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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 253 records · Page 14
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NASA NTRS2020

Modelling climate change impacts on maize yields under low nitrogen input conditions in sub‐Saharan Africa

Smallholder farmers in sub‐Saharan Africa (SSA) currently grow rainfed maize with limited inputs including fertilizer. Climate change may exacerbate current production constraints. Crop models can help quantify the potential impact of climate change on maize yields, but a comprehensive multimodel assessment of simulation accuracy and uncertainty in these low‐input systems is currently lacking. We evaluated the impact of varying [CO2], temperature and rainfall conditions on maize yield, for different nitrogen (N) inputs (0, 80, 160 kg N/ha) for five environments in SSA, including cool subhumid Ethiopia, cool semi‐arid Rwanda, hot subhumid Ghana and hot semi‐arid Mali and Benin using an ensemble of 25 maize models. Models were calibrated with measured grain yield, plant biomass, plant N, leaf area index, harvest index and in‐season soil water content from 2‐year experiments in each country to assess their ability to simulate observed yield. Simulated responses to climate change factors were explored and compared between models. Calibrated models reproduced measured grain yield variations well with average relative root mean square error of 26%, although uncertainty in model prediction was substantial (CV = 28%). Model ensembles gave greater accuracy than any model taken at random. Nitrogen fertilization controlled the response to variations in [CO2], temperature and rainfall. Without N fertilizer input, maize (i) benefited less from an increase in atmospheric [CO2], (ii) was less affected by higher temperature or decreasing rainfall and (iii) was more affected by increased rainfall because N leaching was more critical. The model inter-comparison revealed that simulation of daily soil N supply and N leaching plays a crucial role in simulating climate change impacts for low-input systems. Climate change and N input interactions have strong implications for the design of robust adaptation practices across SSA, because the impact of climate change will be modified if farmers intensify maize production with more mineral fertilizer.

Crop simulation model↗
NASA NTRS2020

Farm-Level Risk Factors of Increased Abortion and Mortality in Domestic Ruminants during the 2010 Rift Valley Fever Outbreak in Central South Africa

Background:Rift Valley fever (RVF) outbreaks in domestic ruminants have severe socio-economic impacts. Climate-based continental predictions providing early warnings to regions at risk for RVF outbreaks are not of a high enough resolution for ruminant owners to assess their individual risk. (2) Methods: We analyzed risk factors for RVF occurrence and severity at the farm level using the number of domestic ruminant deaths and abortions reported by farmers in central South Africa during the 2010 RVF outbreaks using a Bayesian multinomial hurdle framework. (3) Results: We found strong support that the proportion of days with precipitation, the number of water sources, and the proportion of goats in the herd were positively associated with increased severity of RVF (the numbers of deaths and abortions). We did not find an association between any risk factors and whether RVF was reported on farms. (4) Conclusions: At the farm level we identified risk factors of RVF severity; however, there was little support for risk factors of RVF occurrence. The identification of farm-level risk factors for Rift Valley fever virus (RVFV) occurrence would support and potentially improve current prediction methods and would provide animal owners with critical information needed in order to assess their herd’s risk of RVFV infection.

Melinda K Rostel↗
NASA NTRSDate not supplied

Improving Drought Monitoring for the Middle East and North Africa Region via Data Assimilation Using the NASA Land Information System (LIS)

Food and water security become an increasingly pressing concern for countries within the Middle East and North Africa (MENA) region under climate change. Droughts are among the most important issues facing this region in both economic and social terms, which have become much more severe in recent decades. An effective drought monitoring and early warning system is, therefore, critical to support drought impact assessment and risk management. This presentation describes the effort to improve the simulation of hydrological conditions for such semi-arid environment by Noah Multi-parameterization Land Surface Model within the NASA Land Information System (LIS) via assimilating remotely sensed leaf area index and soil moisture in the presence of irrigation. Multi-source satellite evapotranspiration products are used to evaluate the model performance under the impact of the choice of met-forcings, the presence of irrigation and data assimilation. The improved model configuration is aimed to deliver a better soil moisture estimation for the composite drought indicator (CDI) for drought monitoring and to provide a better initial condition in support for hydrological drought forecasting.

