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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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1980

Seasonal variation of radiance variances from satellite observations Implication of seasonal variation of available potential energy in the stratosphere

Nimbus 5 satellite radiances for the period 1973-74 are used to examine the seasonal variation of available potential energy in the stratosphere in order to provide a further observational basis for a long-term numerical simulation of stratospheric circulation. The maximum value of stratospheric zonal available potential energy, A(Z), in the upper and middle stratosphere shows pronounced variations between winter and summer, while little variation occurs in the lower stratospheric A(Z). The aperiodic occurrence of sudden warmings complicates the seasonal variation of A(Z) and A(E) (eddy available potential energy) in the stratosphere, making the energetics irregular. Time-Fourier analysis reveals that the primary variation of A(Z) and A(E) in the stratosphere is annual and semiannual, respectively.

Chen, T.-C.↗
DOE OSTI2019

Observation of seasonal variation of atmospheric multiple-muon events in the NOvA Near Detector

Using two years of data from the NOvA Near Detector at Fermilab, we report a seasonal variation of cosmic ray induced multiple-muon (Nμ≥2) event rates which has an opposite phase to the seasonal variation in the atmospheric temperature. The strength of the seasonal multiple-muon variation is shown to increase as a function of the muon multiplicity. However, no significant dependence of the strength of the seasonal variation of the multiple-muon variation is seen as a function of the muon zenith angle, or the spatial or angular separation between the correlated muons.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2026

Data for Impact of Vertical and Seasonal Variation in Leaf Traits on Simulating Soybean Canopy Photosynthesis via 1D and 3D Modeling

Accurate modeling of photosynthesis is crucial for predicting crop productivity and quantifying the carbon cycle in agroecosystems. Leaf traits are essential inputs for modeling canopy photosynthesis. Yet, many existing models still use fixed plant functional type (PTF)-based values to parameterize leaf traits under a big-leaf or two-big-leaf assumption, neglecting their vertical profiles and seasonal changes. This simplification may introduce significant uncertainties in estimating gross primary productivity (GPP). In this study, we simulated soybean GPP and tested the effects of vertical and seasonal variation in three key leaf photosynthetic traits: the maximum carboxylation rate at 25 °C (Vcmax25), leaf chlorophyll content (LCC), and leaf mass per area (LMA) in the 1D-SCOPE and 3D-Helios models. Weekly field measurements were conducted during the growing season of 2024 to support the simulation. We designed ten leaf trait parameterization schemes by incorporating different combinations of vertical profiles and seasonal changes, while assuming homogeneous canopy architecture in both models. Our results revealed that Vcmax25 vertical and seasonal variation had the strongest influence on simulated GPP in both 1D and 3D models, while LCC and LMA effects were minimal. Particularly, the scheme with an empirically parameterized Vcmax25 profile achieved comparable performance to the scheme with the measured Vcmax25 profile. Both 1D-SCOPE and 3D-Helios accurately modeled GPP (SCOPE: R2 = 0.87, Bias = 0.55 µmol m⁻² s⁻¹; Helios: R2 = 0.9, Bias = 0.22 µmol m⁻² s⁻¹) under the most complex scheme, and their responses to vertical and seasonal variation in leaf traits were consistent, demonstrating the robustness of our findings. Based on our findings, we propose a scalable framework for parameterizing leaf traits to improve GPP simulations. This study contributes to improving the representation of leaf trait dynamics in canopy-level photosynthesis models, potentially enhancing our ability to predict crop productivity and understand agroecosystem carbon dynamics.

