nasa-gesdisc/es-publications-researchareas huggingface dataset:
Structural resistance and functional resilience of the Chaco forest to wildland fires: an approach with MODIS time series (2020)

Forests have resistance that allows them to resist fires without changing to another state, and resilience that allows them to recover after disturbance. These properties are determined by many structural and functional determinants that interact between them. Despite the importance of structural resistance and functional resilience to wildland fires, few studies have evaluated the combined effect that structural and functional determinants have on them. Our goal was to assess the structural resistance and functional resilience to fire using remote sensing information. We specifically assessed the combined effect of pre-fire vegetation characteristics, burn severity, and post-fire precipitation on forest structural resistance and functional resilience to fire. Eighty-five forest plots of 250 m  250 m were selected in areas that burned in 2003. For each burned plot, a paired unburned control plot of 250 m  250 m was selected outside the burned areas. We measured burn severity and post-fire precipitations (20042011). We analysed MODIS time series in order to calculate the following pre- (2002) and post-fire (2011) phenological parameters: minimum level of photosynthetic activity per year; maximum level of photosynthetic activity per year; length of growing season per year; integral of annual photosynthetic activity; relative seasonality of photosynthetic activity. Also we detected plots that changed into a shrubland eight years after the fire. Fifty three per cent of burned plots changed from forest into a shrubland state. Results show that the forest structural resistance to fire depends on the balance between the level of severity and the parameters related to pre-fire aboveground net primary production. The impact of pre-fire vegetation characteristics on functional resilience ability was driven by burn severity and its interactions with pre-fire productivity and seasonality. Results suggest that changes in forest species composition and aboveground net primary production reduced forest structural resistance and functional resilience to fire.

Research areas: Wildfires
Spatiotemporal analysis of absorbing aerosols and radiative forcing over environmentally distinct stations in East Africa during 20012018 (2023)

East Africa (EA) suffers from the inadequate characterization of atmospheric aerosols, with far-reaching consequences of its inability to quantify precisely the impacts of these particles on regional climate. The current study aimed at characterizing absorption and radiative properties of aerosols using the long-term (20012018) AErosol RObotic NETwork (AERONET) and Modern-Era Retrospective analysis for Research and Applications (MERRA-2) data over three environmentally specific sites in EA. The annual mean absorption aerosol optical depth (AAOD440 nm), absorption Angstrom Exponent (AAE440870 nm), total effective radius (REff), and total volume concentration (m3/m2) revealed significant spatial heterogeneity over the domain. The study domain exhibited a significant contribution of fine-mode aerosols compared to the coarse-mode particles. The monthly variation in SSA440 nm over EA explains the strength in absorption aerosols that range from moderate to strong absorbing aerosols. The aerosols exhibited significant variability over the study domain, with the dominance of absorbing fine-mode aerosols over Mbita accounting for 40 to 50 %, while weakly absorbing coarse-mode particles accounted for 8.2 % over Malindi. The study conclusively determined that Mbita was dominated by AAOD mainly from biomass burning in most of the months, whereas Malindi was coated with black carbon. The direct aerosol radiative forcing (DARF) retrieved from both the AERONET and MERRA-2 models showed strong cooling at the top of the atmosphere (TOA; 6 to 27 Wm2) and the bottom of the atmosphere (BOA, 7 to 66 Wm2). However, significant warming was noticed within the atmosphere (ATM; +14 to +76 Wm2), an indication of the role of aerosols in regional climate change. The study contributed to understanding aerosol absorption and radiative characteristics over EA and can form the basis of other related studies over the domain and beyond.

