NASA Research Articles

Climate extremes and their impacts on agriculture across the Eastern Corn Belt Region of the U.S.

The Eastern Corn Belt Region (ECBR) is an important agricultural sector for the U.S. This study analyzes the climate extremes over the contemporary (1980–2018) and future (2036–2099) periods over the ECBR. We evaluated the performance of 32 downscaled models from the U.S. Global Change Research Program's Localized Constructed Analogs (LOCA) of the Coupled Model Intercomparison Project (CMIP5) to simulate extreme temperature and precipitation indices. The LOCA downscaled models were evaluated for the recent past against the National Aeronautics and Space Administration (NASA)-supported gridded observational dataset DAYMET. Results reveal key trends throughout the region that are consistent with previous studies, including significant increases in extreme minimum temperatures, reduction of cold nights, increase of warm nights, and decreases in diurnal temperature ranges. Much of the region demonstrates extreme warming trends in the coldest night of the year (more than 5 °C) and an increase in the heaviest precipitation events over 1980–2018. An optimal model ensemble (OME) was constructed using a Kling-Gupta Efficiency and Bhattacharyya coefficient evaluation to construct a comprehensive ranking procedure. Having outperformed a standard multi-model ensemble approach, the OME was used to evaluate the future changes of extreme climate indices under RCP4.5 and RCP8.5 scenarios. Though the OME showed consistently strong warming throughout the ECBR, variability among the optimal models and across watersheds is quite significant, especially for precipitation indices. Thus, constraining the uncertainty in future climate models, specifically as it relates to agriculture decisions that support climate-resilience, remains a challenge.

Front and Back Covers, Volume 38, Number 3. June 2022

Front and back cover caption, volume 38 issue 3SPACE ANTHROPOLOGYA day on Mars, also known as a sol, lasts approximately 24 hours, 39 minutes, 35 seconds. In order to operate robotic rovers on the red planet, teams of scientists back on earth have to abandon terrestrial rhythms and work according to a new temporality: Mars time. This process is at the heart of Zara Mirmalek's Making time on Mars (2020) and is the inspiration for the front cover illustration by Uni Pang. This ethnography chronicles how the National Aeronautics and Space Administration (NASA) scientists and engineers forged new relationships with time, technology and each other in order to manage a novel multi‐planetary work system.Mirmalek's work, and others like it, are part of the emerging field of space anthropology. While humanity's various relations with the cosmos have been a running thread throughout the discipline's history, contemporary developments, such as the rapid growth of the private space sector and the looming threat of climate change, have pushed celestial matters to the fore. Recent scholarship has examined the collaborative practices of technical experts working on deep space probes, has shed light on the continuing colonial legacies of spaceports around the world and has asked how indigenous ontologies and decolonial thought can challenge techno‐scientific designs for unchecked human expansion into the stars.In this issue, members of the ARIES project — an international research team based at Jagiellonian University — draw on their experience designing and teaching an undergraduate course on the social science of outer space to discuss the current state of space‐oriented research. Engaging with outer space poses distinct methodological and theoretical questions that complicate some of the most fundamental tenets of anthropology. Yet, approaching these issues is crucial for understanding many contemporary social, ecological and political matters across local, planetary and multi‐planetary scales.‘DRIVE AND TALK’ FIELDWORKIn Langhorne Creek, South Australia, seasonal streams cut through a broad floodplain with giant eucalypts and grazing cows, interspersed with vineyards growing shiraz and cabernet sauvignon grapes. On this rich landscape, the descendants of settler‐colonial families have farmed for almost two centuries, irrigating in part with floodwaters from the Angas and Bremer Rivers. These precious waters are collaboratively shared between farms through sluice gates and earthworks systems.In this issue, Georgina Drew, William Skinner and Douglas Bardsley reflect upon the importance of the ‘drive and talk’ for fieldwork in an agricultural landscape: not only to generate empirical data but also phenomenologically, as the farm is felt through the sand and gravel passing under the wheels, the scrubby bushes scraping the chassis, and the muddy embankments navigated by a driver who knows their land inside out.Farming is physical work that requires mobility. At the scale of an Australian farm, mobility involves driving. Ethnographic engagement then is not just mobility but also auto‐mobility, as farmers bounce around their paddocks in pickup trucks with researchers in tow, driving between properties, fording streams, stopping here and there to point out pieces of historic infrastructure, examine vineyards, and explain the country and how it is changing.Water is front of mind in the region. In recent decades, groundwater depletion and rising salinity have represented an existential risk to Langhorne Creek, exacerbated by the major ‘Millennium Drought’. Now, a new pipeline drawing water from further afield provides increased surety. Yet, farmers maintain their vigilance, concerned about climatic fluctuations and changes to ground and surface water flows.By relating to farmer concerns in the intimate setting of the automobile, researchers can generate new understandings of the risks and opportunities for adaptation.

