Cloud Height Research Articles

Intercomparison of Sentinel-5P TROPOMI cloud products for tropospheric trace gas retrievals

Abstract. Clouds have a strong impact on satellite measurements of tropospheric trace gases in the ultraviolet, visible, and near-infrared spectral ranges from space. Therefore, trace gas retrievals rely on information on cloud fraction, cloud albedo, and cloud height from cloud products. In this study, the cloud parameters from different cloud retrieval algorithms for the Sentinel-5 Precursor (S5P) TROPOspheric Monitoring Instrument (TROPOMI) are compared: the Optical Cloud Recognition Algorithm (OCRA) a priori cloud fraction, the Retrieval Of Cloud Information using Neural Networks (ROCINN) CAL (Clouds-As-Layers) cloud fraction and cloud top and base height, the ROCINN CRB (Clouds-as-Reflecting-Boundaries) cloud fraction and cloud height, the Fast Retrieval Scheme for Clouds from the Oxygen A-band (FRESCO) cloud fraction, the interpolated FRESCO cloud height from the TROPOMI NO2 product, the cloud fraction from the NO2 fitting window, the O2–O2 cloud fraction and cloud height, the Mainz Iterative Cloud Retrieval Utilities (MICRU) cloud fraction, and the Visible Infrared Imaging Radiometer Suite (VIIRS) cloud fraction. Two different versions of the TROPOMI cloud products OCRA/ROCINN, FRESCO, and the TROPOMI NO2 product are included in the comparisons (processor version 1.x and 2.x). Overall, the cloud parameters retrieved by the different algorithms show qualitative consistency in version 1.x and good agreement in version 2.x with the exception of the VIIRS cloud fraction, which cannot be directly compared to the other data. Differences between the cloud retrievals are found especially for small cloud heights with a cloud fraction threshold of 0.2, i.e. clouds that are particularly relevant for tropospheric trace gas retrievals. The cloud fractions of the different version 2 cloud products primarily differ over snow- and ice-covered pixels and scenes with sun glint, for which only MICRU includes an explicit treatment. All cloud parameters show some systematic problems related to the across-track dependence, where larger values are found at the edges of the satellite view. The consistency between the cloud parameters from different algorithms depends strongly on how the data are filtered for the comparison, for example, what quality value is used or whether snow- and ice-covered pixels are excluded from the analysis. In summary, clear differences were found between the results of various algorithms, but these differences are reduced in the most recent versions of the cloud data.

A novel fuzzy based deep neural network for rain fall prediction using cloud images

SummaryThe most challenging aspect of weather forecasting is predicting rainfall. In contrast, timely and precise rainfall forecasting is immensely useful in developing effective security measures for active infrastructure projects, logistics, agricultural activities, air transport operations, and flood scenarios. Artificial intelligence has been established to predict rain precipitation, but very little research has been conducted on images than time‐series data to predict rainfall. However, the accuracy of the prediction model utilizing pictures is lower when compared to time series data. Thus a novel fuzzy based deep neural network (NFDNN) model was created to increase rainfall prediction performance. Initially, our research utilized input cloud images, in which the fuzzy wavelet incorporated with neural networks is utilized to identify clouds in the sky. Second, the types of clouds are determined by a fuzzy deep neural networks cloud classifier in which the adaptive fuzzy sparse representation is used. Then, the density‐based spatial clustering for applications containing noise clustering method was used to detect rainy clouds by evaluating the cloud's color and density from the fuzzy deep neural network cloud classifier. Finally, rainfall was predicted using information such as cloud categorization, appearance, and height obtained from cloud position and cloud types. As a result, the proposed NFDNN model gives a better prediction result than the existing methods.

