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At least 829 records · Page 46

Kinetics of Moisture Sorption and Reverse Bias Degradation in Chip Tantalum Capacitors

Exposure of chip MnO2 tantalum capacitors to humid environments might result in increased ESR, leakage currents, and first turn-on failures. However, there is a lack of literature data on the effect of moisture on reverse bias behavior of the parts. The presence of moisture can also result in pop-corning when a high water vapor pressure develops when moisture absorbed in pores of tantalum slugs vaporizes instantly during soldering process resulting in damage to capacitors. A study of kinetics of moisture ingress to and release from active elements of capacitors would allow a better understanding of degradation mechanisms and is important for preventing failures. In this work, a technique for investigation of moisture sorption and desorption in solid chip tantalum capacitors that employs tantalum slugs as a humidity sensor have been developed and kinetics of the process analyzed for different types of capacitors at temperatures from room to 125 ºC. A model that relates diffusion characteristics of polymer cases and size of the slugs to characteristic times of moisture sorption has been developed. A strong effect of moisture on long-term degradation of reverse bias currents in MnO2 cathode capacitors has been demonstrated and physical mechanisms discussed.

Teverovsky, Alexander↗

Kinetics of Moisture Sorption and Reverse Bias Degradation in Chip Tantalum Capacitors

Exposure of chip MnO2 tantalum capacitors to humid environments might result in increased ESR, leakage currents, and first turn-on failures. However, there is a lack of literature data on the effect of moisture on reverse bias behavior of the parts. The presence of moisture can also result in pop-corning when a high water vapor pressure develops when moisture absorbed in pores of tantalum slugs vaporizes instantly during soldering process resulting in damage to capacitors. A study of kinetics of moisture ingress to and release from active elements of capacitors would allow a better understanding of degradation mechanisms and is important for preventing failures. In this work, a technique for investigation of moisture sorption and desorption in solid chip tantalum capacitors that employs tantalum slugs as a humidity sensor have been developed and kinetics of the process analyzed for different types of capacitors at temperatures from room to 125 C. A model that relates diffusion characteristics of polymer cases and size of the slugs to characteristic times of moisture sorption has been developed. A strong effect of moisture on long-term degradation of reverse bias currents in MnO2 cathode capacitors has been demonstrated and physical mechanisms discussed.

Teverovsky, Alexander↗

Controlled Environmental Effects on Creep Test Data of Woven Fabric Webbings for Inflatable Space Modules

eveloping technologies for proposed lunar and Mars space exploration missions. Enhanced habitation sy g studied as potential habitats due to their inherent low mass and small launch volume. One goal of inflatable module research is quantification of the safe-life and end-of-life creep-strain spectrum. Full-scale pressurized inflatable modules are large, costly, and difficult to experimentally study. Therefore, material subcomponents are often studied as an alternative. An experimental thermally controlled long-term creep study of VectranTM webbings for application to inflatable modules is presented. Vectran fibers have high strength and low creep properties. High strength webbing materials are desirable for the load bearing restraint layer of inflatable modules because they are strong, flexible, and lightweight. Characterization of the creep behavior, safe-life, and end-of- life of webbing specimens will help quantify comparable life properties for inflatable modules. Several experimental multiple-year creep studies of webbing specimens in uncontrolled thermal environments have been conducted at NASA Langley Research Center. Experimental data obtained exhibits the classic creep-strain curve due to load, coupled with unique sinusoidal variation due to variation in temperature and humidity over daily and annual time periods. Results also have indicated that specimens fail within a year if the applied load is greater than 50 percent of the rated load. The primary goal of this study is to eliminate thermal effects from the creep data for a group of webbing specimens, and to allow uncontrolled thermal effects to influence the creep data of a second group of webbing specimens. Comparison of both sets of data will define how temperature influences creep data. A unique creep test facility was fabricated to facilitate the generation and comparison of the two sets of data. The facility consists of five creep test stands with an integrated heating and cooling system, and four creep test stands exposed to external environmental or ambient conditions. The facility contains displacement, temperature, humidity, and load sensors. Test specimens consist of one- inch wide, 48-inch long Vectran webbings rated at 12,500 pounds-per-inch. Experimental thermally controlled creep-strain data has been generated for two groups of webbing specimens. Applied load for all test stands was above 9000 lbs and greater than 50 percent of the rated load. Temperatures varied between 58˚F and 83˚F for the four test stands exposed to ambient conditions. Associated creep data exhibited the classic creep- strain profiles. The temperature was set to 72˚F for the five test stands in the controlled temperature environment. Creep data for tests with temperature control also exhibited the classic strain profiles. Data indicated that if the load is greater n thermal effects do not manifest. Therefore, creep tests with loads less than 50 percent of the rated load are planned for in the near future.

