High-resolution measurements of water vapor concentrations and their transport throughout the turbulent planetary boundary layer (PBL) and beyond are key for an enhanced understanding of atmospheric processes. This study presents data from the mobile Atmospheric Monitoring System (ATMONSYS) Differential Absorption Lidar (DIAL), operated with a novel titanium sapphire (Ti:Sa) laser concept, for the first time. The ATMONSYS DIAL aims to resolve turbulence throughout the PBL with a sampling frequency of 10 s and vertical resolutions of less than 200 m. General measuring capabilities during high-noon, clear-sky, summer conditions with a maximum vertical measurement range of >3 km and statistical uncertainties of <5 % are demonstrated. The analysis of turbulence spectra shows good agreement with Kolmogorov's law, demonstrating the system's capability to resolve turbulence. However, deviations from Kolmogorov behavior are observed at certain frequency ranges. By combining the ATMONSYS DIAL with an adjacent high-quality Doppler wind lidar, some of these deviations are mitigated in the co-spectra due to independent noise from both instruments. However, intermediate deviations from Kolmogorov behavior persist, likely due to surrounding surface heterogeneities. The agreement of the co-spectra with Kolmogorov's law at the highest frequencies demonstrates that the ATMONSYS DIAL is capable of resolving turbulent latent energy fluxes down to the measurement's Nyquist frequency of 5x10(-2)Hz. A system cross-intercomparison of the ATMONSYS DIAL with two adjacent water vapor Raman lidars and radiosondes shows overall good agreement between the sensors, despite minor DIAL deficiencies under certain conditions with broken clouds passing over the lidar. The observed profile-to-profile DIAL fluctuations and sensor-to-sensor deviations, in combination with low statistical uncertainty, highlight the advantage of humidity lidars, such as the ATMONSYS DIAL, in capturing both short-term and small-scale dynamics of the lowermost atmosphere.

In this study, we compare the wind measurements of a virtual tower triple Doppler lidar setup to those of a sonic anemometer located at a height of 90 m above ground on an instrumented tower and with those of two single Doppler lidars to evaluate the effect of the horizontal homogeneity assumption used for single Doppler lidar applications on the measurement accuracy. The triple lidar setup was operated in a 90 m stare and a step–stare mode at six heights between 90 and 500 m above ground, while the single lidars were operated in a continuous scan velocity–azimuth display (VAD) mode where one of them had a zenith angle of 54.7° and the other one of 28.0°. The instruments were set up at the boundary-layer field site of the German Meteorological Service (DWD) in July and August of 2020 during the FESST@MOL (Field Experiment on sub-mesoscale spatiotemporal variability at the Meteorological Observatory Lindenberg) 2020 campaign. Overall, we found good agreement of the lidar methods for the whole study period for different averaging times and scan modes compared to the sonic anemometer. For the step–stare mode wind speed measurements, the comparability between the triple lidar and the sonic anemometer was 0.47 m s−1 at an averaging time of 30 min with a bias value of −0.34 m s−1. For wind speed measured by one single lidar setup for the same period with an averaging time of 30 min, we found a comparability of 0.32 m s−1 at an averaging time of 30 min and a bias value of −0.07 m s−1 as well as values of 0.47 and −0.34 m s−1 for the other one, respectively. We also compared the wind velocity measurements of the single and triple lidars at different heights and found decreasing agreement between them with increasing measurement height up to 495 m above ground for the single lidar systems. We found that the single Doppler lidar with the increased zenith angle produced poorer agreement with the triple Doppler lidar setup than the one with the lower zenith angle, especially at higher altitudes. At a height of 495 m above ground and with an averaging time of 30 min the comparability and bias for the larger zenith angle were 0.71 and −0.50 m s−1, respectively, compared to values of 0.57 and −0.28 m s−1 for the smaller zenith angle. Our results confirm that a single Doppler lidar provides reliable wind speed and direction data over heterogeneous but basically flat terrain in different scan configurations. For the virtual tower scanning strategies, we developed a new filtering approach based on a median absolute deviation (MAD) filter combined with a relatively relaxed filtering criterion for the signal-to-noise ratio output by the instrument.

