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At least 973 records · Page 54

Quantifying Long-Term Changes in Carbon Stocks and Forest Structure from Amazon Forest Degradation

Despite sustained declines in Amazon deforestation, forest degradation from logging and firecontinues to threaten carbon stocks, habitat, and biodiversity in frontier forests along the Amazon arcof deforestation. Limited data on the magnitude of carbon losses and rates of carbon recoveryfollowing forest degradation have hindered carbon accounting efforts and contributed to incompletenational reporting to reduce emissions from deforestation and forest degradation (REDD+). Wecombined annual time series of Landsat imagery and high-density airborne lidar data to characterizethe variability, magnitude, and persistence of Amazon forest degradation impacts on abovegroundcarbon density (ACD) and canopy structure. On average, degraded forests contained 45.1% of thecarbon stocks in intact forests, and differences persisted even after 15 years of regrowth. Incomparison to logging, understory fires resulted in the largest and longest-lasting differences in ACD.Heterogeneity in burned forest structure varied by fire severity and frequency. Forests with a historyof one, two, and three or more fires retained only 54.4%, 25.2%, and 7.6% of intact ACD,respectively, when measured after a year of regrowth. Unlike the additive impact of successive fires,selective logging before burning did not explain additional variability in modeled ACD loss andrecovery of burned forests. Airborne lidar also provides quantitative measures of habitat structure thatcan aid the estimation of co-benefits of avoided degradation. Notably, forest carbon stocks recoveredfaster than attributes of canopy structure that are critical for biodiversity in tropical forests, includingthe abundance of tall trees. We provide the first comprehensive look-up table of emissions factors forspecific degradation pathways at standard reporting intervals in the Amazon. Estimated carbon lossand recovery trajectories provide an important foundation for assessing the long-term contributionsfrom forest degradation to regional carbon cycling and advance our understanding of the currentstate of frontier forests.

Rappaport, Danielle I.↗

Long-term dynamics of soil, tree stem and ecosystem methane fluxes in a riparian forest

The carbon (C) budgets of riparian forests are sensitive to climatic variability. Therefore, riparian forests are hot spots of C cycling in landscapes. Only a limited number of studies on continuous measurements of methane (CH 4 ) fluxes from riparian forests is available. Here, in this work, we report continuous high-frequency soil and ecosystem (eddy-covariance; EC) measurements of CH 4 fluxes with a quantum cascade laser absorption spectrometer for a 2.5-year period and measurements of CH 4 fluxes from tree stems using manual chambers for a 1.5 year period from a temperate riparian Alnus incana forest. The results demonstrate that the riparian forest is a minor net annual sink of CH 4 consuming 0.24 kg CH 4 -C ha –1 y –1 . Soil water content is the most important determinant of soil, stem, and EC fluxes, followed by soil temperature. There were significant differences in CH 4 fluxes between the wet and dry periods. During the wet period, 83% of CH 4 was emitted from the tree stems while the ecosystem-level emission was equal to the sum of soil and stem emissions. During the dry period, CH 4 was substantially consumed in the soil whereas stem emissions were very low. A significant difference between the EC fluxes and the sum of soil and stem fluxes during the dry period is most likely caused by emission from the canopy whereas at the ecosystem level the forest was a clear CH 4 sink. Our results together with past measurements of CH 4 fluxes in other riparian forests suggest that temperate riparian forests can be long-term CH 4 sinks.