Kenner, Winfred S.↗

TPSAS-NF1676L-34053-DND

For the purpose of this study the PurpleAir sensor and the Aeroqual AQY1 were used in three different geographical regions and were intercompared with preliminary Department of Environmental Quality (DEQ) data from Pendleton OR, Richmond VA, and Hampton VA. Pendleton experiences colder temperatures and lower humidities, with higher PM2.5 levels in the summer due to forest fires, and use of woodburning stoves in the winter. Richmond is an urban city located along the Eastern Corridor. Hampton, located near the Chesapeake Bay, has a coastal influence. An evaluation of the PurpleAir sensor was made in all three locations, while the Aeroqual AQY1 was evaluated for Richmond and Hampton. PurpleAir PM2.5 levels are typically a factor of two higher when compared to DEQ PM2.5. Aeroqual PM2.5 is typically lower than DEQ PM2.5. Both Aeroqual and PurpleAir exhibit a dependence on relative humidity. Aeroqual ozone captures the diurnal trend when compared with DEQ ozone; however, the correlation varies with season.

Amber Verstynen↗

TPSAS-NF1676L-10726-DND

The principal component radiative transfer model PCRTM (Xu 2006) simulates spectral longwave radiance at a 0.5cm-1 resolution over the wavelengths (50-2760cm-1) using 280 principal components. The CERES product SSF containing CERES field-of-view (FOV) cloud properties based on MODIS pixel information are used as inputs. NASA GMAO(Global Modeling and Assimilation Office)Geos-4 temperature and humidity profiles, as well as SMOBA (Stratosphere Monitoring Ozone Blended Analysis) ozone profiles allow computations for five years (Jan 2001- Dec 2006) of FOV nadir spectral radiance. The approximately twice daily FOV PCRTM simulations along with CERES broadband measurements are time-space averaged to 10deg zonal monthly data. Analysis of monthly seasonal and deseasonalized interannual variability in terms of brightness temperature are presented. Comparison of interannual variability in the portions of the spectrum seen by the AIRS instrument are shown. Comparisons of spectral integrated PCRTM simulations to CERES broadband longwave radiance measurements are made. In order to study the sensitivity of the spatially and temporally averaged TOA spectrum to various atmospheric properties, we perturbed atmospheric and surface temperatures, humidity, cloud height, cloud fraction, and particle size. The sensitivity of the spectrum to these properties depends on region and seasons. Month to month variability of the longwave spectra to these perturbations is 10 to 20% of the global monthly mean perturbation response. In addition, it depends on time period and size of the area used for averaging spectra. In this poster, the magnitude of sensitivity variability and how the sensitivity changes depending on temporal and spatial scale of averaging will be discussed.

Fred G. Rose↗

Evaluation of Global Fire Weather Database Reanalysis and Short-Term Forecast Products

Daily Fire Weather Index (FWI) System components calculated from the NASA Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), are compared to FWI calculations from a global network of weather stations over 2004–2018, and short-term, experimental (8 d) daily FWI forecasts are evaluated for their skill across the Terrestrial Ecoregions of the World for 2018. FWI components from MERRA-2 were, in general, biased low compared to station data, but this reflects a mix of coherent low and high biases of different magnitudes. Biases in different MERRA-2 FWI components were related to different biases in weather input variables for different regions, but temperature and relative humidity biases were the most important overall. FWI forecasts had high skill for 1–2 d lead times for most of the world. For longer lead times, forecast skill decreased most quickly at high latitudes and was most closely related to decreasing skill of relative humidity forecasts. These results provide a baseline for the evaluation and use of fire weather products calculated from global analysis and forecast fields.

