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Copyright of Atmosphere -- Ocean (Taylor & Francis Ltd) is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The excavation of snow layers was used to compare observed and modeled plot-scale brightness temperature (TB) values for 19 and 37 GHz, with regard to snow water equivalent (SWE), snow type, grain size, and layered structure, for 3 land cover types acquired near Churchill, Manitoba, Canada in March of 2010. In situ snow geophysical measurements were input to the Helsinki University of Technology (HUT) multi-layer snow emission model, and performance was characterized by RMSE and MBE. Emission scattering from depth hoar was disproportionate to its SWE contribution when compared to other snow types, and it also masked observed scattering contributions from upper snow layers. The simulated and observed TB diverged above 130 mm SWE, as the model did not capture scattering extinction or snowpack emission. These may impact the initial effective grain size optimization process if applied to the GlobSnow SWE assimilation technique. Grain size is optimized to fit emission simulations to TB from satellite observations; the model's continued sensitivity to SWE above observed signal saturation may be attributed to the existing snowpack. These inaccuracies may then be carried forward in the assimilation process, through variance calculations used to weight the contributions of assimilation modules, leading to less accurate SWE retrievals. [ABSTRACT FROM AUTHOR]

Remarkably low mean September sea ice area in the Canadian Arctic Archipelago (CAA) was observed in 2011 (146×103 km2), a record-breaking level that was nearly exceeded in 2012 (150×103 km2). These values were lower than previous September records set in 1998 (200×103 km2) and 2007 (220×103km2), and are ∼ 60% lower than the 1981-2010 mean September climatology. In this study, the processes contributing to the extreme light years of 2011 and 2012 were investigated, compared to previous extreme minima of 1998 and 2007, and contrasted against historic summer seasons with above average September ice area. The 2011 minimum was associated with positive June through September (JJAS) surface air temperature (SAT) and net solar radiation(K" ) anomalies that facilitated rapid melt, coupled with atmospheric circulation that restricted multi-year ice (MYI) inflow from the Arctic Ocean into the CAA. The 2012 minimum was also associated with positive JJAS SAT and K" anomalies with coincident rapid melt, but further ice decline was temporarily mitigated by atmospheric circulation which drove Arctic Ocean MYI inflow into the CAA. Atmospheric circulation was comparable between 2011 and 1998 (impeding Arctic Ocean MYI inflow) and 2012 and 2007 (inducing Arctic Ocean MYI inflow). However, preconditioning was more apparent leading up to 2011 and 2012 than 1998 and 2007. The rapid melt process in 2011 and 2012 was more intense than observed in 1998 and 2007 because of the thinner ice cover being more susceptible to anomalous thermodynamic forcing. The thinner sea ice cover within the CAA in recent years has also helped counteract the processes that facilitate extreme heavy ice years. The recent extreme light years within the CAA are associated with a longer navigation season within the Northwest Passage. [ABSTRACT FROM AUTHOR]

The article offers information on satellite-passive microwave remote sensing which is used for estimating snow water equivalent (SWE) in northern regions. It focuses on coupling of a thermodynamic multilayered snow model with a passive microwave emission model of layered snowpacks for subarctic and arctic snow water equivalent retrievals. It shows that the coupling of the snow and microwave emission models with successive iterations has improved SWE simulations.

Copyright of Atmosphere -- Ocean (Taylor & Francis Ltd) is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The article offers information on the global terrestrial snow cover in 2015. Topics include the significance of the timing of spring snowmelt, anomalies in snow cover extent (SCE) for the 2015 Arctic spring, and evidence of snowmelt across the terrestrial Arctic region. A figure is also presented which shows changes in regional total stored water between 2003-2015.

