Search Results (214)

The long-term trend of coastal upwelling under global warming has been a research focus in recent years. Based on datasets including sea surface temperature (SST), sea surface wind, air–sea heat fluxes, ocean currents, and sea level pressure, this study explores the long-term trend and underlying mechanisms of the Oman coastal upwelling intensity in summer during 1993–2018. The results indicate a persistent decrease in SST within the Oman upwelling region during this period, suggesting an intensification trend of Oman upwelling. This trend is primarily driven by the strengthened positive wind stress curl (WSC), while the enhanced net shortwave radiation flux at the sea surface partially suppresses the SST cooling induced by the strengthened positive WSC, and the effect of horizontal oceanic heat transport is weak. Further analysis revealed that the increasing trend in the positive WSC results from the nonuniform responses of sea level pressure and the associated surface winds to global warming. There is an increasing trend in sea level pressure over the western Arabian Sea, coupled with decreasing atmospheric pressure over the Arabian Peninsula and the Somali Peninsula. This enhances the atmospheric pressure gradient between land and sea, and consequently strengthens the alongshore winds off the Oman coast. However, in the coastal region, wind changes are less pronounced, resulting in an insignificant trend in the alongshore component of surface wind. Consequently, it results in the increasing positive WSC over the Oman upwelling region, and sustains the intensification trend of Oman coastal upwelling. Full article

As the core components of geophysical dynamic system, oceans and atmospheres are dominated by the Coriolis force, which governs complex dynamic phenomena such as internal waves, gravity currents, vortices, and others involving multi-scale spatiotemporal coupling. Due to the limitations of in situ observations, large-scale rotating tanks have emerged as critical experimental platforms for simulating Earth’s rotational effects. This review summarizes recent advancements in rotating tank applications for studying oceanic flow phenomena, including mesoscale eddies, internal waves, Ekman flows, Rossby waves, gravity currents, and bottom boundary layer dynamics. Advanced measurement techniques, such as particle image velocimetry (PIV) and planar laser-induced fluorescence (PLIF), have enabled quantitative analyses of internal wave breaking-induced mixing and refined investigations of vortex merging dynamics. The findings demonstrate that large-scale rotating tanks provide a controllable experimental framework for unraveling the physical essence of geophysical fluid motions. Such laboratory experimental endeavors in a rotating tank can be applied to more extensive scientific topics, in which the rotation and stratification play important roles, offering crucial support for climate model parameterization and coupled ocean–land–atmosphere mechanisms. Full article

Accurately representing land–atmosphere interactions is essential for numerical weather prediction models, as they have a significant effect on forecasted near-surface meteorological parameters. We used the SURFEX soil model, coupled with the AROME non-hydrostatic numerical weather prediction model at HungaroMet Hungarian Meteorological Service. Land data assimilation techniques are employed to provide the most accurate initial conditions for the AROME-SURFEX system. Initially, the Optimal Interpolation (OI) method was applied to determine the initial conditions for soil temperature and moisture. This study focuses on implementing the more complex and advanced Simplified Extended Kalman Filter (SEKF) for surface data assimilation. The SEKF corrects the soil temperature and soil moisture content using screen-level observations (2-m temperature and relative humidity), offering improvements over OI. We highlight the advantages of the SEKF across different seasons, noting that it is a more physically-based approach with dynamically varying Jacobians. We demonstrate how outlier Jacobians can be filtered using linearity check to handle system nonlinearity. The tuning of appropriate data assimilation parameters, such as observational and background errors, is also crucial for achieving optimal results. We evaluate the impact of the SEKF by conducting forecast verification against in situ atmospheric observations, comparing its performance with that of OI. Our results indicate a significant improvement in winter forecasts. Additionally, a moderate improvement is observed in spring, highlighting the seasonal dependency of the efficiency of the SEKF. Full article

