Lower Boundary Condition Research Articles

Assessing the Performance of Flux Imbalance Prediction Models Using Large Eddy Simulations Over Heterogeneous Land Surfaces

Accurate representation of heat fluxes is crucial for understanding land–atmosphere interactions and improving atmospheric simulations. However, a common issue arises with flux imbalance, where the measured turbulent heat flux tends to be underestimated due to the nonlocal effects of atmospheric secondary circulations. This study evaluated four flux imbalance prediction models by analyzing data from large eddy simulations performed over heterogeneous land surfaces. For that, a checkerboard pattern of soil moisture was used to define the lower boundary conditions for the atmosphere, across heterogeneity scales ranging from 50 m to 2.4 km. The results show that the selected models can effectively predict flux imbalance when provided with proper semi-empirical factors. The presence of two distinct secondary circulations, thermally-induced mesoscale circulation and turbulent organized structures, account for the nonlinear effect of the heterogeneity scale on the flux imbalance, but it does not affect the performance of the selected models. This study suggests that the flux imbalance prediction models are useful for improving e.g. eddy-covariance measurements. Additionally, a quadrant analysis showed an increasing difference between ejections and sweeps with height, which explains the decrease and increase of the turbulent heat flux and flux imbalance, respectively, and underscores the importance of accounting for vertical variations in turbulent fluxes to represent atmospheric processes accurately.

Compressible and anelastic governing-equation solution methods for thermospheric gravity waves with realistic background parameters

Abstract abstract A previously developed numerical-multilayer modeling approach for systems of governing equations is extended so that unwanted terms, resulting from vertical variations in certain background parameters, can be removed from the dispersion-relation polynomial associated with the system. The new approach is applied to linearized anelastic and compressible systems of governing equations for gravity waves including molecular viscosity and thermal diffusion. The ability to remove unwanted terms from the dispersion-relation polynomial is crucial for solving the governing equations when realistic background parameters, such as horizontal velocity and temperature, with strong vertical gradients, are included. With the unwanted terms removed, previously studied dispersion-relation polynomials, for which methods for defining upgoing and downgoing vertical wavenumber roots already exist, are obtained. The new methods are applied to a comprehensive set of medium-scale time-wavepacket examples, with realistic background parameters, lower boundary conditions at 30 km altitude, and modeled wavefields extending up to 500 km altitude. Results from the compressible and anelastic model versions are compared, with compressible governing-equation solutions understood as the more physically accurate of the two. The new methods provide significantly less computationally expensive alternatives to nonlinear time-step methods, which makes them useful for comprehensive studies of the behavior of viscous/diffusive gravity waves and also for large studies of cases based on observational data. Additionally, they generalize previously existing Fourier methods that have been applied to inviscid problems while providing a theoretical framework for the study of viscous/diffusive gravity waves. Graphic abstract

A Statistical Study of the Day‐To‐Day Variability of Diurnal and Semidiurnal Tides in the Ionospheric Dynamo Region From MIGHTI/ICON Observations

AbstractThe statistics of day‐to‐day tidal variability within 35‐day running mean windows is obtained from Michelson Interferometer for Global High‐Resolution Thermospheric Imaging (MIGHTI)/Ionospheric Connection Explorer (ICON) observations in the 90–107 km height region for the year 2020. Temperature standard deviations for 18 diurnal and semidiurnal tidal components, and for four quasi‐stationary planetary waves are presented, as function of latitude, altitude, and day‐of‐year. Our results show that the day‐to‐day variability (DTDV) can be as large as 70% of the monthly mean amplitudes, thus providing a significant source of variability for the ionospheric E‐region dynamo and hence for the F‐region plasma. We further validate our results with COSMIC‐2 ionospheric observations and present an approach to extend the MIGHTI/ICON results to all latitudes using Hough Mode Extension fitting, to produce global tidal fields and their statistical DTDV that are suitable as lower boundary conditions for nudging and ensemble modeling of TIE‐GCM. In the future, this will likely help to establish a data‐driven perspective of space weather variability caused by the tidal weather of the lower atmosphere.

