Meteorological Model Research Articles

Refining the Selection of Historical Period in Analog Ensemble Technique

A precise estimate of solar energy output is essential for its efficient integration into the power grid as solar energy becomes a more significant renewable energy source. Contrarily, the creation of solar energy involves fluctuation and uncertainty. The integration and operation of energy systems are complicated by the uncertainty in solar energy projection. As a post-processing technique to lower systematic and random errors in the operational meteorological forecast model, the analog ensemble algorithm will be introduced in this study. When determining the appropriate historical and predictive data required to use the approach, an optimization is conducted for the historical period in order to further maximize the capabilities of the analog ensemble. To determine statistical consistency and spread skill, the model is evaluated against both the raw forecast model and observations. The outcome lowers the uncertainty in the predicted data by demonstrating that statistical findings improve significantly even with 1-month historical data. Nevertheless, the optimization with a year’s worth of historical data demonstrates a notable decrease in the outcomes, limiting overestimation and lowering uncertainty. Specifically, analog ensemble algorithms calibrate analog forecasts that are equivalent to the latest target forecasts within a set of previous deterministic forecasts. Overall, we conclude that analog ensembles assuming a 1-year historical period offer a comprehensive method to minimizing uncertainty and that they should be carefully assessed given the specific forecasting aims and limits.

Even in a dew desert: Dewfall does not provide sufficient moisture for biocrust growth – Evidence from direct measurements and a meteorological model

Knowledge regarding the distribution of non-rainfall water (NRW) and particularly dew has great ecological importance. Nevertheless, the role of NRW as a water source for biocrusts is controversial, with most scholars attributing a central role to NRW as water source for biocrusts. Estimating the amounts of NRW and particularly dew is indeed challenging due to the interrelationship between vapor, temperature and wind. Recently, the use of NRW by biocrusts was also suggested following a meteorological model. Here we compare the amounts obtained by model calculation to the amounts of NRW as measured at 1 m-height above ground (used for meteorological models), and on cobbles, rocks and the soil surface in the Negev. While field measurements at 1 m-height above ground (averaging 0.144 mm/day) showed a fairly good fit (r = 0.52) with model calculation (averaging 0.147 mm/day), and the NRW measurements surpassed the threshold for net photosynthesis for lichens (0.05 mm) and occasionally for cyanobacteria (0.1 mm) on the rocky surfaces (averaging 0.093 mm/day for the cobbles and 0.042 mm/day for the rock slabs), it was substantially below these thresholds at the soil surface (averaging 0.009 mm/day). Our data imply that the amount of NRW reaching the soil surface is too low to provide the soil microorganisms sufficient water for net photosynthesis. With 0.5 mm/day marking the maximum theoretical dew value, the 16.9-fold lower amounts obtained by us at the soil surface in comparison to 1 m-height above ground (used by meteorological models) indicates only 0.03 mm/day at the soil surface, substantially below the required amounts for net photosynthesis by biocrusts. When estimating the amounts of NRW available for biocrusts, meteorological models must be adjusted in accordance with height above ground.

Simulating Microscale Urban Airflow and Pollutant Distributions Based on Computational Fluid Dynamics Model: A Review.

Urban surfaces exert profound influences on local wind patterns, turbulence dynamics, and the dispersion of air pollutants, underscoring the critical need for a thorough understanding of these processes in the realms of urban planning, design, construction, and air quality management. The advent of advanced computational capabilities has propelled the computational fluid dynamics model (CFD) into becoming a mature and widely adopted tool to investigate microscale meteorological phenomena in urban settings. This review provides a comprehensive overview of the current state of CFD-based microscale meteorological simulations, offering insights into their applications, influential factors, and challenges. Significant variables such as the aspect ratio of street canyons, building geometries, ambient wind directions, atmospheric boundary layer stabilities, and street tree configurations play crucial roles in influencing microscale physical processes and the dispersion of air pollutants. The integration of CFD with mesoscale meteorological models and cutting-edge machine learning techniques empowers high-resolution, precise simulations of urban meteorology, establishing a robust scientific basis for sustainable urban development, the mitigation of air pollution, and emergency response planning for hazardous substances. Nonetheless, the broader application of CFD in this domain introduces challenges in grid optimization, enhancing integration with mesoscale models, addressing data limitations, and simulating diverse weather conditions.