Alternative crops are a key aspect of many nature-based solutions in agriculture, and there is a need for more consistent geographic information on biophysical suitability to aid in both farm-level planning and larger-scale analyses. Here we describe an approach for generating consistent, replicable, high-resolution suitability maps for any alternative crop species across the USA. The method employs a criteria-based approach to map potential species performance using a simple suitability index. Criteria for suitable and ideal ranges of values for influential biophysical variables are created using data collected from published sources and are reviewed by experts. Publicly available soil and climate map data are used with the criteria to map suitability for each variable which are integrated into an overall suitability index map. Maps of unsuitable locations are combined to produce a limiting variable map showing which category of environmental variables is most limiting. We demonstrate the application of this approach for two alternative perennial crops, apple (Malus spp.) and Chinese chestnut (Castanea mollissima) and validate its accuracy using known farm locations. Maps of apple and chestnut in four distant study regions show varying patterns of suitability and potential performance depending on the climate and geophysical characteristics of the region. The maps can be used to identify areas of high suitability and compare across regions or between species and be combined with socio-economic and environmental datasets for further analysis. Compared to other approaches, ours can be applied to multiple species with a range of pre-existing knowledge in a consistent way, allowing for reliable mapping and subsequent research and planning for alternative crops and nature-based solutions in agriculture.

The data presented here was collected between 01 June and 14 September 2020 in Falkenberg (Tauche), Germany, during the FESST@MOL (Field Experiment on sub-mesoscale spatio-temporal variability at the Meteorological Observatory Lindenberg) 2020 campaign, which was initiated by the Hans-Ertel-Center for Weather Research. The measurements took place at the boundary layer field site (GM) Falkenberg, Germany. The data collected in this campaign were measured by three Doppler Lidars (DL) set-up as a virtual tower (VT) testing five different VT scanning methods, operated by the Karlsruhe Institute of Technology. We tested different step/stare and range-height-indicator (RHI) scanning methods. Further details on this data set can be found in the attached data documentation.

Numerical weather prediction models operate on grid spacings of a few kilometers, where deep convection begins to become resolvable. Around this scale, the emergence of coherent structures in the planetary boundary layer, often hypothesized to be caused by cold pools, forces the transition from shallow to deep convection. Yet, the kilometer-scale range is typically not resolved by standard surface operational measurement networks. The measurement campaign Field Experiment on Submesoscale Spatio-Temporal Variability in Lindenberg (FESSTVaL) aimed at addressing this gap by observing atmospheric variability at the hectometer-to-kilometer scale, with a particular emphasis on cold pools, wind gusts, and coherent patterns in the planetary boundary layer during summer. A unique feature was the distribution of 150 self-developed and low-cost instruments. More specifically, FESSTVaL included dense networks of 80 autonomous cold pool loggers, 19 weather stations, and 83 soil sensor systems, all installed in a rural region of 15-km radius in eastern Germany, as well as self-developed weather stations handed out to citizens. Boundary layer and upper-air observations were provided by eight Doppler lidars and four microwave radiometers distributed at three supersites; water vapor and temperature were also measured by advanced lidar systems and an infrared spectrometer; and rain was observed by a X-band radar. An uncrewed aircraft, multicopters, and a small radiometer network carried out additional measurements during a 4-week period. In this paper, we present FESSTVaL’s measurement strategy and show first observational results including unprecedented highly resolved spatiotemporal cold-pool structures, both in the horizontal as well as in the vertical dimension, associated with overpassing convective systems.

