Terrain Effects Research Articles

ER-MACG: An Extreme Precipitation Forecasting Model Integrating Self-Attention Based on FY4A Satellite Data

Extreme precipitation events often present significant risks to human life and property, making their accurate prediction an essential focus of current research. Recent studies have primarily concentrated on exploring the formation mechanisms of extreme precipitation. Existing prediction methods do not adequately account for the combined terrain and atmospheric effects, resulting in shortcomings in extreme precipitation forecasting accuracy. Additionally, the satellite data resolution used in prior studies fails to precisely capture nuanced details of abrupt changes in extreme precipitation. To address these shortcomings, this study introduces an innovative approach for accurately predicting extreme precipitation: the multimodal attention ConvLSTM-GAN for extreme rainfall nowcasting (ER-MACG). This model employs high-resolution Fengyun-4A(FY4A) satellite precipitation products, as well as terrain and atmospheric datasets as inputs. The ER-MACG model enhances the ConvLSTM-GAN framework by optimizing the generator structure with an attention module to improve the focus on critical areas and time steps. This model can alleviate the problem of information loss in the spatial–temporal convolutional long short-term memory network (ConvLSTM) and, compared with the standard ConvLSTM-GAN model, can better handle the detailed changes in time and space in extreme precipitation events to achieve more refined predictions. The main findings include the following: (a) The ER-MACG model demonstrated significantly greater predictive accuracy and overall performance than other existing approaches. (b) The exclusive consideration of DEM and LPW data did not significantly enhance the ability to predict extreme precipitation events in Zhejiang Province. (c) The ER-MACG model significantly improved in identifying and predicting extreme precipitation events of different intensity levels.

Turbulent Energy and Carbon Fluxes in an Andean Montane Forest—Energy Balance and Heat Storage

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.

Improving horizon computation algorithm with quasirandom sequences

The topographic horizon can be used to estimate shading for applications requiring an accurate solar resource estimate, including the effects of the local terrain. With high-resolution topography data, horizon estimation significantly contributes to the computation time needed for irradiance simulations. Approximate horizon algorithms have been proposed previously, sampling topography in a finite number of directions. This paper extends this idea by presenting a sampling approach based on the quasirandom sequences. The sampling strategy is optimized with 300,000 km2 of topography data from Europe and the USA. We demonstrate that our algorithm is several orders of magnitude faster than the precise horizon calculation and significantly improves the previous approximate algorithms. In particular, at the ground level with a topography resolution of 1 m/pixel, the proposed method achieved the same accuracy as the old approximate method four times faster. The horizon is one of the key methods in geographical information science and a part of many modeling tools in the built environment. Improvements in computation time benefit all applications that require irradiance modeling, e.g., the yield of vehicle- and building-integrated photovoltaic or temperature modeling of buildings.

Predicting the spread of contamination in water distribution networks laid on sloping terrains

Contamination in domestic and drinking water during the conveyance process is one of the biggest health risks of all time. This is a very common hazard that is expected in the areas where water, sewer, and drainage pipes are laid in trenches near each other. The extent of the contamination spread in the case of intrusion through a pipe leak for water distribution networks (WDNs) laid on sloping terrain is not known. This article deals with the simulation and hydraulic analysis of organic contaminant intrusion in WDNs with significant consideration of the slope of the laid pipes. The source of organic contamination is considered to be the nearby leaking sewer water. The effects of sloping terrain on contaminant spread in the pipe network are studied in detail by injecting contaminant concentrations at eight different critical locations in the network. The results of contamination spread after a particular time at all nodes are compiled, and by using statistical techniques, a relation between the contaminant spread and pipe slope is proposed. The presented model is validated by comparing the actual values of the contaminant in water samples obtained at the site with the calculated ones, and it shows that the values deviate within the range of ±2% only, which is considered a good match. The research proves to be beneficial for the management of water distribution through pipe networks against contaminants to maintaining water quality and public health.