54 ENVIRONMENTAL SCIENCES↗

Development of a Conditioned System-Level Groundwater Model to Evaluate Long-Term Groundwater Impacts within a Performance Assessment - 20115

A preliminary performance assessment (PA) of single-shell tank Waste Management Area (WMA) A-AX located at the U.S. Department of Energy (DOE)'s Hanford Site in southeastern Washington is being conducted to satisfy the requirements of DOE Order 435.1 [1] as it relates to closure of the single-shell radioactive waste tanks in the WMA A-AX tank farms. A PA assesses the fate, transport, and impacts of radionuclides within a low-level radioactive waste disposal facility in its assumed closure configuration and the subsequent potential doses to humans over a 1,000-year compliance period and a 10,000-year performance evaluation period. The WMA A-AX preliminary PA evaluation is structured around the complementary use of process-level and system-level models to calculate the facility performance against established DOE Order 435.1 [1] performance objectives. Process-level models are those that represent a detailed phenomenological representation of processes of concern in the PA. Process models typically only represent one or a few of the components of the PA, such as groundwater flow and transport, and must be integrated with other modeling elements to perform PA calculations. System-level models are those that are abstracted from the process models, retaining the essential features of the process model, while allowing integration of all aspects of the PA in a single modeling framework. System-level models are often characterized by coarser numerical discretization, lower dimensionality, or other similar simplifications compared to the process-level model. Traditionally, a three-dimensional (3-D) process-level model is utilized primarily to evaluate the long-term impact on groundwater and the potential doses to individuals who consume contaminated groundwater. System-level models are also utilized to evaluate the groundwater pathway in PAs. These models typically have reduced dimensionality (1-D) and are conditioned utilizing flow fields (Darcy fluxes) and moisture content distributions that are abstracted from the process level models. The abstraction approach assures that the flow field in both models is consistent for a specific set of input parameters for flow, differing only in the discretization and dimensionality of the two models. The preliminary WMA A-AX PA incorporates a detailed representation of the geological system and hydraulic properties within the 3-D model STOMP{sup C} numerical code so that the effects of relevant features and processes on water flow and radionuclide transport in the subsurface can be evaluated. The complementary system-level model is developed utilizing the GoldSim{sup C} code to implement a simplified, 1-D equivalent model to represent the groundwater pathway. Contaminant transport through the vadose zone and unconfined aquifer for Tc-99 and I-129 were evaluated in each of the models. Adjustments to the saturated portion of the GoldSim{sup C} 1-D model were required to mimic the dispersion effect captured with the 3-D STOMP{sup C} model. Once this conditioning was conducted, highly similar results for the transport of Tc-99 and I-129 were achieved at the point of calculation, located 100 m downgradient from the WMA A-AX fenceline. These radionuclides represent elements that are regarded as primary dose drivers in the PA groundwater pathway analysis. The high degree of conformance between the two models suggests that the use of the equivalent 1-D system model is suitable for evaluating the full suite of radionuclides that will be released from the tank sources within WMA A-AX over the 1,000-year compliance period and over the 10,000-year evaluation period. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

High yield, large-scale synthesis of calcium-based microporous metal-organic framework and examination of the long-term stability for xenon adsorption applications

Here, scale-up synthesis of calcium-based microporous metal-organic framework (SBMOF-1) up to ~400 g in a batch with a yield of >90 % was achieved by a solvothermal reaction of sulfonyldibenzoic acid (SDB) with an excess of calcium chloride. Here, we observed that recrystallization of unreacted SDB at a solvothermal condition caused a moderate reaction yield (40–50 %) at the reference condition of $C_{CaCl_2}$/$C_{SDB}$=1 and $C_{SDB}$/$C_{SDB(ref)}$=1. Simply adding more reagents to the reactor did not increase the mass of product formed per unit volume due to a more pronounced loss of the yield at those conditions. By simultaneously changing the molar ratio of CaCl 2 to SDB, $C_{CaCl_2}$/$C_{SDB}$, and the molar concentration of the SDB reagent, $C_{SDB}$/$C_{SDB(ref)}$, we explored %yield of the reaction. Interestingly, a linear improvement in the yield was observed from 21% (at $C_{CaCl_2}$/$C_{SDB}$=0.5) up to 78% (at $C_{CaCl_2}$/$C_{SDB}$=6) at a fixed ratio of $C_{SDB}$/$C_{SDB(ref)}$=2 and the yield leveled off after further addition. Unlike those at $C_{CaCl_2}$/$C_{SDB}$=1, the yields at a high CaCl 2 excess continued to improve with increasing the $C_{SDB}$/$C_{SDB(ref)}$. When a large pressure vessel (2500 mL EtOH, $C_{CaCl_2}$/$C_{SDB}$=6, $C_{SDB}$/$C_{SDB(ref)}$=8) was used, about 415 g of SBMOF-1 with a yield of 92.3% was produced, indicating 16 × the space yield improvement. The ability to synthesize SBMOF-1 on a large scale allowed us to examine the long-term stability of SBMOF-1 for almost 200 days in the presence of varying levels of relative humidity.

