Utilizing land surface temperature (LST) data derived from Landsat imagery for the period 2019-2023, this study investigated the spatiotemporal evolution of the urban surface thermal environment and driving effects of anthropogenic activities in the Beijing Plain. The analysis was conducted from three perspectives: seasonal variation, interannual dynamics, and driving mechanisms, employing a suite of methods including Getis-Ord Gi* hot/cold spot analysis, temperature grade transition matrix, Standard Deviational Ellipse (SDE) with gravity center migration modeling, and the Geographical Detector.. The results indicated that: (1) The seasonal mean LST followed the order of summer > spring > autumn > winter, with pronounced differences in the spatial pattern of the thermal environment across the four seasons. The average summer LST reached 38.2 °C, spanning a range of 24.7–63.3 °C, and exhibited the strongest heat island agglomeration effect. Temperature decreased radially outward from the central study area, forming a pattern of “a dominant central heat island surrounded by multiple clustered small heat islands”. The core urban districts (Dongcheng and Xicheng) recorded an average temperature roughly 4 °C higher than the eastern plain districts of Shunyi and Tongzhou. In autumn, the high-temperature effect attenuated, accompanied by reduced heat island connectivity and a contracted central heat island extent. In winter and spring, the intensity of the central heat island diminished, and high-temperature zones clustered in the southern plain, forming a “heat island basin”. The winter mean LST was merely 5.0 °C, with the southern districts of Daxing and Fangshan approximately 2.3 °C warmer on average than the northern districts of Miyun and Huairou.. (2) From 2019 to 2023, the areal extent of summer high-temperature hot spots expanded from 581.3 km2 to 811.3 km2, representing a 39.6% increase, with spatial diffusion generally proceeding from the central urban area toward the eastern and southern plain new towns. Temperature grade transitions were dominated by shifts between adjacent grades. Across the study area, regions with upgraded temperature grades covered 1472 km2, while regions with downgraded grades accounted for 1380 km2, manifesting a spatial differentiation of “stable core zone, warming new towns, and cooling ecological areas”. Specifically, the magnitude of temperature grade change in the core built-up area within the Fourth Ring Road was less than 5%. The gravity center of high-temperature zones shifted a cumulative distance of 4.11 km toward the southeast. Concurrently, the area of the Standard Deviational Ellipse increased from 2964.03 km2 to 3130.21 km2, indicating a transition of heat island development from a monocentric agglomeration mode to a multi-cluster diffusion mode. (3) Urban human activities exerted a critical driving effect on LST variations. Individual anthropogenic factors exhibited limited explanatory power for the spatial differentiation of LST, with all q-statistics below 0.2, and all factor interactions presented nonlinearly enhanced effects. The driving pattern underwent systematic transformation along with the urbanization process. In 2019, land cover was the dominant single factor (q = 0.17), whereas by 2023, the interaction between nighttime light intensity and road network density had emerged as the primary driving force (q = 0.21). The explanatory power of road network density as a standalone factor increased annually from 0.02 to 0.06. The core driving mechanism was identified as the synergistic warming effect arising from the combination of anthropogenic heat emissions and impeded heat dissipation due to urban spatial morphology. This study provides updated quantitative observational evidence for thermal environment evolution during Beijing’s urban spatial restructuring, and can serve as a scientific reference for thermal environment regulation in plain new towns and the construction of livable and resilient cities.
During the solar minimum period of 2020–2021, this study investigated ionospheric amplitude scintillations over Haikou, China (19.5°N, 109.1°E, dip lat. 14.4°), using multi-frequency observations at UHF (400 MHz), GPS L-band (1.23 GHz), and S-band (2.1 GHz). The results showed that the occurrence rates of scintillations decreased with increasing frequency, exhibiting a clear negative frequency dependence. Scintillations at all three bands primarily occurred in the equinoctial seasons, with a notable asymmetry between spring and autumn. In addition, UHF scintillations were observed during summer nighttime, indicating the presence of ionospheric disturbances in this season. Event analysis revealed that strong scintillations dominated the UHF band, moderate scintillations prevailed in the L-band, and the S-band was least affected. The observations demonstrated a strong temporal correlation between amplitude scintillations and the occurrence of strong range spread F (SSF) structures. Multi-instrument observations further confirmed that equatorial plasma bubbles (EPBs) served as the primary drivers. The distinct response across frequency bands directly mirrors the multi-scale irregularity structure within EPBs, linking the observed amplitude scintillation index (S4) values hierarchy to irregularity spectral energy distribution and Fresnel scale filtering, thereby transforming multi-frequency observations into a scale-sensitive diagnostic tool for EPB turbulence. These findings advance the understanding of low-latitude scintillation mechanisms by linking frequency-dependent signal degradation to the evolving multi-scale morphology of EPBs, and offer practical guidance for designing robust trans–ionospheric communication and navigation systems.
