High Cloud Cover Research Articles

Intraday analyses on weather-induced sentiment and stock market behavior

We examine the intraday relationship between weather conditions and investor sentiment in the Korean equity market. By uncovering the intermediary role of weather-induced sentiment in affecting market variables, we suggest a potential link between weather conditions, sentiment, and market dynamics. High temperatures, humidity, and cloud coverage negatively affect investors’ moods, while strong winds and long sunshine durations have a positive impact. Although only cloud coverage marginally impacts stock returns, weather factors significantly affect market turnover, volatility, and illiquidity, especially when they alter sentiment dynamics.

Robustness of the relationship between tropical high-cloud cover and large-scale circulations

High clouds play an important role in climate variations by shading the sun and contributing to the greenhouse effect. It has been suggested that these variations are strongly controlled by atmospheric circulations; however, the relationship between high clouds and circulations in global simulations has been confirmed only for a limited number of general circulation models (GCMs). Increasing our understanding of this relationship requires a more complete dataset of state-of-the-art GCMs. This study quantifies the relationship between high clouds and circulations by spatial and temporal correlation using data from 28 atmospheric GCMs along with a global nonhydrostatic model, a new-type of GCM, and reveals a robust and strong relationship in most models. This study also finds that the sensitivity, which is defined as the slope of the relationship between high clouds and mass fluxes of circulations, is highly model-dependent. This suggests that a similar change of circulations does not guarantee that of high clouds, which could be one reason for the complexity in projecting high-cloud changes due to warming. Moreover, this study confirms in both observation and models that the relationship with circulations is stronger for medium-thickness and thick high clouds than for thin clouds. Furthermore, the relationship between high clouds and circulations is more convincing in near-equatorial regions between 15°S–15°N, the ascending branch of the Hadley circulation, where deep convection is especially active.

Mapping Field-Level Maize Yields in Ethiopian Smallholder Systems Using Sentinel-2 Imagery

Remote sensing offers a low-cost method for estimating yields at large spatio-temporal scales. Here, we examined the ability of Sentinel-2 satellite imagery to map field-level maize yields across smallholder farms in two regions in Oromia district, Ethiopia. We evaluated how effectively different indices, the MTCI, GCVI, and NDVI, and different models, linear regression and random forest regression, can be used to map field-level yields. We also examined if models improved by adding weather and soil data and how generalizable our models were if trained in one region and applied to another region, where no data were used for model calibration. We found that random forest regression models that used monthly MTCI composites led to the highest yield prediction accuracies (R2 up to 0.63), particularly when using only localized data for training the model. These models were not very generalizable, especially when applied to regions that had significant haze remaining in the imagery. We also found that adding soil and weather data did little to improve model fit. Our results highlight the ability of Sentinel-2 imagery to map field-level yields in smallholder systems, though accuracies are limited in regions with high cloud cover and haze.

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.

Influence of Image Compositing and Multisource Data Fusion on Multitemporal Land Cover Mapping of Two Philippine Watersheds

Cloud-based remote sensing has spurred the use of techniques to improve mapping accuracy where individual images may have lower quality, especially in areas with complex terrain or high cloud cover. This study investigates the influence of image compositing and multisource data fusion on the multitemporal land cover mapping of the Pagsanjan-Lumban and Baroro Watersheds in the Philippines. Ten random forest models for each study site were used, all using a unique combination of more than 100 different input features. These features fall under three general categories. First, optical features were derived from reflectance bands and ten spectral indices, which were further subdivided into annual percentile and seasonal median composites; second, radar features were derived from ALOS PALSAR by computing textural indices and a simple band ratio; and third, topographic features were computed from the ALOS GDSM. Then, accuracy metrics and McNemar’s test were used to assess and compare the significance of about 90 pairwise model outputs. Data fusion significantly improved the accuracy of multitemporal land cover mapping in most cases. However, image composition had varied impacts for both sites. This could imply local characteristics and feature inputs as potential determinants of the ideal composite method. Hence, the iterative screening or optimization of both input features and composites is recommended to improve multitemporal mapping accuracy.

