nasa-gesdisc/es-publications-researchareas huggingface dataset:
Spatial-Temporal Pattern of Black Carbon (BC) Emission from Biomass Burning and Anthropogenic Sources in New South Wales and the Greater Metropolitan Region of Sydney, Australia (2020)

: Biomass burnings either due to Hazards Reduction Burnings (HRBs) in late autumn and early winter or bushfires during summer periods in various part of the world (e.g., CA, USA or New South Wales, Australia) emit large amount of gaseous pollutants and aerosols. The emissions, under favourable meteorological conditions, can cause elevated atmospheric particulate concentrations in metropolitan areas and beyond. One of the pollutants of concern is black carbon (BC), which is a component of aerosol particles. BC is harmful to health and acts as a radiative forcing agent in increasing the global warming due to its light absorption properties. Remote sensing data from satellites have becoming increasingly available for research, and these provide rich datasets available on global and local scale as well as in situ aethalometer measurements allow researchers to study the emission and dispersion pattern of BC from anthropogenic and natural sources. The Department of Planning, Industry and Environment (DPIE) in New South Wales (NSW) has installed recently from 2014 to 2019 a total of nine aethalometers to measure BC in its state-wide air quality network to determine the source contribution of BC and PM2.5 (particulate Matter less than 2.5 m in diameter) in ambient air from biomass burning and anthropogenic combustion sources. This study analysed the characteristics of spatial and temporal patterns of black carbon (BC) in New South Wales and in the Greater Metropolitan Region (GMR) of Sydney, Australia, by using these data sources as well as the trajectory HYSPLIT (Hybrid Single Particle Lagrangian Integrated Trajectory) modelling tool to determine the source of high BC concentration detected at these sites. The emission characteristics of BC in relation to PM2.5 is dependent on the emission source and is analysed using regression analysis of BC with PM2.5 time series at the receptor site for winter and summer periods. The results show that, during the winter, correlation between BC and PM2.5 is found at nearly all sites while little or no correlation is detected during the summer period. Traffic vehicle emission is the main BC emission source identified in the urban areas but was less so in the regional sites where biomass burnings/wood heating is the dominant source in winter. The BC diurnal patterns at all sites were strongly influenced by meteorology.

Research areas: Air Quality, Environmental Impacts
Time-lag correlations between atmospheric anomalies and earthquake events in Iran and the surrounding Middle East region (19802018) (2021)

The main goal of this study was to survey a possible correlation between atmospheric parameters (air temperature, precipitation rate) and subsequent earthquakes in Iran and the surrounding Middle Eastern region. This research was carried out in response to previous work regarding atmospheric anomalies prior to major earthquake events. Area-averaged daily and monthly time-series data were compiled from global reanalyzed datasets for the study area between 1980 and 2018. The time-lagged correlation test through the cross-correlation function was examined to distinguish possible relationships between earthquake events and climatic elements within daily and monthly shifts. The results revealed that the precipitation has a strong ability to predict the earthquake series at least from 312 months prior to the earthquakes. The estimated lagged correlation confirms a positive relationship between precipitation and subsequent earthquake events within 3 to 103 days lag-time (CCF= 0.036 to 0.046). Contrarily, no precursory relation was found between atmospheric temperature variations and subsequent earthquake events in Iran and the surrounding region.

Research areas: Earthquakes, Atmospheric/Ocean Indicators
Northern Gulf Marine Biodiversity in Relevance to the River Discharge (2021)

This chapter summarizes the results of research studies, which addressed the peculiarity of the estuarine and northern Arabian Gulf marine environment and the influence of the Shatt Al-Arab River and its associated marshes on the oceanography and biodiversity of the northern Gulf. The findings of the studies indicated that the northern waters of Kuwait, which are impacted by the Shatt Al-Arab River discharge, displayed lower salinity, higher nitrate concentration, higher chlorophyll-a, and higher sedimentation. The biodiversity of the northern waters of the Gulf also was significantly distinguished from the adjacent area away from the influence of the river flow. Discharge of the Shatt Al-Arab is considered to be a dominating driver of the northern Gulfs ecology and largely responsible for the primary and secondary productivity of Kuwaits waters. Long-term reduction in river discharge due to man-made alterations (damming and diversion of rivers) impacted the oceanographic characteristics of Kuwaits waters with implication to fisheries resources. Management of Shatt Al-Arab River discharge into the Gulf requires cooperation among the riparian countries and downstream countries like Kuwait to preserve the productivity, biodiversity, and uniqueness of the northern Gulf ecosystems. Long-term monitoring and assessment as well as joint research programs involving scientists from the three concerned countries, Kuwait, Iraq, and Iran, are needed.

