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J. Graham Cogley

Abstract

The latitude dependence of water albedo is usually taken from one of a number of tables available in the literature, but these tables all derive from a single series of calculations, made in 1952, for clear series at noon in the middle of each month. This article contains new tables, in which the albedos are averaged over all radiation received at all elevation angles of the sun (also tabulated). The tables are by month and year, for latitudes 0°C (10°) 90° and latitude belts 0–10° (10°) 80–90°, 0–30° (30°) 60–90° and 30–90° One set is based on the Fresnel equation, another on the data of Grishchenko. In the latter set, albedos are 2–4 percentage points higher at low latitudes, and up to 20 points lower near the pole, than those now in use.

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J. Graham Cogley

Abstract

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J. Graham Cogley
and
A. Henderson-Sellers

Abstract

Ten years of hourly data on radiation, cloud and temperature collected at Resolute, Canada (75°N) show that with respect to clear skies: (i) clouds of all types, heights and extents heat the surface when it is snow-covered; (ii) low clouds certainly cool and high clouds probably warm the surface when it is snow-free; (iii) the transition to scattered then broken then complete cloud cover is accompanied, at least over snow-covered surfaces, by mostly monotonic changes in most radiation-balance quantities, including net radiation; (iv) cirriform overcasts alter the surface radiation climate by relatively strong greenhouse heating offset by relatively modest attenuation of solar radiation, and our empirical results help to substantiate recent model calculations of the cirrus greenhouse effect.

There appears to be no difference in the albedo of bare ground between clear-sky and cirriform overcast conditions, but under stratiform overcasts the albedo of bare ground is on average ∼3% below the value for clear-sky conditions. The dependence of snow albedo on solar elevation angle is complex, and we stress the importance of considering seasonal and other forms of variability in snow albedo parameterizations. There is evidence for contamination of the snow at Resolute by soot or dust.

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P. R. Briggs
and
J. Graham Cogley

Abstract

In most weather station networks there are proportionately too few stations at high elevation, and areal estimates of climatological quantities that vary with elevation are biased. Two-dimensional interpolation between stations cannot remove this bias. The topographic bias can be understood, independently of any knowledge of quantities measured at the weather stations, if information is available on station elevations and on the “real” topography. In particular, the bias can be broken down into two components: resolved bias, which is removable by generating an interpolated “fictive topography” from the station topography, and unresolved bias, which remains even after interpolation and is measured by the difference between fictive and real topography. If resolved and unresolved biases differ in sign, the fictive topography is worse than the station topography as an estimate of the real topography. Biases were evaluated for 18 5° × 5° blocks in the contiguous United States, using station elevations from a standard dataset and real elevations from a digital elevation model with ∼8-km spatial resolution. The resolved biases in estimates of average elevation (station minus fictive) range from −197 to +166 m. The unresolved biases (fictive minus real) range from −398 to +10 m. The net biases (station minus real) range from −389 to +18 m. Biases in elevation for blocks with higher relief are substantial. and several have magnitudes exceeding 10% of the magnitude of real elevation. Topographic bias in area] estimates of annual average precipitation was evaluated by fitting linear functions of location and elevation to precipitation data from weather stations. For 15 of the 18 blocks station precipitation was found (with 95% confidence) to increase linearly with station elevation. Fictive and real precipitation were calculated by substituting fictive and real elevation as arguments in these location-elevation functions. Resolved biases in precipitation are small and of variable sign. Unresolved biases in precipitation are also small in low-relief blocks with reasonably representative station topography, but all high-relief blocks have topographically biased networks; the unresolved bias averages −13%, and the net bias −11%, of real precipitation. These biases are comparable with other, better-understood biases in precipitation due to such causes as gauge undercatch, but the methods described here are capable both of identifying and, in principle, of correcting them. Estimates of other important variables, notably temperature, are also likely to he topographically biased in mountainous regions.

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