Lithium-ion battery capacity and remaining useful life prediction using board learning system and long short-term memory neural network

In order for lithium-ion batteries to function reliably and safely, accurate capacity and remaining useful life (RUL) predictions are essential, but challenging. Some current deep learning-based forecasting methods tend to increase the size of training data and deepen the network structure in an attempt to obtain better predictive results, which is quite resource-intensive. By combining broad learning system (BLS) algorithm and long short-term memory neural network (LSTM NN), a fusion neural network model is developed to outstanding predict the lithium-ion battery capacity and RUL in this work. Specifically, the BLS first produces feature nodes based on the historical capacity data, and applies the enhancement mapping to create enhancement nodes. Afterward, the BLS-LSTM fusion neural network is constructed by concatenating all BLS-created nodes as the input layer of the LSTM NN. Finally, the battery capacity and RUL prediction experiments with different size training sets are conducted to verify the effectiveness of the proposed method based on the battery aging data from the National Aeronautics and Space Administration (NASA) Ames Prognostics Center of Excellence and the Center for Advanced Life Cycle Engineering (CALCE) at the University of Maryland. Experimental results demonstrate that the BLS-LSTM fusion neural network guarantees the precision of the lithium-ion battery capacity and RUL prediction, while the training data can be reduced to only 25% of the whole degraded data.

0585 Use of a Hybrid Closed Loop Insulin Delivery System Improves Sleep and Glycemic Control in Adults with Long-Standing Type 1 Diabetes and Hypoglycemia Unawareness

Abstract Introduction Insulin delivery and continuous glucose monitoring systems (CGMs) have been reported to disrupt sleep in individuals with type 1 diabetes (T1D), potentially thwarting the adoption and continued use of diabetes therapeutic technologies. This study assessed changes in actigraphic sleep and glycemic outcomes in individuals at high risk for life threatening nocturnal hypoglycemia after initiating a hybrid closed loop (HCL) insulin delivery system with integrated CGM. Methods 10 adults (median age=51y) with long-standing T1D (median duration=34y) and hypoglycemia unawareness participated in an 18-month ongoing clinical trial assessing the effectiveness of a HCL system. Wrist actigraphs and CGMs measured sleep and glycemic control, respectively, at baseline (1 week) and at months 3, 6, 9, 12, 15, and 18 (3 weeks) following HCL initiation. Body mass index and hemoglobin A1c (HbA1c) were also collected at these timepoints. Hypoglycemia awareness was assessed using the Clarke hypoglycemia questionnaire, HYPO score, and glycemic lability index. Paired sample t-tests and Cohen’s d effect sizes modeled changes in sleep, glycemic control, and hypoglycemic awareness and the magnitude of these changes from baseline to 18 months. Results Sleep improved from baseline to 18 months [shorter sleep latency (p<0.01), later sleep offset (p<0.05), and less wake after sleep onset (WASO) (<0.01)]. Medium effect sizes were found for later sleep onset (d=0.74) and later sleep midpoints (d=0.77). HCL also improved hypoglycemia awareness from baseline to 18 months [Clarke score (p<0.01), HYPO score (p<0.01), lability index (p<0.05)]. Medium to large effect sizes were found for reduced nocturnal hypoglycemia (percent time glucose was <54mg/dL,<60mg/dL,<70mg/dL; d=0.66 – 0.81), daytime and nocturnal hypoglycemia (percent time glucose was<54mg/dL,<60mg/dL,<70mg/dL; d=0.61 – 0.69), and glucose variability (coefficient of variability; d=0.62). Conclusion HCL insulin delivery with CGM improved sleep over time as indicated by shorter sleep onset latency, later sleep offset, and less WASO. HCL insulin delivery also improved hypoglycemia awareness and led to clinically significant reductions in hypoglycemia and glucose variability. Support (If Any) NIH (R01DK117488 (NG), R01DK091331 (MRR), K99NR017416 (SKM), and UL1TR001878 (University of Pennsylvania Center for Human Phenomic Science)). National Aeronautics and Space Administration (NASA) (NNX14AN49G and 80NSSC20K0243 (NG)) and from the Pennsylvania Department of Health (SAP 4100079750 (IL)).