Downwind Warming of Cities? Inequal Heat Distribution Attributed to Winds

Heat exposure within urban areas is strikingly uneven, posing disproportionate risks to certain communities. While nature-based solutions have gained attention, the role of wind in distributing heat remains less understood in an urban planning scale. This study assessed the interaction between wind direction, speed, and heat advection in Taipei Basin during summers from 2011 to 2020, using data from densely installed meteorological stations. A novel method was developed to capture multiple wind directions while accounting for local terrain and urban effects. Results revealed that wind-induced heat advection is complicated by local terrain and nearby cities in the conurbation, varying heat distribution. Windy conditions were mostly warmer than calm conditions, with north-westerly and westerly winds causing the strongest heat advection. Heat advection increased with wind speeds up to 5.4 m/s and decreased thereafter. Substantial intra-urban differences in heat advection were observed, reaching 4.33°C daytime and 3.34°C nighttime. Upwind areas were not necessarily cooler, while some downwind areas at mountain foot experienced greater warming. Up to 2.6SD of advected heat magnitude was found downwind at night. These findings underscore inequitable heat transfer to areas that do not generate heat and the critical need for wind-sensitive planning for both city-region and inter-urban areas.

Influence of Terrain on Windblown Sand Flow Field Characteristics around Railway Culverts

Aeolian sand hazards are often a threat to culverts, which are important channels and pieces of infrastructure of the desert railway. In addition to wind speed, wind direction, and culvert structure, terrain may also be an important reason for the formation of culvert sand hazards. However, there are few studies on the effect of terrain on the sediment accumulation characteristics of culverts. This paper established computational fluid dynamics (CFD) models of railway culverts (flat and concave culverts) based on Euler’s two-fluid theory. An analysis of the influence of terrain on the distribution law of the flow fields and sand accumulation around railway culverts was carried out. The results show that the horizontal wind speed curves changes in a “W” shape along the centre axis surface from the forecourt to the rearcourt within a range of 30 m~66.8 m. Low-speed backflow is formed at the inlet and outlet of the culvert, and the minimum wind speed reaches −3.6 m/s and −4.2 m/s, respectively, when the height from the bottom of the culvert is 1.0 m and 1.5 m, resulting in intensified sand sedimentation. In concave culverts, the lower the roadbed height, the easier it is for sand to accumulate at the culvert outlet, the rearcourt, and the track; the sand volume fraction is close to 0.63, affecting the normal operation of the trains. On the contrary, the higher the roadbed, the easier it is for sand to accumulate at the culvert inlet, hindering the passage of engineering vehicles and reducing the function of the culverts. These results reveal that terrain plays a pivotal role in the sand accumulation around culverts and that it should be one of the key considerations for the design of new railway culverts. This work can provide a theoretical basis for preventing and managing sand hazards in railway culverts.

Study on Downscaling Correction of Near-Surface Wind Speed Grid Forecasts in Complex Terrain

Accurate forecasting of wind speeds is a crucial aspect of providing fine-scale professional meteorological services (such as wind energy generation and transportation operations etc.). This article utilizes CMA-MESO model forecast data and CARAS-SUR_1 km ground truth grid data from January, April, July, and October 2022, employing the random forest algorithm to establish and evaluate a downscaling correction model for near-surface 1 km resolution wind-speed grid forecast in the complex terrain area of northwestern Hebei Province. The results indicate that after downscaling correction, the spatial distribution of grid forecast wind speeds in the entire complex terrain study area becomes more refined, with spatial resolution improving from 3 km to 1 km, reflecting fine-scale terrain effects. The accuracy of the corrected wind speed forecast significantly improves compared to the original model, with forecast errors showing stability in both time and space. The mean bias decreases from 2.25 m/s to 0.02 m/s, and the root mean square error (RMSE) decreases from 3.26 m/s to 0.52 m/s. Forecast errors caused by complex terrain, forecast lead time, and seasonal factors are significantly reduced. In terms of wind speed categories, the correction significantly improves forecasts for wind speeds below 8 m/s, with RMSE decreasing from 2.02 m/s to 0.59 m/s. For wind speeds above 8 m/s, there is also a good correction effect, with RMSE decreasing from 2.20 m/s to 1.65 m/s. Selecting the analysis of the Zhangjiakou strong wind process on 26 April 2022, it was found that the downscaled corrected forecast wind speed is very close to the observed wind speed at the station and the ground truth grid points. The correction effect is particularly significant in areas affected by strong winds, such as the Bashang Plateau and valleys, which has significant reference value.

