Soil surface roughness in the U.S. Corn Belt varies outside of the growing season due to rainfall and soil management activities such as tillage. This is not consistent with the assumption that roughness is a static parameter in the Soil Moisture Active Passive (SMAP) soil moisture retrieval algorithm. SMAPVEX16-IA, an extensive field campaign focused on calibration of SMAP retrievals in croplands, occurred during a period when roughness is theoretically at a minima. Satellite-scale measurements of rms height and correlation length collected via pinboard, gridboard, and lidar methodologies resulted in a ensemble of model roughness coefficients that, at h = [0.13, 0.97], is significantly rougher than the original SMAP assumption in croplands of h = 0.108. Comparing simulated brightness temperatures using the ensemble h to SMAP observations resulted in a best-fit angular sensitivity coefficient of N = -2 for both horizontal and vertical polarizations. Satellite-scale h is then retrieved for a four-year study period (excluding growing seasons) via the single channel algorithm from SMAP brightness temperatures and in situ observations of soil moisture and temperature. Roughness retrievals are highly variable in the spring as rainfall events decrease h followed by an increase during soil dry-down; h steadily increases in the fall post-harvest as fields are tilled across the network. Retrievals of h are effectively independent of polarization and demonstrate the potential to simultaneously retrieve soil moisture and roughness in the absence of crops. These soil roughness retrievals could provide new information on tillage and other soil management activities.

Estimation of daily evapotranspiration (ET) over cloudy regions highly desires models which rely on meteorological data only. Notwithstanding, the conventional crop coefficient (K-c) method requires detailed knowledge of geo/biophysical properties of the coupled land-vegetation system, precipitation, and soil moisture. Six Eddy Covariance (EC) towers in Iowa, California and New Hampshire of the USA (covering corn, soybeans, prairie, and deciduous forest) were selected. Investigation on 6 years (2007-2012) 15-min micrometeorological records of these sites revealed that there is an indubitable strong interaction between relative humidity (RH), reference ET (ETo), and actual ET at different timescales. This allowed to bypass the need for the non-meteorological inputs and express K-c as a second-order polynomial function of RH and ETo, the ambient regression evapotranspiration model (AREM). The coefficients of the empirical function are crop-specific and may require calibration over different soil types. The mean absolute percentage error (MAPE) of the regression against daily EC observations was 17% during the growing season, and 32% throughout the year with root mean square error (RMSE) of 0.74 mm day(-1) and coefficient of determination of 0.71. The model was fully operational (MAPE of 34% and RMSE of 0.82 mm day(-1)) over the four Iowan sites based on inputs from local weather stations and NLDAS-2 forcing data of NASA. AREM was capable of capturing the dynamics of ET at 15-min and daily timescales irrespective of varying complexities associated with biophysical, geophysical and climatological states.

NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract 1793 Interactive Remote-Controlled Experiment for Instruction in Fluid Mechanics M. Muste, A. Kruger, W. Eichinger, M. Wilson, T. Xing IIHR- Hydroscience & Engineering, The University of Iowa Abstract Just as the Internet has transformed communication and scientific research over the last decade, it is changing industry, commerce, social exchange, and education all over the world. Today engineers control complex systems that may have components in widely separated geographic locations all remotely controlled over Internet. In education, new avenues and methods for enhancing the overall learning experience as well as expanded educational opportunities for a larger pool of students have been enabled by the Internet. One such example is a remotely- accessed instructional laboratory experiment. Initial remote access development has been in the fields of computer science and electrical engineering where the Internet and related infrastructure are part of the curricula. Currently, these advancements are being adapted into engineering programs where a “hands-on” laboratory approach is essential. This paper presents a "proof-of-concept" remote-controlled experiment developed at IIHR- Hydroscience & Engineering (formerly the Iowa Institute of Hydraulic Research) to illustrate a concept for an introductory undergraduate engineering course in fluids mechanics at The College of Engineering, The University of Iowa. The interactive, real-time fluid viscosity experiment allows individuals or groups of students to initiate, conduct, and conclude the laboratory experiment using physical hardware (http://vfl.iihr.uiowa.edu/atac/viscosity.html) from practically any place, at any time. Beyond the interactive learning environment and the related information (handout, experimental procedures, design and construction considerations, etc), the experiment is complemented with additional teaching aids (visualizations, course material, relevant Internet links, applets, etc.) to make it a stand-alone and tutorial assignment that can be accessed independently of the class lectures. This paper demonstrates that remote experimentation in conjunction with additional resources is a viable option for instruction in fluid mechanics by efficiently supplementing the on campus instruction and considerably assisting distance learning and non-traditional student education. Proceedings of the 2004 American Society for Engineering Education Annual Conference & Exposition Copyright © 2004, American Society for Engineering Education

We report on the design, construction and performance of a polarization Raman lidar, built for atmospheric monitoring in the Vipava valley in SW Slovenia, a regional air pollution hot-spot where aerosols are expected to originate from a number of different sources. Its key features are automatized remote operation capability and indoor deployment, which provide high duty cycle in all weather conditions. System optimization and performance studies include the calibration of the depolarization ratio, merging of near-range (analog) and far-range (photon-counting) data, determination of overlap functions and validation of the retrieved observables with radiosonde data.

