Search Results (44)

The Complementary Relationship (CR) principle of evapotranspiration provides an efficient approach for estimating actual evapotranspiration (ET_a), owing to its simplified computation and effectiveness in utilizing meteorological factors. Accurate estimation of actual evapotranspiration (ET_a) is crucial for understanding surface energy and water cycles, especially in permafrost regions. This study aims to evaluate the applicability of two Complementary Relationship (CR)-based methods—Bouchet’s in 1963 and Brutsaert’s in 2015—for estimating ETa on the Qinghai–Tibetan Plateau (QTP), using observations from Eddy Covariance (EC) systems. The potential evapotranspiration (ET_p) was calculated using the Penman equation with two wind functions: the Rome wind function and the Monin–Obukhov Similarity Theory (MOST). The comparison revealed that Bouchet’s method underestimated ET_a during frozen soil periods and overestimated it during thawed periods. In contrast, Brutsaert’s method combined with the MOST yielded the lowest RMSE values (0.67–0.70 mm/day) and the highest correlation coefficients (r > 0.85), indicating superior performance. Sensitivity analysis showed that net radiation (Rn) had the strongest influence on ET_a, with a daily sensitivity coefficient of up to 1.35. This study highlights the improved accuracy and reliability of Brutsaert’s CR method in cold alpine environments, underscoring the importance of considering freeze–thaw dynamics in ET modeling. Future research should incorporate seasonal calibration of key parameters (e.g., ε) to further reduce uncertainty. Full article

Understanding optical turbulence within the atmospheric boundary layer (ABL) is essential for refining atmospheric motion analyses, enhancing numerical weather prediction models, and improving light propagation assessments. This study develops an optical turbulence model for the boundary layer over the South China Sea (SCS) by integrating multiple observational and reanalysis datasets, including ERA5 data from the European Center for Medium-Range Weather Forecasts (ECMWF), radiosonde observations, coherent Doppler wind lidar (CDWL), and ultrasonic anemometer (CSAT3) measurements. Utilizing Monin–Obukhov Similarity Theory (MOST) as the theoretical foundation, the model’s performance is evaluated by comparing its outputs with the observed diurnal cycle of near-surface optical turbulence. Error analysis indicates a root mean square error (RMSE) of less than 1 and a correlation coefficient exceeding 0.6, validating the model’s predictive capability. Moreover, this study demonstrates the feasibility of employing ERA5-derived temperature and pressure profiles as alternative inputs for optical turbulence modeling while leveraging CDWL’s high-resolution observational capacity for all-weather turbulence characterization. A comprehensive statistical analysis of the atmospheric refractive index structure constant ($C_n^2$) from November 2019 to September 2020 highlights its critical implications for optoelectronic system optimization and astronomical observatory site selection in the SCS region. Full article

The estimation of sensible heat flux (H) in drylands is important because it constitutes a significant portion of the net available surface energy. A model to estimate H half-hourly measurements for bare soils was derived by combining the surface renewal (SR) theory and the Monin–Obukhov similarity theory (MOST), involving the land surface temperature (LST), wind speed, and the air temperature in a period of half an hour, H_SR-LST. The surface roughness lengths for momentum ($z_{om}$) and for heat (z_0h) were estimated at neutral conditions. The dataset included dry climates and different measurement heights (1.5 m up to 20 m). Root mean square error ($\mathrm{R}\mathrm{M}\mathrm{S}\mathrm{E}$) over the mean actual sensible heat flux estimate (H_EC), E $={\displaystyle \frac{\mathrm{R}\mathrm{M}\mathrm{S}\mathrm{E}}{\overline{\mathrm{H}\mathrm{E}\mathrm{C}}}}100\%$, was considered excellent, good, and moderate for E values of up to 25%, 35%, and 40%, respectively. In stable conditions, H_SR-LST and H_MOST values were comparable and both were unacceptable (E > 40%). However, the RMSE using H_SR-LST ranged between 8 Wm² and 12 Wm² and performed slightly better than H_MOST. In unstable conditions, H_SR-LST was in excellent, good, and moderate agreement in 3, 6, and 5 cases, respectively; H_MOST was good in 3 cases; and the remaining 11 cases were intolerable because they required site-specific calibration. Full article