A Comparative Study of Cloud Microphysics Schemes in Simulating a Quasi-Linear Convective Thunderstorm Case

An investigation is undertaken to explore a sudden quasi-linear precipitation and gale event that transpired in the afternoon of 30 May 2024 over Beijing. It was situated at the southwestern periphery of a double-center low-vortex system, where a moisture-rich belt efficiently channeled abundant warm, humid air northward from the south. The interplay between dynamical lifting, convergent airflow-induced uplift, and the amplifying effects of the northern mountainous terrain’s topography creates favorable conditions that support the development and persistence of quasi-linear convective precipitation, accompanied by gale-force winds at the surface. The study also analyzes the impacts of five microphysics schemes (Lin, WSM6, Goddard, Morrison, and WDM6) employed in a weather research and forecasting (WRF) numerical model, with which the simulated rainfall and radar reflectivity are compared against ground-based rain gauge network and weather radar observations, respectively. Simulations with the five microphysics schemes demonstrate commendable skills in replicating the macroscopic quasi-linear pattern of the event. Among the schemes assessed, the WSM6 scheme exhibits its superior agreement with radar observations. The Morrison scheme demonstrates superior performance in predicting cumulative rainfall. Nevertheless, five microphysics schemes exhibit limitations in predicting the rainfall amount, the rainfall duration, and the rainfall area, with a discernible lag of approximately 30 min in predicting precipitation onset, indicating a tendency to forecast peak rainfall events slightly posterior to their true occurrence. Furthermore, substantial disparities emerge in the simulation of the vertical distribution of hydrometeors, underscoring the intricacies of microphysical processes.

Vertical gravity gradient in volcano monitoring – In situ measured or theoretical? (Campi Flegrei study)

We analyse the vertical gravity gradient (VGG) properties at calderas using the Campi Flegrei (CF) site in Italy. In situ observed VGG values can depart significantly from the theoretical (normal) value of −308.6 μGal/m, particularly in areas of rugged relief. It is assumed that in sufficiently flat areas, the effect of geology, i.e., of the subsurface density heterogeneities, on VGG could prevail over the effect of terrain (topography), which can subsequently be neglected. With respect to the CF caldera, which is often considered as ‘reasonably flat area’, according to our findings the effect of topography on VGG is usually underestimated, while the effect of deeper geology is overestimated. We model the effect of the near topography on VGG at CF and subsequently verify the results of modelling by in situ observations to support our predictions. The results show that, in terms of VGG, the topographic relief plays a more significant role than the assumed geological sources even at ‘flat’ calderas such as CF. For a better understanding, in addition to CF, we analyse the effect of deeper geological sources on VGG also in the territory of Slovakia using a detailed gravimetric database of Slovakia. As a result, we question the use of in situ observed VGG values when processing and interpreting observed time-lapse gravity changes in volcanic areas accompanied by surface deformation.

Error Analysis and Accuracy Improvement in Forest Canopy Height Estimation Based on GEDI L2A Product: A Case Study in the United States

Various error factors influence the inversion of forest canopy height using GEDI full-waveform LiDAR data, and the interaction of these factors impacts the accuracy of forest canopy height estimation. From an error perspective, there is still a lack of methods to fully correct the impact of various error factors on the retrieval of forest canopy height from GEDI. From the modeling perspective, establishing clear coupling models between various environments, collection parameters, and GEDI forest canopy height errors is challenging. Understanding the comprehensive impact of various environments and collection parameters on the accuracy of GEDI data is crucial for extracting high-quality and precise forest canopy heights. First, we quantitatively assessed the accuracy of GEDI L2A data in forest canopy height inversion and conducted an error analysis. A GEDI forest canopy height error correction model has been developed, taking into account both forest density and terrain effects. This study elucidated the influence of forest density and terrain on the error in forest canopy height estimation, ultimately leading to an improvement in the accuracy of forest canopy height inversion. In light of the identified error patterns, quality control criteria for GEDI footprints are formulated, and a correction model for GEDI forest canopy height is established to achieve high-precision inversion. We selected 19 forest areas located in the United States with high-accuracy Digital Terrain Models (DTMs) and Canopy Height Models (CHMs) to analyze the error factors of GEDI forest canopy heights and assess the proposed accuracy improvement for GEDI forest canopy heights. The findings reveal a decrease in the corrected RMSE value of forest canopy height from 5.60 m to 4.19 m, indicating a 25.18% improvement in accuracy.