36 MATERIALS SCIENCE↗

BioSentinel: Optimizing Growth Conditions for Improved Yeast Cell Viability After Long-Term Desiccation

NASA's BioSentinel mission is one of thirteen secondary payloads to be deployed on the Space Launch System Exploration Mission-1 (SLS EM-1). The BioSentinel nanosatellite will be sent into a heliocentric orbit beyond Low Earth Orbit (LEO), to study the effects of deep space radiation on the budding yeast, Saccharomyces cerevisiae. Ionizing radiation encountered in deep space can create damaging lesions in DNA, including double strand breaks (DSBs). Budding yeast is suitable as a biological model to study these effects, as it is eukaryotic, and can be desiccated for prolonged periods while retaining viability, thus serving as a robust analog for human cells. On the ground, yeast cells are grown in liquid medium, then loaded into the wells of microfluidic cards and air dried prior to integration into the payload. Once the spacecraft reaches its target heliocentric orbit, a mixture of growth medium and metabolic indicator dye will be pumped into the microwells at specific time points to rehydrate the cells and allow them to grow. A 3-color LED detection system will measure changes in growth and metabolism resulting from ionizing radiation exposure. BioSentinel contains a wild type control strain and a rad51 mutant that is defective for DNA damage repair. In this study, we will determine the optimal amount of time to grow diploid yeast cells in liquid culture before they are desiccated for space flight. After an extended time in stationary phase, they become more tolerant to desiccation due to stress caused by nitrogen starvation. However, excessive exposure can lead to loss of viability and to a heterogeneous cell population due to sporulation. Since viability loss during desiccation poses a risk to mission success, a stress preconditioning process during initial growth may increase long-term cell viability. To determine the growth period that improves desiccation tolerance but allows for retention of uniform radiation sensitivity, we will grow both strains in liquid medium for a varying number of days (4 to 7), desiccate the cells, and then observe changes to cell viability and ionizing radiation sensitivity over time. Supported by the Space Life Sciences Training Program at NASA Ames Research Center.

Cui, Kaixin↗

Long-term leaf C:N ratio change under elevated CO 2 and nitrogen deposition in China: Evidence from observations and process-based modeling

Climate change, elevating atmosphere CO 2 (eCO 2 ) and increased nitrogen deposition (iNDEP) are altering the biogeochemical interactions between plants, microbes and soils, which further modify plant leaf carbon-nitrogen (C:N) stoichiometry and their carbon assimilation capability. Many field experiments have observed large sensitivity of leaf C:N ratio to eCO 2 and iNDEP. However, the large-scale pattern of this sensitivity is still unclear, because eCO 2 and iNDEP drive leaf C:N ratio toward opposite directions, which are further compounded by the complex processes of nitrogen acquisition and plant-and-microbial nitrogen competition. Here, we attempt to map the leaf C:N ratio spatial variation in the past 5 decades in China with a combination of data-driven model and process-based modeling. These two approaches showed consistent results. Over different regions, we found that leaf C:N ratio had significant but uneven changes between 2 time periods (1960-1989 and 1990-2015): a 5% ± 8% increase for temperate grasslands in northern China, a 3% ± 6% increase for boreal grasslands in western China, and by contrast, a 7% ± 6% decrease for temperate forests in southern China, and a 3% ± 5% decrease for boreal forests in northeastern China. Additionally, the structural equation models indicated that the leaf C:N change was sensitive to ΔNDEP, ΔCO 2 and ΔMAT rather than ΔMAP and ecosystem types. In this work, process-based modeling suggested that iNDEP was the main source of soil mineral nitrogen change, dominating leaf C:N ratio change in most areas in China, while eCO 2 led to leaf C:N ratio increase in low iNDEP area. This study also indicates that the long-term leaf C:N ratio acclimation was dominated by climate constraint, especially temperature, but was constrained by soil N availability over decade scale.