The Monin-Obukhov similarity theory (MOST) is widely used for surface layer parameterization. Discrepancies in MOST highlight the need to account for large eddy effects. A possible solution is to introduce the boundary layer depth $z_i$ as a new scaling parameter, which may enhance the applicability of the theory. A novel similarity scheme has recently been proposed to explicitly account for large eddy effects under unstable conditions. In this study, we estimated the impact of large eddies on the unstable surface layer using field measurements from a summer experiment on the Tibetan Plateau. Furthermore, we evaluated the proposed scheme and suggested simplifications for its improvements. In this study, the non-dimensional wind shear, ${\varphi }_m$, exhibited greater scatter and larger deviations from MOST than the non-dimensional temperature gradient, ${\varphi }_h$. Additionally, the normalized wind gradient ${\varphi }_m$ is found to depend on both $z/L$ and $z_i/L$, where $z$ is height above ground and $L$ is the Monin-Obukhov length. The additional dependence on $z_i/L$ suggests that it may serve as a crucial missing scaling parameter in the MOST under unstable conditions. Ultimately, we observed that the $z_i$-scaling parameter $C_m$ derived from the proposed scheme maintains a linear correlation with the stability parameter ($-z_i/L$), confirming the scheme’s effectiveness. Moreover, vertical wind gradients, friction velocity, and momentum flux predicted by this new scheme align more closely with observations than those estimated using the classical similarity function, thereby strengthening its feasibility and offers valuable insights for its simplification for Earth System modeling. Full article

In this paper, a water-based aerosol particle counter was used to measure aerosol number concentrations with high temporal resolution at a meteorological tower and on the ground, and the ultrasonic anemometer on the meteorological tower measured the data of the three-dimensional wind speed. The power spectrum of the aerosol particle number concentration fluctuation was obtained by using a Fourier transform, and the characteristics of the power spectrum were deeply analyzed. The results show that the aerosol concentration fluctuation power spectrum satisfies the Monin–Obukhov law in the low-frequency (0.02–0.25 Hz) part of the inertial subregion, which is consistent with the characteristics of atmospheric turbulent motion. Significant attenuation occurs in the high-frequency (0.3–5 Hz) range, which is mainly caused by the attenuation of the aerosol concentration by the intake pipe. Using the similarity of the power spectrum in the low-frequency part, using the “−5/3” line as a standard, the characteristic time of the measurement system is obtained by fitting the transfer function. The results show that in the flux measurement experiments in this paper, the characteristic time is usually less than 1 s. Finally, this paper uses the Fourier transform and wavelet transform to correct the high-frequency attenuation in the fluctuation of aerosol concentration and obtains the corrected aerosol flux. The results show that the effect of high-frequency attenuation on the flux is approximately 1–4% in this experiment. Full article

The unequivocal understanding of the planetary-global climate change has rendered the apportionment of sources and sinks of greenhouse gases in the terrestrial domain, an urgent priority. In the present study, the micrometeorological method of “dynamic gradient fluxes” coupled with the Monin–Obukhov similarity theory, was utilised for the determination of net ecosystem exchange of carbon dioxide (CO₂) from a kiwi plantation. This annual net exchange, in conjunction with the energy and fertiliser equivalent CO₂ used, established the CO₂ footprint of the produce. For the year 2023, the CO₂ Net Ecosystem Exchange (NEE) is −16.20 tonnes per hectare per year (CO₂ uptake by the plantation). The cultivation processes used throughout the year consumed +2.96 tonnes per hectare per year, and after deduction of this value from the NEE, the result is in a net CO₂ sink for the kiwi plantation of −13.24 tonnes per hectare per year. It is hence obvious that, under these conditions, the kiwi plantations in Greece can be net CO₂ sinks. This result is of increasing importance since the country is the fourth largest producer of kiwi globally, with production increasing in later years. Full article

High mountain rainforests are vital in the global energy and carbon cycle. Understanding the exchange of energy and carbon plays an important role in reflecting responses to climate change. In this study, an eddy covariance (EC) measurement system installed in the high Andean Mountains of southern Ecuador was used. As EC measurements are affected by heterogeneous topography and the vegetation height, the main objective was to estimate the effect of the sloped terrain and the forest on the turbulent energy and carbon fluxes considering the energy balance closure (EBC) and the heat storage. The results showed that the performance of the EBC was generally good and estimated it to be 79.5%. This could be improved when the heat storage effect was considered. Based on the variability of the residuals in the diel, modifications in the imbalances were highlighted. Particularly, during daytime, the residuals were largest (56.9 W/m² on average), with a clear overestimation. At nighttime, mean imbalances were rather weak (6.5 W/m²) and mostly positive while strongest underestimations developed in the transition period to morning hours (down to −100 W/m²). With respect to the Monin–Obukhov stability parameter ((z − d)/L) and the friction velocity (u*), it was revealed that the largest overestimations evolved in weak unstable and very stable conditions associated with large u* values. In contrast, underestimation was related to very unstable conditions. The estimated carbon fluxes were independently modelled with a non-linear regression using a light-response relationship and reached a good performance value (R² = 0.51). All fluxes were additionally examined in the annual course to estimate whether both the energy and carbon fluxes resembled the microclimatological conditions of the study site. This unique study demonstrated that EC measurements provide valuable insights into land-surface–atmosphere interactions and contribute to our understanding of energy and carbon exchanges. Moreover, the flux data provide an important basis to validate coupled atmosphere ecosystem models. Full article