Reduction in the Tropical High Cloud Fraction in Response to an Indirect Weakening of the Hadley Cell

AbstractTropical high cloud cover decreases with surface warming in most general circulation models. This reduction, according to the “stability‐iris” hypothesis, is thermodynamically controlled and linked to a decrease in the radiatively‐driven clear‐sky convergence, when the peak anvil clouds rise because of the rising isotherms. The influence of the large‐scale dynamical changes on the tropical high cloud fraction remains difficult to disentangle from the local thermodynamic influence, given that the mean meridional circulation remains inextricably tied to the local thermodynamic structure of the atmosphere. However, using idealized general circulation model simulations, we propose a novel method to segregate the dynamical impact from the thermodynamic impact on the tropical high cloud fraction. To this end, our investigation primarily focuses on the mechanisms underpinning changes in the high cloud cover in the deep tropics in response to extratropical surface warming, when the tropical sea surface temperatures remain invariant. Net convective detrainment of ice cloud condensates decreases at the peak detrainment region, without a rise in its altitude. We also find that the importance of depositional growth of ice cloud condensates in controlling the high cloud fraction response in the deep tropics varies with altitude.

Systematic Differences between the Northern and Southern Hemispheres: Warm-Frontal Ice Water Path Linked to the Origin of Extratropical Cyclones

Abstract Extratropical cyclones (ETCs) produce most of the winter precipitation at midlatitudes and are often associated with the most extreme winter weather events. For climate models to accurately predict the occurrence and severity of these extreme events in a changing climate, they need to accurately represent moist processes in general and ice processes in particular. To provide an observational constraint for model evaluation, because cloud cover and precipitation are prevalent in warm-frontal regions, a compositing method is applied to ice retrievals from satellite observations to explore the ice distribution across warm fronts in both hemispheres. Ice water path (IWP) and its variability are compared between Northern Hemisphere (NH) and Southern Hemisphere (SH) warm fronts for different ETC-wide characteristics, as well as for different ETC origination regions. Results reveal that warm-frontal IWP and its variability tend to be higher in the NH than the SH, even when controlling for the ETC strength and environmental precipitable water (PW). IWP differences between NH and SH are found to be primarily related to where the cyclones originate. As the intertropical convergence zone is shifted north, ETCs that originate close to the northern tropics have more PW than those that originate close to the southern tropics. This, in turn, seems to lead to larger IWP in NH frontal clouds than in the SH frontal clouds at a later time. This highlights the importance, for ice amounts generated in warm-frontal regions, of the environmental conditions that an ETC encounters during its genesis phase. Significance Statement Extratropical cyclones (ETCs) are responsible for most of the winter precipitation in the midlatitudes and are often associated with severe winter weather events. In order for climate models to accurately predict these extreme events in a changing climate, they need to correctly represent moist processes, especially those involving ice. To evaluate and improve these models, we apply a compositing method to satellite observations of ice profiles in warm-frontal regions, which are known for having high cloud cover and precipitation. This helps us understand the distribution of ice across warm fronts in both the Northern Hemisphere (NH) and the Southern Hemisphere (SH). We compare the ice water path (IWP) and its variability between NH and SH warm fronts, considering different characteristics of ETCs and their formation regions. Our findings show that NH warm fronts generally contain more ice, and the amount varies a lot more across warm fronts than for SH warm fronts. This is true even when accounting for the strength of the cyclones and the moisture available to them. These differences in IWP between NH and SH are found to be primarily related to the locations where the cyclones originate. As the intertropical convergence zone (ITCZ) is shifted northward, ETCs originating closer to the northern tropics tend to have more moisture available to them than those originating closer to the southern tropics. This leads to greater ice amounts in NH frontal clouds compared to SH frontal clouds at a later time. These results emphasize the importance of understanding the origin of ETCs in order to accurately characterize ice processes in warm-frontal regions.