Macro- and microphysical characteristics of snowfall and non-snowfall clouds in the West Tianshan Mountains of China based on cloud radar

The macro- and microphysical characteristics of wintertime precipitating clouds and non-precipitating clouds over the West Tianshan Mountains, China, were analyzed with the use of Ka-band radar and weighing rain gauge observations. The data were collected from January to February 2019, December 2019, and from December 2020 to February 2021. Snowfall clouds mainly ranged from 0.15 ~ 2.50 km and had a reflectivity (Z) of mostly 10 ~ 33 dBZ. Non-snowfall clouds were primarily distributed within the height range of 2 ~ 8 km, and the Z values were within the range of − 22 ~ 15 dBZ. Compared with non-snowfall clouds, snowfall clouds have a higher particle water content (M) but a similar radial velocity (V). Light and moderate snowfall clouds were mainly located at heights of 0.15 ~ 3.50 km and had Z values concentrated from 5 ~ 24 dBZ. Heavy snowfall clouds were characterized by a Z of 5 ~ 30 dBZ below 3.5 km. The proportion of clouds with an M value > 0.1 g·m−3 below 2 km was noticeably higher for heavy snow events than for light and moderate snow events. The differences in the distributions and values of snowfall cloud V values were small among the different snow types, and descending motions occurred below 6 km, with V ranging − 1.4 ~ − 0.3 m·s−1. The heights of the non-snowfall cloud top and base during the day were lower than those at night. The snowfall cloud top did not show noticeable diurnal variations. The cloud top and base heights of the non-snowfall clouds both showed a single-peak distribution. The cloud top values of snowfall clouds exhibited bimodal distributions.

Robust variation trends in cloud vertical structure observed from three-decade radiosonde record at Lindenberg, Germany

Clouds substantially affect Earth's energy budget by their interactions with short/long-wave radiation, and small changes in cloud vertical structure (CVS, i.e., the locations of cloud base and top, the thickness and number of cloud layers) can fluctuate the warming effects of anthropogenic forcing. However, the knowledge regarding how the CVS changes over time is still poor owing to a lack of reliable and available datasets. Here, the long-term temporal variations in four-times-daily radiosonde-derived CVS at Lindenberg, Germany, from 1992 to 2020 are analyzed. Robust increasing trends in cloud height/thickness and overlap frequency are found during this three-decade period. Observational results show that the interannual variabilities of the cloud-top height, cloud-base height, and cloud thickness are consistently increasing, with linear trends of 137.75 ± 6.65 m yr−1, 45.73 ± 6.22 m yr−1, and 29.52 ± 3.53 m yr−1, respectively. The occurrence of multi-layer cloud generally increases with a trend of 1.57 ± 0.06% yr−1, whereas the percentages of single-layer cloud and cloudless conditions decrease with trends of −0.44 ± 0.05% yr−1 and −1.12 ± 0.07% yr−1, respectively. Continuous surface warming increases thermal instability, which raises cloud height, particularly for single-layer clouds and the lower layer of multi-layer clouds. The upper-level cloud generates and maintains itself as the upper water vapor and vertical velocity enlarge, thus increasing the cloud top height, total cloud thickness, and cloud overlap frequency. These findings shed new light on the long-term changes in cloud properties caused by climate change.

Impact of 3D cloud structures on the atmospheric trace gas products from UV–Vis sounders – Part 2: Impact on NO2 retrieval and mitigation strategies

