nasa-gesdisc/es-publications-researchareas huggingface dataset:
Optical properties of dust and crop burning emissions over India using ground and satellite data (2020)

Dust storms during the pre-monsoon season (AprilJune) and crop residual burning events during the post-monsoon season (mid-Octobermid-November) are common every year over the Indo-Gangetic plains (IGP). In this paper, we have compared dust storm and crop burning aerosols characteristics for the years 2016, 2017 and 2018 using ground and satellite data. CALIPSO data show that dust layers extended from the ground upto an altitude of about 5 km and the smoke from crop burning upto the height of 2 km. Characteristics of dust and crop burning aerosols show pronounced difference based on Kanpur AERONET data. Dominance of coarse particles (0.615 m) during dust storms (pre-monsoon season), while fine particles (0.050.6 m) dominate during crop residual burning. The spectral variations of single scattering albedo (SSA) during dusty days and crop burning days show low and high fractions of anthropogenic aerosols. We have also observed the impact of dust particles on Himalayan snow (cover, albedo and reflectance) and meteorological parameters (relative humidity and water vapor) on the surface and lower atmosphere using MODIS data and AIRS data at different pressure levels. Pronounced aerosols behaviors of the crop residual burning event coincided with Diwali festival on 3031 October 2016 were observed. Our detailed analysis combining ground and satellite observations provides better understanding of aerosol optical and microphysical properties of dust storms and crop residual burnings. The results will be valuable in monitoring surrounding environment, identifying the emission source and dynamics of dust storms and crop burning emissions over India, especially in the IGP.

Research areas: Environmental Impacts
Significance of the organic aerosol driven climate feedback in the boreal area (2021)

Aerosol particles cool the climate by scattering solar radiation and by acting as cloud condensation nuclei. Higher temperatures resulting from increased greenhouse gas levels have been suggested to lead to increased biogenic secondary organic aerosol and cloud condensation nuclei concentrations creating a negative climate feedback mechanism. Here, we present direct observations on this feedback mechanism utilizing collocated long term aerosol chemical composition measurements and remote sensing observations on aerosol and cloud properties. Summer time organic aerosol loadings showed a clear increase with temperature, with simultaneous increase in cloud condensation nuclei concentration in a boreal forest environment. Remote sensing observations revealed a change in cloud properties with an increase in cloud reflectivity in concert with increasing organic aerosol loadings in the area. The results provide direct observational evidence on the significance of this negative climate feedback mechanism.

Research areas: Atmospheric/Ocean Indicators
Phytodetrital quality (C:N ratio) and temperature changes affect C and N cycling of the intertidal mixotrophic foraminifer Haynesina germanica (2021)

The combination of lower diet quality and increased metabolic rates is assumed to cause cascading effects on organismic C cycling. Future changes in CO2 levels or terrestrial nutrient discharges in marine ecosystems can lead to increased phytoplankton C:N ratios relative to consumer C:N ratios, lowering the quality of the food source. In this study, we compared the single and interactive effects of diet quality and temperature on the feeding behavior and C and N intake and release of a common and abundant intertidal mixotrophic protist, the foraminifer Haynesina germanica. Two batches of artificially produced and dual isotope-labeled (13C/15N) chlorophyte detritus with different C:N ratios (5.6 and 7.1) were fed to the foraminifer at 3 different temperatures (15, 20, 25C). We observed a strong interactive effect of temperature and diet. A very strong increase in feeding rates was observed at 20C for the low-quality food source. Respiration rates of carbon derived from the low-quality diet (C:N ratio of 7.1) were lower than those of the high-quality diets and increased at 25C. This indicates that a high C content of the diet might be of advantage in calcifying mixotrophs, since respired excess C could be advantageous for test calcification. Additionally, respired excess C could be a useful resource of CO2 for kleptoplast photosynthesis and functionality in the mixotrophic lifestyle of H. germanica. Further, the observed effects of diet and temperature could impact nutrient fluxes in the habitat of H. germanica, possibly leading to food-web shifts in the future.

