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The use of analytical solutions of the diffusion equation for 'footprint prediction' is explored. Quantitative information about the 'footprint', i.e., the upwind area most likely to affect a downwind flux measurement at a given height z, is essential when flux measurements from different platforms, particularly airborne ones, are compared. Analytical predictions are evaluated against numerical Lagrangian trajectory simulations which are detailed in a companion paper (Leclerc and Thurtell, 1990). For neutral stability, the structurally simple solutions proposed by Gash (1986) are shown to be capable of satisfactory approximation to numerical simulations over a wide range of heights, zero displacements and roughness lengths. Until more sophisticated practical solutions become available, it is suggested that apparent limitations in the validity of some assumptions underlying the Gash solutions for the case of very large surface roughness (forests) and tentative application of the solutions to cases of small thermal instability be dealt with by semi-empirical adjustment of the ratio of horizontal wind to friction velocity. An upper limit of validity of these solutions for z has yet to be established.

[1] A wavelet analysis was applied to airborne flux measurements over a boreal ecosystem in Canada to investigate thermally induced mesoscale circulations and turbulent organized structures, which are according to large eddy simulation studies considered as one major reason for the energy balance closure problem. Fluxes of sensible heat, latent heat, carbon dioxide, and ozone were separated into a mesoscale and a small-scale turbulence part to quantify those flux contributions that cannot be captured with singletower measurements. Mesoscale fluxes were comparable in magnitude to the energy balance residuals from ground-based tower measurements close to the flight track. A scale-dependent correlation analysis between the fluxes of different scalar quantities could not justify the common practice of correcting eddy covariance measurements of the sensible and the latent heat flux for the lack of energy balance closure according to the Bowen ratio or of correcting carbon dioxide fluxes according to the energy balance residual.Citation: Mauder, M., R. L. Desjardins, and I. MacPherson (2007), Scale analysis of airborne flux measurements over heterogeneous terrain in a boreal ecosystem,

[1] This analysis uses 40 years of hourly observations of temperature (T), relative humidity (RH), and opaque cloud cover from 14 climate stations across the Canadian Prairies to analyze the diurnal cycle climate, represented by the mean T and RH and their diurnal ranges. From April to October, when incoming shortwave radiation dominates over longwave cooling, maximum temperature and the diurnal ranges of T and RH increase with decreasing opaque cloud cover, while minimum temperature is almost independent of cloud. During the winter period, both maximum and minimum temperatures fall with decreasing cloud, as longwave cooling dominates over the net shortwave flux, which is reduced by the high solar zenith angle and surface reflection by snow. We relate the daily mean opaque cloud cover to the longwave and shortwave cloud forcing and the effective cloud albedo, using multiyear measurements of downward shortwave and longwave fluxes, and longwave fluxes under clear skies from historical weather reanalysis. We provide quadratic fits to compute effective cloud albedo and net longwave fluxes from opaque cloud cover. During the warm season, the daytime rise of temperature is related to the net radiation, and the nighttime fall is related to the net longwave cooling. The diurnal range of T, RH, and all the net radiative fluxes have a quasi-linear dependence on the effective cloud albedo. This gives a seasonal climate perspective on the coupled land-surface system of T, RH, and cloud cover over the Canadian Prairies, and the winter transitions in snowy climates.

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Using data from 13 climate stations on the Canadian Prairies, together with opaque cloud cover and daily snow depth, to analyze the winter climate transitions with snow, we find that a snow cover acts as a fast climate switch. Surface temperature falls by about 10 K with fresh snowfall and rises by a similar amount with snowmelt, while the daily range of relative humidity falls to around 5-15% with snow cover. These are robust climate signals. For every 10% decrease in days with snow cover over the Canadian Prairies, the mean October to April climate is warmer by about 1.4 K. Stratifying by daily mean opaque cloud cover across snow transitions shows the rapid shift within 5 days from a diurnal cycle dominated by shortwave cloud forcing to one dominated by longwave cloud forcing. We calculate the change in the surface radiative budget with snow using surface albedo data from the Moderate Resolution Imaging Spectroradiometer and station longwave data. We find that with the fall-winter snow transitions, the surface radiative heating is reduced by 50 Wm À2 , with 69% coming from the reduced net shortwave flux, resulting from the increased surface albedo and a small increase in effective cloud albedo, and 31% from a reduced incoming longwave flux. This drop in surface radiative heating is sufficient to produce a drop in the surface radiometric skin temperature of 11 K. We find that in winter, the monthly mean diurnal climate is more closely coupled to the diurnal shortwave forcing than the mean diurnal climate.

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[1] This paper uses hourly observations from 1953 to 2011 of temperature, relative humidity, and opaque cloud cover from 14 climate stations across the Canadian Prairies to analyze the impact of agricultural land use change on the diurnal cycle climate, represented by the mean temperature and relative humidity and their diurnal ranges. We show the difference between the years 1953-1991 and 1992-2011. The land use changes have been largest in Saskatchewan where 15-20% of the land area has been converted in the past four decades from summer fallow (where the land was left bare for 1 year) to annual cropping. During the growing season from 20 May to 28 August, relative humidity has increased by about 7%. During the first 2 months, 20 May to 19 July, maximum temperatures and the diurnal range of temperature have fallen by 1.2°C and 0.6°C, respectively, cloud cover has increased by about 4%, reducing surface net radiation by 6 W m À2 , and precipitation has increased. We use the dry-downs after precipitation to separate the impact of cloud cover and show the coupling between evapotranspiration and relative humidity. We estimate, using reanalysis data from ERA-Interim, that increased transpiration from the larger area of cropland has reduced the surface Bowen ratio by 0.14-0.2. For the month on either side of the growing season, cloud cover has fallen slightly; maximum temperatures have increased, increasing the diurnal temperature range and the diurnal range of humidity.