Abstract. Operational retrievals of tropospheric trace gases from space-borne spectrometers are based on one-dimensional radiative transfer models. To minimize cloud effects, trace gas retrievals generally implement a simple cloud model based on radiometric cloud fraction estimates and photon path length corrections. The latter relies on measurements of the oxygen collision pair (O2–O2) absorption at 477 nm or on the oxygen A-band around 760 nm to determine an effective cloud height. In reality however, the impact of clouds is much more complex, involving unresolved sub-pixel clouds, scattering of clouds in neighbouring pixels, and cloud shadow effects, such that unresolved three-dimensional effects due to clouds may introduce significant biases in trace gas retrievals. Although clouds have significant effects on trace gas retrievals, the current cloud correction schemes are based on a simple cloud model, and the retrieved cloud parameters must be interpreted as effective values. Consequently, it is difficult to assess the accuracy of the cloud correction only based on analysis of the accuracy of the cloud retrievals, and this study focuses solely on the impact of the 3D cloud structures on the trace gas retrievals. In order to quantify this impact, we study NO2 as a trace gas example and apply standard retrieval methods including approximate cloud corrections to synthetic data generated by the state-of-the-art three-dimensional Monte Carlo radiative transfer model MYSTIC. A sensitivity study is performed for simulations including a box cloud, and the dependency on various parameters is investigated. The most significant bias is found for cloud shadow effects under polluted conditions. Biases depend strongly on cloud shadow fraction, NO2 profile, cloud optical thickness, solar zenith angle, and surface albedo. Several approaches to correct NO2 retrievals under cloud shadow conditions are explored. We find that air mass factors calculated using fitted surface albedo or corrected using the O2–O2 slant column density can partly mitigate cloud shadow effects. However, these approaches are limited to cloud-free pixels affected by surrounding clouds. A parameterization approach is presented based on relationships derived from the sensitivity study. This allows measurements to be identified for which the standard NO2 retrieval produces a significant bias and therefore provides a way to improve the current data flagging approach.

Effects of Different Types of Aerosols on Deep Convective Clouds and Anvil Cirrus

AbstractDeep convective clouds and associated anvils exert opposite radiative effects. The impact of different aerosol types on these two categories of clouds remains a major challenge in understanding aerosol‐cloud interactions. Using 11‐year satellite retrievals, we find that cloud top height (CTH) and ice cloud fraction of deep convective clouds and anvil cirrus identified by Cloud‐Aerosol Lidar with Orthogonal Polarization increase with small aerosol loadings and level off or even decrease with further aerosol increase. Compared with continental aerosols, CTH affected by marine aerosols starts to decrease at smaller aerosol loadings. Moreover, cloud optical depth (COD) of deep convective clouds decreases with aerosol loadings. COD of anvil cirrus increases with increased loadings of most aerosol types but decreases with smoke aerosol. These relationships are mainly attributed to the aerosol effect rather than the meteorological effects. Our findings contribute to the development of models and better assessment of aerosol‐cloud radiative forcing.

Variation and Influencing Factors of Cloud Characteristics over Qinghai Lake from 2006 to 2019

Clouds are an indispensable part of climate change, and the occurrence and development of clouds in the Qinghai Lake area (QHL) have great significance for the regional energy budget and precipitation system. To a certain extent, clouds will affect the water resources, agriculture, animal husbandry, and photovoltaic power industry in this region. In this study, we used CloudSat satellite data, combined with meteorological elements and atmospheric circulation, to analyze the cloud occurrence frequency and cloud water content in QHL. The results demonstrate that the frequency of cloud occurrences in QHL is 33% with a decreasing trend from 2006 to 2019. Altostratus and Nimbostratus are the main types of cloud systems in QHL. The cloud ice water content is 62.21 mg/m3 and the cloud liquid water content is 261.66 mg/m3. The highest value of the vertical cloud fraction occurs from March to June, at a height of 7–11 km in QHL. The height of the mixed-phase clouds is approximately 4–8 km and the ice clouds are above 8 km. The vertical distribution of ice particles is relatively dispersed, while the vertical distribution of liquid particles is relatively concentrated. The time and height of high particle effective radius and high particle concentration are consistent with the high value of cloud water content. The decrease in total cloud occurrence frequency in QHL is caused by the increase in temperature. This study helps to clarify the detailed structure of clouds and the distribution of cloud water resources, which has an important reference value for the study of climate change impact and the sustainable development of lake resources in QHL.