VogCast: A Framework for Modeling Volcanic Air Pollution and Its Application to the 2022 Eruption of Mauna Loa Volcano, Hawai'i

AbstractVolcanic activity and the associated gas emissions into the atmosphere often result in adverse air quality conditions and present a hazard to human health and the environment. Building on a decade‐long effort to provide operational surface sulfur dioxide and sulfate aerosol forecasts for the State of Hawai'i, we present an air quality modeling framework called VogCast. VogCast is designed to simplify ensemble air quality prediction on a regional scale by linking together multiple state‐of‐the‐art models of meteorology, emissions, and dispersion. The framework is open‐source and introduces a new dynamic plume‐rise algorithm for distributing pollutants vertically. Using radar and satellite data, we demonstrate that VogCast reasonably captured the mean injection height, the location, and the general envelope of the vog plume during Mauna Loa's 2022 eruption. The results suggest that during the 12‐day eruption period model performance varied between days with trade and non‐trade wind conditions. Our findings also highlight the importance of sulfur dioxide emission rate and vent parameter inputs for improving forecast accuracy. The broad goal of this work is to better our understanding of vog dispersion and improve air quality prediction for impacted communities.

Can meteorological model forecasts initialize hydrological simulations rather than observed data in ungauged basins?

AbstractFloods are among natural disasters which cause the largest damages worldwide each year, inducing fatalities of human lives, destruction of infrastructure and economical losses. Consequently, forecasting this type of events through hydro‐meteorological models is still of great importance from a civil protection point of view since it allows to reduce hydrological risk by means of early warning systems. Nevertheless, hydrological model initialization in ungauged basins, where there is lack of direct measurements of meteorological information, is a known issue affecting the entire prediction chain. The present study evaluates the possibility of using forecasts provided by the meteorological model MOLOCH developed by CNR‐ISAC forcing the FEST‐WB hydrological model developed by Politecnico di Milano to perform discharge simulations assuming that the forecasting errors are negligible when using the first 24 h of time horizon. The study is carried out in the urban catchments of Milan city, the Seveso‐Olona‐Lambro (SOL) river basins, located in northern Italy. The main hydro‐meteorological variables are analysed by comparing the spatialized and observed meteorological data, provided by an official regional network of weather stations plus a citizen scientists' contribution with the meteorological model forecasts. Moreover, a sensitivity analysis following the well‐known one‐factor‐at‐a‐time methodology is accomplished with the aim of defining which atmospheric forcing, beyond rainfall, mostly affects flowrate forecasts. Results generally show satisfactory correspondences between forecasts and observed data for the discharge variable at daily scale, although an underestimation of precipitation, particularly for severe events in summer, is present. Therefore, using meteorological forecasts to create daily initial conditions for hydrological model, instead of ground observations, might be a reliable and valuable approach, even if some considerations should be borne in mind when coupling the two models.

Genesis of equifinality and multifinality of open systems

The subject of research in the article are the properties of equifinality and multifinality of open systems, widely spread in all subject areas, at all levels of organization: in physical, chemical, biological, economic, social, etc. open systems. Equifinality is a dynamic property of a system that realizes movement (transition) in different ways from different initial states to the same final state. Multifinality is the dynamic property of a system to reach fundamentally different final states under insignificant changes in initial conditions. Examples of realization of the properties of equifinality and multifinality in systems of different nature: physical, biological, economic are considered. The genesis of these properties is investigated. On the basis of the study of the genesis of the properties of equifinality and multifinality its commonality is revealed: both properties are a consequence of the transformation of quasi-continuous quantitative changes into discrete qualitative forms, as well as the limited variety of these forms caused by isomorphism. The origin of the multiplicativity property (increased sensitivity to variation of input parameters) and its difference from multifinality are revealed. The multiplicativity property is manifested in systems with unequal stability, including those possessing positive feedback mechanisms. In some systems, such as meteorological mathematical models, the properties of multiplicativity and multifinality appear simultaneously and cannot be unambiguously distinguished.