&lt;p&gt;We compare the wind measurements of a virtual tower triple Doppler Lidar setup to those of a sonic anemometer located at a height of 90&amp;#160;m above ground on an instrumented tower and with those of a single Doppler Lidar. The instruments were set up at the boundary-layer field site of the German Meteorological Service (DWD) in July and August of 2020 during the FESST@MOL (Field Experiment on sub-mesoscale spatio-temporal variability at the Meteorological Observatory Lindenberg) 2020 campaign. &amp;#160;The triple Lidar setup was operated in a stare and in a step/stare mode at six heights between 90 and 500&amp;#160;m above ground, while the single Lidar was operated in a continuous scan Velocity-Azimuth-Display (VAD) mode with an azimuthal resolution of around 1.5&amp;#160;&amp;#176; and a zenith angle of 55.5&amp;#160;&amp;#176;. Overall, both Lidar methods showed a good agreement for the whole study period for different averaging times and scan modes compared to the sonic anemometer. Additionally, we developed and show a new filtering approach based on a Median Absolute Deviation (MAD) filter for the virtual tower setup and compare it to a filtering approach based on a signal-to-noise ratio SNR threshold. The advantage of the MAD filter is that it is not based on a strict threshold but on the MAD of each 30-second period and can, therefore, better adapt to changing atmospheric conditions. In the comparison the MAD filter leads to a greater data availability while upholding similar comparability and bias values between the triple Lidar and sonic anemometer setups. Our results also show that a single Doppler Lidar is a viable method for measuring wind speed and direction with only small disadvantages, at least for measurement heights similar to our investigation and for comparable heterogeneous but flat landscapes.&lt;/p&gt;

Technology has reached a point where ground-based remote sensing instruments have the ability to greatly increase the spatial and temporal data density compared to conventional instruments. This offers the great opportunity to improve the understanding of individual processes and to increase the predictive capabilities of numerical weather models and reduce their inaccuracies. The goal of this study is to assess these measurement inaccuracies and the usefulness of Doppler lidar systems for these purposes. The data were collected during the FESST@MOL 2020 measurement campaign, organised by the German Weather Service (DWD) and initiated by the Hans-Ertel-Center for Weather Research (HErZ), at the boundary layer field site (GM) of the DWD in Falkenberg (Tauche), Germany. During the measurement campaign, a total of eight Doppler lidars of the brands Halo Photonics and Leosphere were active in different operating modes. We compare the results of triple and single Halo Photonics lidar setups and triple Leosphere lidar setups with the measurements of an ultrasonic anemometer mounted at a height of 90 m at the 99 m high instrumented tower in Falkenberg. The focus of the operating modes was on various virtual tower (VT) measurements and velocity azimuth display (VAD) measurements with the different averaging times of ten and thirty minutes for the mean horizontal wind. The discrepancy in readings between VT and VAD measurements increases with increasing height above the ground while the Halo Photonic lidars performed better in the comparison with the sonic anemometer.

The technological development of ground-based active remote sensing instruments has reached a point where they have the possibility to drastically increase the temporal and spatial data density compared to conventional instruments, which would allow for a better process understanding and is expected to enhance the forecasting skills of numerical weather prediction systems and reduce its uncertainties. To test the measurement uncertainty and feasibility of Doppler Lidar systems we participated in the FESST@MOL 2020 field campaign, organized by the German Meteorological Service (DWD) in Lindenberg, Germany. During this campaign, eight Doppler Lidars were operated at the boundary layer field site (GM) Falkenberg. We evaluated different scanning strategies for the determination of the wind profile in the Atmospheric Boundary Layer (ABL) using multiple different triple Lidar virtual tower (VT) scan patterns including range height indicator (RHI) and step/stare scan modes. We compared these Lidar-based wind measurements with the data from a sonic anemometer on a 99 m tall instrumented tower also located in Falkenberg over a period of four months. The lidar and the sonic anemometer data were processed to 10- and 30- minute averages and compared to each other. The VT measurements underestimated the mean horizontal wind compared to the sonic anemometer by around 0.2 m s‑1. Besides that, we compared the VT data with those from a single fourth nearby Doppler Lidar which was running in a velocity-azimuth display (VAD) mode. The calculated mean horizontal wind values between the two different modes showed a good comparability but differed stronger with increasing height.

