the extreme conditions of hot summer temperature and prolonged drought. The ongoing fires created poor air quality in the region containing most of Alaska’s population, leading to substantial impacts to public health. Suppression costs totaled over $70 million for Southcentral Alaska. This study’s main goals are to place the 2019 season into historical context, provide an attribution analysis, and assess future changes in wildfire risk in the region. The primary tools are meteorological observations and climate model simulations from the NCAR CESM Large Ensemble (LENS). The 2019 fire season in Southcentral Alaska included the hottest and driest June–August season over the 1979–2019 period. The LENS simulation analysis suggests that the anthropogenic signal of increased fire risk had not yet emerged in 2019 because of the CESM’s internal variability, but that the anthropogenic signal will emerge by the 2040–80 period. The effect of warming temperatures dominates the effect of enhanced precipitation in the trend towards increased fire risk.
Uma S. Bhatt; Rick T. Lader; John E. Walsh; Peter A. Bieniek; Richard Thoman; Matthew Berman; Cecilia Borries-Strigle; Kristi Bulock; Jonathan Chriest; Micah Hahn; Amy S. Hendricks; Randi Jandt; Joseph Little; Daniel McEvoy; Chris Moore; T. Scott Rupp; Jennifer Schmidt; Eric Stevens; Heidi Strader; Christine Waigl; James White; Alison York; Robert Ziel. Emerging Anthropogenic Influences on the Southcentral Alaska Temperature and Precipitation Extremes and Related Fires in 2019. Land 2021, 10, 82 .
AMA StyleUma S. Bhatt, Rick T. Lader, John E. Walsh, Peter A. Bieniek, Richard Thoman, Matthew Berman, Cecilia Borries-Strigle, Kristi Bulock, Jonathan Chriest, Micah Hahn, Amy S. Hendricks, Randi Jandt, Joseph Little, Daniel McEvoy, Chris Moore, T. Scott Rupp, Jennifer Schmidt, Eric Stevens, Heidi Strader, Christine Waigl, James White, Alison York, Robert Ziel. Emerging Anthropogenic Influences on the Southcentral Alaska Temperature and Precipitation Extremes and Related Fires in 2019. Land. 2021; 10 (1):82.
Chicago/Turabian StyleUma S. Bhatt; Rick T. Lader; John E. Walsh; Peter A. Bieniek; Richard Thoman; Matthew Berman; Cecilia Borries-Strigle; Kristi Bulock; Jonathan Chriest; Micah Hahn; Amy S. Hendricks; Randi Jandt; Joseph Little; Daniel McEvoy; Chris Moore; T. Scott Rupp; Jennifer Schmidt; Eric Stevens; Heidi Strader; Christine Waigl; James White; Alison York; Robert Ziel. 2021. "Emerging Anthropogenic Influences on the Southcentral Alaska Temperature and Precipitation Extremes and Related Fires in 2019." Land 10, no. 1: 82.
Global warming over the past half century has been amplified in the Arctic, especially in the cold season. Other Arctic indicators, especially those of the cryosphere, show signals consistent with the warming of the past half century. This Arctic amplification of the warming arises from a number of processes in the climate system, including the feedbacks associated with the loss of sea ice and snow, the increase of atmospheric moisture, and the vertical temperature structure of the Arctic atmosphere. Ocean heat fluxes into the Arctic from the North Atlantic and North Pacific also appear to have contributed to the Arctic warming through a reduction of sea ice. Internal variability, which played a major role in Arctic warming during the early twentieth century, appears to have been a minor contributor to the more recent warming, which has also been associated with unprecedented extremes of Arctic temperature and sea ice. There is evidence for increased moisture content of the Arctic atmosphere and corresponding impacts on episodes of extreme warmth. The recent variations of Arctic temperature and associated variables fit well with the simulations of Arctic climate by global and regional climate models. Projected changes include a continued warming of the Arctic even under moderate mitigation scenarios, and an increase of Arctic precipitation consistent with the higher temperatures and atmospheric humidities.
John E. Walsh. Arctic Climate Change, Variability, and Extremes. Arctic Hydrology, Permafrost and Ecosystems 2020, 3 -23.
AMA StyleJohn E. Walsh. Arctic Climate Change, Variability, and Extremes. Arctic Hydrology, Permafrost and Ecosystems. 2020; ():3-23.
Chicago/Turabian StyleJohn E. Walsh. 2020. "Arctic Climate Change, Variability, and Extremes." Arctic Hydrology, Permafrost and Ecosystems , no. : 3-23.