The Michigan–Ontario Ozone Source Experiment (MOOSE): An Overview

The Michigan–Ontario Ozone Source Experiment (MOOSE) is an international air quality field study that took place at the US–Canada Border region in the ozone seasons of 2021 and 2022. MOOSE addressed binational air quality issues stemming from lake breeze phenomena and transboundary transport, as well as local emissions in southeast Michigan and southern Ontario. State-of-the-art scientific techniques applied during MOOSE included the use of multiple advanced mobile laboratories equipped with real-time instrumentation; high-resolution meteorological and air quality models at regional, urban, and neighborhood scales; daily real-time meteorological and air quality forecasts; ground-based and airborne remote sensing; instrumented Unmanned Aerial Vehicles (UAVs); isotopic measurements of reactive nitrogen species; chemical fingerprinting; and fine-scale inverse modeling of emission sources. Major results include characterization of southeast Michigan as VOC-limited for local ozone formation; discovery of significant and unaccounted formaldehyde emissions from industrial sources; quantification of methane emissions from landfills and leaking natural gas pipelines; evaluation of solvent emission impacts on local and regional ozone; characterization of the sources of reactive nitrogen and PM2.5; and improvements to modeling practices for meteorological, receptor, and chemical transport models.

Domain-specific implementation of high-order Discontinuous Galerkin methods in spherical geometry

In recent years, domain-specific languages (DSLs) have achieved significant success in large-scale efforts to reimplement existing meteorological models in a performance portable manner. The dynamical cores of these models are based on finite difference and finite volume schemes, and existing DSLs are generally limited to supporting only these numerical methods. In the meantime, there have been numerous attempts to use high-order Discontinuous Galerkin (DG) methods for atmospheric dynamics, which are currently largely unsupported in main-stream DSLs. In order to link these developments, we present two domain-specific languages which extend the existing GridTools (GT) ecosystem to high-order DG discretization. The first is a C++-based DSL called G4GT, which, despite being no longer supported, gave us the impetus to implement extensions to the subsequent Python-based production DSL called GT4Py to support the operations needed for DG solvers. As a proof of concept, the shallow water equations in spherical geometry are implemented in both DSLs, thus providing a blueprint for the application of domain-specific languages to the development of global atmospheric models. We believe this is the first GPU-capable DSL implementation of DG in spherical geometry. The results demonstrate that a DSL designed for finite difference/volume methods can be successfully extended to implement a DG solver, while preserving the performance-portability of the DSL.

Properties of the mixing layer height retrieved from ceilometer measurements in Slovakia and its relationship to the air pollutant concentrations.

Mixing layer height (MLH) is an important meteorological parameter for air quality since it significantly affects ground-level pollution in the atmosphere. This study examined the properties of the MLH on diurnal and seasonal timescales over a 3-year period (2020-2022) using high temporal resolution measurements from eight Vaisala CL31 ceilometers situated around Slovakia. Hourly averaged MLH data was retrieved from the BL-View software using merged method. The highest daily maxima for the MLH occurred mostly in summer and spring, while the lowest values occurred predominantly during winter and autumn. The average MLH daily maximum in summer was 2229m, and just 859m in winter. During summer, the spatial distribution of the MLH daily maxima was more uniform compared to winter, when the air masses within the individual valleys did not mix well. Correlations between ground-level pollutant concentrations and hourly mean/daily mean MLH were analyzed. The highest correlation, R≈0.6, was found for O3. For PM10, PM2.5, and NOx, the anticorrelations with MLH were found with maximum in winter (R ≈ - 0.3 for hourly data and R ≈ - 0.5 for daily mean data) but no relation in summer. Lastly, the ceilometer MLH was compared to the radiosonde retrieved MLH for various cloud covers. Our analysis is based on an extensive set of empirical data, which can improve the accuracy and effectiveness of meteorological and atmospheric chemistry models. The findings can support air pollution forecasting and warning systems, providing valuable insights for policymakers and researchers.

