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Processes Controlling the Seasonally Varying Emergence of Forced Arctic Longwave Radiation Changes
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The influence of recent and future climate change on spring Arctic cyclones
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TPSAS-NF1676L-34012-DND
Earth’s climate system is highly interconnected, meaning that changes to the global climate influence the United States climatically and economically. In much the same way as European and Asian financial markets affect the U.S. economy, changes to ice sheet mass and energy flows in the far reaches of the planet affect our climate. Life on Earth is sensitive to climate conditions; human society is especially susceptible due to the climate-vulnerable, complex, and often fragile systems that provide food, water, energy, and security. Observed changes to the global climate affecting the United States include rising global temperatures, diminishing sea ice, melting ice sheets and glaciers, rising sea levels, etc. These documented changes have global economic and national security implications, including for the United States. For example, sea level rise alone is putting $100 billion dollars of U.S. military assets at risk, according to the Dept. of Defense. Arctic climate change continues to outpace the rest of the globe. Over the last 30 years, rapid and, in many cases, unprecedented changes to Arctic temperatures, sea ice, snow cover, land ice, and permafrost have occurred. While the Arctic may seem far away, changes in the Arctic climate system have a global reach, affecting sea level, the carbon cycle, atmospheric winds, ocean currents, and potentially the frequency of extreme weather. This presentation discusses the changes in the observed in the Arctic, the projected changes, and the potential impacts to us living the U.S.
An Observationally-Based Determination of the Arctic Sea Ice-Cloud Feedback Since 2000: Isolating the Arctic Cloud Response to Sea Ice Loss
Arctic sea ice responds to and drives Arctic climate change. The interactions between Arctic sea ice and clouds represent a mechanism through which sea ice can drive climate change. We composite active remote sensing satellite cloud properties for ice-free, marginal ice zone (MIZ), and ice-covered surfaces during MIZ crossing events to investigate the influence of the transition from an ice-covered to an ice-free surface on low-level clouds. We demonstrate that the event-based methodology controls for large-scale meteorological factors and isolates the sea ice effect on clouds. We find larger cloud fraction and total water content below ~1.5 km over ice-free relative to ice-covered surfaces during non-summer months, indicating a low-level cloud sensitivity to Arctic sea ice decline. During summer, results show larger cloud fraction and water content over ice-free surfaces, however the differences are statistically indistinguishable. Evidence is provided that atmospheric thermodynamic profile differences cause the cloud property differences, namely that ice-free footprints are warmer, moister, have more positive surface turbulent fluxes and are less stable than their ice-covered counterparts. Ice-free and ice-covered surface cloud property differences scale with surface temperature differences such that cloud property differences are only found in the presence of a surface temperature difference. We conclude that surface temperature differences modulate the cloud response to sea ice loss through influences on surface turbulent fluxes and lower tropospheric stability. The results imply a positive non-summer sea ice-cloud feedback and that up to a 0.02 cloud fraction and 0.05 g m 3 total water content increase in fall are due to the observed sea ice decline.
Estimating the Arctic Cloud-Sea Ice Feedback With Observations during the EOS Period
Arctic sea ice responds to and drives Arctic climate change. The interactions between Arctic sea ice and clouds represent a mechanism through which sea ice can drive climate change. We composite active remote sensing satellite cloud properties for ice-free, marginal ice zone (MIZ), and ice-covered surfaces during MIZ crossing events to investigate the influence of the transition from an ice-covered to an ice-free surface on low-level clouds. We demonstrate that the event-based methodology controls for large-scale meteorological factors and isolates the sea ice effect on clouds. We find larger cloud fraction and total water content below ~1.5 km over ice-free relative to ice-covered surfaces during non-summer months, indicating a low-level cloud sensitivity to Arctic sea ice decline. During summer, results show larger cloud fraction and water content over ice-free surfaces, however the differences are statistically indistinguishable. Evidence is provided that atmospheric thermodynamic profile differences cause the cloud property differences, namely that ice-free footprints are warmer, moister, have more positive surface turbulent fluxes and are less stable than their ice-covered counterparts. Ice-free and ice-covered surface cloud property differences scale with surface temperature differences such that cloud property differences are only found in the presence of a surface temperature difference. We conclude that surface temperature differences modulate the cloud response to sea ice loss through influences on surface turbulent fluxes and lower tropospheric stability. The results imply a positive non-summer sea ice-cloud feedback and that up to a 0.02 cloud fraction and 0.05 g m 3 total water content increase in fall are due to the observed sea ice decline.