Optimal Design and Techno-Economic Analysis of a Grid-Connected Photovoltaic and Battery Hybrid Energy System

The application of green energy technologies (GETs) has been accepted universally due to the industrial revolution, increasing energy demand, high standard of living, population growth and fluctuation of crude oil prices. In view of this, GETs have been recognized on a global note as a promising and significant alternative to meet ever increasing power demand. This research work is aimed at optimal operation and design of hybrid renewable energy system (HRES) to enhance the performance of the power system while taking into consideration the energy produced, levelized cost of energy (LCOE), return on investment (ROI), solar fraction (SF), net present value (NPV), payback period and saved CO2 emissions based on the photovoltaic (PV) orientation. This is due to the fact that the solar panel generates more electrical output when its surface is perpendicular to the solar radiation. The PV orientation significantly affects the output of a solar farm, for this reason, fixed tilted plane, vertical axis tracking system and two axes tracking system are proposed in this research work to estimate their effects on the technical, economic and environmental performance of HRES. This paper presents a grid-connected HRES that comprises utility grid, PV, battery system (BS) and load. The modelling and simulation of HRES are implemented by using PVsyst.7 energy tools in conjunction with the meteorological data made available by the National Aeronautics and Space Administration (NASA). The research outputs show that the two axes tracking system is more techno-economic feasible when compared with the fixed tilted plane and vertical axis tracking system based on the following results: Energy obtained from the grid of 4.657 MW/yr, LCOE of 0.075 ZAR/kWh, ROI of 862.7%, SF of 0.6781, NPV of 828,881.74 ZAR, payback period of 3.5 years and carbon balance of 732.240 tons. The outcomes of the study can be used by the power system planners and designers as benchmarks to utilize the prospect of solar resources for power sector reform and the industrial revolution.

Mars Sample Return (MSR): Planning for Returned Sample Science.

Mars Sample Return (MSR) has been a high priority for the planetary science community for more than four decades. Analyzing martian samples in terrestrial laboratories would advance our understanding of Mars in multiple ways that are impossible using in situ missions alone. The overall MSR concept includes three distinct phases: 1. Selecting and collecting scientifically suitable samples on Mars, currently being carried out by the Mars 2020 mission with the Perseverance rover; 2. Retrieving the samples on Mars and transporting them to Earth; 3. Receiving the samples on Earth, making them available for analysis by the science community for decades to come. With the recent successful collection of the first samples by the Perseverance rover and the ongoing progress by the National Aeronautics and Space Administration (NASA) and the European Space Agency (ESA) on the development of the missions that could retrieve and transport the samples to Earth, MSR continues to move closer to becoming a reality. As Perseverance and the MSR retrieval and return missions progress, it becomes increasingly imperative to develop detailed plans for the receipt and analysis of the samples on Earth to ensure that the full science potential of MSR can be realized.

Harmonizing surface reflectance between Landsat-7 ETM + , Landsat-8 OLI, and Sentinel-2 MSI over China.

