nasa-gesdisc/es-publications-researchareas huggingface dataset:
Investigating ground deformation due to a series of collapse earthquakes by means of the PS-InSAR technique and Sentinel 1 data in Kandy, Sri Lanka (2023)

Time series interferometry synthetic aperture radar (InSAR) techniques have rarely been applied to detect displacement due to low-magnitude (5.5  M) earthquakes. This study exploits the combined permanent scatterer (PS) interferometry (PS-InSAR) and differential interferometry (D-InSAR) methods to investigate the deformation rates due to low-magnitude partial series of collapse earthquakes. Kandy, the hill capital of Sri Lanka, was experiencing a series of collapsed earthquakes. Historical geological evidence of dynamic topography with prolonged vertical movement further promotes the initiatory InSAR investigation. A series of Sentinel 1A images from the years 2019 to 2021 were employed. Initial D-InSAR near-zero baseline analysis suggested possible displacement in the range of 10 mm / year and +2 mm / year for subsidence and uplift, respectively. Using these prior motion velocities, the temporal coherence was optimized in PS-InSAR. Variogram models and ordinary Kriging (OK) were employed to predict deformation for the areas with limited PS detection. Descending orbits images PS show a dominant uplift of +20 mm / year, which are concentrated over Kandy urban areas. Movements along the ascending line of sight at Victoria Dam in the south are in the range of 40 mm / year. Slopes along the Mahaweli river lineament to the east show subsidence in the range of 29 to 36 mm / year. The coregistered landslide hazard map of Kandy shows deformation areas are exposed to landslide risk. Changes in terrestrial and ground water levels measured with the gravity recovery and climate experiment/GRACE-Follow-On during the period reveal significant irregularities. The study can be considered a prototype example that can be extended to investigate low-magnitude incomplete collapse earthquakes in different geological and geotechnical setups for ground deformation.

Research areas: Earthquakes, Land Surface/Agriculture Indicators
Assessment of irrigation water distribution using remotely sensed indicators: A case study of Doho Rice Irrigation Scheme, Uganda (2023)

The rising competition for scarce land and water resources and the need to satisfy the global food demand from an ever-growing population necessitates novel methods to monitor irrigation scheme performance for improved water use efficiency. The traditional methods employed in sub-Saharan Africa to assess irrigation performance are point-based, expensive, and time-consuming, making monitoring and evaluation of these capital-intensive projects difficult. This study aimed at employing satellite data with high spatial and temporal resolution in assessing the performance of Doho Rice Irrigation Scheme through estimations of actual evapotranspiration. Actual evapotranspiration (ETa) was modelled from Landsat 7 imagery using the surface energy balance system algorithm on five clear days between January and April 2020. Using equity and adequacy metrics, the derived ETa was used to assess the irrigation performance of the scheme. Results showed that the equity indicator was generally fair, with the coefficient of variation between 0.11 and 0.08, close to the 0.10 threshold implying irrigation water is fairly distributed within the scheme. The average adequacy was 0.87, above the 0.65 threshold, indicating adequate water supply throughout the scheme. The study's findings can be used in future research and benchmarking with other irrigation schemes to address the country's water resource management challenges.

Research areas: Habitat Conversion/Fragmentation
The current regime of heat waves and their impact on the yield of cereal crops in Ukraine (2022)

