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ABSTRACT In this study, a new type of deicing salt was prepared to overcome the disadvantages of using traditional chlorine deicing salts. As the main component of deicing salt with [...]

This study examines the differences related to microphysical properties of ice in thunderstorms over the Amazon and Congo Basin using the Precipitation Feature (PF) data sets derived from passive microwave and radar observations from the Tropical Rainfall Measuring Mission and Global Precipitation Mission Core Satellites. Analysis reveals that Amazon thunderstorms are likely composed of ice crystals smaller but more numerous than those in the Congo Basin, resulting in half as many flashes per PF on average in the Amazon, for similar Ice Water Content (IWC) or Area of 30 dBZ at −10°C (Acharge). The increase of the flash count following an increase of the IWC (Acharge) is only 72% (61%) as effective in the Amazon as it would be in the Congo Basin area. PFs with similar 30 dBZ radar echo top heights exhibit lower Brightness Temperatures (TBs) in the 85/89, 165, and 183 GHz frequencies over the Amazon, indicating more numerous smaller ice particles compared to those over the Congo Basin, which tend to show colder TBs at 37 GHz, possibly due to more numerous large graupel or hail particles. Comparisons of TBs in PFs with similar 30 dBZ echo top temperature between the Amazon and 3 × 3º global grids show that the median TB in Amazon is higher than that in most oceanic areas but is comparable to areas having high oceanic lightning activity (e.g., South Pacific Convergence Zone). It suggests that systems in the Amazon have similarities with maritime precipitation systems, yet with distinct characteristics indicative of land systems. A comparison is made between Amazon (AM) and Congo Basin (CB) thunderstorms with similar reflectivity values seen by either TRMM or GPM, versus other variables that can help us understand the ice microphysics of these storms (IWC, area of 30 dBZ at −10C, Flash count, TBs). The radar reflectivity being driven by number and size (to the sixth power) of hydrometeors, the hypothesis is that for two storms with a same reflectivity value, one in AM and one in CB, the reflectivity value measured is driven by a higher concentration of large ice particles in CB (i.e., driven by size), while it is driven by a higher concentration of smaller ice particles in AM (i.e., driven by number). We quantify the lightning count difference between the two areas as a function of the amount of ice in the thunderstorm. It shows that AM produces significantly less lightning than CB on average for a similar ice content. Radiometers from TRMM and GPM are then used to compare the median TBs observed in the Amazon with the rest of the globe, to emphasize once again that AM is producing systems that are neither of land nor oceanic nature, but somewhere in the middle. Amazonian systems are principally composed of smaller and more numerous ice crystalsIncreasing the Ice Water Content (IWC) and/or core size of thunderstorms in the Amazon demonstrates lower effectiveness in boosting lightning activityAmazonian systems present brightness temperatures unlike land or oceans but similar to oceanic regions with greater lightning activity Amazonian systems are principally composed of smaller and more numerous ice crystals Increasing the Ice Water Content (IWC) and/or core size of thunderstorms in the Amazon demonstrates lower effectiveness in boosting lightning activity Amazonian systems present brightness temperatures unlike land or oceans but similar to oceanic regions with greater lightning activity

A 16‐year Tropical Rainfall Measuring Mission convective feature (CF) data set and ERA‐Interim reanalysis data are used to examine the nonlinear relationships between thermodynamic environments and the probability of high‐flash rate thunderstorms. First, Bayesian‐like probability functions are established between preselected ERA‐Interim thermodynamic variables and the high‐flash rate CFs. Then, the global geographical distribution of high‐flash rate thunderstorms is validated by applying these functions to the reanalysis data. The results suggest that a sole environmental factor has limited skill to estimate the probability of these events. The combination of four variables, including Convective Available Potential Energy, convection inhibition, low‐level shear, and warm cloud depth, may be used to derive a geographical distribution of high‐flash rate events that is close to the observations. The strong land‐ocean contrast in the frequency of high‐flash rate thunderstorms and some hot spot regions can be closely reproduced based only on these four variables from the reanalysis data. This indicates that the land‐ocean contrast in the occurrence of high‐flash rate thunderstorms can be largely interpreted by the fundamental differences between the thermodynamic conditions over land and ocean. Sole environmental factor has limited skill to estimate the probability of high‐flash rate thunderstormsA combination of four variables can be used to derive a geographical distribution of high‐flash rate events by a Bayesian‐like approachThe strong land‐ocean contrast in the frequency of high‐flash rate thunderstorms can be closely reproduced from the reanalysis data

Mineralized polymeric cryogels with interconnective macroporous structure have demonstrated their potential as promising scaffolding material in bone tissue engineering. However, their capability in inducing osteogenic differentiation of mesenchymal stem cells (MSCs) in vitroand osteogenesis in vivohas not been explored yet. In this work, the roles of the mineralized cryogel on osteogenesis are systematically studied. Mineralized macroporous poly(ethylene glycol)-co-2-hydroxyethyl methacrylate cryogel promotes osteogenic differentiation of rat MSCs, particularly in upregulating the activity of alkaline phosphatase (ALP, ∼5.7-folds) and expression of related osteogenic gene markers (ALP ∼16-folds, osteocalcin ∼133-folds) at 14 days. In vivoimplantation reveals that mineralized cryogels could promote fast osteogenesis and angiogenesis in critical-sized cranial bone defect of a Sprague-Dawley rat model in 4 weeks. The adsorption, entrapment, and concentration of osteogenic growth factors (bone morphogenetic protein 2) and angiogenesis growth factor (vascular endothelial growth factor [VEGF]) in the matrices in vivomay possibly participate in the process of osteogenesis and angiogenesis. Notably, the adsorption of larger amount of VEGF in nonmineralized cryogels facilitates obvious angiogenesis and comparable osteogenesis in bone defect in 8 weeks.Graphical abstractImpact StatementThe current work reported the fabrication and characterization of a biomimicking mineralized polymeric cryogel as scaffolding material in bone regeneration. In addition to its three dimensional porous structure and the osteogenic potential, this biomimicking scaffold was also found to enhance the adsorption of biochemical cues, which in turn greatly promoted the angiogenesis as well as the tissue regeneration.