Remote sensing dynamic monitoring methods often benefit from a dense time series of observations. To enhance these time series, it is sometimes necessary to integrate data from multiple satellite systems. In particular, the Landsat and Sentinel series provide a rich source of data for Earth observations. National Aeronautics and Space Administration (NASA) scientists proposed a method that creates global fixed per-band transformation coefficients to reduce the reflectance difference between Landsat-8 and Sentinel-2 for the harmonized Landsat and Sentinel-2 (HLS) surface reflectance product. However, the coefficient has yet to be further validated in the target study area and the coefficient can only be used for Landsat-8 and Sentinel-2, and is not useful for other sensors. The purpose of this study is to evaluate the potential of integrating surface reflectance data from Landsat-7, Landsat-8, and Sentinel-2. Some differences in the surface reflectance of the sensor pairs were identified, based upon which a cross-sensor conversion model was proposed, i.e., a suitable adjustment equation was fitted using an ordinary least squares (OLS) linear regression method to convert the Sentinel-2 reflectance values closer to the Landsat-7 or Landsat-8 values. The results show that the model adjusted the Sentinel-2 surface reflectance to match Landsat-7 or Landsat-8. The maximum MRE of the adjusted sensor for surface reflectance was reduced from 17.96 to 12.15%. Differences in reflectance produce corresponding differences in estimates of biophysical quantities, such as NDVI, with MRE as high as 18.33%. However, adjusting the Sentinel-2 sensor was able to reduce this part of the discrepancy to about 12.56%. The study believes that despite the differences in these datasets, it appears feasible to integrate these datasets by applying a linear regression correction between the bands.

High-precision GNSS PWV retrieval using dense GNSS sites and in-situ meteorological observations for the evaluation of MERRA-2 and ERA5 reanalysis products over China

Precipitable water vapor (PWV) product with high accuracy and high spatiotemporal resolution is important for climate change research. Hourly PWV products with a high spatiotemporal resolution can be provided by global navigation satellite system (GNSS) and global reanalysis data. The National Aeronautics and Space Administration (NASA) and the European Center for Medium-Range Weather Forecasts (ECMWF) have recently released their global reanalysis of the Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) and the fifth-generation ECMWF Reanalysis (ERA5), respectively. A comprehensive evaluation of these two PWV reanalysis products over China has yet to be fully investigated. In this study, the PWV products of MERRA-2 and ERA5 reanalysis over China have been systematically evaluated based on 339 GNSS sites and in-situ ground meteorological observations from year 2016 to 2018. To mitigate the uncertainties of this evaluation, three enhanced vertical correction models for temperature, pressure and PWV that we developed previously are adopted. Four weighted mean temperature (Tm) models are established for the four regions of China (North China, South China, Tibet Plateau, and Northwest China), and they exhibit better accuracy than the other classical Tm models in China. The evaluation results of the MERRA-2- and ERA5-derived PWV show that the correlation coefficient, biases, and root mean square error (RMSE) in China are 0.98/0.99, −0.51/0.38 mm, and 2.50/1.99 mm, respectively. They both exhibit relatively large difference when applied to South China. For the same grid spatial resolution, ERA5 PWV product exhibits similar performance with MERRA-2. The monthly-mean-reanalysis-derived PWV exhibits obvious seasonality and has the largest difference in summer. ERA5 PWV can provide more details of the spatial pattern compared to MERRA-2 PWV. The diurnal anomaly variation for ERA5 is more consistent with GNSS data, and some differences at certain moments during autumn and winter have been observed. These results show that ERA5 PWV and MERRA-2 PWV exhibits excellent applicability in China and can help us to efficiently use PWV products for climate research in China.