Development of Node-centered finite-volume diffusion method on triangle mesh for detonation propagation simulation in insensitive high explosives

This study presents a numerical simulation of detonation waves in insensitive high explosives (IHE). A direct numerical simulation (DNS) method of detonation waves propagation was developed. It solves two-dimensional reactive Euler equations by using a semi-discrete node-centered finite-volume (NCFV) scheme on triangle mesh. Employing ZND model analytical solution as the initial condition, the upper and lower boundary conditions were designed as local sonic equilibrium conditions. The DNS method was validated using steady detonation wave propagation experimental results for tri-amino-tri-nitro-benzene (TATB) based explosives. The two-dimensional steady detonation propagation of the circular arc experiments was completed using a non-embedded technique (electric and optical fibre probe velocimetry). The comparison results demonstrate that the numerical method can provide a good prediction of the pseudo-steady-state detonation wave front propagation and the angular speed.

Computational Lower Limb Simulator Boundary Conditions to Reproduce Measured TKA Loading in a Cohort of Telemetric Implant Patients.

Recent advancements in computational modeling offer opportunities to refine total knee arthroplasty (TKA) design and treatment strategies. This study developed patient-specific simulator external boundary conditions (EBCs) using a PID-controlled lower limb finite element (FE) model. Calibration of the external actuation required to achieve measured patient-specific joint loading and motion was completed for nine patients with telemetric implants during gait, stair descent, and deep knee bend. The study also compared two EBC scenarios: activity-specific hip AP motion and pelvic rotation (that was averaged across all patients for an activity) and patient-specific hip AP motion and pelvic rotation. Including patient-specific data significantly improved reproduction of joint-level loading, reducing root mean squared error between the target and achieved loading by 28.7% and highlighting the importance of detailed patient data in replicating joint kinematics and kinetics. The principal component analysis (PCA) of the EBCs for the patient dataset showed that one component represented 77.8% of the overall variation, while the first three components represented 97.8%. Given the significant loading variability within the patient cohort, this group of patient-specific models can be run individually to provide insight into expected TKA mechanics variability, and the PCA can be utilized to further create reasonable EBCs that expand the variability evaluated.

Numerical Prediction Uncertainty and Data Worth Analysis of Solute Transport in an Agricultural Clay Till Setting With Preferential Flow

AbstractWith modern agricultural practices, it is essential to quantify flow and solute transport fluxes by numerical models and associated predictions. A major challenge in modeling preferential flow settings is the ability to constrain the often numerous parameters needed to physically represent these systems. Following this, there is a lack of understanding of what parameters and observations carry the most worth for a model to reduce its prediction uncertainty. Here, first‐order second moment (FOSM) analyses were used for a heavily monitored clay till field with preferential flow to investigate which parameters and observation types contribute the most to reducing the uncertainty of bromide predictions at various depths. Using a multi‐objective regularized optimization approach, a 1‐D preferential flow model was calibrated and subjected to FOSM analyses. Key parameters contributing to the prediction uncertainty of bromide concentrations in 0.25–3 m were limited to the lower boundary condition, the mass transfer coefficient, the hydraulic conductivity of the micro‐ and macropore, the macropore porosity, and the water content at wilting point. The data with the largest worth and ability to reduce the pre‐calibration prediction uncertainty were concentration observations closest to the sought prediction depth, drain concentrations, and averaged water table measurements from the entire field. The post‐calibration prediction uncertainty was increased primarily by removing concentration observations closest to the prediction depths. While this study provided new insights into parameter importance and data worth further research is required to understand if these findings apply broadly to clay till settings (or any soil setting) with preferential flow.

