Low Cloud Cover Research Articles

Iterative inversion method for retrieving the optical properties of aerosol under cloud by ground-based scanning lidar

Low and dense cloud cover is often encountered in daily observing experiments with lidar. In such scenarios, the laser cannot penetrate the clouds and it is not possible to use the clean atmosphere to initially calibrate the calibration heights required for the actual inversion, which can pose a significant challenge to the inversion of aerosols under clouds. This paper proposes an iterative proximal calibration algorithm based on slope method and Fernald's backward integral equation, combined with the inherent observational mode characteristics of the micro infrared lidar (mIRLidar). By conditioning the iterative process, the relative error between the obtained extinction coefficient value and the true value becomes smaller and smaller as the number of iterations increases. According to the inversion results of the actual lidar observation data, it can be tentatively concluded that the use of the proximal calibration iterative algorithm eliminates the limitations of the traditional Fernald height calibration method and improves the accuracy of the under-cloud aerosol inversion.

Environmental influence and species occurrence of yellowjacket drones in an invaded area

During the mating season, reproductive individuals of numerous insect species gather in rendezvous areas, which increases mating opportunities. Male hymenopterans often have to move considerable distances during a particular season, searching or waiting for receptive females. Such behavior is likely driven by a complex combination of individual and species-specific traits, environmental influence, and landscape cues. Our field study aimed to determine factors affecting the occurrence of Vespula spp. drones, focusing on the influence of vegetation traits, atmospheric factors and diel effects, and the species occurrence proportion in an invaded area in Patagonia. Our results indicate that the probability of drone presence over different types of vegetation is affected both by plant species and height. Also, weather and time of day influence the number of individuals simultaneously gathering, as higher abundances of flying drones are found in early hours, warmer days and at low cloud cover. Lastly, through mid-flight drone captures, we determined that both V. germanica and V. vulgaris drones are found concurrently in the same rendezvous areas. This constitutes the first exploratory field study reporting the heterospecific occurrence of Vespula spp. drones and overall, our results contribute to the understanding of yellowjackets mating systems.

Clouds reduce downwelling longwave radiation over land in a warming climate.

Clouds greatly influence the Earth's energy balance1,2. Observationally constraining cloud radiative feedback, a notably uncertain climate feedback mechanism3-5, is crucial for improving predictions of climate change5-7 but, so far, remains an elusive objective, and the feedback may be different over the ocean versus over land8-10. Here we show a local negative surface longwave cloud feedback over land at the southern Great Plains site, constrained by direct long-term observation of spectrally resolved downwelling longwave radiance11. This negative cloud feedback at thesouthern Great Plains site causes a -1.77 ± 1.15 W m-2 per decade change in downwelling longwave radiation and suggests that cloud changes may partially modulate the warming effect of increased greenhouse gas concentrations and atmospheric temperatures over land. Specifically, our results are derived from an optimal spectral fingerprinting method12-15 designed to separate surface longwave cloud feedback from other surface forcings and feedbacks, by making use of their unique spectral signatures13-18 in the long-term record of spectrally resolved radiances. Furthermore, we show that the results are not sitespecific: negative surface longwave cloud feedbacks, primarily induced by decreasing low cloud cover in warming climates, are commonly observed over land in reanalysis and satellite datasets. Our findings establish a pivotal observational benchmark of radiative forcing and feedback needed for validating climate model performance over land.

Recent global temperature surge intensified by record-low planetary albedo.

In 2023, the global mean temperature soared to almost 1.5K above the pre-industrial level, surpassing the previous record by about 0.17K. Previous best-guess estimates of known drivers including anthropogenic warming and the El Niño onset fall short by about 0.2K in explaining the temperature rise. Utilizing satellite and reanalysis data, we identify a record-low planetary albedo as the primary factor bridging this gap. The decline is apparently caused largely by a reduced low-cloud cover in the northern mid-latitudes and tropics, in continuation of a multi-annual trend. Further exploring the low-cloud trend and understanding how much of it is due to internal variability, reduced aerosol concentrations, or a possibly emerging low-cloud feedback will be crucial for assessing the current and expected future warming.

