Energy Budget Research Articles

Atlantic salmon Salmo salar do not prioritize digestion when energetic budgets are constrained by warming and hypoxia.

During summer, farmed Atlantic salmon (Salmo salar) can experience prolonged periods of warming and low aquatic oxygen levels due to climate change. This often results in a drop in feed intake; however, the physiological mechanism behind this behaviour is unclear. Digestion is a metabolically expensive process that can demand a high proportion of an animal's energy budget and might not be sustainable under future warming scenarios. We investigated the effects of elevated temperature and acute hypoxia on specific dynamic action (SDA; the energetic cost of digestion), and how much of the energy budget (i.e. aerobic scope, AS) was occupied by SDA in juvenile Atlantic salmon. AS was 9% lower in 21°C-acclimated fish compared to fish reared at their optimum temperature (15°C) and was reduced by ~50% by acute hypoxia (50% air saturation) at both temperatures. Furthermore, we observed an increase in peak oxygen uptakerate during digestion which occupied ~13% of the AS at 15°C and ~20% of AS at 21°C, and increased the total cost of digestion at 21°C. The minimum oxygen tolerance threshold in digesting fish was ~42% and ~53% at 15 and 21°C, respectively, and when digesting fish were exposed to acute hypoxia, gut transit was delayed. Thus, these stressors result in a greater proportion of the available energy budget being directed away from digestion. Moderate environmental hypoxia under both optimal and high temperatures severely impedes digestion and should be avoided to limit exacerbating temperature effects on fish growth.

Viscoplastic elliptical objects impacting a solid surface

This theoretical and numerical study focuses on the physical mechanism driving the spreading of viscoplastic elliptical millimetric/centimetric objects after they impact a solid surface under no-slip conditions. The two-dimensional impacting objects are described as Bingham fluids. The two-dimensional numerical simulations are based on a variational multi-scale approach devoted to multiphase non-Newtonian fluid flows. The obtained results are analyzed considering the spreading dynamics, energy budgets and scaling laws. They show that, under negligible capillary effects, the impacting kinetic energy of the elliptical objects is dissipated through viscoplastic effects during the spreading process, giving rise to three flow regimes: inertio-viscous, inertio-plastic, and mixed inertio-visco-plastic. These regimes are strongly affected by the initial aspect ratio of the impacting objects, which reveals the possibility of using morphology to control spreading. Finally, the results are summarized in a diagram linking the object's maximum spreading and spreading time with different spreading regimes through a single dimensionless parameter called impact number.

A river runs through it: Robust automated mapping of riparian woodlands and land surface phenology across dryland regions

Riparian woodlands in drylands are critically important to human society, global biodiversity, and regional water and energy budgets. These sensitive ecosystems have experienced substantial degradation over the last several decades from climatic change and direct human activity. Nevertheless, quantifying long-term change in dryland riparian woodlands remains a major challenge, and much uncertainty exists in their remaining extent, historical breadth, and likely future trajectories. Dryland landscapes show large, fine-scale spatial heterogeneity in seasonal greenness patterns, driven in part by spatial variation in water availability. Riparian woodlands occur where water is concentrated in the landscape, either as aboveground streamflow or subsurface groundwater. In arid and semi-arid climates, this renders them phenologically distinctive from upland ecosystems. However, despite their importance and distinctiveness, there are currently no automated methods for delineating dryland riparian woodlands across regional extents in the cloud. Here we designed and implemented a cloud-based algorithm to retrieve dryland land surface phenology patterns from multispectral satellite imagery and conducted sensitivity analyses using real and simulated data to demonstrate that the approach is robust for MODIS, Sentinel-2, and Landsat over realistic ranges of noise and cloud cover. We then designed a series of random forest vegetation classifiers that integrate phenological and spectral information, vegetative structure from LiDAR, and topography from LiDAR or the Shuttle Radar Topography Mission. We implemented classifiers for three local study sites and then generalized our model to run regionally across the southwestern United States, with balanced accuracy for the riparian woodland class ranging from 94.5% to 97.5% when validated with local to regional datasets. Generally, phenological information proved more important than any other data source for mapping riparian woodlands, which showed more stability in interannual phenology than did upland vegetation types. To our knowledge, ours is the first regional, annual, automatically-generated and updated approach for mapping dryland riparian woodlands in the southwestern United States, paving the way for improved modeling and management efforts on watershed to regional scales. We also provide one of the first operational, exclusively cloud-based methods to extract dryland land surface phenology patterns using Landsat, Sentinel-2, MODIS, or other sensors, providing a framework for future studies investigating other aspects of long-term or spatial variation in dryland vegetative seasonality across the globe.