Four years (April 2014 to March 2018) of Global Precipitation Measurement (GPM) Precipitation Features data along with colocated the Modern Era Retrospective‐Analysis for Research and Applications‐2 model data are used to identify Freezing Rain Features (FRFs). A Precipitation Feature with presence of both melting layer (maximum temperature of the vertical column > 4 °C) and a layer of subfreezing air (2‐m temperature < 0 °C) adjacent to the surface is considered an FRF. During 4 years of observations, GPM and Modern Era Retrospective‐Analysis for Research and Applications‐2 identify approximately 3,096 FRFs globally (65°S–65°N). Most of them are observed over Northern Hemispheric land in the winter season. The majority of FRFs originates through the “melting process,” whereas only 35 features are associated with “warm rain” process. The locations and seasonal and diurnal distribution patterns of the FRFs over the United States are well matched with the ground‐based observations. The ground‐based observations verify approximately 70% of the FRFs over the United States. Ku‐band radar properties show that FRFs are found shallower (2–5 km) and less intense (<27 dBZ) than precipitation features in general but deeper and more intense than Snow Features. Passive microwave properties show that FRFs Tbs and Polarization‐Corrected Temperature are warmer than Snow Features at all GPM Microwave Imager channels with the largest differences in 166 GHz. The enhancement in Tbs are more distinct with warm rain FRFs. FRF Tb tends to decrease as echo top height increases at all GPM Microwave Imager channels except for 183 GHz, where Tbs have lack of dependence on echo top height. GPM Ku‐band radar and MERRA‐2 reanalysis data are used to identify Freezing Rain eventsRadar and Passive microwave properties of freezing rain events are summarizedPassive microwave properties show that FRFs Tbs and PCTs are warmer than SFs at all GMI channels

A longstanding question for scientists has been whether or not any observable trends or shifts in global lightning activity have occurred since the Industrial Revolution. This study utilized over 8,000 certified ground‐based stations over a 43‐year period, as well as 16 years of Tropical Rainfall Measuring Mission (TRMM) Lightning Imaging Sensor (LIS) data, to provide a better understanding of the processes behind these trends. Ground station results show that many global regions have observed significant increases or decreases in thunder day occurrence. The Amazon, Maritime Continent, India, Congo, Central America, and Argentina display increases in annual thunder days since the 1970s, whereas China, Australia, and the Sahel among others observe decreases in the number of thunder days. The corresponding change in lightning flash density from the TRMM‐LIS, as well as the number of thunderstorm features and lightning flashes per thunderstorm feature, is compared to the thunder day trends during the TRMM lifespan. Results show a positive correlation between the changes of thunder day occurrence and flash density over most regions of the TRMM domain, including the Maritime Continent, China, South Africa, and Argentina. However, there are several regions with disagreements between the flash density and thunder day trends, such as India and Western Africa. The disagreements are related to the changes in the number of flashes per thunderstorm, which suggest other reasons to interpret the long term trends in thunder day occurrence over various regions. Understanding these regional trends in lightning activity is important in understanding the changes of precipitation systems under a varying climate. Global and regional long‐term trends in thunder days are determined at ground stationsLargely positive correlations are observed between the simultaneous thunder‐day and TRMM‐LIS lightning flash density trends throughout the tropics and subtropicsRegions of disagreement in the relationship between trends in thunder days and flash density, all have negative or no correlation between the number of thunderstorms and the number of flashes/LPF

Six‐years (2010–2015) of snow lightningcharacteristics and climatology, including seasonal, diurnal, and surface temperature distribution, are generated. The World Wide Lightning Location Network (WWLLN) and the National Lightning Detection Network lightning observations are collocated with Modern‐Era Retrospective Analysis for Research and Application (MERRA‐2) temperatures. Cold season lightning events are identified as lightning with the MERRA‐2 two‐meter surface temperature colder than 0 °C and then further classified as snow lightningor thundersnow, when the entire vertical temperature profile is below 2 °C, and as freezing rain lightning when there is a temperature warmer than 2 °C somewhere in the column above the freezing surface. The statistics of snow lightning events from WWLLN and National Lightning Detection Network are well matched and are consistent with the climatology of thundersnow days reported at ground‐based stations over the United States. Using 4 years of observations from the Global Precipitation Measuring Mission Ku band radar, 443 Thunder Snow Features (TSFs) are defined, having a contiguous area of nonzero near surface snow precipitation derived from the Ku band radar and MERRA‐2 data, along with collocated WWLLN lightning flashes. The majority (about 394) are found over high mountainous regions such the Himalayas, Tibet, the Andes, and the Zagros mountain regions. Low‐elevation TSFs (45) are observed over the continental and coastal regions. Though only a small number of TSFs are identified with 4 years of Global Precipitation Mission data, most TSFs have maximum radar reflectivity above 30 dBZ at temperature colder than −10 °C, which indicates the importance of the noninductive charging process in these events. Snow lightning characteristics and climatology are generated over the United StatesThe geographical distributions of thundersnow systems observed by the GPM satellite are mapped globallyThe Ku band radar characteristics of global thundersnow snow features are summarized