A Comprehensive Assessment of the Hydrological Evolution and Habitat Quality of the Xiangjiang River Basin

Human disturbance and climatic factors alter the hydrological state of rivers in many ways and have a degree of negative impact on the quality of watershed habitats; quantifying the impact of both human disturbance and climatic factors on hydrological change can help improve the quality of watershed habitats. Therefore, in this research, an integrated watershed assessment framework is proposed to analyse the watershed from four perspectives: hydrological situation, environmental flows, drivers, and habitat quality. A meteorological streamflow model based on the Long Short-Term Memory (LSTM) model was employed to analyse the hydrological evolution and quantify the influence of the drivers from the perspective of hydrological and environmental flows. The Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model was then used to evaluate the spatial and temporal evolution of habitat quality in the basin. And, finally, the grey correlation theory was used to reveal the response of habitat quality to hydrological changes. Studies have shown that annual flow and precipitation are increasing in the Xiangjiang River (XJR) basin, while its annual potential evapotranspiration is decreasing significantly. After 1991, the hydrological conditions of the XJR were highly variable, with the combined rate of change of the most Ecologically Relevant Hydrological Indicators, ERHIs-IHA and ERHIs-EFCs, reaching 26.21% and 121.23%, respectively. Climate change and human disturbance are the main drivers of change for both (with contributions of 60% and 71%, respectively). Between 1990 and 2020, the habitat quality in the basin declined over time (from 0.770 to 0.757), with areas of high habitat value located mainly in mountainous areas and habitat degradation being concentrated in urban areas in the middle and lower reaches, gradually evolving towards areas of high habitat value in the periphery. There is a strong correlation between watershed habitat quality and the ERHIs. The results of the study can provide a scientific basis for maintaining regional ecological security and rational allocation of water resources.

Influence of the lowest model level height and vertical grid resolution on mesoscale meteorological modeling

This study employed the Weather Research and Forecasting (WRF) model to investigate the roles of lowest model level height (LMLH) and vertical grid resolution (VGR) in mesoscale meteorological modeling. Statistical analysis suggests that the vertical configuration of the model has a minor impact on meteorological modeling under daytime convective boundary layer conditions. However, modifying the LMLH can have a noticeable effect on the surface meteorology simulation during nighttime, specifically in the simulations of the 2-m temperature and relative humidity. The contribution of the VGR was mainly reflected in the 10-m wind speed simulation. Further analysis showed that the discrepancies in the surface meteorology variables caused by the LMLH configurations were more apparent during pollution episodes than during regular days. The LMLH had a significant impact on surface meteorology, and the VGR primarily influenced vertical distributions. These findings indicate that the effects of the vertical configuration of the model on meteorological simulation are closely associated with the stability of the boundary layer, which will have important implications for subsequent chemical transport modeling. Decreasing the LMLH and refining the VGR both enhanced the stability of the nocturnal boundary layer, with negligible effects on the convective boundary layer prediction. Reducing the LMLH from 58 m to 30 m resulted in a 7.6% reduction in the simulation error of the surface meteorological variables. A further reduction to 12 m resulted in a 10.6% improvement without a significant increase in the computational cost.

