Stable Atmospheric Conditions Research Articles

Heat wave: a new characterization in terms of energy

Heat waves (HW) are prolonged periods of excessively hot weather that can cause severe socioeconomic and environmental impacts. This study aims to evaluate the differences in stored heat and turbulent flux partitioning during a heat wave event in Mexico City, using observations from an eddy covariance tower during the period from 14 June to 21 June 2023. During this period, net radiation (Rn) and sensible heat flux (H) increased significantly, particularly from noon to evening, reflecting stable atmospheric conditions. The air temperature showed a noticeable increase in the afternoon and evening, whereas absolute humidity decreased. We found that during the heat wave, the Bowen ratio (β) increased by 80% during daylight hours and 65% over a full 24-hour period compared to the pre-heat wave period. This heat release at night prolonged warm conditions, intensifying heat stress. The partitioning of net radiation for latent heat (LE), sensible heat (H), and heat storage (ΔQs) showed significant changes; during the heat wave, 51% of Rn was allocated to H and 34% to ΔQs, compared to pre-heat wave values of 49% and 27%, respectively. This study introduces a new characterization of heat waves in terms of energy, emphasizing the significant shifts in energy flux partitioning and storage. The new characterization highlights the critical role of urban heat storage and its release in exacerbating heat stress during and after heat wave events. This approach provides a comprehensive understanding of the energy dynamics during heat waves, which is essential for developing effective mitigation strategies to combat the adverse effects of extreme heat in urban environments.

Effects of the urban development on the near-surface air temperature and surface energy balance: The case study of Madrid from 1970 to 2020

The aim of the present study is to examine the impact of Madrid's urban growth over the last 50 years (1970–2020). We conduct a modelling study using WRF-ARW with the multilayer urban parameterization BEP-BEM, in which different urban parameters have been incorporated at each point within the model's inner domain according to urban expansion from 1970 to 2020. Two scenarios of important societal interest with different meteorological conditions are selected for this study: a period of intense heatwave during the summer season and a short period of strongly stable atmospheric conditions in winter, both in 2020. The results show that in areas where the urban fraction becomes greater an increase in near-surface air temperature is found for both simulated periods, especially during the night. The urbanization modifies the surface energy balance and turbulent transport in Madrid and its surroundings. It leads to a decrease in latent heat flux due to the high impermeability and reduced vegetation in urban areas. Additionally, the urban areas with a higher density of buildings have a high heat capacity, increasing heat flux storage during the day through solar radiation absorption. This stored energy is released at night, exacerbating the increase in nighttime near-surface air temperature in both periods.

Turbulent Heat Fluxes over Arctic Sea Ice: Measurements and Evaluation of Recent Parameterizations

We present direct eddy covariance measurements of the surface heat flux in sea ice over a wide range of conditions across the Arctic Ocean made during two research cruises. Photographic imagery of the surface around the ship provides a local, in situ estimate of the ice fraction. Aerodynamically rough conditions prevail for the majority of the time in the consolidated pack ice. The results are analyzed in the framework of a recently-developed parameterization scheme in which the exchange coefficients over ice are functions of a roughness Reynolds number, R*, hence account for aerodynamic roughness variability. This parameterization accurately represents the measured fluxes under all conditions, while under aerodynamically rough conditions the existing parameterizations from both the Met Office Unified Model, and ECMWF Integrated Forecast System overestimate the fluxes. The results corroborate those of a previous airborne study over the marginal ice zone, and encompass a wider range of atmospheric stability conditions.

A Single Compartment Relaxed Eddy Accumulation Method

AbstractThe relaxed eddy accumulation (REA) method is a widely‐known technique that measures turbulent fluxes of scalar quantities. The REA technique has been used to measure turbulent fluxes of various compounds, such as methane, ethene, propene, butene, isoprene, nitrous oxides, ozone, and others. The REA method requires the accumulation of scalar concentrations in two separate compartments that conditionally sample updrafts and downdraft events. It is demonstrated here that the assumptions behind the conventional or two‐compartment REA approach allow for one‐compartment sampling, therefore called a one compartment or 1‐C‐REA approach, thereby expanding its operational utility. The one‐compartment sampling method is tested across various land cover types and atmospheric stability conditions, and it is found that the one‐compartment REA can provide results comparable to those determined from conventional two‐compartment REA. This finding enables rapid expansion and practical utility of REA in studies of surface‐atmosphere exchanges, interactions, and feedbacks.