Airflows over mountain barriers in the Alpine region may give rise to strong, gusty downslope winds, called Bora. Oscillations, caused by the flow over an orographic barrier, lead to formation of mountain waves. These waves can only rarely be observed visually and can, in general, not be reliably reproduced by numerical models. Using aerosols as tracers for airmass motion, mountain waves were experimentally observed during Bora outbreak in the Vipava valley, Slovenia, on 24-25 January 2019 by two lidar systems: a vertical scanning lidar positioned just below the peak of the lee side of the mountain range and a fixed direction lidar at valley floor, which were set up to retrieve two-dimensional structure of the airflow over the orographic barrier into the valley. Based on the lidar data, we determined the thickness of airmass layer exhibiting downslope motion, observed hydraulic jump phenomena that gave rise to mountain waves and characterized their properties.

Aerosol vertical profiles are valuable inputs for the evaluation of aerosol transport models, in order to improve the understanding of aerosol pollution ventilation processes which drive the dispersion of pollutants in mountainous regions. With the aim of providing high-accuracy vertical distributions of particle mass concentration for the study of aerosol dispersion in small-scale valleys, vertical profiles of aerosol mass concentration for aerosols from different sources (including Saharan dust and local biomass burning events) were investigated over the Vipava valley, Slovenia, a representative hot-spot for complex mixtures of different aerosol types of both anthropogenic and natural origin. The analysis was based on datasets taken between 1–30 April 2016. In-situ measurements of aerosol size, absorption, and mass concentration were combined with lidar remote sensing, where vertical profiles of aerosol concentration were retrieved. Aerosol samples were characterized by SEM-EDX, to obtain aerosol morphology and chemical composition. Two cases with expected dominant presence of different specific aerosol types (mineral dust and biomass-burning aerosols) show significantly different aerosol properties and distributions within the valley. In the mineral dust case, we observed a decrease of the elevated aerosol layer height and subsequent spreading of mineral dust within the valley, while in the biomass-burning case we observed the lifting of aerosols above the planetary boundary layer (PBL). All uncertainties of size and assumed optical properties, combined, amount to the total uncertainty of aerosol mass concentrations below 30% within the valley. We have also identified the most indicative in-situ parameters for identification of aerosol type.

The conventional Food and Agriculture Organization of the United Nations (FAO) Penman-Monteith (P-M) equation requires knowledge of the available energy to estimate reference evapotranspiration (ETo); however, it is common to ignore the minor energy components (MECs). This study was conducted to determine the effect of not including the MECs in the FAO P-M equation. Fifteen-min micrometeorological records of four sites (covered with corn, soybeans, and prairie) in central Iowa, USA, during the years 2007-2012 were investigated. The major/ minor components of the energy equation were either measured or estimated by in-situ eddy covariance instruments. It was discovered that, on average, the MECs accounted for at least 13% of daily net radiation, leading to 27% decrease in daily ETo. Therefore, an equation is introduced to estimate MECs as a function of net radiation, air temperature, and Monin-Obukhov length; and another equation is regressed to roughly estimate daily MECs as a function of net radiation and day of the year. The findings in this study suggest a fundamental modification of FAO P-M formula by considering the inclusion of MECs in the energy term.

High temporal and spatial resolution profiling of aerosol properties is required to study air pollution sources, aerosol transport, and features of atmospheric structures over complex terrain. A polarization Raman LiDAR with remote operation capability was developed for this purpose and deployed in the Vipava Valley, Slovenia, a location in the Alpine region where high concentrations of aerosols originating from a number of different local and remote sources were found. The system employs two high-power Nd:YAG pulsed lasers at 355 nm and 1064 nm as transmitters and provides the capability to extract the extinction coefficient, backscatter coefficients, depolarization ratio, Ångström exponent, and LiDAR ratio profiles. Automatized remote operation in an indoor environment provides a high duty cycle in all weather conditions. In addition to the detailed description of the device, an assessment of its potential and the retrieval uncertainties of the measured quantities is discussed. System optimization and performance studies include calibration of the depolarization ratio, merging of near-range (analog) and far-range (photon counting) data, determination of overlap functions, and validation of the retrieved observables with radiosonde data. Two cases for assessing LiDAR performance under specific weather conditions (during rain and in the presence of mineral dust) are also presented.