A Parameterization Scheme for Correcting All‐Sky Surface Longwave Downward Radiation Over Rugged Terrain

AbstractAccurate surface longwave downward radiation (SLDR) is crucial for understanding mountain climate dynamics. While existing algorithms notably improve the accuracy of clear‐sky SLDR, a terrain correction algorithm that can correct remotely sensed and model‐simulated all‐sky SLDR on a large scale remains largely unexplored. Here, we propose a parameterization scheme for estimating all‐sky SLDR in rugged terrain. We primarily improve the estimation of nearby terrain thermal contribution by considering topographic asymmetry and incorporate the effects of ice cloud thermal scattering under low water vapor conditions. We validate the reliability of our model using the Discrete Anisotropic Radiative Transfer (DART) model, demonstrating a good agreement with a bias value of −12.8 W/m2 and a RMSE value of 28.2 W/m2. Further evaluation against the Essential Thermal Infrared Remote Sensing (ELITE) SLDR product at three TIPEX‐III in situ sites, located near the bottom of deep valleys with predominantly flat surfaces, indicates significant improvement in our model, reducing the mean bias by 7.4 W/m2 and the mean RMSE by 4.1 W/m2. Post‐terrain correction, the ELITE SLDR difference map exhibits a spatial pattern of “small in the northwest and large in the southeast” in the study area, with the maximum differences reaching 67 W/m2 in the daytime and 54 W/m2 at nighttime. Comparison with existing methods reveals similar improvements due to the consideration of terrain effects. Overall, our SLDR correction model shows enormous potential for correcting remotely sensed and model‐simulated SLDR products on a large scale.

On the suitability of dispersion models of varying degree of complexity for air quality assessment and urban planning

The development of integrated urban services requires the implementation of informative tools that provide a balance between quality, time and costs for air quality assessment. Within this framework, three modeling techniques with different levels of complexity were compared during a winter inversion episode against PM10 concentrations measured in a built-up area in Prague (Czech Republic) characterized by heavy traffic. Although the Gaussian model ATEM satisfied the common statistical-performance criteria, the predictions poorly represented the spatial variability of concentrations in the study domain. The Lagrangian model GRAL provided a better simulation of the effects of terrain and vortice formation inside street canyons, but tended to overpredict the influence of these phenomena. Finally, the most sophisticated of the three models, the Large-Eddy Simulation model PALM, demonstrated the best performance based on an exhaustive analysis of the model outputs in the temporal and spatial dimensions. After model comparison, a sensitivity test of the selected models to the driving meteorology and emissions inputs was carried out. While advanced models can simulate complex urban environments, their suitability for use in urban planning is subject to further considerations, such as computational cost, user expertise, and the usefulness of the output. Thanks to increasing computation power and intensive work on the entire modeling chain, sophisticated models could become routine tools for use in regulatory applications, contributing to future integrated urban service provision.

A theoretical method to characterize the resistance effects of nonflat terrain on wind fields in a parametric wind field model for tropical cyclones

Traditionally, an empirical speed-up factor was introduced to reflect the effects of nonflat terrain on near-surface wind speeds. In this paper, the resistance effects of nonflat terrain are considered by introducing the terrain drag coefficient in the parametric wind field model for tropical cyclones (TCs) with a theoretical method. Terrain effects on wind fields are investigated in complex areas along the coastal zone in China under TC conditions. The results show that the terrain drag coefficient is the function of the slope angle and is sensitive to the spatial resolution. After including the resistance effect of nonflat terrain, the TC intensities weaken overall during landfall, with a slight enhancement near the coastal zone. The wind speeds outside the radius of the maximum wind speed decrease, while the wind speeds within the radius of the maximum wind speed increase. Both the TC eye and the radius of maximum wind speed shrink, which is more obvious when the TC center is entirely over land. As a result, the location and magnitude of the maximum wind speed are affected by the nonflat terrain. The changed structure of the wind fields demonstrates the necessity of considering the effects of nonflat terrain in simulating the wind fields under TC conditions.