54 ENVIRONMENTAL SCIENCES↗

SPRUCE Anaerobic oxidation of methane mitigates net methane production and responds to long-term experimental warming in a northern bog: Supporting data

This data set contains measurements of anaerobic oxidation of methane (AOM), net methane (CH4) production, carbon dioxide (CO2) production, and gross CH4 production measurements from the SPRUCE experiment (Hanson et al. 2017). CH4 is greenhouse gas with 45 times the sustained global warming potential of CO2 over 100 years, which may have significant implications on global climate change. The process of AOM plays a large role in the extent of CH4 emissions from wetland environments like those at the SPRUCE experiment site. This study conducted two on different dates. In experiment 1, net CH4 and CO2 production were measured with a gas chromatograph through the peat profile at in situ temperatures of the SPRUCE plots four times from May to October, 2016 (2016-05 to 2016-10). Two treatments were examined, a Porewater Treatment that was a 1:1 volumetric peat:porewater slurry and a No Porewater Treatment that was field-moist peat with no porewater added. Additionally, net CH4 production were measured at frequent intervals (from 4 hr to 9 d) in peat from selected SPRUCE plots from soil collected on October 16, 2016 (2016-10-16). Samples were collected from the SPRUCE plots, immediately made anaerobic, and transported to the University of Oregon for rate measurements within several days of collection. In experiment 2, AOM, net CH4 production, CO2 production, and gross CH4 production were measured through the peat profile at in situ field temperatures once from samples collected in July, 2021 (2021-07). The same two porewater treatments were examined. AOM was measured with a 13CH4 tracer method using a Picarro G2201-i analyzer for isotopic CO2/CH4 quantification with a small stable isotope module attached. This data set contains three data files in comma separate (*.csv) format. This data set is associated with the following publication: Barney, M, AM Hopple, LL Gregory, JK Keller, and SD Bridgham. 2024. Anaerobic oxidation of methane mitigates net methane production and responds to long-term experimental warming in a northern bog. Soil Biology and Biochemistry, 190, 109316. https://doi.org/10.1016/j.soilbio.2024.109316.

SPRUCE Experiment, Marcell Experimental Forest, Me↗

Long-term Satellite Observations of Asian Dust Storm: Source, Pathway, and Interannual Variability