The satellite‐constellation passive‐microwave Brightness Temperature (TB) observations, with global coverage, and more additions from upcoming CubeSats, have been mainly used in surface precipitation retrievals. However, these observations can also be used to indicate the intensity of convective systems. This study attempts to relate Global Precipitation Mission (GPM) Microwave Imager (GMI) TBs to Geostationary Lightning Mapper (GLM) lightning flashes by using 4 years (02/2018–04/2022) of GPM Precipitation Feature (PF) database. GMI TBs are collocated to the GLM lightning counts, and to the ERA5 reanalysis 2‐m air temperature in PFs. Three Artificial Intelligent Neural Network Models (AI‐NN) are trained to classify PFs producing lightning in a 20‐min window respectively for land, ocean, or coast. The flash rate of the determined Lightning producing PFs (LPFs) is then quantified by three other AI‐NNs, each trained for one of the three regions. Though the models clearly capture the global geographical distribution of LPFs with a Probability Of Detection over 90%, high False Alarm Rates are found, ranging from 49.9% over land to 91.5% over the ocean. The importance of TB at each passive microwave channel varies regionally, corresponding to the different microphysical properties in various types of precipitation systems. The global lightning distribution is derived by applying the AI models to global PFs and is well compared to the lightning climatology from Lightning Imaging Sensor and Optical Transient Detector. This suggests that the use of passive microwave TBs can help to fill the gaps in lightning monitoring thanks to their global coverage. We are taking advantage of the indirect relationship between brightness temperatures (TBs) (from GPM‐GMI core satellite) and lightning rate (from GOES‐GLM) (i.e., low TBs ∼ lightning vs. high TBs ∼ non‐lightning) to build a set of AI Shallow Neural Networks. The goal of the study is to find the extent to which TBs alone can determine the flash rate in a 20‐min window (10‐min before and after) surrounding the measurement of the TBs of a Precipitation Feature (PF). First, models are trained to classify Lightning PFs (LPFs) versus non‐Lightning PFs (nLPFs) and next, models are trained to quantify the flash count (regression). Models are trained in the GLM domain (American continents + surrounding oceans) and then tested globally. Results show that TBs allow a lightning determination and quantification to some extent, but produces high false alarm rates (i.e., ∼50% for land to ∼90% for ocean) due to limitations resulting from the indirect relationship between lightning and TBs (i.e., the limit between LPFs and nLPFs is not clear enough for the models to do better). Global application of the models show similar results to literature lightning climatologies, showing that AI can pick most areal information. This work fits the recent emergence of passive‐microwave only CubeSats. Classification and regression AI shallow neural network models are built using GPM‐MI brightness temperature to predict lightningAI models can accurately determine extremes but brightness temperatures lack information to differentiate lightning in weaker systemsA global lightning climatology is derived from the models' results and shows similar results to satellite derived climatology Classification and regression AI shallow neural network models are built using GPM‐MI brightness temperature to predict lightning AI models can accurately determine extremes but brightness temperatures lack information to differentiate lightning in weaker systems A global lightning climatology is derived from the models' results and shows similar results to satellite derived climatology

The Peterson et al. (2015, https://doi.org/10.1175/JTECH-D-14-00119.1) passive microwave electric field retrieval is applied to 15 years of Tropical Rainfall Measuring Mission (TRMM) satellite observations to estimate the amount of Wilson current supplied to the Global Electric Circuit from individual electrified cloud features (ECFs), which are identified as contiguous precipitating cloud regions that produce Wilson current. Current contributions from 37 million ECFs sampled by TRMM are used to examine the composition of the DC generator current. Thunderstorms are found to supply 61% of the total retrieved current, while electrified shower clouds provide the remaining 39%. ECFs over land contribute 38% of the total current, while the ocean contributions are divided between coastal oceanic regions (35%) and the open ocean (27%). The greatest share of the total TRMM‐retrieved current comes large mesoscale features (>2 × 103km2in area) and features that have peak 20‐km electric fields in excess of 1 kVm−1. This combination of extent and intensity leads to total currents greater than 10 A for a single ECF. The ranking of the tropical chimney regions by total current production is (1) the Americas (38%), (2) Asia (32%), and (3) Africa (15%). ECFs over the tropical Pacific Ocean contribute the remaining 15%. The Africa chimney is most prominent in total lightning activity but lags behind the others in total DC current due to a reduced frequency of electrified weather and weaker per‐storm electric fields and Wilson currents compared to the other chimneys. Tropical Rainfall Measuring Mission satellite observations are used to estimate the amount of current each tropical electrified cloud provides to the Global Electric Circuit. Collecting these estimates more than a decade makes it possible to quantify the importance of various cloud types and the distinct “chimney” regions for the global circuit. The majority of the global generator current is supplied by thunderstorms (61%), while electrified shower clouds that do not produce lightning provide the remaining current (39%). Most of this current comes from large mesoscale storms that have electric fields at 20‐km altitude greater than 1 kVm−1 and individual current contributions exceeding 1 A. Of the three tropical chimney regions—the Americas, Africa, and Asia—Africa produced the most lightning, but the least current. This is because there are few electrified shower clouds in Africa compared to the Americas and Asia, and Africa thunderstorms appear to generate weaker electric fields and Wilson currents than their American and Asian counterparts. Electrified cloud satellite features are used to quantify individual current contributions to the Global Electric CircuitThunderstorms contribute 61% of the total current, while electrified shower clouds provide the remaining 39%Tropical chimney Wilson current production is ranked: (1) the Americas, (2) Asia, and (3) Africa in contrast to Africa's lightning dominance

Evolution of precipitation structures are simulated and compared with radar observations for the November Madden‐Julian Oscillation (MJO) event during the DYNAmics of the MJO (DYNAMO) field campaign. Three ground‐based, ship‐borne, and spaceborne precipitation radars and three cloud‐resolving models (CRMs) driven by observed large‐scale forcing are used to study precipitation structures at different locations over the central equatorial Indian Ocean. Convective strength is represented by 0‐dBZ echo‐top heights, and convective organization by contiguous 17‐dBZ areas. The multi‐radar and multi‐model framework allows for more stringent model validations. The emphasis is on testing models' ability to simulate subtle differences observed at different radar sites when the MJO event passed through. The results show that CRMs forced by site‐specific large‐scale forcing can reproduce not only common features in cloud populations but also subtle variations observed by different radars. The comparisons also revealed common deficiencies in CRM simulations where they underestimate radar echo‐top heights for the strongest convection within large, organized precipitation features. Cross validations with multiple radars and models also enable quantitative comparisons in CRM sensitivity studies using different large‐scale forcing, microphysical schemes and parameters, resolutions, and domain sizes. In terms of radar echo‐top height temporal variations, many model sensitivity tests have better correlations than radar/model comparisons, indicating robustness in model performance on this aspect. It is further shown that well‐validated model simulations could be used to constrain uncertainties in observed echo‐top heights when the low‐resolution surveillance scanning strategy is used. Multiradar observations allow stringent multimodel comparisons and validation for precipitation structures during an MJO event in the Indian OceanCloud‐resolving models constrained by site‐specific‐observed large‐scale forcing can reproduce temporal and spatial variations of radar echo‐top heightsThe multiradar, multimodel framework also benefits quantitative sensitivity studies to highlight common model strength and weakness