Global Fire Weather Database↗

Comparisons of CFD Simulations of Icing Wind Tunnel Clouds with Experiments Conducted at the NASA Propulsions Systems Laboratory

This paper evaluates simulation predictions against experimental test data of icing clouds that were produced during 2018 ice crystal icing physics tests conducted at the NASA Propulsion Systems Laboratory icing wind tunnel. Aero-thermal and cloud parameters are set and known upstream at the tunnel inlet and spray system, but change as the cloud and air thermodynamically interact as the flowing masses reach the tunnel test section. Utilizing the ANSYS Fluent Discrete Phase Model function, 3D computational fluid dynamics (CFD) simulations were performed, capturing the thermodynamic interactions between the test parameters, and providing predictions of the aero thermal and cloud conditions at the tunnel test section. Simulation predictions were compared with test data that were measured at the tunnel exit plane. Evaluations focused on the cloud concentration (total water content), humidity content, and air temperature. CFD simulation predictions showed areas of agreement and disagreement. Simulations showed that cloud concentration profiles at the test section are strongly related to the initial spray nozzle pattern used at the tunnel inlet. Experimental data suggest that greater dispersion of the cloud occurred as the simulated cloud predicted areas of high and low cloud concentration compared to test data profiles. Simulations, however, captured the magnitude and location of the change in humidity content and the change in air temperature due to the presence of the cloud reasonably well, when compared to test data. This result would suggest that while the ANSYS simulation did not fully predict the spreading of the cloud as measured during experiment, it did capture evaporation and the molecular movements of air and vapor relatively well.

CFD↗

Comparisons of CFD Simulations of Icing Wind Tunnel Clouds with Experiments Conducted at the NASA Propulsions Systems Laboratory

This paper evaluates simulation predictions against experimental test data of icing clouds that were produced during 2018 ice crystal icing physics tests conducted at the NASA Propulsion Systems Laboratory icing wind tunnel. Aero-thermal and cloud parameters are set and known upstream at the tunnel inlet and spray system, but change as the cloud and air thermodynamically interact as the flowing masses reach the tunnel test section. Utilizing the ANSYS Fluent Discrete Phase Model function, 3D computational fluid dynamics (CFD) simulations were performed, capturing the thermodynamic interactions between the test parameters, and providing predictions of the aero thermal and cloud conditions at the tunnel test section. Simulation predictions were compared with test data that were measured at the tunnel exit plane. Evaluations focused on the cloud concentration (total water content), humidity content, and air temperature. CFD simulation predictions showed areas of agreement and disagreement. Simulations showed that cloud concentration profiles at the test section are strongly related to the initial spray nozzle pattern used at the tunnel inlet. Experimental data suggest that greater dispersion of the cloud occurred as the simulated cloud predicted areas of high and low cloud concentration compared to test data profiles. Simulations, however, captured the magnitude and location of the change in humidity content and the change in air temperature due to the presence of the cloud reasonably well, when compared to test data. This result would suggest that while the ANSYS simulation did not fully predict the spreading of the cloud as measured during experiment, it did capture evaporation and the molecular movements of air and vapor relatively well.

CFD↗

Airborne High Spectral Resolution Lidar-2 Measurements of Enhanced Depolarization in Marine Aerosols