Chemical Data Assimilation With Aqueous Chemistry in WRF‐Chem Coupled With WRFDA (V4.4.1)

AbstractThis study introduces a new chemistry option in the Weather Research and Forecasting model data assimilation (WRFDA) system, coupled with the WRF‐Chem model (Version 4.4.1), to incorporate aqueous chemistry (AQCHEM) in the assimilation of ground‐level chemical measurements. The new DA capability includes the integration of aqueous‐phase aerosols from the Regional Atmospheric Chemistry Mechanism (RACM) gas chemistry, the Modal Aerosol Dynamics Model for Europe (MADE) aerosol chemistry, and the Volatility Basis Set (VBS) for secondary organic aerosol production. The RACM‐MADE‐VBS‐AQCHEM scheme facilitates aerosol‐cloud‐precipitation interactions by activating aerosol particles in cloud water during the model simulation. With the goal of enhancing air quality forecasting in cloudy conditions, this new implementation is demonstrated in the weakly coupled three‐dimensional variational data assimilation (3D‐Var) system through regional air quality cycling over East Asia. Surface particulate matter (PM) concentrations and four gas species (SO2, NO2, O3, and CO) are assimilated every 6 hr for the month of March 2019. The results show that including aqueous‐phase aerosols in both the analysis and forecast can represent aerosol wet removal processes associated with cloud development and rainfall production. During a pollution event with high cloud cover, simulations without aerosols defined in cloud water exhibit significantly higher values for liquid water path, and surface PM10 (PM2.5) concentrations are overestimated by a factor of 10 (3) when wet scavenging processes dominate. On the contrary, AQCHEM proves to be helpful in simulating the wet deposition of aerosols, accurately predicting the evolution of surface PM concentrations without such overestimation.

A specific stratospheric precursory signal of overshooting convective systems over the southern slope of the Tibetan Plateau

Using the TRMM PR observations, ERA5 reanalysis and Outgoing Longwave Radiation (OLR) datasets, a specific stratospheric precursory signal to the occurrence of overshooting convective systems (OCSs) over the southern slope of the Tibetan Plateau (SSTP) is investigated. We compared two types of OCS events: OCSs associated with stratospheric intrusions and other OCSs. The results indicate that there is a notable decline in the tropopause height starting two days before to on the day of the OCS onset for OCSs associated with stratospheric intrusions, but the tropopause height for other OCSs increases with the occurrence of OCS. It is found that the descending of the tropopause height is accompanied by downward intrusion of stratospheric high potential vorticity (PV) air into the troposphere for the OCSs associated with stratospheric intrusions. The increase in PV near the tropopause can cause an increase in temperature and relative vorticity near the tropopause. The OCSs associated with stratospheric intrusions are closely related to strong synoptic variability. As the stratospheric intrusion deepens on the day of the OCS onset, increased relative vorticity near the tropopause, stronger upward motion in the troposphere associated with divergence and convergence, more specific humidity in the troposphere, and weakened static stability in the middle troposphere are found within the OCS region, which are conducive to the development of deep convection that penetrates into the stratospheric intrusion. Compared with OCSs associated with stratospheric intrusions, other OCS events are characterized by stronger high cloud cover (HCC) and negative Outgoing Longwave Radiation (OLR) anomaly, as well as higher upward movement in the troposphere. This is conducive to other OCSs occurring in a more barotropic convective environment characteristic of the Asian monsoon, the vertical development height of weakened static stability and upward motion are higher, promoting the development of convective activity to higher altitudes and penetrating into the tropopause, thereby causing the uplift of the tropopause.

An observational analysis of the eastern tropical Pacific Shallow Meridional Circulation using YOTC data and pilot balloons from Isla del Coco, Costa Rica

The low-level circulation of the atmosphere over Isla del Coco has been studied and the presence of a northerly wind at low levels of the atmosphere in the eastern tropical Pacific, in addition to the deep Hadley circulation cell, has been confirmed. Using data from pilot balloons (May 1997 through January 1999, October 2007 through April 2008), the northern flow is between 1 and 5 km high, depending on the time of year, with a maximum speed located between 2 and 3 km above the surface. The generating mechanism of the surface return flow in the Hadley circulation cell has been formulated as a sea breeze, Ekman pumping of the boundary layer, and it could even be a response to the Rossby wave generated by warming in the Chocó region. These results agree with those obtained from the ERA5 reanalysis (January 1979 through December 2020), which show that the southern return cell varies in position and height during the course of the year, with a poorly organized circulation in March and strengthening from July to February. The incorporation of data of low, medium and high cloud cover from Year of the Tropical Convection (boreal summer 2009) evidenced the presence of high-level clouds in the ITCZ region and low-level clouds to the south of the ITCZ, latitudes where the south surface circulation cell is located.