Understanding the impact of deep convection on the thermodynamic structure of the tropical upper troposphere and lower stratosphere (UTLS) is vital because convection and temperatures play an important role in regulating stratospheric water vapor through direct convective injection and in enhancing the presence of thin cirrus clouds, both of which play a significant role in the climate. This study quantifies the UTLS vertical temperature structure changes near deep convection over the Pacific Warm Pool and the Tropical Atlantic Continental and Oceanic region. The deep convection observed from the Tropical Rainfall Measuring Mission satellite are collocated with high vertical resolution temperature profiles from the COSMIC GPS Radio Occultation satellites along with ERA‐Interim reanalysis from 2007 to 2011. COSMIC and ERA‐Interim observe warm temperature anomalies (0.2 to 0.8 K) within 10–14 km, then transitioning to a layer of cool anomalies (−0.4 to −1.5 K) within 14–17 km. Above the cold‐point tropopause, warm anomalies (<1 K) are observed for oceanic convection, whereas cool anomalies are displayed for land convection within 17–20 km. The amplitude of temperature anomalies increases for deeper convection, marked by higher 20 dBZ radar echo top heights or colder infrared cloud top temperatures. COSMIC also observes enhanced UTLS diurnal temperature variations of about 0.2–0.3 K in both regions near deep convection. ERA‐Interim shows generally good agreement with COSMIC on the UTLS temperature anomalies near deep convection but displays larger differences above the tropopause, especially near land convection. Deep convection produces warm anomalies from 10–14 km, stronger cooling between 14–17 km, and a mix of warming/cooling between 17–20 kmDeep convection enhances the amplitude of diurnal temperature anomalies in the upper troposphere/lower stratosphere by 0.1–0.3 KTemperature anomalies are stronger near deeper convection with significant anomaly differences when comparing land and ocean convection

In the early 1900s, J. W. Whipple began to validate C. T. R. Wilson's global electric circuit (GEC) hypothesis by correlating the diurnal variation of global thunder days with the diurnal variation of the fair weather electric field measured by the Carnegie Cruise. This study applies 16+ years of precipitation feature (PF) data from the Tropical Rainfall Measuring Mission, including lightning data from the Lightning Imaging Sensor, alongside 12 years of electric field measurements from Vostok, Antarctica, to further examine this relationship. Joint diurnal‐seasonal variations of the electric field are introduced and compared with a variety of PF parameters that are potentially related to the GEC. All tested PF parameters showed significant correlations to the electric field on the joint seasonal‐diurnal timescale, with the flash rate and volume of 30 dBZ between the −5°C and −35°C isotherms showing the best linear correlations with R2values of 0.67 and 0.62, respectively. Furthermore, these relationships are analyzed during the two different phases of the El Niño–Southern Oscillation. Results show different seasonal‐diurnal variations of the electric field during El Niño and La Niña periods, with enhancements in the electric field between the months of January through April at 16–24 UTC in La Niña years. A similar trend is shown in global PF parameters, indicating relationships between the variations seen in the fair weather electric field and the variations of global PFs at diurnal, seasonal, and interannual timescales. This provides further evidence that PFs around the globe have a direct connection to the GEC. Determines the TRMM electrified cloud parameters that have the best joint seasonal‐diurnal correlation to the global electric circuitFinds the differences in the measured GEC between the two ENSO phases. Distinct differences can be seen in the GEC between the two phasesDetermined that similar patterns of seasonal‐diurnal variation as the GEC can be seen in the TRMM parameters during the two phases of ENSO

Trends of tropical (30°N–30°S) mean daytime and nighttime outgoing longwave radiations (OLRs) from the Clouds and Earth's Radiant Energy System (CERES) and the Atmospheric Infrared Sounder (AIRS) are analyzed using data from 2003 to 2013. Both the daytime and nighttime OLRs from these instruments show decreasing trends because of El Niño conditions early in the period and La Niña conditions at the end. However, the daytime and nighttime OLRs decrease at different rates with the OLR decreasing faster during daytime than nighttime. The daytime‐nighttime OLR trend is consistent across CERES Terra, Aqua observations, and computed OLR based upon AIRS and Moderate‐Resolution Imaging Spectroradiometer (MODIS) retrievals. To understand the cause of the differing decreasing rates of daytime and nighttime OLRs, high cloud fraction and effective temperature are examined using cloud retrievals from MODIS and AIRS. Unlike the very consistent OLR trends between CERES and AIRS, the trends in cloud properties are not as consistent, which are likely due to the different cloud retrieval methods used. When MODIS and AIRS cloud properties are used to compute OLR, the daytime and nighttime OLR trends based upon MODIS cloud properties are approximately half as large as the trends from AIRS cloud properties, but their daytime‐nighttime OLR trends are in agreement. This demonstrates that though the current cloud retrieval algorithms lack the accuracy to pinpoint the changes of daytime and nighttime clouds in the tropics, they do provide a radiatively consistent view for daytime and nighttime OLR changes. The causes for the larger decreasing daytime OLR trend than that for nighttime OLR are not clear and further studies are needed. In this study, trends of tropical (30°N–30°S) mean daytime and nighttime outgoing longwave radiations (OLRs) from the Clouds and Earth's Radiant Energy System (CERES) and the Atmospheric Infrared Sounder (AIRS) instruments are analyzed using data from January 2003 to December 2013. Both the daytime and the nighttime OLR data records from these instruments show decreasing trends owing to the occurrence of El Niño conditions early in the period and La Niña conditions at the end. However, the daytime and nighttime OLRs decrease at different rates with the daytime OLR decreasing faster than the nighttime OLR. The daytime‐nighttime OLR trend is consistent across CERES Terra, Aqua observations, and computed OLR based upon AIRS and MODIS retrievals. Cloud retrievals from multiple satellite sensors are examined to understand the cause of the changes in OLR. Tropical mean daytime and nighttime OLR show consistent decreasing trends between 2003 and 2013 from different data sets due to ENSO eventsAll data sets show that the daytime OLR decreases faster than that of the nighttime during this time periodCloud properties from different sensors are examined to understand the cause of the faster decreasing daytime trend than nighttime trend