Investigation of Coastal Winds and Turbulence Characteristics Using Doppler Lidar

AbstractSea ports play a major role in the transport of goods worldwide, and knowledge of wind characteristics in these areas is vital to maintaining safety. However, coastal wind flow can be highly complex and turbulent, necessitating additional analysis. A Doppler lidar providing continuous wind profiles is deployed in the Port of Genoa, Italy, to characterize the mean wind velocity and turbulence properties within the coastal surface layer (40–250 m above ground level). Weather conditions, reanalysis data, and transient wind profiles are combined to analyze wind field characteristics on a day which experienced a thunderstorm. We also utilize a method to identify and categorize sources of turbulence through analysis of lidar derived quantities such as wind shear, turbulent kinetic energy, and vertical skewness. Seasonal variations in the wind properties are investigated by selecting data from June (summer) and December (winter). Differences are found in dominant wind direction and the associated frequency of convective mixing, with onshore winds most common in summer and offshore winds in winter. The measured lidar velocity is also compared against Monin–Obukhov similarity theory predictions, showing satisfactory agreement at low heights but struggling to reproduce observations of the stable atmospheric conditions present during winter.

MONTPEL: A multi-component Penman-Monteith energy balance model

Mechanistic modelling is gradually replacing empiricism in crop models, focusing on leaf-level physiological processes. This shift necessitates simulating crop surface temperature at infra-canopy sub-daily scales but many crop models still rely on empirical formulations for canopy temperature estimation, typically on a daily basis. We developed MONTPEL, a multi-component Penman-Monteith model that allows simulating the crop energy balance with flexible canopy representations (“BigLeaf” vs. “Layered”, “Lumped” vs. “Sunlit-Shaded”) and accounts for atmospheric stability conditions. We analyzed the model behavior, sensitivity and accuracy, using measurements from four wheat (Triticum aestivum L.) experiments conducted under varying pedoclimatic and water stress conditions. Measurements included hourly energy balance terms (total net radiation, soil heat flux, sensible and latent energy fluxes), hourly temperature of the canopy surface or of leaves at different depths inside the canopy, and sunlit and shaded leaf temperatures around solar noon at different dates. MONTPEL reproduced the measured energy balance terms with a root mean square error (RMSE) between 21 and 87 Wm-2 and a coefficient of determination (R²) exceeding 0.65. The model's accuracy in simulating canopy temperature, with RMSE ≤ 2.2 °C and R² ≥ 0.92, remained consistent regardless of measurement scale. Adjusting the aerodynamic resistance for atmospheric stability minimized simulated canopy temperature errors, notably in semi-arid conditions. Crop latent energy flux and temperature were most sensitive to the maximal stomatal conductance (gs,max) parameter. However, using a single gs,max value across the simulated experiments yielded satisfactory results, suggesting a weak sensitivity to the temporal and site-to-site variability of gs,max. Distinguishing sunlit from shaded canopy fractions systematically resulted in lower latent energy fluxes compared to “Lumped” canopy representation results. Analysis identified limitations in the multi-component approach, particularly an unrealistic uniform temperature shift across leaf layers when soil surface temperature changes.

