nasa-gesdisc/es-publications-researchareas huggingface dataset:
Meteorological factors contributing to organic and elemental carbon concentrations in PM10 near an open-pit coal mine (2022)

Variations in the carbonaceous aerosol contents, organic carbon (OC) and elemental carbon (EC), in particulate matter less than 10 m in size (PM10), were analyzed at sites influenced by coal mining in an open-pit mine located in northern Colombia. Samples were collected during different seasonal periods throughout 2015. Meteorological variables for each site were examined during the different seasons. Aerosols were detected using a thermal-optical reflectance protocol method. The highest PM10 concentrations, between the ranges of 28.2  8.2 g m3 and 75.0  36.5 g m3, were recorded during the dry season. However, the highest concentrations of OC (4.814.2 g m3) and EC (2.913.9 g m3) in PM10 were observed during the transition period between the dry and wet seasons. The strong correlation between OC and EC in PM10 (r = 0.61.0) during the transition season indicates a common primary combustion source. High OC (> 8.3 g m3) and EC (> 6.9 g m3) concentrations were associated with low wind speeds (< 2.1 m s1) moving in different directions. Analyses of the sources of atmospheric aerosol pollutants in the mining area in northern Colombia showed that the daily maximum total carbon concentrations were mainly associated with regional atmospheric transport of particulate matter from industrial areas and biomass burning sites located in the territory of Venezuela.

Research areas: Energy Production/Use, Air Quality, Environmental Impacts
Mapping photovoltaic power plants in China using Landsat, random forest, and Google Earth Engine (2022)

Abstract. Photovoltaic (PV) technology, an efficient solution for mitigating the impacts of climate change, has been increasingly used across the world to replace fossil fuel power to minimize greenhouse gas emissions. With the world's highest cumulative and fastest built PV capacity, China needs to assess the environmental and social impacts of these established PV power plants. However, a comprehensive map regarding the PV power plants' locations and extent remains scarce on the country scale. This study developed a workflow, combining machine learning and visual interpretation methods with big satellite data, to map PV power plants across China. We applied a pixel-based random forest (RF) model to classify the PV power plants from composite images in 2020 with a 30 m spatial resolution on the Google Earth Engine (GEE). The resulting classification map was further improved by a visual interpretation approach. Eventually, we established a map of PV power plants in China by 2020, covering a total area of 2917 km2. We found that most PV power plants were situated on cropland, followed by barren land and grassland, based on the derived national PV map. In addition, the installation of PV power plants has generally decreased the vegetation cover. This new dataset is expected to be conducive to policy management, environmental assessment, and further classification of PV power plants. The dataset of photovoltaic power plant distribution in China by 2020 is available to the public at https://doi.org/10.5281/zenodo.6849477 (Zhang et al., 2022).

Research areas: Energy Production/Use
Development of a solar energy forecasting system for two real solar plants based on WRF Solar with aerosol input and a solar plant model (2022)

Regional meteorological models are becoming a generalized tool for solar energy production forecasting, due to their capacity to simulate different types of cloud formations and their interaction with solar radiation. The greater demand for reliable forecasting tools in the energy industry is the motivation for the development of an integrated system that combines the Weather Research and Forecasting atmospheric model package designed to fulfill the needs of solar energy applications (WRF-Solar), with the solaR power plant model. This study focuses on the use and validation of this coupled tool in forecasting the energy production for two real solar plants, one in Spain and another in India. A period of one year for the Spanish emplacement and nine months for the Indian site are simulated with a daily operational forecasting set-up. Aerosol data from the Copernicus Atmosphere Monitoring Service (CAMS) are considered in the calculations, a new capability in WRF-Solar. Power predictions are obtained and compared with real data from the inverters of both plants provided by the operating company. The results show that WRF-Solar obtains accurate forecasts of global, direct, and diffuse radiation and of the ambient temperature that solaR uses as input to predict the energy production of the solar plants. The normalized Mean Annual Errors (NMAE) is 5.18% in the Spanish and 5.59% in the Indian plant for the first day of predictions, demonstrating a reliable performance of the forecasting system in different climate locations. The skill scores for the second day of prediction are also promising, with practically the same errors as the previous day (5.19% and 6.17 for Spain and India respectively). By comparing the model predictions, with and without AOD input during the dustiest days in the Spanish site, the importance of the aerosol effect inclusion is demonstrated with an improvement up to 10% in the energy forecast. These results demonstrate the systems potential both for solar plant operation and energy market applications.