Optical lightning sensors like the Optical Transient Detector and Lightning Imaging Sensor (LIS) measure total lightning across large swaths of the globe with high detection efficiency. With two upcoming missions that employ these sensors—LIS on the International Space Station and the Geostationary Lightning Mapper on the GOES‐R satellite—there has been increased interest in what these measurements can reveal about lightning and thunderstorms in addition to total flash activity. Optical lightning imagers are capable of observing the characteristics of individual flashes that include their sizes, durations, and radiative energies. However, it is important to exercise caution when interpreting trends in optical flash measurements because they can be affected by the scene. This study uses coincident measurements from the Tropical Rainfall Measuring Mission (TRMM) satellite to examine the properties of LIS flashes and the surrounding cloud regions they illuminate. These combined measurements are used to assess to what extent optical flash characteristics can be used to make inferences about flash structure and energetics. Clouds illuminated by lightning over land and ocean regions that are otherwise similar based on TRMM measurements are identified. Even when LIS flashes occur in similar clouds and background radiances, oceanic flashes are still shown to be larger, brighter, longer lasting, more prone to horizontal propagation, and to contain more groups than their land‐based counterparts. This suggests that the optical trends noted in literature are not entirely the result of radiative transfer effects but rather stem from physical differences in the flashes. Why do lightning flashes illuminate the clouds in the way they do? Some flashes produce bright stationary optical pulses that illuminate a large fraction of the storm. Others are dim and move around in the cloud as they evolve. The Lightning Imaging Sensor (LIS) onboard the Tropical Rainfall Measuring Mission (TRMM) satellite surveyed lightning flashes of all shapes, sizes, and radiances across the tropics. Because LIS is an optical imager, however, it is unclear to what extent the observed characteristics of LIS flashes are influenced by scattering in the surrounding cloud. Fortunately, the TRMM sensor package includes a variety of instruments for characterizing the lightning‐producing storm. These include a Visible and Infrared Scanner (VIRS), Microwave Imager (TMI), and Precipitation Radar (PR). This study integrates data from these instruments with LIS to construct a database of cloud regions that are illuminated by lightning. This Illuminated Cloud Feature (ICF) database allows the optical energy from lightning that is observed by LIS to be related to the radar structure and microphysics of the parent thunderstorm. The ICF database is used to identify exotic types of lightning and to show that oceanic lightning flashes are more radiant than flashes over land even when they occur in similar clouds. Optical lightning measurements can be used to identify propagating flashesFlash characteristics are sensitive to cloud properties that affect scatteringOceanic flashes are still larger and more energetic when they occur in similar cloud regions as their land‐based counterparts

To characterize and quantify tropopause‐reaching deep convection, 1 year of Global Precipitation Mission (GPM) Ku band radar echoes are surveyed in relation to several reference levels derived from the ERA‐Interim reanalysis data set. Consistent with the observations of the Tropical Rainfall Measuring Mission over the tropics, the GPM has detected tropopause‐reaching deep convection dominantly over tropical land, especially over Panama and Central Africa. At middle and high latitudes, tropopause‐reaching convective storms are mainly found over land in the Northern Hemisphere during the summer. Compared to those in the tropics, convective cores at middle and high latitudes have relatively larger sizes at the tropopause, especially those over central North America. The zonal distributions of the occurrences of 15 dBZ and 20 dBZ radar echoes at the tropopause show two comparable maxima, one in the tropics and the other in northern middle‐high latitudes. This implies that the convection penetrating the tropopause at northern middle‐high latitudes is as frequent as those over the tropics. It is important to understand their role in the vertical transport of trace gases between the troposphere and the stratosphere. GPM shows a geographical distribution of convection reaching tropopause in tropics similar to that from TRMMConvection frequently reaches above tropopause over northern middle‐high latitudes land in summerOvershooting deep convection at middle‐high latitudes has bigger area near the tropopause than those in tropics

The real driving emission test using a portable emission measurement system is the advanced solution to assess NOx emissions from heavy-duty vehicles in recent years. To reflect the NOx emissions of heavy-duty vehicles more realistically, the restrictions on driving conditions will likely be relaxed in the next emission standard for heavy-duty vehicles. In this study, several tests with different payloads were conducted on a China VI heavy-duty vehicle under two different driving conditions. The test results show that some NOx emissions “spikes” may occur in any driving type during the tests of heavy-duty vehicles, and they are mainly related to the NOx conversion efficiency of the SCR system. In general, there is no obvious relevance between the NOx emission rate and the driving type, but the increase of the vehicle speed is beneficial to maintain the temperature of the SCR system in the high-efficiency zone, thus reducing the NOx emission rate. The variation of driving conditions will cause a change in the valid windows of the test, which will lead to a change in the evaluation results of NOx emission compliance. Adding motorway driving to the test route significantly increases the power threshold of the valid windows and reduces specific NOx emissions of the valid windows, with a minimum reduction of more than 30% and a maximum reduction of nearly 50% for “SENOx-90” in this study. The variation in driving conditions can severely affect the true NOx emissions assessment, especially for low-payload tests. In this study, the difference in NOx emissions assessed due to variation in driving conditions reached 1/3 of the total NOx emissions and the difference will gradually decrease as the vehicle load increases.