Experimental investigation of propagation evolution characteristics of internal solitary waves passing through downslope topography

In contrast to the extensive research on the propagation evolution of internal solitary waves (ISWs) over continental shelf topography, few investigations have been conducted on the propagation evolution of ISWs over downslope topography. In this experiment, the characteristics of the ISWs passing over a downslope topography were investigated in an immiscible two-layer fluid system to clearly capture the waveform information. The main objective of this study was to analyze the propagation evolution of ISWs with different incident amplitudes passing through a downslope topography. Using the particle image velocimetry technique, the evolutionary characteristics of ISWs (such as waveform, wave height, energy budget, and flow field) are investigated. According to the flow field analysis results, the phase velocity near the downslope topography changes with the propagation of ISWs. Moreover, the gradient distribution of velocity progressively becomes perpendicular to the right surface of the topography. Furthermore, a counterclockwise vortex gradually forms at the right upper vertex of the topography. The propagation of ISWs is influenced by varying water depth and topography. The front waveform of ISWs is significantly flat, and the back is steeper than the original back waveform. Around the tail wave, an upward convex wave packet is generated. The trends of wave energy and wave height losses are broadly consistent. Furthermore, the energy loss is related to the incident wave height with a 20% higher loss rate for large-amplitude ISWs than small-amplitude ISWs at the inflection point of the topography.

A novel numerical implementation for the surface energy budget of melting snowpacks and glaciers

Abstract. The surface energy budget drives the melt of the snow cover and glacier ice and its computation is thus of crucial importance in numerical models. This surface energy budget is the result of various surface energy fluxes, which depend on the input meteorological variables and surface temperature; of heat conduction towards the interior of the snow/ice; and potentially of surface melting if the melt temperature is reached. The surface temperature and melt rate of a snowpack or ice are thus driven by coupled processes. In addition, these energy fluxes are non-linear with respect to the surface temperature, making their numerical treatment challenging. To handle this complexity, some of the current numerical models tend to rely on a sequential treatment of the involved physical processes, in which surface fluxes, heat conduction, and melting are treated with some degree of decoupling. Similarly, some models do not explicitly define a surface temperature and rather use the temperature of the internal point closest to the surface instead. While these kinds of approaches simplify the implementation and increase the modularity of models, they can also introduce several problems, such as instabilities and mesh sensitivity. Here, we present a numerical methodology to treat the surface and internal energy budgets of snowpacks and glaciers in a tightly coupled manner, including potential surface melting when the melt temperature is reached. Specific care is provided to ensure that the proposed numerical scheme is as fast and robust as classical numerical treatment of the surface energy budget. Comparisons based on simple test cases show that the proposed methodology yields smaller errors for almost all time steps and mesh sizes considered and does not suffer from numerical instabilities, contrary to some classical treatments.

Near-Surface Atmospheric Response to Meso- and Submesoscale Current and Thermal Feedbacks