Introduction: Climate change (CC) and the increased occurrence of extreme climatic events pose a serious threat to crop yields and their stability worldwide. This study analyzed the CC mitigation potential of an alley cropping system on crop physiological stresses and growth as compared to a monoculture system. Materials and Methods: Growth of winter durum wheat, cultivated alone (agriculture) and in combination with hybrid walnut (agroforestry), was simulated with the Hi-sAFe agroforestry model, as driven by business-as-usual Intergovernmental Panel on Climate Change (IPCC) projections, split into three scenarios, representing Past (1951–1990), Present (1991–2030), and Future (2031–2070) climatic conditions. Crop growth and the occurrence of thermal, nitrogen, and water stresses were analyzed. Results: Cold-related stresses were modest in Past and almost disappeared over time. Heat, drought, and nitrogen stresses increased about twofold from Past to Future, but were reduced by 20–35% in agroforestry, already with medium-sized trees (diameter at breast height (DBH) of about 10–15 cm). Crop yields in agriculture increased from Past to the end of Present and then remained stable. This moderately decreased with tree age in agroforestry (especially in Future). Discussion: The impact of CC on the crop was buffered in agroforestry, especially for the most extreme climatic events. The mitigation of crop microclimate and the increased stability of crop yields highlight the potential of agroforestry as a CC adaptation strategy.

The shade tolerance of black currants (Ribes nigrum cv. Consort) was studied by measuring the growth and productivity of mature plants in the field for three seasons under full sun or artificial shade netting in Urbana, IL. Shade treatments reduced photosynthetically active radiation (PAR) from 37% to 83%. Yield was not reduced in shade levels up to 65% but decreased by as much as 66% under 83% shade. Shade had minimal effect on stem rejuvenation in the first 2 years, but reduced rejuvenation in the third year from 14 new stems in full sun to eight new stems in 83% shade. Stem diameter decreased 8% to 19% with 83% shade, whereas no changes were observed in up to 65% shade. Plant height increased 5% to 8% from open sun to 83% shade. Specific leaf weight decreased and leaf area increased with shade. Powdery mildew severity increased with shade, and disease-resistant cultivars should be considered for understory crops. Our results indicate that growth and productivity of black currants can be maintained in moderate shade but shade levels beyond 65% will significantly reduce agronomic performance.

This study provides methane (CH4) emission estimates for mature female African beef cattle in a semi-arid region in Southern Kenya using open-path laser spectroscopy together with a backward Lagrangian Stochastic (bLS) dispersion modeling technique. We deployed two open-path lasers to determine 10-min averages of line-integrated CH 4 measurements upwind and downwind of fenced enclosures (so-called bomas: a location where the cattle are gathered at night) during 14 nights in September/October 2019. The measurements were filtered for wind direction deviations and friction velocity before the model was applied. We compared the obtained emission factors (EFs) with the Intergovernmental Panel on Climate Change (IPCC) Tier 1 estimates for the Sub-Saharan African (SSA) countries, which were mostly derived from studies carried out in developed countries and adapted to the conditions in Africa. The resulting EF of 75.4 ± 15.99 kg year −1 and the EFs calculated from other studies carried out in Africa indicate the need for the further development of region-specific EFs depending on animal breed, livestock systems, feed quantity, and composition to improve the IPCC Tier 1 estimates.