Potential of a Nonperennial Tributary Integrated with Solar Energy for Rural Electrification: A Case Study of Ikukwa Village in Tanzania

This study evaluates the hydropower potential in the design of a micro-hydro/solar photovoltaic hybrid system with battery energy storage for increasing the access to electricity in Ikukwa Village in Mbeya Region of Tanzania. Usually, hybridized hydropower schemes are designed from perennial streams for the provision of electricity. This study incorporates the run-of-the river (COE) power scheme, which originates from the untapped potential of nonperennial hydro-energy source and the use of traditional approach of data measurements for Ikata tributary to design hybrid system. The system is optimized by the minimization of the total net present cost (NPC) and cost of energy (COE) using the soft computing method of Hybrid Optimization of Multiple Energy Resources (HOMER) software and artificial intelligent (AI) techniques. AI optimization techniques such as particle swarm optimization (PSO), grey wolf optimization (GWO), and GWO-PSO hybrid (GWO-PSOHD) algorithms have been employed for further optimal results. The data for solar radiation and the tributary have been obtained from the National Aeronautics and Space Administration (NASA) and traditional methods of measurements, respectively. The estimated maximum water flow rate and head are 2.943 m3/s and 13 m, respectively. In the same period, the approximated theoretical power potential of the tributary is found to be 375 kW. Total NPCs obtained from HOMER, PSO, GWO, and GWO-PSOHD methods are $ 141, 397.76, $ 95 167.21, $ 92 472.82, and $ 91,854.10, respectively. Similarly, the optimal results of COE from HOMER, PSO, GWO, and GWO-PSOHD approaches are $ 0.1818/kWh, $ 0.1185/kWh, $ 0.1182/kWh, and $ 0.1181/kWh, respectively. Comparatively, PSO implementation has indicated the greatest energy cost, while the cost acquired by GWO-PSOHD is the lowest for all aforementioned AI optimization techniques. The tributary under study has a high potential of diversification of energy sources for rural electrification in the area of study and other parts of the world with comparable conditions.

Analyses of potential evapotranspiration of two major towns in Enugu State, Nigeria

Evapotranspiration (ET) may account for up to 70% of the annual precipitation even in humid region. Understanding ET is essential for management of water resource, crop water requirement as well as irrigation designs/scheduling etc. Therefore, this study tries to analyze potential ET over Enugu State using meteorological data from weather stations and compared the results obtained with that from satellite remote sensed techniques. The meteorological data from 1999 to 2014 were collected from Nigerian Meteorological agency (NIMET) for two stations in Enugu State (Enugu town and Nsukka). The data were processed and ET calculated using CROPWAT software. Also, necessary data for ET were downloaded from global atmospheric reanalysis product by European Centre for Medium-Range Weather Forecast (ERA-Interim) and National Aeronautics and Space Administration (NASA). Daily and monthly potential ET results were estimated for Enugu and Nsukka. The potential ET obtained for both stations varies with month and seasons with higher values in dry season than rainy season. The potential ET obtained from NIMET, NASA and ERA-Interim have similar trend but varied in magnitude. Statistically, ETNIMET was the most accurate followed by ETNASA.

Abdominal Examination Of Children With Telemedicine In Covid-19 Pandemic

The first application of telemedicine was a banal event on March 10, 1876, when British inventor Alexander Graham Bell accidentally spilled acid on his suit while working on his patented "telephone apparatus" and used the device to call his colleague Thomas A. Watson, who was present in the next room, for help. If the distance was only a few meters during this first medical emergency or remote call only 130 years ago, telemedicine has developed until today to a tool that enabled the ground personnel of the American space agency "NASA" to provide medical monitoring or care for astronauts located in the thermosphere - in real time.

Comparing Coarse-Resolution Land Surface Temperature Products over Western Australia

Satellite-derived land surface temperature (LST) has commonly been used to monitor global temperature changes. The MODIS MYD11A2 product is the most common coarse-resolution product used for this purpose. An updated MODIS product (MYD21A2) and new VIIRS (VNP21A2) product have also recently become available. This study analyses eight-day, quality-controlled, LST imagery over Western Australia (WA) for the three products for an urban and a non-urban area for the years 2013, 2016, and 2019. An analysis of the data indicates that (i) the averaged daytime LST difference between the three products for Perth city over the three years was 1.32 °C, while at night it was 0.89 °C; (ii) the averaged daytime difference over the Kimberley region was 7.02 °C with a night average difference of 2.39 °C; and (iii) both the MYD21A2 and VNP21A2 products still appear to record anomalous monthly LST values, particularly in the humid Kimberley monsoonal months. The overall objective of the National Aeronautics and Space Administration (NASA) is to ensure that the LST values of the two satellite system products are comparable, so evidence of LST value differences will require further investigation, especially if the older product is to be replaced by the newer systems.