Influence of atmospheric stability conditions on wind energy density in Ali Al-Gharbi region of Iraq

Atmospheric stability is considered as one of the most important factors affecting the increase or decrease in wind speed in the atmosphere and thus affects the wind energy density. This study aims to analyze the stability of the atmospheric conditions in southern part of Iraq, specifically in the Ali Al-Gharbi region, using one of methods to determine atmospheric stability called Monin-Obukhov length . Field data of horizontal and vertical wind speed and air temperature collected at three heights (10m, 30m, and 50m) in 2017 from tower installed in Ali Al-Gharbi region. The results show that the vertical wind speed increases with height up to 30 m and decreases at 50 m, while the horizontal wind speed increases as the height increases. The friction velocity , surface heat flux , momentum flux and shear stress were calculated and the stability conditions were determined. Results revealed that stable atmospheric condition was the most frequent with about 59% occasions occurring during the year followed by unstable (40%) and neutral (1%) conditions. The highest wind energy density was in stable conditions (0 ≤ L< 200), with percentage (58% - 57%) in spring season at both heights 10m and 50m, respectively, followed by unstable conditions (-200 < L ≤ 0), while the lowest wind energy density was in neutral conditions (-200 ≤ L ≥ 200) with percentage (1.3% - 0.8%) in autumn season.Atmospheric stability is considered as one of the most important factors affecting the increase or decrease in wind speed in the atmosphere and thus affects the wind energy density. This study aims to analyze the stability of the atmospheric conditions in southern part of Iraq, specifically in the Ali Al-Gharbi region, using one of methods to determine atmospheric stability called Monin-Obukhov length . Field data of horizontal and vertical wind speed and air temperature collected at three heights (10m, 30m, and 50m) in 2017 from tower installed in Ali Al-Gharbi region. The results show that the vertical wind speed increases with height up to 30 m and decreases at 50 m, while the horizontal wind speed increases as the height increases. The friction velocity , surface heat flux , momentum flux and shear stress were calculated and the stability conditions were determined. Results revealed that stable atmospheric condition was the most frequent with about 59% occasions occurring during the year followed by unstable (40%) and neutral (1%) conditions. The highest wind energy density was in stable conditions (0 ≤ L< 200), with percentage (58% - 57%) in spring season at both heights 10m and 50m, respectively, followed by unstable conditions (-200 < L ≤ 0), while the lowest wind energy density was in neutral conditions (-200 ≤ L ≥ 200) with percentage (1.3% - 0.8%) in autumn season.

Multiscale CFD analysis of urban air pollution dome and ventilation enhancement via an urban chimney

Air pollution episodes are critical environmental challenges in urban areas, primarily linked to the lack of ventilation during calm and stable atmospheric conditions, rather than a significant increase in emissions. The prevailing circulation pattern under these conditions is the Urban Heat Island Circulation (UHIC), which governs the characteristics of the urban pollution dome and the distribution of pollutants. This study aims to assess the UHIC's influence on spatial and temporal variations in pollutant concentrations and to investigate the efficiency of an Urban Chimney (UC) in improving air quality. Due to the interaction of micro- and meso-scale flows, a multi-scale analysis is required. For this purpose, a pressure-based CFD solver is adapted for analyzing airflow and pollutant dispersion in a multi-scale environment. A coordinate transformation method is used to account for meso-scale effects, and the resulting source terms are applied to the solver. The species transport equation is transformed to the new coordinate system, and the effects of species diffusion on enthalpy transport are included in the governing equations. The results demonstrate that UHIC reduces the average pollutant concentration and causes pollution peaks near ground level and at the city center. The interaction of micro-scale flow within the chimney with meso-scale UHIC impacts the flow field and pollutant concentration across the entire domain, decreasing the urban plume's vertical velocity by 40 percent and the mixing height at the city center by 20 percent. It also increases the vertical velocity within the UC by 23 percent. The UC can serve as a controlling tool for urban ventilation, and its capacity to remove pollutants increases sixfold when interacting with UHIC, reducing pollutant concentration citywide.