The greatest impacts of climate change on ecosystems, wildlife and humans often arise from extreme events rather than changes in climatic means. Northern high latitudes, including the Arctic, experience a variety of climate-related extreme events, yet there has been little attempt to synthesize information on extreme events in this region. This review surveys work on various types of extreme events in northern high latitudes, addressing (1) the evidence for variations and changes based on analyses of recent historical data and (2) projected changes based primarily on studies utilizing global climate models. The survey of extreme weather and climate events includes temperature, precipitation, snow, freezing rain, atmospheric blocking, cyclones, and wind. The survey also includes cryospheric and biophysical impacts: sea ice rapid loss events, Greenland Ice Sheet melt, floods, drought, wildfire, coastal erosion, terrestrial ecosystems, and marine ecosystems. Temperature and sea ice rank at the high end of the spectra of evidence for change and confidence in future change, while drought, flooding and cyclones rank at the lower end. Research priorities identified on the basis of this review include greater use of high-resolution models and observing system enhancements that target extreme events. There is also a need for further work on attribution, impacts on ecosystems and humans, and thresholds or tipping points that may be triggered by extreme events in high latitudes.
John E. Walsh; Thomas Ballinger; Eugénie S. Euskirchen; Edward Hanna; Johanna Mård; James E. Overland; Helge Tangen; Timo Vihma. Extreme weather and climate events in northern areas: A review. Earth-Science Reviews 2020, 209, 103324 .
AMA StyleJohn E. Walsh, Thomas Ballinger, Eugénie S. Euskirchen, Edward Hanna, Johanna Mård, James E. Overland, Helge Tangen, Timo Vihma. Extreme weather and climate events in northern areas: A review. Earth-Science Reviews. 2020; 209 ():103324.
Chicago/Turabian StyleJohn E. Walsh; Thomas Ballinger; Eugénie S. Euskirchen; Edward Hanna; Johanna Mård; James E. Overland; Helge Tangen; Timo Vihma. 2020. "Extreme weather and climate events in northern areas: A review." Earth-Science Reviews 209, no. : 103324.
We explore the response of wintertime Arctic sea ice growth to strong cyclones and to large-scale circulation patterns on the daily scale using Earth system model output in phase 5 of the Coupled Model Intercomparison Project (CMIP5). A combined metrics ranking method selects three CMIP5 models that are successful in reproducing the wintertime Arctic dipole (AD) pattern. A cyclone identification method is applied to select strong cyclones in two subregions in the North Atlantic to examine their different impacts on sea ice growth. The total change of sea ice growth rate (SGR) is split into those respectively driven by the dynamic and thermodynamic atmospheric forcing. Three models reproduce the downward longwave radiation anomalies that generally match thermodynamic SGR anomalies in response to both strong cyclones and large-scale circulation patterns. For large-scale circulation patterns, the negative AD outweighs the positive Arctic Oscillation in thermodynamically inhibiting SGR in both impact area and magnitude. Despite the disagreement on the spatial distribution, the three CMIP5 models agree on the weaker response of dynamic SGR than thermodynamic SGR. As the Arctic warms, the thinner sea ice results in more ice production and smaller spatial heterogeneity of thickness, dampening the SGR response to the dynamic forcing. The higher temperature increases the specific heat of sea ice, thus dampening the SGR response to the thermodynamic forcing. In this way, the atmospheric forcing is projected to contribute less to change daily SGR in the future climate.
Lei Cai; Vladimir A. Alexeev; John Walsh. Arctic Sea Ice Growth in Response to Synoptic- and Large-Scale Atmospheric Forcing from CMIP5 Models. Journal of Climate 2020, 33, 6083 -6099.
AMA StyleLei Cai, Vladimir A. Alexeev, John Walsh. Arctic Sea Ice Growth in Response to Synoptic- and Large-Scale Atmospheric Forcing from CMIP5 Models. Journal of Climate. 2020; 33 (14):6083-6099.
Chicago/Turabian StyleLei Cai; Vladimir A. Alexeev; John Walsh. 2020. "Arctic Sea Ice Growth in Response to Synoptic- and Large-Scale Atmospheric Forcing from CMIP5 Models." Journal of Climate 33, no. 14: 6083-6099.
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.
Peter A. Bieniek; Uma S. Bhatt; Alison York; John Walsh; Rick Lader; Heidi Strader; Robert Ziel; Randi R. Jandt; Richard L. Thoman. Lightning Variability in Dynamically Downscaled Simulations of Alaska’s Present and Future Summer Climate. Journal of Applied Meteorology and Climatology 2020, 59, 1139 -1152.
AMA StylePeter A. Bieniek, Uma S. Bhatt, Alison York, John Walsh, Rick Lader, Heidi Strader, Robert Ziel, Randi R. Jandt, Richard L. Thoman. Lightning Variability in Dynamically Downscaled Simulations of Alaska’s Present and Future Summer Climate. Journal of Applied Meteorology and Climatology. 2020; 59 (6):1139-1152.