This study conducts a comprehensive evaluation of four scenario experiments using the CMA_WSP, WRF, and WRF_FITCH models to enhance forecasts of hub-height wind speeds at multiple wind farms in Northern China, particularly under significant wind speed fluctuations during high wind conditions. The experiments apply various wind speed calculation methods, including the Monin–Obukhov similarity theory (ST) and wind farm parameterization (WFP), within a 9 km resolution framework. Data from four geographically distinct stations were analyzed to assess their forecast accuracy over a 72 h period, focusing on the transitional wind events characterized by substantial fluctuations. The CMA_WSP model with the ST method (CMOST) achieved the highest scores across the evaluation metrics. Meanwhile, the WRF_FITCH model with the WFP method (FETA) demonstrated superior performance to the other WRF models, achieving the lowest RMSE and a greater stability. Nevertheless, all models encountered difficulties in predicting the exact timing of extreme wind events. This study also explores the effects of these methods on the wind power density (WPD) distribution, emphasizing the boundary layer’s influence at the hub-heighthub-height of 85 m. This influence leads to significant variations in the central and coastal regions. In contrast to other methods that account for the comprehensive effects of the entire boundary layer, the ST method primarily relies on the near-surface 10 m wind speed to calculate the hub-height wind speed. These findings provide important insights for enhancing wind speed and WPD forecasts under transitional weather conditions. Full article

The carbon source/sink nature and the water balance of a drip-irrigated and mulched watermelon cultivated under a semi-arid climate were investigated. Biodegradable films, plants and some fruits were left on the soil as green manure. The study spanned from watermelon planting to the subsequent crop (June–November 2023). The eddy covariance technique was employed to monitor water vapor (H₂O) and carbon dioxide (CO₂) fluxes, which were partitioned into transpiration, evaporation, photosynthesis and respiration, respectively, using the flux variance similarity method.This method utilizesthe Monin–Obukhov similarity theory to separate stomatal (photosynthesis and transpiration) from non-stomatal (respiration and evaporation) processes. The results indicate that mulching films contribute to carbon sequestration in the soil (+19.3 g C m⁻²). However, the mulched watermelon crop presented in this study functions as a net carbon source, with a net biome exchange, representing the net rate of C accumulation in or loss from ecosystems, equal to +230 g C m⁻². This is primarily due to the substantial amount of carbon exported through marketable fruits. Fixed water scheduling led to water waste through deep percolation (approximately 1/6 of the water supplied), which also contributed to the loss of organic carbon via leaching (−4.3 g C m⁻²). These findings recommend further research to enhance the sustainability of this crop in terms of both water and carbon balances. Full article

This study proposes a microscale flow model to estimate mean wind speed, fluctuating wind speed and wind direction over complex terrain considering the effects of topography, atmospheric stability, and turbine wakes. Firstly, the effect of topography is considered using Computational Fluid Dynamics (CFD). Next, a mesoscale model is presented to account for the effect of atmospheric stability. The effect of turbine wakes on the mean and fluctuating wind speeds are then represented by an advanced wake model. The model is validated using the measurement data of a wind farm located in the North of Japan. The measured wind data by Lidar at a reference height are horizontally extrapolated to a nearby met mast hub height and validated by a cup anemometer. Moreover, a novel averaging method is proposed to calculate a directional equivalent Monin–Obukhov length scale to account for the effect of atmospheric stability. Finally, the measured wind data at the reference height are vertically extrapolated and validated at the lidar location. The predicted mean and fluctuating wind speeds show good agreement with the measurements. Full article