Modeling water flow and volumetric water content in a degraded peat comparing unimodal with bimodal porosity and flux with pressure head boundary condition

AbstractDegraded peatlands release large amounts of greenhouse gases. The development of effective mitigation and management measures requires an understanding of relevant site‐specific biogeochemical and hydraulic processes. However, the simulation of water fluxes and vadose zone state variables of degrading peatlands relies on proper process description, parameterization of hydraulic functions, and representation of the boundary conditions. The objective of this study was to analyze the effects of unimodal versus bimodal soil hydraulic functions and pressure head versus flux‐type lower boundary conditions (LBCs) on the calculated hydraulic characteristics of a degraded peat profile. HYDRUS‐1D was used to study the hydraulic flow dynamics parameterized with data from a weighable groundwater lysimeter for the period from May 1 to December 31, 2019. Simulations comparing uni‐ and bimodal hydraulic functions showed only minor differences. Simulations of soil water pressure at a depth of 30 cm using a flux‐type LBC (RMSE: 27 cm, where RMSE is root mean square error) performed better than simulations using a pressure head LBC (RMSE: 48 cm). The pressure head LBC performed better at simulating volumetric water contents in 30‐cm depth than the flux LBC variant (RMSE: 0.05 vs. 0.09 cm3 cm−3). For specific site conditions with a shallow, fluctuating groundwater table and temporary air entrapment, the choice of LBC was important for a more accurate simulation of soil water fluxes and volumetric water content.

Water Balance In Hapic Cambisols Under Forest And Pasture In The Bonfim Watershed: Mountainous Region Of Rio De Janeiro State

Objective: To estimate the water volumes of the main components of BH in a Haplic Cambisol in forests and pastures in the Bonfim River basin, mountainous region of RJ. Theoretical framework: The water balance (BH) accounts for the volumes of water input and output in a given space (Haplic Cambisols under forests and pastures). Method: The study period was 01/01/2000 and 12/31/2019. The HYDRUS-1D model was used to estimate water volumes in BH. Pedotransfer functions were used to determine the physical water parameters of water retention and conduction in the soil. The daily precipitation and evapotranspiration data were considered upper boundary conditions, and the lower boundary conditions were considered free drainage. Water absorption by the roots was considered as the additional factor (Sink factor) in the soil water mass balance. Results and conclusion: The average annual precipitation was 1462 mm and the potential evapotranspiration was 1026 mm. In lhe area under pastures: 83%, 7% and 9% of the total precipitated and percolated, transpired and evaporated, respectively. In areas under forests: these values were 43%, 51% and 6%. In the dry season, evapotranspiration was 20% of the total precipitation in the forest area and 8% in the pasture areas. Percolation in the dry season was 17% of the total precipitation in the pasture and 7% in the forest. In the rainy season the percolated values were 66% in the pasture and 36% in the forest. Implications of the research: Knowing the volumes of water in the components of the BH can help in decisions regarding the organization of land use and cover systems in basins of the Atlantic Forest biome. Changing soil use and cover systems alters the volumes of water percolated or evapotranspired. Originality/value: Estimating the water volumes in the BH components in pasture and forest allows predicting the effects of climate change and land use and their consequences.

Understanding snow saltation parameterizations: lessons from theory, experiments and numerical simulations

Abstract. Drifting and blowing snow are important features in polar and high mountain regions. They control the surface mass balance in windy conditions and influence sublimation of snow and ice surfaces. Despite their importance, model representations in weather and climate assessments have high uncertainties because the associated physical processes are complex and highly variable in space and time. This contribution investigates the saltation system, which is the lower boundary condition for drifting and blowing snow models. Using a combination of (previous) measurements and new physics-based modeling with large-eddy simulation (LES), we show that the prevailing parameterizations that describe the saltation system in atmospheric models are based on contradictory assumptions: while some scaling laws are typical of a saltation system dominated by aerodynamic entrainment, others represent a saltation system controlled by splash. We show that both regimes can exist, depending on the friction velocity. Contrary to sand saltation, aerodynamic entrainment of surface particles is not negligible. It is important at low wind speeds, leading to a saltation height and near-surface particle velocity which increase with the friction velocity. In a splash-dominated saltation regime at higher friction velocities, the saltation height and near-surface particle velocity become invariant with the friction velocity and closer to what is observed with sand. These findings are accompanied by a detailed description of the theoretical, experimental and numerical arguments behind snow saltation parameterizations. This work offers a comprehensive understanding of the snow saltation system and its scaling laws, useful for both modelers and experimentalists.

