scholarly journals Vertical Profiles of Ozone Concentration Collected by an Unmanned Aerial Vehicle and the Mixing of the Nighttime Boundary Layer over an Amazonian Urban Area

Atmosphere ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 599 ◽  
Author(s):  
Guimarães ◽  
Ye ◽  
Batista ◽  
Barbosa ◽  
Ribeiro ◽  
...  

The nighttime boundary layer was studied in an urban area surrounded by tropical forest by use of a copter-type unmanned aerial vehicle (UAV) in central Amazonia during the wet season. Fifty-seven vertical profiles of ozone concentration, potential temperature, and specific humidity were collected from surface to 500 m above ground level (a.g.l.) at high vertical and temporal resolutions by use of embedded sensors on the UAV. Abrupt changes in ozone concentration with altitude served as a proxy of nighttime boundary layer (NBL) height for the case of a normal, undisturbed, stratified nighttime atmosphere, corresponding to 40% of the cases. The median height of the boundary layer was 300 m. A turbulent mixing NBL constituted 28% of the profiles, while the median height of the boundary layer was 290 m. The remaining 32% of profiles corresponded to complex atmospheres without clear boundary layer heights. The occurrence of the three different cases correlated well with relative cloud cover. The results show that the standard nighttime model widely implemented in chemical transport models holds just 40% of the time, suggesting new challenges in modeling of regional nighttime chemistry. The boundary layer heights were also somewhat higher than observed previously over forested and pasture areas in Amazonia, indicating the important effect of the urban heat island.

Atmosphere ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1371
Author(s):  
Patrícia Guimarães ◽  
Jianhuai Ye ◽  
Carla Batista ◽  
Rafael Barbosa ◽  
Igor Ribeiro ◽  
...  

Nighttime vertical profiles of ozone, PM2.5 and PM10 particulate matter, carbon monoxide, temperature, and humidity were collected by a copter-type unmanned aerial vehicle (UAV) over the city of Manaus, Brazil, in central Amazon during the dry season of 2018. The vertical profiles were analyzed to understand the structure of the urban nighttime boundary layer (NBL) and pollution within it. The ozone concentration, temperature, and humidity had an inflection between 225 and 350 m on most nights, representing the top of the urban NBL. The profile of carbon monoxide concentration correlated well with the local evening vehicular congestion of a modern transportation fleet, providing insight into the surface-atmosphere dynamics. In contrast, events of elevated PM2.5 and PM10 concentrations were not explained well by local urban emissions, but rather by back trajectories that intersected regional biomass burning. These results highlight the potential of the emerging technologies of sensor payloads on UAVs to provide new constraints and insights for understanding the pollution dynamics in nighttime boundary layers in urban regions.


2021 ◽  
Vol 13 (15) ◽  
pp. 2885
Author(s):  
Mei Li ◽  
Zengyuan Li ◽  
Qingwang Liu ◽  
Erxue Chen

Plantation forests play a critical role in forest products and ecosystems. Unmanned aerial vehicle (UAV) remote sensing has become a promising technology in forest related applications. The stand heights will reflect the growth and competition of individual trees in plantation. UAV laser scanning (ULS) and UAV stereo photogrammetry (USP) can both be used to estimate stand heights using different algorithms. Thus, this study aimed to deeply explore the variations of four kinds of stand heights including mean height, Lorey’s height, dominated height, and median height of coniferous plantations using different models based on ULS and USP data. In addition, the impacts of thinned point density of 30 pts to 10 pts, 5 pts, 1 pts, and 0.8 pts/m2 were also analyzed. Forest stand heights were estimated from ULS and USP data metrics by linear regression and the prediction accuracy was assessed by 10-fold cross validation. The results showed that the prediction accuracy of the stand heights using metrics from USP was basically as good as that of ULS. Lorey’s height had the highest prediction accuracy, followed by dominated height, mean height, and median height. The correlation between height percentiles metrics from ULS and USP increased with the increased height. Different stand heights had their corresponding best height percentiles as variables based on stand height characteristics. Furthermore, canopy height model (CHM)-based metrics performed slightly better than normalized point cloud (NPC)-based metrics. The USP was not able to extract exact terrain information in a continuous coniferous plantation for forest canopy cover (CC) over 0.49. The combination of USP and terrain from ULS can be used to estimate forest stand heights with high accuracy. In addition, the estimation accuracy of each forest stand height was slightly affected by point density, which can also be ignored.


