nasa-gesdisc/es-publications-researchareas huggingface dataset:
Monitoring temporary ponds dynamics in arid areas with remote sensing and spatial modelling. (2010)

A hydrologic pond model was developed that simulates daily spatial and temporal variations (area, volume and height) of temporary ponds around Barkedji, a village located in the Ferlo Region in Senegal. The model was tested with rainfall input data from a meteorological station and from Tropical Rainfall Measuring Mission (TRMM) satellites. During calibration phase, we used climatic, hydrologic and topographic field data of Barkedji pond collected daily during the 2002 rainy season. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Digital Elevation Model (DEM) and a QuickBird satellite image acquired in August 2005 (2.5 m pixel size) were used to apply the hydrologic model to all ponds (98 ponds) of the study area. With input rainfall data from the meteorological station, simulated water heights values for years 2001 and 2002 were significantly correlated with observed water heights for Furdu, Mous 2 and Mous 3 ponds, respectively with 0.81, 0.67 and 0.88 Nash coefficients. With rainfall data from TRMM satellite as model input, correlations were lower, particularly for year 2001. For year 2002, the results were acceptable with 0.61, 0.65 and 15 0.57 Nash coefficients for Barkedji, Furdu and Mous 3 ponds, respectively. To assess the accuracy of our model for simulating water areas, we used a pond map derived from Quickbird imagery (August 2007). The validation showed that modelled water areas were significantly correlated with observed pond surfaces (r2=0.90). Overall, our results demonstrate the possibility of using a simple hydrologic model with remote sensing data (Quickbird, ASTER DEM, TRMM) to assess pond water heights and water areas of a homogeneous arid area.

Research areas: Validation
Model assessment and verification (2010)

Clustering of observed winds and classification of simulated winds were used for meteorological and air quality model evaluation. We simulated meteorology with MM5 and particulate matter (PM) with CMAQ for December to January 20002001 in the San Francisco Bay Area (SFBA). EOFs were used to classify simulated winds among the patterns identified by a previous clustering of observations. We investigated the match between the classification of the simulated winds and the original clustering. Agreement between the clustering of observed winds and the classification of simulated winds implies model validity. Disagreement serves as a diagnostic tool, indicating how inaccurately modeled winds may explain degraded air quality model performance. This novel framework complements traditional model validation methods.

Research areas: Validation
Long-term spatio-temporal trends in atmospheric aerosols and trace gases over Pakistan using remote sensing (2023)

One of today's most important environmental problems is air pollution augmentation. Air pollution is getting worse over time and hurts human health. For the current study, various polar orbiting satellites were utilized to collect data on PM2.5, SO2, AOD, CO, and ozone over Pakistan between January 2005 and December 2021. According to the spatial distribution results, these characteristics have high values throughout central Punjab, western Baluchistan, central Sindh, and Khyber Pakhtunkhwa. The seasonal variation in PM2.5, SO2, AOD, CO, and ozone was calculated using monthly data. The greatest value for PM2.5 is 8.7  108 kg/m3 during the monsoon season, while the highest value for SO2 is 1.4  105 kg/m2 during the winter. Over Punjab, Sindh, Baluchistan, KPK, and Gilgit, AOD was between 0.7 and > 1.0, CO was 127.2 ppb, and ozone was 330.7 DU. Furthermore, we create correlation maps of AOD, CO, SO2, PM2.5, and ozone and evaluate their relationship of high and low values across Pakistan. We looked into the 0.99 correlation between AOD and PM2.5, the strongest ever recorded. Despite this, we look at time series graphs to show the rising and falling pattern of these parameters from January 2005 to December 2021. We also used tables to determine the relative change in Multan, Lahore, Karachi, Peshawar, Quetta, Rawalpindi, Faisalabad, Hyderabad, Gujranwala, and Abbottabad in Pakistan from January 2005 to December 2021.