Estimating the effort required to detect Kirtland's snakes (Clonophis kirtlandii)

AbstractSnakes are difficult to study due to their cryptic coloration, minimal movements, and use of inaccessible habitats. Although well‐timed surveys during a species' active season can result in higher detection rates and conserve survey resources (i.e., time and money), survey effort may not ensure the detection of rare and cryptic species. Thus, in such instances, a strategic species‐specific sampling design is needed. The Kirtland's snake (Clonophis kirtlandii) is a rare, cryptic species assumed to be experiencing range‐wide declines. Naturalists have noted the disappearance of Kirtland's snakes from various habitats since the early 1970s. The primary objective of our study was to determine detection of Kirtland's snakes and the environmental and temporal factors influencing detection. We calculated the effort needed to detect individuals at sites by estimating detection probabilities of 3 known Kirtland's snake populations in Illinois from 2019 to 2021. Based on 77 Kirtland's snake detections over 226 site visits (34.1%) across 3 study sites, we found that high cloud cover, moderate air temperature, and low relative humidity enhanced the detection probability of this species. The middle of May to the beginning of July was the best time to conduct surveys when detection rates were highest. As our results suggested, it is imperative to establish strategic monitoring programs maximizing conservation resources to document populations for conservation action and range shifts for species of conservation concern, such as Kirtland's snakes.

On the Roles of Precipitation and Entrainment in Stratocumulus Transitions between Mesoscale States

Abstract Stratocumulus occur in closed- or open-cell states, which tend to be associated with high or low cloud cover and the absence or presence of precipitation, respectively. Thus, the transition between these states has substantial implications for the role of this cloud type in Earth’s radiation budget. In this study, we analyze transitions between these states using an ensemble of 127 large-eddy simulations, covering a wide range of conditions. Our analysis is focused on the behavior of these clouds in a cloud fraction (fc) scene albedo (A) phase space, which has been shown in previous studies to be a useful framework for interpreting system behavior. For the transition from closed to open cells, we find that precipitation creates narrower clouds and scavenges cloud droplets for all fc. However, precipitation decreases the cloud depth for fc > 0.8 only, causing a rapid decrease in A. For fc < 0.8, the cloud depth actually increases due to mesoscale organization of the cloud field. As the cloud deepening balances the effects of cloud droplet scavenging in terms of influence on A, changes in A are determined by the decreasing fc only, causing a linear decrease in A for fc < 0.8. For the transition from open to closed cells, we find that longwave radiative cooling drives the cloud development, with cloud widening dominating for fc < 0.5. For fc > 0.5, clouds begin to deepen gradually due to the decreasing efficiency of lateral expansion. The smooth switch between cloud widening and deepening leads to a more gentle change in A compared to the transitions under precipitating conditions. Significance Statement By reflecting a substantial fraction of solar shortwave radiation back to space, shallow clouds constitute a major cooling agent in Earth’s radiation budget. To constrain this effect, a profound understanding of cloud cover and cloud albedo is necessary. In this study, we analyze the processes that drive the variability in these cloud properties in stratocumulus clouds, a very common cloud type covering approximately 20% of the globe. For these clouds, we show that changes from low to high or high to low cloud cover are different due to the underlying cloud micro- and macrophysics, elucidating this crucial aspect of aerosol–cloud–climate interactions.

A Modified Version of the Direct Sampling Method for Filling Gaps in Landsat 7 and Sentinel 2 Satellite Imagery in the Coastal Area of Rhone River