Vipava valley in Slovenia is a representative hot-spot for complex mixtures of different aerosol types of both anthropogenic and natural origin. Aerosol loading distributions and optical properties were investigated using a two-wavelength polarization Raman LiDAR, which provided extinction coefficient, backscatter coefficient, depolarization ratio, backscatter Ångström exponent and LiDAR ratio profiles. Two different representative meteorological situations were investigated to explore the possibility of identifying aerosol types present in the valley. In the first case, we investigated the effect of strong downslope (Bora) wind on aerosol structures and characteristics. In addition to observing Kelvin–Helmholtz instability above the valley, at the height of the adjacent mountain ridge, we found new evidence for Bora-induced processes which inject soil dust aerosols into the free troposphere up to twice the height of the planetary boundary layer (PBL). In the second case, we investigated aerosol properties and distributions in stable weather conditions. From the observed stratified vertical aerosol structure and specific optical properties of different layers we identified predominant aerosol types in these layers.

Presence of atmospheric aerosols affects the Earth’s radiation budget and thus also atmospheric thermal structure, which in turn affects cloud and planetary boundary layer (PBL) dynamics. We combine in-situ and remote measurements to determine aerosol properties in a representative hot-spot for air pollution in a complex terrain configuration. Vertical profiles of aerosol properties were investigated using a two-wavelength polarization Raman lidar system in the Vipava valley. Using lidar-obtained particle depolarization ratio, lidar ratio and backscatter Angstrom exponent (355 nm / 1064 nm), which depend on aerosol shape, size and refractive index, thus the aerosols can be identified and the roles of different aerosol types in the observed atmospheric processes were investigated. In addition, aerosol absorption coefficients were measured in-situ by Aethalometers (AE33, Magee Scientific / Aerosol d.o.o.) on the valley floor and on the adjacent mountain range, 850 m above the lidar site. Our primary goal was to study the variability of aerosol types within and above the Vipava valley, which was performed using the entire lidar dataset from August – December 2017. Primary anthropogenic aerosols within the valley is mainly emitted from two sources: individual domestic heating systems, which mostly use biomass fuel and traffic. Natural aerosols, transported by long-range transport, such as mineral dust and sea salt, were observed both above the PBL and entering into the PBL. Vertical distributions of aerosol properties, in par- ticular the particle depolarization ratio, indicated atmospheric stratification with different aerosol types occupying different height ranges. In the presence of Bora (strong down-slope wind), Kelvin-Helmholtz instabilities were observed between the PBL and the free troposphere. Using aerosol type identification capability of our system, we discovered that this instability was responsible for ejecting aerosols from the PBL up to 2 km into the free troposphere. In addition, we improved the reliability of aerosol identification in vertical profiles using absorption coeffi- cient measured by Aethalometer. Combining it with the aerosol extinction coefficient at 355 nm derived from lidar data, we derived aerosol single scattering albedo (SSA), which is an important parameter for aerosol characterization.

Vipava valley in southwest Slovenia is a representative hot-spot for complex mixtures of different aerosol types of both anthropogenic and natural origin in mountainous terrain. An investigation of aerosol properties throughout the troposphere in different atmospheric conditions was made possible by a deployment of a two-wavelength polarization Raman lidar system combining with in-situ measurements in the valley (in the town of Ajdovscina) from September 2017. Using its aerosol identification capabilities, which are based on particle depolarization ratio and lidar ratio measurements, it was possible to identify predominant aerosol types in the observed atmospheric structures, for example in different atmospheric layers in the case of stratified atmosphere. Primary anthropogenic aerosols within the valley were found to be mainly emitted from two sources: individual domestic heating systems, which mostly use biomass fuel, and from traffic. A considerable fraction of natural aerosols (for example mineral dust and sea salt), transported over large distances, were observed both above and entering into the planetary boundary layer. According to the properties of different aerosol types, backscatter contribution of each aerosol type was evaluated and the corresponding extinction contribution was derived from lidar observations. Statistical analysis of the presence of different aerosol types was performed on the entire available dataset from 2017 and 2018.

Particulate matter emitted from tunnel-ventilated animal feeding operations (AFOs) is known to transport malodorous compounds. As a mitigation strategy, vegetative environmental buffers (VEBs) are often installed surrounding AFOs to capture particulates and induce lofting and dispersion. Currently, point measurements are the primary means by which VEB performance has been investigated. The existing techniques lack spatial and temporal resolution and fail to assign the observed particulate reduction to capture, lofting, or dispersion. This study presents a technique for estimating the capture efficiency of a VEB using lidar and attributes all observed reduction to particulate capture, thereby delineating the effects of capture and lofting. The experiments revealed a capture efficiency ranging from 21 to 74%. Instantaneous lidar scans showed periodic lofting well above the VEB, but when scans were averaged over several hours, the plumes appeared Gaussian. This paper documents experimental evidence quantifying the capture efficiency of a VEB. It also establishes an experimental framework for future studies on the efficacy of various emissions mitigation strategies. (C) 2017 Elsevier B.V. All rights reserved.