Mineral magnetic proxies for evaluation of anthropogenic pollution at children's playgrounds – a case study from Sofia city

Quality of the urban environment where children play is of great concern for protecting their health. Thus, fast and economically feasible proxy methods for assessment of urban environment are increasingly applied. In this study, settled dust from 13 playgrounds from Sofia city (Bulgaria), was investigated by mineral magnetism, portable X-ray fluorescence measurements, and scanning electron microscopy. The aim of the study was to evaluate the degree of anthropogenic pollution of playgrounds during winter and summer seasons and to identify pollution sources. Magnetic susceptibility (χ) was measured for two dust fractions - very coarse (grain sizes between 1 and 2 mm) and size fraction of d < 1 mm. In spite of this rough separation, systematic seasonal difference in χ of the two fractions is observed. Winter dust, containing larger amount of finer fraction shows lower χ. Regardless of lower relative content of d < 1 mm fraction, summer playground dusts are more strongly magnetic. Complex Pollution Load Index (PLI), calculated using contents of Cu, Zn, S, Pb (Potentially Toxic Elements (PTE)), shows higher contamination in summer dust, compared to winter. Anhysteretic and isothermal remanences of dust d < 1 mm demonstrate prevailing magnetically stable grains at playgrounds located at greater distance from major boulevards. Thermomagnetic analyses of magnetic susceptibility identified magnetite as the main magnetic mineral, although metallic iron was also evident in summer dust. Based on the meteorological models of atmospheric circulation over Sofia, the pollution sources suggested in a previous research, on one hand, and the carried out Factor Analysis, on the other hand, the results point out that in spite of higher PM10 dust load in winter, summer dust pollution causes stronger PTEs contamination. Factor analysis revealed four factors, explaining most of variability in the data. These factors were identified as: 1) re-suspension of soil and road dust; 2) fine particles magnetite of stable single domain grain size, originating probably from traffic exhaust and non-exhaust emissions; 3) emissions from installations burning waste materials; 4) coal burning.

Climate-induced decline in the quality and quantity of European hops calls for immediate adaptation measures

A recent rise in the global brewery sector has increased the demand for high-quality, late summer hops. The effects of ongoing and predicted climate change on the yield and aroma of hops, however, remain largely unknown. Here, we combine meteorological measurements and model projections to assess the climate sensitivity of the yield, alpha content and cone development of European hops between 1970 and 2050 CE, when temperature increases by 1.4 °C and precipitation decreases by 24 mm. Accounting for almost 90% of all hop-growing regions, our results from Germany, the Czech Republic and Slovenia show that hop ripening started approximately 20 days earlier, production declined by almost 0.2 t/ha/year, and the alpha content decreased by circa 0.6% when comparing data before and after 1994 CE. A predicted decline in hop yield and alpha content of 4–18% and 20–31% by 2050 CE, respectively, calls for immediate adaptation measures to stabilize an ever-growing global sector.

Hurricane wind regimes for forests of North America

Despite the ubiquity of tropical cyclones and their impacts on forests, little is known about how tropical cyclone regimes shape the ecology and evolution of tree species. We used a simple meteorological model (HURRECON) to estimate wind fields from hurricanes in the Western North Atlantic and Eastern North Pacific tropical cyclone basins from storms occurring between 1851 and 2022. We characterize how the intensity and frequency of hurricanes differ among geographically distinct hurricane regimes and define four hurricane regimes for North America (Continental, Inland, Coastal, and Fringe). Along this coastal-to-inland gradient, we found major differences in the frequency and intensity of hurricane wind regimes. The Fringe regime experiences category 1 winds relatively frequently [return period (RP) 25 y], whereas the Inland regime experiences category 1 winds very infrequently (RP ~3,000 y). We discuss how species traits related to tree windfirmness, such as mechanical properties and crown traits, may vary along hurricane regime gradients. Quantitative characterization of forest hurricane regimes provides a critical step for understanding the evolutionary and ecological role of hurricane regimes in wind-prone forests.