By grouping the contiguous precipitating area detected by the precipitation radar on board the Global Precipitation Mission (GPM) core satellite, snapshots of precipitation systems are summarized as precipitation features (PFs), and their properties are cataloged from 1 year GPM observations. These PFs are categorized by their area and depth and convective intensity based on the 20 and 40 dBZ radar echo tops, respectively. The largest PFs are found mainly over ocean at the mid‐high latitudes, especially over southern ocean. The deepest PFs are mainly over tropical land, the West Pacific Warm Pool, and the Great Plains of the United States and Argentina. The most convectively intense PFs are dominant over land regions, including midlatitude and high latitude. The zonal precipitation contribution from extremely large precipitation systems is greater in midlatitude and high latitude than in the tropics. These extreme precipitation systems are rare but contribute significantly to the global precipitation. It is important to include their impacts in global climate models to correctly describe the global water cycle. Largest, deepest, and strongest storms are shown with spaceborne radarExtreme events are rare but important in global water cycle

This study uses a 16‐yr Tropical Rainfall Measuring Mission (TRMM) Convective Features (CFs) and ERA‐Interim reanalysis data to investigate the relative importance of four large‐scale environmental variables to thunderstorms with random forest models. These four variables include Convective Available Potential Energy (CAPE), Convective Inhibition (CIN), low‐level wind shear, and warm cloud depth (WCD). First, these selected four environmental variables show a distinguished difference between CFs with and without lightning flashes. Specifically, CFs with at least one flash have higher CAPE, CIN, and lower WCD than those without lightning. Then, using these four variables, the geographical distribution of thunderstorms, especially the land‐ocean contrast in the occurrence of thunderstorms, is closely reproduced with a global random forest model. Such results suggest that a random forest model with key large‐scale environmental variables can be a useful tool to estimate the occurrence of global lightning thunderstorms. The study also investigates the relative importance of the selected variables to the occurrence of thunderstorms regionally. Relatively higher skill scores in the regional random forest model than the global one indicate the variation of roles of large scale environment variables over different regions. Though the data‐driven models can be utilized to estimate the occurrence of global thunderstorms, how to link the regional relative importance of these variable to the physical processes of thunderstorms needs further investigation. The geographical distribution of thunderstorms is closely reproduced by a global random forest modelThe regional and global random forest models can be used to investigate the relative importance of different large‐scale variables for thunderstorm over different regionsConvective available potential energy, convective inhibition, and warm cloud depth are confirmed as important variables to parameterize convective intensity at the sub‐grid scale in climate model The geographical distribution of thunderstorms is closely reproduced by a global random forest model The regional and global random forest models can be used to investigate the relative importance of different large‐scale variables for thunderstorm over different regions Convective available potential energy, convective inhibition, and warm cloud depth are confirmed as important variables to parameterize convective intensity at the sub‐grid scale in climate model

This study applies new satellite datasets and methodologies to build on previous research exploring the physical relationship between lightning and precipitation in mid‐/high latitudes. Specifically, 3 years of Geostationary Lightning Mapper and Global Precipitation Measurement Mission core satellite coincident observations are examined to investigate relationships between lightning flash rate and microwave characteristics of convective precipitation features (cPFs) over the Americas and surrounding oceans between ±50° latitude. Mid‐/high latitude cPFs with lightning are characterized by colder temperatures of maximum 30 dBz echo top height and a smaller range of microwave brightness temperatures when compared to the tropics. Brightness temperature characteristics of electrically active cPFs are highly correlated to radar‐diagnosed ice mass and largely insensitive to synoptic‐scale proxies for convective strength and organization. Low flash density cPFs tend to be more sensitive to synoptic‐scale instability and shear than high flash density cPFs. Regional differences in the environmental forcing and characteristics of electrically active cPFs are shown. For example, the elevated terrain surrounding the Amazon River Basin is characterized by stronger vertical updrafts indicated by higher values of normalized CAPE while the La Plata River Basin is characterized by both stronger updrafts and higher values of radar‐diagnosed ice water mass. New satellite‐based lightning observations collected over Earth's mid‐/high latitudes provide opportunities to observe and better understand relationships between lightning and precipitation properties over a larger domain than that of the historically sampled global tropics. Considered at hemispheric scales, newly combined continuously observed lightning data and low‐Earth orbiting precipitation “snapshots” suggest lightning and precipitation relationships derived from tropical observations also hold for the mid‐/high latitudes. Regional nuances are found in the electrical and microwave characteristics of deep convection—mid‐/high latitude convection is characterized by colder 30‐dBz echo top heights (indicating stronger updrafts) and a smaller range of microwave brightness temperatures when compared to the tropics. Large‐scale environments where electrically active convection is observed are also examined. Physical processes tied to deep convection (e.g., lofting of ice or updraft strength) can explain some trends in the satellite‐observed precipitation and lightning data. Regional differences in the percentage of electrically active convection characterized by stronger inferred updrafts and higher derived values of ice are discussed. Global precipitation measurement combined with geostationary lightning mapper observations facilitates new investigations of convective precipitation in the mid‐/high latitudesConvective life cycle stage can be inferred by examining flash rate in terms of radar and passive microwave propertiesDifferent synoptic environmental influences on observed precipitation/lightning properties are explained by impacts on physical processes Global precipitation measurement combined with geostationary lightning mapper observations facilitates new investigations of convective precipitation in the mid‐/high latitudes Convective life cycle stage can be inferred by examining flash rate in terms of radar and passive microwave properties Different synoptic environmental influences on observed precipitation/lightning properties are explained by impacts on physical processes

It has long been understood that fog plays an important role in the atmospheric radiation budget and contributes to many transportation related fatalities and injuries. This study utilizes >8,000 Global Surface Summary of the Day (GSOD) ground stations to investigate trends observed in fog‐days over the past 44‐years, and to examine the validity of these trends under varying observational techniques. Results show strong large‐scale regional trends in the GSOD fog‐day data, with the United States (USA) and much of Europe observing ∼20–25% and ∼3–5% decreases respectively in fog‐day occurrence. However, when comparing fog‐day counts to simultaneous visibility, it is evident that several different fog‐day data collection techniques were used throughout the timeseries in many regions. For example, many stations in the USA made data collection changes in the mid 1990s, and again in the mid 2000s. To identify the artifacts from different data collection techniques, a simple method is developed to determine which stations indeed encountered at least one false deviation to the timeseries. After applying the methodology to all GSOD stations, 1,696 stations are identified as being potentially quality long‐term fog‐day stations. Utilizing these stations, more reliable regional trends can be derived over some specific regions. Spain, Australia, and China show statistically significant decreases in fog‐day occurrence. India and Japan show increases in fog day occurrence. Further analysis shows that the driving factors of fog such as temperature and moisture have changed regionally during the last four decades and could be linked to the long‐term regional fog‐day trends. Global and regional trends in fog days are determined with the original Global Surface Summary of the Day ground station dataDeviations in the daily mean visibility timeseries are found during fog days, indicating a potential change in fog day determinationA method is constructed to remove stations with artificial trends, and the fog day trends in the remaining 1,696 are explored Global and regional trends in fog days are determined with the original Global Surface Summary of the Day ground station data Deviations in the daily mean visibility timeseries are found during fog days, indicating a potential change in fog day determination A method is constructed to remove stations with artificial trends, and the fog day trends in the remaining 1,696 are explored