Impact of meteorological conditions on tropospheric ozone and associated with parameterization methods for quantitative assessment and monitoring

In recent years, the heavy ozone pollution events around the world have shown a sudden frequently increase, which has aroused widespread concern in the government and the public. It is well known that O3 is driven by photochemical reactions triggered by solar radiation (direct and indirect solar radiation), the O3 concentration calculated by chemical mechanism is mostly significantly lower than the actual O3 observation. Based on the study of the effect of meteorological conditions on the “additional increment” of O3 in three representative regions of Beijing, Hangzhou and Guangzhou from 2015 to 2020, an innovation diagnostic theory algorithm that the cross-cutting effects of atmospheric clouds on the chemical pattern of O3 solar radiation is established in this study. On this basis, a parametric evaluation method of O3 is established. The novelty of this study is 1) Comprehensive influence of the meteorological conditions and photochemical reactions mechanisms on the cross-cutting effects of O3 concentration are given. Especially low-level clouds in the troposphere, which have significantly large variable effects on the reflection and refraction of O3 through solar radiation. Theory quantitative algorithm of cloud scattering, cloud height, cloud volume and cloud structure changes, as well as feedback effects caused by water vapor condensation, which closely related to the transformation of O3 precursors are given. 2) Based on this, a parameterization method for quantitative O3 assessment and monitoring, which is a Parameterization for Linking Ozone pollution with Meteorological conditions. 3) Applying the theoretical algorithm and parameterization method of this study, comparing the changes of O3 in 2018 with 2019, an objective quantitative distinction between emission reduction and meteorological impact was made, showing that emission reduction still played a leading role, with a contribution rate of about 27%. This shows that the created quantitative algorithm of atmospheric cloud theory and the innovative parameterization method can provide an objective quantitative basis for O3 pollution decision-making and public emission reduction.

Global Distribution of Clouds over Six Years: A Review Using Multiple Sensors and Reanalysis Data

A six-year global study of cloud distribution and cloud properties obtained from observations of the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), the Atmospheric Infrared Sounder (AIRS), and the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) data is presented in this study. From the CALIPSO observations, the highest clouds for both daytime and night-time were found in the Inter Tropical Convergence Zone (ITCZ) region. The lowest cloud heights were found towards the poles due to the decrease in the tropopause height. Seasonal studies also revealed a high dominance of clouds in the 70 °S–80 °S (Antarctic) region in the June–July–August (JJA) season and a high dominance of Arctic clouds in the December–January–February (DJF) and September–October–November (SON) seasons. The coldest cloud top temperatures (CTT) were mostly observed over land in the ITCZ and the polar regions, while the warmest CTTs were mostly observed in the mid-latitudes and over the oceans. Regions with CTTs greater than 0 °C experienced less precipitation than regions with CTTs less than 0 °C.

Confidence and Error Analyses of the Radiosonde and Ka-Wavelength Cloud Radar for Detecting the Cloud Vertical Structure

A macro-vertical structure is closely related to weather evolution and the energy budget balance of the atmospheric system of the Earth. In this study, radiosonde data were used to identify a cloud vertical structure (CVS) using the adjusted relative humidity threshold method. To evaluate the reliability and stability of this method, the results obtained based on the spatiotemporal matching criteria established in this study were compared with Ka-band millimetre-wave cloud radar (MMCR) observation data. This comparison showed that both devices exhibit high consistency in low-level cloud detection. With the increase in the cloud height, the frequency of the cloud appearance detection by the radiosonde became higher than that by the MMCR. In spring, the results of the CVS detection by the two devices were in good agreement. Specifically, the determination coefficients of the modified degrees of freedom (adjusted R-square) of the cloud base height (CBH) and cloud top height (CTH) detected by the two devices were 0.934 and 0.879, respectively. The horizontal drift of the radiosonde was the smallest in summer, and the adj. R-square values of the CBH and CTH were 0.814 and 0.852, respectively. The CVS observation results by the radiosonde and the MMCR were significantly different in autumn (the adj. R-Square values of the CBH and CTH were 0.715 and 0.629, respectively). In winter, the adj. R-Square values of the CBH and CTH observed by the radiosonde and the MMCR were 0.958 and 0.710, respectively. The statistics and analysis of the results of the distribution characteristics of the CVSs using radiosonde data from 2019 to 2021 from Xi’an showed that the average CTH and CBH were at 7–10 km and 3–5 km, respectively. The frequencies of the cloud absence, rainfall, and two- and three-layer clouds were the highest in the winter (34.36%), autumn (12.99%), and summer, respectively.