Land Surface Temperature (LST), as a core variable in the coupling of land–atmosphere energy transfers and ecological responses, relies heavily on the global coverage capacity of thermal infrared remote sensing (TIR-LST) for dynamic monitoring. Currently, the time reconstruction method of the TIR-LST products from China’s Fengyun polar-orbiting satellite under dynamic cloud interference remains under exploration. This study focuses on the Heihe River Basin in western China, and addresses the issue of cloud coverage in relation to the Fengyun-3C (FY-3C) satellite TIR-LST. An innovative spatiotemporal reconstruction framework based on multi-source data collaboration was developed. Using a hybrid ensemble learning framework of random forest and ridge regression, environmental parameters such as vegetation index (NDVI), land cover type (LC), digital elevation model (DEM), and terrain slope were integrated. A downscaling and multi-factor collaborative representation model for land surface temperature was constructed, thereby integrating the passive microwave LST and thermal infrared VIRR-LST from the FY-3C satellite. This produced a seamless LST dataset with 1 km resolution for the period of 2017–2019, with temporal continuity across space. The validation results show that the reconstructed data significantly improves accuracy compared to the original VIRR-LST and demonstrates notable spatiotemporal consistency with MODIS LST at the daily scale (annual R² ≥ 0.88, RMSE < 2.3 K). This method successfully reconstructed the FY-3C satellite’s 1 km level all-weather LST time series, providing reliable technical support for the use of domestic satellite data in remote sensing applications such as ecological drought monitoring and urban heat island tracking. Full article

Water use efficiency (WUE), as an important metric for ecosystem resilience, has been identified to play a significant role in the coupling of carbon and water cycles. The farming–pastoral ecotone of Northern China (FPENC), which is highly susceptible to drought due to water scarcity, has long been recognized as an ecologically fragile zone. The ecological restoration projects in China have mitigated land degradation and maintain the sustainability of dryland. However, the process of greening in drylands has the potential to impact water availability. A comprehensive analysis of the WUE in the FPENC can help to understand the carbon absorption and water consumption. Using gross primary production (GPP) and evapotranspiration (ET) data from a MODerate resolution Imaging Spectroradiometer (MODIS), alongside biophysical variables data and land cover information, the spatio-temporal variations in WUE from 2003 to 2022 were examined. Additionally, its driving force and the ecosystem resilience were also revealed. Results indicated that the annual mean of WUE fluctuated between 0.52 and 2.60 gC kgH₂O⁻¹, showing a non-significant decreasing trend across the FPENC. Notably, the annual averaged WUE underwent a significant decline before 2012 (p < 0.05), and then showed a slight increased trend (p = 0.14) during the year afterward (i.e., 2013–2022). In terms of climatic controls, temperature (Temp) and soil volumetric water content (VSWC) dominantly affected WUE from 2003 to 2012; VPD (vapor pressure deficit), VSWC, and Temp showed comprehensive controls from 2013 to 2022. The findings suggest that a wetter atmosphere and increased soil moisture contribute to the decline in WUE. In total, 59.2% of FPENC was shown to be non-resilient, as grassland occupy the majority of the area, located in Mu Us Sandy land and Horqin Sand Land. These results underscore the importance of climatic factors in the regulation WUE over FPENC and highlight the necessity for focused research on WUE responses to climate change, particularly extreme events like droughts, in the future. Full article