Due to a lack of observations, it is a big challenge to quantify the momentum flux transported from the troposphere into the lower stratosphere by gravity waves generated by convection. This limits our understanding of the dynamics of general circulation in the stratosphere and the realism of simulations of the Quasi Biennial Oscillation. In the past decade, some general circulation models have linked the momentum flux to the latent heating from subgrid scale convective precipitation with some success. However, there is still a large uncertainty in the sources of subgrid scale convection in these models. This study applies the links between the momentum flux and convective latent heating directly to the convective precipitation derived from 16 years of TRMM precipitation radar observations in the tropics and subtropics. The total and directional momentum flux at 100 hPa are derived at individual convective pixels by using the TRMM Spectrum Latent Heating product and large‐scale wind profiles from the ERA‐Interim dataset. For the first time, we are able to estimate the geographical distribution of momentum flux at 100 hPa in tropics and subtropics from the observed convective sources. The diurnal, seasonal, and interannual variations of the derived momentum flux are presented and discussed. These results could provide a reference to validate the dynamic coupling between the tropical troposphere and the stratosphere in the general circulation models. Latent heat source data derived from space borne radar observation are used to estimate convective gravity wave momentum flux globallyMean conditional MF is generally larger over land than over ocean, mainly due to the larger latent heating ratesThere are still large differences in the convective GW MF between TRMM and WACCM6, due to representation of convection in the model Latent heat source data derived from space borne radar observation are used to estimate convective gravity wave momentum flux globally Mean conditional MF is generally larger over land than over ocean, mainly due to the larger latent heating rates There are still large differences in the convective GW MF between TRMM and WACCM6, due to representation of convection in the model

Mesoscale convective systems (MCSs) occur frequently over the tropics and mid‐latitudes and have a large impact on the local precipitation amounts as well as large‐scale circulation through their modulation of the vertical diabatic heating profile. To fully understand and quantify these effects, MCSs must be studied throughout their lifetimes at both mid‐ and tropical latitudes, over both land and ocean. This can be accomplished by tracking the storm using a global scale data set of precipitation and using this information to composite collocated active sensor measurements to produce a detailed analysis of storm properties along the lifetime of the MCS. To do this, we utilize precipitation features (PFs) produced using observations from the Global Precipitation Measurement (GPM) mission's core satellite and from Integrated Multi‐satellitE Retrievals for GPM data by grouping contiguous raining pixels in both data sets. We propose a simplified tracking algorithm to track systems throughout their lifetimes. Lightning data from the World Wide Lightning Location Network are collocated to these tracks along with GPM PFs. These are then composited relative to the time step along the track that has the greatest number of lightning flashes, which is used as a proxy for MCSs with lightning reaching the maximum convective intensity. We then examine various radar variables for tropical and mid‐latitude systems of varying lifetimes over both land and ocean in order to determine the differences and similarities between these types of systems. Large‐scale precipitation systems are important to the local and global climate. It is important to understand their lifecycle better for better inclusion in weather and climate models. We have developed a simple method to track these systems as they develop so that their lifecycle can be studied. A simplified tracking algorithm has been produced to follow the lifecycle of large‐scale precipitation systems using Integrated Multi‐satellitE Retrievals for GPMThe lifecycle of large‐scale precipitation systems can be studied in detail through composite Global Precipitation Measurement measurements collocated to the track A simplified tracking algorithm has been produced to follow the lifecycle of large‐scale precipitation systems using Integrated Multi‐satellitE Retrievals for GPM The lifecycle of large‐scale precipitation systems can be studied in detail through composite Global Precipitation Measurement measurements collocated to the track

Abstract: The thermal properties of four heteropoly complexes α-K3H3[SiW11Ni(H2O)O39]·11.5H2O (I), α-K3H2[SiW11Fe(H2O)O39]·9H2O (II), α-[(C4H9)4N]3.5H1.5[SiW11Fe(H2O)O39]·4.5H2O (III) and α-[(C4H9)4N]3.5H2.5[SiW11Cu(H2O)O39]·6H2O (IV) were studied by means of TG, DTA and DSC. The activation energy and reaction order of the thermal decomposition reaction of these complexes have been calculated.

Accurate, high‐resolution measurements of the precipitation diurnal cycle are important for understanding local variations in precipitation and the underlying processes which cause them. Combining 16 years of measurements from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) and 4 years from the Global Precipitation Measurement (GPM) Dual‐frequency Precipitation Radar (DPR) creates a 20‐year mean of near surface precipitation rate at 0.1° × 0.1°, hourly resolution from 35°N to 35°S. Similar data sets are created using the same proportions of the TRMM Microwave Imager and GPM Microwave Imager measurements, and 18 years of the Integrated Multi‐satellitE Retrievals for GPM (IMERG) precipitation product. The phase and amplitude of the diurnal variation from each data set are calculated at each grid point using a fast Fourier transform (FFT). The satellite data are validated with 14 years of hourly National Climatic Data Center rain gauge measurements over the southeast United States by applying the same FFT method. Spaceborne radar best represents the unaveraged magnitude and diurnal phase measured by the gauges in this region. Time delays are found in precipitation retrievals from passive microwave observations as well as in the IMERG product. The strengths and weaknesses of these high‐resolution data sets in determining the diurnal cycle of precipitation on a climatological scale are discussed across the tropics and subtropics. In general, when compared to PR and DPR retrievals, IMERG overestimates the global precipitation and has varying time lags, which tend to be larger and earlier over regions where organized convective systems are common. Satellite‐derived precipitation estimates have regionally and data set dependent deficiencies in estimating the precipitation diurnal cycleSatellite datasets may include lags or advances in precipitation timing, complicating the analysis of diurnal precipitationHigh spatial resolution precipitation measurements are valuable for examining diurnal precipitaiton cycles with large regional variablity Satellite‐derived precipitation estimates have regionally and data set dependent deficiencies in estimating the precipitation diurnal cycle Satellite datasets may include lags or advances in precipitation timing, complicating the analysis of diurnal precipitation High spatial resolution precipitation measurements are valuable for examining diurnal precipitaiton cycles with large regional variablity