Research areas: Ecosystems
Widespread phytoplankton blooms triggered by 20192020 Australian wildfires (2021)

Droughts and climate-change-driven warming are leading to more frequent and intense wildfires13, arguably contributing to the severe 20192020 Australian wildfires4. The environmental and ecological impacts of the fires include loss of habitats and the emission of substantial amounts of atmospheric aerosols57. Aerosol emissions from wildfires can lead to the atmospheric transport of macronutrients and bio-essential trace metals such as nitrogen and iron, respectively810. It has been suggested that the oceanic deposition of wildfire aerosols can relieve nutrient limitations and, consequently, enhance marine productivity11,12, but direct observations are lacking. Here we use satellite and autonomous biogeochemical Argo float data to evaluate the effect of 20192020 Australian wildfire aerosol deposition on phytoplankton productivity. We find anomalously widespread phytoplankton blooms from December 2019 to March 2020 in the Southern Ocean downwind of Australia. Aerosol samples originating from the Australian wildfires contained a high iron content and atmospheric trajectories show that these aerosols were likely to be transported to the bloom regions, suggesting that the blooms resulted from the fertilization of the iron-limited waters of the Southern Ocean. Climate models project more frequent and severe wildfires in many regions13. A greater appreciation of the links between wildfires, pyrogenic aerosols13, nutrient cycling and marine photosynthesis could improve our understanding of the contemporary and glacialinterglacial cycling of atmospheric CO2 and the global climate system.

Research areas: Water Quality, Wildfires
Relationship of the Ozone Mini-Hole Over Siberia in January 2016 to Atmospheric Blocking (2021)

Using satellite data and reanalysis data, the characteristics and mechanisms of the formation of an ozone mini-hole in the atmosphere over Siberia in the winter of 20152016 have been investigated. The relationship between the regional negative anomaly of the total ozone content (TOC), reaching 140 Dobson units, with atmospheric blocking was established. The TOC anomaly was mainly due to a decrease in the ozone content in the lower stratosphere, reaching 50% near the 70 hPa level. With the key contribution of atmospheric dynamic processes to the formation of the ozone mini-hole, the possibility of the contribution of ozone destruction in heterogeneous reactions on the surface of polar stratospheric clouds, due to a strong decrease in temperature in the stratosphere above the blocking region, was noted.

Research areas: Atmospheric/Ocean Indicators
The Influence of Climate Change on River Corridors in Drylands: The Case of the Tehuacan-Cuicatlan Biosphere Reserve (2021)

The Tehuacan-Cuicatlan Biosphere Reserve, Mexico (TCBR) is the southernmost arid or semi-arid zone with the highest biodiversity in North America and is a UNESCO World Heritage site. Two main hydrographic streams cross the TCBR, the Salado River (an endogenous river) and the Grande River (an exogenous river). This study investigated temperature anomalies over the past 40 years. We analyzed potential differences between sub-basins and riparian areas on both streams using various indices, namely the Global Warming Index (GWI), Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), and Normalized Difference Drought Index (NDDI), and analyzed the potential relationship of these indices with climate change. Time series of satellite-based precipitation (June 2000December 2020) and air temperature (January 1980December 2020) were analyzed. A set of Landsat 8 OLI TIRS imagery from the driest and wettest months (20132020) was used to estimate NDVI, NDWI, and NDDI. These indices were evaluated separately for the sub-basins and river corridors in the dry and rainy seasons. The precipitation records indicate that in the Grande river sub-basin, precipitation is higher than in the Salado river sub basin. Normalized temperature anomalies and the GWI suggest a warming trend from 1994 to 2020, increasing up to 0.86C in the Salado River and 0.52C in the Grande River. The Grande and Salado sub basins showed significant differences between dry and wet seasons for each index (NDVI, NDWI, and NDDI). A Discriminant Analysis showed that the Salado sub-basin and the Salado River corridor are associated with severe drying conditions in the dry season (highest NDDI values). In the wet season, the Grande River corridor showed intermediate values of NDVI and NDWI but low values of NDDI. The Grande River corridor in the dry season was characterized by intermediate values of NDVI, NDWI, and NDDI. These river corridors provide environmental services in a trade-off with the stream and should be considered biodiversity hotspots. Due to the accentuated warming trend and the lowest precipitation, the Salado River sub-basin showed desertification signs associated with climate change. Both the Salado and the Grande River corridors showed resilience strategies to face climatic conditions.