Wanshu Nie↗
NASA NTRS2021

The connection between forest degradation and urban energy demand in sub-Saharan Africa: a characterization based on high-resolution remote sensing data

Charcoal is a key energy source for urban households in sub-Saharan Africa and charcoal production is the main cause of forest degradation across the region. We used multitemporal high-resolution remote sensing optical imagery to quantify the extent and intensity of forest degradation associated with charcoal production and its impact on forest carbon stocks for the main supplying area of an African capital. This analysis documents the advance of forest degradation and quantifies its aboveground biomass removals over a seven-year period, registering that, between 2013 and 2016, the average annual area under charcoal production was 103 sq.km and the annual aboveground biomass removals reached 1081 000 (SD = 2461) Mg. Kiln densities in the study area rose to 2 kilns-ha, with an average of 90.7 Mg ha^(−1) of extracted aboveground biomass. Charcoal production was responsible for the degradation of 55.5% of the mopane woodlands in the study area between 2013 and 2019. We estimated post-disturbance recovery times using an ecosystem model calibrated for the study area. The simulations showed that recovery times could require up to 150 years for current aboveground biomass extraction rates. The results of the remote sensing analysis and the simulations of the ecosystem model corroborate the unsustainability of the present patterns of charcoal production. The detailed characterization of the spatial and temporal patterns of charcoal production was combined with household survey information to quantify the impact of the urban energy demand of the Maputo urban area on forest carbon stocks. The analysis shows that Maputo charcoal demand was responsible for the annual degradation of up to 175.3 sq.km and that the contribution of the study area to this demand fluctuated between 75% and 33% over the study period. The extent, advance pace and distance from urban centers documented in this study support the idea that forest degradation from charcoal production cannot merely be considered a peri-urban process. The intensity of the aboveground biomass (AGB) removals and its contribution to forest carbon stocks changes is significant at the national and regional levels.

F Sedano↗
NASA NTRS2022

Operational maize yield forecasts for Sub-Saharan Africa using Earth observation data and machine learning

Food insecurity continues to grow in Sub-Saharan Africa (SSA). In 2019, chronically malnourished people numbered nearly 240 million, or 20% of the population in SSA. Globally, numerous efforts have been made to anticipate potential droughts, crop conditions, and food shortages to foster improved food insecurity early warning and risk management. To support this goal, we develop an Earth Observation (EO) and machine-learning-based operational, subnational maize yield forecast system and evaluate its out-of-sample forecast skills during the growing seasons for Kenya, Somalia, Malawi, and Burkina Faso. In general, forecast skills improve substantially during the vegetative growth period (VP) and gradually during the reproductive development period (RP). Thus, mid-season assessment can provide effective early warning months before harvest. Skillful forecasts (Nash Sutcliffe Efficiency (NSE) > 0.6 and Mean Absolute Percentage Error (MAPE) < 20%) appear approximately two dekads after the VP; for example, they appear in May in Kenya and Somalia, January in Malawi, and July in Burkina Faso.

Donghoon Lee↗
NASA NTRS2022

Towards Effective Drought Monitoring in the Middle East and North Africa (Mena) Region: Implications From Assimilating Leaf Area Index and Soil Moisture Into the Noah-Mp Land Surface Model for Morocco

The Middle East and North Africa (MENA) region has experienced more frequent and severe drought events in recent decades, leading to increasingly pressing concerns over already strained food and water security. An effective drought monitoring and early warning system is thus critical to support risk mitigation and management by countries in the region. Here we investigate the potential for assimilation of leaf area index (LAI) and soil moisture observations to improve the representation of the overall hydrological and carbon cycles and drought by an advanced land surface model. The results reveal that assimilating soil moisture does not meaningfully improve model representation of the hydrological and biospheric processes for this region, but instead it degrades the simulation of the interannual variation in evapotranspiration (ET) and carbon fluxes, mainly due to model weaknesses in representing prognostic phenology. However, assimilating LAI leads to greater improvement, especially for transpiration and carbon fluxes, by constraining the timing of simulated vegetation growth response to evolving climate conditions. LAI assimilation also helps to correct for the erroneous interaction between the prognostic phenology and irrigation during summertime, effectively reducing a large positive bias in ET and carbon fluxes. Independently assimilating LAI or soil moisture alters the categorization of drought, with the differences being greater for more severe drought categories. We highlight the vegetation representation in response to changing land use and hydroclimate as one of the key processes to be captured for building a successful drought early warning system for the MENA region.