Surveillance for jugular venous thrombosis in astronauts

Thrombosis of the left internal jugular vein in an astronaut aboard the International Space Station was recently described, incidentally discovered during a research study of blood flow in neck veins in microgravity. Given this event, and the high incidence of flow abnormalities, the National Aeronautics and Space Administration (NASA) instituted an occupational surveillance program to evaluate astronauts for venous thrombosis. Duplex ultrasound of the bilateral internal jugular veins was conducted on all NASA astronauts terrestrially, and at three points during spaceflight. Respiratory maneuvers were performed. Images were analyzed for thrombosis and certain hemodynamic characteristics, including peak velocity and degree of echogenicity. Eleven astronauts were evaluated with matching terrestrial and in-flight ultrasounds. No thrombosis was detected. Compared to terrestrial ultrasound measurements, in-flight peak velocity was reduced and lowest in the left. Six of 11 astronauts had mild-moderate echogenicity in the left internal jugular vein during spaceflight, but none had more than mild echogenicity in the right internal jugular vein. Two astronauts developed retrograde blood flow in the left internal jugular vein. Abnormal flow characteristics in microgravity, most prominent in the left internal jugular vein, may signal an increased risk for thrombus formation in some individuals.

Diversification of South American Vespertilionidae (Chiroptera) is not constrained by evolutionary priority effects

Abstract According to diversity-dependent diversification (DDD) theory, diversification slows down as niches are gradually filled by cladogenesis. A corollary of DDD is to assume a richness ceiling, a contentious topic for continental clades. Evolutionary priority effect is a related phenomenon whereby secondary colonizers have their diversification constrained owing to pre-emption of niches by incumbent groups. South American aerial insectivorous bats are composed of incumbent, non-Vespertilionidae groups (SA non-vesper) and the later immigrant Vespertilionidae (SA vesper). We investigated whether DDD and priority effects explain SA vesper diversification history, while also comparing it with North/Central American vespertilionids (NA vesper), an incumbent lineage in that region. Diversification analysis supported a single regime of diversification rates across all groups, with little decrease through time. Geographical state diversification of vespertilionids selected a best-fitting model with different speciation rates for NA endemics, SA endemics and widespread species, but equal extinction. The model presented higher speciation for SA endemics over NA endemics. Thus, DDD and priority effects are inconsistent with the diversification of South American aerial insectivorous bats. We discuss how SA vesper are comparatively depauperate, probably because of a shorter evolutionary history and/or cryptic diversity when compared with NA vesper, instead of niche conservatism.

A Camera-Based Method for Collecting Rapid Vegetation Data to Support Remote-Sensing Studies of Shrubland Biodiversity

The decline in biodiversity in Mediterranean-type ecosystems (MTEs) and other shrublands underscores the importance of understanding the trends in species loss through consistent vegetation mapping over broad spatial and temporal ranges, which is increasingly accomplished with optical remote sensing (imaging spectroscopy). Airborne missions planned by the National Aeronautics and Space Administration (NASA) and other groups (e.g., US National Ecological Observatory Network, NEON) are essential for improving high-quality maps of vegetation and plant species. These surveys require robust and efficient ground calibration/validation data; however, barriers to ground-data collection exist, such as steep terrain, which is a common feature of Mediterranean-type ecosystems. We developed and tested a method for rapidly collecting ground-truth data for shrubland plant communities across steep topographic gradients in southern California. Our method utilizes semi-aerial photos taken with a high-resolution digital camera mounted on a telescoping pole to capture groundcover, and a point-intercept image-classification program (Photogrid) that allows efficient sub-sampling of field images to derive vegetation percent-cover estimates while reducing human bias. Here, we assessed the quality of data collection using the image-based method compared to a traditional point-intercept ground survey and performed time trials to compare the efficiency of various survey efforts. The results showed no significant difference in estimates of percent cover and Simpson’s diversity derived from the point-intercept and those derived using the image-based method; however, there was lower correspondence in estimates of species richness and evenness. The image-based method was overall more efficient than the point-intercept surveys, reducing the total survey time by 13 to 46 min per plot depending on sampling effort. The difference in survey time between the two methods became increasingly greater when the vegetation height was above 1 m. Due to the high correspondence between estimates of species percent cover derived from the image-based compared to the point-intercept method, we recommend this type of survey for the verification of remote-sensing datasets featuring percent cover of individual species or closely related plant groups, for use in classifying UAS imagery, and especially for use in MTEs that have steep, rugged terrain and other situations such as tall, dense-growing shrubs where traditional field methods are dangerous or burdensome.