Chicago/Turabian StylePeter A. Bieniek; Uma S. Bhatt; Alison York; John Walsh; Rick Lader; Heidi Strader; Robert Ziel; Randi R. Jandt; Richard L. Thoman. 2020. "Lightning Variability in Dynamically Downscaled Simulations of Alaska’s Present and Future Summer Climate." Journal of Applied Meteorology and Climatology 59, no. 6: 1139-1152.
Large sea ice loss on the synoptic time scale is examined in various subregions in the Arctic as well as at the pan-Arctic scale. It is found that the frequency of large daily sea ice loss (LDSIL) days is significantly correlated with the September sea ice extent over the Beaufort–Chukchi–Siberian Seas, the Laptev–Kara Seas, the central Arctic, and the all-Arctic regions, indicating a link between the synoptic sea ice variability and the interannual variability of the annual minimum sea ice extent. A composite analysis reveals dipoles of anomalous cyclones and anticyclones associated with LDSIL days. Different from the well-known Arctic dipole pattern, the east–west dipoles are found over the corresponding regions of LDSIL in the Arctic marginal seas and are associated with the increasing occurrence of Rossby wave breaking and atmospheric rivers. The anticyclones of the dipoles are persistent and quasi-stationary, reminiscent of blocking. The anomalous poleward flow between the cyclone and the anticyclone enhances the poleward transport of heat and water vapor in the lower troposphere. Although enhanced downward shortwave radiation, associated with reduced cloud fraction, is found in some regions, it is not collocated with the regions of LDSIL. In contrast, enhanced downward longwave radiation owing to increasing column water vapor shows good spatial correspondence with LDSIL, indicating the importance of atmospheric rivers in LDSIL events. Lead/lag composites with respect to the onset of LDSIL episodes reveal precursor wave trains spanning the midlatitudes. The wave trains have predominantly zonal energy propagation in the midlatitudes and do not show a clear link to tropical or subtropical forcing.
Zhuo Wang; John Walsh; Sarah Szymborski; Melinda Peng. Rapid Arctic Sea Ice Loss on the Synoptic Time Scale and Related Atmospheric Circulation Anomalies. Journal of Climate 2020, 33, 1597 -1617.
AMA StyleZhuo Wang, John Walsh, Sarah Szymborski, Melinda Peng. Rapid Arctic Sea Ice Loss on the Synoptic Time Scale and Related Atmospheric Circulation Anomalies. Journal of Climate. 2020; 33 (5):1597-1617.
Chicago/Turabian StyleZhuo Wang; John Walsh; Sarah Szymborski; Melinda Peng. 2020. "Rapid Arctic Sea Ice Loss on the Synoptic Time Scale and Related Atmospheric Circulation Anomalies." Journal of Climate 33, no. 5: 1597-1617.
Richard L. Thoman; Uma S. Bhatt; Peter A. Bieniek; Brian R. Brettschneider; Michael Brubaker; Seth L. Danielson; Zachary Labe; Rick Lader; Walter N. Meier; Gay Sheffield; John Walsh. The Record Low Bering Sea Ice Extent in 2018: Context, Impacts, and an Assessment of the Role of Anthropogenic Climate Change. Bulletin of the American Meteorological Society 2020, 101, S53 -S58.
AMA StyleRichard L. Thoman, Uma S. Bhatt, Peter A. Bieniek, Brian R. Brettschneider, Michael Brubaker, Seth L. Danielson, Zachary Labe, Rick Lader, Walter N. Meier, Gay Sheffield, John Walsh. The Record Low Bering Sea Ice Extent in 2018: Context, Impacts, and an Assessment of the Role of Anthropogenic Climate Change. Bulletin of the American Meteorological Society. 2020; 101 (1):S53-S58.
Chicago/Turabian StyleRichard L. Thoman; Uma S. Bhatt; Peter A. Bieniek; Brian R. Brettschneider; Michael Brubaker; Seth L. Danielson; Zachary Labe; Rick Lader; Walter N. Meier; Gay Sheffield; John Walsh. 2020. "The Record Low Bering Sea Ice Extent in 2018: Context, Impacts, and an Assessment of the Role of Anthropogenic Climate Change." Bulletin of the American Meteorological Society 101, no. 1: S53-S58.
John Walsh; Yuji Kodama; Takashi Yamanouchi. The Fifth International Symposium on Arctic Research (ISAR-5). Polar Science 2019, 21, 1 -5.
AMA StyleJohn Walsh, Yuji Kodama, Takashi Yamanouchi. The Fifth International Symposium on Arctic Research (ISAR-5). Polar Science. 2019; 21 ():1-5.
Chicago/Turabian StyleJohn Walsh; Yuji Kodama; Takashi Yamanouchi. 2019. "The Fifth International Symposium on Arctic Research (ISAR-5)." Polar Science 21, no. : 1-5.