Evaluating Statewide NAIP Photogrammetric Point Clouds for Operational Improvement of National Forest Inventory Estimates in Mixed Hardwood Forests of the Southeastern U.S.

The U.S. Forest Service, Forest Inventory and Analysis (FIA) program is tasked with making and reporting estimates of various forest attributes using a design-based network of permanent sampling plots. To make its estimates more precise, FIA uses a technique known as post-stratification to group plots into more homogenous classes, which helps lower variance when deriving population means. Currently FIA uses a nationally available map of tree canopy cover for post-stratification, which tends to work well for forest area estimates but less so for structural attributes like volume. Here we explore the use of new statewide digital aerial photogrammetric (DAP) point clouds developed from stereo imagery collected by the National Agricultural Imagery Program (NAIP) to improve these estimates in the southeastern mixed hardwood forests of Tennessee and Virginia, United States (U.S.). Our objectives are to 1. evaluate the relative quality of NAIP DAP point clouds using airborne LiDAR and FIA tree height measurements, and 2. assess the ability of NAIP digital height models (DHMs) to improve operational forest inventory estimates above the gains already achieved from FIA’s current post-stratification approach. Our results show the NAIP point clouds were moderately to strongly correlated with FIA field measured maximum tree heights (average Pearson’s r = 0.74) with a slight negative bias (−1.56 m) and an RMSE error of ~4.0 m. The NAIP point cloud heights were also more accurate for softwoods (R2s = 0.60–0.79) than hardwoods (R2s = 0.33–0.50) with an error structure that was consistent across multiple years of FIA measurements. Several factors served to degrade the relationship between the NAIP point clouds and FIA data, including a lack of 3D points in areas of advanced hardwood senescence, spurious height values in deep shadows and imprecision of FIA plot locations (which were estimated to be off the true locations by +/− 8 m). Using NAIP strata maps for post-stratification yielded forest volume estimates that were 31% more precise on average than estimates stratified with tree canopy cover data. Combining NAIP DHMs with forest type information from national map products helped improve stratification performance, especially for softwoods. The monetary value of using NAIP height maps to post-stratify FIA survey unit total volume estimates was USD 1.8 million vs. the costs of installing more field plots to achieve similar precision gains. Overall, our results show the benefit and growing feasibility of using NAIP point clouds to improve FIA’s operational forest inventory estimates.

Sensitivity Analysis of Ozone Profiles Retrieved from SCIAMACHY Limb Radiance Based on the Weighted Multiplicative Algebraic Reconstruction Technique

A detailed sensitivity analysis of ozone density profile retrieval was applied to scattering solar radiance spectra measured with the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) instrument aboard the ENVIronmental SATellite (ENVISAT). The vertical density distribution of ozone between 10 and 69 km was obtained using the weighted multiplicative algebraic reconstruction technique and the radiative transfer model for SCIAMACHY. This study investigates the error sources for the retrieved ozone profiles, which are relevant to explain the difference between two independent instruments. The numerical simulation method was adapted to quantify the impact of various error sources on the retrieval accuracy of ozone profiles. First, the tangent height (TH) registration was found to be the largest error source. Assuming an aerosol-free atmosphere, under the condition of background aerosol, the ozone profile showed a negative deviation of ~2–10% below 40 km. With an incorrect a priori profile, ozone estimates may result in a 5–10% average error at the upper and lower boundaries. The ozone retrieval error caused by the uncertainty of surface albedo, ozone absorption cross-section, temperature, pressure profile, and low clouds was relatively small. The random error caused by the disturbance of the measurement vector obeying a Gaussian distribution did not exceed 5%. Second, the estimation of various error sources for different solar zenith angles was investigated. The error sources most strongly dependent on SZAs were aerosols, surface albedo, and clouds. Finally, the error estimation of the ozone retrieval between the northern hemisphere (NH) and the southern hemisphere (SH) was investigated, revealing that there were no strong interhemispheric differences, except for cloud height. These results can be used for interpretation of instrumental comparisons and validation of SCIAMACHY ozone profiles retrieved from different algorithms in a rigorous manner.