Constraining Arctic Climate Projections of Wintertime Warming With Surface Turbulent Flux Observations and Representation of Surface-Atmosphere Coupling
The drivers of rapid Arctic climate change—record sea ice loss, warming SSTs, and a lengthening of the sea ice melt season—compel us to understand how this complex system operates and use this knowledge to enhance Arctic predictability. Changing energy flows sparked by sea ice decline, spotlight atmosphere-surface coupling processes as central to Arctic system function and its climate change response. Despite this, the representation of surface turbulent flux parameterizations in models has not kept pace with our understanding. The large uncertainty in Arctic climate change projections, the central role of atmosphere-surface coupling, and the large discrepancy in model representation of surface turbulent fluxes indicates that these processes may serve as useful observational constraints on projected Arctic climate change. This possibility requires an evaluation of surface turbulent fluxes and their sensitivity to controlling factors (surface-air temperature and moisture differences, sea ice, and winds) within contemporary climate models (here Coupled Model Intercomparison Project 6). The influence of individual controlling factors and their interactions is diagnosed using a multi-linear regression approach. This evaluation is done for four sea ice loss regimes, determined from observational sea ice loss trends, to control for the confounding effects of natural variability between models and observations. The comparisons between satellite- and model-derived surface turbulent fluxes illustrate that while models capture the general sensitivity of surface turbulent fluxes to declining sea ice and to surface-air gradients of temperature and moisture, substantial mean state biases exist. Specifically, the central Arctic is too weak of a heat sink to the winter atmosphere compared to observations, with implications to the simulated atmospheric circulation variability and thermodynamic profiles. Models were found to be about 50% more efficient at turning an air-sea temperature gradient anomaly into a sensible heat flux anomaly relative to observations. Further, the influence of sea ice concentration on the sensible heat flux is underestimated in models compared to observations. The opposite is found for the latent heat flux variability in models; where the latent heat flux is too sensitive to a sea ice concentration anomaly. Lastly, the results suggest that present-day trends in sea ice retreat regions may serve as suitable observational constraints of projected Arctic warming.
SEARCH Workshop on Large-Scale Atmosphere/Cryosphere Observations
The purpose of the workshop held in Seattle during 27-29 November 2001 was to review existing land, sea ice, and atmospheric observations and the prospect for an Arctic System Reanalysis, through white papers, invited speakers, and panels. A major task for SEARCH was to determine how existing observation systems can be best used and enhanced to understand and anticipate the course of the ongoing changes in the Arctic. The primary workshop conclusion is that there is no cohesion among various Arctic disciplines and data types to form a complete observation set of Arctic change; a second workshop conclusion is that present data sets are vastly underutilized in understanding Arctic change; a third conclusion is that a distributed observing system must accommodate a wide range of spatial patterns of variability.
Space-Based Observations for Understanding Changes in the Arctic-Boreal Zone
Observations taken over the last few decades indicate that dramatic changes are occurring in the ArcticBoreal Zone (ABZ), which are having significant impacts on ABZ inhabitants, infrastructure, flora and fauna, and economies. While suitable for detecting overall change, the current capability is inadequate for systematic monitoring and for improving process based and large scale understanding of the integrated components of the ABZ, which includes the cryosphere, biosphere, hydrosphere, and atmosphere. Such knowledge will lead to improvements in Earth system models, enabling more accurate prediction of future changes and development of informed adaptation and mitigation strategies. In this article, we review the strengths and limitations of current space based observational capabilities for several important ABZ components and make recommendations for improving upon these current capabilities. We recommend an interdisciplinary and stepwise approach to develop a comprehensive ABZ Observing Network (ABZON), beginning with an initial focus on observing networks designed to gain process based understanding for individual ABZ components and systems that can then serve as the building blocks for a comprehensive ABZON.