Wanshu Nie↗
NASA NTRS2023

Comparison of Dust Optical Depth From Multi-Sensor Products and MONARCH (Multiscale Online Non-hydrostatic AtmospheRe CHemistry) Dust Reanalysis Over North Africa, the Middle East, and Europe

Aerosol reanalysis datasets are model-based, observationally constrained, continuous 3D aerosol fields with a relatively high temporal frequency that can be used to assess aerosol variations and trends, climate effects, and impacts on socioeconomic sectors, such as health. Here we compare and assess the recently published MONARCH (Multiscale Online Non-hydrostatic AtmospheRe CHemistry) high-resolution regional desert dust reanalysis over northern Africa, the Middle East, and Europe (NAMEE) with a combination of ground-based observations and space-based dust retrievals and products. In particular, we compare the total and coarse dust optical depth (DOD) from the new reanalysis with DOD products derived from MODIS (MODerate resolution Imaging Spectroradiometer), MISR (Multi-angle Imaging SpectroRadiometer), and IASI (Infrared Atmospheric Sounding Interferometer) spaceborne instruments. Despite the larger uncertainties, satellite-based datasets provide a better geographical coverage than ground-based observations, and the use of different retrievals and products allows at least partially overcoming some single-product weaknesses in the comparison. Nevertheless, limitations and uncertainties due to the type of sensor, its operating principle, its sensitivity, its temporal and spatial resolution, and the methodology for retrieving or further deriving dust products are factors that bias the reanalysis assessment. We, therefore, also use ground-based DOD observations provided by 238 stations of the AERONET (AErosol RObotic NETwork) located within the NAMEE region as a reference evaluation dataset. In particular, prior to the reanalysis assessment, the satellite datasets were evaluated against AERONET, showing moderate underestimations in the vicinities of dust sources and downwind regions, whereas small or significant overestimations, depending on the dataset, can be found in the remote regions. Taking these results into consideration, the MONARCH reanalysis assessment shows that total and coarse-DOD simulations are consistent with satellite- and ground-based data, qualitatively capturing the major dust sources in the area in addition to the dust transport patterns. Moreover, the MONARCH reanalysis reproduces the seasonal dust cycle, identifying the increased dust activity that occurred in the NAMEE region during spring and summer. The quantitative comparison between the MONARCH reanalysis DOD and satellite multi-sensor products shows that the reanalysis tends to slightly overestimate the desert dust that is emitted from the source regions and underestimate the transported dust over the outflow regions, implying that the model's removal of dust particles from the atmosphere, through deposition processes, is too effective. More specifically, small positive biases are found over the Sahara desert (0.04) and negative biases over the Atlantic Ocean and the Arabian Sea (−0.04), which constitute the main pathways of the long-range dust transport. Considering the DOD values recorded on average there, such discrepancies can be considered low, as the low relative bias in the Sahara desert (< 50 %) and over the adjacent maritime regions (< 100 %) certifies. Similarly, over areas with intense dust activity, the linear correlation coefficient between the MONARCH reanalysis simulations and the ensemble of the satellite products is significantly high for both total and coarse DOD, reaching 0.8 over the Middle East, the Atlantic Ocean, and the Arabian Sea and exceeding it over the African continent. Moreover, the low relative biases and high correlations are associated with regions for which large numbers of observations are available, thus allowing for robust reanalysis assessment.

Michail Mytilinaios↗
NASA NTRSDate not supplied

SERVIR - Connecting Space to Village in Africa, Asia and the Americas

SERVIR is a joint NASA and USAID program that partners with countries and organizations to support locally led efforts to strengthen climate resilience, food and water security, forest and carbon management, and air quality. This unique program integrates NASA’s world class scientists and data with USAID’s development expertise and network of partners and relationships around the world. SERVIR harnesses the power of satellite data and science collaboration to support healthy, sustainable communities, livelihoods and environments. SERVIR’s name is derived from Latin, meaning "to serve.” We serve and partner with leading local, national, and regional institutions in Africa, Asia, and Latin America and in partnership with scientists and subject matter experts to co-develop and implement activities called “services.” Each of SERVIR’s services provide a comprehensive suite of geospatial data, software, and training materials, all of which are tailored to the unique needs of SERVIR’s end users. Each service is collaboratively designed and implemented with the help of partners and users, such as local governments and NGOs, to better support decision-making. When SERVIR plans new services, it prioritizes long-term dialogue and engagement with communities to ensure that services are sustainable, socially inclusive, and suited to local needs. SERVIR strives to make the power of Earth science more accessible and inclusive. All web tools are made publicly available to help promote greater uptake and long-term use of SERVIR’s services.