Research areas: Ecosystems, Habitat Conversion/Fragmentation
Evaluation of MERRA-2 hourly surface solar radiation across China (2022)

Accurate global horizontal irradiance (GHI) is key to solar energy resource assessment and prediction. The GHI provided by MERRA-2 (Version 2 of the Modern-Era Retrospective Analysis for Research and Applications) still needs to be evaluated over China. In this study, GHI observed by 37 ground stations in 2018 are used to systematically assess the MERRA-2 GHI performance for all-sky, clear-sky and cloudy days. Moreover, aerosol and cloud products from MERRA-2 are compared with satellite counterparts to determine the dominant factor affecting MERRA-2 GHI. The results show that MERRA-2 overestimates the hourly and daily mean GHI by 69.35 W/m2 and 27.54 W/m2 on all-sky days, respectively. The mean bias error and root mean square error of hourly GHI between MERRA-2 and CERN are 4.98 W/m2 and 124.85 W/m2 on clear-sky days and 107.16 W/m2 and 215.24 W/m2 on cloudy days, respectively. These values indicate a much greater overestimation of MERRA-2 GHI on cloudy days than on clear-sky days. By comparing cloud fraction (CF) and aerosol optical thickness (AOD) between the Moderate-resolution Imaging Spectroradiometer (MODIS) and MERRA-2, we find that the overestimation of MERRA-2 GHI in most areas is induced by the substantial underestimation of MERRA-2 CF. MERRA-2 underestimates AOD in North China and further enhances the overestimation of GHI caused by the underestimation of MERRA-2 CF, whereas the overestimation of AOD in the Sichuan Basin and Southeastern China partly counterbalances the overestimation of GHI caused by the underestimation of MERRA-2 CF.

Research areas: Sun-Earth Interactions
Projection of the Near-Future PM2.5 in Northern Peninsular Southeast Asia under RCP8.5 (2022)

Throughout the year, particularly during the dry season, the northern peninsula of Southeast Asia struggles with air pollution from PM2.5. In this study, we used the Nested Regional Climate and Chemistry Model (NRCM-Chem) to predict the PM2.5 concentrations over Southeast Asias northern peninsula during the years 20202029 under the Representative Concentration Pathway (RCP)8.5. In general, the model reasonably shows a good result, including temperature, precipitation, and PM2.5 concentration, compared to the observation with an Index of Agreement (IOA) in the range of 0.63 to 0.80. However, there were some underestimations for modeled precipitation and temperature and an overestimation for modeled PM2.5 concentration. As a response to changes in climatic parameters and the emission of PM2.5s precursors, PM2.5 concentrations tend to increase across the region in the range of (+1) to (+35) g/m3 during the dry season (November to April) and decline in the range of (3) to (30) g/m3 during the wet season (May to October). The maximum increase in PM2.5 concentrations were found in March by >40 g/m3.

Research areas: Air Quality
Biomass burning aerosols observed in Eastern Finland during the Russian wildfires in summer 2010  Part 2: Remote sensing (2012)