Photosynthesis↗
NASA NTRS2019

Seasonal Variations of Arctic Low-Level Clouds and its Linkage to Sea Ice Seasonal Variations

Using CALIPSO-CloudSat-Clouds and the Earth's Radiant Energy System (CERES)-Moderate Resolution Imaging Spectrometer (MODIS) (C3M) dataset, this study documents the seasonal variation of sea ice, cloud, and related atmospheric properties in the Arctic region (70°N–82°N) during the period 2007-2010. The surface type stratification used reveals the surface type influence on the Arctic cloud liquid water path (LWP)seasonality. Four surface types are defined: i) Permanent Ocean, ii) Land, iii) Permanent Ice, and iv) Transient Sea Ice. The Transient Ice regions are further divided into sub-regions according to the onset dates of melt/freeze season. Results show that the sea ice cover has no significant direct influence on the seasonal variation of the water vapor in the lower troposphere and the low-level cloud LWP. Rather, the role played by sea ice appear indirect by modifying the surface temperature response to increased solar insolation and influencing lower tropospheric stability (LTS). The results suggest that the combined increase in atmospheric water vapor due to warming air temperatures and the weakening of the inversion strength that governs the seasonal structure of cloud LWP. Over Transient Ice regions, the results suggest that the May peak in LWP coincides with a decrease in LTS and that is insensitive to melt and freeze onset. Variations in melt and freeze onset set are found to influence probably distribution of cloud LWP where regions of earlier melt and later freeze onset how a higher likelihood of larger values.

Yueyue Yu↗
NASA NTRS1985

Formulation of cosmic-ray solar daily variation and its seasonal variation, produced from generalized stationary anisotropy of solar origin

In previous papers, a formulation was presented of cosmic ray daily variations produced from solar anisotropies stationary through a year, and also of their annual (or seasonal) modulation caused by the annual variation of the rotation axis of the Earth relative to that of the Sun. These anisotropies are symmetric for an arbitrary rotation around an axis. From observations of the tri-diurnal variation, it has been suggested that solar anisotropies also contain some axis-asymmetric term of the third order with respect to the IMF-axis. This suggestion has recently found support in a theoretical study by Munakata and Nagashima. According to their results, the terms of axis-asymmetry with respect to IMF-axis appear also in the 2nd order anisotropy, together with some different kinds of axis-symmetric terms. The contribution of these anisotropies to the daily variation is different from that of those discussed previously. The above mentioned formulation is extended to a case of a generalized anisotropy.

Tatsuoka, R.↗
DOE OSTI2020

Anaerobic Storage and Conversion of Microalgal Biomass to Manage Seasonal Variation in Cultivation

Seasonal variation in microalgal biomass production is a well-known challenge when optimizing economics for algal fuel conversion, especially given the fluctuation in biomass production between winter and summer. Wet storage offers significant potential for cost and energy savings compared to dewatering and dry storage. This study demonstrates the feasibility of preserving harvested Scenedesmus acutus biomass through wet anaerobic storage for use in biochemical conversion. Anaerobic storage effectively preserved biomass with minimal degradation of carbohydrates and preservation of lipids and proteins. Screening experiments identified optimal pretreatment conditions for stored biomass. Scale-up of pretreatment enabled fermentation of the hydrolysate to butyric acid and indicated no observable difference in conversion between unstored and stored biomass. Lipid extraction improved by a relative 12% for stored biomass. These results suggest that wet anaerobic storage can effectively manage seasonal variation in biomass production and is compatible with biochemical approaches for biofuel production.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

Using the Atmospheric Radiation Measurement (ARM) Datasets to Evaluate Climate Models in Simulating Diurnal and Seasonal Variations of Tropical Clouds