EFFICIENT USE OF LANDSAT-8 DATA TO MINIMIZE CLOUD COVERAGE IN THE ANALYSIS OF SOYBEAN, CORN, AND COTTON CULTIVATION

This study aimed to manipulate databases from the Landsat-8 project to select orbital scenes with minimal cloud coverage aligned with the growth periods of cotton, corn, and soybean crops in the Cerrado biome. Employing an Extract, Transform, Load (ETL) approach, the research focused on extracting and transforming large datasets by integrating georeferenced information from IBGE and data from the Agricultural Risk Zoning (ZARC). The planting windows for the 2014 to 2019 harvests were identified with a 20% or lower climate risk, considering variables such as soil and climate conditions. The results indicated that the availability of images with low cloud coverage is inversely related to the planting windows, especially during critical periods. To streamline the processing, algorithms were developed in R and Python, and a script for automatic image downloading was implemented. Despite data standardization challenges, applying big data techniques proved essential for the analysis. This study enhances efficiency in agricultural planning and emphasizes the importance of further exploring remote sensing technologies in response to current food security and sustainability demands.

Systematic Upstream Large-Scale Control of Subtropical Low-Cloud Properties

Abstract It has recently been shown that the slow adjustment of the atmospheric boundary layer (ABL) to perturbations of the large-scale atmospheric conditions translate into an upstream control of the low-cloud cover (LCC) variability at climatological timescales in the subtropics. In this study we expand upon this recent study to investigate upstream control of the climatology of low-cloud radiative effect (CRE), as well as cloud properties relevant to their radiative effect: cloud liquid water path (LWP), and cloud optical depth (COD).We use machine-learning statistical models with feature selection capabilities (random-forests) to determine the influence of the local and upstream large-scale conditions in monthly data. These conditions are determined using back-trajectories in monthly-mean wind fields. Total CRE, dominated by the shortwave contribution, exhibits a dependence on upstream Estimated Inversion Strength (EIS), but not on upstream Sea-Surface Temperature (SST) as LCC does. Upstream control of COD was present but was not as consistent as LCC or CRE across different regions and cloud regimes, while LWP does not exhibit strong upstream control at all. This implies that the control of other boundary layer properties could explain the differences in response between LCC and CRE to SST and EIS. Looking at five subtropical eastern basins, it appears that key lead times are region-specific. The inclusion of upstream control provides significant improvements to the predictive skill of statistical models over local linear regression, with improvements in variance explained well over 20% in many cases.

Relationship Between Short and Long Wave Radiation with Cloud Cover in Baghdad City

Short waves are waves that have a short wavelength and are characterised by high frequencies. Therefore, they propagate over short distances from the source and are used for wireless communications and radio broadcasting. As for long waves, they have a long wavelength characterised by low frequencies and usually extend far from the source easily. When the clouds prevent sunlight from reaching Earth, it reflects a large part of it and absorbs part of the radiation that passes through it, so that less radiation reaches the Earth’s surface as a result of the clouds. The daily data of the high, medium, and low cloud cover, as well as the daily and annual data of solar radiation (long and short-wave radiation) were extracted from satellite data collected by the European Center for Medium-Range Weather Forecasting (ECMWF) over the Baghdad station at 00:00 am and 12:00 pm for the period (2015-2019). The study aims to find the effect of cloud cover on long and short waves and to find the type of relationship between them. The results showed that. The High and medium clouds are more visible in winter and less in summer. The clouds of all kinds decrease at 00:00 am and can be observed at noon. The relationship between solar radiation and cloud cover is inverse. In 2015 different types of clouds appeared, including low-lying cumulus and cumulus-medium. The radiation of long waves increases in the spring and summer when the amount of solar radiation entering the atmosphere is greater, and therefore the atmosphere derives its heat from these long waves emanating from the surface of the earth, at a time when the air could not absorb the short waves that make up the sun’s rays when it penetrated it. Through the Pearson coefficient test, several results were obtained, including that the relationship between high, medium, and low cloud cover, as well as total solar radiation, showed an inverse association; the more clouds there are, the less solar radiation reaches the earth’s surface.

Differential growth rate, water use efficiency and climate sensitivity between males and females of Ilex aquifolium in north-western Spain.