In the summer 2010 extensive wildfires in the western parts of Russia emitted massive amounts of smoke and aerosols into the atmosphere. These smoke plumes also drifted to Finland over 1000 km away from the fires. The smoke plumes were detected in Kuopio (Eastern Finland) with a wide range of instruments on two specific days: July 29 and August 8. The plumes were studied with several spaceborne instruments: MODIS, OMI, AIRS and CALIOP. Furthermore, a ground-based remote sensing instrument (Cimel) was also used in the analysis. Our results show that ground-based and spaceborne instruments were in good agreement on the Aerosol optical depth (AOD550) values during the episode (Julymid August). The correlation coefficient between MODIS and AERONET measurements done in Kuopio was 0.98 and the mean difference was 0.005 (AERONET AOD being larger). Spaceborne measurements of carbon monoxide provided a clear indicator for biomass burning aerosols. Particle mass (PM2.5) and AERONET AOD550 measurements were also in good agreement with a correlation coefficient of 0.87. Single scattering albedo (SSA675) values derived from AERONET measurements and calculated from in-situ absorption and scattering measurements had similar values close 0.9. On average, the daily in-situ SSA values were 0.02 smaller than the corresponding AERONET values. CALIOP provided vertical profiles of the smoke plumes for the two most polluted days in Kuopio. In July the plume was located close to the surface (mainly below 2 km) while in August the plume had two elevated layers: one between 1 and 2 km and the other between 2.5 and 4 km.

Research areas: Wildfires, Air Quality
Incorporating gridded concentration data in air pollution back trajectories analysis for source identification (2021)

The identification of air pollution sources is a challenging task due to the confounding effects of local and transboundary emitters. While the Potential Source Contribution Function (PSCF) is a useful tool for trajectory analysis and source identification, it can overestimate the impact of less polluted areas in which a trajectory event passed through. In this work, we propose incorporating air pollutant concentration fields from reanalysis data to improve the PSCF method's performance that avoids the overcontribution of less polluted areas. We develop the 3D-PSCF-CONC based on an updated three-dimensional version of the PSCF method (3D-PSCF). We used as a test case the Metropolitan Area of Sao Paulo (MASP) in Brazil, one of the most polluted regions in the world, for comparing the results of the conventional and the new PSCF method. A monitoring station in Vitoria - Espirito Santo, Brazil which has smaller local emissions than MASP was used as an auxiliary test case. Hourly carbon monoxide (CO) and sulfur dioxide (SO2) concentrations from 2015 to 2019 of monitoring stations were analyzed. The daily average concentrations of CO and SO2 were used as a threshold on the probability calculations. An overall of 1825 backward trajectories from HYSPLIT version 4 was processed using the three models. CO and SO2 surface concentrations from MERRA-2, with a resolution of 0.5 x 0.625 was incorporated in the 3D-PSCF-CONC to correct the potential contribution calculation based on the air pollutant concentration field. Our results revealed that the 3D-PSCF-CONC reached a more consistent identification of local and regional sources, rather than emphasizing mostly the regional sources as the other PSCF methods. The 3D-PSCF-CONC reduced the potential contribution of less polluted and high precipitation areas. The analysis suggests a contribution of vehicular sources close to the receptor site in MASP and long-range transport of industrial emissions and biomass burning from the land clearing of sugarcane production. This work presents an important tool for understanding the air pollution process and source identification.

Research areas: Air Quality, Environmental Impacts
Signature of tropospheric ozone and nitrogen dioxide from space: A case study for Athens, Greece (2014)

The aim of the present study is to investigate the variability of the tropospheric ozone and nitrogen dioxide (NO2) columns over mainland Greece, by using observations carried out by satellite-borne instrumentation and Multi Sensor Reanalysis. The results obtained show that the tropospheric ozone residual (TOR) dispersed farther away than the tropospheric NO2 column (TNO), due to the longer TOR's lifetime in respect to that of TNO. This results in the influence of the air quality of the nearby southern islands from the air pollution of the greater Athens basin. Furthermore, the TOR and TNO columns over Athens, for the period October 2004 to December 2011 were found to be negatively correlated with a correlation coefficient 0.85, in contrast to recent findings which suggested strong positive correlation. Interestingly, this strong negative correlation into a slight positive correlation when the TNO concentration becomes higher than around 4  1015 molec cm2, thus being best fitted by a quadratic relationship. In addition, the temporal evolution of TOR during 19791993 showed a decline of 0.2% per decade and just after 1993 it seems to obey a positive trend of 0.1% per decade, thus recovering during the period 19932011 almost 63% of the lost TOR amounts through the years 19791993. Finally, the association between TOR, the total ozone column (TOZ), the tropopause height and the outgoing longwave radiation (OLR) is presented by analysing observations during 19792011. An unexpected positive correlation between OLR and TOR was found, which may probably be attributed to the fact that enhanced abundance in tropospheric water vapor reduces the summertime TOR maximum by destructing ozone in the lower and middle troposphere through uptake mechanisms, thus emitting higher amounts of longwave radiation upwards.

