Elizabeth N. Cassano

Modeled precipitation variability over the Greenland Ice Sheet

On the basis of the evaluation of recent Greenland precipitation studies, some of the deficiencies in the modeled precipitation are probably related to the topographic data employed in modeling. In this paper the modern digital elevation data of Ekholm [1996] is used. If the horizontal pressure gradient force in σ coordinates is separated into its irrotational and rotational parts, which are expressed by the equivalent geopotential and geo-stream-function, respectively, the topographic effect on the precipitation can be accurately modeled. The equivalent geopotential and geo-stream-function are implemented in a fully consistent manner in the generalized ω-equation in this paper. A simplified large-scale condensation without evaporation of condensate is also used. These improvements are combined to yield an improved dynamic method. Two aspects of the precipitation distribution are refined by the improved dynamic method. One is the 10 cm yr−1 contour near Summit, Greenland, and the other is a relative large precipitation area centered near the point (70°N, 49°W). Extensive comparisons are made between the retrieved precipitation and the observed annual accumulation time series from 11 ice core sites on the ice sheet. The modeled precipitation from the original method must use sealers to have a high degree of interannual correspondence between the measured accumulation and the retrieved precipitation, but the retrieved precipitation from the improved method increases at all ice core sites and a good correspondence is obtained without any sealer being required. The spatial average of multiyear mean error ( e¯j) is 11.5 cm yr−1 for the modeled precipitation from the improved method, while that for P from ERA-15 is 14.5 cm yr−1. The total mean error (eM) is 3.0 cm yr−1 for the improved method, while eM for the P from ERA-15 is 4.0 cm yr−1. These two errors show that the precipitation modeled by the improved method is better than the P from ERA-15. Thus the distribution of precipitation over the 11 sites retrieved by the improved dynamic method is considerably refined. Large downward trends in annual amounts are present in the precipitation retrieved by the improved dynamic method for all of Greenland and its southern and central west coastal regions. The modeled precipitation from the improved dynamic method and observed accumulation from ice cores are all in agreement with the Thomas et al. [1999] result that the southern Greenland ice sheet above 2000 m is approximately in balance. It also shows that local thickening and thinning areas of the ice sheet derived by airborne laser altimetry from 1993 to 1999 over the entire Greenland above 2000 m [Krabill et al., 2000] are approximately consistent with precipitation change retrieved by the improved dynamic method.

Case Studies of High Wind Events in Barrow, Alaska: Climatological Context and Development Processes

The Beaufort‐Chukchi cyclones of October 1963 and August 2000 produced the highest winds ever recorded in Barrow, Alaska. In both cases, winds of 25 m s21 were observed with gusts unofficially reported at 33 m s 21. The October 1963 storm caused significant flooding, contaminated drinking water, and interrupted power supplies. The August 2000 storm caused the wreck of a

A Factorial Analysis of Storm Surge Flooding in Barrow, Alaska

6 million dredge, and removed roofs from 40 buildings. Both storms were unusual in that they tracked eastward from the East Siberian Sea into the Chukchi and Beaufort Seas, rather than following a more typical northward track into the Arctic Ocean. This paper addresses, through modeling and analysis, the development processes of these two storms. The October 1963 system was a long-lived, warm core, zonally elongated cyclone that traversed around the Arctic basin through the Canadian Archipelago. The August 2000 system was an open-wave cyclone that dissipated rapidly into a weak, cold core eddy in the Alaskan sector of the Beaufort Sea. Approximating the contributions to development using terms in a quasigeostrophic omega equation, it was found that both storms were characterized by the increasing importance of the convergence of the Q vector (representing differential vorticity advection and thermal advection) in the midtroposphere, at the expense of forcing by the turbulent fluxes of heat, moisture, and momentum in the boundary layer. However, the influence of surface turbulent fluxes in the early stages of development was important, particularly for the August 2000 cyclone, which passed over an extensive coastal lead in the East Siberian Sea. This study concludes that the observed retreat in western Arctic ice cover is unlikely to be an important contributor to increasing cyclonic activity in the region, but that ice retreat north of Eurasia could have an impact.

Synoptic conditions during wintertime temperature extremes in Alaska

Abstract This paper describes work to improve the understanding of the broad range of factors affecting the occurrence of flooding in Barrow, Alaska, using as a basis the series of extreme events that have affected the community over the past 50 years. A numerical weather prediction model and a storm surge inundation model have been applied to the 21 case studies identified in National Weather Service data as high wind events. Based on this simulation work flow, a reduced-form model that adequately describes the flooding response has been developed. Specifically, it was found that when wind is forecast to be greater than 13 m s−1 (30 mph) for at least 20 h, this is the most accurate predictor of the possibility of damaging flood. It was found that wind direction, the magnitude of fetch to the sea ice edge (when present), and maximum wind speed were in contrast relatively small contributors to the likelihood of flooding.