Three-dimension holographic numerical simulation of gravity anomalies

In gravity-anomaly-based prospecting, it is difficult to achieve large-scale and high-precision inversion imaging of complex geological models. To address this issue, this paper proposes a three-dimensional holographic numerical simulation method for gravity anomalies. This method transforms the 3D partial differential equation of gravity potential into many independent 1D differential equations with different wavenumbers by performing a 2D Fourier transform along the horizontal direction. It decomposes a large-scale 3D numerical modeling problem into many 1D numerical modeling problems, which greatly reduces the computation and memory requirements of modeling, and each 1D differential equation is independent, so it has high parallelism. The vertical direction is reserved as the spatial domain, which has strict upper and lower boundary conditions; The horizontal 2D Fourier transform uses a holographic Fourier transform (Holo-FT) with a full interval of integration, consistent with the physical boundary in the horizontal direction, thus the physical information of the gravity potential described by the three-dimensional partial differential equation is fully and accurately simulated. Using the high parallelism of the algorithm, the CPU is used for parallel solving ordinary differential equations, while the GPU is used for parallel computing of Holo-FT, which implements the CPU-GPU parallel acceleration scheme and further improves the efficiency of this algorithm.

Thermal structure of the southern Caribbean and northwestern South America: implications for seismogenesis

Abstract. The seismogenesis of rocks is mainly affected by their mineral composition and in situ conditions (temperature and state of stress). Diverse laboratory experiments have explored the frictional behaviour of the rocks and rock-forming minerals most common in the crust and uppermost mantle. However, it is debated how to “upscale” these results to the lithosphere. In particular, most earthquakes in the crust nucleate down to the crustal seismogenic depth (CSD), which is a proxy for the maximum depth of crustal earthquake ruptures in seismic hazard assessments. In this study we propose a workflow to upscale and validate those laboratory experiments to natural geological conditions relevant for crustal and upper-mantle rocks. We used the southern Caribbean and northwestern South America as a case study to explore the three-dimensional spatial variation of the CSD (mapped as D90, the 90 % percentile of hypocentral depths) and the temperatures at which crustal earthquakes likely occur. A 3D steady-state thermal field was computed for the region with a finite-element scheme using the software GOLEM, considering the uppermost 75 km of a previously published 3D data-integrative lithospheric configuration, lithology-constrained thermal parameters, and appropriate upper and lower boundary conditions. The model was validated using additional, independent measurements of downhole temperatures and heat flow. We found that the majority of crustal earthquakes nucleate at temperatures less than 350 ∘C, in agreement with frictional experiments of typical crustal rocks. A few outliers with larger hypocentral temperatures evidence nucleation conditions consistent with the seismogenic window of olivine-rich rocks, and can be due to either uncertainties in the Moho depths and/or in the earthquake hypocentres or the presence of ultramafic rocks within different crustal blocks and allochthonous terranes accreted to this complex margin. Moreover, the spatial distribution of crustal seismicity in the region correlates with the geothermal gradient, with no crustal earthquakes occurring in domains with low thermal gradient. Finally, we find that the largest earthquake recorded in the region (Mw=7.1, Murindó sequence, in 1992) nucleated close to the CSD, highlighting the importance of considering this lower-stability transition for seismogenesis when characterizing the depth of seismogenic sources in hazard assessments. The approach presented in this study goes beyond a statistical approach in that the local heterogeneity of physical properties is considered in our simulations and additionally validated by the observed depth distribution of earthquakes. The coherence of the calculated hypocentral temperatures with those expected from laboratory measurements provides additional support to our modelling workflow. This approach can be applied to other tectonic settings worldwide, and it could be further refined as new, high-quality hypocentral locations and heat flow and temperature observations become available.

