Optical Depth Research Articles

Evolution of the Climate Forcing During the Two Years After the Hunga Tonga‐Hunga Ha'apai Eruption

AbstractWe calculate the climate forcing for the 2 ys after the 15 January 2022, Hunga Tonga‐Hunga Ha'apai (Hunga) eruption. We use satellite observations of stratospheric aerosols, trace gases and temperatures to compute the tropopause radiative flux changes relative to climatology. Overall, the net downward radiative flux decreased compared to climatology. The Hunga stratospheric water vapor anomaly initially increases the downward infrared radiative flux, but this forcing diminishes as the anomaly disperses. The Hunga aerosols cause a solar flux reduction that dominates the net flux change over most of the 2 yrs period. Hunga induced temperature changes produce a decrease in downward long‐wave flux. Hunga induced ozone reduction increases the short‐wave downward flux creating small sub‐tropical increase in total flux from mid‐2022 to 2023. By the end of 2023, most of the Hunga induced radiative forcing changes have disappeared. There is some disagreement in the satellite measured stratospheric aerosol optical depth (SAOD) observations which we view as a measure of the uncertainty; however, the SAOD uncertainty does not alter our conclusion that, overall, aerosols dominate the radiative flux changes.

The Fe Kα Compton shoulder in accreting supermassive black holes

ABSTRACT Reprocessed X-ray radiation from active galactic nuclei (AGN) carries important information about the properties of the circumnuclear material around the black hole. The X-ray photons travel from the very centre of the system and interact with that material often producing strong emission lines. The $\rm {Fe\, K\alpha }$ Compton shoulder (CS) is formed by fluorescent $\rm {Fe\, K\alpha }$ photons that perform Compton scatterings with the intercepting material and lose energy to form the distinct shoulder shape. In this work, we use the ray-tracing code RefleX to explore how the physical properties of the medium, as well as its geometry, affect the shape of the CS. We start by running simulations using a simple toroidal reflector, to test the effect of the metal composition, metallicity, column density, dust presence and velocity on the $\rm {Fe\, K\alpha }$ line, and its CS. We confirm that the shape of the CS is sensitive to the optical depth of the intercepting medium, which can be regulated by either changing the metal composition or the line-of-sight column density of the circumnuclear material. Next, we create a series of models, which feature different geometrical configurations of dust and gas, and explore how the CS is affected by such configurations finding that components that can regulate the line-of-sight column density affect the $\rm {Fe\, K\alpha }$ and its CS. Finally, we test whether observatories such as the recently launched XRISM and future Athena will make the CS a useful spectral feature of nearby AGN, by applying specific models on simulated spectra of the Circinus galaxy. The CS has the potential to be used to help constrain properties of the circumnuclear material yet with some limitations.

Observation-inferred resilience loss of the Amazon rainforest possibly due to internal climate variability

Abstract. Recent observation-based studies suggest that the Amazon rainforest has lost substantial resilience since 1990, indicating that the forest might undergo a critical transition in the near future due to global warming and deforestation. The idea is to use trends in a lag-1 auto-correlation of leaf density as an early-warning signal of an imminent critical threshold for rainforest dieback. Here we test whether the observed change in auto-correlations could arise from internal variability using historical and control simulations of nine sixth-generation Earth system model ensembles (Phase 6 of the Coupled Model Intercomparison Project, CMIP6). We quantify trends in the leaf area index auto-correlation from both models and satellite-observed vegetation optical depth from 1990 to 2017. Four models reproduce the observed trend with at least one historical realization whereby the observations lie at the upper limit of model variability. Three out of these four models exhibit similar behavior in control runs, suggesting that historical forcing is not necessary for simulating the observed trends. Furthermore, we do not observe a critical transition in any future runs under the strongest greenhouse gas emission scenario (SSP5-8.5) until 2100 in the four models that best reproduce the past observed trends. Hence, the currently observed trends could be caused simply by internal variability and, unless the data records are extended, have limited applicability as an early-warning signal. Our results suggest that the current rapid decline in the Amazon rainforest coverage is not foremost caused by global warming.