Snowfall and snow season length across Alaska control the surface hydrology and underlying soil properties and also influence near‐surface air temperature by changing the energy balance. Current projections of warming suggest that considerable change will occur to key snow parameters, possibly contributing to extensive infrastructure damage from thawing permafrost, an increased frequency of rain‐on‐snow events and reduced soil recharge in the spring due to shallow end‐of‐winter snowpack. This study investigates projected changes to mean annual snowfall, dates of snow onset and snowmelt and extreme snowfall for Alaska, using dynamically downscaled reanalysis and climate model simulations. These include the ERA‐Interim reanalysis from 1981 to 2010, and two Coupled Model Intercomparison Project Phase 5 models: Community Climate System Model version 4 (CCSM4) and Geophysical Fluid Dynamics Laboratory Climate Model version 3 (GFDL‐CM3) from 1981 to 2100. The analysis is presented in 30‐year periods (i.e., 1981–2010, 2011–2040, 2041–2070 and 2071–2100) with the future scenarios from Representative Concentration Pathway 8.5. Late‐century projections of average annual snowfall at low elevations (0–1,000 m) show decreases of 41.3 and 40.6% for CCSM4 and GFDL‐CM3, respectively. At high elevations (1,000–2,000 m), the reductions are smaller at 13.5 and 14.2%, respectively. End‐of‐winter snow‐water equivalent displays reductions at all elevations in the future periods. Snow season length is shortened due to later snow onset and earlier snowmelt; many locations in southwest Alaska no longer experience continuous winter snowpack by the late‐century period. Maximum 2‐day snowfall amounts are projected to decrease near Anchorage and Nome, while Fairbanks and Utqiaġvik (Barrow) show no significant trend.
Rick Lader; John Walsh; Uma S. Bhatt; Peter A. Bieniek. Anticipated changes to the snow season in Alaska: Elevation dependency, timing and extremes. International Journal of Climatology 2019, 40, 169 -187.
AMA StyleRick Lader, John Walsh, Uma S. Bhatt, Peter A. Bieniek. Anticipated changes to the snow season in Alaska: Elevation dependency, timing and extremes. International Journal of Climatology. 2019; 40 (1):169-187.
Chicago/Turabian StyleRick Lader; John Walsh; Uma S. Bhatt; Peter A. Bieniek. 2019. "Anticipated changes to the snow season in Alaska: Elevation dependency, timing and extremes." International Journal of Climatology 40, no. 1: 169-187.
Basic statistical metrics such as autocorrelations and across-region lag correlations of sea ice variations provide benchmarks for the assessments of forecast skill achieved by other methods such as more sophisticated statistical formulations, numerical models, and heuristic approaches. In this study we use observational data to evaluate the contribution of the trend to the skill of persistence-based statistical forecasts of monthly and seasonal ice extent on the pan-Arctic and regional scales. We focus on the Beaufort Sea for which the Barnett Severity Index provides a metric of historical variations in ice conditions over the summer shipping season. The variance about the trend line differs little among various methods of detrending (piecewise linear, quadratic, cubic, exponential). Application of the piecewise linear trend calculation indicates an acceleration of the winter and summer trends during the 1990s. Persistence-based statistical forecasts of the Barnett Severity Index as well as September pan-Arctic ice extent show significant statistical skill out to several seasons when the data include the trend. However, this apparent skill largely vanishes when the data are detrended. In only a few regions does September ice extent correlate significantly with antecedent ice anomalies in the same region more than 2 months earlier. The springtime “predictability barrier” in regional forecasts based on persistence of ice extent anomalies is not reduced by the inclusion of several decades of pre-satellite data. No region shows significant correlation with the detrended September pan-Arctic ice extent at lead times greater than a month or two; the concurrent correlations are strongest with the East Siberian Sea. The Beaufort Sea's ice extent as far back as July explains about 20 % of the variance of the Barnett Severity Index, which is primarily a September metric. The Chukchi Sea is the only other region showing a significant association with the Barnett Severity Index, although only at a lead time of a month or two.
John Walsh; J. Scott Stewart; Florence Fetterer. Benchmark seasonal prediction skill estimates based on regional indices. The Cryosphere 2019, 13, 1073 -1088.
AMA StyleJohn Walsh, J. Scott Stewart, Florence Fetterer. Benchmark seasonal prediction skill estimates based on regional indices. The Cryosphere. 2019; 13 (4):1073-1088.
Chicago/Turabian StyleJohn Walsh; J. Scott Stewart; Florence Fetterer. 2019. "Benchmark seasonal prediction skill estimates based on regional indices." The Cryosphere 13, no. 4: 1073-1088.