Integrating burned area as a complementary performance measure for daily fire danger assessment: A large-scale test

Fire indices are used to describe the weather conditions that influence fire ignition and fire behavior. Although many studies analyzed their performance on fire occurrence at daily resolution, few focused on their ability to capture the burned area, which is usually analyzed at the weekly or monthly scale. Cumulative Logarithmic Area Ranking Efficiency (CLARE) is a newly developed metric that takes burned area into account when assessing daily fire danger. The use of CLARE in addition to the Area Under the receiver operating characteristic Curve (AUC) in the selection process of fire indices or fire occurrence models provides a complementary metric that allows for the evaluation of a model's ability to assess burned area. We evaluated the CLARE performance in 11 regions ranging from the European Alps to the Mediterranean basin. We also assessed the impact of (i) different groups of input variables (meteorological variables vs. fire indices), (ii) model complexity in terms of number of variables, and (iii) the modeling approach (Generalized Linear Models vs. Maxent) on the performance of CLARE. We found that models that achieve a high AUC for predicting fire occurrence may fail to show a high performance when predicting burned area. Using a multi-variable modeling approach is likely to provide higher CLARE performance than using single-variable fire index models, especially among models that have high AUC. Moreover, using this approach led to better multi-variable meteorological model performance than single-variable fire index models for some regions. This may be particularly valuable for regions where the calculation of fire indices is not possible. Finally, the differences between the modeling approaches were mainly related to the region or input variable groups. Overall, our results highlight that including burned area in the fire danger assessment process is feasible across a wide range of environmental conditions and provides valuable insights.

Advantage of bulk lightning models for predicting lightning frequency over Japan

This study examined the performance of an explicit bulk lightning model coupled with a meteorological model for forecasting lightning by numerical weather prediction over Japan. The evaluation was conducted by comparing the lightning predicted by the explicit bulk lightning model, diagnosed empirically by the numerical model, and observed by ground base measurements. From the results, the bulk lightning model performed better in terms of lightning frequency than did the diagnostic scheme, which overestimated the lightning frequency, although there were no appreciable differences in the score of each method for the geographical distribution and time correlation compared with the observations. These results suggest that the explicit bulk lightning model is advantageous for predicting lightning frequency. The sensitivity of the simulated lightning to the choice of cloud microphysical model was also examined by using a two-moment and a one-moment bulk microphysical scheme. Sensitivity experiments on the choice of microphysical model indicated that the two-moment bulk scheme reproduced the observed lightning well, while the one-moment bulk scheme overestimated the lightning frequency. Analyses suggested that the overestimation of the lightning in the one-moment bulk scheme originated from active charge separation by riming electrification, in which graupel was produced more frequently and was assumed to fall faster. These results suggest that the explicit bulk lightning model with the two-moment bulk microphysical scheme offers an alternative to conventional lightning prediction methods.Graphical abstract

A harmonic oscillator model of atmospheric dynamics using the Newton-Kepler planetary approach

Projection of future meteorological patterns such as median temperature and precipitation are necessary for governments to facilitate civil aviation, forecast agricultural productions, and advise future public energy policies. Various models were proposed based on historical data such as the short-term 7-day forecast or the long-term Global Forecast System to study climate change over the coming decades. We strike a balance by examining the harmonic oscillator model in mid-term weather projections. This model is the starting point to provide general mathematical guidelines to inform governmental agencies to forecast levels of energy consumptions for residential cooling in summer and heating in winter to provide energy subsidies for low-income populations and for non-profit organizations to support countries needing energy assistance. Additionally, mid-term meteorological models are especially useful during time of global energy disruptions. A model is derived based on orbital mechanics, planetary science, and astronomy using Newton’s Law of Universal Gravitation and Kepler’s Laws of Planetary Motions. We optimize the model with historical data on a specific region. The model’s predictions were then statistically compared with the actual data in the same time period in the region in a reverse goodness of fit test. We also gave certain directions on the generalized harmonic oscillator model in the future. In sum, the current harmonic oscillator method can be beneficially utilized by governments to forecast natural phenomena in order to provide timely assistance to respective populations such as in the control of infectious diseases or predicting extreme temperature fluctuations in the planning of agricultural productions.