Simultaneous Characterization of Wildfire Smoke and Surface Properties With Imaging Spectroscopy During the FIREX-AQ Field Campaign.

We introduce and evaluate an approach for the simultaneous retrieval of aerosol and surface properties from Airborne Visible/Infrared Imaging Spectrometer Classic (AVIRIS‐C) data collected during wildfires. The joint National Aeronautics and Space Administration (NASA) National Oceanic and Atmospheric Administration Fire Influence on Regional to Global Environments and Air Quality field campaign took place in August 2019, and involved two aircraft and coordinated ground‐based observations. The AVIRIS‐C instrument acquired data from onboard NASA's high altitude ER‐2 research aircraft, coincident in space and time with aerosol observations obtained from the Aerosol Robotic Network (AERONET) DRAGON mobile platform in the smoke plume downwind of the Williams Flats Fire in northern Washington in August 2019. Observations in this smoke plume were used to assess the capacity of optimal‐estimation based retrievals to simultaneously estimate aerosol optical depth (AOD) and surface reflectance from Visible Shortwave Infrared (VSWIR) imaging spectroscopy. Radiative transfer modeling of the sensitivities in spectral information collected over smoke reveal the potential capacity of high spectral resolution retrievals to distinguish between sulfate and smoke aerosol models, as well as sensitivity to the aerosol size distribution. Comparison with ground‐based AERONET observations demonstrates that AVIRIS‐C retrievals of AOD compare favorably with direct sun AOD measurements. Our analyses suggest that spectral information collected from the full VSWIR spectral interval, not just the shortest wavelengths, enables accurate retrievals. We use this approach to continuously map both aerosols and surface reflectance at high spatial resolution across heterogeneous terrain, even under relatively high AOD conditions associated with wildfire smoke.

NEX-GDDP Multimodel Ensemble vs. E-OBS—Evaluation of the Extreme Temperatures and Precipitation over Southeast Europe: Historical Comparison

The present study evaluates the National Aeronautics Space Administration (NASA) Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset that provides statistically downscaled CMIP5 historical and future climate projections of the daily precipitation sum and extreme temperatures at high spatial resolution. A multimodel ensemble from all 21 available models is composed and compared against gridded observations from E-OBS. The study is performed over Southeast Europe for the whole time span of the historical period of NEX-GDDP 1950–2005. The performance of the NEX-GDDP data was evaluated at multiple time scales such as annual, seasonal, monthly, and daily. The skill of the multimodel ensemble to reproduce the interannual variability, as well as the long-term trend, is also evaluated. Moreover, key climate indices of the Expert Team on Climate Change Detection and Indices (ETCCDI), derived from the ensemble extreme temperatures and precipitation are superimposed on their counterparts based on the reference dataset E-OBS. Findings of the performed research indicate that NEX-GDDP parameters are in good agreement with the reference over the considered period on monthly, seasonal and annual scales which agrees with the outcomes from similar studies for other parts of the world. There are also no systematic differences in the pattern of the biases of the minimum and maximum temperature. Generally, the multimodel ensemble reproduces the extreme temperatures significantly better than the precipitation sum. The analysis reveals also the nonnegligible inefficiency of the NEX-GDDP ensemble to reproduce the long-term trend of the considered parameters as well as the climate extremes expressed with the ETCCDI indices.