Key observational indicators of climate change in the Arctic, most spanning a 47 year period (1971–2017) demonstrate fundamental changes among nine key elements of the Arctic system. We find that, coherent with increasing air temperature, there is an intensification of the hydrological cycle, evident from increases in humidity, precipitation, river discharge, glacier equilibrium line altitude and land ice wastage. Downward trends continue in sea ice thickness (and extent) and spring snow cover extent and duration, while near-surface permafrost continues to warm. Several of the climate indicators exhibit a significant statistical correlation with air temperature or precipitation, reinforcing the notion that increasing air temperatures and precipitation are drivers of major changes in various components of the Arctic system. To progress beyond a presentation of the Arctic physical climate changes, we find a correspondence between air temperature and biophysical indicators such as tundra biomass and identify numerous biophysical disruptions with cascading effects throughout the trophic levels. These include: increased delivery of organic matter and nutrients to Arctic near‐coastal zones; condensed flowering and pollination plant species periods; timing mismatch between plant flowering and pollinators; increased plant vulnerability to insect disturbance; increased shrub biomass; increased ignition of wildfires; increased growing season CO2 uptake, with counterbalancing increases in shoulder season and winter CO2 emissions; increased carbon cycling, regulated by local hydrology and permafrost thaw; conversion between terrestrial and aquatic ecosystems; and shifting animal distribution and demographics. The Arctic biophysical system is now clearly trending away from its 20th Century state and into an unprecedented state, with implications not only within but beyond the Arctic. The indicator time series of this study are freely downloadable at AMAP.no.
Jason E Box; William T Colgan; Torben Røjle Christensen; Niels Martin Schmidt; Magnus Lund; Frans-Jan W Parmentier; Ross Brown; Uma S Bhatt; Eugénie S Euskirchen; Vladimir E Romanovsky; John Walsh; James E Overland; Muyin Wang; Robert W Corell; Walter N Meier; Bert Wouters; Sebastian Mernild; Johanna Mård; Janet Pawlak; Morten Skovgård Olsen. Key indicators of Arctic climate change: 1971–2017. Environmental Research Letters 2019, 14, 045010 .
AMA StyleJason E Box, William T Colgan, Torben Røjle Christensen, Niels Martin Schmidt, Magnus Lund, Frans-Jan W Parmentier, Ross Brown, Uma S Bhatt, Eugénie S Euskirchen, Vladimir E Romanovsky, John Walsh, James E Overland, Muyin Wang, Robert W Corell, Walter N Meier, Bert Wouters, Sebastian Mernild, Johanna Mård, Janet Pawlak, Morten Skovgård Olsen. Key indicators of Arctic climate change: 1971–2017. Environmental Research Letters. 2019; 14 (4):045010.
Chicago/Turabian StyleJason E Box; William T Colgan; Torben Røjle Christensen; Niels Martin Schmidt; Magnus Lund; Frans-Jan W Parmentier; Ross Brown; Uma S Bhatt; Eugénie S Euskirchen; Vladimir E Romanovsky; John Walsh; James E Overland; Muyin Wang; Robert W Corell; Walter N Meier; Bert Wouters; Sebastian Mernild; Johanna Mård; Janet Pawlak; Morten Skovgård Olsen. 2019. "Key indicators of Arctic climate change: 1971–2017." Environmental Research Letters 14, no. 4: 045010.
Thirty models in phase 5 of the Coupled Model Intercomparison Project (CMIP5) are evaluated for their performances in reproducing two summertime atmospheric circulation patterns in the Arctic: the Arctic Oscillation (AO) and Arctic dipole (AD). The reference AO and AD are extracted from the ERA-Interim dataset (1979–2016). Model evaluation is conducted during the historical period (1901–2005). Models are ranked by a combined metrics approach based on two pattern correlation coefficients (PCCs) and two explained variances for the AO and AD, respectively. In the projected period (2006–2100), most models produce a positive trend for the AO index and a negative trend for the AD index in summer. The models ranked higher based on the combined metrics ranking show greater consistency and smaller values in the magnitudes of trends of AO and AD than the lower-ranked ones. The projected trends in the AO and AD contribute to a slight increase, if not a decrease, of the air temperature and an acceleration of precipitation increase in the twenty-first century over Arctic Alaska, which is the reverse of over the Barents and Kara Seas. Changes in the AO and AD are relatively minor contributing factors to the projected temperature and precipitation changes in the Arctic, among which the changes in the AD play a bigger role than those in the AO. The summer AO and AD have a stronger impact on the spatial asymmetry of the precipitation field than on the air temperature field.
Lei Cai; Vladimir A. Alexeev; John Walsh; Uma S. Bhatt. Patterns, Impacts, and Future Projections of Summer Variability in the Arctic from CMIP5 Models. Journal of Climate 2018, 31, 9815 -9833.
AMA StyleLei Cai, Vladimir A. Alexeev, John Walsh, Uma S. Bhatt. Patterns, Impacts, and Future Projections of Summer Variability in the Arctic from CMIP5 Models. Journal of Climate. 2018; 31 (24):9815-9833.