The 2020 wildfire season in the Western U.S. was historic in its intensity and impact on the land and atmosphere. This study aims to characterize satellite retrievals of carbon monoxide (CO), a tracer of combustion and signature of those fires, from two key satellite instruments: the Cross-track Infrared Sounder (CrIS) and the Tropospheric Monitoring Instrument (TROPOMI). We evaluate them during this event and assess their synergies. These two retrievals are matched temporally, as the host satellites are in tandem orbit and spatially by aggregating TROPOMI to the CrIS resolution. Both instruments show that the Western U.S. displayed significantly higher daily average CO columns compared to the Central and Eastern U.S. during the wildfires. TROPOMI showed up to a factor of two larger daily averages than CrIS during the most intense fire period, likely due to differences in the vertical sensitivity of the two instruments and representative of near-surface CO abundance near the fires. On the other hand, there was excellent agreement between the instruments in downwind free tropospheric plumes (scatter plot slopes of 0.96–0.99), consistent with their vertical sensitivities and indicative of mostly lofted smoke. Temporally, TROPOMI CO column peaks were delayed relative to the Fire Radiative Power (FRP), and CrIS peaks were delayed with respect to TROPOMI, particularly during the intense initial weeks of September, suggesting boundary layer buildup and ventilation. Satellite retrievals were evaluated using ground-based CO column estimates from the Network for the Detection of Atmospheric Composition Change (NDACC) and the Total Carbon Column Observing Network (TCCON), showing Normalized Mean Errors (NMEs) for CrIS and TROPOMI below 32% and 24%, respectively, when compared to all stations studied. While Normalized Mean Bias (NMB) was typically low (absolute value below 15%), there were larger negative biases at Pasadena, likely associated with sharp spatial gradients due to topography and proximity to a large city, which is consistent with previous research. In situ CO profiles from AirCore showed an elevated smoke plume for 15 September 2020, highlighted consistency between TROPOMI and CrIS CO columns for lofted plumes. This study demonstrates that both CrIS and TROPOMI provide complementary information on CO distribution. CrIS’s sensitivity in the middle and lower free troposphere, coupled with TROPOMI’s effectiveness at capturing total columns, offers a more comprehensive view of CO distribution during the wildfires than either retrieval alone. By combining data from both satellites as a ratio, more detailed information about the vertical location of the plumes can potentially be extracted. This approach can enhance air quality models, improve vertical estimation accuracy, and establish a new method for assessing lower tropospheric CO concentrations during significant wildfire events. Full article

The interplay between terrestrial water storage and vegetation dynamics in arid regions is critical for understanding ecohydrological responses to climate change and human activities. This study examines the coupling between total water storage anomaly (TWSA) and vegetation greenness changes in the Hexi Corridor, an arid region in northwestern China consisting of three inland river basins—Shule, Heihe, and Shiyang—from 2002 to 2022. Utilizing TWSA data from GRACE/GRACE-FO satellites and MODIS Enhanced Vegetation Index (EVI) data, we applied a trend analysis and partial correlation statistical techniques to assess spatiotemporal patterns and their drivers across varying aridity gradients and land cover types. The results reveal a significant decline in TWSA across the Hexi Corridor (−0.10 cm/year, p < 0.01), despite a modest increase in precipitation (1.69 mm/year, p = 0.114). The spatial analysis shows that TWSA deficits are most pronounced in the northern Shiyang Basin (−600 to −300 cm cumulative TWSA), while the southern Qilian Mountain regions exhibit accumulation (0 to 800 cm). Vegetation greening is strongest in irrigated croplands, particularly in arid and hyper-arid regions of the study area. The partial correlation analysis highlights distinct drivers: in the wetter semi-humid and semi-arid regions, precipitation plays a dominant role in driving TWSA trends. Such a rainfall dominance gives way to temperature- and human-dominated vegetation greening in the arid and hyper-arid regions. The decoupling of TWSA and precipitation highlights the importance of human irrigation activities and the warming-induced atmospheric water demand in co-driving the TWSA dynamics in arid regions. These findings suggest that while irrigation expansion cause satellite-observed greening, it exacerbates water stress through increased evapotranspiration and groundwater depletion, particularly in most water-limited arid zones. This study reveals the complex ecohydrological dynamics in drylands, emphasizing the need for a holistic view of dryland greening in the context of global warming, the escalating human demand of freshwater resources, and the efforts in achieving sustainable development. Full article