Space-Based Observations for Understanding Changes in the Arctic-Boreal Zone
Observations taken over the last few decades indicate that dramatic changes are occurring in the ArcticBoreal Zone (ABZ), which are having significant impacts on ABZ inhabitants, infrastructure, flora and fauna, and economies. While suitable for detecting overall change, the current capability is inadequate for systematic monitoring and for improving processbased and largescale understanding of the integrated components of the ABZ, which includes the cryosphere, biosphere, hydrosphere, and atmosphere. Such knowledge will lead to improvements in Earth system models, enabling more accurate prediction of future changes and development of informed adaptation and mitigation strategies. In Duncan et al. (2020), we review the strengths and limitations of current spacebased observational capabilities for several important ABZ components and make recommendations for improving upon these current capabilities. We recommend an interdisciplinary and stepwise approach to develop a comprehensive ABZ Observing Network (ABZON), beginning with an initial focus on observing networks designed to gain processbased understanding for individual ABZ components and systems that can then serve as the building blocks for a comprehensive ABZON.
Projected Regime Shift in Arctic Cloud and Water Vapor Feedbacks
The Arctic climate is changing faster than any other large-scale region on Earth. A variety of positive feedback mechanisms are responsible for the amplification, most of which are linked with changes in snow and ice cover, surface temperature (T(sub s)), atmospheric water vapor (WV), and cloud properties. As greenhouse gases continue to accumulate in the atmosphere, air temperature and water vapor content also increase, leading to a warmer surface and ice loss, which further enhance evaporation and WV. Many details of these interrelated feedbacks are poorly understood, yet are essential for understanding the pace and regional variations in future Arctic change. We use a global climate model (Goddard Institute for Space Studies, Atmosphere-Ocean Model) to examine several components of these feedbacks, how they vary by season, and how they are projected to change through the 21st century. One positive feedback begins with an increase in T(sub s) that produces an increase in WV, which in turn increases the downward longwave flux (DLF) and T(sub s), leading to further evaporation. Another associates the expected increases in cloud cover and optical thickness with increasing DLF and T(sub s). We examine the sensitivities between DLF and other climate variables in these feedbacks and find that they are strongest in the non-summer seasons, leading to the largest amplification in Ts during these months. Later in the 21st century, however, DLF becomes less sensitive to changes in WV and cloud optical thickness, as they cause the atmosphere to emit longwave radiation more nearly as a black body. This regime shift in sensitivity implies that the amplified pace of Arctic change relative to the northern hemisphere could relax in the future.
Revisiting the Potential of Melt Pond Fraction as a Predictor for the Seasonal Arctic Sea Ice Extent Minimum
The rapid change in Arctic sea ice in recent decades has led to a rising demand for seasonal sea ice prediction. A recent modeling study that employed a prognostic melt pond model in a stand-alone sea ice model found that September Arctic sea ice extent can be accurately predicted from the melt pond fraction in May. Here we show that satellite observations show no evidence of predictive skill in May. However, we find that a significantly strong relationship (high predictability) first emerges as the melt pond fraction is integrated from early May to late June, with a persistent strong relationship only occurring after late July. Our results highlight that late spring to mid summer melt pond information is required to improve the prediction skill of the seasonal sea ice minimum. Furthermore, satellite observations indicate a much higher percentage of melt pond formation in May than does the aforementioned model simulation, which points to the need to reconcile model simulations and observations, in order to better understand key mechanisms of melt pond formation and evolution and their influence on sea ice state.