Integrating Doppler LiDAR and machine learning into land-use regression model for assessing contribution of vertical atmospheric processes to urban PM2.5 pollution

Air pollution has been recognized as a global issue, through adverse effects on environment and health. While vertical atmospheric processes substantially affect urban air pollution, traditional epidemiological research using Land-use regression (LUR) modeling usually focused on ground-level attributes without considering upper-level atmospheric conditions. This study aimed to integrate Doppler LiDAR and machine learning techniques into LUR models (LURF-LiDAR) to comprehensively evaluate urban air pollution in Hong Kong, and to assess complex interactions between vertical atmospheric processes and urban air pollution from long-term (i.e., annual) and short-term (i.e., two air pollution episodes) views in 2021. The results demonstrated significant improvements in model performance, achieving CV R2 values of 0.81 (95 % CI: 0.75–0.86) for the long-term PM2.5 prediction model and 0.90 (95 % CI: 0.87–0.91) for the short-term models. Approximately 69 % of ground-level air pollution arose from the mixing of ground- and lower-level (105 m–225 m) particles, while 21 % was associated with upper-level (825 m–945 m) atmospheric processes. The identified transboundary air pollution (TAP) layer was located at ~900 m above the ground. The identified Episode one (E1: 7 Jan–22 Jan) was induced by the accumulation of local emissions under stable atmospheric conditions, whereas Episode two (E2: 13 Dec–24 Dec) was regulated by TAP under instable and turbulent conditions. Our improved air quality prediction model is accurate and comprehensive with high interpretability for supporting urban planning and air quality policies.

The emission of CO from tropical rainforest soils

Abstract. Soil carbon monoxide (CO) fluxes represent a net balance between biological soil CO uptake and abiotic soil and (senescent) plant CO production. Studies largely from temperate and boreal forests indicate that soils serve as a net sink for CO, but uncertainty remains about the role of tropical rainforest soils to date. Here we report the first direct measurements of soil CO fluxes in a tropical rainforest and compare them with estimates of net ecosystem CO fluxes derived from accumulation of CO at night under stable atmospheric conditions. Furthermore, we used laboratory experiments to demonstrate the importance of temperature on net soil CO fluxes. Net soil surface CO fluxes ranged from −0.19 to 3.36 nmol m−2 s−1, averaging ∼1 nmol CO m−2 s−1. Fluxes varied with season and topographic location, with the highest fluxes measured in the dry season in a seasonally inundated valley. Ecosystem CO fluxes estimated from nocturnal canopy air profiles, which showed CO mixing ratios that consistently decreased with height, ranged between 0.3 and 2.0 nmol CO m−2 s−1. A canopy layer budget method, using the nocturnal increase in CO, estimated similar flux magnitudes (1.1 to 2.3 nmol CO m−2 s−1). In the wet season, a greater valley ecosystem CO production was observed in comparison to measured soil valley CO fluxes, suggesting a contribution of the valley stream to overall CO emissions. Laboratory incubations demonstrated a clear increase in CO production with temperature that was also observed in field fluxes, though high correlations between soil temperature and moisture limit our ability to interpret the field relationship. At a common temperature (25 °C), expected plateau and valley senescent-leaf CO production was small (0.012 and 0.002 nmol CO m−2 s−1) in comparison to expected soil material CO emissions (∼ 0.9 nmol CO m−2 s−1). Based on our field and laboratory observations, we expect that tropical rainforest ecosystems are a net source of CO, with thermal-degradation-induced soil emissions likely being the main contributor to ecosystem CO emissions. Extrapolating our first observation-based tropical rainforest soil emission estimate of ∼ 1 nmol m−2 s−1, global tropical rainforest soil emissions of ∼ 16.0 Tg CO yr−1 are estimated. Nevertheless, total ecosystem CO emissions might be higher, since valley streams and inundated areas might represent local CO emission hot spots. To further improve tropical forest ecosystem CO emission estimates, more in situ tropical forest soil and ecosystem CO flux measurements are essential.