Quantifying the Long-Term MODIS Cloud Regime Dependent Relationship between Aerosol Optical Depth and Cloud Properties over China

Aerosols modify cloud properties and influence the regional climate. The impacts of aerosols on clouds differ for various cloud types, but their long-term relationships have not been fully characterized on a cloud regime basis. In this study, we quantified the cloud regime-dependent relationship between aerosol optical depth (AOD) and cloud properties over China using Moderate-Resolution Imaging Spectroradiometer (MODIS) data from 2002 to 2019. Daily clouds in each 1° by 1° grid were categorized into seven cloud regimes based on the “k-means” clustering algorithm. Overall, the cloud height increased, the cloud thickness and liquid water path increased, and the total cloud cover decreased for all cloud regimes during the study period. Linear correlations between AOD and cloud properties were found within stratocumulus, deep convective, and high cloud regimes, showing consistency with the classic aerosol–cloud interaction paradigms. Using stepwise multivariable linear regression, we found that the meteorological factors dominated the variation of cloud top pressure, while AOD dominated the variation of total cloud cover for most cloud regimes. There are regional differences in the main meteorological factors affecting the cloud properties.

Highlighting the role of earth observation Sentinel5P TROPOMI in monitoring volcanic eruptions: a report on Hunga Tonga, a Submarine Volcano

ABSTRACT The present study utilized earth observation Sentinel5P TROPOMI (TROPOspheric Monitoring Instrument) data for monitoring submarine volcanic activities. The world has seen a sequence of abrupt volcanic eruptions within one-month duration i.e., on 20th December 2021, 13th January 2022 and 15th January 2022. This caused the emissions of natural gaseous pollutants such as Sulphur Dioxide (SO2), Hydrogen Sulphide (H2S) and ash particles. Atmospheric SO2, AAI (Absorbing Aerosol Index) and Cloud fraction data are retrieved from the TROPOMI onboard the Copernicus Sentinel5P European Space Agency satellite. Results confirmed the increased concentration of SO2 column density after 20th December, and it was observed to be 0.002 mol/m2, the highest concentration during the period of study. Generally, SO2 concentration stays within 0.001 mol/m2 or less. Concentration was seen increasing after the first eruption and reached maximum after 15th January 2022 eruption to a level up to 0.002 mol/m2. Similar outcomes were observed for AAI for the chosen site. AAI values increased to 25,000 fold (AAI values of 1.25) during the first eruption and increased to 29,000 fold on 15th January 2022 after eruptions (AAI values of 1.45) as compared AAI values of 0.005 or negative AAI values before eruptions. A cloud fraction of value 1 is observed during this time, along with the top most cloud height at 14,233.16 m (14.23 kms) above the crater of the volcano (maximum estimation limit by S5P). These values are higher as compared to isolated islands, as there are no other sources of emissions at surrounding environment. The outcomes support the role of Earth Observation datasets for disaster monitoring and management plans for mitigation.

Microphysical Analysis of Precipitation in the Central and Eastern Margins of the Tibetan Plateau

