Explore the vast range of titles available.

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.

Rotary-wing small unmanned aircraft systems (sUAS) are increasingly being used for sampling thermodynamic and chemical properties of the Earth’s atmospheric boundary layer (ABL) because of their ability to measure at high spatial and temporal resolutions. Therefore, they have the potential to be used for long-term quasi-continuous monitoring of the ABL, which is critical for improving ABL parameterizations and improving numerical weather prediction (NWP) models through data assimilation. Before rotary-wing aircraft can be used for these purposes, however, their performance and the sensors used therein must be adequately characterized. In the present study, we describe recent calibration and validation procedures for thermodynamic sensors used on two rotary-wing aircraft: A DJI S-1000 and MD4-1000. These evaluations indicated a high level of confidence in the on-board measurements. We then used these measurements to characterize the spatiotemporal variability of near-surface (up to 300-m AGL) temperature and moisture fields as a component of two recent field campaigns: The Verification of the Origins of Rotation in Tornadoes Experiment in the Southeast U.S. (VORTEX-SE) in Alabama, and the Land Atmosphere Feedback Experiment (LAFE) in northern Oklahoma.

We present unique observations of a total solar eclipse from a small unmanned aircraft system (sUAS) platform that was operated during the 21 August 2017 North American solar eclipse. The observations were collected near Ten Mile, Tennessee, where eclipse totality lasted 2 min 38 s. A 2-m micrometeorological tripod was erected on-site to measure surface and air temperature, near-surface water vapour, incoming and outgoing shortwave and longwave radiative fluxes, and turbulent fluxes. The sUAS platform and micrometeorological tripod observations indicate significant cooling below a height of 50 m above ground level (a.g.l.) during and shortly after totality. Near-surface temperatures do not return to pre-eclipse values until about 60 min following totality. Above about 50 m a.g.l., smaller temperature changes are observed during the eclipse, as the duration of the eclipse has less influence on deeper boundary-layer turbulence. Additionally, the sensible heat flux becomes slightly negative around totality, and the turbulence kinetic energy and vertical velocity variance concurrently decrease. The evolution of the near-surface meteorological fields are investigated in more detail using a large-eddy simulation (LES) model. The simulations generally reproduce the observations well, in terms of the timing and magnitude of changes in temperature, moisture and sensible and latent heat fluxes. However, the LES model slightly underestimates the diurnal range and decrease in temperature during the eclipse while overestimating the sensible heat fluxes.

The authors wish to make the following correction to this paper [...]

Airborne turbulence measurement gives a spatial distribution of air–surface fluxes that networks of fixed surface sites typically cannot capture. Much work has improved the accuracy of such measurements and the estimation of the uncertainty peculiar to streams of turbulence data measured from the air. A particularly significant challenge and opportunity is to distinguish fluxes from different surface types, especially those occurring in patches smaller than the necessary averaging length. The flux fragment method (FFM), a conditional-sampling variant of eddy covariance in the space–time domain, was presented in 2008. It was shown capable of segregating the mean flux density (CO 2 , H 2 O, sensible heat) in maize from that in soybeans over the patchwork farmlands of Illinois. This was, however, an ideal surface for the method, and the random-error estimate used a relatively rudimentary bootstrap resampling. The present paper describes an upgraded random-error estimate that accounts for the serial correlation of the time/space series and the heterogeneity of the signal. Results are presented from the Alaskan tundra. Though recognized as important, systematic error estimates are not covered in this paper. Some discussion is offered on the relation of the FFM to other approaches similarly motivated, particularly those using wavelets. Successful measurement of the variation of air–surface exchange over heterogeneous surfaces has value for developing and improving process models relating surface flux to remotely sensible quantities, such as the vegetative land-cover type and its condition.

Small environmental research aircraft (ERA) are becoming more common for detailed studies of air–surface interactions. The Sky Arrow 650 ERA, used by multiple groups, is designed to minimize the complexity of high-precision airborne turbulent wind measurement. Its relative wind probe, of a nine-port design, is furthermore used with several other airplanes. This paper gives an overview of 1) calibration of the model that converts the probe’s raw measurements to meteorological quantities; 2) quality control and assurance (QC–QA) in postprocessing of these quantities to compute fluxes; and 3) sensitivity of fluxes to errors in calibration parameters. The model, an adapted version of standard models of potential flow and aerodynamic upwash, is calibrated using an integrated method to derive a globally optimum set of parameters from in-flight maneuvers. Methods of QC–QA from the tower flux community are adopted for use with airborne flux data to provide more objective selection criteria for large datasets. Last, measurements taken from a standard operational flight are used to show fluxes to be most sensitive to calibration parameters that directly affect the vertical wind component. In another test with the same data, varying all calibration parameters simultaneously by ±10% of their optimum values, the model computes a response in the fluxes smaller than 10%, though a larger response may occur if only a subset of parameters is perturbed. A MATLAB toolbox has been developed that facilitates the procedures presented here.