Near-Surface Thermodynamic Influences on Evaporation Duct Shape

This study utilizes in situ measurements and numerical weather prediction forecasts curated during the Coupled Air–Sea Processes Electromagnetic Ducting Research (CASPER) east field campaign to assess how thermodynamic properties in the marine atmospheric surface layer influence evaporation duct shape independent of duct height. More specifically, we investigate evaporation duct shape through a duct shape parameter, a parameter known to affect the propagation of X-band radar signals and is directly related to the curvature of the duct. Relationships between this duct shape parameter and air sea temperature difference (ASTD) reveal that during unstable periods (ASTD < 0), the duct shape parameter is generally larger than in near-neutral or stable atmospheric conditions, indicating tighter curvature of the M-profile. Furthermore, for any specific duct height, a strong linear relationship between the near-surface-specific humidity gradient and the duct shape parameter is found, suggesting that it is primarily driven by near-surface humidity gradients. The results demonstrate that an a priori estimate of duct shape, for a given duct height, is possible if the near-surface humidity gradient is known.

A numerical analysis of wind farm wake characteristics in the southern part of the North Sea

The rapid expansion of wind farms in the North Sea requires a better understanding of the wind turbines’ wake effects. In this study, the classification of wake patterns under different atmospheric boundary layer stability conditions is investigated. For this purpose, the Weather Research and Forecast model is utilized to calculate wind farm wake effects over the southern North Sea for a year-long period. The atmospheric stability is characterized by the value of Monin-Obukhov length, and seven different classes are considered. The results have shown that the predominance of the stability condition depends on seasonality. In autumn and winter months very unstable conditions prevail, while in spring and summer periods near-neutral and stable events occur more frequently. The different atmospheric stability conditions have distinct effects on the averaged wind-speed deficits. Specifically, in near-neutral and stable stratification, wakes propagate further downwind of the wind turbines affecting neighboring wind farms, while in the case of unstable conditions, these effects are weaker.

Aeroelastic analysis of a very large wind turbine in various atmospheric stability conditions

With the growing trend towards larger wind turbine rotor diameters, the impact of wind shear on rotor performance and loads becomes increasingly significant. Atmospheric stability strongly influences wind shear, leading to higher wind shear under stable atmospheric conditions. In this study, the aeroelastic performance of the IEA 22 MW rotor is assessed under inflow conditions generated by different methods. Inflow conditions were generated using turbulence models specified in the IEC Standards and also by Large Eddy simulations. Standalone OpenFAST simulations were conducted with the respective inflow conditions.It was found that at rated and above-rated wind speeds, the time-averaged wind turbine design loads were higher in stable atmospheric conditions, in comparison to the IEC NTM inflow conditions, while the opposite held for below-rated wind speeds. Specifically, the time-averaged root flapwise bending moment and rotor thrust were found to be higher by up to 7% in stable atmospheres. However, maximum design and fatigue loads were considerably higher in the IEC NTM case due to elevated turbulence levels. Compared to the IEC NTM case, the damage equivalent root flapwise bending moment was found to be 30% to 70% lower in the different scenarios.

A critical insight into the most effective CFD settings to model atmospheric stability in wind energy applications

An accurate reconstruction of the Atmospheric Boundary Layer (ABL) is key for the estimation of energy production and loads in modern wind turbines since, at current rotor heights, the vertical structure of the ABL is heavily influenced by thermal stratification effects. The wind power community usually accounts for these effects by semi-empirical modifications to the neutral ABL profile obtained using linear solvers such as WAsP; this approach, however, may not be suitable for sites with complex terrain, time-dependent thermal effects, or dense canopies. In these applications, methods with higher fidelity, such as Computational Fluid Dynamics (CFD) approaches based on steady or unsteady Reynolds Averaged Navier-Stokes (RANS) equations are needed. While CFD is recognized as providing more accurate results for these realistic cases, its use is still not a common best practice. In the current study, the WindModeller CFD tool by Ansys was employed to assess the effect of various inlet boundary conditions on the predicted wind speed profiles in unstable and stable atmospheric conditions. The test case is a wind farm in North Dakota, USA, characterized by a simple terrain but strong atmospheric stability effects and temperature fluctuations. The comparison of CFD results with experimental measurements and WAsP-CFD simulations reveals a high level of agreement between CFD and experimental data in stable conditions. In the case of unstable conditions, despite the good representation of the wind field, a high sensitivity to inlet boundary conditions is highlighted.