Research areas: Atmospheric/Ocean Indicators, Environmental Impacts
Long-term climatology and spatial trends of absorption, scattering, and total aerosol optical depths over East Africa during 20012019 (2022)

The unprecedented increase in anthropogenic activities, coupled with the prevailing climatic conditions, has increased the aerosol load over East Africa (EA). Given this, the present study examined the trends in total, absorption, scattering, and total aerosol extinction optical depth (TAOD, AAOD, SAOD, and TAEOD) over EA, alongside trends in single scattering albedo (SSA). For this purpose, the AOD of different optical properties retrieved from multiple sensors and the Modern-Era Retrospective Analysis for Research and Applications (MERRA-2) model between January 2001 to December 2019 were utilized to estimate trends and assess their statistical significance. The spatial patterns of seasonal mean AOD from the Moderate-resolution Imaging Spectroradiometer (MODIS) sensor and MERRA-2 model were generally characterized with high (>0.35) and low (<0.2) AOD centers over EA observed during the local dry and wet seasons, respectively. Also, the spatial trend analysis revealed a general increase in TAOD, being positive and significant over the arid and semi-arid zones of the northeastern part of EA, which is majorly dominated by locally derived dust. The local dry (wet) months generally experienced positive (negative) trends in TAOD, associated with seasonal cycles of rainfall. High and significant positive trends in AAOD were dominated over the study domain, attributed to an increased amount of biomass burning, variations in soil moisture, and changes in the rainfall pattern. The trends in TAEOD showed a distinct pattern, except over some months that depicted significant increasing trends attributed to changes in climatic conditions and anthropogenic activities. At last, the study domain exhibited decreasing trends in SSA, signifying strong absorption of direct solar radiation resulting in a warming effect. The study revealed patterns of trends in aerosol optical properties and forms the basis for further research in aerosols over EA.

Research areas: Atmospheric/Ocean Indicators, Environmental Impacts
Uncertainty quantification of multi-source hydrological data products for the improvement of water budget estimations in small-scale Sakarya basin, Turkey (2022)

The present study aims to improve the efficacy of water budget (WB) estimations from various hydrological data products, by (1) evaluating the uncertainties of hydrological data products, (2) merging four precipitation and six evapotranspiration products using their error variances, and (3) employing the constrained Kalman filter (CKF) method to distribute residual errors among water budget components based on their relative uncertainties. The results show that applying bias correction before the merging process improved estimations of precipitation products with decreasing root mean square error (RMSE), except Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN). Variable Infiltration Capacity (VIC) and bias-corrected Climate Prediction Center Morphing Technique (CMORPH) products outperformed other evapotranspiration and bias-corrected precipitation products, respectively, in terms of mean merging weights. The terrestrial water storage change is the primary reason for non-closure errors, mainly caused by the coarse resolution of Gravity Recovery and Climate Experiment (GRACE). The CKF results were insensitive to variations in uncertainties of runoff. Precipitation derived from the CKF was the best precipitation output, with the highest correlation coefficient (CC) and smallest root mean square deviation (RMSD).

Research areas: Validation
Photosynthetic trends in India derived from remote sensing measurements during 20002019: vegetation dynamics and key climate drivers (2022)

Significant changes in the photosynthesis of terrestrial vegetation are observed in recent decades due to climate variability, land use and land cover changes, frequent disasters and anthropogenic forcing, but this situation in the Indian context remains largely unexplored. Here, therefore, we estimate the longterm changes in photosynthesis and its key climate drivers in India. The gross photosynthetic activity peaks (FPAR mean = 0.57) in postmonsoon (September, October and November) due to high soil moisture (87.26 kg/m2), good precipitation (5.2 mm/day) and optimum temperature (21.46 C) conditions, whereas it is smallest (FPAR mean = 0.4) in summer (March, April and May) due to very high temperature (27.37 C) and lower soil moisture (55.45 kg/m2). The trend in FPAR over 20002019 reveals enhanced photosynthetic activity in India. In the northwest, both soil moisture and temperature have a positive influence on greening (i.e. moisture induced greening). Conversely, the unfavourable soil moisture and temperature conditions dominate in the peninsular region to trigger browning there (i.e. warming induced moisture stress). Our analyses suggest that the photosynthetic trend is primarily controlled by trend in the soil moisture (44.31%) and air temperature (32.54%). The warming induced moisture stress can be a serious threat in the future to drive browning in more areas. Extreme events such as droughts, landslides and fires are expected to increase in the hilly regions such as the northeast due to browning. Furthermore, as food production and forest resources influence the economy of a country like India, management and conservation of greenery are inevitable for a sustainable ecosystem.