2021 ◽  
Author(s):  
Marco A. Franco ◽  
Florian Ditas ◽  
Leslie Ann Kremper ◽  
Luiz A. T. Machado ◽  
Meinrat O. Andreae ◽  
...  

Abstract. New particle formation (NPF), referring to the nucleation of molecular clusters and their subsequent growth into the cloud condensation nuclei (CCN) size range, is a globally significant and climate-relevant source of atmospheric aerosols. Classical NPF exhibiting continuous growth from a few nanometers to the Aitken mode around 60–70 nm is widely observed in the planetary boundary layer (PBL) around the world, but not in central Amazonia. Here, classical NPF events are rarely observed in the PBL, but instead, NPF begins in the upper troposphere (UT), followed by downdraft injection of sub-50 nm (CN< 50) particles into the PBL and their subsequent growth. Central aspects of our understanding of these processes in the Amazon have remained enigmatic, however. Based on more than six years of aerosol and meteorological data from the Amazon Tall Tower Observatory (ATTO, Feb 2014 to Sep 2020), we analyzed the diurnal and seasonal patterns as well as meteorological conditions during 254 of such Amazonian growth events on 217 event days, which show a sudden occurrence of particles between 10 and 50 nm in the PBL, followed by their growth to CCN sizes. The occurrence of events was significantly higher during the wet season, with 88 % of all events from January to June, than during the dry season, with 12 % from July to December, probably due to differences in the condensation sink (CS), atmospheric aerosol load, and meteorological conditions. Across all events, a median growth rate (GR) of 5.2 nm h−1 and a median CS of 0.0011 s−1 were observed. The growth events were more frequent during the daytime (74 %) and showed higher GR (5.9 nm h−1) compared to nighttime events (4.0 nm h−1), emphasizing the role of photochemistry and PBL evolution in particle growth. About 70 % of the events showed a negative anomaly of the equivalent potential temperature (∆θ'e) – as a marker for downdrafts – and a low satellite brightness temperature (Tir) – as a marker for deep convective clouds – in good agreement with particle injection from the UT in the course of strong convective activity. About 30 % of the events, however, occurred in the absence of deep convection, partly under clear sky conditions, and with a positive ∆θ'e anomaly. Therefore, these events do not appear to be related to downdraft injection and suggest the existence of other currently unknown sources of the sub-50 nm particles.


2018 ◽  
Vol 33 (5) ◽  
pp. 1109-1120 ◽  
Author(s):  
David E. Jahn ◽  
William A. Gallus

Abstract The Great Plains low-level jet (LLJ) is influential in the initiation and evolution of nocturnal convection through the northward advection of heat and moisture, as well as convergence in the region of the LLJ nose. However, accurate numerical model forecasts of LLJs remain a challenge, related to the performance of the planetary boundary layer (PBL) scheme in the stable boundary layer. Evaluated here using a series of LLJ cases from the Plains Elevated Convection at Night (PECAN) program are modifications to a commonly used local PBL scheme, Mellor–Yamada–Nakanishi–Niino (MYNN), available in the Weather Research and Forecasting (WRF) Model. WRF forecast mean absolute error (MAE) and bias are calculated relative to PECAN rawinsonde observations. The first MYNN modification invokes a new set of constants for the scheme closure equations that, in the vicinity of the LLJ, decreases forecast MAEs of wind speed, potential temperature, and specific humidity more than 19%. For comparison, the Yonsei University (YSU) scheme results in wind speed MAEs 22% lower but specific humidity MAEs 17% greater than in the original MYNN scheme. The second MYNN modification, which incorporates the effects of potential kinetic energy and uses a nonzero mixing length in stable conditions as dependent on bulk shear, reduces wind speed MAEs 66% for levels below the LLJ, but increases MAEs at higher levels. Finally, Rapid Refresh analyses, which are often used for forecast verification, are evaluated here and found to exhibit a relatively large average wind speed bias of 3 m s−1 in the region below the LLJ, but with relatively small potential temperature and specific humidity biases.