Heatwaves are severely increasing due to climate change, significantly impacting public health and ecosystems. In April 2023, Baripada, a town in North Odisha, recorded the highest reported near-surface air temperature globally on 14 April 2023, according to global weather observations, which were widely reported by national and international weather monitoring platforms. This study investigates the dynamics behind this heatwave using the Weather Research and Forecasting (WRF) model to simulate atmospheric conditions, focusing on the interplay between upper-level convergence, subsiding air masses, and dry north-westerly winds. Land Surface Temperature (LST) analysis from satellite data like LANDSAT, validated the extreme temperatures, aligning with the model simulations. Results revealed a combination of synoptic and local meteorological factors, including low relative humidity, anti-cyclonic circulation, and soil dryness, as key drivers of this event. By integrating the advanced modelling and observational data, this study highlights the urgent need for robust meteorological early warning systems and adaptive heat-health preparedness strategies to mitigate the impacts of extreme heat events in vulnerable regions. The findings contribute to a deeper understanding of heatwave mechanisms, with broader implications for global climate resilience.
The present study investigates the potential interplanetary (IP) drivers—Interplanetary Coronal Mass Ejections (ICMEs) and Corotating Interaction Regions (CIRs)—associated with Geomagnetic Storms (GSs) with Dst ⩽-50 nT during the ascending phase and the first six years of the solar cycle 25 (SC25). A total of 83 GSs were identified during the ascending phase of SC25 and 107 during its first six years. A statistical assessment based on examining the behavior of the IP magnetic field (IMF) and solar wind parameters is conducted to identify the dominant storm driver. The relative occurrence of each driver type was quantified using percentages. The results indicate that during the ascending phase of the SC25, CIR-driven storms account for 47% of all events, while ICME-driven account for 10% and shock-associated ICME storms for 43%. When the analysis is extended to the first six years of the SC25, the occurrence of CIRs slightly improves and becomes comparable to the fraction of ICME-related storms. However, distinct differences emerge when storm intensity is considered. CIRs primarily drive strong GSs (-100<Dst⩽-50 nT), contributing 58% of strong GSs during the ascending phase of SC25 and 61% during the six-year interval, whereas shock-associated ICMEs dominate the intense storm category (-200<Dst⩽-100 nT), accounting for 80% and 65% of intense GSs during the ascending phase and the first six years of SC25, respectively. All extreme GSs (Dst⩽-200 nT) are exclusively associated with ICMEs accompanied by shocks. A comparative analysis of the GS occurrence, intensity, and IP origins during the investigated periods of SCs 24 and 25 further reveals that SC25 exhibits both a higher frequency (107 GSs for SC25 compared to 84 GSs for SC24) and greater intensity (Mean Dst is -86±nT for SC25 compared to -79±24 nT for SC24) of geomagnetic activity when the extended time period and extreme GSs are considered.
To support the interpretation of data from the Mercury Radiometer and Thermal Infrared Spectrometer (MERTIS) onboard the ESA–JAXA BepiColombo mission, we conducted emissivity and reflectance measurements of elemental sulfur, three sulfide minerals (MgS, CaS, and FeS), and their mixtures. Our goal is to assess MERTIS’s capability to distinguish between elemental sulfur and sulfide phases in Mercury’s regolith. Samples were measured across the 7–14 μm thermal infrared range at Mercury-relevant temperatures up to 450 °C. Reflectance spectra were also acquired at room temperature before and after heating to provide complementary datasets. Results show that our Mg+S and Ca+S mixtures are distinguishable from their corresponding sulfides at MERTIS wavelengths. In contrast, FeS remains highly emissive under all conditions, complicating its identification through thermal infrared data alone. These findings provide important constraints for interpreting MERTIS observations and contribute to our understanding of sulfur-bearing materials on Mercury’s surface.
The Sentinel-3A/3B (S3A/B) satellites were launched in 2016 and 2018, respectively, as part of the Copernicus Program and their on-board radar altimeters provide key variables for the understanding of surface ocean dynamics and the monitoring of sea level, such as measurements of significant wave height, wind speed and sea surface height. The EUMETSAT service contract ”Copernicus Altimetry Service” (COPAS) has the goal to monitor the performance of S3 observations over ocean and validate the newly available improved products ensuring the long-term stability of the missions.Here, we provide an overview of the S3A and S3B Baseline Collection 005 (hereafter BC005) performance over the ocean compared to the previous processing baselines. Our analysis focuses on geophysical parameters such as topography, wind and waves. We used for this study mono-mission and multi-mission diagnostics, like cross-over analysis as well as comparison of maps and time series. Particular attention is given to the long-term analysis of the S3 mission performance.BC005 has become operational with the release on 9th March 2023. The new baseline provides improved sea level products and shows an overall increased quality of the observations. A full reprocessing campaign based on the new baseline collection has been completed during 2023, in order to ensure homogeneous S3A/B observations over the whole duration of both missions.BC005 brings several relevant evolutions and anomaly fixes to the S3 altimetry marine products such as correction of USO sign reading, range walk correction to SAR mode, exact dynamic zero-masking, new sea state bias correction and new GPD+ (GNSS-derived Path Delay Plus) tropospheric correction. The first two provide key improvements on the long-term stability of the S3 sea level record, rectifying the drift on global long-term trends of sea level anomaly that were previously reported for S3A/B.