Research areas: Atmospheric/Ocean Indicators, Land Surface/Agriculture Indicators, Habitat Conversion/Fragmentation
Tropical cyclones shape mangrove productivity gradients in the Indian subcontinent (2021)

Recent literature on the impact of cyclones on mangrove forest productivity indicates that nutrient fertilizations aided by tropical cyclones enhance the productivity of mangrove forests. We probe the implications of these predictions in the context of Indian mangroves to propose potential future directions for mangrove research in the subcontinent. First, we look at the time series trend (20002020) in satellite-derived gross primary productivity (GPP) datasets for seven mangrove forests across the countrys coastline. Second, we compare seasonal changes in soil nutrient levels for a specific site to further the arguments proposed in the literature and investigate the role of potential drivers of mangrove productivity. We find overall increasing trends for GPP over the past two decades for all seven mangrove sites with seasonal fluctuations closely connected to the tropical storm activities for three sites (Bhitarkanika, Pichavaram, and Charao). Additionally, organic carbon and nitrogen levels showed no significant trend, but phosphorus levels were higher during the post-monsoon-winter period for Bhitarkanika. Our findings expand the predictions of previous studies that emphasized the role of storm-induced nutrient fluxes and freshwater supply as primary drivers of productivity gradients in mangroves. Our study provides insights on how mangrove productivity may change with fluctuating frequency and magnitude of cyclones under a changing climate, implying the need for more mechanistic studies in understanding the long-term impact on mangrove productivity in the region.

Research areas: Severe Storms, Ecosystems
Impact of COVID-19 induced lockdown on land surface temperature, aerosol, and urban heat in Europe and North America (2021)

The outbreak of SARS CoV-2 (COVID-19) has posed a serious threat to human beings, society, and economic activities all over the world. Worldwide rigorous containment measures for limiting the spread of the virus have several beneficial environmental implications due to decreased anthropogenic emissions and air pollutants, which provide a unique opportunity to understand and quantify the human impact on atmospheric environment. In the present study, the associated changes in Land Surface Temperature (LST), aerosol, and atmospheric water vapor content were investigated over highly COVID-19 impacted areas, namely, Europe and North America. The key findings revealed a large-scale negative standardized LST anomaly during nighttime across Europe (0.11 C to 2.6 C), USA (0.70 C) and Canada (0.27 C) in MarchMay of the pandemic year 2020 compared to the mean of 20152019, which can be partly ascribed to the lockdown effect. The reduced LST was corroborated with the negative anomaly of air temperature measured at meteorological stations (i.e. 0.46 C to 0.96 C). A larger decrease in nighttime LST was also seen in urban areas (by 12 C) compared to rural landscapes, which suggests a weakness of the urban heat island effect during the lockdown period due to large decrease in absorbing aerosols and air pollutants. On the contrary, daytime LST increased over most parts of Europe due to less attenuation of solar radiation by atmospheric aerosols. Synoptic meteorological variability and several surface-related factors may mask these changes and significantly affect the variations in LST, aerosols and water vapor content. The changes in LST may be a temporary phenomenon during the lockdown but provides an excellent opportunity to investigate the effects of various forcing controlling factors in urban microclimate and a strong evidence base for potential environmental benefits through urban planning and policy implementation.