Assessing the Sensitivity of Snow Depth Simulations to Land Surface Parameterizations within Noah-MP in Northern Xinjiang, China

Snow cover plays a crucial role in the surface energy balance and hydrology and serves as a key indicator of climate change. In this study, we conducted an ensemble simulation comprising 48 members generated by randomly combining the parameterizations of five physical processes within the Noah-MP model. Utilizing the variance-based Sobol total sensitivity index, we quantified the sensitivity of regional-scale snow depth simulations to parameterization schemes. Additionally, we analyzed the spatial patterns of the parameterization sensitivities and assessed the uncertainty of the multi-parameterization scheme ensemble simulation. The results demonstrated that the differences in snow depth simulation results among the 48 scheme combinations were more pronounced in mountain regions, with melting mechanisms being the primary factor contributing to uncertainty in ensemble simulation. Contrasting mountain regions, the sensitivity index for the physical process of partitioning precipitation into rainfall and snowfall was notably higher in basin areas. Unexpectedly, the sensitivity index of the lower boundary condition of the physical process of soil temperature was negligible across the entire region. Surface layer drag coefficient and snow surface albedo parameterization schemes demonstrated meaningful sensitivity in localized areas, while the sensitivity index of the first snow layer or soil temperature time scheme exhibited a high level of sensitivity throughout the entire region. The uncertainty of snow depth ensemble simulation in mountainous areas is predominantly concentrated between 0.2 and 0.3 m, which is significantly higher than that in basin areas. This study aims to provide valuable insights into the judicious selection of parameterization schemes for modeling snow processes.

Impacts of Topography‐Driven Water Redistribution on Terrestrial Water Storage Change in California Through Ecosystem Responses

AbstractLateral subsurface flow plays an essential role in sustaining the terrestrial ecosystem, but it is not explicitly represented in most Earth System Models. In this study, we implemented an explicit lateral saturated flow model into the E3SM land model (ELM). The model explicitly describes lateral flow in the saturated zone by representing, for each model grid, an idealized hillslope consisting of five hydrologically connected soil columns. We conducted three model experiments driven by 0.125° atmospheric forcing data during 1980–2015 over California using models of the default ELM, a modified version of ELM to enhance infiltration, and the model with the lateral saturated flow model. The simulated runoff, evapotranspiration, and terrestrial water storage anomaly (TWSA) from the three simulations were evaluated against available observations, and the model explicitly representing lateral flow performs best. The new model produces greater gridcell‐averaged evapotranspiration especially over the mountainous regions with moderate relief and seasonally dry climates. Most importantly, it improves the modeled seasonal variations, interannual variabilities, and the recent decadal decline of TWSA. Many of these improvements can be attributed to the enhanced ecosystem resilience to droughts as demonstrated by transpiration increases caused by lateral flow. Model sensitivity experiments suggest that subsurface runoff is most sensitive to the ratio between horizontal and vertical saturated hydraulic conductivity, followed by hillslope planforms (convergent, divergent, and uniform), number of columns, and lower boundary conditions. Future work should effectively characterize hillslopes in global models and explore the long‐term influences of lateral water movement on modeled biogeochemical cycle.

Modeling and Observations of the Effects of the Alfvén Velocity Profile on the Ionospheric Alfvén Resonator

AbstractWe have modeled the individual harmonic frequencies of the Ionospheric Alfvén Resonator (IAR) at Eskdalemuir by solving a one‐dimensional wave equation and using non‐uniform modeled Alfvén velocity profiles. By comparing the results of the modeling alongside harmonics obtained from the Eskdalemuir, UK, data set from 2013 to 2021, the effects of the non‐uniformity of the Alfvén velocity profile on the IAR are considered. We calculated the offset between the fundamental frequency and the harmonic frequency separation and found that this is not constant. From this parameter, we infer that the lower boundary condition of the electric field of the IAR is closest to a node, which agrees with previous studies. We compare the results of the non‐uniform model with previous uniform models and evaluate their interpretations and the implications for the lower boundary condition.

Exploring soil radon (Rn) concentrations and their connection to geological and meteorological factors.

The relationship between soil radon and meteorological parameters in a region can provide insight into natural processes occurring between the lithosphere and the atmosphere. Understanding this relationship can help models establish more realistic results, rather than depending on theoretical consequences. Radon variation can be complicated to model due to the various physical variables which can affect it, posing a limitation in atmospheric studies. To predict Rn variation from meteorological parameters, a hybrid mod el called multiANN, which is a combination of multi-regression and artificial neural network (ANN) models, is established. The model was trained with 70% of the data and tested on the remaining 30%, and its robustness was tested using the Monte-Carlo method. The regions with low performance are identified and possibly related to seismic events. This model can be a good candidate for predicting Rn concentrations from meteorological parameters and establishing the lower boundary conditions in seismo-ionospheric coupling models.