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. Full article

This study assesses the performance of the Weather Research and Forecasting (WRF) model using a high-resolution spatial grid (1 km) with various combinations of physical parameterization packages to simulate a severe event in August 2021 in the southeastern Brazilian coast. After determining the optimal set of physical parameterizations for representing wind patterns during this event, a year-long evaluation was conducted, covering forecast horizons of 24, 48, and 72 h. The simulation results were compared with observational wind data from four weather stations. The findings highlight variations in the efficacy of different physical parameterization sets, with certain sets encountering challenges in accurately depicting the peak of the severe event. The most favorable results were achieved using a combination of Tiedtke (cumulus), Thompson (microphysics), TKE (boundary layer), Monin-Obukhov (surface layer), Unified-NOAH (land surface), and RRTMG (shortwave and longwave radiation). Over the one-year forecasting period, the WRF model effectively represented the overall wind pattern, including forecasts up to three days in advance (72-h forecast horizon). Generally, the statistical metrics indicate robust model performance, even for the 72-h forecast horizon, with correlation coefficients consistently exceeding 0.60 at all analyzed points. While the model proficiently captured wind distribution, it tended to overestimate northeast wind speed and gust intensities. Notably, forecast accuracy decreased as stations approached the ocean, exemplified by the ATPM station. Full article

The sea surface roughness parameterization and the universal stability function are key components of the evaporation duct prediction model based on the Monin–Obukhov similarity theory. They determine the model’s performance, which in turn affects the efficiency and accuracy of electromagnetic applications at sea. In this study, we collected layered meteorological and hydrological observation data and preprocessed them to obtain near-surface reference modified refractivity profiles. We then optimized the sea surface roughness parameterization and the universal stability function using particle swarm optimization and simulated annealing algorithms. The results show that the particle swarm optimization algorithm outperforms the simulated annealing algorithm. Compared to the original model, the particle swarm optimization algorithm improved the prediction accuracy of the model by 5.09% under stable conditions and by 9.97% under unstable conditions, demonstrating the feasibility of the proposed method for optimizing the evaporation duct prediction model. Subsequently, we compared the electromagnetic wave propagation path losses under two different evaporation duct heights and modified refractivity profile states, confirming that the modified refractivity profile is more suitable as the accuracy criterion for the evaporation duct prediction model. Full article

Evaporation ducts are abnormal states of the atmosphere in the air–sea boundary layer that directly affect the propagation trajectory of electromagnetic (EM) waves. Therefore, an accurate diagnosis of the evaporation duct height (EDH) is important for studying the propagation trajectory of EM waves in evaporation ducts. Most evaporation duct models (EDMs) based on the Monin–Obukhov similarity theory are empirical methods. Different EDMs have different levels of environmental adaptability. Evaporation duct diagnosis methods based on machine learning methods only consider the mathematical relationship between data and do not explore the physical mechanism of evaporation ducts. To solve the above problems, this study observed the meteorological and hydrological parameters of the five layers of the low-altitude atmosphere in the East China Sea on board the research vessel Xiangyanghong 18 in April 2021 and obtained the atmospheric refractivity profile. An evaporation duct multimodel fusion diagnosis method (MMF) based on a library for support vector machines (LIBSVM) is proposed. First, based on the observed meteorological and hydrological data, the differences between the EDH diagnosis results of different EDMs and MMF were analyzed. When ASTD ≥ 0, the average errors of the diagnostic results of BYC, NPS, NWA, NRL, LKB, and MMF are 2.57 m, 2.92 m, 2.67 m, 3.27 m, 2.57 m, and 0.24 m, respectively. When ASTD < 0, the average errors are 2.95 m, 2.94 m, 2.98 m, 2.99 m, 2.97 m, and 0.41 m, respectively. Then, the EM wave path loss accuracy analysis was performed on the EDH diagnosis results of the NPS model and the MMF. When ASTD ≥ 0, the average path loss errors of the NPS model and MMF are 5.44 dB and 2.74 dB, respectively. When ASTD < 0, the average errors are 5.21 dB and 3.46 dB, respectively. The results show that the MMF is suitable for EDH diagnosis, and the diagnosis accuracy is higher than other models. Full article

The mean velocity distributions of unstably and stably stratified atmospheric surface layers (ASLs) are investigated here using the symmetry approach. Symmetry groups for the mean momentum and the Reynolds stress equations of ASL are searched under random dilation transformations, which, with different leading order balances in different flow regions, lead to a set of specific scalings for the characteristic length ${\ell }_{13}$ (defined by Reynolds shear stress and mean shear). In particular, symmetry analysis shows that in the shear-dominated region, ${\ell }_{13}$ scales linearly with the surface height z, which corresponds to the classical log law of mean velocity. In the buoyancy-dominated region, ${\ell }_{13}/L\sim {\left(z,/,L\right)}^{4/3}$ for unstably stratified ASL and ${\ell }_{13}/L\sim const$ for stably stratified ASL, where L is the Obukhov length. The specific formula of the celebrated Monin–Obukhov similarity function is obtained, and hence an algebraic model of mean velocity profiles in ASL is derived, showing good agreement with the datum from the QingTu Lake observation array (QLOA) in China. Full article