Research areas: Air Quality
Investigating the unprecedented summer 2022 penetration of the Indian monsoon to Iran and evaluation of global and regional model forecasts (2023)

The Indian Summer Monsoon (ISM) significantly impacts the climate of the Asian continent. During the summer of 2022, the penetration of monsoonal waves towards higher latitudes led to severe and unprecedented floods in various parts of Iran, Pakistan, and southern Afghanistan. In this study, we utilized meteorological data from weather stations, satellite remote sensing, reanalysis data, and teleconnection indices to investigate the penetration of monsoonal waves at higher latitudes in Iran. We also employed outputs from two global models, the Global Forecast System (GFS) and Climate Forecast System (CFS), and the Weather Research and Forecasting Model (WRF) regional model, to examine their forecasts of heavy monsoon rains. Our analysis of teleconnection indices revealed that La Ni   na, combined with a negative or neutral Dipole Mode Index (DMI) and a positive Indian Monsoon Index (IMI), intensified monsoon-related rainfall in the region. The low-pressure system over India weakened, while the system over central Iran strengthened. Additionally, we observed a meridional rotation of the Somali low-level jet. Generally, southern to southwestern Iran, as well as central and eastern regions, receive moisture from the Arabian Sea due to southerly and easterly winds from water surfaces. Comparing forecasts with 27 days lead times and extended 1015 days from the CFS and GFS global models demonstrated that neither of models accurately predicted the observed range of rainfall over Iran in the extended period. However, the WRF regional model predictions were significantly better. We also discovered that the 48-hour forecast from the WRF model outperformed other forecasts for this case study.

Research areas: Atmospheric/Ocean Indicators, Validation
Impact of urbanization and land-use/land-cover change on diurnal temperature range: A case study of tropical urban airshed of India using remote sensing data (2015)

Diurnal temperature range (DTR) is an important climate change index. Its knowledge is important to a range of issues and themes in earth sciences central to urban climatology and humanenvironment interactions. The present study investigates the effect of urbanization on the land surface temperature (LST) based DTR. This study presents spatial and temporal variations of satellite based estimates of annually averaged DTR over megacity Delhi, the capital of India, which are shown for a period of 11 years during 20012011 and analyzes this with regard to its land-use/land-cover (LU/LC) changes and population growth. Delhi which witnessed massive urbanization in terms of population growth (decadal growth rate of Delhi during 20012011 was 20.96%) and major transformations in the LU/LC (built-up area crossed more than 53%) are experiencing severity in its micro and macroclimate. There was a consistent increase in the areas experiencing DTR below 11 C which typically resembled the urban class viz. from 26.4% in the year 2001 to 65.3% in the year 2011 and subsequently the DTR of entire Delhi which was 12.48 C in the year 2001 gradually reduced to 10.34 C in the year 2011, exhibiting asignificant decreasing trend. Rapidly urbanizing areas like Rohini, Dwarka, Vasant Kunj, Kaushambi, Khanjhawala Village, IIT, Safdarjung Airport, etc. registered a significant decreasing trend in the DTR. In the background of the converging DTR, which was primarily due to the increase in the minimum temperatures, a grim situation in terms of potentially net increase in the heat-related mortality rate especially for the young children below 15 years of age is envisaged for Delhi. Considering the earlier findings that the level of risk of death remained the highest and longest for Delhi, in comparison to megacities like Sao Paulo and London, the study calls for strong and urgent heat island mitigation measures.

Research areas: Habitat Conversion/Fragmentation, Atmospheric/Ocean Indicators, Heat, Public Health
Impact of land use/land cover (LULC) changes on latent/sensible heat flux and precipitation over Turkiye (2023)

Landuse and land cover (LULC) changes have some implications on landatmosphere interactions, surface energy budget, and hydrological cycle. The understanding of LULC changes and their interactions with the environment provide better management of agriculture, forests, and water resources. LULC changes are frequently observed in developing countries such as Turkiye and much research has been conducted in this field. However, few studies investigated the countrywide LULC changes and their interactions with energy fluxes and precipitation. In this paper, LULC changes in Turkiye over the last two decades have been evaluated by utilizing an Enhanced Vegetation Index (EVI) derived from the Terra satellite. The latent and sensible heat fluxes were obtained from the Modern-Era Retrospective analysis for Research and Applications (MERRA-2) reanalysis datasets. Precipitation data were acquired from the Tropical Rainfall Measuring Mission (TRMM) satellite. The results showed that EVI has an increasing trend over Turkiye between 2000 and 2021, while climate changeinduced desertification, droughts, and forest fires have threatened the vegetative cover in some portions of the country. The latent heat flux has a rising trend due to increasing vegetative cover and irrigated areas. A slight reduction was observed in sensible heat flux, while a sharp increase was witnessed in specific humidity. EVI represented a high positive correlation (R = 0.84) with sensible heat flux and a moderate positive correlation (R = 0.69) with latent heat flux. No significant relation was determined between EVI and precipitation on a monthly basis.