How Will Sea Ice Loss Affect the Greenland Ice Sheet? On the Puzzling Features of Greenland Ice-Core Isotopic Composition
The modern cryosphere, Earth's frozen water regime, is in fast transition. Greenland ice cores show how fast theses changes can be, presenting evidence of up to 15 C warming events over timescales of less than a decade. These events, called Dansgaard/Oeschger (D/O) events, are believed to be associated with rapid changes in Arctic sea ice, although the underlying mechanisms are still unclear. The modern demise of Arctic sea ice may, in turn, instigate abrupt changes on the Greenland Ice Sheet. The Arctic Sea Ice and Greenland Ice Sheet Sensitivity (Ice2Ice Chttps://ice2ice.b.uib.noD) initiative, sponsored by the European Research Council, seeks to quantify these past rapid changes to improve our understanding of what the future may hold for the Arctic. Twenty scientists gathered in Copenhagen as part of this initiative to discuss the most recent observational, technological, and model developments toward quantifying the mechanisms behind past climate changes in Greenland. Much of the discussion focused on the causes behind the changes in stable water isotopes recorded in ice cores. The participants discussed sources of variability for stable water isotopes and framed ways that new studies could improve understanding of modern climate. The participants also discussed how climate models could provide insights into the relative roles of local and nonlocal processes in affecting stable water isotopes within the Greenland Ice Sheet. Presentations of modeling results showed how a change in the source or seasonality of precipitation could occur not only between glacial and modern climates but also between abrupt events. Recent fieldwork campaigns illustrate an important role of stable isotopes in atmospheric vapor and diffusion in the final stable isotope signal in ice. Further, indications from recent fieldwork campaigns illustrate an important role of stable isotopes in atmospheric vapor and diffusion in the final stable isotope signal in ice. This feature complicates the quantitative interpretation of ice core signals but also makes the stable ice isotope signal a more robust regional indicator of climate, speakers noted. Meeting participants agreed that to further our understanding of these relationships, we need more process-focused field and laboratory campaigns.
Arctic Climate and Atmospheric Planetary Waves
Analysis of a fifty-year record (1946-1995) of monthly-averaged sea level pressure data provides a link between the phases of planetary-scale sea level pressure waves and Arctic Ocean and ice variability. Results of this analysis show: (1) a breakdown of the dominant wave I pattern in the late 1960's, (2) shifts in the mean phase of waves 1 and 2 since this breakdown, (3) an eastward shift in the phases of both waves 1 and 2 during the years of simulated cyclonic Arctic Ocean circulation relative to their phases during the years of anticyclonic circulation, (4) a strong decadal variability of wave phase associated with simulated Arctic Ocean circulation changes. Finally, the Arctic atmospheric circulation patterns that emerge when waves 1 and 2 are in their extreme eastern and western positions suggest an alternative approach to determine significant forcing patterns of sea ice and high-latitude variability.
Arctic Climate and Atmospheric Planetary Waves
Analysis of a fifty-year record (1946-1995) of monthly-averaged sea level pressure data provides a link between the phases of planetary-scale sea level pressure waves and Arctic Ocean and ice variability. Results of this analysis show: (1) a breakdown of the dominant wave 1 pattern in the late 1960's, (2) shifts in the mean phase of waves 1 and 2 since this breakdown, (3) an eastward shift in the phases of both waves 1 and 2 during the years of simulated cyclonic Arctic Ocean circulation relative to their phases during the years of anticyclonic circulation, (4) a strong decadal variability of wave phase associated with simulated Arctic Ocean circulation changes. Finally, the Arctic atmospheric circulation patterns that emerge when waves 1 and 2 are in their extreme eastern and western positions suggest an alternative approach for determining significant forcing patterns of sea ice and high-latitude variability.
Climate Drivers of Arctic Tundra Variability and Change Using an Indicators Framework
This study applies an indicators framework to investigate climate drivers of tundra vegetation trends and variability over the 1982–2019 period. Previously known indicators relevant for tundra productivity (summer warmth index (SWI), coastal spring sea-ice (SI) area, coastal summer open-water (OW)) and three additional indicators (continentality, summer precipitation, and the Arctic Dipole (AD): second mode of sea level pressure variability) are analyzed with maximum annual Normalized Difference Vegetation Index (MaxNDVI) and the sum of summer bi-weekly (time-integrated) NDVI (TI-NDVI) from the Advanced Very High Resolution Radiometer time-series. Climatological mean, trends, and correlations between variables are presented. Changes in SI continue to drive variations in the other indicators. As spring SI has decreased, summer OW, summer warmth, MaxNDVI, and TI-NDVI have increased. However, the initial very strong upward trends in previous studies for MaxNDVI and TI-NDVI are weakening and becoming spatially and temporally more variable as the ice retreats from the coastal areas. TI-NDVI has declined over the last decade particularly over High Arctic regions and southwest Alaska. The continentality index (CI) (maximum minus minimum monthly temperatures) is decreasing across the tundra, more so over North America than Eurasia. The relationship has weakened between SI and SWI and TI-NDVI, as the maritime influence of OW has increased along with total precipitation. The winter AD is correlated in Eurasia with spring SI, summer OW, MaxNDVI, TI-NDVI, the CI and total summer precipitation. This winter connection to tundra emphasizes the role of SI in driving the summer indicators. The winter (DJF) AD drives SI variations which in turn shape summer OW, the atmospheric SWI and NDVI anomalies. The winter and spring indicators represent potential predictors of tundra vegetation productivity a season or two in advance of the growing season.
