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Ross D. Brown

Abstract

Historical and reconstructed snow cover data from stations in Canada, the United States, the former Soviet Union, and the People’s Republic of China were used to reconstruct monthly snow cover extent (SCE) fluctuations over midlatitudinal (∼40°–60°N) regions of North America (NA) and Eurasia back to the early 1900s using an areal snow index approach. The station distribution over NA allowed SCE to be reconstructed back to 1915 for 6 months (November–April), along with estimates of monthly mean snow water equivalent (SWE) from gridded daily snow depth data. Over Eurasia, SCE was able to be reconstructed back to 1922, but major gaps in the station network limited the approach to 3 months (October, March, and April). The reconstruction provided evidence of a general twentieth century increase in NA SCE, with significant increases in winter (December–February) SWE averaging 3.9% per decade. The results are consistent with an observed increasing trend in winter snow depth over Russia and provide further evidence for systematic increases in precipitation over NH midlatitudes. North American spring snow cover was characterized by rapid decreases during the 1980s and early 1990s with a significant long-term decrease in April SWE averaging 4.4% per decade. Eurasia was characterized by a significant reduction in April SCE over the 1922–97 period associated with a significant spring warming. The snow cover reduction was significant at the hemispheric scale with an estimated average NH SCE loss of 3.1 × 106 km2 (100 yr)−1 associated with significant warming of 1.26°C (100 yr)−1 over NH midlatitudinal land areas (40°–60°N). The computed temperature sensitivity of NH April SCE was −2.04 × 106 km2 °C−1. Since 1950, March SCE decreases have become more important than those in April with significant reductions over both continents averaging 8.5 × 106 km2 (100 yr)−1. March was also observed to have experienced the largest warming during the November–April snow season with significant post-1950 warming trends in both continents averaging 4.1°C (100 yr)−1. The hemisphere-wide elevated March snow cover–temperature response is consistent with the position of the snowline over continental grassland vegetation zones where snow cover is relatively shallow and the potential snow cover area–albedo feedback is large.

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Gilbert D. Kinzer and Ross Gunn

Abstract

A theoretical and experimental study of the physical behavior of freely falling waterdrops is carried out. The influence of ventilation and environment upon the evaporation and equilibrium temperature is formulated in quantitative terms.

The theoretical approach emphasizes the vapor and heat transferred to packets of environmental air that make transient contact with the liquid sphere. The basic psychrometric equation is derived for a freely-falling spherical drop. Measurements of the evaporation, equilibrium temperature and time to reach equilibrium were carried out for single drops and compared with theory. Evaporation data are presented for drops from the largest size down to those of cloud size.

New methods and apparatus especially devised to study freely falling drops are described.

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Ross Gunn and Gilbert D. Kinzer

Abstract

The terminal velocities for distilled water droplets falling through stagnant air are accurately determined. More than 1500 droplets of mass from 0.2 to 100,000 micrograms, embracing droplets so small that Stokes' law is obeyed up to and including droplets so large that they are mechanically unstable, were measured by a new method employing electronic techniques. An apparatus for the production of electrically charged artificial water droplets at a controllable rate is described. The over-all accuracy of the mass-terminal-velocity measurements is better than 0.7 per cent.

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D. G. Ross and D. G. Fox

Abstract

This paper describes results from a study to evaluate components of an operational air quality modeling system for complex terrain. In particular, the Cinder Cone Butte (CCB) “modeler's dataset” is used to evaluate the current technique for incorporating terrain influences and atmospheric stability into the system's 3D diagnostic wind-field model.

The wind-field model is used in conjunction with a Gaussian puff model to compare predicted and observed tracer concentrations for different configurations, chosen to highlight the influence of the model's technique for incorporating terrain and atmospheric stability in the final flow field. A quantitative statistical basis, including the use of a bootstrap resampling procedure to estimate confidence limits for the performance measures, is used for the evaluation. The results show that the model's technique for incorporating terrain and atmospheric stability yields a significant improvement in predictive performance. Even when only routinely available input data are used, the performance is shown to be as good as that of models based directly on the CCB dataset itself.

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GROVER D. HUGHES and ROBERT B. ROSS

Abstract

No Abstract Available.

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Richard D. Hunter and Ross K. Meentemeyer

Abstract

Accurately mapped meteorological data are an essential component for hydrologic and ecological research conducted at broad scales. A simple yet effective method for mapping daily weather conditions across heterogeneous landscapes is described and assessed. Daily weather data recorded at point locations are integrated with long-term-average climate maps to reconstruct spatially explicit estimates of daily precipitation and temperature extrema. The method uses ordinary kriging to interpolate base station data spatially into fields of approximately 2-km grain size. The fields are subsequently adjusted by 30-yr-average climate maps [Parameter-Elevation Regression on Independent Slopes Model (PRISM)], which incorporate adiabatic lapse rates, orographic effects, coastal proximity, and other environmental factors. The accuracy assessment evaluated an interpolation-only approach and the new method by comparing predicted and observed values from an independent validation dataset. The results of the accuracy assessment are compared for a 24-yr period for California. For all three weather variables, mean absolute errors (MAE) of the climate-imprint method were considerably smaller than those of the interpolation-only approach. MAE for predicted daily precipitation was ±2.5 mm, with a bias of +0.01. MAE for predicted daily minimum and maximum temperatures were ±1.7° and ±2.0°C, respectively, with corresponding biases of −0.41° and −0.38°C. MAE differed seasonally for all three weather variables, but the method was stable despite variation in the number of base stations available for each day.