First atmospheric aerosol-monitoring results from the Geostationary Environment Monitoring Spectrometer (GEMS) over Asia

Abstract. Aerosol optical properties have been provided by the Geostationary Environment Monitoring Spectrometer (GEMS), the world's first geostationary-Earth-orbit (GEO) satellite instrument designed for air quality monitoring. This study describes improvements made to the GEMS aerosol retrieval (AERAOD) algorithm, including spectral binning, surface reflectance estimation, cloud masking, and post-processing, along with validation results. These enhancements aim to provide more accurate and reliable aerosol-monitoring results for Asia. The adoption of spectral binning in the lookup table (LUT) approach reduces random errors and enhances the stability of satellite measurements. In addition, we introduced a new high-resolution database for surface reflectance estimation based on the minimum-reflectance method, which was adapted to the GEMS pixel resolution. Monthly background aerosol optical depth (BAOD) values were used to estimate hourly GEMS surface reflectance consistently. Advanced cloud-removal techniques have been implemented to significantly improve the effectiveness of cloud detection and enhance aerosol retrieval quality. An innovative post-processing correction method based on machine learning has been introduced to address artificial diurnal biases in aerosol optical depth (AOD) observations. In this study, we investigated selected aerosol events, highlighting the capability of GEMS in monitoring and providing insights into hourly aerosol optical properties during various atmospheric events. The performance of the GEMS AERAOD products was validated against the Aerosol Robotic Network (AERONET) and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) data for the period from November 2021 to October 2022. GEMS AOD at 443 nm demonstrated a strong correlation with AERONET AOD at 443 nm (R = 0.792). However, it exhibited biased patterns, including the underestimation of high AOD values and overestimation of low-AOD conditions. Different aerosol types (highly absorbing fine aerosols, dust aerosols, and non-absorbing aerosols) exhibited distinct validation results. The retrievals of GEMS single-scattering albedo (SSA) at 443 nm agreed well with the AERONET SSA at 440 nm within reasonable error ranges, with variations observed among aerosol types. For GEMS AOD at 443 nm exceeding 0.4 (1.0), 42.76 % (56.61 %) and 67.25 % (85.70 %) of GEMS SSA data points fell within the ±0.03 and ±0.05 error bounds, respectively. Model-enforced post-processing correction improved GEMS AOD and SSA performance, thereby reducing the diurnal variation in the biases. The validation of the retrievals of GEMS aerosol layer height (ALH) against the CALIOP data demonstrates good agreement, with a mean bias of −0.225 km and 55.29 % (71.70 %) of data points falling within ±1 km (1.5 km).

Climatic characteristics and meteorology-sensitivity of surface solar radiation in reanalysis products compared to observations and satellite data over China

Due to the significant role of the surface solar radiation (SSR) in climate, hydrological, and biogeochemical cycles, this study evaluates the climatology, annual cycle, and interannual variability and meteorological sensitivity (total cloud cover (TCC), aerosol optical depth (AOD), and precipitable water (PW)) of six reanalysis SSR datasets (GLDAS, ERA5, NCEP1, NCEP2, JRA55, and MERRA2) using a satellite dataset (CERES SYN), and 130 radiation stations in China during 2001–2020.The results show that the climatology (R = 0.88–0.93) and annual cycle (R = 0.92–0.98) of the SSR datasets exhibit better spatial characteristics in these products compared to interannual variability (EOF1: R = 0.03–0.88; EOF2: R = 0.27–0.83). The GLDAS has relatively small estimation SSR error in the climatology but is limited to reproduce interannual variability (EOF1: R = 0.08). As the concentration of meteorological elements increases, the sensitivity of most SSRs errors to TCC increases, while the trend of sensitivity to AOD and PW decreases due to the mitigating effect of the corresponding tendency of TCC error reduction. The importance of PW for estimating SSRs increased significantly in high altitude, ranging from 29.5 to 53%. Overall, ERA5 is the most consistent in quality of the three time-scales and high-meteorological variability.

Sensitivity analysis of a Martian atmospheric column model with data from the Mars Science Laboratory

Abstract. An extensive sensitivity analysis was performed for a horizontally homogeneous and hydrostatic 1-D column model at the Mars Science Laboratory (MSL) location. Model experiments were compared with observations from the Curiosity Rover Environmental Monitoring Station humidity (REMS-H) device and ChemCam. Based on our earlier column model investigations, model surface temperature and pressure, dust optical depth (τ), and column precipitable water content (PWC) were the parameters that we investigated with our sensitivity analysis. Our analysis suggests that the most sensitive parameters for the column model temperature profile are τ and surface temperature. The initial value of PWC does not affect the temperature profile of the model, but it is the most important parameter for the humidity profile. The fixed value of τ also seems to have some effect on the humidity profile of the model. Based on our analysis, variations in surface pressure initialization are negligible for the model's temperature and almost negligible for the model's humidity predictions. The model simulations are generally in good agreement with the observations. Our additional model experiments with a different shape of the model's initial humidity profile yielded better results compared to the well-mixed assumption in the predicted water vapor volume mixing ratios at 1.6 m.