2019 ◽  
Vol 23 (2) ◽  
pp. 1-27 ◽  
Author(s):  
Eugene S. Takle ◽  
Daniel A. Rajewski ◽  
Samantha L. Purdy

Abstract The Iowa Atmospheric Observatory was established to better understand the unique microclimate characteristics of a wind farm. The facility consists of a pair of 120-m towers identically instrumented to observe basic landscape–atmosphere interactions in a highly managed agricultural landscape. The towers, one within and one outside of a utility-scale low-density-array wind farm, are equipped to measure vertical profiles of temperature, wind, moisture, and pressure and can host specialized sensors for a wide range of environmental conditions. Tower measurements during the 2016 growing season demonstrate the ability to distinguish microclimate differences created by single or multiple turbines from natural conditions over homogeneous agricultural fields. Microclimate differences between the two towers are reported as contrasts in normalized wind speed, normalized turbulence intensity, potential temperature, and water vapor mixing ratio. Differences are analyzed according to conditions of no wind farm influence (i.e., no wake) versus wind farm influence (i.e., waked flow) with distance downwind from a single wind turbine or a large group of turbines. Differences are also determined for more specific atmospheric conditions according to thermal stratification. Results demonstrate agreement with most, but not all, currently available numerical flow-field simulations of large wind farm arrays and of individual turbines. In particular, the well-documented higher nighttime surface temperature in wind farms is examined in vertical profiles that confirm this effect to be a “suppression of cooling” rather than a warming process. A summary is provided of how the wind farm boundary layer differs from the natural boundary layer derived from concurrent measurements over the summer of 2016.


2006 ◽  
Vol 19 (17) ◽  
pp. 4198-4206 ◽  
Author(s):  
Benjamin I. Cook ◽  
Gordon B. Bonan ◽  
Samuel Levis

Abstract The effects of increased soil moisture on wet season (October–March) precipitation in southern Africa are investigated using the Community Climate System Model version 3 (CCSM3). In the CTRL case, soil moisture is allowed to interact dynamically with the atmosphere. In the MOIST case, soil moisture is set so that evapotranspiration is not limited by the supply of water. The MOIST scenario actually results in decreased precipitation over the region of perturbed soil moisture, compared to CTRL. The increased soil moisture alters the surface energy balance, resulting in a shift from sensible to latent heating. This manifests in two ways relevant for precipitation processes. First, the shift from sensible to latent heating cools the surface, causing a higher surface pressure, a reduced boundary layer height, and an increased vertical gradient in equivalent potential temperature. These changes are indicative of an increase in atmospheric stability, inhibiting vertical movement of air parcels and decreasing the ability of precipitation to form. Second, the surface changes induce anomalous surface divergence and increased subsidence. This causes a reduction in cloud cover and specific humidity above 700 hPa and results in a net decrease of column-integrated precipitable water, despite the increased surface water flux, indicating a reduction in moisture convergence. Based on this and a previous study, soil moisture may act as a negative feedback to precipitation in southern Africa, helping to buffer the system against any external forcing of precipitation (e.g., ENSO).


2021 ◽  
Vol 1925 (1) ◽  
pp. 012068
Author(s):  
D G Chechin ◽  
A Yu Artamonov ◽  
N Ye Bodunkov ◽  
M Yu Kalyagin ◽  
A M Shevchenko ◽  
...  

2019 ◽  
Vol 12 (5) ◽  
pp. 2139-2153 ◽  
Author(s):  
Hendrik Wouters ◽  
Irina Y. Petrova ◽  
Chiel C. van Heerwaarden ◽  
Jordi Vilà-Guerau de Arellano ◽  
Adriaan J. Teuling ◽  
...  