Research areas: Land Surface/Agriculture Indicators
Investigation on the role of aerosols on precipitation enhancement over Kerala during August 2018 (2022)

Previous studies based on satellite data and model analysis have shown that the dust over Arabian Sea correlates positively with the Indian summer monsoon. During August 2018, over a period of a few days from August 13, the state of Kerala experienced anomalous rainfall, which was followed by heavy floods. In the present study, the meteorological factors and the aerosol conditions during this event are investigated. MERRA 2 reanalysis data suggests that the dust loading over the Arabian Sea during the month of August, during which the anomalous event of rainfall took place, is the highest in the last decade. Using CALIPSO aerosol vertical profiles, OMI Absorbing Aerosol Index and the HYSPLIT back trajectory analysis, higher altitude dust transport from the arid gulf region towards the Arabian sea and near to Kerala coast is confirmed during the heavy precipitation days and even prior to that. Changes in cloud properties like Cloud Fraction (CF), Cloud Top Temperature (CTT), Cloud Water Liquid Water Path (CWLWP) and Cloud Condensation Nuclei (CCN) with AOD variations during the period clearly indicate that there is a close relation between the aerosols and the cloud properties over the region. Observed CWLWP in the study on August 14 and 15, 2018 was 80% higher than the monthly average value. CCN concentration was increased by 23 percent during the severe rainy days of August when the CTT was about 16 K lower than the monthly mean value. Dust aerosols at altitudes of 24 km and further higher at 1015 km, along with the deep convective clouds, point to the possibility of aerosol-cloud-precipitation interaction under conducive meteorological conditions. INSAT- 3D temperature profiles show an interesting enhancement of temperature (1 K) at altitudes  3 km, where elevated dust layers are noticed. This elevated heating could pave the way for moisture convergence and it is further confirmed from the INSAT derived Relative Humidity profiles. Investigation of vertical winds shows strong updrafts over the region during the period of heavy precipitation, indicative of the coexistence of moisture and CCN at higher altitudes. The study infers that the moisture built up over the region was excessive, enough to overwhelm the commonly observed semi direct effect caused by aerosols, and in contradiction, the aerosols amplify the cloud cover and precipitation over the Kerala region during the period of study. Thus the heavy dust loading over the South Eastern Arabian Sea region, near the west coast of Kerala, together with the conducive meteorological conditions and orography of the region led to intensified precipitation over Kerala during the mid of August 2018.

Research areas: Atmospheric/Ocean Indicators
Spatio-temporal distribution of pollutant trace gases (CO, CH4, O3 and NO2) in India: an observational study (2022)

India is one of the largest contributors to anthropogenic emissions during the recent decade associated with its rapid economic growth in India. Trace gases are important components in the climate change process and due to that climate change, there will be a change in their atmospheric concentrations as the climate is sensitive to Earths; therefore, proper assessment of trace gases is necessary for ongoing sudden changes in climate. In this study, we used remote-sensing datasets from the Atmospheric Infrared Sounder (AIRS) and Ozone Monitoring Instrument (OMI) to analyze the spatio-temporal variations of four trace gases, like methane (CH4), ozone (O3), carbon monoxide (CO), and nitrogen dioxide (NO2) over India region during 20062015 and taken four seasons (i.e., winter, spring, summer, and winter) to interpret the seasonal variation. The project focuses on the temporal pattern of pollutant trace gases i.e., monthly, seasonal, and annual mean variations of trace gases, trend analysis of trace gases, and a comparison of the seasonal behavior of the trace gases by trend analysis was assessed. Higher concentrations of CO show east-to-west, CH4 show north-to-south, and O3 south-to-north gradient, indicating the variations in trace gases due to the impact of emissions and local meteorology. On the other hand, due to immense population density, huge traffic emissions, tremendous, polluted air, and overgrown industrial activities, total NO2 concentrations shoot up over Delhi, Lucknow, and Kolkata. Now as a result of seasonal variation in the long-range transport of air parcels and biomass burning activities, all trace gases shown significant seasonal variations in the spring season and substantially reduced in the summer season. However, in the winter season, O3 concentration evaluates minimum due to less amount of heat on cold days which leads to the reduction of O3 formation. Due to trace gases, all are significant to get regional climate variability. In this study by taking 2006 as a base year and investigate the behaviors of gases for 20072015 years to exhibit the increment and decrements in four seasons of all trace gases by taking the most populated 11 different cities of India.

