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Surface-layer parameterizations for heat, mass, momentum, and turbulence exchange are a critical component of the land surface models (LSMs) used in weather prediction and climate models. Although formulations derived from Monin–Obukhov similarity theory (MOST) have long been used, bulk Richardson (Rib) parameterizations have recently been suggested as a MOST alternative but have been evaluated over a limited number of land-cover and climate types. Examining the parameterizations' applicability over other regions, particularly drylands that cover approximately 41% of terrestrial land surfaces, is a critical step toward implementing the parameterizations into LSMs. One year (1 January–31 December 2018) of eddy covariance measurements from a 10-m tower in southeastern Arizona and a 200-m tower in western Texas were used to determine how well the Rib parameterizations for friction velocity ( u * ), sensible heat flux (H), and turbulent kinetic energy (TKE) compare against MOST-derived parameterizations of these quantities. Independent of stability, wind speed regime, and season, the Rib u * and TKE parameterizations performed better than the MOST parameterizations, whereas MOST better represented H. Observations from the 200-m tower indicated that the parameterizations' performance degraded as a function of height above ground. Overall, the Rib parameterizations revealed promising results, confirming better performance than traditional MOST relationships for kinematic (i.e., u * ) and turbulence (i.e., TKE) quantities, although caution is needed when applying the RibH parameterizations to drylands. These findings represent an important milestone for the applicability of Rib parameterizations, given the large fraction of Earth's surface covered by drylands. Significance Statement: Weather forecasting models rely upon complex mathematical relationships to predict temperature, wind, and moisture. Monin–Obukhov similarity theory (MOST) has long been used to forecast these quantities near the land surface, even though MOST's limitations are well known in the scientific community. Researchers have suggested an alternative to MOST called the bulk Richardson (Rib) approach. To allow for the Rib approach to be used in weather forecasting models, the approach needs to be tested over different land-cover and climate types. In this study, we applied the Rib approach to dry areas of the United States and found that the approach better represented turbulence variables than MOST relationships. These findings are an important step toward using Rib relationships in weather forecasting models. [ABSTRACT FROM AUTHOR]

Quantification of the emission rates of various gases from soils at night remains a challenge, confronting climate science (in the case of CO2 and CH4) and agriculture science (for NH3 and N2O, among others). In the stable conditions prevailing at night, concentrations of such emitted gases build up at the surface during the night, with intermittent interruptions commonly attributed to the passage of packets of turbulence. The utility of conventional micrometeorological experimental methods in such circumstances is questionable, and chamber methods have been developed to meet the challenge. Here, a statistical approach is proposed, in which micrometeorological field data are used to replicate the likely characteristics of a chamber experiment, yielding estimates of surface fluxes at the surface itself and not at some height above it. The methodology proposed is developmental at this time, with details intended to correspond to the use of both closed and vented chambers. Its application to three recent field studies is explored: (1) a study of nocturnal CO2 emission from two test areas (one previously tilled and the other not) in Ohio in 2015; (2) a similar experiment conducted in Zimbabwe in 2013 (one area previously tilled and a second left fallow), and (3) an investigation of NH3 effluxes from a crop previously treated with urea ammonium nitrate (UAN), in Illinois in 2014. There are few measurements with which to compare the results presented here, however the values obtained are within the range of available field data. [ABSTRACT FROM AUTHOR]