Research areas: Air Quality
Two Heavy Rainfall Types over the Korean Peninsula in the Humid East Asian Summer Environment: A Satellite Observation Study (2015)

A total of 10 years (200211) of Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) reflectivities, signaling heavy rainfall (>10 mm h1), were objectively classified by applying the K-means clustering method in order to obtain typical reflectivity profiles associated with heavy rainfall over East Asia. Two types of heavy rainfall emerged as the most important rain processes over East Asia: type 1 (cold type) characterized by high storm height and abundant ice water under convectively unstable conditions, developing mostly over inland China; and type 2 (warm type) associated with a lower storm height and lower ice water content, developing mostly over the ocean. These two types also show sharp contrasts in relation to their seasonal changes and in the diurnal variation of frequency maxima, in addition to other contrasting meteorological parameters. The PR-derived heavy rain events were observed over the Korean peninsula and their spatiotemporal evolution was examined using 10-yr composites of 11-m brightness temperature from geostationary satellites and Interim ECMWF Re-Analysis (ERA-Interim) data. Cold-type heavy rainfall over Korea is characterized by an eastward moving cloud system with an oval shape while the warm type shows a comparatively wide spatial distribution over an area extending from the southwest to northeast. Overall the warm-type process appears to link the low-level moisture convergence area to the vertically aligned divergence area formed over the jet stream level. This setup continuously pushes air upward under moist-adiabatically near-neutral conditions and thus yields heavy rainfall. As warm-type heavy rainfall persists longer, it is considered to be more responsible for flood events occurring over the Korean peninsula.

Research areas: Atmospheric/Ocean Indicators
Reduction of surface radiative forcing observed from remote sensing data during global COVID-19 lockdown (2021)

The calamity of the COVID-19 pandemic during the early half of 2020 not only caused a huge physical and economic loss but altered the social behavior of the whole world. The social and economic stagnation imposed in many countries and served as a major cause of perturbation in atmospheric composition. This paper utilized the relation between atmospheric composition and surface radiation and analyzed the impact of global COVID-19 lockdown on land surface solar and thermal radiation. Top of atmosphere (TOA) and surface radiation are obtained from the Clouds and Earth's Radiant Energy System (CERES) and European Reanalysis product (ERA5) reanalysis product. Aerosol Optical Depth (AOD) is obtained from Moderate Resolution Imaging Spectroradiometer (MODIS) while Nitrogen dioxide (NO2), and sulfur dioxide (SO2) are obtained from Ozone Monitoring Instrument (OMI). Observations of all mentioned parameters are studied for the global lockdown period of 2020 (from January to July) and compared with the corresponding months of the previous four years (201619) observations. Regarding surface radiation, April 2020 is the most affected month during the pandemic in which 0.2% increased net solar radiation (NSR), while 3.45% and 4.8% decreased net thermal radiation (NTR) and net radiation (NR) respectively was observed. Average radiative forcing during MarchMay 2020 was observed as 1.09 Wm2, 2.19 Wm2 and 1.09 Wm2 for NSR, NTR and NR, respectively. AOD was reduced by 0.2% in May 2020 while NO2 and SO2 were reduced by 5.4% and 8.8%, respectively, in April 2020. It was observed that NO2 kept on reducing since January 2020 while SO2 kept on reducing since February 2020 which were the pre-lockdown months. These results suggest that a more sophisticated analysis is needed to explain the atmosphere-radiation relation.