Chicago/Turabian StyleLei Cai; Vladimir A. Alexeev; John Walsh; Uma S. Bhatt. 2018. "Patterns, Impacts, and Future Projections of Summer Variability in the Arctic from CMIP5 Models." Journal of Climate 31, no. 24: 9815-9833.
Trends and variations of the amount of cold airmass in the Arctic and the Northern Hemisphere are evaluated for the 60 year period, 1959-2018. The two indicators are (1) Polar Cold Air Mass (PCAM), which is the amount of air below a potential temperature threshold, and (2) Negative Heat Content (NHC), which includes a weighting by coldness. Because the metrics of coldness are based on multiple layers in the atmosphere, they provide a more comprehensive framework for assessment of warming than is provided by surface air temperatures alone. The negative trends of PCAM and NHC are stronger (as % per decade) when the threshold is 245 K rather than 280 K, indicating that the loss of extremely cold air is happening at a faster rate than the loss of moderately cold air. The loss of cold air has accelerated, as the most rapid loss of NHC has occurred in recent decades (1989-2018). The spatial patterns of the trends of PCAM and NHC provide another manifestation of Arctic amplification. Of the various teleconnection indices, the Atlantic Multidecadal Oscillation shows the strongest correlations with the spatially integrated metrics of moderate coldness. Several Pacific indices also correlate significantly with these indicators. However, the amount of extremely cold airmass does not correlate significantly with the indices of internal variability used here.
Yuki Kanno; John Walsh; Muhammad Rais Abdillah; Junpei Yamaguchi; Toshiki Iwasaki. Indicators and trends of polar cold airmass. Environmental Research Letters 2018, 14, 025006 .
AMA StyleYuki Kanno, John Walsh, Muhammad Rais Abdillah, Junpei Yamaguchi, Toshiki Iwasaki. Indicators and trends of polar cold airmass. Environmental Research Letters. 2018; 14 (2):025006.
Chicago/Turabian StyleYuki Kanno; John Walsh; Muhammad Rais Abdillah; Junpei Yamaguchi; Toshiki Iwasaki. 2018. "Indicators and trends of polar cold airmass." Environmental Research Letters 14, no. 2: 025006.
Climate warming is expected to disproportionately affect crop yields in the southern United States due to excessive heat stress, while presenting new farming opportunities through a longer growing season farther north. Few studies have investigated the impact of this warming on agro-climate indices that link meteorological data with important field dates in northern regions. This study employs regional dynamical downscaling using the Weather Research and Forecasting (WRF) Model to assess changes in growing season length (GSL), spring planting dates, and occurrences of plant heat stress (PHS) for five regions in Alaska. Differences between future representative concentration pathway 8.5 (RCP8.5; 2011–40, 2041–70, 2071–2100) and historical (1981–2010) periods are obtained using boundary forcing from the Geophysical Fluid Dynamics Laboratory Climate Model, version 3, and the NCAR Community Climate System Model, version 4. The model output is bias corrected using ERA-Interim. Median GSL shows increases of 48–87 days by 2071–2100, with the largest changes in northern Alaska. Similarly, by 2071–2100, planting dates advance 2–4 weeks, and PHS days increase from near 0 to 5–10 instances per summer in the hottest areas. The largest GSL changes occur in the mid- (2041–70) and late century (2071–2100), when a warming signal emerges from the historical interannual variability. These periods coincide with the greatest divergence of the RCPs, suggesting that near-term decision-making may affect substantial future changes. Early-century (2011–40) projections show median GSL increases of 8–27 days, which is close to the historical standard deviation of GSL. Thus, internal variability will remain an important source of uncertainty into the midcentury, despite a trend for longer growing seasons.
Rick Lader; John E. Walsh; Uma S. Bhatt; Peter A. Bieniek. Agro-Climate Projections for a Warming Alaska. Earth Interactions 2018, 22, 1 -24.
AMA StyleRick Lader, John E. Walsh, Uma S. Bhatt, Peter A. Bieniek. Agro-Climate Projections for a Warming Alaska. Earth Interactions. 2018; 22 (18):1-24.
Chicago/Turabian StyleRick Lader; John E. Walsh; Uma S. Bhatt; Peter A. Bieniek. 2018. "Agro-Climate Projections for a Warming Alaska." Earth Interactions 22, no. 18: 1-24.
