[1] Accurately simulating gross primary productivity (GPP) in terrestrial ecosystem models is critical because errors in simulated GPP propagate through the model to introduce additional errors in simulated biomass and other fluxes. We evaluated simulated, daily average GPP from 26 models against estimated GPP at 39 eddy covariance flux tower sites across the United States and Canada. None of the models in this study match estimated GPP within observed uncertainty. On average, models overestimate GPP in winter, spring, and fall, and underestimate GPP in summer. Models overpredicted GPP under dry conditions and for temperatures below 0 C. Improvements in simulated soil moisture and ecosystem response to drought or humidity stress will improve simulated GPP under dry conditions. Adding a low-temperature response to shut down GPP for temperatures below 0 C will reduce the positive bias in winter, spring, and fall and improve simulated phenology. The negative bias in summer and poor overall performance resulted from mismatches between simulated and observed light use efficiency (LUE). Improving simulated GPP requires better leaf-to-canopy scaling and better values of model parameters that control the maximum potential GPP, such as ɛ max (LUE), V cmax (unstressed Rubisco catalytic capacity) or J max (the maximum electron transport rate).

Abstract. We analyzed half-hourly tower-based flux measurements of carbon dioxide (CO2) from a boreal aspen forest and a temperate mixed deciduous forest in Canada to examine the influences of clouds on forest carbon uptake. We showed that the presence of clouds consistently and significantly increased the net ecosystem exchanges (NEE) of CO2 of both forests from the level under clear skies. The enhancement varied with cloudiness, solar elevation angles, and differed between the two forests. For the aspen forest the enhancement at the peak ranged from about 30% for the 200-25 ø interval of solar elevation angles to about 55% for the 550-60 ø interval. For the mixed forest the enhancement at the peak ranged from more than 60% for the 300-35 ø interval of solar elevation angles to about 30% for the 650-70 ø interval. Averaged over solar elevation angles >20 ø , the aspen and mixed forests had the maximal NEE at the irradiance equivalent to 78 and 71% of the clear-sky radiation, respectively. The general patterns of current sky conditions at both sites permit further increases in cloudiness to enhance their carbon uptake. We found that both forests can tolerate exceedingly large reductions of solar radiation (53% for the aspen forest and 46% for the mixed forest) caused by increases in cloudiness without lowering their capacities of carbon uptake. We suggest that the enhancement of carbon uptake under cloudy conditions results from the interactions of multiple environmental factors associated with the presence of clouds. IntroductionClouds, as a natural weather element at a given location, strongly influence environmental conditions on the ground surface via radiative transfer, latent heating, and precipitation [Benner and Curry, 1998]. Therefore it is expected that clouds can have important ramifications on CO2 exchanges between terrestrial ecosystems and the overlying atmosphere.

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Evaporation, drainage, and changes in storage for a bare Plainfield sand were measured with a lysimeter during June, July, and August 1967, under natural rainfall conditions. Cumulative evaporation at any stage was proportional to the square root of time following each heavy rainfall. The drainage rate was found to be an exponential function of water storage. Both relations can be predicted from flow theory with knowledge of soil capillary conductivity, diffusivity, and moisture retention characteristics. Using these two relations and daily rainfall data, the water storage in the top 150 cm was predicted over the season to within 0.3 cm.