Research areas: Habitat Conversion/Fragmentation
Impact of elevated aerosol layer on the cloud macrophysical properties prior to monsoon onset (2013)

Atmospheric aerosols alter the radiation balance by absorption/scattering of solar radiation, and indirectly by modifying the cloud microphysical properties. Observations during the Cloud Aerosol Interaction and Precipitation Enhancement Experiment (CAIPEEX) provide a unique opportunity to investigate the aerosolecloud interaction in a dry to wet transition phase prior to the onset of southwest monsoon. It is observed that aerosol loading increased over the central Indian region in spite of the increase in surface rainfall. This aerosol loading was observed mainly in the 2e5 km level above surface. The origin and influence of elevated aerosol layer have been investigated with the help of WRF-Chem simulations by conducting sensitivity experiments for dust emissions, modified based on the satellite observations. To enhance the dust emissions, the erodible fraction over the Thar Desert region is enhanced to an average factor of 1.7 based on TOMS aerosol index (AI) and USGS land use category, which contributed to enhanced dust emissions by a factor of 1.25 over the study region. This enhancement of dust emission from Thar Desert can result in an increased radiative heating due to elevated aerosol layers, which leads to an increase in the ice mixing ratio and ice water content in the regions of dry to wet transition. It is shown that even natural dust emissions (without changes in anthropogenic emissions) may also influence the spatial and temporal distribution of cloud and precipitation and the hydrological cycle.

Research areas: Atmospheric/Ocean Indicators
Impact of COVID-19 on spatio-temporal variation of aerosols and air pollutants concentration over India derived from MODIS, OMI and AIRS (2023)

The atmospheric aerosols and air pollutants affect the earth's atmosphere, human health and climate system. Human-induced aerosols and air pollutants are the major causes of the deterioration of air quality. The COVID-19 lockdown restricted the movement of people and vehicles, stopped industrial and agricultural activities and may have impacts on the aerosols in the atmosphere. Spatio-temporal map of MODIS Terra AOD_550 nm, OMI Aura UVAI, Ozone, NO2,SO 2 and AIRS CO during the lockdown illustrates the significant reduction in their concentration. During the lockdown, the North India shows a record reduction of over 20% in Aerosol Optical Depth and Aerosol Index values. A substantial decrease in AOD and AI was also observed in Eastern and Western parts of India. The average AOD value were reduced from 1.36 (20162019) to 1.09 (2020) over India during the lockdown. The satellite-retrieved aerosol variables over India recorded lowest AOD values on 29th March, 2020 (0.2566) and 21st April 2020 (0.2591). Similarly, air pollutants CO, NO2 and SO2 also significantly reduced in India. Despite all variables showing a reduction in concentration, Ozone recorded an increase in value during lockdown primarily over North and North-eastern parts of India. Western India recorded a substantial reduction in SO2 (47%) followed by Central India (31%). As pan India is considered, CO was reduced by 1%, NO2 reduced by 15.29% and SO2 was reduced by 26.82% during the lockdown period. This abrupt reduction in aerosol and air pollutants concentration over India was mainly due to the lockdown of COVID-19.