The Best Aircraft Turbulence (BAT) probe is used by multiple research groups worldwide. To promote an accurate interpretation of the data obtained from the probe’s unusual nine-port design, a detailed understanding of the BAT probe’s function along with a characterization and minimization of its systematic anomalies is necessary. This paper describes recent tests to enhance understanding of the probe’s behavior. The tests completed in the Wright Brothers Wind Tunnel at the Massachusetts Institute of Technology (MIT) built on earlier findings at Purdue University. Overall the true-vertical wind relative to the probe was found to have a systematic anomaly of about 10%–15%, an acceptable value borne out by considerable field experience and further reducible by modeling and removing. However, significant departure from theoretical behavior was found, making detailed generalization to other BAT probes still inadvisable. Based on these discoveries, recommendations are made for further experiments to explain the anomalous behavior, reduce the systematic anomaly, and generalize the characterizations.

Upscaling point measurements from micrometeorological towers is a challenging task that is important for a variety of applications, for example, in process studies of convection initiation, carbon and energy budget studies, and the improvement of model parameterizations. In the present study, a technique was developed to determine the horizontal variability in sensible heat flux H surrounding micrometeorological towers. The technique was evaluated using 15-min flux observations, as well as measurements of land surface temperature and air temperature obtained from small unmanned aircraft systems (sUAS) conducted during a one-day measurement campaign. The computed H was found to be comparable to the micrometeorological measurements to within 5–10 W m −2 . Furthermore, when comparing H computed using this technique with H determined using large-eddy simulations (LES), differences of <10 W m −2 were typically found. Thus, implementing this technique using observations from sUAS will help determine sensible heat flux variability at horizontal spatial scales larger than can be provided from flux tower measurements alone.

The microbial by-product nitrous oxide (N2O), a potent greenhouse gas and ozone depleting substance, has conventionally been assumed to have minimal emissions in permafrost regions. This assumption has been questioned by recent in situ studies which have demonstrated that some geologic features in permafrost may, in fact, have elevated emissions comparable to those of tropical soils. However, these recent studies, along with every known in situ study focused on permafrost N2O fluxes, have used chambers to examine small areas (<50 m2). In late August 2013, we used the airborne eddy-covariance technique to make in situ N2O flux measurements over the North Slope of Alaska from a low-flying aircraft spanning a much larger area: around 310 km2. We observed large variability of N2O fluxes with many areas exhibiting negligible emissions. Still, the daily mean averaged over our flight campaign was 3.8 (2.2–4.7) mg N2O m−2 d−1 with the 90 % confidence interval shown in parentheses. If these measurements are representative of the whole month, then the permafrost areas we observed emitted a total of around 0.04–0.09 g m−2 for August, which is comparable to what is typically assumed to be the upper limit of yearly emissions for these regions.

The microbial by-product nitrous oxide (N2O), a potent greenhouse gas and ozone depleting substance, has conventionally been assumed to have minimal emissions in permafrost regions. This assumption has been questioned by recent in situ studies which have demonstrated that some geologic features in permafrost may, in fact, have elevated emissions comparable to those of tropical soils. However, these recent studies, along with every known in situ study focused on permafrost N2O fluxes, have used chambers to examine small areas (<50 m2). In late August 2013, we used the airborne eddy-covariance technique to make in situ N2O flux measurements over the North Slope of Alaska from a low-flying aircraft spanning a much larger area: around 310 km2. We observed large variability of N2O fluxes with many areas exhibiting negligible emissions. Still, the daily mean averaged over our flight campaign was 3.8 (2.2–4.7) mg N2O m-2d-1 with the 90% confidence interval shown in parentheses. If these measurements are representative of the whole month, then the permafrost areas we observed emitted a total of around 0.04–0.09 g m-2 for August, which is comparable to what is typically assumed to be the upper limit of yearly emissions for these regions