Abstract. The coupling between soil, vegetation and atmosphere is thought to be crucial in the development and intensification of weather extremes, especially meteorological droughts, heat waves and severe storms. Therefore, understanding the evolution of the atmospheric boundary layer (ABL) and the role of land–atmosphere feedbacks is necessary for earlier warnings, better climate projection and timely societal adaptation. However, this understanding is hampered by the difficulties of attributing cause–effect relationships from complex coupled models and the irregular space–time distribution of in situ observations of the land–atmosphere system. As such, there is a need for simple deterministic appraisals that systematically discriminate land–atmosphere interactions from observed weather phenomena over large domains and climatological time spans. Here, we present a new interactive data platform to study the behavior of the ABL and land–atmosphere interactions based on worldwide weather balloon soundings and an ABL model. This software tool – referred to as CLASS4GL (http://class4gl.eu, last access: 27 May 2018) – is developed with the objectives of (a) mining appropriate global observational data from ∼15 million weather balloon soundings since 1981 and combining them with satellite and reanalysis data and (b) constraining and initializing a numerical model of the daytime evolution of the ABL that serves as a tool to interpret these observations mechanistically and deterministically. As a result, it fully automizes extensive global model experiments to assess the effects of land and atmospheric conditions on the ABL evolution as observed in different climate regions around the world. The suitability of the set of observations, model formulations and global parameters employed by CLASS4GL is extensively validated. In most cases, the framework is able to realistically reproduce the observed daytime response of the mixed-layer height, potential temperature and specific humidity from the balloon soundings. In this extensive global validation exercise, a bias of 10.1 m h−1, −0.036 K h−1 and 0.06 g kg−1 h−1 is found for the morning-to-afternoon evolution of the mixed-layer height, potential temperature and specific humidity. The virtual tool is in continuous development and aims to foster a better process understanding of the drivers of the ABL evolution and their global distribution, particularly during the onset and amplification of weather extremes. Finally, it can also be used to scrutinize the representation of land–atmosphere feedbacks and ABL dynamics in Earth system models, numerical weather prediction models, atmospheric reanalysis and satellite retrievals, with the ultimate goal of improving local climate projections, providing earlier warning of extreme weather and fostering a more effective development of climate adaptation strategies. The tool can be easily downloaded via http://class4gl.eu (last access: 27 May 2018) and is open source.


2019 ◽  
Author(s):  
Hendrik Wouters ◽  
Irina Y. Petrova ◽  
Chiel C. van Heerwaarden ◽  
Jordi Vilà-Guerau de Arellano ◽  
Adriaan J. Teuling ◽  
...  

Abstract. The coupling between soil, vegetation and atmosphere is thought to be crucial in the development and intensification of weather extremes, especially meteorological droughts, heatwaves and severe storms. Therefore, understanding evolution of the atmospheric boundary layer (ABL) and the role of land–atmosphere feedbacks is necessary for earlier warnings, better climate projection and timely societal adaptation. However, this understanding is hampered by the difficulties to attribute cause–effect relationships from complex coupled models, and the irregular space–time distribution of in situ observations of the land–atmosphere system. As such, there is a need for simple deterministic appraisals that systematically discriminate land–atmosphere interactions from observed weather phenomena over large domains and climatological time spans. Here, we present a new interactive data platform to study the behaviour of the ABL and land–atmosphere interactions based on worldwide weather balloon soundings and an ABL model. This software tool – referred to as CLASS4GL (http://class4gl.eu) – is developed with the objectives to (a) mine appropriate global observational data from over 2 million weather balloon soundings since 1981 and combine them with satellite and reanalysis data, and (b) constrain and initialize a numerical model of the daytime evolution of the ABL that serves as a tool to interpret these observations mechanistically and deterministically. As a result, it fully automises extensive global model experiments to assess the effects of land and atmospheric conditions on the ABL evolution as observed in different climate regions around the world. The suitability of the set of observations, model formulations and global parameters employed by CLASS4GL is extensively validated. In most cases, the framework is able to realistically reproduce the observed daytime response of the ABL height, potential temperature and specific humidity from the balloon soundings. In this extensive global validation exercise, a bias of 0.2 m h−1, −0.052 K h−1 and 0.07 g kg−1 h−1 is found for the morning-to-afternoon evolution of the ABL height, potential temperature and specific humidity. The virtual tool is in continuous development, and aims to foster a better process-understanding of the drivers of the ABL evolution and their global distribution, particularly during the onset and amplification of weather extremes. Finally, it can also be used to scrutinize the representation of land–atmosphere feedbacks and ABL dynamics in Earth system models, numerical weather prediction models, atmospheric reanalysis, and satellite retrievals, with the ultimate goal to improve local climate projections, provide earlier warning of extreme weather, and foster a more effective development of climate adaptation strategies. The tool can be easily downloaded via http://class4gl.eu and is open source.


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