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Ross D. Brown and Barry E. Goodison

Abstract

Seasonal snow cover information over southern Canada was reconstructed from daily snowfall and maximum temperature data back to 1915 using a simple mass balance approach with snowmelt estimated via a calibrated temperature index method. The reconstruction method was able to account for 70%–80% of the variance in annual snow cover duration (SCD) over most of southern Canada for the 1955–1992 calibration period. The data were used to construct regional SCD anomaly series in four regions spanning the continent. The regional SCD series were characterized by high interannual variability, with most of the variance concentrated at periods less than 5 years. Spring (MAM) snow cover variability was characterized by a prominent spectral peak with a period of approximately 4 years, which appeared to be linked to tropical Pacific sea surface temperature variability.

There was no evidence of statistically significant long-term trends in snow cover in any of the regions, but the data suggested that winter (DJF) snow cover had increased and spring snow cover had decreased over much of southern Canada. One of the most prominent regional features was a systematic decrease in winter and spring snow cover over the prairies since approximately 1970. However, current low snow cover values in this region are still within the expected range of natural variability. Linear combinations of the regional SCD series, including data from the Great Plains, were able to explain 81% and 75% of the variance in North American winter and spring snow covered area (SCA) over the 1972–1992 period. Reconstructed values of SCA back to 1915 suggested that North American winter snow cover has exhibited a gradual increase of 11.0 × 103 km2 yr−1 during much of this century, while spring snow cover has decreased by an average −6.0 × 103 km2 yr−1. These represent rather small changes in SCA (<10% of current mean SCA over a 100-yr period).

Of the several teleconnection indices investigated, the Pacific-North American (PNA) pattern was observed to exert the strongest influence on snow cover variability; the positive phase of the PNA pattern was associated with reduced snow cover in all seasons over western Canada. The influence of ENSO on snow cover variability was found to be highly variable in both time and space, with lag 0 correlations indicating that El Niño was associated with less snow cover over western Canada. These correlations were much weaker than the PNA pattern. The influence of the North Atlantic oscillation pattern was observed to be mainly confined to winter snow cover variations across the eastern United States and southern Ontario.

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ROBERT B. ROSS and MAURICE D. BLUM

Abstract

No Abstract Available.

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Ross D. Brown and Philip W. Mote

Abstract

A snowpack model sensitivity study, observed changes of snow cover in the NOAA satellite dataset, and snow cover simulations from the Coupled Model Intercomparison Project phase 3 (CMIP3) multimodel dataset are used to provide new insights into the climate response of Northern Hemisphere (NH) snow cover. Under conditions of warming and increasing precipitation that characterizes both observed and projected climate change over much of the NH land area with seasonal snow cover, the sensitivity analysis indicated snow cover duration (SCD) was the snow cover variable exhibiting the strongest climate sensitivity, with sensitivity varying with climate regime and elevation. The highest snow cover–climate sensitivity was found in maritime climates with extensive winter snowfall—for example, the coastal mountains of western North America (NA). Analysis of trends in snow cover duration during the 1966–2007 period of NOAA data showed the largest decreases were concentrated in a zone where seasonal mean air temperatures were in the range of −5° to +5°C that extended around the midlatitudinal coastal margins of the continents. These findings were echoed by the climate models that showed earlier and more widespread decreases in SCD than annual maximum snow water equivalent (SWEmax), with the zone of earliest significant decrease located over the maritime margins of NA and western Europe. The lowest SCD–climate sensitivity was observed in continental interior climates with relatively cold and dry winters, where precipitation plays a greater role in snow cover variability. The sensitivity analysis suggested a potentially complex elevation response of SCD and SWEmax to increasing temperature and precipitation in mountain regions as a result of nonlinear interactions between the duration of the snow season and snow accumulation rates.

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Todd D. Ringler, Ross P. Heikes, and David A. Randall

Abstract

This paper documents the development and testing of a new type of atmospheric dynamical core. The model solves the vorticity and divergence equations in place of the momentum equation. The model is discretized in the horizontal using a geodesic grid that is nearly uniform over the entire globe. The geodesic grid is formed by recursively bisecting the triangular faces of a regular icosahedron and projecting those new vertices onto the surface of the sphere. All of the analytic horizontal operators are reduced to line integrals, which are numerically evaluated with second-order accuracy. In the vertical direction the model can use a variety of coordinate systems, including a generalized sigma coordinate that is attached to the top of the boundary layer. Terms related to gravity wave propagation are isolated and an efficient semi-implicit time-stepping scheme is implemented. Since this model combines many of the positive attributes of both spectral models and conventional finite-difference models into a single dynamical core, it represents a distinctively new approach to modeling the atmosphere’s general circulation.

The model is tested using the idealized forcing proposed by Held and Suarez. Results are presented for simulations using 2562 polygons (approximately 4.5° × 4.5°) and using 10 242 polygons (approximately 2.25° × 2.25°). The results are compared to those obtained with spectral model simulations truncated at T30 and T63. In terms of first and second moments of state variables such as the zonal wind, meridional wind, and temperature, the geodesic grid model results using 2562 polygons are comparable to those of a spectral model truncated at slightly less than T30, while a simulation with 10 242 polygons is comparable to a spectral model simulation truncated at slightly less than T63.

In order to further demonstrate the viability of this modeling approach, preliminary results obtained from a full-physics general circulation model that uses this dynamical core are presented. The dominant features of the DJF climate are captured in the full-physics simulation.

In terms of computational efficiency, the geodesic grid model is somewhat slower than the spectral model used for comparison. Model timings completed on an SGI Origin 2000 indicate that the geodesic grid model with 10 242 polygons is 20% slower than the spectral model truncated at T63. The geodesic grid model is more competitive at higher resolution than at lower resolution, so further optimization and future trends toward higher resolution should benefit the geodesic grid model.

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