Among the many components that contribute to air pollution, airborne mineral dust plays an important role due to its biogeochemical impact on the ecosystem and its radiative-forcing effect on the climate system. In East Asia, dust storms frequently accompany the cold and dry air masses that occur as part of springtime cold front systems. Outbreaks of Asian dust storms occur often in the arid and semi-arid areas of northwestern China -about 1.6x10(exp 6) square kilometers including the Gobi and Taklimakan deserts- with continuous expanding of spatial coverage. These airborne dust particles, originating in desert areas far from polluted regions, interact with anthropogenic sulfate and soot aerosols emitted from Chinese megacities during their transport over the mainland. Adding the intricate effects of clouds and marine aerosols, dust particles reaching the marine environment can have drastically different properties than those from their sources. Furthermore, these aerosols, once generated over the source regions, can be transported out of the boundary layer into the free troposphere and can travel thousands of kilometers across the Pacific into the United States and beyond. In this paper, we will demonstrate the capability of a new satellite algorithm to retrieve aerosol properties (e.g., optical thickness, single scattering albedo) over bright-reflecting surfaces such as urban areas and deserts. Such retrievals have been difficult to perform using previously available algorithms that use wavelengths from the mid-visible to the near IR because they have trouble separating the aerosol signal from the contribution due to the bright surface reflectance. This new algorithm, called Deep Blue, utilizes blue-wavelength measurements from instruments such as SeaWiFS and MODIS to infer the properties of aerosols, since the surface reflectance over land in the blue part of the spectrum is much lower than for longer wavelength channels. Reasonable agreements have been achieved between Deep Blue retrievals of aerosol optical thickness and those directly from AERONET sunphotometers over desert and semi-desert regions. New Deep Blue products will allow scientists to determine quantitatively the aerosol properties near sources using high spatial resolution measurements from SeaWiFS and MODIS-like instruments. Long-term satellite measurements (1998 - 2007) from SeaWiFS will be utilized to investigate the interannual variability of source, pathway, and dust loading associated with the Asian dust storm outbreaks. In addition, monthly averaged aerosol optical thickness during the springtime from SeaWiFS will also be compared with the MODIS Deep Blue products.

Hsu, N. Christina↗

Estimating Long Term Surface Soil Moisture in the GCIP Area From Satellite Microwave Observations

Soil moisture is an important component of the water and energy balances of the Earth's surface. Furthermore, it has been identified as a parameter of significant potential for improving the accuracy of large-scale land surface-atmosphere interaction models. However, accurate estimates of surface soil moisture are often difficult to make, especially at large spatial scales. Soil moisture is a highly variable land surface parameter, and while point measurements are usually accurate, they are representative only of the immediate site which was sampled. Simple averaging of point values to obtain spatial means often leads to substantial errors. Since remotely sensed observations are already a spatially averaged or areally integrated value, they are ideally suited for measuring land surface parameters, and as such, are a logical input to regional or larger scale land process models. A nine-year database of surface soil moisture is being developed for the Central United States from satellite microwave observations. This region forms much of the GCIP study area, and contains most of the Mississippi, Rio Grande, and Red River drainages. Daytime and nighttime microwave brightness temperatures were observed at a frequency of 6.6 GHz, by the Scanning Multichannel Microwave Radiometer (SMMR), onboard the Nimbus 7 satellite. The life of the SMMR instrument spanned from Nov. 1978 to Aug. 1987. At 6.6 GHz, the instrument provided a spatial resolution of approximately 150 km, and an orbital frequency over any pixel-sized area of about 2 daytime and 2 nighttime passes per week. Ground measurements of surface soil moisture from various locations throughout the study area are used to calibrate the microwave observations. Because ground measurements are usually only single point values, and since the time of satellite coverage does not always coincide with the ground measurements, the soil moisture data were used to calibrate a regional water balance for the top 1, 5, and 10 cm surface layers in order to interpolate daily surface moisture values. Such a climate-based approach is often more appropriate for estimating large-area spatially averaged soil moisture because meteorological data are generally more spatially representative than isolated point measurements of soil moisture. Vegetation radiative transfer characteristics, such as the canopy transmissivity, were estimated from vegetation indices such as the Normalized Difference Vegetation Index (NDVI) and the 37 GHz Microwave Polarization Difference Index (MPDI). Passive microwave remote sensing presents the greatest potential for providing regular spatially representative estimates of surface soil moisture at global scales. Real time estimates should improve weather and climate modelling efforts, while the development of historical data sets will provide necessary information for simulation and validation of long-term climate and global change studies.