Sensitivity of the Prediction of Wind Turbine Wakes to the Sub-Grid Scale Model

In a large-eddy simulation (LES) approach, the sub-grid scale (SGS) model accounts for the contribution of eddies and their fluxes whose length scales are smaller than the filter width. In wind turbine and farm simulations, different SGS models have been adopted, but their impact on turbine performance and wake prediction remains unknown for non-neutrally stable atmospheric boundary layers. Here, large-eddy simulations of an NREL–5MW wind turbine in stable atmospheric conditions are performed with six SGS models: standard Smagorinsky, Lagrangian-Averaged Scale-Dependent Dynamic (LASDD), Wall-Adapting Local Eddy-Viscosity, Turbulent Kinetic Energy, Stability Dependent Smagorinsky, and Anisotropic Minimum-Dissipation (AMD) models. The resolved flow field and turbine loading have shown limited sensitivity to the SGS model with some deviations from the LASDD in wind speed and turbulence intensity at the turbine elevation. This limited sensitivity is owed to the adopted high-resolution grid necessary to provide an acceptable resolution for the actuator-line method. Regarding the computational costs, the LASDD model has the highest compute overhead to the LES compared to the other five SGS models. The AMD model is simple to implement and provides three-dimensional variation of the SGS eddy-viscosity without any parameter tuning, thus it has the highest potential to be used in LES of wind turbines and farms operating in stable conditions.

Land-based wind plant wake characterization using dual-Doppler radar measurements at AWAKEN

Wind plant wakes have been shown to persist for tens of kilometers downstream in offshore environments, reducing the power output of neighboring plants, but their behavior on land remains relatively unexplored through observation. This study capitalizes on the unique and extensive field data collected for the American WAKE ExperimeNt (AWAKEN) project underway in northern Oklahoma. X-band dual-Doppler radars deployed at this site measure wind speed and direction at 25-m and 2-min resolution within a 30-km range, capturing the interactions between three neighboring wind plants. These measurements show that the wake of one wind plant extends at least 15 km downstream under easterly wind and stable atmospheric conditions. Though the wake wind speed increases within the first 10 km, it plateaus at 90% of the freestream wind speed. The spanwise velocity distribution within the wake initially shows the clear signature of the wind plant layout, which is smoothed as it propagates downstream, indicating spanwise momentum transfer is a key mechanism in wind plant wake development and recovery. These findings have important implications for wind plant siting decisions and resource assessments, and provide insights into atmospheric interactions at the wind plant scale.

Role of rotational and divergence effects induced by wind turbines wakes on near-ground air warming

Various studies, involving numerical simulations, satellite measurements, and field measurement campaigns, have demonstrated that wind turbine wakes can lead to changes in near-ground air temperature. To investigate these phenomena an Actuator Disk with Rotation (ADR) is implemented within the LES non-hydrostatic atmospheric model Meso-NH and validated using the NewMEXICO wind tunnel measurements and the VERTEX field measurement campaign. The NewMEXICO case allows the aerodynamic validation of the approach, especially the effect of the wake on wind speed components. On the VERTEX case, meteorological effects of wind turbines are studied under various atmospheric stability conditions through the application of homogeneous sensible heat fluxes at the ground level. Results show wake-related warming and cooling near the ground for stable and unstable conditions respectively, and no significant change for neutral conditions. These results show a good tendency agreement with the VERTEX campaign’s measurements. The comparison between an Actuator Disk with No Rotation (ADNR) and an ADR simulation show the dual contribution of the rotation of the wake and the growth of the stream tube on the temperature change in the wake but also on the near-ground air temperature.