Dioecious plant species, i.e., those in which male and female functions are housed in different individuals, are particularly vulnerable to global environmental changes. For long-lived plant species, such as trees, long-term studies are imperative to understand how growth patterns and their sensitivity to climate variability differentially affect the sexes. Here, we explore long-term intersexual differences in wood traits, namely radial growth rates, water use efficiency quantified as stable carbon isotope abundance of wood cellulose, and their climate sensitivity in Ilex aquifolium trees growing in a natural population in NW Spain. We found that sex differences in secondary growth rates were variable over time, with males outperforming females in both radial growth rates and water use efficiency in recent decades. Summer water stress significantly reduced the growth of female trees in the following growing season, while the growth of male trees was primarily favoured by cloudy and rainy conditions the previous fall and winter combined with low cloud cover and warm conditions in summer. Sex-dependent lagged correlations between radial growth and water availability were found, with a strong association between tree growth and cumulative water availability in females at 30 months and in males at 10 months. Overall, our results point to greater vulnerability of female tress to increasing drought, which could lead to sex-ratio biases threatening population viability in the future.

Seasonal variations of Arctic cloud in recent 14 years using CALIPSO-GOCCP

This study documents the three-dimensional structure and long-term trend of Arctic cloud cover with 14-year Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations from a seasonal perspective. Results show that Arctic Ocean presents larger low-level cloudiness and more evident vertical contrast between low and high-level cloud cover than Arctic land. Furthermore, Arctic Atlantic experiences the largest total and low-level cloud cover all year long, with relatively weak seasonal variation. In contrast, the low-level cloud cover over Arctic Pacific displays a pronounced bimodal annual cycle, as well as the low-level cloud cover over Arctic land. Arctic Atlantic with the maximum cloud fraction has the highest altitude of about 1.2 km above open sea in winter, which is near the surface in summer. The cloudiness in the lower troposphere over open water is significantly larger than that over ice except in winter, whereas, the liquid-containing cloud over open water is significantly larger than that over ice in the lower troposphere in four seasons. Moreover, though the liquid-containing cloud dominates the low-level cloud cover, its increasing trend is driven by liquid-containing and ice-containing cloud together. Instead, the ice-containing cloud dominates the high-level cloud cover and its increasing trend in all seasons over most Arctic regions, except a negative trend over Greenland in winter. Our work presents a more comprehensive picture of the Arctic cloud cover, which provides an insight into understanding of Arctic cloud and Arctic climate system.

Pan-Arctic methanesulfonic acid aerosol: source regions, atmospheric drivers, and future projections

Natural aerosols are an important, yet understudied, part of the Arctic climate system. Natural marine biogenic aerosol components (e.g., methanesulfonic acid, MSA) are becoming increasingly important due to changing environmental conditions. In this study, we combine in situ aerosol observations with atmospheric transport modeling and meteorological reanalysis data in a data-driven framework with the aim to (1) identify the seasonal cycles and source regions of MSA, (2) elucidate the relationships between MSA and atmospheric variables, and (3) project the response of MSA based on trends extrapolated from reanalysis variables and determine which variables are contributing to these projected changes. We have identified the main source areas of MSA to be the Atlantic and Pacific sectors of the Arctic. Using gradient-boosted trees, we were able to explain 84% of the variance and find that the most important variables for MSA are indirectly related to either the gas- or aqueous-phase oxidation of dimethyl sulfide (DMS): shortwave and longwave downwelling radiation, temperature, and low cloud cover. We project MSA to undergo a seasonal shift, with non-monotonic decreases in April/May and increases in June-September, over the next 50 years. Different variables in different months are driving these changes, highlighting the complexity of influences on this natural aerosol component. Although the response of MSA due to changing oceanic variables (sea surface temperature, DMS emissions, and sea ice) and precipitation remains to be seen, here we are able to show that MSA will likely undergo a seasonal shift solely due to changes in atmospheric variables.

Impacts of synoptic weather patterns on Hefei's ozone in warm season and analysis of transport pathways during extreme pollution events

Extreme ozone pollution events (EOPEs) are associated with synoptic weather patterns (SWPs) and pose severe health and ecological risks. However, a systematic investigation of the meteorological causes, transport pathways, and source contributions to historical EOPEs is still lacking. In this paper, the K-means clustering method is applied to identify six dominant SWPs during the warm season in the Yangtze River Delta (YRD) region from 2016 to 2022. It provides an integrated analysis of the meteorological factors affecting ozone pollution in Hefei under different SWPs. Using the WRF-FLEXPART model, the transport pathways (TPPs) and geographical sources of the near-surface air masses in Hefei during EOPEs are investigated. The results reveal that Hefei experienced the highest ozone concentration (134.77 ± 42.82 µg/m³), exceedance frequency (46 days (23.23 %)), and proportion of EOPEs (21 instances, 47.7 %) under the control of peripheral subsidence of typhoon (Type 5). Regional southeast winds correlated with the ozone pollution in Hefei. During EOPEs, a high boundary layer height, solar radiation, and temperature; low humidity and cloud cover; and pronounced subsidence airflow occurred over Hefei and the broader YRD region. The East-South (E_S) patterns exhibited the highest frequency (28 instances, 65.11 %). Regarding the TPPs and geographical sources of the near-surface air masses during historical EOPEs. The YRD was the main source for land-originating air masses under E_S patterns (50.28 %), with Hefei, southern Anhui, southern Jiangsu, and northern Zhejiang being key contributors. These findings can help improve ozone pollution early warning and control mechanisms at urban and regional scales.