Heat waves are one of the most dangerous meteorological phenomena, the manifestations of which have become more frequent in all regions of the globe in recent decades. Due to excessively high temperatures persisting for a long time, heat waves cause heat stress in living organisms and plants, and negatively affect various sectors of the national economy. Although the mechanism of heat wave formation is well known, the question of determining and predicting the intensity and duration of these processes in advance, as well as the areas of their propagation, remains open, including due to the lack of unified concept of a heat wave. This study analyzed the spatiotemporal distribution of extremely warm days and heat waves for the period 1996-2021 in 16 regions of Ukraine, where the production of the main agricultural crops (winter wheat, spring barley, corn) is concentrated. The analysis was performed using the surface skin temperature Ts, which contains information about the temperature of both the canopy and ground surface.
It was found that during the study period, the number of extremely warm days increased in all regions of the country and in all seasons of the year, with the most significant increase occurring in the last decade in winter and autumn. The warmest year was 2020, when the number of extremely warm days in some regions reached 100-106 per year. The frequency of heat waves at the end of the study period almost doubled compared to the beginning, reaching an average of 8-10 cases per year. The average seasonal frequency of heat waves was 4-5 cases in summer and 2-4 cases in other seasons. The longest heat waves lasting 17-19 days were recorded in all agro-climatic zones in August 2010. In other seasons, the maximum duration of heat waves did not exceed 10-14 days.
Statistical assessment of the relationship between the seasonal number of extremely warm days and the grain yield crops showed that an increase in these days in the spring leads to decrease in the yield crops of winter wheat and spring barley; in summer this negative impact is observed for corn.

Research areas: Heat, Agriculture
Effect of Greenhouse Gases on Human Health (2022)

Greenhouse gases (GHGs) are the essential component for our planet earth to maintain an ambient condition for our survival. These gases in collaboration form an atmospheric layer which protects direct UV rays from reaching the earth. Human activities have increased the use of these gases artificially for many commercial purposes. Along with global warming and climate change greenhouse gases have adverse impacts on human health. Although human body has the capacity to cope with short-term exposure of these gases, long-term high concentration exposure becomes detrimental. The chronic exposure slowly affects multiple different organs primarily including the respiratory system, cardiovascular system, the central nervous system (CNS), the immune system, the digestive system and often the reproductive system. This chapter summarizes the mechanism of action and the adverse effects of greenhouse gases on human health and the primary target organs in an attempt to better understand the consequences of our actions.

Research areas: Greenhouse Gases, Public Health
Improved air quality leads to enhanced vegetation growth during the COVID19 lockdown in India (2023)

The direct effect of pandemic induced lockdown (LD) on environment is widely explored, but its secondary impacts remain largely unexplored. Therefore, we assess the response of surface greenness and photosynthetic activity to the LD-induced improvement of air quality in India. Our analysis reveals a significant improvement in air quality marked by reduced levels of aerosols (AOD, 19.27%) and Particulate Matter (PM 2.5, 23%) during LD (2020)from pre-LD (MarchSeptember months for the period 20172019). The vegetation exhibits a positive response, reflected by the increase in surface greenness [Enhanced Vegetation Index (EVI, +10.4%)] and photosynthetic activity [Solar Induced Fluorescence (SiF, +11%)], during LD from pre-LD that coincides with two major agricultural seasons of India; Zaid (MarchMay) and Kharif (JuneSeptember). In addition, the croplands show a higher response [two-fold in EVI (14.45%) and four-fold in SiF (17.7%)] than that of forests. The prolonged growing period (phenology) and high rate of photosynthesis (intensification) led to the enhanced greening during LD owing to the reduced atmospheric pollution. This study, therefore, provides new insights into the response of vegetation to the improved air quality, which would give ideas to counter the challenges of food security in the context of climate pollution, and combat global warming by more greening.

Research areas: Land Surface/Agriculture Indicators, Air Quality
Analytical Approach of Haematology in Variation to Physical Parameters of Indian Mackerel and Yellowfin Tuna from Indian Waters (2023)

Study of haematology assists to understand the relationship of an organism amid the blood parameters with the habitat, as well as its susceptibility to the environment. Yellowfin tuna and Indian mackerel are two important commercial fish species in the Indian waters. Studies of haematological parameters of these two species were done from two locations, that is, the Arabian Sea and the Bay of Bengal, respectively. The purpose outlined in this study is to assess the health status of both fishes and to observe the relative similarity among the various haematological parameters. One-time sampling was done in March 2021 from Andaman and Nicobar Islands, Odisha, Kerala and Lakshadweep Islands simultaneously using requisite craft and gear. Blood samples of Indian mackerel and yellowfin tuna were taken from all these specimens and analysed for haematology. All the parameters showed a certain degree of variation, with WBC (white blood cells) in tunas dominating. Statistical analysis revealed that all the parameters were distinctly related and shared a relatively high degree of closeness. Bray-Curtis dendrogram showed maximum similarity between Andaman and Nicobar Islands and Kerala. Chlorophyll data derived through remote sensing gave a positive correlation with haematological and physio-chemical parameters. Overall, the study provides a comprehensive account of the haematology in fish which gives a positive state of the fish as well as base information for future studies from these areas. This data can be used to draw the similarities or differences between fishes from tropical water at a global scale.