Research areas: Heat
Long-term spatial and temporal variations of aerosol optical depth during 20002020 over Zambia, southcentral Africa (2021)

The study aimed at using Moderate Resolution Imaging Spectroradiometer (MODIS-Terra) to investigate long-term spatial and temporal aerosol variations over Zambia during 20002020. Based on data availability, ground truthing for MODIS-Terra was done over Mongu in western Zambia using Aerosol Robotic Network (AERONET) data for 20012009. The correlation coefficient between MODIS-Terra and AERONET is 0.42 and statistically significant at 95% confidence level. The aerosol optical depth at 550nm (AOD550) and Angstrom exponent (AE470-870) annual mean spatial distribution indicates high and moderate to low patterns explaining distinct features of aerosol loadings from different areas over Zambia. Generally, the AOD550 and AE470-870 spatial gradient values increase from southern to northern Zambia explaining fine mode particles mainly produced by local intensive anthropogenic and urban/small and large-scale industrial emission activities in the cities. Seasonal climatology reveals that highest AOD550 is observed during SON, followed by JJA, DJF, with the lowest recorded during MAM. It is also observed from AE470-870 that fine particles are prominent during JJA and SON. The insignificant decreasing (increasing) trend of AOD550 is revealed over Mwinilunga, Misamfu, Mfuwe, Choma, and Kabwe (Mongu). Further results showed that fire hotspot density intensifies over central parts of Africa, including Zambia from June to November. Moreover, the 5-day air mass back trajectory analysis suggests that aerosol sources over Zambia are associated with short- and long-distance ranges from East Africa, Congo Basin, Madagascar, and Atlantic and Indian oceans with diverse transport pathways in different seasons. These findings may help enhance a better understanding of climatic effects and atmospheric aerosol sources in Zambia.

Research areas: Validation
A machine learning approach for spatiotemporal imputation of MODIS chlorophyll-a (2021)

The Moderate Resolution Imaging Spectroradiometer (MODIS) level-3 chlorophyll-a (Chl-a) product is one of the widely used ocean colour products that is often used for water quality monitoring of marine ecosystems. However, this product includes a large amount of missing data due to high surface reflectance and cloudy conditions that inevitably affect its suitability for spatiotemporal analysis of water quality. The objective of this study was to compare four Machine Learning (ML) techniques including K-nearest neighbour (KNN), Support Vector Regression (SVR), Random Forest Regression (RFR), and Artificial Neural Network (ANN) with well-known Data Interpolation Empirical Orthogonal Function (DINEOF) method for spatiotemporal missing imputation of MODIS Chl-a. The Southern Caspian Sea, which has a high Chl-a concentration, was selected as the case study. A cross-validation approach ranging missing data ratio from 0.1 to 0.8 was implemented to investigate the optimal parameters of the models and compare their performance for missing imputation. The results indicated that all ML models, except KNN, outperformed the DINEOF method for missing imputation of MODIS Chl-a. The SVR with the highest accuracy and the lowest variability of errors had the best performance among the five competing models, while the KNN showed the worst performance. The main reason for the better accuracy of the SVR than the other models is its structural risk minimization procedure that leads to the better generalization of the SVR model. The current results showed that the ML techniques used in the current study, the SVR in particular, are able to produce reliable imputations of the MODIS Chl-a missing data and can be a useful tool in water quality monitoring of marine ecosystems.

Research areas: Validation
Biological carbon pump efficiency enhanced by atmospheric dust deposition in the North Pacific Subtropical Gyre (2021)

We examine the flux and composition of sinking particles collected at 4500 m depth in the southeastern part of the North Pacific Subtropical Gyre (NPSG) from August 2011 to June 2012. Satellite-derived net primary production was higher in JanuaryMay 2012 compared with the rest of the study period. Both the biogenic and lithogenic particle fluxes were significantly higher in spring (MarchMay 2012) than at other times. The export efficiency via the transfer of produced organic carbon to the deep ocean interior (i.e., carbon sequestration) doubled during this time. Two prominent particle flux peaks were observed in March and May 2012, coinciding with the atmospheric dust-deposition peaks within the temporal resolution of the data. Coincident increases in the biogenic and lithogenic particle fluxes suggest that dust deposition in the NPSG enhances the biological carbon-pump efficiency. Strong coupling between the particulate organic carbon and biogenic opal fluxes implies that nutrient supply via atmospheric dust deposition stimulated diatom growth in this area. Dust deposition during the productive season therefore plays an important role in carbon sequestration.