Can Sub‐Daily Multivariate Bias Correction of Regional Climate Model Boundary Conditions Improve Simulation of the Diurnal Precipitation Cycle?

AbstractThe diurnal cycle is often poorly reproduced in global climate model (GCM) simulations, particularly in terms of rainfall frequency and amplitude. While improvements in the regional climate model (RCM) with bias‐corrected boundaries have been reported in previous studies, they assumed that diurnal patterns are simulated correctly by the GCM, potentially leading to inaccuracies in the maximum rainfall timing and magnitude within the RCM domain. Here we provide the first examination of improvements to the diurnal cycle, within a RCM domain, achieved through the use of sophisticated bias‐corrected lateral and lower boundary conditions. Results show that the RCMs with bias‐corrected boundaries generally present improvement in capturing both rainfall timing and magnitude, particularly in northern Australia, where a strong diurnal pattern in rainfall is prevalent. We show that correcting systematic sub‐daily multivariate bias in RCM boundaries improves the diurnal rainfall cycle, which is particularly important in regions where short‐term intense precipitation occurs.

Description and evaluation of the new UM–UKCA (vn11.0) Double Extended Stratospheric–Tropospheric (DEST vn1.0) scheme for comprehensive modelling of halogen chemistry in the stratosphere

Abstract. The paper describes the development and performance of the Double Extended Stratospheric–Tropospheric (DEST vn1.0) chemistry scheme, which forms a part of the Met Office's Unified Model coupled to the United Kingdom Chemistry and Aerosol (UM–UKCA) chemistry–climate model, which is the atmospheric composition model of the United Kingdom Earth System Model (UKESM). The scheme extends the standard Stratospheric–Tropospheric chemistry scheme (StratTrop) by including a range of important updates to the halogen chemistry. These allow process-oriented studies of stratospheric ozone depletion and recovery, including the impacts from both controlled long-lived ozone-depleting substances (ODSs) and emerging issues around uncontrolled very short-lived substances (VSLS). The main updates in DEST are (i) an explicit treatment of 14 of the most important long-lived ODSs; (ii) an inclusion of brominated VSLS (Br-VSLS) emissions and chemistry; and (iii) an inclusion of chlorinated VSLS (Cl-VSLS) emissions/LBCs (lower boundary conditions) and chemistry. We evaluate the scheme's performance by comparing DEST simulations against analogous runs made with the standard StratTrop scheme and against observational and reanalysis datasets. Overall, our scheme addresses some significant shortcomings in the representation of atmospheric halogens in the standard StratTrop scheme and will thus be particularly relevant for studies of ozone layer recovery and processes affecting it, in support of future World Meteorological Organization (WMO) Ozone Assessment Reports.

Improving the Forecasts of Surface Latent Heat Fluxes and Surface Air Temperature in the GRAPES Global Forecast System

The GRAPES (Global/Regional Assimilation and Prediction System) global medium-range forecast system (GRAPES_GFS) is a new generation numerical weather forecast model developed by the China Meteorological Administration (CMA). However, the forecasts of surface latent heat fluxes and surface air temperature have systematic biases, which affect the forecasts of atmospheric dynamics by modifying the lower boundary conditions and degrading the application of GRAPES_GFS since the 2 m air temperature is one of the key components of weather forecast products. Here, we add a soil resistance term to reduce soil evaporation, which ultimately reduces the positive forecast bias of the land surface latent heat flux. We also reduce the positive forecast bias of the ocean surface latent heat flux by considering the effect of salinity in the calculation of the ocean surface vapor pressure and by adjusting the parameterizations of roughness length for the exchanges in momentum, heat, and moisture between the ocean surface and atmosphere. Moreover, we modify the parameterization of the roughness length for the exchanges in heat and moisture between the land surface and atmosphere to reduce the cold bias of the nighttime 2 m air temperature forecast over areas with lower vegetation height. We also consider the supercooled soil water to reduce the warm forecast bias of the 2 m air temperature over northern China during winter. These modified parameterizations are incorporated into the GRAPES_GFS and show good performance based on a set of evaluation experiments. This paper highlights the importance of the representations of the land/ocean surface and boundary layer processes in the forecasting of surface heat fluxes and 2 m air temperature.