Research areas: Energy Production/Use, Sun-Earth Interactions
In-stream turbines for rethinking hydropower development in the Amazon basin (2021)

Given growing energy demands and continued interest in hydropower development, it is important that we rethink hydropower to avoid detrimental socioenvironmental consequences of large dams planned in regions such as the Amazon River basin. Here, we show that ~63% of total energy planned to be generated from conventional hydropower in the Brazilian Amazon could be harnessed using in-stream turbines that use kinetic energy of water without requiring storage. At five of the nine selected planned dam sites, the entirety of energy from planned hydropower could be generated using in-stream turbines by using only a fraction of the river stretch that large dams would affect. We find the cost (US$ kWh1) for in-stream turbines to be ~50% of the conventional hydropower cost. Our results have important implications for sustainable hydropower development in the Amazon and worldwide through transition to power generation methods that meet energy needs while minimizing the negative socioenvironment impacts.

Research areas: Energy Production/Use
Two-stage GIS-MCDM based algorithm to identify plausible regions at micro level to install wind farms: A case study of India (2022)

Efficiency of the installed wind farms is location-specific. Various research works used the concepts of Geographical Information Systems (GIS) and Multi-criteria-techniques (MCDM) to identify suitable locations. However, research works addressing the micro-level site selection are limited. This study proposes a two-stage GIS-MCDM based algorithm that can identify the plausible regions for installing wind farms at the microscopic level. The developed tool, built on the philosophy of fuzzy Analytical Hierarchy Process (FAHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), differentiates the regions based on technological, economic, social, and environmental aspects. For demonstration purposes, India is chosen as a study region, implying national-level analysis as stage-1 and state-wise analysis as stage-2. Results suggest that the suitable area for wind farm development in India is approximately 1805131 km2, out of which about 650 km2 is considered as highly suitable, and the following best has 330321 km2. The most suitable locations are in the western and southern parts of India, mainly in Gujarat and Tamil Nadu states. These findings of stage-2 present the hierarchy of plausible regions within each state. The developed tool is the first of its kind, help the decision-maker to extend it for siting solar farms and other energy sources.

Research areas: Energy Production/Use
Cost-reliability analysis of hybrid pumped-battery storage for solar and wind energy integration in an island community (2021)

This paper presents a mathematical model for estimating the optimal sizing and assessing a standalone hybrid power system's performance entirely based on variable renewable energy sources and coupled with a hybrid energy storage system. This study evaluates how different levels of the main components' capital cost and the loss of power supply probability would affect the cost of energy and the power system's optimal sizing. The case study selected for this study was Ometepe Island in Nicaragua, where the crater lake of an extinct volcano was considered a feasible upper reservoir of a pumped storage hydropower plant, reducing the investments associated with this component. The mathematical formulation considers energy storage losses and gains, and the Pareto efficient solutions of the multi-objective optimization model simultaneously increase reliability, reduce the cost of energy, and minimize curtailment energy. By employing time-series with an hourly resolution, the model allows assessing the impact of the interannual variability of renewable energy sources on the system's performance. As for the case study, the cost of energy obtained from the model results ranges between 0.047/kWh and 0.095/kWh, based on international reference values, and these values match the information available in the literature and other databases.