Airborne NASA Langley Research Center (LaRC) High Spectral Resolution Lidar-2 (HSRL-2) measurements acquired during the recent NASA EVS-3 Aerosol Cloud Meteorology Interactions over the Western Atlantic Experiment (ACTIVATE) revealed enhanced particulate linear depolarization associated with aerosols within the marine boundary layer. These HSRL-2 observations were acquired off the east coast of the United States in February and March 2020 when this lidar was deployed on the NASA LaRC UC-12 aircraft. HSRL-2 measured profiles of aerosol backscattering, extinction,and depolarization at 355 and 532nm and aerosol backscattering and depolarization at 1064nm. Typically HSRL-2 measures low (<5%) linear particulate depolarization associated with marine sea salt aerosols. However, during several ACTIVATE flights, particularly those that occurred with outbreaks of cold, dry air, linear particulate depolarization exceeded 15-20% (532nm) for aerosols within a few hundred meters above the surface. These high values indicated that these particles were nonspherical. Elevated depolarization values were also observed at 355 and 1064 nm. HSRL-2 measured aerosol extinction/backscatter ratio (“lidar ratio”) values around 20-25 sr (355 and 532 nm) that are typically associated with sea salt particles. Coincident measurements of relative humidity from dropsondes released from the UC-12and in situ Diode Laser Hygrometer (DLH) measurements flown on the NASA HU-25 aircraft showed that highest depolarization values of these nonspherical particles were found when the relative humidity (RH)was below 50-60%.These lidar observations of elevated depolarization associated with sea salt aerosol are consistent with previous lidar measurements of sea salt aerosols in dry conditions. We discuss these HSRL-2 measurements also in the context of coincident airborne in situ measurements of particle size and composition acquired on the HU-25 aircraft. We also found that CALIOP satellite measurements observed elevated depolarization during some similar cold air outbreaks. In such cases, the operational CALIOP algorithms attributed the elevated depolarization to nonspherical dust particles rather than the more likely scenario of nonspherical sea salt particles associated with low RH.

aerosols↗

Clouds and Convective Self-Aggregation in a Multi-Model Ensemble of Radiative-Convective Equilibrium Simulations

The Radiative-Convective Equilibrium Model Intercomparison Project (RCEMIP) is an intercomparison of multiple types of numerical models configured in radiative-convective56equilibrium (RCE). RCE is an idealization of the tropical atmosphere that has long been used to study basic questions in climate science. Here, we employ RCE to investigate the role that clouds and convective activity play in determining cloud feedbacks, climatecsensitivity, the state of convective aggregation, and the equilibrium climate. RCEMIP is unique amongst intercomparisons in its inclusion of a wide range of model types, including atmospheric general circulation models (GCMs), single column models (SCMs), cloud-resolving models (CRMs), large eddy simulations (LES), and global cloud-resolving models (GCRMs). The first results are presented from the RCEMIP ensemble of more than 30 models. While there are large differences across the RCEMIP ensemble in the representation of mean profiles of temperature, humidity, and cloudiness, in a majority of models anvil clouds rise, warm, and decrease in area coverage in response to an increase in sea surface temperature (SST). Nearly all models exhibit self-aggregation in large domains and agree that self-aggregation acts to dry and warm the troposphere, reduce high cloudiness, and increase cooling to space. The degree of self-aggregation exhibits no clear tendency with warming. There is a wide range of climate sensitivities, but models with parameterized convection tend to have lower climate sensitivities than models with explicit convection. In models with parameterized convection, aggregated simulations have lower climate sensitivities than un-aggregated simulations. Plain Language Summary This study investigates tropical clouds and climate using results from more than 30 different numerical models set up in a simplified framework. The dataset of model simulations is unique in that it includes a wide range of model types configured in a consistent manner. We address some of the biggest open questions in climate science, including how cloud properties change with warming and the role that the tendency of clouds to form clusters plays in determining the average climate and how climate changes. While there are large differences in how the different models simulate average temperature, humidity, and cloudiness, in a majority of models, the amount of high clouds decreases as climate warms. Nearly all models simulate a tendency for clouds to cluster together. There is agreement that when the clouds are clustered, the atmosphere is drier with fewer clouds overall. We don’t find a conclusive result for how cloud clustering changes as the climate warms.

Allison A. Wing↗

Mechanisms Associated with Daytime and Nighttime Heat Waves over the Contiguous United States

Heat waves are extreme climate events that have the potential to cause immense stress on human health, agriculture, and energy systems, so understanding the processes leading to their onset is crucial. There is no single accepted definition for heat waves, but they are generally described as a sustained amount of time where temperature exceeds a local threshold. Multiple different temperature variables are potentially relevant, as high values of both daily maximum (Tmax) and minimum (Tmin) temperatures can be detrimental to human health. In this study, we focus explicitly on the different mechanisms associated with summertime heat waves manifested during daytime versus nighttime hours over the contiguous United States. Heat waves are examined using the National Aeronautics and Space Administration (NASA) Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2). Over 1980–2018, the increase in the number of heat wave days per summer was generally stronger for nighttime heat wave days than daytime heat wave days, with localized regions of significant positive trends. Processes linked with daytime and nighttime heat waves are identified through composite analysis of precipitation, soil moisture, clouds, humidity and fluxes of heat and moisture. Daytime heat waves are associated with dry conditions, reduced cloud cover, and increased sensible heating. Mechanisms leading to nighttime heat waves differ regionally across the US, but they are typically associated with increased clouds, humidity and/or low-level temperature advection. In the Midwest US, enhanced moisture is transported from the Gulf of Mexico during nighttime heat waves.