Through the observation and study of the raindrop spectrum, we can not only explore the evolution law of precipitation but also understand the microphysical characteristics of different types of precipitation clouds. This paper uses the raindrop spectrum data observed at Naqu Station, Yushu Station, Linzhi Station, and Emei Mount Station, as well as cloud radar data in the Yushu region in the Tibetan Plateau. Raindrop spectral characteristics are studied, and the raindrop size distribution (DSD) characteristics of the four stations are analyzed. The results are as follows: (1) The overall raindrop spectral concentration of the four stations decreases with the increase in particle size after the peak value. The downtrend is most gentle at the peak. (2) All rain intensity levels show the characteristics of multiple vertices. At Linzhi Station, Naqu Station and Yushu Station, the particles with a diameter of <1 mm contributed the most to the precipitation rate, while the particles with a diameter of <1 mm at Emei Mount Station contributed the least to the precipitation rate. (3) The precipitation in the central and eastern margins of the Tibetan Plateau is dominated by small and medium-sized particles, accounting for 95–99% of the precipitation particle number concentration. (4) The raindrop spectra of the three types of precipitation clouds at the four sites are all cumulonimbus precipitation Cumulonimbus in the uppermost layer, stratiform cloud precipitation stratiform cloud in the lowermost layer, and mixed cloud precipitation stratiform cloud in between. (5) Cloud radar analysis of precipitation structure shows that cumulonimbus and mixed clouds develop vigorously, and the highest cloud height can reach 13 km, but the average precipitation duration of mixed clouds is shorter than that of cumulonimbus; stratiform clouds develop relatively smoothly, with cloud heights of 6–7 km, the average precipitation duration is the shortest.

ICESAT-2 Lidar retrievals for a smoke and clouds case: estimates in the south america region

The present study aims to estimate the height of smoke aerosols and clouds from the Advanced Topographic Laser Altimeter System (ATLAS) instrument sensor onboard the Ice, Cloud and land Elevation Satellite-2 (ICESat-2). The study was conducted during the dry season on September 14th of 2020, when there was a large number spot of biomass burning fires and smoke aerosol layers over the Amazon and the South American region. Most often, the smoke plumes move with southward winds, along the east of the Andes. During this period occasionally polar cold fronts move from the south, meeting the smoke aerosol layers. Initially, daily images from the polar orbit satellites such as Terra, Aqua, NOAA and Suomi were used to identify the spatial location of smoke plumes and clouds over the region. Then, ICESat-2 tracks were analyzed to evaluate their presence in the study area. The results show that ICESat-2 data retrieval is able to estimate the height of the aerosol layer and the top of the cloud. Some tracks show clearly higher clouds, with tops reaching about 12-13 km, when there is the presence of a cold front or deep convective cumulonimbus. Over clear sky regions where smoke is observed, estimated heights from the lidar are on the order of 3-4 km. Local profiles of temperature obtained from radiosondes show inversion layers at similar heights as detected by the lidar sensor. These inversion layers seem to be associated with the warming effect of the absorbing biomass burning aerosols.

Altimetric observation of wave attenuation through the Antarctic marginal ice zone using ICESat-2

Abstract. The Antarctic marginal ice zone (MIZ) is a highly dynamic region where sea ice interacts with ocean surface waves generated in ice-free areas of the Southern Ocean. Improved large-scale (satellite-based) estimates of MIZ extent and variability are crucial for understanding atmosphere–ice–ocean interactions and biological processes and detection of change therein. Legacy methods for defining the MIZ are typically based on sea ice concentration thresholds and do not directly relate to the fundamental physical processes driving MIZ variability. To address this, new techniques have been developed to measure the spatial extent of significant wave height attenuation in sea ice from variations in Ice, Cloud and land Elevation Satellite-2 (ICESat-2) surface heights. The poleward wave penetration limit (boundary) is defined as the location where significant wave height attenuation equals the estimated error in significant wave height. Extensive automated and manual acceptance/rejection criteria are employed to ensure confidence in along-track wave penetration width estimates due to significant cloud contamination of ICESat-2 data or where wave attenuation is not observed. Analysis of 304 ICESat-2 tracks retrieved from four months of 2019 (February, May, September and December) reveals that sea-ice-concentration-derived MIZ width estimates are far narrower (by a factor of ∼ 7 on average) than those from the new technique presented here. These results suggest that indirect methods of MIZ estimation based on sea ice concentration are insufficient for representing physical processes that define the MIZ. Improved large-scale measurements of wave attenuation in the MIZ will play an important role in increasing our understanding of this complex sea ice zone.