Owe, Manfred↗

An Approach for the Long-Term 30-m Land Surface Snow-Free Albedo Retrieval from Historic Landsat Surface Reflectance and MODIS-based A Priori Anisotropy Knowledge

Land surface albedo has been recognized by the Global Terrestrial Observing System (GTOS) as an essential climate variable crucial for accurate modeling and monitoring of the Earth's radiative budget. While global climate studies can leverage albedo datasets from MODIS, VIIRS, and other coarse-resolution sensors, many applications in heterogeneous environments can benefit from higher-resolution albedo products derived from Landsat. We previously developed a "MODIS-concurrent" approach for the 30-meter albedo estimation which relied on combining post-2000 Landsat data with MODIS Bidirectional Reflectance Distribution Function (BRDF) information. Here we present a "pre-MODIS era" approach to extend 30-m surface albedo generation in time back to the 1980s, through an a priori anisotropy Look-Up Table (LUT) built up from the high quality MCD43A BRDF estimates over representative homogenous regions. Each entry in the LUT reflects a unique combination of land cover, seasonality, terrain information, disturbance age and type, and Landsat optical spectral bands. An initial conceptual LUT was created for the Pacific Northwest (PNW) of the United States and provides BRDF shapes estimated from MODIS observations for undisturbed and disturbed surface types (including recovery trajectories of burned areas and non-fire disturbances). By accepting the assumption of a generally invariant BRDF shape for similar land surface structures as a priori information, spectral white-sky and black-sky albedos are derived through albedo-to-nadir reflectance ratios as a bridge between the Landsat and MODIS scale. A further narrow-to-broadband conversion based on radiative transfer simulations is adopted to produce broadband albedos at visible, near infrared, and shortwave regimes.We evaluate the accuracy of resultant Landsat albedo using available field measurements at forested AmeriFlux stations in the PNW region, and examine the consistency of the surface albedo generated by this approach respectively with that from the "concurrent" approach and the coincident MODIS operational surface albedo products. Using the tower measurements as reference, the derived Landsat 30-m snow-free shortwave broadband albedo yields an absolute accuracy of 0.02 with a root mean square error less than 0.016 and a bias of no more than 0.007. A further cross-comparison over individual scenes shows that the retrieved white sky shortwave albedo from the "pre-MODIS era" LUT approach is highly consistent (R(exp 2) = 0.988, the scene-averaged low RMSE = 0.009 and bias = −0.005) with that generated by the earlier "concurrent" approach. The Landsat albedo also exhibits more detailed landscape texture and a wider dynamic range of albedo values than the coincident 500-m MODIS operational products (MCD43A3), especially in the heterogeneous regions. Collectively, the "pre-MODIS" LUT and "concurrent" approaches provide a practical way to retrieve long-term Landsat albedo from the historic Landsat archives as far back as the 1980s, as well as the current Landsat-8 mission, and thus support investigations into the evolution of the albedo of terrestrial biomes at fine resolution.

Albedo algorithm↗

Technology Alignment and Portfolio Prioritization (TAPP): Advanced Methods in Strategic Analysis, Technology Forecasting and Long Term Planning for Human Exploration and Operations, Advanced Exploration Systems and Advanced Concepts