Earth Observation (EO) data, such as Landsat 7 (L7) and Sentinel 2 (S2) imagery, are often used to monitor the state of natural resources all over the world. However, this type of data tends to suffer from high cloud cover percentages during rainfall/snow seasons. This has led researchers to focus on developing algorithms for filling gaps in optical satellite imagery. The present work proposes two modifications to an existing gap-filling approach known as the Direct Sampling (DS) method. These modifications refer to ensuring the algorithm starts filling unknown pixels (UPs) that have a specified minimum number of known neighbors (Nx) and to reducing the search area to pixels that share similar reflectance as the Nx of the selected UP. Experiments were performed on images acquired from coastal water bodies in France. The validation of the modified gap-filling approach was performed by imposing artificial gaps on originally gap-free images and comparing the simulated images with the real ones. Results indicate that satisfactory performance can be achieved for most spectral bands. Moreover, it appears that the bi-layer (BL) version of the algorithm tends to outperform the uni-layer (UL) version in terms of overall accuracy. For instance, in the case of B04 of an L7 image with a cloud percentage of 27.26%, accuracy values for UL and BL simulations are, respectively, 64.05 and 79.61%. Furthermore, it has been confirmed that the introduced modifications have indeed helped in improving the overall accuracy and in reducing the processing time. As a matter of fact, the implementation of a conditional filling path (minNx = 4) and a targeted search (n2 = 200) when filling cloud gaps in L7 imagery has contributed to an average increase in accuracy of around 35.06% and an average gain in processing time by around 78.18%, respectively.

Hybrid mark–resight approaches account for heterogeneous detection bias in aerial surveys

Abstract Population abundance estimation is a critical yet challenging task for wildlife management decision‐making. For aerial surveys of terrestrial mammals in highly heterogenous landscapes, estimation models that address multiple sources of detection bias are needed. A typical hybrid mark–resight model includes an additive parameter that accounts for detection probabilities derived from marked animals. While this additive hybrid method improves abundance estimates, there remains a need to account for heterogeneity due to the conditional dependence in detection probability inherent in aerial surveys with multiple observers. We propose a modified approach, referred to as a conditional hybrid model, to address this heterogeneity directly. The conditional hybrid model applies a mark–resight approach typically used to account for tag loss in mark–recapture studies to aerial surveys with a subset of the population marked with GPS collars. We conduct a structured comparison between the additive and conditional hybrid estimation models and fit these two hybrid models to data from a 2020 aerial survey of mule deer in southern California. Both the additive and conditional hybrid models had general agreement in overall model structure and variable importance, however, the conditional model outperformed the additive model in capturing sources of detection heterogeneity and overall abundance estimates differed by 9%. Our top‐ranked models suggest that deer movement, larger group sizes, and rougher topography increased detection probability, whereas high cloud cover, obscuring vegetation and high observer fatigue and helicopter height decreased detection probability. Our findings illustrate the need to assess multiple correction methods when estimating abundance from aerial survey data to ensure accurate abundance estimates are being used to inform wildlife management strategies, with the caveat that specific survey conditions may dictate which method is the most appropriate for achieving robust estimates. These approaches represent the cutting‐edge science on wildlife abundance estimation from aerial survey data, a critical ingredient for effective wildlife management. By testing innovative hybrid methods, we present the first formal comparison of the strengths and weaknesses of each method within a highly heterogeneous landscape, providing practitioners with necessary information for future application.

A Study on Rice Growth Monitoring Using Drone Remote Sensing

Rice paddy is one of the key crops of Korean agriculture and it has long been regarded as an important crop. Due to the high self-sufficiency of rice in Korea, the need to establish systematic rice paddy field data is increasing, and rice paddy research using remote sensing is being conducted several times in Korea. The optical satellite remote sensing method faces difficulties in data acquisition due to the abundance of clouds caused by the summer monsoon season, a characteristic of the domestic climate. However, the drone remote sensing method equipped with an optical sensor has the advantage of being able to freely acquire data, avoiding periods with high cloud cover. In this study, a drone equipped with a multispectral optical sensor was utilized to measure the height of rice paddy. Compared to satellites, drones provide the advantage of flexible timing for observations, allowing for the acquisition of high-frequency time-series data according to specific preferences. In this study, we seek to obtain values related to rice growth rates by analyzing optical data acquired through drone remote sensing. The DJI MAVIC 2 PRO drone was employed, and the Metashape program was utilized to generate a highresolution digital elevation model (DEM) from optical data. After the harvest period, rice-free rice paddy data were assumed to be digital terrain model (DTM), the height of the rice paddies. During the rice growth period, a digital surface model (DSM) was generated from drone imagery, and by calculating the difference between DSM and DTM, the height and growth of the rice plants were observed. Using network GPS measurement data, we validated monthly DEM models. This allowed us to anticipate the acquisition of precise rice growth data throughout the year, from planting to harvest.