Pollutant emissions to the atmosphere commonly derive from nonpoint sources that are extended in space. Such sources may contain area, volume, line, or a combination of emission types. Currently, point measurements, often combined with models, are the primary means by which atmospheric emission rates are estimated from extended sources. Point measurement arrays often lack in spatial and temporal resolution and accuracy. In recent years, lidar has supplemented point measurements in agricultural research by sampling spatial ensembles nearly instantaneously. Here, a methodology using backscatter data from an elastic scanning lidar is presented to estimate emission rates from extended sources. To demonstrate the approach, a known amount of particulate matter was released upwind of a vegetative environmental buffer, a barrier designed to intercept emissions from animal production facilities. The emission rate was estimated downwind of the buffer, and the buffer capture efficiency ( percentage of particles captured) was calculated. Efficiencies ranged from 21% to 74% and agree with the ranges previously published. A comprehensive uncertainty analysis of the lidar methodology was performed, revealing an uncertainty of 20% in the emission rate estimate; suggestions for significantly reducing this uncertainty in future studies are made. The methodology introduced here is demonstrated by estimating the efficiency of a vegetative buffer, but it can also be applied to any extended emission source for which point samples are inadequate, such as roads, animal feedlots, and cotton gin operations. It can also be applied to any pollutant for which a lidar system is configured, such as particulate matter, carbon dioxide, and ammonia.

The Vipava valley in Slovenia is well known for the appearance of strong, gusty North-East Bora winds, which occur as a result of air flows over an adjacent orographic barrier. There are three prevailing wind directions within the valley which were found to give rise to specific types of atmospheric structures. These structures were investigated using a Mie scattering lidar operating at 1064nm, which provided high temporal and spatial resolution backscatter data on aerosols, which were used as tracers for atmospheric flows. Wind properties were monitored at the bottom of the valley and at the rim of the barrier using two ultrasonic anemometers. Twelve time periods between February and April 2015 were selected when lidar data was available. The periods were classified according to the wind speed and direction and investigated in terms of appearance of atmospheric structures. In two periods with strong or moderate Bora, periodic atmospheric structures in the lidar data were observed at heights above the mountain barrier and are believed to be Kelvin–Helmholtz waves, induced by wind shear. No temporal correlation was found between these structures and wind gusts at the ground level. The influence of the wind on the height of the planetary boundary layer was studied as well. In periods with low wind speeds, the vertical evolution of the planetary boundary layer was found to be governed by solar radiation and clouds. In periods with strong or moderate Bora wind, convection within the planetary boundary layer was found to be much weaker due to strong turbulence close to the ground, which inhibited mixing through the entire layer.

Hydrometeorological models are often evaluated and optimized on the basis of micrometeorological measurements. However, it has been known for more than three decades that surface measurements of sensible and latent heat energy (LE) are systematically underestimated. We studied this problem using six years of eddy-correlation measurements for four fields (corn, soybean, and prairie) in central Iowa, USA. We recorded major components of the energy equation (i.e. net radiation, sensible heat flux, LE, and soil heat flux, photosynthesis), and indirectly estimated most of the minor components of energy balance (namely storage in the soil, canopy and air). Storage in the canopy was related to leaf area index (LAI) acquired from Moderate Resolution Imaging Spectrometer (MODIS). In this paper, a diagnostic approach is investigated where systematic error is identified first. Three dimensional (3D) plots of the residual of energy equation vs. potential variables indicated the imbalance was largest mainly during the cold non-growing season when the soil was dry. Correlations between energy balance residual (EBR) and energy components showed that soil storage was not precisely estimated. Finally, an a-posteriori analysis (constrained linear multiple regression (CMLR)) was conducted to quantify the contribution of major/minor components of the energy equation towards EBR. The result highlights that the contribution of pertinent components of energy to EBR is mainly controlled by prevailing monthly hydrometeorological conditions; however, precise quantification of causes of imbalance is site-specific. A comparison between the a-posteriori analysis technique and the Bowen-ratio method demonstrates that the Bowen-ratio basically presumes a higher level of underestimation in LE. The results obtained in this study suggest that a-posteriori analysis may offer a superior methodology to correct measured eddy-correlation measurements. Furthermore, the overall trends in the correction of LE measurements suggest that there is a potential for rough monthly corrections of LE, irrespective of the type of crop.