A 4‐year Global Precipitation Measurement (GPM) Precipitation Feature (PF) data set is used to quantify the frequency and global distribution of overshooting convection. In this study, overshooting convection is defined as PFs with maximum 20 dBZ echo top height (MAXHT20) greater than the height of the lapse rate tropopause, derived from ERA‐Interim reanalysis data. The geographical distribution of overshooting convection exhibits a strong preference for specific land regions, such as over the central United States, Argentina, Central Africa, and Colombia. Larger areas and greater occurrence of 20 dBZ radar reflectivity at the tropopause are found in northern middle to high latitudes than in the tropics. The occurrence of 20 dBZ radar reflectivity reaching above the level of 380 K potential temperature (Z380K) in middle and high latitudes is found to be comparable to that in the tropics. Furthermore, a methodology is developed to detect overshooting convection using the GPM Microwave Imager measured brightness temperature at 183.31 ± 3 and 183.31 ± 7 GHz, and Polarization Corrected Temperature at 89 GHz. The geographical distribution of overshooting convection can be closely reproduced using the combinations of these brightness temperatures with an average Heidke skill score of 0.4 and probability of 0.38. This shows the possibility of identifying overshooting convection from microwave observations at high‐frequency channels near the water vapor absorption line centered at 183.31 GHz from other satellite missions. Larger areas and greater occurrence of 20 dBZ radar reflectivity at the tropopause are found in northern middle to high latitudesExtratropical overshooting convection has a profound effect on the stratosphereGeographical distribution of overshooting convection can be reproduced from GPM microwave observations at high‐frequency channels

A specialized satellite version of the passive microwave electric field retrieval algorithm (Peterson et al., 2015) is applied to observations from the Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Measurement (GPM) satellites to estimate the generator current for the Global Electric Circuit (GEC) and compute its temporal variability. By integrating retrieved Wilson currents from electrified clouds across the globe, we estimate a total mean current of between 1.4 kA (assuming the 7% fraction of electrified clouds producing downward currents measured by the ER‐2 is representative) to 1.6 kA (assuming all electrified clouds contribute to the GEC). These current estimates come from all types of convective weather without preference, including Electrified Shower Clouds (ESCs). The diurnal distribution of the retrieved generator current is in excellent agreement with the Carnegie curve (RMS difference: 1.7%). The temporal variability of the total mean generator current ranges from 110% on semi‐annual timescales (29% on an annual timescale) to 7.5% on decadal timescales with notable responses to the Madden‐Julian Oscillation and El Nino Southern Oscillation. The geographical distribution of current includes significant contributions from oceanic regions in addition to the land‐based tropical chimneys. The relative importance of the Americas and Asia chimneys compared to Africa is consistent with the best modern ground‐based observations and further highlights the importance of ESCs for the GEC. The estimated GEC generator current is 1.4‐1.6 kAThe generator current varies primarily with the (semi) annual cycle and diurnal cycle, but ENSO and MJO signals are notedThe estimated generator current varies least on decadal (7.5%) and weekly (2%) time scales and the latter is likely not a global signal Electrified weather across the globe powers the Global Electric Circuit (GEC) that regulates the electrical potential of the ionosphere. As it is impossible to measure the current provided by every electrified cloud directly, we use a retrieval algorithm to quantify this current from Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Measurement (GPM) satellite measurements. We then examine the variability of this generator current on time scales that range from one day to more than a decade.We estimate that electrified weather provides an average current of 1.4 kA and 1.6 kA globally. Though current contributions can be found in land and ocean regions across the globe, large concentrations are found in the tropics near the equator and in the "tropical chimneys" of the Americas, Africa, and Asia. The greatest source of variability in the GEC generator current is on the semi‐annual time scale (110%) followed by local hour (58%), and universal time (34% ‐ Carnegie curve). The smallest variations are on the decadal (7.5%) and weekly (2%) time scales.

Electrified clouds are known to play a major role in the Global Electric Circuit. These clouds produce upward currents which maintain the potential difference between Earth's surface and the upper atmosphere. In this study, model output from two simulations of the Community Earth System Model (CESM) are compared with conduction currents and other data derived from the Tropical Rainfall Measuring Mission (TRMM) satellite, including both the Lightning Imaging Sensor and Precipitation Radar. The intention is to determine CESM's skill at representing these microphysical and dynamical properties of clouds. Then, these cloud properties are used to develop a model parameterization to compute conduction currents from electrified clouds. Specifically, we evaluate the ability of global mean convective mass flux, ice water path, and convective precipitation to represent conduction current sources. Parameterizations using these variables yield derived global mean currents that agree well with the geographical patterns of TRMM currents. In addition, comparing the diurnal variations of modeled global mean current to the observed diurnal variations of electric potential gradient, root-mean-square (RMS) errors range between 6.5% and 8.1%, but the maximum occurs 4 to 6?h early in all three variables. Output currents derived from the model variables generally match well to the currents derived from TRMM, and the total global current estimates agree well with past studies. This suggests that cloud parameters are well suited for representing the global distribution and strength of currents in a global model framework. Annual averaged cloud parameters agree well with TRMM precipitation and derived currentsCloud parameters can be used to derive Wilson currents in a global climate modelDerived Wilson currents show a similar diurnal variation as that seen in past climatological variations