Intercomparison of In Situ Sensors for Ground-Based Land Surface Temperature Measurements.

Land surface temperature (LST) is a key variable in the determination of land surface energy exchange processes from local to global scales. Accurate ground measurements of LST are necessary for a number of applications including validation of satellite LST products or improvement of both climate and numerical weather prediction models. With the objective of assessing the quality of in situ measurements of LST and to evaluate the quantitative uncertainties in the ground-based LST measurements, intensive field experiments were conducted at NOAA's Air Resources Laboratory (ARL)'s Atmospheric Turbulence and Diffusion Division (ATDD) in Oak Ridge, Tennessee, USA, from October 2015 to January 2016. The results of the comparison of LSTs retrieved by three narrow angle broadband infrared temperature sensors (IRT), hemispherical longwave radiation (LWR) measurements by pyrgeometers, forward looking infrared camera with direct LSTs by multiple thermocouples (TC), and near surface air temperature (AT) are presented here. The brightness temperature (BT) measurements by the IRTs agreed well with a bias of <0.23 °C, and root mean square error (RMSE) of <0.36 °C. The daytime LST(TC) and LST(IRT) showed better agreement (bias = 0.26 °C and RMSE = 0.67 °C) than with LST(LWR) (bias > 1.1 and RMSE > 1.46 °C). In contrast, the difference between nighttime LSTs by IRTs, TCs, and LWR were <0.47 °C, whereas nighttime AT explained >81% of the variance in LST(IRT) with a bias of 2.64 °C and RMSE of 3.6 °C. To evaluate the annual and seasonal differences in LST(IRT), LST(LWR) and AT, the analysis was extended to four grassland sites in the USA. For the annual dataset of LST, the bias between LST (IRT) and LST (LWR) was <0.7 °C, except at the semiarid grassland (1.5 °C), whereas the absolute bias between AT and LST at the four sites were <2 °C. The monthly difference between LST (IRT) and LST (LWR) (or AT) reached up to 2 °C (5 °C), whereas half-hourly differences between LSTs and AT were several degrees in magnitude depending on the site characteristics, time of the day and the season.

CO2 exchange and evapotranspiration across dryland ecosystems of southwestern North America.

Global-scale studies suggest that dryland ecosystems dominate an increasing trend in the magnitude and interannual variability of the land CO2 sink. However, such analyses are poorly constrained by measured CO2 exchange in drylands. Here we address this observation gap with eddy covariance data from 25 sites in the water-limited Southwest region of North America with observed ranges in annual precipitation of 100-1000 mm, annual temperatures of 2-25°C, and records of 3-10 years (150 site-years in total). Annual fluxes were integrated using site-specific ecohydrologic years to group precipitation with resulting ecosystem exchanges. We found a wide range of carbon sink/source function, with mean annual net ecosystem production (NEP) varying from -350 to +330 gCm-2 across sites with diverse vegetation types, contrasting with the more constant sink typically measured in mesic ecosystems. In this region, only forest-dominated sites were consistent carbon sinks. Interannual variability of NEP, gross ecosystem production (GEP), and ecosystem respiration (Reco ) was larger than for mesic regions, and half the sites switched between functioning as C sinks/C sources in wet/dry years. The sites demonstrated coherent responses of GEP and NEP to anomalies in annual evapotranspiration (ET), used here as a proxy for annually available water after hydrologic losses. Notably, GEP and Reco were negatively related to temperature, both interannually within site and spatially across sites, in contrast to positive temperature effects commonly reported for mesic ecosystems. Models based on MODIS satellite observations matched the cross-site spatial pattern in mean annual GEP but consistently underestimated mean annual ET by ~50%. Importantly, the MODIS-based models captured only 20-30% of interannual variation magnitude. These results suggest the contribution of this dryland region to variability of regional to global CO2 exchange may be up to 3-5 times larger than current estimates.

Measurement of trace gas fluxes over an unfertilized agricultural field using the flux-gradient technique.

Trace gas fluxes exhibit extensive spatial and temporal variability that is dependent on a number of factors, including meteorology, ambient concentration, and emission source size. Previous studies have found that agricultural fertilization contributes to higher fluxes of certain gases. The magnitude of trace gas fluxes over unfertilized crops is still uncertain. In the present study, deposition of ammonia (NH), nitric acid (HNO), and sulfur dioxide (SO) was measured over unfertilized soybean using the flux-gradient technique. The eddy diffusivity was estimated from eddy covariance measurements of temperature fluxes, resulting in K of 0.64 ± 0.30 m s. Flux means and standard deviations were -0.14 ± 0.13, -0.22 ± 0.19, and -0.38 ± 0.54 µg m s for NH, HNO, and SO, respectively. Low concentrations of NH and HNO increased the relative uncertainties in the deposition velocities estimated from measured fluxes. This contributed to dissimilarities between deposition velocities estimated from the resistance analogy and deposition velocities estimated from fluxes. However, wet canopy conditions during the study may have led to an underestimation of deposition by the resistance analogy because the resistance method does not accurately describe the enhanced deposition rates that occur after dew formation. Quantification of vegetation characteristics, such as leaf wetness and apoplast chemistry, would be beneficial in future studies to more accurately determine stomatal resistance and its influence on fluxes.

Sub-canopy deposition of ozone in a stand of cutleaf coneflower.

Although there has been a great deal of research on ozone, interest in exposure of native, herbaceous species is relatively recent and it is still not clear what role the pollutant has in their ecological fitness. The ozone exposure of a plant is usually expressed in terms of the concentration above the canopy or as a time-weighted index. However, to understand the physiological effects of ozone it is necessary to quantify the ozone flux to individual leaves as they develop, which requires knowing the deposition velocity and concentration of the pollutant as a function of height throughout the plant canopy. We used a high-order closure model of sub-canopy turbulence to estimate ozone profiles in stands of cutleaf coneflower (Rudbeckia laciniata L.) located in the Great Smoky Mountains National Park, USA. The model was run for periods coinciding with a short field study, during which we measured vertical concentration profiles of ozone along with measurements of atmospheric turbulence and other meteorological and plant variables. Predictions of ozone profiles by the model are compared with observations throughout the canopy.