Investigating the Potential of Using Mixdown Altitudes to Forecast Peak Wind Gusts

Abstract Forecast models based on the gust factor, the ratio of peak gust to sustained wind speed, have shown promise in predicting peak wind gusts in recent years. These models assume that turbulent vertical transport forced by wind flowing over upstream terrain mixes high-momentum air aloft down to the surface. A recently constructed database of hourly peak gusts, together with approximately coincident, nearby upper-air wind observations, is used to identify mixdown altitudes, the altitudes from which peak gusts descend, during different weather scenarios at 16 locations across the United States. Median mixdown altitudes generally ranged from 50 to 450 m AGL with occasional exceptions, particularly for convective gusts and at mountainous locations where terrain effects are likely to amplify gusts. A mixdown model in which surface peak gusts are predicted by obtaining forecast upper-air winds within this altitude interval was developed and tested. Our results suggest that a mixdown model methodology for forecasting peak gusts may be feasible at locations and during weather conditions where terrain-forced turbulent mixing is the principal cause of wind gusts.

An advanced TSMK-FVC approach combined with Landsat 5/8 imagery for assessing the long-term effects of terrain and climate on vegetation growth.

As an exceptional geographical entity, the vegetation of the Qinghai-Tibetan Plateau (QTP) exhibits high sensitivity to climate change. The Baima Snow Mountain National Nature Reserve (BNNR) is located in the south-eastern sector of the QTP, serving as a transition area from sub-tropical evergreen broadleaf forest to high-mountain vegetation. However, there has been limited exploration into predicting the temporal and spatial variability of vegetation cover using anti-interference methods to address outliers in long-term historical data. Additionally, the correlation between these variables and environmental factors in natural forests with complex terrain has rarely been analyzed. This study has developed an advanced approach based on TS (Theil-Sen slope estimator) MK (Mann-Kendall test)-FVC (fractional vegetation cover) to accurately evaluate and predict the time and spatial shifts in FVC within the BNNR, utilizing the GEE (Google Earth Engine). The satellite data utilized in this paper consisted of Landsat images spanning from 1986 to2020. By integrating TS and MK methodologies to monitor and assess the FVC trend, the Hurst index was employed to forecast FVC. Furthermore, the association between FVC and topographic factors was evaluated, the partial correlation between FVC and climatic influences was analyzed at the pixel level (30×30m). Here are the results of this research: (1) Overall, the FVC of the BNNR exhibits a growth trend, with the mean FVC value increasing from 59.40% in 1986 to 68.67% in 2020. (2) The results based on the TS-MK algorithm showed that the percentage of the area of the study area with an increasing and decreasing trend was 59.03% (significant increase of 28.04%) and 22.13% (significant decrease of 6.42%), respectively. The coupling of the Hurst exponent with the Theil-Sen slope estimator suggests that the majority of regions within the BNNR are projected to sustain an upward trend in FVC in the future. (3) Overlaying the outcomes of TS-MK with the terrain factors revealed that the FVC changes were notably influenced by elevation. The partial correlation analysis between climate factors and vegetation changes indicated that temperature exerts a significant influence on vegetation cover, demonstrating a high spatial correlation.