Abstract Current feedback (CFB) and thermal feedback (TFB) have been shown to strongly influence both atmospheric and oceanic dynamics at the oceanic mesoscale (10–250 km). At smaller scales, oceanic submesoscale currents (SMCs; 0.1–10 km) have a major influence on the ocean’s energy budget, variability, and ecosystems. However, submesoscale air–sea interactions are not well understood because of observational and modeling limitations related to their scales. Here, we use a realistic submesoscale-permitting coupled oceanic and atmospheric model to quantify the spatiotemporal variability of TFB and CFB coupling in the northwest tropical Atlantic Ocean. While CFB still acts as a submesoscale eddy killer by inducing an energy sink from the SMCs to the atmosphere, it appears to be more efficient at the submesoscale by approximately 30% than at the mesoscale. Submesoscale CFB affects the surface stress, however, the finite time scale of SMCs for adjusting the atmospheric boundary layer results in a diminished low-level wind response, weakening partial ocean reenergization by about 70%. Unlike at the mesoscale, submesoscale CFB induces stress/wind convergence/divergence, influencing the atmospheric boundary layer through vertical motions. The linear relationship between the surface stress derivative or wind derivative fields and sea surface temperature gradients, widespread at the mesoscale, decreases by approximately 35% ± 7% or 77% ± 10%, respectively, at the submesoscale. In addition, submesoscale TFB induces turbulent heat fluxes comparable to those at the mesoscale. Seasonal variability in meso- and submesoscale CFB and TFB coupling is mostly related to background wind speed. Also, disentangling submesoscale CFB and TFB is challenging because they can reinforce or counteract each other.

Energy budget characteristics of the subseasonal Scandinavian pattern

Based on daily Japanese 55-year reanalysis data, this study analysed the daily energy budget characteristics of 94 Scandinavian (SCA) events in the positive phase during 62 winters from 1958 to 2020. Low-frequency circulation anomalies characterize the SCA events. The maintenance of low-frequency anomalies mainly comes from the extraction of both available potential energy (APE) and kinetic energy (KE) from the background field during both the developing stage and the decaying stage. This energy conversion characteristic is related to the “locking” effect of the background field. During the developing stage, the interactions among the low-frequency circulation anomalies continuously generate KE, which is the main source for initiating the primary circulation anomalies around western Europe and the Scandinavian Peninsula. Meanwhile, the horizontal KE advection maintains the KE of the circulation anomalies around Lake Baikal. The decay process of the SCA events is mainly related to the damping effect on the APE due to diabatic heating and the interactions among the low-frequency circulation anomalies. The SCA event is a type of atmospheric internal dynamic pattern.

Improvement of Albedo and Snow-Cover Simulation during Snow Events over the Tibetan Plateau

Abstract The snow albedo is a vital component of land–atmosphere coupling models. It plays a critical role in regulating land surface energy exchange by controlling incoming solar radiation absorbed by the land surface and influencing the timing and rate of snowmelt. Accurate snow albedo simulation is essential to obtain surface energy balance and snow-cover estimates. Here, the simulation of albedo and snow cover using the Weather Research and Forecasting Model and an improved snow albedo scheme is verified against satellite-retrieved products during and immediately following eight snowfall events over the Tibetan Plateau. The improved model successfully characterizes the spatial pattern and inverted U-shaped temporal pattern of albedo over the entire Tibetan Plateau. This is attributed to the local optimization of snow-age parameters and explicit consideration of snow depth in the improved scheme. Compared with the previous model, the model proposed herein greatly decreases the overestimated albedo (by 0.13–0.27), yielding a bias range of ±0.08, mean relative bias decrease of 70%, and significant increase in the spatial correlation coefficient of 0.03–0.39 (mean: 0.13). The significant improvements of albedo estimates appear in deep snow-covered regions, largely attributed to parameter optimization related to snow albedo decay, while less improvements appear over the shallow snow-covered regions. Accurate reproduction of the spatiotemporal variation in albedo alleviated snow-cover overestimation by small amounts. For snow-cover estimates, the improved model consistently decreases the false-alarm rate by 0.03, and increases the overall accuracy and equitable threat score by 0.04 and 0.03, respectively. Moreover, the improved scheme shows an equivalent improvement of albedo estimates at both 1- and 5-km grid spacing over the eastern Tibetan Plateau; this is also true for snow-cover estimates. Significance Statement Snow albedo schemes in widely used numerical weather prediction models show notable shortcomings in complex mountainous regions, hindering accurate surface energy balance and snow-cover prediction. The purpose of this study is to better understand the role of snow albedo on snow-cover estimates and reveal the application potential of an improved snow albedo scheme across the Tibetan Plateau. This is important because snow albedo influences the timing and rate of snowmelt, and in turn snow-cover estimates, through regulating the surface energy budget. Our results highlight the strong application potential of our improved scheme in reducing snow simulation errors, confirm the importance of snow depth on snow albedo, and provide a new perspective for improving the accuracy of snow forecast over the topographically high Tibetan Plateau.