We use the long-term Atmospheric Radiation Measurement (ARM) datasets collected at the three Tropical Western Pacific (TWP) sites as a tropical testbed to evaluate the ability of the Community Atmosphere Model (CAM5) to simulate the various types of clouds, their seasonal and diurnal variations, and their impact on surface radiation. We conducted a series of CAM5 simulations at various horizontal grid spacing (around 2°, 1°, 0.5°, and 0.25°) with meteorological constraints from reanalysis. Model biases in the seasonal cycle of cloudiness are found to be weakly dependent on model resolution. Positive biases (up to 20%) in the annual mean total cloud fraction appear mostly in stratiform ice clouds. Higher-resolution simulations do reduce the positive bias in the frequency of ice clouds, but they inadvertently increase the negative biases in convective clouds and low-level liquid clouds, leading to a positive bias in annual mean shortwave fluxes at the sites, as high as 65 W m-2 in the 0.25° simulation. Such resolution-dependent biases in clouds can adversely lead to biases in ambient thermodynamic properties and, in turn, feedback on clouds. Both the CAM5 model and ARM observations show distinct diurnal cycles in total, stratiform and convective cloud fractions; however, they are out-of-phase by 12 hours and the biases vary by site. Our results suggest that biases in deep convection affect the vertical distribution and diurnal cycle of stratiform clouds through the transport of vapor and/or the detrainment of liquid and ice. We also found that the modelled gridmean surface longwave fluxes are systematically larger than site measurements when the grid that the ARM sites reside in is partially covered by ocean. The modeled longwave fluxes at such sites also lack a discernable diurnal cycle because the ocean part of the grid is warmer and less sensitive to radiative heating/cooling compared to land. Higher spatial resolution is more helpful is this regard. Our testbed approach can be easily adapted for the evaluation of new parameterizations being developed for CAM5 or other global or regional model simulations at high spatial resolutions.

Wang, Hailong↗
DOE OSTI2015

Observation of seasonal variation of atmospheric multiple-muon events in the MINOS Near and Far Detectors

We report the first observation of seasonal modulations in the rates of cosmic ray multiple-muon events at two underground sites, the MINOS Near Detector with an overburden of 225 mwe, and the MINOS Far Detector site at 2100 mwe. At the deeper site, multiple-muon events with muons separated by more than 8 m exhibit a seasonal rate that peaks during the summer, similar to that of single-muon events. Conversely, the rate of multiple-muon events with muons separated by less than 5–8 m, and the rate of multiple-muon events in the smaller, shallower Near Detector, exhibit a seasonal rate modulation that peaks in the winter.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2010

Global View of Aerosol Vertical Distributions from CALIPSO Lidar Measurements and GOCART Simulations: Regional and Seasonal Variations

This study examines seasonal variations of the vertical distribution of aerosols through a statistical analysis of the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) lidar observations from June 2006 to November 2007. A data-screening scheme is developed to attain good quality data in cloud-free conditions, and the polarization measurement is used to separate dust from non-dust aerosol. The CALIPSO aerosol observations are compared with aerosol simulations from the Goddard Chemistry Aerosol Radiation Transport (GOCART) model and aerosol optical depth (AOD) measurements from the MODerate resolution Imaging Spectroradiometer (MODIS). The CALIPSO observations of geographical patterns and seasonal variations of AOD are generally consistent with GOCART simulations and MODIS retrievals especially near source regions, while the magnitude of AOD shows large discrepancies in most regions. Both the CALIPSO observation and GOCART model show that the aerosol extinction scale heights in major dust and smoke source regions are generally higher than that in industrial pollution source regions. The CALIPSO aerosol lidar ratio also generally agrees with GOCART model within 30% on regional scales. Major differences between satellite observations and GOCART model are identified, including (1) an underestimate of aerosol extinction by GOCART over the Indian sub-continent, (2) much larger aerosol extinction calculated by GOCART than observed by CALIPSO in dust source regions, (3) much weaker in magnitude and more concentrated aerosol in the lower atmosphere in CALIPSO observation than GOCART model over transported areas in midlatitudes, and (4) consistently lower aerosol scale height by CALIPSO observation than GOCART model. Possible factors contributing to these differences are discussed.

Yu, Hongbin↗
NASA NTRS2001

Modeled Seasonal Variations of Firn Density Induced by Steady State Surface Air Temperature Cycle

Seasonal variations of firn density in ice-sheet firn layers have been attributed to variations in deposition processes or other processes within the upper firn. A recent high-resolution (mm scale) density profile, measured along a 181 m core from Antarctica, showed small-scale density variations with a clear seasonal cycle that apparently was not-related to seasonal variations in deposition or known near-surface processes (Gerland and others 1999). A recent model of surface elevation changes (Zwally and Li, submitted) produced a seasonal variation in firn densification, and explained the seasonal surface elevation changes observed by satellite radar altimeters. In this study, we apply our 1-D time-dependent numerical model of firn densification that includes a temperature-dependent formulation of firn densification based on laboratory measurements of grain growth. The model is driven by a steady-state seasonal surface temperature and a constant accumulation rate appropriate for the measured Antarctic ice core. The modeled seasonal variations in firn density show that the layers of snow deposited during spring to mid-summer with the highest temperature history compress to the highest density, and the layers deposited during later summer to autumn with the lowest temperature history compress to the lowest density. The initial amplitude of the seasonal difference of about 0.13 reduces to about 0.09 in five years and asymptotically to 0.92 at depth, which is consistent with the core measurements.