Against the backdrop of global warming, heatwaves in China have become more frequent, posing serious risks to public health and socio-economic stability. However, existing identification methods lack precision, and the driving mechanisms of heatwaves remain unclear. This study applies the Excess Heat Factor (EHF) to characterize heatwaves across China from 2013 to 2023, analyzing their spatiotemporal patterns and exploring key drivers such as atmospheric circulation and soil moisture. Key findings reveal significant regional differences: (1) Frequency and Duration—The southeastern coastal regions (e.g., the Yangtze River Delta) experience higher annual heatwave frequencies (1.75–3.5 events) but shorter durations (6.5–8.5 days). In contrast, the arid northwest has both frequent (1.5–3.5 events per year) and prolonged (8.5–14.5 days) heatwaves, while the Tibetan Plateau sees weaker and shorter events. (2) Driving Factors—Heatwaves in the Yangtze River Delta are primarily driven by an intensified subtropical high, leading to subsidence and clear-sky conditions. In Fujian, anomalous low-level winds enhance heat accumulation, while coastal areas show strong soil moisture–temperature coupling, where drier soils intensify warming. Conversely, soil moisture has a weaker influence on the Tibetan Plateau, suggesting a dominant atmospheric control. It is important to note that the EHF index used in this study does not directly account for humidity, which may limit its applicability in humid regions. Additionally, the ERA5 and ERA5-Land reanalysis data were not systematically validated against ground observations, introducing potential uncertainties. Full article

The wind field, a critical atmospheric parameter, significantly influences climate, weather forecasting, aviation safety, and wind energy applications. The precise observation of wind fields is essential for improving weather predictions, studying climate change, ensuring aviation safety, and optimizing wind energy systems. Among the various wind field detection methods, coherent wind lidar technology stands out due to its superior detection range, accuracy, and robustness. However, the high-range resolution required for applications such as aircraft takeoff and landing or wind turbine region monitoring presents unique challenges in wind detection. To address the aforementioned challenges, this study established a modular coherent Doppler wind lidar simulation system. Unlike traditional single-module simulation approaches, this system achieves multi-parameter coupling analysis of laser emission under pulse modulation, atmospheric transmission, and wind speed inversion through integrated hardware-transmission-processing collaborative modeling. Subsequently, by adjusting key parameters of the system model, an in-depth analysis of wind speed inversion within a 1.2 km detection range was conducted, investigating the dual impacts of reducing pulse duration on both range resolution and wind speed measurement accuracy. Furthermore, a Mach–Zehnder modulator module was implemented in the radar hardware section to generate odd–even pulse pairs, while a differential correlation algorithm was introduced in the data processing module to enhance range resolution. Ultimately, wind speed measurements with a 4.5 m range resolution along the laser emission direction were achieved in simulations. Comparative analysis shows that pulse modulation techniques effectively reduce wind speed measurement errors caused by short-pulse methods, offering a reliable framework for practical wind field measurements. Full article

Accurate wildfire spread modeling critically depends on the representation of wind dynamics, which vary with terrain, land cover characteristics, and height above ground. Many fire spread models are often coupled with coarse atmospheric grids that cannot explicitly resolve the vertical variation of wind near flame heights. Rothermel’s fire spread model, a widely used parameterization, relies on midflame wind speed to calculate the fire rate of spread. In coupled fire atmosphere models such as the Community Fire Behavior Model (CFBM), users are required to specify the midflame height before running a fire spread simulation. This study evaluates the use of logarithmic interpolation wind adjustment factors (WAF) for improving midflame wind speed estimates, which are critical for the Rothermel model. We compare the fixed wind height approach that is currently used in CFBM with WAF-derived winds for unsheltered and sheltered surface fire spread. For the first time in this context, these simulations are validated against satellite and ground-based observations of fire perimeters. The results show that WAF implementation improves fire perimeter predictions for both grass and canopy fires while reducing the overestimation of fire spread. Moreover, this approach solely depends on the fuel bed depth and estimation of canopy density, enhancing operational efficiency by eliminating the need for users to specify a wind height for simulations. 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

We model and describe the combined effect of a series of urban heat islands (UHIs), generated by nearby cities aligned as an archipelago, on the vertical diffusion of heat and the temperature structure in the lower atmosphere over an urban chain in northwestern Morocco. We use the Weather and Forecasting Model (WRF) coupled to an urban canopy model to run simulations during the northern summer. We show that when the land surface is characterized accurately, the WRF model can effectively resolve the scale of the urban archipelago effect and describe its detailed diurnal structure. Our results indicate that the combined effect of multiple UHIs in proximity is more impactful than the sum of their parts. Specifically, the urban archipelago’s effect alters the vertical temperature structure through upward diffusion of heat and extends its scale from local to meso-scale. This alters the wind pattern and may affect local weather conditions and air quality. These results underline the importance of considering the urban archipelago effect when studying urban climate. They also extend beyond academic research to offer valuable insights for urban planners in emphasizing the importance of urban typology and spatial proximity in city design and balancing cities’ interconnectivity with sustainable development and resilience. Full article