Systematic Integration of Applications into the Surface Biology and Geology (SBG) Earth Mission Architecture Study

AbstractThe Surface Biology and Geology (SBG) concept is the first National Aeronautics and Space Administration (NASA) Earth mission to develop and implement systematic integration of science application needs at the architecture study stage. Prior NASA mission concept and planning activities presumed that science measurement needs would encompasss application measurement needs and so did not explicitly evaluate and include applications at this stage. However, the effort presented here identified, documented and integrated application needs that would not have been included by considering research science needs only. First, a low latency of no greater than 24 hr was identified as the optimal target to enable the maximum number of applications and was then carried through into all SBG candidate architectures. Second, many applications expressed needs around improved spatial and temporal resolution. While increased spatial resolution would not be possible under current cost and technology considerations, the need for improved resolution for temporal sampling helped drive and bolster discussions with international partners such as the European Space Agency, Italian Space Agency, and Centre National D’Etudes Spatiales. Lastly, we found that the applications and science were synergistic with one another; for example, mission concept decisions to consider additional measurement features were driven by both high relevance application and science priorities, and in particular, evapotranspiration for agriculture and high temperature features for fires and geologic hazards. This paper discusses the process and key contributions originating from the SBG Applications Working Group and how they shaped SBG at the architecture study stage. This stage in the mission planning considers the trade space of spacecraft instruments and architectures, and evaluates which formulations are suitable candidates for SBG. The approach described here may be utilized as a framework for applications and science to inform future NASA satellite mission studies.

ASSESSMENT OF SOLAR ENERGY POTENTIAL OF NIGERIA FOR SOLAR POWER GENERATION THROUGH NUMERICAL SOLAR IRRADIANCE MAPPING

Any thorough analysis of solar energy applications in the country requires a solar resources map. Many maps have been developed, but they only show distributions presented in colour intensities. Solar irradiance can only be estimated from such maps. Using on the spot experimental data for solar map production does not provide accurate maps because various climatic and environmental conditions such as dust haze and cloud cover affect the amount of solar energy that reaches the ground in various locations in Nigeria. This is particularly true during the harmattan period. Therefore data generated from such methods cannot be used to develop accurate numerical solar maps. Data for such applications should be collected from outer space and over a long time for various locations. The National Aeronautics and Space Administration (NASA) provides a resources base for such data. The data used in this study covered 25 years (1994-2018). The average daily global solar irradiance for various longitude-latitude nodes is calculated from such data. With these data available, it is possible to estimate the average daily global solar irradiance for any location provided the longitude and latitude is known. Irradiance values for 300 locations in the country are evaluated from details presented by the maps. To validate the map, experimental irradiance values for selected locations are compared with values extracted from the solar irradiance map. Calculated irradiance values are found to agree satisfactorily with experimental values. The maximum percentage difference between calculated and experimental values is 6.8%. This proved that the solar map developed is a satisfactory provides a satisfactory representation of solar data for the various locations and can be used for other locations where such data does not exist. KEYWORDS: Solar Energy, Solar Maps, Irradiance, Energy Patterns,

LAND USE PATTERN USING SEMIAUTOMATIC CLASSIFICATION PLUGIN (SCP) WITH OPEN SOURCE DATA

Since the early 1970s, NASA (National Aeronautics and Space Administration of the United States) has been developing a series of multispectral satellites known as Landsat. Landsat photos are frequently used in environmental studies. Image classification is one of the most important tasks in image processing and analysis. It's used to look at different forms of land use and cover. Satellite photos, like high resolution satellite images, are obtained using remote sensing. However, just examining these photos isn't enough; we also need to process them. Thus, to analyze these images, we need to classify them. For this paper the Landsat classification has been performed on the Sungai Petani a major city in Malaysia. Using Landsat 8-OLI data, this paper propose a wavelet transform-based Landsat classification. This classification analysis has been performed using the plugin tool Semi-Automatic Classification tool in QGIS software.