Jun, Li↗
NASA NTRS1991

Seasonal variations in urinary risk factors among patients with nephrolithiasis

Twenty-four hour urine specimens from 5,677 stone-forming patients throughout the United States were analyzed for seasonal variations in urinary risk factors for nephrolithiasis. Determinations were performed for urine volume, pH, calcium, oxalate, phosphorus, sodium, magnesium, citrate, sulfate, uric acid, and the relative supersaturation (RS) of calcium oxalate, brushite, monosodium urate, and uric acid. Criteria for significant seasonal variation included a significant difference in monthly means of risk factors, seasonal grouping of the data by the Student-Newman-Keuls multiple range test, consistent year-to-year trends and a physiologically significant range. Minimum urine volume of 1.54 +/- 0.70 SD L/day occurred in October while a maximum urine volume of 1.76 +/- 0.78 SD L/day was observed during February. Minimum urine pH of 5.94 +/- 0.64 SD was observed during July and August while a maximum pH of 6.18 +/- 0.61 SD was observed during February. Daily urinary excretion of sodium was lowest during August, 158 +/- 74 SD mEq/day and highest during February 177 +/- 70 SD mEq/day. The RS of brushite and uric acid were found to display significant pH-dependent seasonal variation with a maximum RS of uric acid 2.26 +/- 1.98 SD in June and a low of 1.48 +/- 1.30 SD in February. Maximum RS of brushite 2.75 +/- 2.58 was observed during February. Minimum RS of brushite 1.93 +/- 1.70 SD was observed in June. Phosphorus excretion displayed seasonal variation about a spring-fall axis with a maximum value 1042 +/- 373 SD mg/day in April and a minimum value of 895 +/- 289 SD mg/day. Urine volume, sodium, and pH were significantly lower during the summer (June, July, August) than in the winter (December, January, February). The RS of uric acid was higher, but that of brushite and monosodium urate was lower in the summer than in the winter. The seasonal changes observed in urine volume, pH, sodium, and the RS of brushite and uric acid are consistent with summertime sweating and increased physical activity. Seasonal variations in phosphorus excretion are probably dietary in origin. The summertime was characterized by an increased propensity for the crystallization of uric acid but not of calcium oxalate or calcium phosphate.

NASA Discipline Regulatory Physiology↗
NASA NTRS2014

Aerosol Seasonal Variations over Urban-Industrial Regions in Ukraine According to AERONET and POLDER Measurements

The paper presents an investigation of aerosol seasonal variations in several urban-industrial regions in Ukraine. Our analysis of seasonal variations of optical and physical aerosol parameters is based on the sun-photometer 2008-2013 data from two urban ground-based AERONET (AErosol RObotic NETwork) sites in Ukraine (Kyiv, Lugansk) as well as on satellite POLDER instrument data for urban-industrial areas in Ukraine. We also analyzed the data from one AERONET site in Belarus (Minsk) in order to compare with the Ukrainian sites. Aerosol amount and optical depth (AOD) values in the atmosphere columns over the large urbanized areas like Kyiv and Minsk have maximum values in the spring (April-May) and late summer (August), whereas minimum values are observed in late autumn. The results show that fine-mode particles are most frequently detected during the spring and late summer seasons. The analysis of the seasonal AOD variations over the urban-industrial areas in the eastern and central parts of Ukraine according to both ground-based and POLDER data exhibits the similar traits. The seasonal variation similarity in the regions denotes the resemblance in basic aerosol sources that are closely related to properties of aerosol particles. The behavior of basic aerosol parameters in the western part of Ukraine is different from eastern and central regions and shows an earlier appearance of the spring and summer AOD maxima. Spectral single-scattering albedo, complex refractive index and size distribution of aerosol particles in the atmosphere column over Kyiv have different behavior for warm (April-October) and cold seasons. The seasonal features of fine and coarse aerosol particle behavior over the Kyiv site were analyzed. A prevailing influence of the fine-mode particles on the optical properties of the aerosol layer over the region has been established. The back-trajectory and cluster analysis techniques were applied to study the seasonal back trajectories and prevailing directions of the arrived air mass for the Kyiv and Minsk sites.