SERVIR↗
NASA NTRSDate not supplied

Interactions Between Landslides, the Mining Industry, and the Communities Tethered to This Industry in KwaZulu Natal, South Africa

The nature of the hilly and insecure terrain of the mining industry can also be home to numerous landslides that impact the lives of those dependent on this economy for survival. However, the connections between localized landslides in the mining sector and impacts to lives and livelihoods are often overlooked. This research focuses on the eThekwini Metropolitan Municipality of the KwaZulu-Natal Province of South Africa where frequent summer rains along with the steep terrain leads to abundant number of landslides. The mining analysis was performed within the eThekwini Municipality, while the entirety of KwaZulu-Natal Province was considered for the societal impact research.

Rachel Soobitsky↗
NASA NTRS1992

Microfossils and possible microfossils from the Early Archean Onverwacht Group, Barberton Mountain Land, South Africa

There is widespread textural evidence for microbial activity in the cherts of the Early Archean Onverwacht Group. Layers with fine carbonaceous laminations resembling fossil microbial mats are abundant in the cherty metasediments of the predominantly basaltic Hooggenoeg and Kromberg Formations. In rare cases, filamentous microfossils are associated with the laminae. The morphologies of the fossils, as well as the texture of the encompassing laminae suggest an affinity to modern mat-dwelling cyanobacteria or bacteria. A variety of spheroidal and ellipsoidal structures present in cherts of the Hooggenoeg and Kromberg Formations resemble modern coccoidal bacteria and bacterial structures, including spores. The development of spores may have enabled early microorganisms to survive the relatively harsh surficial conditions, including the effects of very large meteorite impacts on the young Earth.

Non-NASA Center↗
NASA NTRS1994

Depositional and tectonic setting of the Archean Moodies Group, Barberton Greenstone Belt, South Africa

The 3.22-3.10 Ga old Moodies Group, uppermost unit of the Swaziland Supergroup in the Barberton Greenstone Belt (BGB), is the oldest exposed, well-preserved quartz-rich sedimentary sequence on earth. It is preserved in structurally separate blocks in a heavily deformed fold-and-thrust belt. North of the Inyoka Fault, Moodies strata reach up to 3700 m in thickness. Detailed mapping, correlation of measured sections, and systematic analysis of paleocurrents show that the lower Moodies Group north of the Inyoka Fault forms a deepening- and fining-upward sequence from a basal alluvial conglomerate through braided fluvial, tidal, and deltaic sandstones to offshore sandy shelf deposits. The basal conglomerate and overlying fluvial facies were derived from the north and include abundant detritus eroded from underlying Fig Tree Group dacitic volcanic rocks. Shoreline-parallel transport and extensive reworking dominate overlying deltaic, tidal, and marine facies. The lithologies and arrangement of Moodies Group facies, sandstone petrology, the unconformable relationship between Moodies strata and older deformed rocks, presence of at least one syndepositional normal fault, and presence of basaltic flow rocks and airfall fall tuffs interbedded with the terrestrial strata collectively suggest that the lower Moodies Group was deposited in one or more intramontane basins in an extensional setting. Thinner Moodies sections south of the Inyoka Fault, generally less than 1000 m thick, may be correlative with the basal Moodies Group north of the Inyoka Fault and were probably deposited in separate basins. A northerly derived, southward-thinning fan-delta conglomerate in the upper part of the Moodies Group in the central BGB overlies lower strata with an angular unconformity. This and associated upper Moodies conglomerates mark the beginning of basin shortening by south- to southeast-directed thrust faulting along the northern margin of the BGB and suggest that the upper Moodies Group was deposited in a foreland basin. Timing, orientation, and style of shortening suggest that this deformation eventually incorporated most of the BGB into a major fold-and-thrust belt.