Arctic Radiation-Cloud-Aerosol-Surface Interaction eXperiment (ARCSIX)
The Arctic climate system is amidst a transition. Over the last 40 years, the Arctic sea ice pack has transformed from a predominantly thick, multi-year sea ice to a predominantly thin, seasonal sea ice, termed the “New Arctic”. The observed rapid changes in the Arctic sea ice pack are an integral part of the Arctic Amplification phenomenon and represent a response to and a feedback on global climate change. As a result, the role of the Arctic within the global climate system is changing. Substantial uncertainty exists in our understanding of the atmosphere-surface interactions within the Arctic system, limiting our knowledge of the Arctic’s role in the future climate. Advancing our understanding of the Arctic climate system requires (1) measurements of the coupling between radiative processes and sea ice surface properties during summer sea ice melt; (2) measurements of the processes controlling the predominant Arctic cloud regimes and their properties (Fig. 1); and (3) improvements in the ability to monitor Arctic cloud, radiation, and sea ice processes from space. A key challenge is that thin, low clouds that are radiatively important to the Arctic surface energy budget can go undetected (Fig. 1). The Arctic Radiation-Cloud-Aerosol-Surface-Interaction eXperiment (ARCSIX) is an airborne campaign based at the Pituffik Space Base in Greenland from May-August 2024 sponsored by the National Aeronautics and Space Administration (NASA) to address these needs. ARCSIX consists of two airborne measurement campaigns taking place in two 3-week intervals during the early and late sea ice melt season: late May through early June and late July through early August, respectively. ARCSIX science is guided by three broad science questions that encapsulate the key influences of radiation-cloud-aerosol-sea ice coupling and a remote sensing and modeling objective: Science Question 1 (Radiation): What is the impact of the predominant summer Arctic cloud types on the radiative surface energy budget? Science Question 2 (Cloud Life Cycle): What processes control the evolution and maintenance of the predominant cloud regimes in the summertime Arctic? Science Question 3 (Sea Ice): How do the two-way interactions between surface properties and atmospheric forcings affect the sea ice evolution? Remote Sensing and Modeling Objective: Enhance our long-term space-based monitoring and predictive capabilities of Arctic sea ice, clouds, and aerosols.
Northern Winter Climate Change: Assessment of Uncertainty in CMIP5 Projections Related to Stratosphere-Troposphere Coupling
Future changes in the stratospheric circulation could have an important impact on northern winter tropospheric climate change, given that sea level pressure (SLP) responds not only to tropospheric circulation variations but also to vertically coherent variations in troposphere-stratosphere circulation. Here we assess northern winter stratospheric change and its potential to influence surface climate change in the Coupled Model Intercomparison Project-Phase 5 (CMIP5) multimodel ensemble. In the stratosphere at high latitudes, an easterly change in zonally averaged zonal wind is found for the majority of the CMIP5 models, under the Representative Concentration Pathway 8.5 scenario. Comparable results are also found in the 1% CO2 increase per year projections, indicating that the stratospheric easterly change is common feature in future climate projections. This stratospheric wind change, however, shows a significant spread among the models. By using linear regression, we quantify the impact of tropical upper troposphere warming, polar amplification, and the stratospheric wind change on SLP. We find that the intermodel spread in stratospheric wind change contributes substantially to the intermodel spread in Arctic SLP change. The role of the stratosphere in determining part of the spread in SLP change is supported by the fact that the SLP change lags the stratospheric zonally averaged wind change. Taken together, these findings provide further support for the importance of simulating the coupling between the stratosphere and the troposphere, to narrow the uncertainty in the future projection of tropospheric circulation changes.