Research areas: Air Quality, Environmental Impacts
The Dust Comportment in the Latitudinal Band 10 North - 20 North in Africa: Emission and Deposition (2022)

The three measurement periods: the TOMS Nimbus-7 TOMSN7L3 v008 from 1978 to 1993, the TOMS EP TOMSEPL3 v008 from 1996 to 2005 and the OMI OMTO3d v003 from 2004 to 2008 have allowed the presence of dust to be observed in the 10 North to 20 North latitudinal band (10 - 20 band) of Africa. The 10 - 20 band has a permanent dust presence. The AERONET data show AOD peaks exceeding 2 in Senegal and Niger (on an AOD scale). The statistical study reveals intra-annual relationships in deposition. In Senegal, a significant deposition is observed.

Research areas: Air Quality
Impact of dust accumulation and deposits on polycrystalline solar panel: Case of Senegal (2022)

This study focuses on the Sahel, one of the areas with the highest concentration of desert dust, with source areas having fine particle emissions in Chad, Niger, Mauritania, etc. It also includes areas of subsidence of air masses that promote the deposition of dust, such as Senegal. It turns out that the countries of Sahel are among the poorest in the world. They have a relatively low electrification rate. However, this area is also characterized by its good solar potential which makes it an ideal place for the installation of photovoltaic solar collectors. Senegal has launched the challenge to solve this problem of electrification by turning to renewable energies. But being a drop zone, the sensors on the ground will be impacted. This study defines the impact of the thickness of the dust deposit layer on a polycrystalline photovoltaic sensor. By looking at the behaviour of irradiation and aerosol deposition in Senegal with the ERA5 and Giovanni data, the intra-annual profile of deposition and irradiation in Senegal was established. By applying the results obtained on the climatology of these parameters to a monocrystalline solar photovoltaic collector, it was contrasted that the evolution of the power, as well as the yield of the collector was strongly impacted by the accumulation of the deposit after 5 years. The power delivered by the collector went from 59.779 W during the month of the 1st year of accumulation to 4.28 W during the last month of the 5th year of accumulation. The resulting yield is also affected. More detailed illustrations are given in this work.

	 

	Key words: Dust, accumulation, photovoltaic, polycrystalline, efficiency, Senegal.

Research areas: Sun-Earth Interactions, Energy Production/Use
Impact of prevailing atmospheric conditions on diurnal variability of the pre-monsoon rainfall over a tropical location, Kolkata (2022)

The annual rainfall amount over Gangetic West Bengal is predominantly determined by monsoon (June to September) and pre-monsoon (March to May) rain events. Consequently, such seasonal precipitation is directly linked to the socio-economic advancement of the area. In this paper, some characteristics of pre-monsoon rainfall over a tropical urban location, Kolkata have been explored utilizing ground-based observations. Pre-monsoon rainfall over Kolkata is characterized by convective rain events and thunderstorms, mostly occurring from afternoon to night (15:30 IST  21:30 IST) span. Emphasis has been given to the set-in time of pre-monsoon rain events, based upon which they are classified as expected (14:30 IST  18:30 IST) and delayed (after 18:30 IST). Efforts have been made to assess the sustaining atmospheric conditions (in terms of temperature, water vapour, liquid water content and instability parameter) associated with such rain events prevailing over two non-overlapping time spans of pre-monsoon season. The mean diurnal variations of integrated water vapour (IWV), liquid water path (LWP), and instability parameter, namely, convective available potential energy (CAPE) during the expected and delayed rain event dates show distinct intensity in the increasing trends prior to the respective rainfall peaks. It has been observed that for the delayed events, the temperature difference between ground and 2000 m altitude begins to fall at a later part of the evening in comparison with the expected ones. Overall the investigated parameters exhibited distinguishable nature of variations for the two classes of rain events over the study location.