Long-term changes in the diurnal cycle of total cloud cover over the Tibetan Plateau

The diurnal cycle of total cloud cover (DCTCC) plays an important role in climate change over the Tibetan Plateau (TP). This study used the International Satellite Cloud Climate Project-H (ISCCP-H) observations, the fifth generation of reanalysis of the European Centre for Medium Range Weather Forecasts (ERA5), the second-generation Modern-ERA Retrospective analysis for Research and Applications (MERRA-2) reanalysis data, and 21 models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) AMIP simulations from 1984 to 2014 to investigate the climatology and long-term variations in the DCTCC over the TP. The total cloud cover (TCC) over the TP exhibits sinusoidal-like unimodal diurnal cycles and is quantified with four metrics: the daily mean (μ), daily peak time (tmax), daily coefficient of variation (cv), and full width at half-maximum of DCTCC (half width); the 30-year means of these four indices of TCC averaged over the TP were approximately 65.45%, 14:00 LST, 0.16 and 10 h, respectively. From 1984 to 2014, the TP-average μ of TCC decreased by −2.64%/decade, which was closely associated with the abrupt change in high cloud (clouds with cloud top pressure <440 hPa, defined by the ISCCP) cover (HCC) from 1998 to 1999. The tmax was postponing by approximately 0.12 h/decade, and the DCTCC was narrowing and becoming steeper. These climatology observations and trends were dominated by the middle cloud (clouds with cloud top pressure between 440 and 680 hPa, defined by the ISCCP) cover and contributed to by the HCC. There were gross deviations in the climatological DCTCC from the reanalysis datasets and models, and they can hardly reproduce the long-term trends of the DCTCC. The climatology and long-term variations of the diurnal cycles of the 2 m temperature (T2m), 10 m wind speed (U10m), vertical integral of divergence of moisture flux (DMF) and relative humidity (RH) at 250 hPa and 500 hPa exhibited significant correlations with those of the DCTCC over the TP. Over most of the TP region, the secular variations in μ of TCC were negatively correlated with those of T2m, which were dominated by the correlations between TCC and T2m during the daytime. The secular variations in the nighttime-averaged HCC have a positive association with those in the T2m over the northern TP. The spatial pattern of correlations between μ of TCC and μ of U10m and DMF were mainly reflected in the HCC. The secular variations in μ of RH were positively correlated with those of the cloud cover. The lags in the tmax of the TCC were negatively correlated with the variations in the tmax of T2m and positively associated with those of RH at 250 hPa over parts of the eastern TP. The long-term changes in the cv of the TCC were mainly positively correlated with those of T2m over most of the TP region and were partly correlated with the other factors. The decadal narrowing of the diurnal cycles of HCC was positively contributed to by the long-term trends in the half width of RH at 250 hPa over the central TP.

Spatial and Temporal Availability of Cloud-free Optical Observations in the Tropics to Monitor Deforestation

State-of-the-art methodologies to monitor deforestation rely mostly on optical satellite observations. High-density optical time series can enable the detection of deforestation almost as soon as it occurs. However, deforestation monitoring in the tropics can be hindered by high cloud coverage, and thus the responsiveness of managers, enforcement agencies, and scientists. To understand the implications of cloud contamination in freely available optical data we analyzed combined time series from Landsat 7, 8, and Sentinel-2 over the tropics from 2017–2021. Datasets derived for each 30 m × 30 m of the 59.4 M km2 domain include a) number of cloud-free observations per year, b) maximum consecutive days without clear imagery within a year, and c) final date of the longest waiting period. The datasets reflect where and when data gaps in optical time series exist due to cloud contamination. Scripts to access and extend the datasets are shared and documented. The datasets can be used to prioritize areas where complementary observations, such as radar imagery, are needed for implementing effective deforestation alert systems.