Atmospheric 137Cs dispersion following the Fukushima Daiichi nuclear accident: Local-scale simulations using CALMET and LAPMOD

This paper investigates a local-scale radionuclide dispersion modeling, focusing on the 20 km range of the Fukushima accident. The California Meteorological Model (CALMET) was used to calculate the diagnostic wind fields for simulation using on-site meteorological observations, and the Lagrangian Particle Model (LAPMOD) was used to simulate the dispersion of the 137Cs. The simulation was validated against the measurement from two 137Cs airborne concentration stations (Futaba and Naraha). A comprehensive sensitivity analysis was implemented to the source term, the number of particles per second, and the disturbance in wind speed and direction. The results show that the simulation agrees well with the measurement at Futaba (Geometric Mean Bias: 0.79, Fractional Mean Bias: 0.58) than that at Naraha (Geometric Mean Bias: 1.01, Fractional Mean Bias: 0.52), especially for the peak values. The sensitivity analysis indicates that the simulation is highly affected by the source term and the wind direction.

Evaluation of meteorological microphysical schemas based on the WRF model for simulation of rainfall in the northeastern region of Iran

Study regionThe Khorasan Razavi Province represents a variety of climatic types in the northeastern region of Iran. It lies between 56° 19′ and 61° 16′ east longitude and 33° 52′–37° 42′ north latitude, which is one of the largest and most densely populated provinces in Iran. Study focusThe aim of this study is using the Weather Research and Forecasting (WRF) model to evaluate and simulate rainfall in the northeastern region of Iran based on the climatic conditions in order to rainfall forecasting, also warn about and control probable floods. New hydrological insights for the regionFollowing the climatic classification of the study area, the six WRF model schemas were employed to implement the model in this area: Purdue-Lin (Lin), WRF Single-Moment class 3, 5, 6 (WSM3, WSM5, WSM6), and WRF Double-Moment class 5, 6 (WDM5, WDM6). The results revealed that the Threat Score (TS) coefficients for the WDM5 and Lin schemas in the desert climate are 1 and 0.97, respectively; the TS coefficient for each one of the Lin, WSM3, and WDM6 have the value of 0.60 in the semi-desert climate. The Lin scheme performs the best in all climates of the study area. The results revealed that the WRF model accurately simulates rainfall in the climatic conditions of the region. Hydrologists and planners will be able to use this meteorological model as an input to hydrological models based on the output of the WRF model, which can provide early flood warnings within the next 24 h based on these findings.

Impact of AWiFS derived land use/land cover over the intensely urbanised domain of National Capital Region (NCR) - Delhi in simulating monsoon weather

Land-Use/Land-Cover (LULC) plays a crucial role in meteorological models because they determine the crustal properties that interfere with the exchange of energy, momentum, and moisture between the land surface and the atmosphere. The current study integrates a legitimate ground-truth LULC based on the Advanced Wide Field Sensor (AWiFS) in the Weather Research and Forecasting (WRF) model framework for simulating short-term monsoon weather over the National Capital Region (NCR Delhi), the biggest urban settlement in the Monsoon Zone. AWiFS provides LULC data at 56 m spatial resolution. The newly implemented AWiFS LULC precisely distinguishes the WRF model default Moderate Resolution Imaging Spectroradiometer (MODIS) classification and urban representation. Both simulations most well capture the urban meteorological influence over the urban core. However, the AWiFS more accurately depicts NCR urban Land Use (LU), highlighted in the spatial and Probability Density Function (PDF) distributions of various meteorological variables, and captures numerous small-scale suburban settlements outside the central core zone. The impact of the omission of the Noida suburban in MODIS LU is also notable in the planetary boundary layer (PBL). Convective parameters and precipitation correlate strongly, and the AWiFS simulation considerably enhanced Convective Available Potential Energy (CAPE), Convective Inhibition (CIN) and other associated variables. Further, it indicates that a higher magnitude (>200 J kg−1 in difference) of CAPE is simulated over Faridabad, likely an urban-induced downwind effect due to the accurate representation of the Noida suburban in AWiFS. The study highlights the importance of updated LULC in enhancing model realisation, and AWiFS-based simulation showed improved performance.