Extreme events↗

Potential of a Plant Gas Exchange Mechanistic Model to Predict Plant Transpiration in Veggie on ISS

Plants are an essential part of long-duration space travel, as they enable food production and contribute to air revitalization through photosynthesis, and water recycling through transpiration. Understanding their growth mechanisms is essential to use them to sustain human life in space. In particular, gas exchange – e.g., CO2 absorption and water transpiration – are modified in microgravity because of the lack of buoyancy-driven convection, and in the long run, this could result in impaired plant growth. Water absorbed by the plants mainly depends on their size and on environmental conditions (air temperature, humidity and ventilation), but in microgravity watering plants is a delicate operation – too much water results in flooded roots and too little water leads in a few hours to wilted plants. This is regularly experienced in the Veggie system on ISS, which enables small-scale food production in microgravity since 2014. This presentation explores how a mechanistic model of plant gas exchange can help predict plant transpiration in Veggie and thus better predict daily watering. For each plant, inputs on canopy leaf area (acquired with daily photos), air temperature and relative humidity in the plant compartment, as well as airspeed at the top of its canopy enable accurate predictions of transpiration in microgravity. This brings a better understanding of water movement through the plant in microgravity in relation to ventilation and plant size and would result in easier management of plant watering in Veggie. Ultimately, this work could be applied to any space crop production in microgravity and be used for water management and yield predictions. This work was funded by NASA Space Biology through NASA postdoctoral program / USRA.

Lucie Poulet↗

Potential of a Plant Gas Exchange Mechanistic Model to Predict Plant Transpiration in Veggie on ISS

Plants are an essential part of long-duration space travel, as they enable food production and contribute to air revitalization through photosynthesis, and water recycling through transpiration. Understanding their growth mechanisms is essential to use them to sustain human life in space. In particular, gas exchange – e.g., CO2 absorption and water transpiration – are modified in microgravity because of the lack of buoyancy-driven convection, and in the long run, this could result in impaired plant growth. Water absorbed by the plants mainly depends on their size and on environmental conditions (air temperature, humidity and ventilation), but in microgravity watering plants is a delicate operation – too much water results in flooded roots and too little water leads in a few hours to wilted plants. This is regularly experienced in the Veggie system on ISS, which enables small-scale food production in microgravity since 2014. This presentation explores how a mechanistic model of plant gas exchange can help predict plant transpiration in Veggie and thus better predict daily watering. For each plant, inputs on canopy leaf area (acquired with daily photos), air temperature and relative humidity in the plant compartment, as well as airspeed at the top of its canopy enable accurate predictions of transpiration in microgravity. This brings a better understanding of water movement through the plant in microgravity in relation to ventilation and plant size and would result in easier management of plant watering in Veggie. Ultimately, this work could be applied to any space crop production in microgravity and be used for water management and yield predictions. This work was funded by NASA Space Biology through NASA postdoctoral program / USRA.

Lucie Poulet↗

Establishing an Urban Heat Exposure Severity Index for Infrastructure Prioritization in Tempe, Arizona, Using NASA Earth Observations and LiDAR