Midlatitude atmospheric responses to Arctic sensible heat flux anomalies in Community Climate Model, Version 4

The large-scale atmospheric state associated with widespread wintertime warm and cold extremes in southern Alaska was identified using 1989 to 2007 European Centre for Medium-Range Weather Forecasts Interim Re-Analysis (ERA-I) data. Extremes were defined as days with the coldest and warmest 1% of daily temperatures. Widespread extreme events were identified for days when at least 25 50 km grid cells in the study domain met the extreme temperature criteria. A total of 55 cold and 74 warm extreme days were identified in 19 winters. Composites of the atmospheric state from 5days before through the day of the extreme events were analyzed to assess the large-scale atmospheric state associated with the extremes. The method of self-organizing maps (SOMs) was used to identify the range of sea level pressure (SLP) patterns present in the ERA-I December–February data, and these SLP patterns were then used to stratify the extreme days by their large-scale atmospheric circulation. Composites for all warm or cold extreme days showed less intense features than those for specific SLP patterns. In all of the composites temperature advection, strongest at 700 hPa, and anomalous longwave radiation were the primary factors that led to the extreme events. The anomalous downwelling longwave radiationwas due to either reduced cloud cover, during cold extremes, or to increased cloud cover, during warm extremes. The SOM composites provided additional insight into the temporal evolution of the extreme days and highlighted different portions of southern Alaska most likely to experience temperature extremes for a given SOM SLP pattern.

Linkages between Arctic summer circulation regimes and regional sea ice anomalies

Possible linkages between Arctic sea ice loss and midlatitude weather are strongly debated in the literature. We analyze a coupled model simulation to assess the possibility of Arctic ice variability forcing a midlatitude response, ensuring consistency between atmosphere, ocean, and ice components. We work with weekly running mean daily sensible heat fluxes with the self-organizing map technique to identify Arctic sensible heat flux anomaly patterns and the associated atmospheric response, without the need of metrics to define the Arctic forcing or measure the midlatitude response. We find that low-level warm anomalies during autumn can build planetary wave patterns that propagate downstream into the midlatitudes, creating robust surface cold anomalies in the eastern United States.

Analysis of WRF extreme daily precipitation over Alaska using self-organizing maps

The downward trend in overall Arctic summer sea ice extent has been substantial, particularly in the last few decades. Departures in ice extent from year to year can be very large, however, in part due to the high variability in summer atmospheric circulation patterns. Anomalies in the Pacific sector ice cover can be partially compensated by anomalies of opposite sign in the Atlantic sector. An assessment of linkages between summer atmospheric patterns and sectoral anomalies in the area of maximum open water north of 70°N demonstrates that there is asymmetry in the mechanisms. Years with low ice extent and high open water fraction are uniformly associated with positive temperature anomalies and southerly flow in both the Atlantic and Pacific sectors. However, years with high extent and low open water fraction in both sectors reveal two dominant mechanisms. Some years with anomalously low maximum open water fraction are associated with negative temperature anomalies and southerly transport—a cool summer pattern that allows ice to persist over larger areas. However, other low open water years are characterized by an “ice factory” mechanism, whereby—even when melting—ice cover is continually replenished by advection from the north.

Classification of synoptic patterns in the western Arctic associated with extreme events at Barrow, Alaska, USA

We analyze daily precipitation extremes from simulations of a polar-optimized version of the Weather Research and Forecasting (WRF) model. Simulations cover 19 years and use the Regional Arctic System Model (RASM) domain. We focus on Alaska because of its proximity to the Pacific and Arctic oceans; both provide large moisture fetch inland. Alaska’s topography also has important impacts on orographically forced precipitation. We use self-organizing maps (SOMs) to understand circulation characteristics conducive for extreme precipitation events. The SOM algorithm employs an artificial neural network that uses an unsupervised training process, which results in finding general patterns of circulation behavior. The SOM is trained with mean sea level pressure (MSLP) anomalies. Widespread extreme events, defined as at least 25 grid points experiencing 99th percentile precipitation, are examined using SOMs. Widespread extreme days are mapped onto the SOM of MSLP anomalies, indicating circulation patterns. SOMs aid in determining high-frequency nodes, and hence, circulations are conducive to extremes. Multiple circulation patterns are responsible for extreme days, which are differentiated by where extreme events occur in Alaska. Additionally, several meteorological fields are composited for nodes accessed by extreme and nonextreme events to determine specific conditions necessary for a widespread extreme event. Individual and adjacent node composites producemore physically reasonable circulations as opposed to composites of all extremes, which include multiple synoptic regimes. Temporal evolution of extreme events is also traced through SOM space. Thus, this analysis lays the groundwork for diagnosing differences in atmospheric circulations and their associated widespread, extreme precipitation events.