Alaska has experienced some of the strongest warming rates in the Northern Hemisphere since the mid-20th century. The winter-season warming is especially strong: approximately 4.1 °C since 1950. The atmospheric circulation contributes to interannual variability of Alaska's temperatures through advection and thereby contributes to temperature trends over decadal to multidecadal timescales. In this study, we quantify the contribution of the atmospheric circulation to Alaska's warming by using an analog methodology to identify years with sea level pressure patterns most closely resembling the pressure pattern of each year between 1950 and 2017. The analogs enable a dynamical adjustment of temperature anomalies by removing the contribution of the atmospheric circulation. The dynamical adjustment explains approximately half the variance of Alaska's statewide temperature in winter, and smaller fractions in the other seasons. The unexplained variance, termed the “excess warmth,” shows a systematic increase from 1950 to 2017. The trends in the excess warmth correspond to a warming of 2.1 °C in winter and spring, 1.3 °C in summer, and 0.5 °C in autumn, which are consistent with the trends simulated by global climate models run with historical and projected greenhouse gas concentrations for the same period. The excess warmth accounts for 51% of the Alaska's winter warming and 75% of Alaska's annual mean warming over the 1950–2017 time period.
John E. Walsh; Brian Brettschneider. Attribution of recent warming in Alaska. Polar Science 2018, 21, 101 -109.
AMA StyleJohn E. Walsh, Brian Brettschneider. Attribution of recent warming in Alaska. Polar Science. 2018; 21 ():101-109.
Chicago/Turabian StyleJohn E. Walsh; Brian Brettschneider. 2018. "Attribution of recent warming in Alaska." Polar Science 21, no. : 101-109.
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.
Peter A. Bieniek; Uma S. Bhatt; John E. Walsh; Rick Lader; Brad Griffith; Jennifer K. Roach; Richard L. Thoman. Assessment of Alaska Rain-on-Snow Events Using Dynamical Downscaling. Journal of Applied Meteorology and Climatology 2018, 57, 1847 -1863.
AMA StylePeter A. Bieniek, Uma S. Bhatt, John E. Walsh, Rick Lader, Brad Griffith, Jennifer K. Roach, Richard L. Thoman. Assessment of Alaska Rain-on-Snow Events Using Dynamical Downscaling. Journal of Applied Meteorology and Climatology. 2018; 57 (8):1847-1863.
Chicago/Turabian StylePeter A. Bieniek; Uma S. Bhatt; John E. Walsh; Rick Lader; Brad Griffith; Jennifer K. Roach; Richard L. Thoman. 2018. "Assessment of Alaska Rain-on-Snow Events Using Dynamical Downscaling." Journal of Applied Meteorology and Climatology 57, no. 8: 1847-1863.
Using thresholds of physical climate variables developed from community observations, together with two large-scale datasets, we have produced local indices directly relevant to the impacts of a reduced sea ice cover on Alaska coastal communities. The indices include the number of false freeze-ups defined by transient exceedances of ice concentration prior to a corresponding exceedance that persists, false break-ups, timing of freeze-up and break-up, length of the open water duration, number of days when the winds preclude hunting via boat (wind speed threshold exceedances), the number of wind events conducive to geomorphological work or damage to infrastructure from ocean waves, and the number of these wind events with on- and along-shore components promoting water setup along the coastline. We demonstrate how community observations can inform use of large-scale datasets to derive these locally relevant indices. The two primary large-scale datasets are the Historical Sea Ice Atlas for Alaska and the atmospheric output from a regional climate model used to downscale the ERA-Interim atmospheric reanalysis. We illustrate the variability and trends of these indices by application to the rural Alaska communities of Kotzebue, Shishmaref, and Utqiaġvik (previously Barrow), although the same procedure and metrics can be applied to other coastal communities. Over the 1979–2014 time period, there has been a marked increase in the number of combined false freeze-ups and false break-ups as well as the number of days too windy for hunting via boat for all three communities, especially Utqiaġvik. At Utqiaġvik, there has been an approximate tripling of the number of wind events conducive to coastline erosion from 1979 to 2014. We have also found a delay in freeze-up and earlier break-up, leading to a lengthened open water period for all of the communities examined.
Rebecca J. Rolph; Andrew R. Mahoney; John Walsh; Philip A. Loring. Impacts of a lengthening open water season on Alaskan coastal communities: deriving locally relevant indices from large-scale datasets and community observations. The Cryosphere 2018, 12, 1779 -1790.
AMA StyleRebecca J. Rolph, Andrew R. Mahoney, John Walsh, Philip A. Loring. Impacts of a lengthening open water season on Alaskan coastal communities: deriving locally relevant indices from large-scale datasets and community observations. The Cryosphere. 2018; 12 (5):1779-1790.
Chicago/Turabian StyleRebecca J. Rolph; Andrew R. Mahoney; John Walsh; Philip A. Loring. 2018. "Impacts of a lengthening open water season on Alaskan coastal communities: deriving locally relevant indices from large-scale datasets and community observations." The Cryosphere 12, no. 5: 1779-1790.