NASA Discipline Exobiology↗
NASA NTRS1990

Carbonate petrography, kerogen distribution, and carbon and oxygen isotope variations in an early Proterozoic transition from limestone to iron-formation deposition, Transvaal Supergroup, South Africa

The transition zone comprises Campbellrand microbialaminated (replacing "cryptalgalaminate") limestone and shale, with minor dolomite, conformably overlain by the Kuruman Iron Formation of which the basal part is characterized by siderite-rich microbanded iron-formation with minor magnetite and some hematite-containing units. The iron-formation contains subordinate intraclastic and microbialaminated siderite mesobands and was deposited in deeper water than the limestones. The sequence is virtually unaltered with diagenetic mineral assemblages reflecting a temperature interval of about 110 degrees to 170 degrees C and pressures of 2 kbars. Carbonate minerals in the different rock types are represented by primary micritic precipitates (now recrystallized to microsparite), early precompactional sparry cements and concretions, deep burial limpid euhedral sparites, and spar cements precipitated from metamorphic fluids in close contact with diabase sills. Paragenetic pathways of the carbonate minerals are broadly similar in all lithofacies with kerogen intimately associated with them. Kerogen occurs as pigmentation in carbonate crystals, as reworked organic detritus in clastic-textured carbonate units, and as segregations of kerogen pigment around late diagenetic carbonate crystals. Locally kerogen may also be replaced by carbonate spar. Carbon isotope compositions of the carbonate minerals and kerogen are dependent on their mode of occurrence and on the composition of the dominant carbonate species in a specific lithofacies. Integration of sedimentary, petrographic, geochemical, and isotopic results makes it possible to distinguish between depositional, early diagenetic, deep burial, and metamorphic effects on the isotopic compositions of the carbonate minerals and the kerogen in the sequence. Major conclusions are that deep burial thermal decarboxylation led to 13C depletion in euhedral ferroan sparites and 13C enrichment in kerogen (organic carbon). Metamorphic sparites are most depleted in 13C. Carbonates in oxide-rich iron-formations are more depleted in 13C than those in siderite-rich iron-formation whereas the kerogens in oxide banded iron-formations (BIF) are more enriched. This implies that the siderite-rich iron-formations were not derived from oxide-rich iron-formation through reduction of ferric iron by organic matter. Organic matter oxidation by ferric iron did, however, decrease the abundance of kerogen in oxide-rich iron-formation and led to the formation of isotopically very light sparry carbonates. Siderite and calcmicrosparite both represent recrystallized primary micritic precipitates but differ in their 13C composition, with the siderites depleted in 13C by 4.6 per mil on average relative to calcmicrosparite. This means that the siderites were precipitated from water with dissolved inorganic carbon depleted in 13C by about 9 per mil relative to that from which the limestones precipitated. This implies an ocean system stratified with regard to total carbonate, with the deeper water, from which siderite-rich iron-formation formed, depleted in 13C. Iron-formations were deposited in areas of very low organic matter supply. Depletion of 13C may, therefore, derive not from degradation of organic matter but from hydrothermal activity, a conclusion which is supported by 18O composition of the carbonate minerals and trace element and rare earth element (REE) compositions of the iron-formations.

NASA Discipline Number 52-30↗
NASA NTRS2014

The Sensitivity of WRF Daily Summertime Simulations over West Africa to Alternative Parameterizations. Part 1: African Wave Circulation

The performance of the NCAR Weather Research and Forecasting Model (WRF) as a West African regional-atmospheric model is evaluated. The study tests the sensitivity of WRF-simulated vorticity maxima associated with African easterly waves to 64 combinations of alternative parameterizations in a series of simulations in September. In all, 104 simulations of 12-day duration during 11 consecutive years are examined. The 64 combinations combine WRF parameterizations of cumulus convection, radiation transfer, surface hydrology, and PBL physics. Simulated daily and mean circulation results are validated against NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA) and NCEP/Department of Energy Global Reanalysis 2. Precipitation is considered in a second part of this two-part paper. A wide range of 700-hPa vorticity validation scores demonstrates the influence of alternative parameterizations. The best WRF performers achieve correlations against reanalysis of 0.40-0.60 and realistic amplitudes of spatiotemporal variability for the 2006 focus year while a parallel-benchmark simulation by the NASA Regional Model-3 (RM3) achieves higher correlations, but less realistic spatiotemporal variability. The largest favorable impact on WRF-vorticity validation is achieved by selecting the Grell-Devenyi cumulus convection scheme, resulting in higher correlations against reanalysis than simulations using the Kain-Fritch convection. Other parameterizations have less-obvious impact, although WRF configurations incorporating one surface model and PBL scheme consistently performed poorly. A comparison of reanalysis circulation against two NASA radiosonde stations confirms that both reanalyses represent observations well enough to validate the WRF results. Validation statistics for optimized WRF configurations simulating the parallel period during 10 additional years are less favorable than for 2006.

variability↗