Research areas: Energy Production/Use
Assessment of solar and wind energy potential in Far North Queensland (2022)

The study aims at selecting suitable sites for solar and wind power developments in remote areas of Far North Queensland (FNQ), Australia. A Geographical Information System (GIS) based multi-criteria approach has been introduced to map potential locations for solar and wind, considering various aspects such as climatic, technical, topography, social, environmental, and economic. The potential of solar and wind energy in suitable land areas has been assessed based on the technologies and site conditions. Analysis of the present study shows that the total suitable areas in selected regions are 57,705.46 km<SUP>2</SUP> (70.56% of total selected land areas) with a power potential of 5,956.14 GW for solar and 58,482.79 km<SUP>2</SUP> (71.51% of total selected land areas) with a power potential of 421.12 GW for wind energy developments. In addition, the study shows that Carpentaria shire has the highest suitable area of 45,689.55 km<SUP>2</SUP> for solar and 46,115.27 km<SUP>2</SUP> for wind, while Injinoo shire has the lowest implementable area of 105.74 km<SUP>2</SUP> for solar and 137.75 km<SUP>2</SUP> for wind. This study provides a significant pathway for parties interested in investing in renewable energy in FNQ.

Research areas: Energy Production/Use, Sun-Earth Interactions
Small hydropower development potential in the Densu River Basin, Ghana (2022)

The study investigated potential sites for the development of Small Hydropower Systems (SHP) to augment the existing energy supply in the UDRB. Remote sensing and the Soil and Water Assessment Tool (SWAT) were employed to generate and simulate basin parameters for the hydropower analysis. The energy potential of suitable sites was evaluated using flow duration curves (FDC) and power duration curves (PDC). Results indicate that the upper DRB has potential for small hydropower development with nine sites along the river having an estimated combined firm power of 7.89 MW. The highest hydropower potential sites were located at HP1, HP7, and HP4 with corresponding firm energies of 13.39 GWh, 7.94 GWh, and 6.83 GWh and estimated annual energy production of 28.68 GWh, 14.36 GWh, and 12.68 GWh respectively. Given the adequate spacing distance between sites HP1 and HP4 (11.38 km) and HP4 and HP7 (11.31 km) with a combined annual energy production of 55.72 GWh, a cascade hydropower arrangement of sites HP1, HP4, and HP7 is recommended along the Upper section of the Densu River. However, based on the analysis, these hydropower sites could be developed as a cascade storage hydropower with a 50% or 75% dependability with an installed Francis turbine.

Research areas: Energy Production/Use
Mining Exports and Climate Variability Influencing Grace-Derived Water Storage Trend Estimates in Australia (2020)

GRACE and GRACE-FO satellites track the variations of Earth's gravity field since 2002. It is widely assumed that water transfers dominate such measurement, hence GRACE data is routinely used as an estimation of the Total Water Storage Change (TWS). Often, it is disaggregated to infer water storage changes in storage compartments such as glaciers, lakes, or aquifers. Here we show that, in Australia, two considerations are crucial for interpreting GRACE data. First, iron ore mining exports impact the gravity signal in the Northwest at a rate of -425 Mt/yr. Second, given the non-stationarity of the Australian climate, 15 years of gravity data are not sufficient to fully capture the climate variability and to depict a long-term vision of water storage trends for resilient water storage compartments such as large aquifers.

Research areas: Validation
Monitoring Wildfires in Forest and Grassland Related to Sugarcane Burning with Geotechnologies (2021)