Numerical Study on the Precipitation Concentration over the Western Coast of Sumatra Island

Abstract Large amounts of tropical precipitation have been observed as significantly concentrated over the western coast of Sumatra Island. In the present study, we used a cloud-resolving model to perform 14-day numerical simulations and reproduce the distinctive precipitation distributions over western Sumatra Island and adjacent areas. The control experiment, in which the warmer sea surface temperature (SST) near the coast was incorporated and the terminal velocity and effective radius of ice clouds were parameterized to be temperature dependent, adequately reproduced the precipitation concentration as well as the diurnal cycles of precipitation. We then used the column-integrated frozen moist static energy budget equation, which is virtually equivalent to the column-integrated moisture budget equation under the weak temperature gradient assumption, to formulate sensitivity experiments focusing on the effects of coastal SST and upper-level ice clouds. Analysis of the time-averaged fields revealed that the column-integrated moisture and precipitation in the coast were significantly reduced when a cooler coastal SST or larger ice cloud particle size was assumed. Based on the comparison of the sensitivity experiments and in situ observations, we speculate that ice clouds, which are exported from inland convection that is strictly regulated by solar radiation, promote the accumulation of moisture in the coastal region by mitigating radiative cooling. Together with the moisture and heat supplied by the warm ocean surface, they contribute to the large amounts of precipitation here.

Agrivoltaic system success: A review of parameters that matter

Solar energy is a rapidly growing sector, and agrivoltaic farms are playing an increasingly important role in meeting the world's energy needs. However, as the size and complexity of these farms increase, so do the challenges associated with managing them efficiently. This article presents a comprehensive review of the fundamental parameters that underpin agrivoltaic systems. Focusing on the latest research, this review examines the challenges and opportunities intrinsic to the implementation of agrivoltaic energy systems, paying particular attention to the various parameters that contribute to their performance. These parameters encompass a range of factors such as heat islands, shading factors, and surface energy budget. The review underscores the importance of considering a diverse array of parameters when developing agrivoltaic energy systems to optimize their efficiency and effectiveness.

Laboratory Investigation of Energy Dissipation and Turbulent Mixing During Internal Solitary Wave Breaking on the Rough Shelf Slope

AbstractWhen internal solitary waves (ISW) propagate to the continental shelf, they typically runup and break on the forereef. This process might lead to periodic temperature drops at the reef slope, which has potential to protect coral reefs from bleaching threats. A series of laboratory experiments were conducted to investigate turbulence characteristics and energy dissipation during the ISW breaking events on the shelf slope with different bottom roughness to mimic the forereef environment. Particle image velocimetry (PIV) and planar laser‐induced fluorescence (PLIF) were coupled to obtain simultaneous high‐resolution velocity and density fields, based on which we then calculate the energy budget and turbulent dissipation rate. We found that the ISW breaking can be divided into two turbulent processes, the production of shear instability and coherent structures. Ratio of energy loss is weakened with the increase of bottom roughness and the collapse height, while the rough structure substantially enhanced the turbulent dissipation rate. The mixing efficiency is between 0.1 and 0.3, close to its maximal rate at 0.25. Our results reveal that the bottom roughness has impact on the mixing efficiency and turbulent process during the ISW breaking events. We found that rough structures at the shelf slope inhibit the mixing efficiency, especially in cases with small amplitude incline ISW. This finding may help us to better understand the reef damage and coral reef decline and support the management of coral protection strategy.