Research areas: Air Quality
Impact of Biomass Burning on Black Carbon and NO2 Over North Eastern Region of India Using Multi-satellite Observations (2023)

Large scale biomass burning like forest fires and crop residue burning can significantly impact the physical environment, including land cover, land use, ecology, habitats, and climate change. We investigated the effect of fire counts on surface Black Carbon mass concentration (BCC) and Tropospheric Columnar NO2 (TCN) over the North Eastern Region (NER) of India in the domain: 20 N30 N and 88 E98 E for 15 years from 2006 to 2020 using MODIS, MERRA-2 and OMI data. Significant fire counts are recorded in January, February, March, and April. An average of 65,000 fire counts is recorded in March and April during the 15 years of study over the domain. TCN is high in Mizoram, Manipur, and Nagaland, followed by Assam, Tripura, and Meghalaya in March and April, which varies from 18.79 9 1014 to 29.08 9 1014 cm-2 in March, 10.76 9 101415.81 9 1014 cm-2 in January and February, and 12.67 9 101414.2 9 1014 cm-2 in April. Spatially averaged BC varies from 1.80 to 2.76 lgm-3 in January and February and 1.822.36 lgm-3 in March. BCC is high in Mizoram, Tripura, Manipur, Nagaland, and Brahmaputra valley of Assam than in the rest of the NER.

Research areas: Environmental Impacts, Air Quality
Four decades of aviation visibility at Bhairahawa airport, gateway to Buddha's birthplace Lumbini, Nepal (2023)

Over four decades of visibility data at Bhairahawa airport (BWA), a recently upgraded international airport near Lumbini, a UNESCO heritage site in Nepal has been analyzed. In this study, we also investigated one of the important microclimatic behavior of fog i.e., onset and dispersal timings, and its implication on aviation. Temporal variations of poor visibility conditions at BWA are found to be primarily associated with variations in haze and fog. Haze at BWA accounts for the highest percentage (~27%) of time and its annual occurrence is increasing (0.57% yr 1). There is a significant upward trend of hazy days in all seasons, the highest (1.46% day yr 1) being in post-monsoon. The overall seasonal poor visibility, too, has increased significantly in all seasons, with the highest trend in post-monsoon (1.57% yr 1). Similarly, fog frequency in the winter season has also increased noticeably for fog days (1.05% day yr 1), dense fog days (0.51% day yr 1), general fog hours (0.55% hour yr 1) and dense fog hours (0.20% hour yr 1). We found that fog at BWA is usually formed overnight and dissipates before noon. Daytime onset and late dispersion of fog are more common in the peak winter months of December and January. Further, we investigated the relationship between visibility and aerosol optical depth (AOD) and found a moderate negative correlation (r = 0.66, p < 0.001) between them in the monsoon season. However, AOD is found to have a weaker correlation with visibility during winter (r = 0.36) and pre-monsoon (r = 0.23) seasons, when there is a more pronounced influence of meteorological conditions on the occurrence of visibility. We have observed a better correlation (r = 0.74) between fine particulate matter concentration (PM2.5) and visibility. Examining the effect of relative humidity (RH) on AOD (or, PM2.5) and visibility revealed that higher RH tends to lower visibility. Visibility at BWA airport is gradually worsening due to local and regional air pollution emissions and changing meteorological conditions. The degraded visibility at BWA airport will negatively impact flight safety and timeliness. Effective implementation of regionally coordinated air pollution mitigation measures can be a sustainable step towards the improvement of visibility in long run. However, the installation of ground equipment like CAT-II/III Instrument Landing System (ILS) for aircraft take-off and landings, and advanced surface movement guidance and control system (A-SMGCS) are highly advisable to lessen the damage potential to aviation.

Research areas: Air Quality
Forest Fire Emissions in Equatorial Asia and Their Recent Delay Anomaly in the Dry Season (2023)

In Equatorial Asia, forest fires are a significant contributor to greenhouse gas emissions. This study explains the conditions of forest fire emissions in Equatorial Asia and how they might connect to precipitation in the region. Integrated satellite and model data were used to relate to forest fire emissions. Several methods were applied to understand the spatial and temporal nature of emissions, namely time-series, time-averaged, correlation, and Hovmoller diagram. The results suggested that from 1980 to 2021, the emissions were generated from three regions: east of Sumatra Island, south and east of Borneo Island, and the capital city of Jakarta on Java Island. During this period, several massive emission events occurred in 1982, 1998, 2002, and 2006. South Borneo was the highest emitter for 41 years. Emissions in Sumatra and Borneo were mainly due to forest fires, while those in Jakarta were due to industries and transportation. The two main emitter islands, Borneo and Sumatra, have shown different strengths of correlation with precipitation. It is considered weak in East Sumatra, around  0.2, while South Borneo is stronger at about  0.5. However, from 2009 onward, Borneo had abnormal conditions, where carbon emissions remained low even in high forest fires. This is contrary to the previous decades. Apart from that, carbon emissions were also delayed after the rainy season. Borneos forest fire emissions were due to peat organic matter burning. From 2009 to 2021, there is a possibility that the peat had regained its ability to hold water, so carbon emissions became lower and delayed. This clearly shows that forest fires have been the main contributor to carbon emissions in Equatorial Asia for several decades, and precipitation plays a crucial role in it. The emissions can be reduced when the peat soil regains its capacity as water storage in long-term precipitation periods.