Die Technologie hat einen Punkt erreicht an dem bodenbasierte Fernerkundungsinstrumente die Möglichkeit haben die räumliche und zeitliche Datendichte im Vergleich zu konventionellen Instrumenten stark zu erhöhen. Das bietet die große Chance das Verständnis über einzelne Prozesse zu verbessern und die Vorhersagefähigkeiten von numerischen Wettermodellen zu erhöhen und ihre Ungenauigkeiten zu verringern. Das Ziel der Studie ist es diese Messungenauigkeiten und die Nutzbarkeit von Doppler Lidar Systemen für diese Zwecke zu überprüfen. Die Daten wurden während der FESST@MOL 2020 Messkampagne, organisiert von dem Deutschen Wetterdienst (DWD) und initiiert von dem Hans-Ertel-Zentrum für Wetterforschung (HErZ), auf dem Grenzschichtmessfeld (GM) des DWD in Falkenberg (Tauche), Deutschland erhoben. Während der Messkampagne waren insgesamt acht Doppler Lidare der Marken Halo Photonics und Leosphere in verschiedenen Betriebsmodi aktiv. In dieser Arbeit vergleichen wir die Ergebnisse von Triple und Single Lidar Setups, von Geräten der Marke Halo Photonics und Triple Lidar Setups von Geräten der Marke Leosphere mit den Messungen eines Ultraschallanemometers, angebracht auf einer Höhe von 90 m an dem 99 m hohem, mit Instrumenten bestückten, Messturm in Falkenberg. Der Fokus der Betriebsmodi liegt auf verschiedenen virtuellen Turm (VT) Messungen und Velocity Azimuth Display (VAD) Messungen mit den Mittelungszeiten von zehn und dreißig Minuten des mittleren horizontalen Windes. Die Diskrepanz der Messwerte zwischen VT und VAD Messungen nimmt mit steigender Höhe über dem Boden zu.

By averaging in time and/or space, models predict less variable light patterns under tree canopies than in reality. We measured light every minute in 24 positions in a grid under different chestnut orchards, for several clear and overcast days. We also modelled this light with a purposely created 3D, spatially explicit, ray-tracing light interception model, where canopy porosity was calibrated to match measured daily light. Finally, we used both the measured and modeled light patterns transmitted under the tree canopies to estimate the daily net photosynthesis (A(n)) and radiation use efficiency (RUE) of an understory wheat leaf. As expected, modeled light was more uniform than measured light, even at equal daily light. This resulted in large overestimation of daily A(n) and RUE of the understory leaf. Averaging light in time increased the overestimations even further. A sensitivity analysis showed that this overestimation remained substantial over the range of realistic values for leaf photosynthetic parameters (i.e. V-c,V-max, J(max), R-d) of the understory crop.

Agroforestry represents a solution to land degradation by agriculture, but social barriers to wider application of agroforestry persist. More than half of all cropland in the USA is leased rather than owner-operated, and the short terms of most leases preclude agroforestry. Given insufficient research on tenure models appropriate for agroforestry in the USA, the primary objective of this study was to identify examples of farmers practicing agroforestry on land they do not own. We conducted interviews with these farmers, and, in several cases, with landowners, in order to document their tenure arrangements. In some cases, additional parties also played a role, such as farmland investors, a farmer operating an integrated enterprise, and non-profit organizations or public agencies. Our findings include eleven case studies involving diverse entities and forms of cooperation in multi-party agroforestry (MA). MA generally emerged from shared objectives and intensive planning. MA appears to be adaptable to private, investor, institutional, and public landowners, as well as beginning farmers and others seeking land access without ownership. We identify limitations and strategies for further research and development of MA.

In the Midwest U.S. dominated corn-soybean landscape, agroforestry systems can be particularly valuable for increasing the provisioning and regulatory capacity of the agricultural landscape. However, these systems have not yet been broadly integrated into the landscape of this region since they are mostly relegated to marginal lands. A growing body of literature suggests a path to increase the adoption of agroforestry in the Midwest U.S. lies in the incorporation of low-input food-producing tree species that provide economic incentives for farmers. Studies of the system-level integration of such approaches have proceeded by using the currently available cultivars and breeding selections of various tree nut and fruit species. While existing varieties and breeding selections provide the opportunity for initial system development and integration, their broad adaptability to the Midwest U.S. and its marginal land-types is unexplored. Thus, a second tier of research includes the genetic improvement and adaptation of tree crop selections to their respective target environments throughout the Midwest U.S. Fortunately, select tree crops of interest are amendable to systematic breeding and have wild relatives that are endemic across the region. In this paper, we discuss the value of these wild relatives for broadening the adaption of cultivated tree crop selections by using the hazelnut as an example species. We present a framework using geospatial tools to define and prioritize target environments for breeding and, in turn, exploiting wild relative germplasm.