Forecasting water discharges of the river Marmarik (Armenia) according to the kinematic wave equation

The article provides an overview of methods for short-term forecasting of water flow in mountain rivers based on physical-statistical and regression equations, conceptual approaches. Requirements for forecast models for the Armenian rivers are noted, which correspond to the kinematic wave model, but so far there are no forecast results for the Armenian rivers using this model. The purpose of the study was to test a mathematical model of a kinematic wave for a short-term forecast of water discharges on the mountainous Armenian river Marmarik. The model of a kinematic wave can be obtained after simplifying
 the model of channel runoff in a general form, i.e., after excluding from consideration deformations, local constant and variable backwaters from narrowing of channels, confluence of rivers, surge phenomena, and also after excluding the influence of the lower boundary condition, which is responsible for the characteristic of the diffusion spreading of the flood wave.
 A kinematic wave model was tested on the Marmarik River, which is an important water body in Armenia. We used series of observations of urgent water discharges during the spring flood from April 1 to June 30 for 2015—2018 at the top of the river Marmarik — Hankavan settlement, lower alignment — Aghavnadzor settlement and at the alignment on the main tributary of the river Gomraget — Meghradzor village. It was found that in the dynamic parametrization of the model, the anthropogenic impact should be introduced as an additional parameter. The obtained values of water discharges when making verification forecasts in the aggregate characterize the kinematic wave model as an effective approach according to
 the criteria for assessing the quality of forecast methods of the Hydrometeorological Center and Nash—Sutcliffe. The kinematic wave model is easy to use with a small amount of initial information without meteorological data, which will facilitate its implementation for practical applications.

Assessment of severe aerosol events from NASA MODIS and VIIRS aerosol products for data assimilation and climate continuity

Abstract. While the use and data assimilation (DA) of operational Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol data is commonplace, MODIS is scheduled to sunset in the next year. For data continuity, focus has turned to the development of next-generation aerosol products and sensors such as those associated with the Visible Infrared Imaging Radiometer Suite (VIIRS) on Suomi NPOESS Preparation Project (S-NPP) and NOAA-20. Like MODIS algorithms, products from these sensors require their own set of extensive error characterization and correction exercises. This is particularly true in the context of monitoring significant aerosol events that tax an algorithm's ability to separate cloud from aerosol and account for multiple scattering related errors exacerbated by uncertainties in aerosol optical properties. To investigate the performance of polar-orbiting satellite algorithms to monitor and characterize significant events, a level 3 (L3) product has been developed using a consistent aggregation methodology for 4 years of observations (2016–2019) that is referred to as the SSEC/NRL L3 product. Included in this product are the AErosol RObotic NETwork (AERONET), MODIS Dark Target, Deep Blue, and Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithms. These MODIS “baseline algorithms” are compared to NASA's recently released NASA Deep Blue algorithm for use with VIIRS. Using this new dataset, the relative performance of the algorithms for both land and ocean were investigated with a focus on the relative skill of detecting severe events and accuracy of the retrievals using AERONET. Maps of higher-percentile aerosol optical depth (AOD) regions of the world by product identified those with the highest measured AODs and determined what is high by local standards. While patterns in AOD match across products and median to moderate AOD values match well, there are regionally correlated biases between products based on sampling, algorithm differences, and AOD range – in particular for higher AOD events. Most notable are differences in boreal biomass burning and Saharan dust. Significant percentile biases must be accounted for when data are used in trend studies, data assimilation, or inverse modeling. These biases vary by aerosol regime and are likely due to retrieval assumptions in lower boundary conditions and aerosol optical models.