The joint effects of the El Niño-Southern Oscillation and Arctic Oscillation on tropical Indian Ocean heat flux during boreal winter

In this study, the joint effects of the El Niño-Southern Oscillation (ENSO) and Arctic Oscillation (AO) on winter net surface heat flux (Qnet) anomalies over the tropical Indian Ocean (TIO) are investigated for the 1979/1980–2017/2018 period. The results show that, in multisource datasets, the Qnet pattern for El Niño plus positive AO cases is the most robust. The major feature of Qnet is dominated by a significant dipole pattern, with oceanic heat gain anomalies appearing over the southeastern TIO and oceanic heat loss near the western TIO. Analysis of the flux components shows that the Qnet anomalies are mainly contributed by changes in latent heat flux and shortwave radiation (QLHF and QSWR), which are tightly associated with the regional atmospheric and oceanic conditions. In association with positive AO, northerly wind anomalies on the eastern flanks of a low-level anomalous anticyclone in the Arabian Sea enhance the intertropical convergence zone (ITCZ) in the western TIO. Meanwhile, the El Niño-related SST warming occurs in the western TIO. Both enhanced ITCZ and anomalous SST warming favour in situ increased low and middle cloud cover and a reduced QSWR. Furthermore, under El Niño's effect, a low-level anomalous anticyclone located in the southeastern TIO leads to a positive QLHF through decreased near-surface wind speed and increased near-surface air humidity. As a result, a dipole Qnet pattern tends to be observed for the combination of El Niño and positive AO.

Cold Surge Impacts on the Structure, Energy Budget, and Turbulence of the South China Sea Boundary Layer

Abstract Episodic cold surges in the East Asia winter monsoon can penetrate deep into the South China Sea (SCS), enhance consequent tropical rainfall, and further strengthen the East Asia meridional overturning circulation. These cold surges can promote strong surface fluxes and lead to a deeper marine boundary layer (MBL). However, there is a lack of boundary layer studies over the SCS, unlike many other well-studied regions such as the north Atlantic Ocean and the central-eastern Pacific Ocean. In this study, we use high resolution radiosonde data of temperature and humidity profiles over Dongsha Island (116.69E, 20.70N) to identify the inversion layer, mixed layer, cloud base, cloud top, and factors controlling low cloud cover for the period of December-January-February from 2010 to 2020. We perform an energy budget analysis with ERA-5 meteorological variables and surface fluxes. Here we show a strong turbulent flux convergence of both heat and moisture within the SCS MBL during cold surges, which leads to a lifting of the mixed layer to ~1.0 km and inversion layer to ~2.0 km and associated cloud development over Dongsha Island. The cold and dry horizontal advection is balanced by this vertical turbulent flux convergence in the energy budget. Overall, cold surges over the SCS enhance lower branch of winter monsoon meridional overturning circulation with stronger inversion and higher low cloud covers.

Converging Findings of Climate Models and Satellite Observations on the Positive Impact of European Forests on Cloud Cover

AbstractAlthough afforestation is a potential strategy to mitigate climate change by sequestering carbon, its potential biophysical effects on climate, such as regulating surface albedo, evapotranspiration, and energy balance, have not been fully incorporated into climate change mitigation strategies. This is partly due to the challenges associated with modeling the complex bidirectional interactions between vegetation and climate. In this study, we assess the impact of afforestation on low cloud cover using a regional climate model (RCM) and Earth observation data, applying a space‐for‐time approach to overcome limitations that may arise from comparing satellite and RCM results, such as different background climate conditions or different extents of land cover change. Our results show a consistent increase in low cloud cover in Europe due to afforestation in both datasets (3.71% and 3.56% on average, respectively), but the magnitude and direction of this effect depend on various factors, including location, seasonality, and forest type. These results suggest that afforestation can have important feedbacks on the climate system, and that its biophysical effects must be considered in climate change mitigation strategies. Furthermore, we emphasize the role of the modeling community in developing accurate and reliable approaches to assess the biophysical effects of land cover change on climate.