Climatology, trends, and future projections of aerosol optical depth over the Middle East and North Africa region in CMIP6 models

This study assesses the aerosol optical depth (AOD) from historical simulations (2003–2014) and future climate scenarios (2015–2100) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) over the Middle East and North Africa (MENA) region. Multi-model mean (MME) AOD statistics are generated as the average of those from the five best-performing CMIP6 models, which reproduce observational climate statistics. These models were selected based on the validation of various climate metrics, including strong pattern correlations with observations (>0.8). The resulting MME reproduces the observed AOD seasonal cycle well. The observed positive trends (summer and annual) over the Arabian Peninsula (AP) and negative trends (winter) over North Africa are well captured by MME, as regional meteorological drivers associated with observed AOD trends, with few discrepancies. Crucially, the MME fails to capture the AOD trends over North West Africa (NWA). For MENA and NWA regions, two high-emission scenarios, SSP370 and SSP585, project a continuous rise in the annual mean AOD until the end of the century. In contrast, the low-emission scenarios, SSP126 and SSP245, project a decreasing AOD trend. Interestingly, the projected future AOD area-averaged over the AP region varies significantly across all four scenarios in time. Notably, a substantial decrease of about 8–10% in the AOD is projected by the SSP126, SSP245, and SSP585 scenarios at the end of the century (2080–2100) relative to the current period. This projected decrease in annual-mean AOD, including the frequency of extreme AOD years under SSP585, is potentially associated with a concurrent increase in annual-mean rainfall over the AP.

Evaluation and analysis of long-term MODIS MAIAC aerosol products in China

NASA has released the latest Moderate Resolution Imaging Spectroradiometer (MODIS) Multi-Angle Implementation of Atmospheric Correction (MAIAC) Collection 6 (C6) and Collection 6.1 (C6.1) aerosol optical depth (AOD) products with 1 km spatial resolution. This study validated and compared C6 and C6.1 MAIAC AOD products with AERONET observations in terms of accuracy and stability, and analyzed the spatiotemporal characteristics of AOD at different scales in China. The results show that the overall accuracy of MAIAC products is good, with correlation coefficient (R) > 0.9, mean bias (BIAS) < 0.015, and the fraction within the expected error (EE) > 68 %. However, after the algorithm update, the accuracy of Terra MAIAC aerosol products C6.1 has significantly decreased. The accuracy of the products varies with the region. The accuracy of C6.1 in North China, Central East China, and West China, is comparable to or even exceeds that of C6, but performs poorly in South China. In addition, the stability of the updated C6.1 MAIAC aerosol products has not seen significantly improvement. The metrics of no product can all meet the stability goals of the Global Climate Observing System (GCOS, 0.02 per decade) in China. C6.1 improves the retrieval frequency in many regions and temporarily solves the problem of AOD discontinuity at the boundaries of different aerosol models in C6, but there are some fixed climatological AOD blocks (AOD = 0.014) in the eastern Tibetan Plateau region. Both C6 and C6.1 can capture similar annual variation characteristics of AOD to those observed at the AERONET sites. The study provides possible references for improving the MAIAC algorithm and building long-term stable aerosol records.

Study of dust events based on multi-source data in the North Slope of the Tianshan Mountains

To reveal the spatial-temporal characteristics of atmospheric pollution during dust events on the North Slope of the Tianshan Mountains (NSTM), this study conducted a joint detection experiment from April to June from 2019 to 2021 at Shihezi, using satellite remote sensing, a microwave radiometer, meteorological sensors, and environmental monitors. Using long-term detection data from the aforementioned equipment, this study analyzed the characteristics of meteorological elements, Aerosol Optical Depth (AOD), PM, and gaseous pollutants. The main findings are as follows: The dust particles from the two severe pollution dust events on April 9, 2020, and May 1, 2021, on the NSTM originated from the Gurbantünggüt Desert and were transported along the northwest direction, leading to a significant increase in AOD (averaging 1.36 g/m2) and dust column mass concentration (averaging 1.58 g/m2). During the two dust storms, the PM10 concentration peaks reached 2536.5 μg/m³ and 1804.5 μg/m³, respectively. The average relative humidity (RH) was less than 30%, the average wind speed was more than 6 m/s, and the average visibility (V) was less than 1000 m. Moreover, during the dust events from April to June, the temperature and relative humidity were higher in June, but the wind speed was lower. The vertical thermodynamic interactions of the dust storms were stronger than those of the blowing and floating dust storms. Finally, the relationship between PM10 and V was fitted using the following equation: V=11326.8166e−0.0015PM10.This study provides scientific support for the prediction of dust storms on the NSTM.