Estimation of Surface Sensible Heat Flux due to Precipitation over CONUS and Its Impact on Urban Extreme Precipitation Modeling

Abstract The surface sensible heat flux induced by precipitation (QP) is a consequence of the temperature difference between the surface and the rain droplets. Despite its seemingly negligible nature, QP is frequently omitted from both meteorological and climatological models. Nevertheless, it is important to acknowledge the numerous occasions in which the instantaneous values of QP can be significant, particularly during extreme precipitation events. This study undertakes a comprehensive assessment of QP across the contiguous United States (CONUS) utilizing high-resolution reanalysis, observational data, and numerical modeling to examine the influence of QP on precipitation and the surface energy budget. The findings indicate that the spatial distribution of QP climatology is analogous to that of precipitation, with magnitudes ranging from 2 to 3 W m−2 predominantly over the Midwest and Southeast regions. A seasonal analysis of QP reveals that the highest values occurring during the June–August (JJA) period, averaging 3.18 W m−2. Peak QP values of approximately 4 W m−2 are observed during JJA over the Great Plains region. We hypothesize that the QP during an extreme precipitation event would be nonnegligible and have a significant impact on the local weather. To test this conjecture, we perform high-resolution simulations with and without QP during an extreme precipitation event over the Chicago Metropolitan Area (CMA). The results show that the QP may be a dominant factor compared to other components of surface heat flux during the zenith of precipitation hours. Also, QP has the potential to not only diminish precipitation but also alter and reconfigure the remaining surface energy budget components.

On-fault earthquake energy density partitioning from shocked garnet in an exhumed seismic midcrustal fault.

The energy released during an earthquake is mostly dissipated in the fault zone and subordinately as radiated seismic waves. The on-fault energy budget is partitioned into frictional heat, generation of new grain surface by microfracturing, and crystal-lattice distortion associated with dislocation defects. The relative contribution of these components is debated and difficult to assess, but this energy partitioning strongly influences earthquake mechanics. We use high-resolution scanning-electron-microscopy techniques, especially to analyze shocked garnet in a fault wall-rock, to provide the first estimate of all three energy components for a seismic fault patch exhumed from midcrustal conditions. Fault single-jerk seismicity is recorded by the presence of pristine quenched frictional melt. The estimated value of energy per unit fault surface is ~13 megajoules per square meter for heat, which is predominant with respect to both surface energy (up to 0.29 megajoules per square meter) and energy associated with crystal lattice distortion (0.02 megajoules per square meter).

Using Bright Point Shapes to Constrain Wave Heating of the Solar Corona: Predictions for DKIST

Magnetic bright points on the solar photosphere mark the footpoints of kilogauss magnetic flux tubes extending toward the corona. Convective buffeting of these tubes is believed to excite magnetohydrodynamic waves, which can propagate to the corona and deposit heat there. Measuring wave excitation via bright point motion can thus constrain coronal and heliospheric models, and this has been done extensively with centroid tracking, which can estimate kink-mode wave excitation. DKIST is the first telescope to provide well-resolved observations of bright points, allowing shape and size measurements to probe the excitation of other wave modes that have been difficult, if not impossible, to study to date. In this work, we demonstrate a method of automatic bright point tracking that robustly identifies the shapes of bright points, and we develop a technique for interpreting measured bright point shape changes as the driving of a range of thin-tube wave modes. We demonstrate these techniques on a MURaM simulation of DKIST-like resolution. These initial results suggest that modes other than the long-studied kink mode could increase the total available energy budget for wave heating by 50%. Pending observational verification as well as modeling of the propagation and dissipation of these additional wave modes, this could represent a significant increase in the potency of wave-turbulence heating models.

Remote sensing and spectroscopy of lichens.

Lichens are combinations of two symbiotic organisms, a green alga or cyanobacterium and a fungus. They grow in nearly all terrestrial ecosystems and survive in habitats, which are very dry or cold, or too poor in nutrients to maintain vegetation growth. Because lichens grow on visible surfaces and exhibit spectral properties, which are clearly different from, for example, vegetation, it is possible to distinguish them in remote sensing data. In this first systematic review article on remote sensing of lichens, we analyze and summarize which lichen species or genera, and in which habitats and geographical regions, have been remotely sensed, and which remote sensing or spectroscopic technologies have been used. We found that laboratory or insitu measured spectra of over 70 lichen species have been reported to date. We show that studies on remote sensing of lichens fall under seven broad themes: (1) collection of lichen spectra for quantification of lichen species or characteristics, (2) pollution monitoring with lichens as ecological indicators, (3) geological and lithological mapping, (4) desert and dryland monitoring, (5) animal habitat monitoring, (6) land cover or vegetation mapping, and (7) surface energy budget modeling.