The paper summarizes an end-to-end activity connecting the global climate modeling enterprise with users of climate information in Alaska. The effort included retrieval of the requisite observational datasets and model output, a model evaluation and selection procedure, the actual downscaling by the delta method with its inherent bias-adjustment, and the provision of products to a range of users through visualization software that empowers users to explore the downscaled output and its sensitivities. An additional software tool enables users to examine skill metrics and relative rankings of 21 global models for Alaska and six other domains in the Northern Hemisphere. The downscaled temperatures and precipitation are made available as calendar-month decadal means under three different greenhouse forcing scenarios through 2100 for more than 4000 communities in Alaska and western Canada. The visualization package displays the uncertainties inherent in the multi-model ensemble projections. These uncertainties are often larger than the projected changes.
John Walsh; Uma Bhatt; Jeremy S. Littell; Matthew Leonawicz; Michael Lindgren; Thomas A. Kurkowski; Peter A. Bieniek; Richard Thoman; Stephen Gray; T. Scott Rupp. Downscaling of climate model output for Alaskan stakeholders. Environmental Modelling & Software 2018, 110, 38 -51.
AMA StyleJohn Walsh, Uma Bhatt, Jeremy S. Littell, Matthew Leonawicz, Michael Lindgren, Thomas A. Kurkowski, Peter A. Bieniek, Richard Thoman, Stephen Gray, T. Scott Rupp. Downscaling of climate model output for Alaskan stakeholders. Environmental Modelling & Software. 2018; 110 ():38-51.
Chicago/Turabian StyleJohn Walsh; Uma Bhatt; Jeremy S. Littell; Matthew Leonawicz; Michael Lindgren; Thomas A. Kurkowski; Peter A. Bieniek; Richard Thoman; Stephen Gray; T. Scott Rupp. 2018. "Downscaling of climate model output for Alaskan stakeholders." Environmental Modelling & Software 110, no. : 38-51.
The Arctic is a vital component of the global climate, and its rapid environmental evolution is an important element of climate change around the world. To detect and diagnose the changes occurring to the coupled Arctic climate system, a state-of-the-art synthesis for assessment and monitoring is imperative. This paper presents the Arctic System Reanalysis, version 2 (ASRv2), a multiagency, university-led retrospective analysis (reanalysis) of the greater Arctic region using blends of the polar-optimized version of the Weather Research and Forecasting (Polar WRF) Model and WRF three-dimensional variational data assimilated observations for a comprehensive integration of the regional climate of the Arctic for 2000–12. New features in ASRv2 compared to version 1 (ASRv1) include 1) higher-resolution depiction in space (15-km horizontal resolution), 2) updated model physics including subgrid-scale cloud fraction interaction with radiation, and 3) a dual outer-loop routine for more accurate data assimilation. ASRv2 surface and pressure-level products are available at 3-hourly and monthly mean time scales at the National Center for Atmospheric Research (NCAR). Analysis of ASRv2 reveals superior reproduction of near-surface and tropospheric variables. Broadscale analysis of forecast precipitation and site-specific comparisons of downward radiative fluxes demonstrate significant improvement over ASRv1. The high-resolution topography and land surface, including weekly updated vegetation and realistic sea ice fraction, sea ice thickness, and snow-cover depth on sea ice, resolve finescale processes such as topographically forced winds. Thus, ASRv2 permits a reconstruction of the rapid change in the Arctic since the beginning of the twenty-first century–complementing global reanalyses. ASRv2 products will be useful for environmental models, verification of regional processes, or siting of future observation networks.
D. H. Bromwich; A. B. Wilson; L. Bai; Z. Liu; M. Barlage; C.-F. Shih; S. Maldonado; K. M. Hines; S.-H. Wang; J. Woollen; B. Kuo; H.-C. Lin; T.-K. Wee; M. C. Serreze; John Walsh. The Arctic System Reanalysis, Version 2. Bulletin of the American Meteorological Society 2018, 99, 805 -828.
AMA StyleD. H. Bromwich, A. B. Wilson, L. Bai, Z. Liu, M. Barlage, C.-F. Shih, S. Maldonado, K. M. Hines, S.-H. Wang, J. Woollen, B. Kuo, H.-C. Lin, T.-K. Wee, M. C. Serreze, John Walsh. The Arctic System Reanalysis, Version 2. Bulletin of the American Meteorological Society. 2018; 99 (4):805-828.
Chicago/Turabian StyleD. H. Bromwich; A. B. Wilson; L. Bai; Z. Liu; M. Barlage; C.-F. Shih; S. Maldonado; K. M. Hines; S.-H. Wang; J. Woollen; B. Kuo; H.-C. Lin; T.-K. Wee; M. C. Serreze; John Walsh. 2018. "The Arctic System Reanalysis, Version 2." Bulletin of the American Meteorological Society 99, no. 4: 805-828.