Research areas: Sun-Earth Interactions, Air Quality
An Analysis of the Aerosol Lifecycle Over India: COALESCE Intercomparison of Three General Circulation Models (2022)

Atmospheric aerosols or atmospheric particulate matter affects climate variables like temperature and rainfall, agricultural productivity, soil, and human health. We evaluated aerosol lifecycle over India via simulations (20052014) from three general circulation models under the COALESCE project (carbonaceous aerosol emissions, source apportionment, and climate impacts; Venkataraman et al., 2020, 10.1175/bams-d-19-0030.1). The ECHAM6.3-HAM2.3, CAM5.3, and NICAM-SPRINTARS simulations use identical regional emissions (from the Speciated Multi-pollutant generator, SMoG-India-v1). Satisfactory model simulations of meteorological variable magnitudes and seasonal cycle have been achieved partly from the adoption of nudging. Estimations of anthropogenic aerosol, aerosol optical depth (AOD), and particulate matter surface concentrations are significantly improved from (a) dust tuning (b) use of satellite-derived organic aerosol to carbon ratio, and (c) nudged meteorology to capture variables influencing the production of secondary sulfate. Larger wintertime under prediction (30% to 60%) results from over prediction of seasonal planetary boundary layer height and the absence of secondary ammonium nitrate and organic aerosols. Vertical dispersion to higher altitudes than in observations calls for improved modeling of vertical mass flux representation. Carbonaceous aerosol residence time and AOD fraction larger than global mean values in India, with a seasonal predominance in the autumn and winter seasons can be explained by enhanced regional emissions from residential biofuel cooking, agricultural stubble burning, and traditional informal industries like brick production.

Research areas: Air Quality, Environmental Impacts
Evaluation of the TRMM product for monitoring drought over Paraiba State, northeastern Brazil: a trend analysis (2021)

Droughts are complex natural phenomena that influence society's development in different aspects; therefore, monitoring their behavior and future trends is a useful task to assist the management of natural resources. In addition, the use of satellite-estimated rainfall data emerges as a promising tool to monitor these phenomena in large spatial domains. The Tropical Rainfall Measuring Mission (TRMM) products have been validated in several studies and stand out among the available products. Therefore, this work seeks to evaluate TRMM-estimated rainfall data's performance for monitoring the behavior and spatiotemporal trends of meteorological droughts over Paraiba State, based on the standardized precipitation index (SPI) from 1998 to 2017. Then, 78 rain gauge-measured and 187 TRMM-estimated rainfall time series were used, and trends of drought behavior, duration, and severity at eight time scales were evaluated using the MannKendall and Sen tests. The results show that the TRMM-estimated rainfall data accurately captured the pattern of recent extreme rainfall events that occurred over Paraiba State. Drought events tend to be drier, longer-lasting, and more severe in most of the state. The greatest inconsistencies between the results obtained from rain gauge-measured and TRMM-estimated rainfall data are concentrated in the area closest to the coast. Furthermore, long-term drought trends are more pronounced than short-term drought, and the TRMM-estimated rainfall data correctly identified this pattern. Thus, TRMM-estimated rainfall data are a valuable source of data for identifying drought behavior and trends over much of the region.

Research areas: Droughts
Influence of major typhoons on ocean, atmosphere and air quality of Northwest Pacific during August 2020 (2022)

Tropical storms (TSs)/Typhoons (TYs) in the Northwest Pacific (NWP) region are one of the most devastating natural hazards, which cause large-scale impacts on human life and infrastructure. In August 2020, a total of 9 tropical storms were identified by International Best Track Archive for Climate Stewardship (IBTrACS) in the NWP region. These TSs/TYs made their landfall over the coastal parts of China, North Korea, and South Korea, while none of them made their landfall over Taiwan. These conditions were unique in recent years and induced drought conditions in Taiwan during 2020. We have carried out a three-dimensional analysis of oceanic, atmospheric, and meteorological parameters for the evaluation of changes associated with typhoons during August 2020. The model, satellite, and ground observations data have been used for the assessment of the impact of these TS/TYs on the ocean, atmosphere, and air quality. The rise in ocean temperature (1 C2 C) was observed even at the depth of 100 m. Strong upwelling of the ocean water in the NWP originated a change in the mixed layer depth and also has affected the salinity in South China, East China, and the Philippines Sea. The strong convective forces during the storm conditions produced a prominent rise in CO and Ozone concentration. These typhoons also affected the air quality of Taiwan during August 2020. The transboundary air pollutants triggered the enhancement in particulate matter (PM1.0 and PM2.5) and surface ozone over Taiwan, which resulted in major health hazards to a large population.

Research areas: Severe Storms, Atmospheric/Ocean Indicators, Air Quality