Why Do CO2 Quadrupling Simulations Warm More Than Twice as Much as CO2 Doubling Simulations in CMIP6?

AbstractWe compare abrupt CO2‐quadrupling (abrupt‐4xCO2) and ‐doubling (abrupt‐2xCO2) simulations across 10 CMIP6 models. Two models (CESM2 and MRI‐ESM2‐0) warm substantially more than twice as much under abrupt‐4xCO2 than abrupt‐2xCO2, which cannot be explained by the non‐logarithmic scaling of CO2 forcing. Using an energy balance model, we show that increased warming rates within these two models are driven by both less‐negative radiative feedbacks and smaller global effective heat capacity under abrupt‐4xCO2. These differences are caused by a decrease in low cloud cover and shallower ocean heat storage, respectively; both are linked to smaller fractional declines in the Atlantic Meridional Overturning Circulation (AMOC) under abrupt‐4xCO2 (relative to abrupt‐2xCO2). On a global scale, higher climate sensitivity under larger forcing can be explained by a feedback‐temperature dependence; however, we find that forcing‐dependent spatial warming patterns due to AMOC decline are an important physical mechanism which reduces warming in a way that is not captured by a global‐mean framework.

The effects of solar insolation and cloud opacity on the optimum array size for a direct-coupled solar pumping system

The widespread adoption of solar photovoltaic pumping technology requires pertinent information on the sizing and design of these systems. This research investigated how the ratio of photovoltaic array peak power to motor power consumption, solar insolation and cloud opacity affects the water yield of a direct-coupled solar PV pumping system. The specific aim was to estimate the optimum photovoltaic power to motor power consumption (OPVM) ratio for a 3 W DC pump under Jamaican weather conditions. The PVM ratio is the ratio of peak array power to nominal motor power consumption. Four experimental direct coupled solar pumping systems were set up and the water yield for each measured daily for thirty days. Each system was identical in every respect except each having a different solar array peak power. The findings show that there is a strong correlation (Pearson coefficient of −0.903) between solar insolation and the optimum photovoltaic power to motor power consumption ratio. Additionally, there was found to be a strong correlation between average cloud opacity and optimum photovoltaic power to motor power consumption ratio (Pearson coefficient of 0.899). Both correlations were shown to be statistically significant, with both yielding p-values <0.001. The findings of the correlation analysis indicate that a relatively large PVM ratio would be economical when used on a site that regularly receives relatively low insolation and heavy cloud cover. Finally, the daily optimum photovoltaic power to motor power consumption ratio ranged from approximately 2.3 to 5.0. Generally, it was observed that the OPVM ratio shifted below 2.4 on clear sunny days and above 4.0 on very cloudy days. While these conclusions may not exactly extrapolate to scales of practical application, performance metrics of larger systems are expected to bear some similarity. Being guided by these results, additional studies at these larger scales are recommended.

OCCURRENCES OF LOW CLOUDS OVER THE WESTERN MARGINS OF THE CONGO BASIN (SEPTEMBER TO DECEMBER 2021)

This study aims to analyze the occurrence of low cumuliform clouds over the western margins of the Congo Basin from September to December 2021. The imagery of the Cloud Top Height product of Meteosat Second Generation set on synoptic hours (i.e. 00 hours, 06 hours, 12 hours and 18 hours) have been retained for this study. Through these data, we have developed an observation grid of 1° over the entire Congolese territory to make an inventory of low clouds identified at each 1°. The results obtained show that the low clouds appear most often between 00 hours and 12 hours. And the spatial distribution of the occurrences of clouds attests that the low cloud cover remains more pronounced in the Southern, Southwestern and Northern parts of the country.