Photoacoustic Image Analysis of Dental Tissue Using Two Wavelengths: A Comparative Study

This work compares photoacoustic images of a tooth by analyzing the signals generated with wavelengths 532 and 355 nm. This comparison addresses the differences in the optical properties of dental tissue for these wavelengths that affect the resulting photoacoustic images. A pulsed Nd:YAG laser was used to illuminate a complete extracted tooth sample, and 2D photoacoustic images (PAIs) were reconstructed using the single-sensor scanning synthetic aperture focusing technique (SSC-SAFT), which is a suitable method for our experimental system with forward detection mode. Signal comparison was conducted using sinogram, signal-to-noise ratio (SNR), root mean square (RMS), arrival time, maximum amplitude, and fast Fourier transform (FFT). PAI comparison utilized intensity profile, edge correlation, and image composition tools. The signal analysis revealed that at 532 nm, the signals exhibited longer decay time and a wider distribution of vibration frequencies due to higher laser pulse energy and greater optical penetration depth. Conversely, at 355 nm, the signals had shorter decay times and a lower frequency distribution, which was attributed to lower energy but improved optical absorption, resulting in reconstructed images with better sharpness and contour definition. This study contributes to the advancement of photoacoustic imaging technology in dentistry by providing insights that could optimize signal generation and image reconstruction for dental tissue.

Long-Term Evaluation of Aerosol Optical Properties in the Levantine Region: A Comparative Analysis of AERONET and Aqua/MODIS

The focus on aerosol analysis in the Levantine Region is driven by climate-change impacts, the region’s increasing urban development and industrial activities, and its geographical proximity to major dust-source areas. This study conducts a comparative analysis of aerosol optical depth data from Aqua/MODIS and AERONET during different periods between 2003 and 2023 at four stations: IMS-METU-ERDEMLI (Mersin/Türkiye) (2004–2019), CUT-TEPAK (Limassol/Cyprus) (2010–2023), Cairo_EMA_2 (Cairo/Egypt) (2010–2023), and SEDE_BOKER (Sede Boker/Israel) (2003–2023). The objective is to evaluate the variability and reliability of AOD measurements between satellite and ground-based observations and to determine how well they represent regional climatology. The highest percentage of measurements within the expected error envelope was observed at the IMS-METU-ERDEMLI station, indicating the best agreement between MODIS and AERONET data at this location. The Seasonal-Trend Decomposition using Loess (STL) method revealed consistent spring and summer peaks influenced by dust transport from the Sahara and the Middle East, with lower values in winter. The study also considers the influence of cloud fraction on MODIS measurements and includes aerosol classification. A statistically significant slight positive trend in AOD values was identified at the IMS-METU-ERDEMLI station. Conversely, no significant trends were detected at the other stations. The results of this study agree with those of previous research on the impact of long-range dust transport on regional aerosol loadings, emphasizing the importance of integrating satellite and ground-based observations.

TensorFlow Hydrodynamics Analysis for Ly-[formula omitted] Simulations

We introduce the Python program THALAS (TensorFlow Hydrodynamics Analysis for Lyman-Alpha Simulations), which maps baryon fields (baryon density, temperature, and velocity) to Lyα optical depth fields in both real space and redshift space. Unlike previous Lyα codes, THALAS is fully differentiable, enabling a wide variety of potential applications for general analysis of hydrodynamical simulations and cosmological inference. To demonstrate THALAS’s capabilities, we apply it to the Lyα forest inversion problem: given a Lyα optical depth field, we reconstruct the corresponding real-space dark matter density field. Such applications are relevant to both cosmological and three-dimensional tomographic analyses of Lyman Alpha forest data.