Research areas: Ecosystems
Hydrological Model Evaluation of Ground, GPM IMERG, and CHIRPS precipitation data for Shabelle Basin in Ethiopia (2023)

Consistent and accurate precipitation measurement is a fundamental input component of the hydrological model. However, most developing countries, including Ethiopia, lack consistent and precise precipitation measurements. Nevertheless, satellitebased precipitation data may play a crucial role in bridging the data gap and providing precipitation inputs for rainfall-runoff models in regions with limited ground data. The study compares the ground precipitation data from the Ethiopian meteorological agency and SWALIM to the satellite-based GPM_IMERG and CHIRPS precipitation products. HECHMS software was used to model rainfall-runoff simulation, and the study areas spatial characteristics and model development were processed with ArcGIS and HEC- GeoHMS. Since the data on hand is enough and fit for continuous event assessment, the deficit and constant loss method, a continuous event-based loss method, was tested, and found good model performance results. The onhand 14 years of precipitation and discharge data were divided into seven years for calibration and seven years for validation. Using NashSutcliffe efficiency (ENS), coefficient of determination (R2), Root Mean Square Error (RMSE), and percentage bias objective functions, the performance of the satellite precipitation was evaluated. During calibration periods (Jan 2013 to Dec 2009), the model performance showed ENS values of 0.65, R2 values of 0.68, RMSE values of 0.6, a percent bias of 0.58% for the metrological stations, ENS values of 0.61, R2 values of 0.64, RMSE values of 0.6, a percent bias of 5.38% for CHIRPS, and ENS values of 0.63, R2 values of 0.66, RMSE values of 0.7, and a percent bias of 18.9% for GMP_IMERG satellite precipitation products. During validation periods (Jan 2010 to Dec 2016), the model performance showed ENS values of 0.75, R2 values of 0.78, RMSE values of 0.6, a percent bias of -16.9% for the metrological stations, ENS values of 0.71, R2 values of 0.74, RMSE values of 0.6, a percent bias of -22.12% for CHIRPS2, and ENS values of 0.76, R2 values of 0.76, RMSE values of 0.5, and a percent bias of -0.03% for GPM_IMERG satellite precipitation products. The study showed that the HEC-HMS model performed well and gave very good results for the hydrological model for the CHIRPS and GPM_IMERG rainfall products. The study also indicates that the model outperformed well during the validation period. Overall, the study found that the simulated GPM_IMERG product gave better results than the simulated CHIRPS product.

Research areas: Validation
Changing PM2.5 and related meteorology over India from 19502014: a new perspective from a chemistry-climate model ensemble (2023)

Surface PM2.5 concentrations in India have increased dramatically as emissions have risen in recent years. The role of meteorological factors in this increase is unclear, mainly due to a lack of long-term observations over the region. A 12-member ensemble of historical (19502014) simulations from the Community Earth System Model version 2-Whole Atmosphere Community Climate Model version 6 (CESM2-WACCM6) offers an unprecedented opportunity to examine simulated PM2.5 and meteorology for 20th century climates that can arise due to climate noise under the same historical greenhouse gas and air pollutant emission trajectories. CESM2-WACCM6 includes interactive aerosol and gas-phase chemistry in the atmosphere coupled to ocean-sea ice-land models, and each ensemble member differs only in its initial conditions of the climate state. We systematically examine, decade-by-decade, the changes in PM2.5 and associated meteorology, including wind speed, surface temperature inversions, boundary layer height, precipitation, and relative humidity in four cities in India: Chennai, Kolkata, Mumbai, and New Delhi. Forced changes clearly emerge in meteorological variables from 1950 to 2014, including increases in both relative humidity and temperature inversion strength, and decreases in boundary layer height and average surface wind speed. The timing of these changes varies by city: boundary layer heights decrease most over New Delhi in the premonsoon season (ensemble average decrease of 400 m), but over Mumbai in the postmonsoon season (ensemble average decrease of 100 m). PM2.5 concentrations increase across India regardless of climate variability, with an almost threefold increase from 1950 to 2014 over New Delhi. Analysis of dimensionless variables shows that PM2.5 exhibits larger ensemble mean trends and smaller variability than the trends in the meteorological variables, enabling us to infer that the increase in PM2.5 is predominantly controlled by increases in anthropogenic emissions rather than climate variability. Overall, our simulations corroborate the dominant role of air pollutant emissions on poor air quality in India.