Sugarcane is an important agro-industrial crop for the production of food, biofuels and bioproducts. However, the agricultural management of this crop generates significant socioeconomic and environmental impacts. The burning of sugarcane-cultivated fields, a practice used to facilitate planting and harvesting, is used extensively in Mexico and other sugarcane-producing countries but causes nitrogen volatilization, a decrease in microorganisms and organic material in the soils, and increased wildfires in forest ecosystems and respiratory health problems in surrounding areas. Academic evidence has shown that sugarcane harvesting with biomass burning is associated with the generation of GHGs and an increase in extreme weather conditions, such as rising temperatures and more frequent and prolonged droughts. These effects, in turn, have modified the structure of vegetation communities and ecosystems, as well as affected carbon and water cycles and the regional climate system and therefore the productivity and profitability of crops. The objective of this work was to determine the distribution patterns of wildfires and their impact on forest and rainforest areas near sugarcane crops in the Huasteca Potosina region, Mexico, during the period 20102020, using high and low spatial resolution satellite images. MODIS (Moderate Resolution Imaging Spectroradiometer) MCD64A1 satellite images were used to evaluate sugarcane-burnt areas impacted by drought to assess thermal anomalies, whereas Landsat 8 OLI images were used to calculate and monitor burned areas, both in sugarcane crops and in perimeter forests and rainforests. The products generated will serve to demonstrate the impact of sugarcane burning and help establish proposals for agroforestry sustainability to prevent, monitor, control and manage future wildfires.

Research areas: Wildfires, Environmental Impacts
Exceptional loss in ozone in the Arctic winter/spring of 2019/2020 (2021)

Abstract. Severe vortex-wide ozone loss in the Arctic would expose both ecosystems and several millions of people to unhealthy ultraviolet radiation. Adding to these worries, and extreme events as the harbingers of climate change, exceptionally low ozone with column values below 220 DU occurred over the Arctic in March and April 2020. Sporadic occurrences of low ozone with less than 220 DU at different regions of the vortex for almost 3 weeks were found for the first time in the observed history in the Arctic. Furthermore, a large ozone loss of about 2.03.4 ppmv triggered by an unprecedented chlorine activation (1.52.2 ppbv) matching the levels occurring in the Antarctic was also observed. The polar processing situation led to the first-ever appearance of loss saturation in the Arctic. Apart from these, there were also ozone-mini holes in December 2019 and January 2020 driven by atmospheric dynamics. The large loss in ozone in the colder Arctic winters is intriguing and demands rigorous monitoring of the region.

Research areas: Public Health
A high-resolution unified observational data product of mesoscale convective systems and isolated deep convection in the United States for 2004–2017 (2021)

Abstract. Deep convection possesses markedly distinct properties at different spatiotemporal scales. We present an original high-resolution (4 km, hourly) unified data product of mesoscale convective systems (MCSs) and isolated deep convection (IDC) in the United States east of the Rocky Mountains and examine their climatological characteristics from 2004 to 2017. The data product is produced by applying an updated Flexible Object Tracker algorithm to hourly satellite brightness temperature, radar reflectivity, and precipitation datasets. Analysis of the data product shows that MCSs are much larger and longer-lasting than IDC, but IDC occurs about 100 times more frequently than MCSs, with a mean convective intensity comparable to that of MCSs. Hence both MCS and IDC are essential contributors to precipitation east of the Rocky Mountains, although their precipitation shows significantly different spatiotemporal characteristics. IDC precipitation concentrates in summer in the Southeast with a peak in the late afternoon, while MCS precipitation is significant in all seasons, especially for spring and summer in the Great Plains. The spatial distribution of MCS precipitation amounts varies by season, while diurnally, MCS precipitation generally peaks during nighttime except in the Southeast. Potential uncertainties and limitations of the data product are also discussed. The data product is useful for investigating the atmospheric environments and physical processes associated with different types of convective systems; quantifying the impacts of convection on hydrology, atmospheric chemistry, and severe weather events; and evaluating and improving the representation of convective processes in weather and climate models. The data product is available at https://doi.org/10.25584/1632005 (Li et al., 2020).

