ALBERT

Description: The present study presents a detailed analysis of the diurnal and monthly cycles the surface boundary layer and of surface energy balance in a sparse natural vegetation canopy on Huancayo observatory (12.04 ∘ S, 75.32 ∘ W, 3313 m ASL), which is located in the central Andes of Perú (Mantaro Valley) during an entire year (May 2018–April 2019). We used a set of meteorological sensors (temperature, relative humidity, wind) installed in a gradient tower 30 m high, a set of radiative sensors to measure all irradiance components, and a set of tensiometers and heat flux plate to measure soil moisture, soil temperatures and soil heat flux. To estimate turbulent energy fluxes (sensible and latent), two flux–gradient methods: the aerodynamic method and the Bowen-ratio energy-balance method were used. The ground heat flux at surface was estimated using a molecular heat transfer equation. The results show minimum mean monthly temperatures and more stable conditions were observed in June and July before sunrise, while maximum mean monthly temperatures in October and November and more unstable conditions in February and March. From May to August inverted water vapor profiles near the surface were observed (more intense in July) at night hours, which indicate a transfer of water vapor as dewfall on the surface. The patterns of wind direction indicate well-defined mountain–valley circulation from south-east to south-west especially in fall–winter months (April–August). The maximum mean monthly sensible heat fluxes were found in June and September while minimum in February and March. Maximum mean monthly latent heat fluxes were found in February and March while minimum in June and July. The surface albedo and the Bowen ratio indicate semi-arid conditions in wet summer months and extreme arid conditions in dry winter months. The comparisons between sensible heat flux ( Q H ) and latent heat flux ( Q E ), estimated by the two methods show a good agreement (R 2 above 0.8). The comparison between available energy and the sum of Q E and Q H fluxes shows a good level of agreement (R 2 = 0.86) with important imbalance contributions after sunrise and around noon, probably by advection processes generated by heterogeneities on the surface around the Huancayo observatory and intensified by the mountain–valley circulation.

Description: The operation of a Remotely Piloted Aircraft System (RPAS) over a hilly area in northern Germany allows inspection of the variability of the profiles of temperature, humidity, and wind speed next to a small hill. Four cases in nearly stationary conditions are analyzed. Two events are windy, one overcast and the other with clear skies, whereas the two other cases have weak winds, one overcast, and one with clear skies and dissipating mist. The profiles are made at five locations surrounding the hill, separated by a distance from each other of 5 km at most, sampling up to 130 m above the ground. The average profiles and their standard deviations indicate that the variability in the windy cases is approximately constant with height, likely linked to the turbulent flow itself, whereas, for the weak wind cases, the variability diminishes with height, and it is probably linked to the surface variability. The variability between soundings is large. The computation of the root mean square error with respect to the average of the soundings for each case shows that the site closest to the average is the one over open terrain and low vegetation, whereas the site in the forest is the farthest from average. Comparison with the profiles to the nearest grid point of the European Centre for Medium-Range Weather Forecasts (ECMWF) model shows that the closest values are provided by the average of the soundings and by the site closest to the average. Despite the small dataset collected during this exercise, the methodology developed here can be used for more cases and locations with the aim to characterize better the local variability in the lower atmosphere. In this sense, a non-dimensional heterogeneity index is proposed to quantify the topographically and thermally induced variability in complex terrain.

Description: The exchange of heat, momentum, and mass in the atmosphere over mountainous terrain is controlled by synoptic-scale dynamics, thermally driven mesoscale circulations, and turbulence. This article reviews the key challenges relevant to the understanding of exchange processes in the mountain boundary layer and outlines possible research priorities for the future. The review describes the limitations of the experimental study of turbulent exchange over complex terrain, the impact of slope and valley breezes on the structure of the convective boundary layer, and the role of intermittent mixing and wave–turbulence interaction in the stable boundary layer. The interplay between exchange processes at different spatial scales is discussed in depth, emphasizing the role of elevated and ground-based stable layers in controlling multi-scale interactions in the atmosphere over and near mountains. Implications of the current understanding of exchange processes over mountains towards the improvement of numerical weather prediction and climate models are discussed, considering in particular the representation of surface boundary conditions, the parameterization of sub-grid-scale exchange, and the development of stochastic perturbation schemes.

Description: After Landsat 8 was launched in 2013, it was observed that for Thermal Infrared sensor (TIRS) bands, radiance from outside of an instrument’s field-of-view produced a non-uniform ghost signal across the focal plane that varied depending on the out-of-scene content (i.e., the stray light effect). A new stray light correction algorithm (SLCA) is currently operational and has been implemented into the United States Geological Survey (USGS) ground system since February 2017. The SLCA has also been applied to reprocess historical Landsat 8 scenes. After approximately two years of SLCA implementation, more land surface temperature (LST) validation studies are required to check the effect of correction in the estimation of LST from different retrieval algorithms. For this purpose, three different LST estimation method algorithms (i.e., the radiative transfer equation (RTE), single-channel algorithm (SCA), and split-window algorithm (SWA)) have been assessed. The study site is located on the campus of the University of Balearic Islands on the island of Mallorca (Spain) in the western Mediterranean Sea. The site is considered a heterogeneous area that is composed of different types of surfaces, such as buildings, asphalt roads, farming areas, sloped terrains, orange fields, almond trees, lawns, and some natural vegetation regions. Data from 21 scenes, which were acquired by the Landsat 8-TIRS sensor and extracted from a 100 × 100 m2 pixel, were used to retrieve the LST with different algorithms; then, they were compared with in situ LST measurements from a broadband thermal infrared radiometer located on the same Landsat 8 pixel. The results show good performances of the three methods, with the SWA showing the lowest observed RMSE (within 1.6–2 K), whereas the SCA applied to the TIRS band 10 (10 µm) was also appropriate, with a RMSE ranging within 2.0–2.3 K. The LST estimates using the RTE algorithm display the highest observed RMSE values (within 2.0–3.6 K) of all of the compared methods, but with an almost unbiased value of −0.1 K for the case of techniques applied to band 10 data. The SWAs are the preferred method to estimate the LST in our study area. However, further validation studies around the world are required.