Research areas: Wildfires, Greenhouse Gases
Evaluation of TRMM 3B43v7 Satellite Precipitation in the Pantanal of Mato Grosso do Sul in the Years 1998 to 2019 (2023)

Remote sensing can assist in the acquisition of scarce surface data. The analyzes for validation of the precipitation product estimated by the TRMM satellite (Tropical Rainfall Measuring Mission) were carried out with the precipitation data observed on the surface during the period from 1998 to 2019. For this purpose, precipitation data from the Pantanal biome meteorological stations were used, located between the 16 and 22S parallels and the 55 and 58W meridians, and compared with the data from the TRMM 3B42 V7 product algorithms. Statistical analysis was performed based on the correlation coefficient, root mean square error (RMSE), and relative bias (BIAS) between the monthly precipitation data observed on the surface and the estimated precipitation data. The results found for product 3B43 V7 indicated that the precipitation estimates were representative when compared to the surface observations. However, when compared for the rainy and dry periods, there was underestimation and overestimation, respectively, of the product. The product 3B42 V7 satisfactorily represents the precipitation that occurs on the surface.

Research areas: Validation
Dissolved silicon and its isotopes in the water column of the Bay of Bengal: Internal cycling versus lateral transport (2015)

The concentration of dissolved Si and its isotope composition are measured in the Bay of Bengal (BoB) region of the northern Indian Ocean; the isotope data are the first data set from the northern Indian Ocean. The measurements are made in eight depth profiles closely along the 87E transect (GIO1 section of the international GEOTRACES program) and in a few samples from the northern shelf of the bay. Dissolved Si in the water column varies from  0.6 to  152.5 lmol/kg, whereas the d30Si data cover a range +1.2& to +3.6&. The depth profiles of dissolved Si show generally lower values in the surface increasing with depth, whereas the pattern reverses in the case of d30Si. These vertical distribution patterns of Si and d30Si are similar to those reported in other oceanic regions and suggestive of the significant role of biological processes in governing Si biogeochemistry in the upper layers (top  1500 m). In contrast, dissolved Si in near surface waters of the northern shelf and the southernmost station is exceptionally high. These results indicate a continental supply of dissolved Si from the GangaBrahmaputra river system (GB) and submarine groundwater discharge (SGD) to the shelf region, and an intrusion of high salinity waters from the Arabian Sea in the southern bay. The d30Si values of  1.34  0.10& for deep/bottom waters of the BoB (depth >1500 m) are similar to those reported for the deep Southern Ocean and indicate the dominant control of water mass mixing. The dissolved Si concentrations in the bottom waters of the BoB are generally higher than those of the water mass endmembers, which suggest the need for an additional source of Si; in situ particle dissolution and/or benthic release in the central bay seem to be the potential candidate. The annual Si budget in the top  100 m of the BoB seems to suggest that meso-scale eddies frequently occurring during non-monsoon periods can supply at the most  2.6 g Si/m2/year, which is about 33% of the Si requirement to support new production in the bay. The supply of dissolved Si ( 1.3  0.5   1011 mol/year) from the GB river system and SGD has been calculated based on the distributions of dissolved Si concentration and d30Si in the northern shelf waters. A comparison of this supply with the reported Si flux upstream of the estuarine zone indicates about 40% removal of dissolved Si in the GB estuary. The mass balance of Si isotopes in the deep waters indicates that the dissolution of diatoms is the main cause of excess Si in the bay.

Research areas: Ecosystems