Research areas: Atmospheric/Ocean Indicators
What's in a name? On the use and significance of the term “polar vortex” (2022)

Mainstream and popular science media are rife with misunderstandings about what a "polar vortex" is. The term most aptly describes the stratospheric polar vortex, a single feature dominating the cool-season circulation from ∼15-50 km. Regional jet stream variations dominate the tropospheric circulation, which is not well-described as a polar vortex; indeed, there is no single consistent definition of a tropospheric polar vortex in the literature. Stratospheric polar vortex disturbances profoundly influence extreme weather events, including cold air outbreaks (CAOs). How the stratospheric polar vortex affects tropospheric jets, whose local excursions drive CAOs, is not fully understood. Public-facing parts of publications describing research on this topic are not always clear about how the "polar vortex" is defined; greater clarity could improve communications both within the community and with non-specialist audiences.

Research areas: Atmospheric/Ocean Indicators
Climate Archives (2013)

After a brief introduction into the marine carbon cycle, the calcite compensation theory and the rain-ratio hypothesis, two theories that may explain glacial to interglacial changes in atmospheric CO2 concentrations are presented. The validity of these theories in the Southern Ocean is tested with B/Ca-reconstructed carbonate ion concentrations of deep and intermediate waters. Deglacial [CO32] excursions reveal a close relationship between changes in the oceanic inorganic carbon system and atmospheric CO2, which follow the predictions of the calcite compensation theory on glacial-interglacial timescales. Short-termed [CO32] variations are likely due to the influence of the biological pump and/or changes in circulation patterns.

Research areas: Atmospheric/Ocean Indicators
Seasonal to decadal spatiotemporal variations of the global ocean carbon sink (2022)

AbstractThe global ocean has absorbed approximately 30% of anthropogenic CO2 since the beginning of the industrial revolution. However, the spatiotemporal evolution of this important global carbon sink varies substantially on all timescales and has not yet been well evaluated. Here, based on a reconstructed observationbased product of surface ocean pCO2 and airsea CO2 flux (the MPISOMFFN method), we investigated seasonal to decadal spatiotemporal variations of the ocean CO2 sink during the past three decades using an adaptive data analysis method. Two predominant variations are modulated annual cycles and decadal fluctuations, which account for approximately 46% and 25% of all extracted components, respectively. Although the whole summer to nonsummer seasonal difference pattern is determined by the Southern Ocean, the nonsummer CO2 sink at midlatitudes in both hemispheres shows an increasing trend (a total increase of approximately 1.0 PgC during the period 19822019), while it is relatively stable in summer. On decadal timescales for the global ocean carbon sink, unlike the weakening decade (19901999) and the reinvigoration decade (20002009) in which the Southern Ocean plays the dominant role, the reinforcement decade (20102019) is mainly the result from the weakening source effect in the equatorial Pacific Ocean. Our results suggest that except for the Southern Ocean's role in the global ocean carbon sink, the strengthening nonsummer's sink at midlatitudes in both hemispheres and the decadal or longer timescales of equatorial Pacific Ocean dynamics should be fully considered in understanding the oceanic carbon cycle on a global scale.

Research areas: Atmospheric/Ocean Indicators
Recent Increases in Exposure to Extreme Humid-Heat Events (2021)

Extreme heat research has largely focused on dry-heat, while humid-heat that poses a substantial threat to human-health remains relatively understudied. Using hourly high-resolution ERA5 reanalysis and HadISD station data, we provide the first spatially comprehensive, global-scale characterization of the magnitude, seasonal timing, and frequency of dry- and wet-bulb temperature extremes and their trends. While the peak dry- and humid-heat extreme occurrences often coincide, their timing differs in climatologically wet regions. Since 1979, dry- and humid-heat extremes have become more frequent over most land regions, with the greatest increases in the tropics and Arctic. Humid-heat extremes have increased disproportionately over populated regions (∼5.0 days per-person per-decade) relative to global land-areas (∼3.6 days per-unit-land-area per-decade) and population exposure to humid-heat has increased at a faster rate than to dry-heat. Our study highlights the need for a multivariate approach to understand and mitigate future harm from heat stress in a warming world.

Research areas: Heat, Atmospheric/Ocean Indicators