Regulatory agencies have been investigating a number of alternatives for classifying lakes into hydogeologically and ecologically similar assemblages that will facilitate establishment of attainable water quality standards. Concerns over the ability of traditional statistical classifiers to effectively classify environmental data have led to increasing interest in machine (predictive) learning classification tools such as decision trees. This paper compares the performance (classification strength) of a classification tree-based watershed classification model of Nebraska reservoirs to a discriminant analysis (DA)-based watershed classification system and reservoir classes derived from Omernik's Level IV Ecoregions. The performance of classification tree and DA-based watershed classification methods were also compared with respect to their cross-validation prediction errors. The results suggest that both watershed-based classification approaches (classification tree and DA) were more effective than Omernik's Level IV ecoregions in accounting for observed variations in water quality characteristics of Nebraska reservoirs. Moreover, this study demonstrates the utility of a classification tree algorithm, either as a supplement or alternative to DA, in handling the complexities of watershed variables and classifying Nebraska reservoirs for the purpose of water quality management. The classification tree also provides water resource managers with a useful interpretive classification interface. [ABSTRACT FROM AUTHOR]

Because the Arctic is so integrally connected with the Earth's climate system, there is concern that the recent era of global warming has irreversibly altered the polar sea ice cover. This can have global consequences. However, we need to improve our knowledge of sea ice-atmosphere teleconnections if we are to increase our confidence in such climate change scenarios. In this paper, we apply the method of principal components analysis to twenty years of pentad-averaged Arctic sea ice concentration anomaly data derived from satellite observations to retrieve the most significant spatial and temporal patterns. We then linked these patterns to coincident 500 mb geopotential height (500Z) data. The strongest spatial-temporal ice concentration anomaly pattern over the 1980-1999 period was the phase-shifted anomalies between the Greenland and Barents Seas and the Labrador Sea and in Davis Strait. We found this pattern to be associated with strong low pressure anomalies over the North Atlantic and is significantly correlated with the large-scale atmospheric patterns of the North Atlantic Oscillation and El Niño. Other regions where spatially and temporally consistent patterns of anomalous ice concentrations were identified include the Beaufort Sea, on the Siberian side of the Arctic Basin, and the Sea of Okhotsk. We identify the atmospheric patterns coincident with these anomalies. We conclude that our approach of linking PCA results of ice anomaly data with highly loading 500Z patterns is an effective analysis method. We recommend that this study be extended to link full atmospheric PCA results with the sea ice pentads used here. [ABSTRACT FROM AUTHOR]

Copyright of Atmosphere - Ocean (Canadian Meteorological & Oceanographic Society) is the property of Canadian Meteorological & Oceanographic Society and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Atmosphere - Ocean (Canadian Meteorological & Oceanographic Society) is the property of Canadian Meteorological & Oceanographic Society and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract: Terrestrial snow cover is of significance to global geophysical systems because of its influence on both climatological and hydrological processes. Snow cover acts as a layer which modifies energy exchange between the surface and atmosphere, and as the frozen storage term in the water balance, affecting runoff and streamflow. This review addresses two challenges with regard to snow cover: how to monitor this variable adequately over time, and how to couple trends and variability in snow cover to atmospheric circulation. Developments in remote-sensing technology have provided a range of satellite-derived data products which complement in situ snow measurement procedures. Variability in data spatial resolution and domain, temporal repeatability, time series length and the level of snow-cover information derived (for example, snow extent vs. snow water equivalent) means that data application plays a large role in the utilization of an appropriate dataset. Given the variability in snow-cover data properties, the state of knowledge regarding interactions between snow cover and the atmosphere is similarly mixed. No standardized trends in continental or hemispheric snow cover are evident and the direction of forcing between snow cover and the atmosphere is still ambiguous. Identified associations are typically regional in extent, and statistically moderate in strength, proving cause-and-effect relationships difficult to identify. Future research needs are outlined, with an emphasis on passive-microwave imagery. These data have the necessary characteristics (quantitative estimates of snow-water equivalent, all-weather imaging) to provide the input data to the process based studies necessary to isolate linkages between snow cover and the atmosphere. [ABSTRACT FROM AUTHOR]

Copyright of Atmosphere - Ocean (Canadian Meteorological & Oceanographic Society) is the property of Canadian Meteorological & Oceanographic Society and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The article highlights the changes in terrestrial snow cover in the Arctic in 2013. Topics discussed include the determination of Northern Hemisphere spring snow cover extent (SCE) anomalies, the continued reduction of SCE from the historical mean during May and June, and the snow depth anomalies during the season.