Research areas: Air Quality, Environmental Impacts
Spectral Aerosol Radiative Forcing and Efficiency of the La Palma Volcanic Plume over the Izana Observatory (2023)

On 19 September 2021, a volcanic eruption began on the island of La Palma (Canary Islands, Spain). The eruption has allowed the assessment of an unprecedented multidisciplinary study on the effects of the volcanic plume. This work presents the estimation of the spectral direct radiative forcing (F) and efficiency (FEff) from solar radiation measurements at the Izana Observatory (IZO) located on the island of Tenerife (140 km from the volcano). During the eruption, the IZO was affected by different types of aerosols: volcanic, Saharan mineral dust, and a mixture of volcanic and dust aerosols. Three case studies were identified using ground-based (lidar) data, satellite-based (Sentinel-5P Tropospheric Monitoring Instrument, TROPOMI) data, reanalysis data (Modern-Era Retrospective Analysis for Research and Applications, version 2, MERRA-2), and backward trajectories (Flexible Trajectories, FLEXTRA), and subsequently characterised in terms of optical and micro-physical properties using ground-based sun-photometry measurements. Despite the F of the volcanic aerosols being greater than that of the dust events (associated with the larger aerosol load present), the FEff was found to be lower. The spectral FEff values at 440 nm ranged between 1.9 and 2.6 Wm2nm1AOD1 for the mineral dust and mixed volcanic and dust particles, and between 1.6 and 3.3 Wm2nm1AOD1 for the volcanic aerosols, considering solar zenith angles between 30 and 70, respectively.

Research areas: Volcanic Eruptions, Sun-Earth Interactions
GIS-Based Urban Traffic Assessment in a Historical European City under the Influence of Infrastructure Works and COVID-19 (2023)

Urban areas have developed organically over time, driven by the economic success of cities. However, this development has usually been accompanied by the side effects of urbanization, such as increased traffic and its associated problems: traffic congestion, increased accident rates and pollution. As urban populations grow and expand, the importance of GIS lies in its ability to collect a large amount of geospatial data, including human-generated data. This data is necessary to understand the complexity of the city, set priorities, solve complicated planning problems and perform a variety of spatial analysis, which shows not only the feasibility but also the consistency of the proposed infrastructure with the requirements of a sustainable city. In this paper, we demonstrate the benefits of integrating real-time traffic data with GIS technology and remote sensing data for analyzing the impact of infrastructure works and COVID-19 on traffic in Oradea, Romania. The case study was focused on the historical center of Oradea and was based on remote sensing data collected before, during, and after traffic restrictions. The study also shows the need for using GIS and crowdsourcing-based applications in traffic analysis and planning.

Research areas: Habitat Conversion/Fragmentation
Variations of multiple gaseous emissions associated with the great Sumatra earthquakes in 2004 and 2005 (2023)