High-Resolution Characterization of Aerosol Optical Depth and Its Correlation with Meteorological Factors in Afghanistan

High-Resolution Characterization of Aerosol Optical Depth and Its Correlation with Meteorological Factors in Afghanistan

Aerosol optical depth data fusion with Geostationary Korea Multi-Purpose Satellite (GEO-KOMPSAT-2) instruments GEMS, AMI, and GOCI-II: statistical and deep neural network methods

Aerosol optical depth data fusion with Geostationary Korea Multi-Purpose Satellite (GEO-KOMPSAT-2) instruments GEMS, AMI, and GOCI-II: statistical and deep neural network methods

Precipitation and cloud Parameters's characteristics of stratus in summer in Ningxia, eastern of northwest China

Stratus is the main artificial seeding target for weather modification in Ningxia. Meteorological satellites can detect macro and microcosmic physical parameters of large-scale stratus. Researching precipitation and cloud parameter characteristics of stratus can provide scientific and technological support for understanding the development and evolution of stratus to identify seeding conditions and effects. Eight typical stratus precipitation events of the summers of 2016–2021 of Ningxia were selected, using the nine point average method, that matched characteristic cloud parameters retrieved by FY-2G satellite with precipitation classification data of 25 national meteorological observation stations in Ningxia. These stratus precipitation characteristics were correlated with cloud parameters. The results indicate that precipitation decreased rapidly from the southeast to the northwest of Ningxia. In the synoptic background of precipitation, the cloud top height, super-cooled layer thickness, cloud optical thickness, cloud particle effective radius, and cloud liquid water content were all larger than those in the synoptic background of no precipitation. The spatial distribution feature manifests as gradually increased from southeast to northwest. The cloud top temperature and cloud blackbody temperature were smaller than those in the synoptic background of no precipitation. The cloud top temperature was near the cloud “seeding temperature window”, and the depth of the super-cooled layer was thick. This was in line with the “Seeder-Feeder” structure characteristic of cold stratus.

Urban Air Pollution Exposure Impact on COVID-19 Transmission in a Few Metropolitan Regions

Based on outdoor air pollution and meteorological daily time series observational and in-situ monitoring data, this study investigated the impacts of environmental factors under different urban climates on COVID-19 transmission in four hotspot European metropolises (Berlin, London, Madrid, and Paris) from March 2020 to March 2022. Through applied statistical methods and cross-correlation tests involving multiple datasets pertaining to the main air pollutants (inhalable particulate matter PM2.5 and PM10, nitrogen dioxide (NO2), and ozone (O3)) and climate parameters (air temperature at 2 m height, relative humidity, wind speed intensity and direction, planetary boundary layer height, and surface solar irradiance), a direct positive impact of aerosol loading (PM2.5, PM10, and aerosol optical depth (AOD)) on COVID-19 spreading and severity was revealed. Despite some urban differences existing between the selected cities, particularly for the spring–summer periods, we have observed negative correlations between daily new COVID-19 cases and deaths and daily average ground-level ozone concentration, air temperature at 2 m height, planetary boundary layer height, and surface solar irradiance. Air relative humidity and urban population density have a direct impact on COVID-19 diffusion in large metropolitan areas, and the findings of this study highlight the crucial role of air pollution, in synergy with climate variability, in viral pathogens dispersion in COVID-19 transmission in large urban areas. This information can be used by decision-makers to develop targeted interventions during epidemic periods to reduce the potential risks associated with air pollution exposure and to promote the sustainable development of urban economies.

Physical and optical properties of cirrus and subvisible cirrus clouds over Arabian sea and Bay of Bengal region

Cirrus clouds play a crucial role in regulating the Earth’s radiation budget, and this paper aims to contribute to a deeper understanding of their optical and geometrical properties over the Arabian Sea (AS) and Bay of Bengal (BoB) regions using CALIPSO data. Comprehensive statistics are derived, encompassing mean values of cirrus cloud top, base altitude, geometrical thickness, cloud optical depth, and temperature. Over the AS region, the mean values are 15.10 ± 1.50 km, 12.63 ± 1.75 km, 2.52 ± 1.37 km, 0.4 ± 0.58, and -62.30 ± 10.6 (°C), respectively. For the BoB region, the corresponding values are 15.43 ± 1.51 km, 12.72 ± 1.74 km, 2.71 ± 1.46 km, 0.49 ± 0.67, and -64.35 ± 10.7 (°C). A larger spread in optical depth and a higher frequency of occurrence for both cirrus and subvisible cirrus (SVC) clouds were observed over BoB compared to AS. Additionally, the study delves into SVC cloud characteristics, emphasizing their thinness and higher base altitudes compared to cirrus clouds. This comprehensive investigation contributes valuable insights into the distinctive properties of cirrus and SVC clouds in these regions, enhancing our knowledge of atmospheric processes and their implications for climate modelling and predictions.