Melt pond fractions on Arctic summer sea ice retrieved from Sentinel-3 satellite data with a constrained physical forward model

Abstract. The presence of melt ponds on Arctic summer sea ice significantly alters its albedo and thereby the surface energy budget and mass balance. Large-scale observations of melt pond coverage and sea ice albedo are crucial to investigate the role of sea ice for Arctic amplification and its representation in global climate models. We present the new Melt Pond Detection 2 (MPD2) algorithm, which retrieves melt pond, sea ice, and open-ocean fractions as well as surface albedo from Sentinel-3 visible and near-infrared reflectances. In contrast to most other algorithms, our method uses neither fixed values for the spectral albedo of the surface constituents nor an artificial neural network. Instead, it aims for a fully physical representation of the reflective properties of the surface constituents based on their optical characteristics. The state vector X, containing the optical properties of melt ponds and sea ice along with the area fractions of melt ponds and open ocean, is optimized in an iterative procedure to match the measured reflectances and describe the surface state. A major problem in unmixing a compound pixel is that a mixture of half open water and half bright ice cannot be distinguished from a homogeneous pixel of darker ice. In order to overcome this, we suggest constraining the retrieval with a priori information. Initial values and constraint of the surface fractions are derived with an empirical retrieval which uses the same spectral reflectances as implemented in the physical retrieval. The snow grain size and optical thickness change with time, and thus the ice surface albedo changes throughout the season. Therefore, field observations of spectral albedo are used to develop a parameterization of the sea ice optical properties as a function of the temperature history of the sea ice. With these a priori data, the iterative optimization is initialized and constrained, resulting in a retrieval uncertainty of below 8 % for melt pond and 9 % for open-ocean fractions compared to the reference dataset. As reference data for evaluation, a 10 m resolution product of melt pond and open-ocean fraction from Sentinel-2 optical imagery is used.

Analysis and Modeling of Turbulence Anisotropy of a Swirled Hot Streak Flow

Abstract This study is carried out in the context of hot streak flows in high-pressure turbines, for which a correct prediction of the temperature evolution is required. The present work particularly focuses on the turbulence anisotropy analysis of a swirled hot streak flow in a bent channel representative of a nozzle guide vane (NGV) passage of a high-pressure turbine. Large-eddy simulations are conducted with the in-house solver IC3 in order to measure and characterize the anisotropy of turbulence. Moreover, to evaluate turbulence modeling, steady simulations of the bent channel are performed with the elsA software, which solves the Reynolds-averaged Navier–Stokes (RANS) equations. LES is first used to complete a turbulent kinetic energy (TKE) budget that enables to understand the energetic transfers associated with turbulence. This budget reveals two distinct zones where turbulence activity is impacted when the curvature is reached. The analysis of the anisotropy of turbulence based on two metrics highlights a misalignment of the Reynolds stress tensor and the mean strain-rate tensor (Schmitt's criterion), and a strong anisotropy developing inside the bent duct (Lumley's analysis) that may cause the failure of the classical RANS turbulence models based on Boussinesq's hypothesis. To check this hypothesis, RANS is positioned against LES with different turbulence models that accounts or not for the anisotropy of turbulence. Both turbulence activity (TKE budgets, Lumley's analysis) and aerothermal fields (radial distributions) are compared. Results show that Explicit Algebraic Reynolds Turbulence Models (EARSM) enable to better account for the anisotropy of turbulence, which in turn promote a better prediction of temperature, both in terms of intensity and trajectory.