Three-dimensional (3D) temporal variations and correlation analysis of CO, CH4 and O3 concentrations associated with the 26 December 2004 Sumatra-Andaman MW 9.1 Earthquake and 28 March 2005 Sumatra-Nias MW 8.6 Earthquake offshore of Sumatra, Indonesia were investigated using satellite data from AQUA AIRS in order to understand the lithospheric and atmospheric interactions during seismic activities. These great earthquakes occurred in the subduction zone northwest of the Sumatra Island. It was observed that large amounts of gases were emitted from the Earth's crust into the atmosphere before, during and after the earthquakes compared to the earthquake-free periods and background areas. Anomalies in CO, CH4 and O3 concentrations occurred along the NW-trending Sumatra fault system and peak values were found in the epicenter areas. Temporally, the anomalies occurred from 3 months before the Sumatra-Andaman Earthquake to 1 month after the Sumatra-Nias Earthquake and they lasted for 7 months. The correlation coefficients between the gas parameters increased with the period closer to the earthquake occurrence. More CO and CH4 were emitted from the epicenter area and O3 was produced in the background area during earthquake preparation period and occurrence reflected in the correlation analysis. The data indicated that the gaseous anomalies were most probably attributed to the gas emissions caused by the two great earthquakes that were accompanied by intense tectonic activities and fractures produced in the crust. After the underground gases were emitted into the atmosphere, they underwent a series of physical (diffusion, convection, etc.) and chemical reactions, which consequently lead to the gases (e.g. CO, CH4 and O3) anomalies at different altitudes in the atmosphere. The results are helpful in improving the judgment ability to understand geochemical earthquake anomalies and understanding the mechanism of lithosphere-coversphere-atmosphere-ionosphere coupling (LCAIC).

Research areas: Earthquakes
How to Measure the Amount of Aerosol Optical Thickness in the Atmosphere in a Simple Way: A Calitoo Handheld Sun-Photometer Measurement (2023)

To have useful information about the effects of atmospheric particles on visibility degradation, extinction of solar radiation, climate changes, and tropospheric corrections in remote sensing, aerosol optical thickness (AOT) plays a crucial role. So, the measurement of AOT is an essential task for atmospheric physicists. In this regard, this article presents a systematic way in a simple form using a Calitoo handheld sun-photometer (SPM) to study atmospheric AOT. Zanjan city is selected for a period of six months as an example due to existing reference data for comparison. Hence, we use a schedule distributed in seven times, including 8:00, 9:30, 10:45, solar noon, 13:45, 15:30, and 17:00 in local time. The used wavelengths for recording are 465, 540, and 619 nm. Our data analysis shows that the mean value for AOT at those wavelengths are 0.25, 0.21, and 0.20, respectively. Also, the mean Angstrom exponent (AE) extracted from the AOTs at 465, and 619 nm is 0.80. Accordingly, AE versus AOT plot demonstrates that most of the particles in Zanjans atmosphere are classified as urban industrial (64%) and dust plus mixed (36%) particles. In addition, to have a metric, a comparison between the AOT extracted from simultaneous measurements of Calitoo handheld and Cimel automatic SPMs is employed that indicates a strong correlation (r = 0.99) between them. Furthermore, OMI, Aqua MODIS, and Terra MODIS AOT products are compared with the Calitoo SPM AOT data. The results reveal that there is a better relationship between MODIS and Calitoo data than OMI. This study leads us to conclude that it can open new insights by simple instruments to study the atmospheres that are unknown to scientists due to the limitations of geographical stations.

Research areas: Validation
Synoptic view of an unprecedented red Noctiluca scintillans bloom in the Beibu Gulf, China (2023)

An unprecedented red Noctiluca scintillans (RNS) bloom in February 2021 in the Beibu Gulf, China was investigated using multi-sensor imagery. The location and spatial extent of the RNS patches were delineated based on the spectral signature. A combination of satellite remote sensing and numerical model data over the region was used to detect and monitor the development and progress of the RNS bloom and figure out the possible mechanism. Multi-sensor satellite imagery demonstrates a total coverage area of >20,000 km2 for the two-phase bloom event from Feb 13 to 26, with abrupt dissipation on Feb 17 and reappearance on Feb 20. Analysis of the initialization mechanism of the bloom suggests that nutrients conveyed from the western coast of Guangdong through Qiongzhou Strait and from convective transport in the offshore area together stimulated the outbreak of the bloom. The most distinctive finding is the negative correlation between the area of RNS patches and wind speed. The abrupt disappearance of the RNS bloom deserves further study.

Research areas: Water Quality, Ecosystems