ALBERT

Description: Abrupt cold events have been detected in numerous North Atlantic climate records from the Holocene. Several mechanisms have been discussed as possible triggers for these climate shifts persisting decades to centuries. Here, we describe two abrupt cold events that occurred during an orbitally forced transient Holocene simulation using the Community Climate System Model version 3. Both events occurred during the late Holocene (4305-4267 BP and 3046-3018 BP, respectively). They were characterized by substantial surface cooling (-2.3 and -1.8 °C, respectively) and freshening (-0.6 and -0.5 PSU, respectively) as well as severe sea ice advance east of Newfoundland and south of Greenland, reaching as far as the Iceland Basin in the northeastern Atlantic at the climaxes of the cold events. Convection and deep-water formation in the northwestern Atlantic collapsed during the events, while the Atlantic Meridional Overturning Circulation was not substantially affected (weakening by only about 10% and 5%, respectively). The events were triggered by prolonged phases of a positive North Atlantic Oscillation caused substantial changes in the sub-polar ocean circulation and associated freshwater transports, resulting in a weakening of the sub-polar gyre. Our results suggest a possible mechanism by which abrupt cold events in the North Atlantic region may be triggered by internal climate variability without the need of an external (e.g. solar or volcanic) forcing.

Description: The impact of a subgrid-scale ice thickness distribution (ITD) and two standard ice strength formulations on simulated Arctic sea ice climate is investigated. To this end different model configurations with and without an ITD were tuned by minimizing the weighted mean error between the simulated and observed sea ice concentration, thickness and drift speed with an semi-automatic parameter optimization routine. The standard ITD and ice strength parameterization lead to larger errors when compared to the simple single-category model with an ice strength parameterization based on the mean ice thickness. Interestingly, the simpler ice strength formulation, which depends linearly on the mean ice thickness, also reduces the model-observation error when using an ITD. For the ice strength parameterization that makes use of the ITD, the effective ice strength depends strongly on the number of thickness categories, so that introducing more categories can lead to overall thicker ice that is more easily deformed.

Description: The patterns of sea ice retreat in the Arctic Ocean are investigated using two global climate models (GCMs) that have profound differences in their large-scale mean winter atmospheric circulation and sea ice drift patterns. The Community Earth System Model Large Ensemble (CESM-LE) presents a mean sea level pressure pattern that is in general agreement with observations for the late twentieth century. The Community Climate System Model, version 4 (CCSM4), exhibits a low bias in its mean sea level pressure over the Arctic region with a deeper Icelandic low. A dynamical mechanism is presented in which large-scale mean winter atmospheric circulation has significant effect on the following September sea ice extent anomaly by influencing ice divergence in specific areas. A Lagrangian model is used to backtrack the 80°N line from the approximate time of the melt onset to its prior positions throughout the previous winter and quantify the divergence across the Pacific and Eurasian sectors of the Arctic. It is found that CCSM4 simulates more sea ice divergence in the Beaufort and Chukchi Seas and less divergence in the Eurasian seas when compared to CESM-LE, leading to a Pacific-centric sea ice retreat. On the other hand, CESM-LE shows a more symmetrical retreat between the Pacific, Eurasian, and Atlantic sectors of the Arctic. Given that a positive trend in the Arctic Oscillation (AO) index, associated with low sea level pressure anomalies in the Arctic, is a robust feature of GCMs participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5), these results suggest that the sea ice retreat in the Pacific sector could be amplified during the transition to a seasonal ice cover.

Description: An important aspect of understanding the impacts of climate change on society is determining how the distribution of weather regimes will change. Arctic amplification results in greater warming over the Arctic compared to the midlatitudes, and this study examines how patterns of Arctic air masses will be affected. The authors employ the Community Earth System Model Large Ensemble (CESM-LE) RCP 8.5, consisting of 30 ensemble members run through the twenty-first century. Self-organizing maps are used to define archetypes of 850-hPa equivalent potential temperature anomalies with respect to a changing climate and assess changes in their frequency of occurrence. In the model, a pattern with negative anomalies over the central Arctic becomes less frequent in the future. There is also an increase in the frequency of patterns associated with an amplified ridge (trough) with positive (negative) anomalies over western (eastern) North America. It is hypothesized that the increase in frequency of such patterns is the result of enhanced forcing of baroclinic waves owing to reduced sea ice over the western Arctic. There is also a decline in patterns that have anomalously high over the North Atlantic, a pattern that is associated with intense ridging in the 500-hPa flow over the North Atlantic and colder over Europe. The authors relate the decrease of these patterns to an enhancement of the North Atlantic jet induced by a warming deficit in the North Atlantic Ocean.