An evaluation of energy and carbon budgets in diverse cropping systems for sustainable diversification of rainfed uplands in India's eastern hill and plateau region

With increasing cost and use of energy in agriculture, the traditional practice of mono-cropping of rice in upland is neither sustainable nor eco-friendly. It is necessary to identify crop diversification options with high energy efficiency, productivity, and low global warming potential (GWP). In this experiment, an inclusive system analysis was accomplished for 3 years (2016–2019) of five mono-cropping production (MCP) systems namely rice (R), finger millet (FM), black gram (BG), horse gram (HG), pigeon pea (PP), and four intercropped systems viz. R+BG, R+HG, FM+ BG, and FM + HG. The key objective was to evaluate the flow of energy, carbon balance, and GWP of these varied production systems. Puddled rice was recorded as an energy-exhaustive crop (27,803 MJ ha−1), while horse gram was noted to have the lowest energy use (26,537 MJ ha−1). The total energy output from pigeon pea (130,312 MJ ha−1) and diversified intercropped systems (142,135 MJ ha−1) was 65.3% and 80.3% higher than mono-cultured systems, respectively. Rice and rice-based intercropping production systems showed higher carbon footprints (1,264–1,392 kg CO2 eq. ha−1). Results showed that R+BG and R+HG were the most energy-efficient production systems, having higher energy ratio (5.8 and 6.0), higher carbon efficiency (7.41 and 8.24), and carbon sustainability index (6.41 and 7.24) as against 3.30, 3.61, and 2.61 observed under sole cropping production systems. On average, rice and rice-based production systems had 7.4 times higher GWP than other production systems. In productivity terms, pigeon pea and FM+HG had higher rice equivalent yields of 8.81 and 5.79 t ha−1 and benefit-cost ratios of 2.29 and 1.87, respectively. Thus, the present study suggests that pigeon pea and finger millet-based intercropping systems were the most appropriate crop diversification options for the rainfed upland agro-ecosystem of the eastern region of India.

Transients obscured by dusty discs

ABSTRACT Dust absorption is invoked in a number of contexts for hiding a star that has survived some sort of transient event from view. Dust formed in a transient is expanding away from the star and, in spherical models, the mass and energy budgets implied by a high optical depth at late times make such models untenable. Concentrating the dust in a disc or torus can in principle hide a source from an equatorial observer using less mass and so delay this problem. However, using axisymmetric dust radiation transfer models with a range of equatorial dust concentrations, we find that this is quite difficult to achieve in practice. The polar optical depth must be either low or high to avoid scattering optical photons to equatorial observers. Most of the emission remains at wavelengths easily observed by JWST. The equatorial brightness can be significantly suppressed for very discy configurations with little polar optical depth – but only by a factor of ∼2 for polar optical depths of τp = 1 and ∼5 for τp = 0.1 even for a very high optical depth disc (τe = 1000) viewed edge-on. It is particularly difficult to hide a source with silicate dusts because the absorption feature near 10 µm frequently leads to the emission being concentrated just bluewards of the feature, near 8 µm.

Inclusion of the radiative effect of deep convective clouds in the Eta model simulations

AbstractConvective clouds play an important role in the local energy budget by directly interacting with solar and terrestrial radiation. However, radiation parameterization schemes of atmospheric models generally consider clouds produced from microphysics schemes or some other grid saturation criteria. Deep convective parameterization schemes tend to rain out the convective cloud before the radiation scheme perceives its water load. This may be a source of the positive bias of the incoming solar radiation at the surface. The objective of this work is to include the effects of deep convective clouds in the radiation scheme of the regional Eta model and to evaluate the impacts on the net radiative energy and other meteorological variables. The radiation scheme is the Rapid Radiative Transfer Model. The work is developed in four stages. The positive bias in the incoming solar radiation was diagnosed in the first stage. In the second stage, the parameters of the convective parameterization scheme were modified to increase convective precipitation. In the third stage, the parameters of the microphysics scheme were modified to increase explicit clouds. In the fourth and last stage, in addition to the previous modifications, the condensates from the convective parameterization were input into the radiation scheme. The runs were performed for a period of one summer rainy month with intense convective activity over South America. Including deep convective cloud condensates into the radiation scheme improved the cloud cover, the diurnal cycle of the surface net radiation, and the 2‐m temperature. However, the reduction of the net radiation at the surface caused the reduction of the available energy for convective instability and, consequently, the precipitation reduction. The results show the importance of including cumulus cloud water load in the radiative scheme for bias reduction in the radiative energy components.