Accurate identification of dust emission sources is crucial for simulating dust aerosols in atmospheric chemical models. Therefore, a dynamically updated dust source function (DSF) was developed within the dust emission scheme of the Weather Research and Forecasting model coupled with chemistry (WRF-Chem) to simulate an East Asian dust storm event from 13 to 16 March 2021. Utilizing satellite-derived input of vegetation cover, snow cover, soil texture, and land use, the DSF was updated to better identify dust source areas over bare soils and sparsely vegetated regions in western China and central-western Mongolia. With the updated DSF, simulated dust emissions increase significantly over western China and Mongolia. The dust aerosol simulations demonstrate substantial improvements in near-surface PM₁₀ concentrations, a better agreement with remotely sensed dust aerosol optical depth (DOD), and a more accurate representation of the vertical distribution of dust extinction coefficients compared to observations. This study highlights the importance of integrating real-time data to accurately characterize dust emission sources, thereby improving atmospheric environment simulations. Full article

The Arctic Ocean has a uniquely complex system associated with tightly coupled ocean–ice–atmosphere–land interactions. The Arctic Ocean is considered to be highly susceptible to global climate change, with the potential for dramatic environmental impacts at both regional and global scales, and its spatial differences particularly have been exacerbated. A comprehensive understanding of Arctic Ocean environmental responses to climate change thus requires classifying the Arctic Ocean into subregions that describe spatial homogeneity of the clusters and heterogeneity between clusters based on ocean physical properties and implementing the regional-scale analysis. In this study, utilizing the long-term optimum interpolation sea surface temperature (SST) datasets for the period 1982–2023, which is one of the essential indicators of physical processes, we applied the K-means clustering algorithm to generate subregions of the Arctic Ocean, reflecting distinct physical characteristics. Using the variance ratio criterion, the optimal number of subregions for spatial clustering was 12. Employing methods such as information mapping and pairwise multi-comparison analysis, we found that the 12 subregions of the Arctic Ocean well represent spatial heterogeneity and homogeneity of physical properties, including sea ice concentration, surface ocean currents, SST, and sea surface salinity. Spatial patterns in SST changes also matched well with the boundaries of clustered subregions. The newly identified physical subregions of the Arctic Ocean will contribute to a more comprehensive understanding of the Arctic Ocean’s environmental response to accelerating climate change. Full article

Surface fluxes are vital to understanding land–atmosphere interactions, with similarity theory forming the basis for their parameterization. However, this theory has limitations, particularly due to large eddy effects, which have not been widely considered in Earth system models. A novel scheme was proposed to address this, considering large eddy effects under unstable atmospheric conditions. This study systematically evaluates the proposed scheme using the CoLM2014 model, FLUXNET2015 data, and ERA5 data. Based on the analysis of flux parameterization mechanisms, it proposes specific improvements aimed at enhancing the scheme’s performance. Our findings indicate that the proposed and classical schemes yield similar results, partly because they employ the same dimensionless wind speed gradient under near-neutral conditions. Furthermore, the results revealed that friction velocity responded more strongly to large eddies than did heat flux, as friction velocity influenced atmospheric stability and thereby mitigates the large eddy effects on heat flux. Additionally, our analysis reveals that bare soil exhibits the most pronounced changes in surface fluxes and energy partitioning, while grassland-type and forest-type sites display more complex responses. These findings indicate that different land cover types respond distinctly to the influence of large eddies. Overall, this research deepens our understanding of large eddy impacts and improves Earth system modeling by enhancing land–atmosphere interaction parameterization. Full article