Measurement of the on-road wind environment in channelled roadways

A road test was undertaken to characterize the complex wind environment experienced by vehicles in channelled roadways. Channelled roadways consist of highways that are bordered by forests, hills, or other terrain features. A test vehicle was outfitted with three fast-response pressure probes in front of the vehicle located at 1 m, 2 m, and 3 m above the ground. Measurements were acquired on three highway routes in Canada with varying degrees of surrounding terrain, roadside forest cover, and in different wind conditions. Reference wind conditions were established using a network of federally-managed weather stations. The study identified that the effects of terrain and roadside forests can cause changes in wind direction of more than 50∘ to 90∘ relative to nearby reference weather stations. Directional channelling of winds was observed in forested and complex terrain, where changes in the wind direction mimicked the changes in highway alignment. The on-road video files were analysed using a machine-learning algorithm to quantitatively assess road-side forests and terrain and to identify fully-channelled sections of highway. Generalized channelled-flow trends were identified by considering the wind conditions in the channelled sections of all three routes. A linear relationship between the flow direction in the channel to that of the reference conditions was observed when the reference wind direction and the highway was within ±50∘. As the reference wind direction approached perpendicularity to the channelled segments, greater variations in the on-road wind direction were observed due to the unsteady flow within the channel. On-road wind speeds on each route were a maximum when the reference wind direction was approximately aligned with the highway and decreased to approximately 20% of the reference wind speed when the reference wind was perpendicular to the channel.

3D Marine Controlled-Source Electromagnetic Numerical Simulation Considering Terrain and Static Effect

The marine controlled-source electromagnetic (CSEM) method is an important geophysical method for the exploration of marine hydrocarbon resources. In marine CSEM forward modeling the uplift terrain, such as submarine hills and seamounts, the static effects caused by polymetallic nodules and hydrothermal sulfide are ignored which can lead to the deviation of marine CSEM data. To improve the accuracy of data processing and interpretation, this study realizes efficient 3D numerical simulation considering submarine uplift terrain and static effect based on the finite difference (FD) algorithm in a fictitious wave domain. First, based on the correspondence principle between the fictitious wave domain and a real diffusive domain, we derive the FD electromagnetic field iteration equations of the fictitious wave domain, and apply the fictitious emission source and the boundary condition of complex frequency shifted-perfectly matched layer (CFS-PML). We use the inverse transformation method to convert the electromagnetic response to the diffusive domain. Then, we carry out simulations on typical 1D and 3D reservoir models to verify the correctness and effectiveness of the algorithm. Furthermore, we design an uplift terrain model and a static effect model and study the influence of parameters such as top width, bottom width, height and volume of uplift terrain on the CSEM field response characteristics through the forward modeling of multiple models and discuss the influence of parameters such as electrical conductivity, length, width, thickness, depth and volume of a shallow anomaly on the marine CSEM response. Finally, we analyze the characteristics and rules of electromagnetic field propagation of uplift terrain and static effect, which provides theoretical guidance for the design of marine CSEM exploration systems.

Comparative research of the effect of the unilateral vertical slope at tunnel portals on aerodynamic performances of trains

This study set out to explore the effect of a unilateral vertical slope terrain at tunnel portals on the aerodynamic performances and operating stability of a train through a single-track tunnel. Hence, the surrounding flow field and aerodynamic performances of the train traveling through a single-track tunnel with three different configurations of tunnel portal terrain were comparatively investigated using numerical simulations. These three tunnel cases were the tunnels without vertical slope at the entrance and exit, with unilateral vertical slope at the entrance, and with unilateral vertical slope at the exit. The key results revealed that the vortex characteristics around the tail car exhibited strong asymmetry as the tail car entered into the tunnel case with a unilateral vertical slope topography at the entrance, which was obviously different from those of the other two tunnel cases. On the contrary, the vortex characteristics around the tail car under the three tunnel cases exhibited a strong similarity as the tail car was exiting the tunnel. The existence of the unilateral vertical slope at the entrance led to Fy, Mx, and Mz with the greatest magnitude value and fluctuation intensity for the tail car moving into the tunnel. Compared to the tunnel without unilateral vertical slope, the peak-to-peak value of Fy, Mx, and Mz of the tail car increased by 175%, 191.2%, and 70.42%, respectively. Furthermore, a high-intensity main frequency region was observed from the spectral analysis result of Fy, Mx, and Mz between t = 5 and 11 s as the tail car moved into the tunnel. These findings contribute to a better understanding of the phenomenon that the tail car of a train experienced pronounced transverse vibrations as the train passed through a single-track tunnel.