Located on the banks of the Salt River in the Sonoran Desert, Tempe, Arizona, features a semi-arid climate with summer daily maximum temperatures regularly exceeding 37.8°C. Tempe is also subject to the southwestern monsoon season from July-September and the humidity exacerbates the high temperatures. Furthermore, the rapid urbanization experienced in Tempe has resulted in an intensification of the urban heat island. The summer of 2020 shattered the previous record of days exceeding 43.4°C, leading to higher energy and water costs, lower comfort, and increased risk of heat stroke for residents. Recognizing the impacts of extreme heat, the City of Tempe partnered with the Healthy Urban Environments initiative and NASA DEVELOP to identify census tracts that experience a higher mean land surface temperature than the city average. The NASA DEVELOP team used remotely sensed land surface temperature (LST), normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), normalized difference water index (NDWI), and albedo data calculated from Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) instruments from 2015 to 2020 to create heat hazard and exposure maps. LiDAR point cloud data, provided by the United States Geological Survey through Arizona State University’s Map and Geospatial Hub, were used to derive 3D buildings, building footprints, and tree point data for a shading analysis of walking paths, roads, and buildings at the census tract level. In situ meteorological measurements including air temperature and humidity were used to compare the macro-scale temperature measurements. The team worked with the City of Tempe to develop a methodology to process available data and identify areas of highest concern for urban heat effects within the city. With these insights, Tempe, Arizona can better address these issues with data-driven information to make decisions regarding heat mitigation and adaptation efforts.

John Dialesandro↗

Small Particle Glovebox Experiments - Preliminary Results

A substantial portion of the asteroid samples returned by the HAYABUSA2 and OSIRIS-REx missions will consist of small (submm) components (due to the collection of those particles on the asteroid surface and due to the fragmenting of larger, friable material post-collection). In order to minimize the alteration/oxidation of asteroid regolith, the bulk collections will be stored and curated in nitrogen purged gloveboxes. The processing of small particles in an N2 glovebox will present challenges that are different from those experienced during lunar and meteorite sample processing. Particles in this size range are susceptible to unpredictable electrostatic charging that can result in sample loss during processing operations. Methods for the handling of sub-mm particles have been well developed for environments with ambient atmospheric conditions and relative humidity (RH) ranges between 40-70%. In such conditions, a number of factors can be successfully employed to minimize the effects of triboelectric charging, including the use of Po-210 sources that neutralize excess charge and the utilization of conductive manipulation tools and sample substrates. However, relative humidity levels above 40% also contribute significantly to dissipation of triboelectric effects. We had not previously investigated our charge mitigation methods in a completely dry, nitrogen-purged environment, or whether they would be sufficient in enabling the successful processing of sub-mm samples. Current glovebox configurations in use in our lunar and meteorite curation laboratories are optimized for the processing of macroscopic samples and tools; these glovebox designs are likely unsuitable for the processing of collections for which the bulk collection is comprised of sub-mm components. Small particle sample preparation requires the use of an optical magnification instrument – typically a stereo binocular microscope with at least 20x magnification. Current glovebox designs are not optimized for the utilization or integration of stereo microscopes; while many current cabinets include microscope viewports that enable the use of small, externally mounted stereo microscopes, the focusing methods (usually involving the use of a lab jack) lack the fidelity and precision required for small particle manipulation and imaging. Working distances of higher (>50x magnification) objective lenses may preclude the external use of a stereo microscope through a viewport; in order to successfully manipulate and image very small (< 20m) particles, stereo and digital microscope systems that are integrated within the glovebox should be investigated. Finally, ergonomic considerations for small particle work within a glovebox must be considered to minimize risk of injury to sample processors. In order to investigate some of the unknown parameters relating to small particle processing within an N2 glovebox, we conducted preliminary, qualitative experiments utilizing a small lunar cabinet that was originally used for film development.

C. J. Snead↗

An upgraded G-band differential absorption radar system for future airborne studies

A proof-of-concept, 170 GHz frequency-modulated, continuous-wave (FMCW) radar has been developed for measuring water vapor profiles within the cloudy boundary layer from an airborne platform. The measurement concept exploits the differential absorption accrued by two or more transmitted frequencies in the vicinity of the 183 GHz water absorption line to retrieve range-resolved humidity profiles, so-called differential absorption radar (DAR). The upgraded system design includes important considerations for monostatic radar operation with an open fuselage viewport (i.e. no radome). The radar features an all-solid-state tansmitter with > 0:4 W continuous transmit power, a 60 cm primary aperture and corresponding 58 dB antenna gain, and more than 80 dB transmit/receive isolation, enabling near thermal-noise-limited sensitivity with a 8 dB noise figure receiver. Ice-cloud radar returns are detected beyond 8 km in height from the ground, demonstrating the high sensitivity of the system. In addition to in-cloud humidity profiling capabilities, deployment of a water vapor DAR from an airborne platform enables measurements of total column water vapor (TCWV) for all weather and surface scenarios. Precision estimates and potential biases for future TCWV measurements are discussed.