Description: This study compares the accuracy of visually estimated ice concentrations by eight analysts at the Canadian Ice Service with three standards: (i) ice concentrations calculated from automated image segmentation, (ii) ice concentrations calculated from automated image segmentation that were validated by the analysts, and (iii) the modal ice concentration estimate by the group. A total of 76 predefined areas in 67 RADARSAT-2 images are used in this study. Analysts overestimate ice concentrations when compared to all three standards, most notably for low ice concentrations (1/10–3/10). The spread of ice concentration estimates is highest for middle concentrations (5/10, 6/10) and smallest for the 9/10 ice concentration. The overestimation in low concentrations and high variability in middle concentrations introduce uncertainty into the ice concentration distribution in ice charts. The uncertainty may have downstream implications for numerical modelling and sea ice climatology. Inter-analyst agreement is also measured to determine which classifier's ice concentration estimates (analyst or automated image segmentation) disagreed the most. It was found that one of the eight analysts disagreed the most, followed second by the automated segmentation algorithm. This suggests high agreement in ice concentration estimates between analysts at the Canadian Ice Service. The high agreement, but consistent overestimation, results in an overall accuracy of ice concentration estimates in polygons to be 39 %, 95 % CI [34 %, 43 %], for an exact match in the ice concentration estimate with calculated ice concentration from segmentation and, 84 %, 95 % CI [80 %, 87 %], for the ±1 ice concentration category. Only images with high contrast between ice and open water and well-defined floes are used: true accuracy is expected to be lower than what is found in this study.

Description: The impact of Arctic sea ice concentrations, surface albedo, cloud fraction, and cloud ice and liquid water paths on the surface shortwave (SW) radiation budget is analyzed in the twentieth-century simulations of three coupled models participating in the Intergovernmental Panel on Climate Change Fourth Assessment Report. The models are the Goddard Institute for Space Studies Model E-R (GISS-ER), the Met Office Third Hadley Centre Coupled Ocean–Atmosphere GCM (UKMO HadCM3), and the National Center for Atmosphere Research Community Climate System Model, version 3 (NCAR CCSM3). In agreement with observations, the models all have high Arctic mean cloud fractions in summer; however, large differences are found in the cloud ice and liquid water contents. The simulated Arctic clouds of CCSM3 have the highest liquid water content, greatly exceeding the values observed during the Surface Heat Budget of the Arctic Ocean (SHEBA) campaign. Both GISS-ER and HadCM3 lack liquid water and have excessive ice amounts in Arctic clouds compared to SHEBA observations. In CCSM3, the high surface albedo and strong cloud SW radiative forcing both significantly decrease the amount of SW radiation absorbed by the Arctic Ocean surface during the summer. In the GISS-ER and HadCM3 models, the surface and cloud effects compensate one another: GISS-ER has both a higher summer surface albedo and a larger surface incoming SW flux when compared to HadCM3. Because of the differences in the models’ cloud and surface properties, the Arctic Ocean surface gains about 20% and 40% more solar energy during the melt period in the GISS-ER and HadCM3 models, respectively, compared to CCSM3. In twenty-first-century climate runs, discrepancies in the surface net SW flux partly explain the range in the models’ sea ice area changes. Substantial decrease in sea ice area simulated during the twenty-first century in CCSM3 is associated with a large drop in surface albedo that is only partly compensated by increased cloud SW forcing. In this model, an initially high cloud liquid water content reduces the effect of the increase in cloud fraction and cloud liquid water on the cloud optical thickness, limiting the ability of clouds to compensate for the large surface albedo decrease. In HadCM3 and GISS-ER, the compensation of the surface albedo and cloud SW forcing results in negligible changes in the net SW flux and is one of the factors explaining moderate future sea ice area trends. Thus, model representations of cloud properties for today’s climate determine the ability of clouds to compensate for the effect of surface albedo decrease on the future shortwave radiative budget of the Arctic Ocean and, as a consequence, the sea ice mass balance.

Description: This study focuses on errors in extreme precipitation in gridded station products incurred during the upscaling of station measurements to a grid, referred to as representativeness errors. Gridded precipitation station analyses are valuable observational data sources with a wide variety of applications, including model validation. The representativeness errors associated with two gridding methods are presented, consistent with either a point or areal average interpretation of model output, and it is shown that they differ significantly (up to 30%). An experiment is conducted to determine the errors associated with station density, through repeated gridding of station data within the United States using subsequently fewer stations. Two distinct error responses to reduced station density are found, which are attributed to differences in the spatial homogeneity of precipitation distributions. The error responses characterize the eastern and western United States, which are respectively more and less homogeneous. As the station density decreases, the influence of stations farther from the analysis point increases, and therefore, if the distributions are inhomogeneous in space, the analysis point is influenced by stations with very different precipitation distributions. Finally, ranges of potential percent representativeness errors of the median and extreme precipitation across the United States are created for high-resolution (0.25°) and low-resolution areal averaged (0.9° lat × 1.25° lon) precipitation fields. For example, the range of the representativeness errors is estimated, for annual extreme precipitation, to be from +16% to −12% in the low-resolution data, when station density is 5 stations per 0.9° lat × 1.25° lon grid box.