Spatial-temporal characteristics analysis of solar irradiance forecast errors in Europe and North America

Accurate photovoltaic (PV) power forecast is crucial to power systems. Solar irradiance forecast is the fundamentals of PV power forecast. Current researches merely focus on improving the forecast accuracy. There hasn't been comprehensive study on the spatial-temporal characteristics of solar irradiance forecast errors. Thus, this paper analyzed the error characteristics of solar irradiance forecast provided by European Centre for Medium-Range Weather Forecasts (ECMWF), one of the most accurate numerical weather prediction (NWP) products. ECMWF's forecasts were compared with ERA5 solar irradiance reanalysis data to reveal the error distribution characteristics. Four-year (2017–2020) data from the geographical region bounded by 63°N, −126°W, 21°S, and 36°E (covering most parts of Europe and North America) were studied. Experiments show that solar irradiance forecast errors peak at noon of the local time. Furthermore, correlations between solar irradiance forecast errors and other weather variables were also revealed. Experiments show that solar irradiance forecast errors have negative correlation with low cloud cover forecast errors and positive correlation with air temperature forecast errors. The possible reasons for the correlation relationship were also analyzed in detail. This paper systematically reveals the spatial-temporal characteristics of solar irradiance forecast errors and provides a useful guideline for solar PV system operation.

Divergent Responses of Summer Terrestrial Evapotranspiration to Cloud Increase in East Asia

AbstractCloud impact on terrestrial evapotranspiration (ET) can be significant, while a fundamental understanding of ET response to cloud change has not been addressed in regional aspects. In this study, seven ET datasets from satellite and land surface models are used to analyze the summer ET in response to low cloud cover (LCC) over East Asia, in combination with satellite microwave and optical vegetation data, as well as ERA5 climatic and surface parameters. In general, all ET datasets present a strong negative relationship with LCC over dense vegetation (e.g., forests), which leads to the ET reduction of more than −0.5 mmday−1 under the large LCC increase, compared with the least cloudy sky conditions. Such reduction is stronger under more humid and denser forests (aridity index AI &gt; 0.5 and enhanced vegetation index EVI &gt; 0.6). In contrast, a positive relationship between ET and LCC presents over arid and sparse lands (AI &lt; 0.2 and EVI &lt; 0.2), accompanied by enhanced ET (&gt;0.2 mmday−1). Analysis shows that under increased LCC conditions, substantial reduction in radiation availability results in the decline in both plant transpiration (ETveg) and soil evaporation (ETsoil) over humid dense vegetation, dominating the overall negative response. The increase of near‐surface relative humidity over arid sparse vegetation may indicate a stronger moisture availability, which promotes ETsoil and partly offsets the negative effect of radiation reduction. The change of vegetation water content, indicated by a satellite microwave vegetation index, is important for ETveg over arid mountainous lands with cloud cover. These findings contribute new insights to the understanding of vegetation‐atmosphere interactions.

Characteristics and mechanisms of near-surface negative atmospheric electric field anomalies preceding the 5 September 2022, Ms 6.8 Luding earthquake in China

Abstract. A magnitude 6.8 strike-slip earthquake (EQ) struck Luding, Sichuan Province, China, on 5 September 2022, resulting in significant damage to nearby Ganzi Prefecture and the city of Ya'an. In this research, the near-surface atmospheric electric field (AEF) recorded at four sites 15 d before the Luding EQ was analyzed and differentiated, and multisource auxiliary data including precipitation, cloud base height, and low cloud cover were used at the same time. Nine possible seismic AEF anomalies at four sites were obtained preliminarily. Accordingly, microwave brightness temperature (MBT) data, which are very sensitive to the surface dielectrics and are closely related to the air ionization, together with surface soil moisture, lithology, and a 3D-simulated crustal stress field, were jointly analyzed to confirm the seismic relations of the obtained negative AEF anomalies. The geophysical environment for crustal high-stress concentration, positive charge carrier transfer, and surface accumulation was demonstrated to exist and to meet the conditions necessary to generate local negative AEF anomalies. Furthermore, to deal with the spatial disparities in sites and regions with potential atmospheric ionization, near-surface wind field data were employed to scrutinize the reliability of the AEF anomalies by comprehensively analyzing the spatial relationships among surface charges accumulation areas, wind direction and speed, and the AEF sites. Finally, four negative AEF anomalies were deemed to be closely related to the Luding EQ, and the remaining five possible anomalies were ruled out. A possible mechanism of negative AEF anomalies before the Luding EQ is proposed: positive charge carriers were generated from the underground high-stress concentration areas and then transferred to and accumulated on the ground surface to ionize the surface air, thus disturbing the AEF above the ground. This study presents a method for identifying and analyzing seismic AEF anomalies and is also beneficial for the examination of the pre-earthquake coupling process between the coversphere and the atmosphere.