Comparing tree structures derived among airborne, terrestrial and mobile LiDAR systems in urban parks

ABSTRACT Measuring tree structure using three-dimensional (3D) mapping tools such as light detection and ranging (LiDAR) remote sensing is needed to provide well-managed and designed green spaces. The metrics used to estimate tree structure could be different depending on which LiDAR systems are used. This may lead to confusion and reduce confidence when evaluating tree structures and their derived products, such as plant area index (PAI). Therefore, studies that can determine similarities among measurements derived from different LiDAR systems are needed. In this study, structural canopy metrics in airborne laser scanning (ALS), terrestrial laser scanning (TLS), and mobile laser scanning (MLS) were compared to seek consistencies among the three LiDAR systems. The specific objectives were to test whether the estimates made by the metrics differed depending on single or clustered trees and to test whether LiDAR-derived errors in the metrics are related to tree structures. Tree point clouds were manually classified into single and clustered trees. Heights-related metrics, Rumple Index, area, and PAI were calculated for comparison analysis. Root-mean-square error (RMSE), bias, and Pearson’s correlation coefficient (r) were calculated to evaluate the consistencies in each metric among the LiDAR systems. The results showed that the maximum height of the point clouds (ZMAX) and max and mean heights derived from the canopy height models (minCHM and maxCHM) demonstrated good consistency (RMSE% < 10%, Bias% < 10%, and r > 0.900). Moreover, the biases from the ZMAX- and CHM-derived metrics comparisons among the LiDAR systems did not show strong linear relationships with the tree heights and canopy complexities (i.e. Pearson’s correlation coefficient r < |0.29|). On the contrary, the 95th percentile (Zq95) height and mean z height (ZMEAN) differed depending on the tree classes and showed significant linear relations with canopy heights and complexity. The configurations of LiDAR systems, such as point density and sensing locations, seem to affect the Zq95, ZMEAN metrics, and PAI. Our results suggest that assessing for consistencies among the different LiDAR systems is required before using multiple LiDAR systems interchangeably to estimate the structure of urban park areas.

Satellites Suggest Rising Tropical High Cloud Altitude: 2002–2021

AbstractTropical upper‐troposphere clouds are expected to rise under global warming, contributing a positive radiative feedback. Here we show that Moderate Resolution Imaging Spectroradiometer (MODIS) retrievals over 2002–2021 from the Terra and Aqua satellites report a tropical‐mean high‐cloud altitude increase of 6.9 ± 2.7 m yr−1 (±2σ), while atmospheric models report 5.6 ± 3.0 m yr−1 over 1979–2014. During their common overlap period, however, the observed trend is greater than that of the models. The atmospheric models also show a tropically confined cloud‐height response to El Nino, whereas the observed cloud height response peak extends into the subtropics. Poleward of the mid‐latitudes, Aqua and Terra MODIS have cloud‐height drifts relative to each other, highlighting the need for deeper investigation of potential time‐dependent biases in MODIS cloud retrievals. Both sensors report significant tropical cloud height increases since 2002, which are statistically consistent with those simulated by climate models.

Floating particles mixing characteristics in an eccentric stirred tank coupled with dislocated fractal impellers

Abstract The mixing characteristics of floating particle dispersion process in an eccentric stirred tank with dislocated fractal impellers were investigated using computational fluid dynamics (CFD) and experimental analyses. Solid concentration distribution, axial solid concentration profile, cloud height, solid integrated velocity, power consumption and just drawdown speed were investigated. Results showed that dislocated fractal impeller can enhance solid integrated velocity and fluid turbulent fluctuation intensity compared with dislocated pitched blade impeller, and eccentric agitation coupled with dislocated fractal impeller could destroy the typical circulation loops and symmetric flow field and improve the axial circulation efficiency of floating particles on the basis of dislocated fractal impeller. Eccentric agitation coupled with dislocated fractal impeller could further enhance the floating particle dispersion homogeneity (MI) and decrease the just drawdown speed (N jd) on the basis of dislocated fractal impeller and dislocated pitched blade impeller at the specific power consumption. Meanwhile, eccentric ratio of 0.3 or 0.4 was optimal for the floating particle mixing process in this work.