Unusually low dust activity in North Africa in June 2023: Causes, impacts and future projections

Dust activity during the pre-monsoon season in Africa has an impact on the monsoon circulation and the Atlantic hurricane season. During early June 2023 the atmosphere was relatively clear over West Africa and the eastern tropical Atlantic, in contrast with the dustier June 2020. The negative phase of the North Atlantic Oscillation suppressed dust lifting, with an equatorward shifted African Easterly Jet limiting its downstream advection. On the other hand, dust accumulated in the atmosphere over northeastern Africa, with the negative dust aerosol optical depth (DAOD) anomalies over western Africa and the positive anomalies over eastern Africa more than two standard deviations away from the climatological mean. The lack of dust led to an up to 55 W m−2 increase in the surface downward shortwave radiation flux and a 35 W m−2 decrease in the longwave flux, and is in line with the record-breaking sea surface temperatures over the eastern tropical Atlantic and the active start to the Atlantic hurricane season. In order to explore future projections of DAOD, a multi-model ensemble (MME) is constructed from 29 models that integrate the sixth phase of the Coupled Model Intercomparison Project (CMIP6). It captures the positive trend in the June DAOD over the eastern tropical Atlantic during 1980–2014, although the amplitude is roughly a factor of six smaller than the 0.0017 year−1 in the reanalysis dataset. The CMIP6 MME projects a further increase in DAOD in the region at a rate of up to 0.0003 year−1 in the most extreme climate change scenario for 2066–2100, which is comparable to that seen during the historical period, even though the mean values are projected to decrease by 0.03–0.06. While lower dust loadings may lead to improved air quality, they will likely further fuel pre-season and early season storms in the North Atlantic, which have become more frequent in recent decades.

Dust Emissions on Mars From Phoenix Lidar Measurements in Relation to Local Meteorological Conditions

AbstractThe diurnal cycle of dust aerosols on Mars is studied by analyzing lidar observations at the Phoenix landing site under cloud‐ and fog‐free conditions and in the absence of elevated, long‐range transported dust layers. There is a pronounced diurnal cycle in the dust‐layer height with minimum heights of 4–6 km occurring between 11:00 and 17:00 local time. The ratio of the aerosol optical depth (AOD) within the lowermost 2 km to the total AOD reaches peak values at the same time. This can be explained by local dust emissions driven by the diurnal cycle of heating and cooling in the boundary layer. Analysis of wind and pressure measurements show that the gustiness of surface winds and the frequency of convective vortices undergo diurnal variations resembling those of AOD, indicating that these processes are the main drivers for local dust emissions.

Spatiotemporal Evolution in the Thermal Environment and Impact Analysis of Drivers in the Beijing–Tianjin–Hebei Urban Agglomeration of China from 2000 to 2020

As urbanization advances, the issue of urban heat islands (UHIs) grows increasingly serious, with UHIs gradually transitioning into regional urban heat islands. There is still a lack of research on the evolution and drivers of the thermal environment in urban agglomerations; therefore, in this study, we used trend analysis methods and spatial statistical analysis tools to investigate these issues in the Beijing–Tianjin–Hebei (BTH) urban agglomeration. The results demonstrated the following: (1) The land surface temperature (LST) exhibited low fluctuation, while the relative land surface temperature (RLST) fluctuated significantly. In Zhangjiakou and Chengde, the LST and RLST evolution trends were complex, and the results differed between daytime and nighttime, as well as between the annual and seasonal scales. In other regions, the trends of LST and RLST evolution were more obvious. (2) During the daytime, the high UHI clusters centered on “BJ–TJ–LF” and “SJZ–XT–HD” formed gradually; during the nighttime, the high UHI clusters were mainly observed in built-up areas. The distribution range and direction of UHIs showed greater degrees of evolution during the daytime in summer. (3) The total UHI area showed an increasing trend, and the intensity of heat stress suffered by the BTH agglomeration was increasing. (4) In BTH and Hebei, aerosol optical depth, surface solar radiation, population density, and gross domestic product were the dominant factors influencing UHIs; moreover, in Beijing and Tianjin, all factors showed an basically equal impact. The methodology and findings of this study hold significant implications for guiding urban construction, optimizing urban structure, and improving urban thermal comfort in the BTH urban agglomeration.