Driving Factors and Trade-Offs/Synergies Analysis of the Spatiotemporal Changes of Multiple Ecosystem Services in the Han River Basin, China

Uncovering the trade-offs and synergy relationship of multiple ecosystem services (ESs) is important for scientific ecosystem management and the improvement of ecological service functions. In this study, we investigated the spatiotemporal changes of four typical ES types (i.e., water yield (WY), carbon storage (CS), soil conservation (SC), and habitat quality (HQ)) from 2001 to 2020 in the Han River Basin (HRB). Meanwhile, the trade-offs and synergies between paired ESs and the socioecological drivers of these ESs were further explored. The results showed that grassland, cropland, and bare land decreased by 12,141.3 km2, 624.09 km2, and 22.1 km2 during the study period, respectively, which can be attributed to their conversion to forests in the HRB. Temporally, the WY, CS, and SC all showed a continuously increasing trend. Spatially, WY and HQ exhibited bipolar clustering characteristics, with WY exhibiting low-value clustering in the upstream and high-value clustering in the downstream, while CS showed the clustering characteristics of a scattered distribution of cold and hot spots from 2001 to 2020. The spatial patterns of aggregation locations in CS and HQ were relatively similar, with clusters of higher ES values mainly distributed in the western and central regions and clusters of lower ES values mainly located in the eastern and southeastern regions, while the aggregation of WY was spatially concentrated. Overall, the CS showed a significant positive correlation with HQ, but a significant negative correlation with WY. Spatially, WY and HQ, CS, and SC showed a substantial trade-off relationship in the northwest and southeast parts of the study area, while HQ, CS, and SC mainly exhibited a synergistic relationship in most parts of the study area. Slope and temperature had high influencing factor coefficients on multiple ESs; the mixed effect of terrain and natural factors was significantly greater than the impact of a single factor on ESs, and terrain factors played an essential role in the changes in ESs. The findings can provide technical and theoretical support for integrated scientific ecosystem management and sustainable development at the local scale.

Comprehensive assessment of five near-real-time satellite precipitation products in the Lower Yangtze River Basin and the Lixiahe region, China: Dual perspectives from time series and extreme events

Near real-time satellite precipitation products (NSPPs) have significant potential in meteorological hydrological monitoring and forecasting due to their timeliness. Previous evaluation-oriented studies have either focused on the uncertainty of time series or on the monitoring capability of extreme events. There is limited research that comprehensively considers both aspects to provide a systematic knowledge. Moreover, there is still insufficient understanding of the accuracy of hourly precipitation estimates. This study conducts a comprehensive evaluation between five NSPPs (IMERG Early, IMERG Late, GSMaP NRT, GSMaP NRT Gauge and PERSIANN CCS) from two main perspectives at hourly scale: an assessment of time series spanning from 2018 to 2022 over the Lower Yangtze River Basin and the Lixiahe region and an examination of the four extreme events over the Tai Lake Basin and the Chao Lake Basin. HP-metrics are proposed to evaluate bias in the location of extreme rainfall, rainy area, and precipitation amount over time, comprehensively analyzing performance in terms of extreme events. The results show that, for general and seasonal assessment, IMERG Late generally performed best with good statistical metrics, with the highest CSI (0.343), CC (0.445), KGE ‘(0.295) in annual results, and the best agreement in capturing convective rain diurnal curves (summer CC = 0.820). GSMaP showed a better detection capability especially in spring and summer, and also performed better in capturing frequency curves, but always showed large estimation errors. IMERG and GSMaP detected worse CC region close to the water body. And the effect of high terrain on GSMaP NRT is more obvious in winter. For the evaluation in detecting the extreme events, IMERG and GSMaP overestimated the area and intensity and had a certain ability to discriminate the location of extreme precipitation, based on the temporal variation of HP-metrics. The rapid expansion or contraction of the extent of the extreme precipitation region could degrade the detection capability of HP-π. The comprehensive understanding of NSPPs provides valuable insights for upgrading satellite retrieval algorithms and making informed selection for precipitation products in meteorological hydrological applications.