Air–sea interactions in stable atmospheric conditions: lessons from the desert semi-enclosed Gulf of Eilat (Aqaba)

Abstract. Accurately quantifying air–sea heat and gas exchange is crucial for comprehending thermoregulation processes and modeling ocean dynamics; these models incorporate bulk formulae for air–sea exchange derived in unstable atmospheric conditions. Therefore, their applicability in stable atmospheric conditions, such as desert-enclosed basins in the Gulf of Eilat/Aqaba (coral refugium), Red Sea, and Persian Gulf, is unclear. We present 2-year eddy covariance results from the Gulf of Eilat, a natural laboratory for studying air–sea interactions in stable atmospheric conditions, which are directly related to ocean dynamics. The measured mean evaporation, 3.22 m yr−1, approximately double that previously estimated by bulk formulae, exceeds the heat flux provided by radiation. Notably, in arid environments, the wind speed seasonal trend drives maximum evaporation in summer, with a minimum winter rate. The higher evaporation rate appears when elevated wind, particularly in the afternoon, coincides with an increase in vapor pressure difference. The inability of the bulk formulae approach to capture the seasonal (opposite from our measurements) and annual trend of evaporation is linked to errors in quantifying the atmospheric boundary layer stability parameter. Most of the year, there is a net cooling effect of surface water (−79 W m−2), primarily through evaporation. The substantial heat deficit is compensated by the advection of heat via northbound currents from the Red Sea, which we indirectly quantify from energy balance considerations. Cold and dry synoptic-scale winds induce extreme heat loss through air–sea fluxes and are correlated with the destabilization of the water column during winter and initiation of vertical water-column mixing.

Wind Shear Model Considering Atmospheric Stability to Improve Accuracy of Wind Resource Assessment

An accurate wind shear model is an important prerequisite in extrapolating the wind resource from lower heights to the increasing hub height of wind turbines. Based on the 1-year dataset (collected in 2014) consisting of 15-minute intervals collected at heights of 2, 10, 50, 100, and 150 m on an anemometer tower in northern China, the present study focuses on the time-varying relationship between the wind shear coefficient (WSC) and atmospheric stability and proposes a wind shear model considering atmospheric stability. Through the relationship between Monin–Obukhov (M-O) length and gradient Richardson number, the M-O length is directly calculated by wind data, and the WSC is calculated by combining the Panofsky and Dutton (PD) models, which enhances the engineering practicability of the model. Then, the performance of the model is quantified and compared with two alternative methods: the use of annual average WSC and the use of stability change WSC extrapolation. The analysis demonstrates that the proposed model outperforms the other approaches in terms of normal root mean square error (NRMSE) and normal bias (NB). More specifically, this method reduces the NRMSE and NB by 24–29% and 76–95%, respectively. Meanwhile, it reaches the highest extrapolation accuracy under unstable and stable atmospheric conditions. The results are verified using the Weibull distribution.

Future projection of tropical cyclone genesis in the Western North pacific using high-resolution GCMs and genesis potential indices

The study employed high-resolution atmospheric general circulation models (AGCM) to simulate tropical cyclones (TCs) and evaluated two TC genesis potential indices in reflecting projected TC changes in the western North Pacific (WNP) under a warming scenario. Both indices accurately represented the seasonal variation of TC genesis frequency (TCGF) and its spatial distribution in historical simulations and observation data. The widely-used TC genesis potential index (χGPI) projected a significant increase in TCGF in response to a warmer ocean surface. However, this projection conflicted with the significant reduction in the model projection due to the dominant control of SST on the χGPI. Higher SST in remote ocean basins often over dominated the destabilization effect of in-situ warmer SST and caused more stable atmospheric conditions in the WNP, resulting in fewer TC occurrences. By contrast, the revised index (χMqGPI), which considers gross moisture condensation, projected a TCGF decrease that more accurately reflected the decreasing trend of TCGF in the warming simulations by AGCM, although the degree of reduction was smaller than that derived directly from TC detection scheme. The results suggest the plausibility of using χMqGPI, based on the results of multimodel coarse-resolution CMIP6 climate models, to project future changes in TCGF in the WNP.