Satellite derived SO2 emissions from the relatively low-intensity, effusive 2021 eruption of Fagradalsfjall, Iceland

In March 2021 an effusive eruption began at the Fagradalsfjall volcanic system in Iceland, ending nearly 800 years of dormancy on the Reykjanes peninsula. The eruption produced lava flows and moderate gas emissions and, although it did not cause significant disruption, highlighted the need for near real-time monitoring of volcanic activity on the peninsula for future eruptions. The activity passed through several phases, each characterised by a different eruption style, providing a rich testbed for monitoring methodologies.We present measurements of the volcanic sulphur dioxide (SO2) emission rate and injection altitude throughout the eruption, generated by combining satellite SO2 imagery from TROPOMI with PlumeTraj, a back-trajectory analysis toolkit. We compare the results with ground-based measurements of the emission rate and plume altitude, finding excellent agreement in the plume altitude. Reasonable agreement was also found between the measured emission rates, with the best match for stronger and more continuous emissions. This demonstrates the ability for PlumeTraj to monitor SO2 emissions from future effusive eruptions, while highlighting the need for care when analysing results from low altitude plumes or during periods of high cloud cover.

Proteinaceous Matter in PM2.5 in Suburban Guiyang, Southwestern China: Decreased Importance in Long‐Range Transport and Atmospheric Degradation

AbstractProteinaceous matter (PrM) is a substantial constituent in bioaerosols. However, the sources and atmospheric processes of PrM remain large uncertainties. The characterizations, sources, and potential atmospheric processes of free amino acids (FAAs) and combined amino acids (CAAs) were investigated via a set of 1‐year fine particle (PM2.5) samples collected in suburban Guiyang (a hilly basin area in Southwest China). The annual average concentrations of FAAs and CAAs were 156.31 ± 41.52 and 315.36 ± 147.66 ng m−3, respectively. The dominant FAA and CAA species were proline, which was different from previous observations with glycine as a major species. The results indicated that the sources or atmospheric processes of aerosol PrM at this study site were different from previous observations in the urban and suburban areas. The analysis of AA‐nitrogen isotope compositions and air mass back trajectories suggested that the abundances of aerosol FAAs and CAAs were highly controlled by primary sources (particularly plants) with less impact from long‐range transport. Furthermore, the contributions of PrM degradation by ozone‐ and hydroxyl radical‐related processes to total FAAs were found to be minor. The overall results suggested that the long‐range transport and atmospheric degradation of PrM were insignificant factors affecting aerosol PrM abundance in this suburban area with the weak atmospheric oxidation capacity, high cloud cover rate, and frequent precipitation. Thus, the findings improve our understanding of the sources and atmospheric processes of aerosol PrM.

Satellite-based shoreline detection along high-energy macrotidal coasts and influence of beach state

Earth observation coupled with novel image analysis techniques now present a unique and powerful tool for the historical study of shoreline change at local to global scale. However, satellite-derived shoreline (SDS) data is limited in certain areas and is associated with large uncertainties relating to environmental factors, tidal range, and wave action. We use 14 years of monthly topographic surveys at two macrotidal sites in the UK representing end members of beach type (reflective, dissipative) to investigate the influence of tidal elevation and wave action on SDS accuracy. We find that applying appropriate water level corrections can significantly improve SDS accuracy. Results show that a different approach is required for water level definition depending on beach type and reveal that ultimately SDS accuracy is primarily controlled by beach state (beach profile shape). Accounting for tidal elevation led to substantial accuracy improvement at both sites and formed the optimal SDS strategy for the reflective site (Slapton). At the dissipative site (Perranporth) considering wave-induced water level fluctuations (wave setup and/or runup), including wave shoaling, was critical for reducing the tidally corrected SDS RMSE by a third and the mean bias by three quarters. An important realization for areas with high cloud cover such as the UK, and/or low satellite coverage, was that critically low image availability restricts temporally the type of phenomenon that can be detected (e.g., seasonal/interannual variability) and may compromise computed long-term trends. Our results suggest that the optimal approach is site-specific and depends on the shoreline translation method used and is therefore different depending on the application. We propose optimal SDS strategies to increase confidence in SDS extraction in meso-macrotidal environments with potentially low satellite useability (i.e., high cloud cover and/or low satellite coverage) depending on the spatial scale of the intended application. Long-term trends derived using this approach can reproduce trends from ground-based surveys and therefore enable more accurate projections of future shoreline position to be made.