Research areas: Atmospheric/Ocean Indicators
Mapping marine habitats in the Gulf of Guinea: A contribution to the future establishment of Marine Protected Areas in Principe Island (2023)

Accurate mapping of marine benthic habitats, using acoustic technologies such as Side-Scan Sonar (SSS), is a useful tool for marine conservation and management, as well as to support zoning processes of maritime activities in the coastal environment. Georeferenced habitat maps can improve management of isolated tropical coastal and marine ecosystems, where rapid unsustainable anthropogenic coastal development often occurs. In this study, SSS was employed to map subtidal marine habitats of Principe Island (Gulf of Guinea, West Africa) to determine areas of especial interest for biodiversity or marine resource conservation. The SSS methodology was applied, during the BIO-Principe Scientific Expedition (2016), in four target areas, both inside and outside its UNESCO Biosphere Reserve, covering 675 ha between 3 and 30 m depth, also combining SCUBA diving and video transects. These areas were chosen based on their geographical location and habitat information, provided by the local stakeholders. Over the total surface mapped, five main habitats were recorded: sandy seabeds (flat sandbanks and rippled sandbanks), rhodolith seabeds (rhodoliths interspersed with scleractinian coral colonies and macroalgae), biogenic (mud/sedimentary) seabeds, and rocky seabed (bedrock and rocky reefs). In the northern, eastern, and southern areas of the island, sandy bottoms with ripples, interspersed with small biogenic sedimentary beds and rhodolith bottoms predominated. The southwestern area, Baia das Agulhas, concentrated the greatest variability and richness of habitats, including the largest rhodolith seascape. This study provided a consistent and detailed dataset to support the creation and design of future MPAs, already planned by the Principes government, adding including essential information on areas containing key habitats (e.g. rhodoliths) not detected in previous reports.

Research areas: Ecosystems
Assessment of satellite products for filling rainfall data gaps in the Amazon region (2021)

Rainfall data series with adequate quality and length are often incomplete or nonexistent. Thus, filling in rainfall gaps becomes necessary to complete databases. This article proposes the use of satellite products (TRMMTropical Rainfall Measuring Mission, CHIRPSClimate Hazards Group InfraRed Precipitation with Stations and CMORPHCPC Morphing Technique) to fill gaps in the rainfall historical series. The simple regression method, using satellite rainfall estimates, was tested to fill the missing data from 164 rainfall gauge stations in the Amazon region. Large dispersions were observed between rainfall data, with R2 ranging from 0.383 to 0.844, the best results were found in areas with less rainfall. As well, the greatest performance of the products was verified in the dry period, with r and d higher than 0.899 and 0.950, respectively. The product with the best representation in the region was CHIRPS, which had the lowest monthly values of mean absolute error (0.979 mm) and root mean square error (3.656 mm). The results confirm that the satellite estimates satisfactorily represent the seasonal variation of rainfall in the region, despite presenting cases of overestimation and underestimation of data. The higher performance of CHIRPS can be explained by the higher spatial resolution (0.05), allowing for more accurate weather forecasts. In fact, CHIRPS has the CHPclim model, which adds other factors to the good product performance. These characteristics justify the better performance of the CHIRPS product for filling gaps in daily rainfall data in the Amazon region, favoring the best monthly rainfall estimates for each region state analyzed. Recommendations for Resource Managers Satellite products have been increasingly used for estimating rainfall data in regions with a low number of installed rainfall gauge stations. Thus, the assessment and selection of these products needs to be elaborated for the best decision making of water resource managers. Rainfall data are important to recognize the occurrence patterns for prediction of the climatic behavior of a region. Sectors such as agriculture and disaster prevention (droughts, floods, erosion of watersheds, and river silting) need knowledge of rainfall for planning, management, and mitigation. Knowledge of rainfall behavior is very important in the Amazon region. In this case, the dry season and temperatures have been increasing due to global climate change. These changes establish conditions for more intense fires, which increases the deforestation of the region.

Research areas: Validation