Monje, Raquel↗

Hiatus of wetland methane emissions associated with recent La Niña episodes in the Asian monsoon region

The variability of methane emissions from wetlands in the tropics and northern temperate regions can explain more than 70% of the interannual variation in global wetland methane emissions, which are largely driven by climate variability. We use climate reanalysis, remote sensing wetland area dataset and simulations from 11 land models contributing to Global Methane Budget to investigate the interannual variation and anomalies of wetland methane emissions in the Asian Monsoon region. Methane emissions in this region steadily increased over 2000–2012. However, abnormally low methane emissions were found in equatorial fully humid (Af), warm temperate winter dry (Cw), and warm temperate fully humid (Cf) Asian Monsoon climate sub-regions in 2008, 2009 and 2011, respectively. These spatially-shifting low emissions occurred simultaneously with observed wetland area shrinkage due to abnormally low precipitation. Interannual variability of wetland methane emissions in Asian Monsoon region are primarily driven by South Asian Monsoon system. However, the abnormally low emissions are related to strong La Niña events, and its accompanying effect of weakened East Asian Monsoon system and eastward Western Pacific subtropical high, which drives the shifting pattern of rainfall, and thus the spatial pattern of methane emission anomalies.

wetlands↗

Large Contribution of Meteorological Factors to Inter-Decadal Changes in Regional Aerosol Optical Depth

Aerosol optical depth (AOD) has become a crucial metric for assessing global climate change. Although global and regional AOD trends have been studied extensively, it remains unclear what factors are driving the inter-decadal variations in regional AOD and how to quantify the relative contribution of each dominant factor. This study used a long-term (1980–2016) aerosol dataset from the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) reanalysis, along with two satellite-based AOD datasets (MODIS/Terra and MISR) from 2001 to 2016, to investigate the long-term trends in global and regional aerosol loading. Statistical models based on emission factors and meteorological parameters were developed to identify the main factors driving the inter-decadal changes of regional AOD and to quantify their contribution. Evaluation of the MERRA-2 AOD with the ground-based measurements of AERONET indicated significant spatial agreement on the global scale (r= 0.85, root-mean-square error = 0.12, mean fractional error = 38.7 %, fractional gross error = 9.86 % and index of agreement = 0.94). However, when AOD observations from the China Aerosol Remote Sensing Network (CARSNET) were employed for independent verification, the results showed that MERRA-2 AODs generally underestimated CARSNET AODs in China (relative mean bias = 0.72 and fractional gross error =−34.3 %). In general, MERRA-2 was able to quantitatively reproduce the annual and seasonal AOD trends on both regional and global scales, as observed by MODIS/Terra, although some differences were found when compared to MISR. Over the 37-year period in this study, significant decreasing trends were observed over Europe and the eastern United States. In contrast, eastern China and southern Asia showed AOD increases, but the increasing trend of the former reversed sharply in the most recent decade. The statistical analyses suggested that the meteorological parameters explained a larger proportion of the AOD variability (20.4 %–72.8 %) over almost all regions of interest (ROIs) during 1980–2014 when compared with emission factors (0 %–56 %). Further analysis also showed that SO2 was the dominant emission factor, explaining 12.7 %–32.6 % of the variation in AOD over anthropogenic-aerosol-dominant regions, while black carbon or organic carbon was the leading factor over the biomass-burning-dominant (BBD) regions, contributing 24.0 %–27.7 % of the variation. Additionally, wind speed was found to be the leading meteorological parameter, explaining 11.8 %–30.3 % of the variance over the mineral-dust-dominant regions, while ambient humidity (including soil moisture and relative humidity) was the top meteorological parameter over the BBD regions, accounting for 11.7 %–35.5 % of the variation. The results of this study indicate that the variation in meteorological parameters is a key factor in determining the inter-decadal change in regional AOD.

Huizheng Che↗