Pest control by wild arthropods is an important ecosystem service in fruit crops, especially due to markets that value minimal pesticide use. Techniques to augment on-farm habitat for wild arthropods have focused on flowering ground cover planted within orchards and hedgerows on field borders. However, natural enemies found in groundcover often do not favor tree canopy habitat. Conversely, while hedgerows can effectively provide natural enemies that prefer woody microhabitats, their impact diminishes away from field edges. Shrub crops interplanted within orchards could resolve both problems, providing woody habitat for natural enemies directly adjacent to target crop trees. In a multi-layer agroforestry system in Illinois, we vacuum sampled arthropod communities across layers and recorded vegetation characteristics and pest damage on apples. Using generalized linear models, information theoretic model selection, and non-metric multidimensional scaling, we evaluated the effects of three shrub treatments (raspberries, hazelnuts, and both species) on pest and natural enemy guilds in apple trees and shrubs, and on the frequency of pest damage on apples. Shrub composition was an important predictor of arthropod communities on shrubs. However, shrub treatment had only minor impacts on arthropods in apple canopies, indicating the habitats are less similar than anticipated. While two arthropod guilds in apple canopies were linked to pest damage frequency, neither was sensitive to changes in the shrub layer. Results suggest that shrub crop interplanting does not inherently resolve the ecological complexities that impede existing approaches in conservation biological control.

Agroforestry, the intentional integration of trees with crops and/or livestock, can lead to multiple economic and ecological benefits compared to trees and crops/livestock grown separately. Field experimentation has been the primary approach to understanding the tree–crop interactions inherent in agroforestry. However, the number of field experiments has been limited by slow tree maturation and difficulty in obtaining consistent funding. Models have the potential to overcome these hurdles and rapidly advance understanding of agroforestry systems. Hi-sAFe is a mechanistic, biophysical model designed to explore the interactions within agroforestry systems that mix trees with crops. The model couples the pre-existing STICS crop model to a new tree model that includes several plasticity mechanisms responsive to tree–tree and tree–crop competition for light, water, and nitrogen. Monoculture crop and tree systems can also be simulated, enabling calculation of the land equivalent ratio. The model’s 3D and spatially explicit form is key for accurately representing many competition and facilitation processes. Hi-sAFe is a novel tool for exploring agroforestry designs (e.g., tree spacing, crop type, tree row orientation), management strategies (e.g., thinning, branch pruning, root pruning, fertilization, irrigation), and responses to environmental variation (e.g., latitude, climate change, soil depth, soil structure and fertility, fluctuating water table). By improving our understanding of the complex interactions within agroforestry systems, Hi-sAFe can ultimately facilitate adoption of agroforestry as a sustainable land-use practice.

The maize-soybean rotation (MSR) dominates the Midwest United States and degrades many ecological functions. Black walnut (Juglans nigra L.) plantation forestry (PF) and alley cropping (AC) are two alternative land-uses that can enhance productivity and restore ecosystem services. Given the lack of robust market mechanisms to monetize ecosystems services, we tested whether the profitability of PF and AC could drive adoption in the Midwest. Publically available data on black walnut soil suitability, timber prices, crop productivity, and cash rents were combined in a high-resolution spatial analysis to identify regions where these alternatives can outcompete MSR. To avoid selecting an arbitrary discount rate at which to make comparisons, we determined the threshold discount rate necessary to make PF or AC economically competitive with MSR. We show that, with a 5% discount rate, PF and AC could be more profitable on 17.0% and 23.4% of MSR land, respectively. Contrary to the common assumption that woody agricultural alternatives should first be adopted in marginal row crop areas, the economic competitiveness of PF and AC was not correlated with MSR productivity. Instead, black walnut growth rate was the central driver of PF and AC competitiveness, underscoring a necessary shift away from the current MSR-centric perspective in defining target regions for land-use alternatives. Results reveal major opportunities for landowners and investors to increase profitability by investing in PF and AC on both "marginal" and productive MSR land.