Ukraine↗
DOE OSTI2025

Seasonal variations of the atmospheric muon neutrino spectrum measured with IceCube

This study presents an analysis of seasonal variations in the atmospheric muon neutrino flux, using 11.3 years of data from the IceCube Neutrino Observatory. By leveraging a novel spectral unfolding method, we explore the energy range from 125 GeV to 10 TeV for zenith angles from 90° to 110°, corresponding to the Antarctic atmosphere. Our findings reveal that the differential measurement of the amplitudes of the seasonal variation is consistent with an energy-dependent decrease reaching (-4.5 ± 1.2)% during Austral winter and increase to (+ 3.9 ± 1.3)% during Austral summer relative to the annual average at 10 TeV. While the unfolded flux exceeds the model predictions by up to 30%, the differential measurement of the seasonal to annual average flux remains unaffected. The measured seasonal variations of the muon neutrino spectrum are consistent with theoretical predictions using the MCEq code and the NRLMSISE-00 atmospheric model.

Astroparticle Physics and High-Energy Cosmic Pheno↗
DOE OSTI2023

Remote sensing of seasonal variation of LAI and fAPAR in a deciduous broadleaf forest

Climate change is affecting the phenology of terrestrial ecosystems. In deciduous forests, phenology in leaf area index (LAI) is the primary driver of seasonal variation in the fraction of absorbed photosynthetically active radiation (fAPAR), which drives photosynthesis. Remote sensing has been widely used to estimate LAI and fAPAR. However, while many studies have examined both empirical and model-based relationships among LAI, fAPAR, and spectral vegetation indices (SVI) from remote sensing, few studies have systematically and empirically examined how relationships among these variables change over the growing season. In this study, we examine how and why seasonal-scale covariation differs among time series of remotely sensed SVIs and both LAI and fAPAR based on current understanding and theory. To do this we use newly available remote sensing data sets in combination with time series of in-situ measurements and a canopy radiative transfer model to analyze how seasonal variation in canopy and environmental conditions affect relationships among remotely sensed SVIs, LAI, and fAPAR at a temperate deciduous forest site in central Massachusetts. Our results show that accounting for seasonal variation in canopy shadowing, which is driven by variation in solar zenith angle, improved remote sensing-based estimates of LAI, fAPAR, and daily total APAR. Specifically, we show that the phenology of SVIs is strongly influenced by seasonal variation in near infrared (NIR) reflectance arising from systematic variation in the canopy shadow fraction that is independent of changes in LAI or fAPAR. Therefore, results of this work provide a refined basis for understanding how remote sensing can be used to monitor and model the phenology of LAI, fAPAR, APAR, and gross primary productivity in temperate deciduous forests.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1984

Explanation of the Normal Winter Anomaly from the Seasonal Variation of Short Wave Absorption

The frequency dependence of the winter anomaly (WA) of radio wave absorption indicates the altitude range where the considered seasonal variation of absorption, L, takes place: 75-95 km. In this height region considerable seasonal variations of ionic composition and effective recombination coefficient, alpha sub e, exist, which can cause seasonal variations of electron concentration, N, and absorption, L. An attempt to render a qualitative estimation of the normal WA, i.e., the increased ratio of winter over summer absorption, L sub w/L sub s, at medium latitudes 40 deg and 50 deg, for solar zenith angles CHi = 60 deg and 75 deg is made. This is compared with existing experimental data.

Velinov, P. J.↗