Research areas: Water Quality
Long term trend in aerosol direct radiative effects over Indian Ocean region from multi- satellite observations (2021)

Long-term (20002020) trend in aerosol optical depth (AOD) and the associated radiative effect over Indian Ocean region (Arabian Sea and Bay of Bengal) during winter time south Asian outflow is investigated using multi-satellite data. Analysis revealed a statistically significant increasing trend of 0.01 year1 over the study regions. This study revealed that aerosols are confined within 2 km from ocean surface, and the trend in columnar AOD is significantly modulated by aerosol loading at higher altitudes. Although there has been no significant change in aerosol direct radiative forcing efficiency, the significant enhancement in AOD over the study region has induced an increase in cooling at the top of the atmosphere by 0.1 to 0.2 W m2 year1.

Research areas: Atmospheric/Ocean Indicators
The Increasing Trend of Black Carbon and Organic Carbon in Jordan During the Period of 2007 to 2018 (2021)

During the last decades, carbonaceous aerosol extinctions such as black carbon and organic carbon
extinctions exhibit an increasing trend across the globe. Measurements of carbonaceous aerosol in
Jordan were done using satellite data during the period 2007 to 2018. These measurements were done
in four locations of Jordan - Irbid in the north, Amman and Az-Zarqa in the middle, and Maan in the
south. Black carbon extinction in Jordan increased slightly (slope = 0.0001) during this period, while
organic carbon extinction increased slightly (slope = (0.7  10) x10 -5 ) in three locations and decreased
slightly in one location (Irbid location (slope = -2x10 -5 )). Organic carbon extinction measurements were
greater than black carbon extinction measurements in all locations with varying ratios depending on the
location of the measurements. Black carbon and organic carbon scattering measurements have the
same behavior as extinction, with larger values in the north and smaller values in the south. Scattering
values of organic carbon are larger than black carbon scattering values. Scattering values of organic
carbon increased slightly in all locations (slope = 0.0001) while scattering values of black carbon
decreased in three locations (Irbid, Amman, and Maan) and increased in one location (Az-Zarqa).
Column mass density and surface mass concentration measurements show that organic carbon had
larger values than black carbon in all locations besides that both organic carbon and black carbon had
values decreasing when we go from north to south.

Research areas: Air Quality
Extreme Aerosol Events at Mesa Verde, Colorado: Implications for Air Quality Management (2021)

A significant concern for public health and visibility is airborne particulate matter, especially during extreme events. Of most relevance for health, air quality, and climate is the role of fine aerosol particles, specifically particulate matter with aerodynamic diameters less than or equal to 2.5 micrometers (PM2.5). The purpose of this study was to examine PM2.5 extreme events between 1989 and 2018 at Mesa Verde, Colorado using Interagency Monitoring of Protected Visual Environments (IMPROVE) monitoring data. Extreme events were identified as those with PM2.5 on a given day exceeding the 90th percentile value for that given month. We examine the weekly, monthly, and interannual trends in the number of extreme events at Mesa Verde, in addition to identifying the sources of the extreme events with the aid of the Navy Aerosol Analysis and Prediction (NAAPS) aerosol model. Four sources were used in the classification scheme: Asian dust, non-Asian dust, smoke, and other. Our results show that extreme PM2.5 events in the spring are driven mostly by the dust categories, whereas summertime events are influenced largely by smoke. The colder winter months have more influence from other sources that are thought to be largely anthropogenic in nature. No weekly cycle was observed for the number of events due to each source; however, interannual analysis shows that the relative amount of dust and smoke events compared to other events have increased in the last decade, especially smoke since 2008. The results of this work indicate that, to minimize and mitigate the effects of extreme PM2.5 events in the southwestern Colorado area, it is important to focus mainly on smoke and dust forecasting in the spring and summer months. Wintertime extreme events may be easier to regulate as they derive more from anthropogenic pollutants accumulating in shallow boundary layers in stagnant conditions.

Research areas: Air Quality