The Advanced Concepts Office (ACO) at NASA, Marshall Space Flight Center is expanding its current technology assessment methodologies. ACO is developing a framework called TAPP that uses a variety of methods, such as association mining and rule learning from data mining, structure development using a Technological Innovation System (TIS), and social network modeling to measure structural relationships. The role of ACO is to 1) produce a broad spectrum of ideas and alternatives for a variety of NASA's missions, 2) determine mission architecture feasibility and appropriateness to NASA's strategic plans, and 3) define a project in enough detail to establish an initial baseline capable of meeting mission objectives ACO's role supports the decision­-making process associated with the maturation of concepts for traveling through, living in, and understanding space. ACO performs concept studies and technology assessments to determine the degree of alignment between mission objectives and new technologies. The first step in technology assessment is to identify the current technology maturity in terms of a technology readiness level (TRL). The second step is to determine the difficulty associated with advancing a technology from one state to the next state. NASA has used TRLs since 1970 and ACO formalized them in 1995. The DoD, ESA, Oil & Gas, and DoE have adopted TRLs as a means to assess technology maturity. However, "with the emergence of more complex systems and system of systems, it has been increasingly recognized that TRL assessments have limitations, especially when considering [the] integration of complex systems." When performing the second step in a technology assessment, NASA requires that an Advancement Degree of Difficulty (AD2) method be utilized. NASA has used and developed or used a variety of methods to perform this step: Expert Opinion or Delphi Approach, Value Engineering or Value Stream, Analytical Hierarchy Process (AHP), Technique for the Order of Prioritization by Similarity to Ideal Solution (TOPSIS), and other multi­‐criteria decision-making methods. These methods can be labor-intensive, often contain cognitive or parochial bias, and do not consider the competing prioritization between mission architectures. Strategic Decision-Making (SDM) processes cannot be properly understood unless the context of the technology is understood. This makes assessing technological change particularly challenging due to the relationships "between incumbent technology and the incumbent (innovation) system in relation to the emerging technology and the emerging innovation system." The central idea in technology dynamics is to consider all activities that contribute to the development, diffusion, and use of innovations as system functions. Bergek defines system functions within a TIS to address what is actually happening and has a direct influence on the ultimate performance of the system and technology development. ACO uses similar metrics and is expanding these metrics to account for the structure and context of the technology. At NASA technology and strategy is strongly interrelated. NASA's Strategic Space Technology Investment Plan (SSTIP) prioritizes those technologies essential to the pursuit of NASA's missions and national interests. The SSTIP is strongly coupled with NASA's Technology Roadmaps to provide investment guidance during the next four years, within a twenty-year horizon. This paper discusses the methods ACO is currently developing to better perform technology assessments while taking into consideration Strategic Alignment, Technology Forecasting, and Long Term Planning.

Funaro, Gregory V.↗

Long-term behaviour of starspots. III - Active longitudes on the long-period RS CVn star HK Lacertae

Thirteen years of photometry were used to study active longitudes on the surface of HK Lacertae. The decaying and forming phenomena of active areas in the years of 1980-1981, 1983-1984, and 1988-1989 are shown. New activity centers suddenly occur near the same orbital phase (0.6) and have lifetimes of several (greater than 6) years. The average rotational period of HK Lac is 24.2852 d; compared to the orbital period of 24.4284 d, this implies a 32 degree/year drift of the active areas on the stellar surface. Two possible interpretations for the period difference are discussed: pseudosynchronism and rigidity of magnetic patterns. The active longitudes on HK Lac are compared with similar phenomena found on the sun.

Olah, K.↗

Long-term impact of light- and elevated temperature-induced degradation on photovoltaic arrays

Low levelized cost of electricity (LCOE) has been identified as critical for widespread adoption of photovoltaics (PV) without subsidies. Maintaining decades-long high-energy production is often an under-recognized opportunity in meeting cost goals because component lifetimes are not fully quantified at the time of manufacture. Whereas certain standardized tests minimize risk of early failure, there is little guidance to quantitatively predict degradation (or lack thereof) over decades, based on accelerated tests. In this article, we move toward bridging the understanding between indoor accelerated tests and outdoor performance data, with the goal of predicting energy yield with enough accuracy to inform financial decisions. Light- and elevated temperature-induced degradation (LETID) in p-type Si modules is analyzed in terms of impact on long-term module performance and thus LCOE. A method to predict the progression of LETID, using fixed kinetic constants and a numerical solution to the basic reaction rate equations, is detailed. Predictions are compared against both published data and that new to this study. These data include both indoor accelerated tests and fielded modules. We use the results in financial models to derive LCOE of modules in different climates with varying amounts of LETID, including uncertainty. Cost models based on the predictions indicate that LETID has a significant and climate-dependent impact on LCOE. Finally, we show that - even given the uncertainties identified in the study - these financial calculations can provide useful guidance to quantify risk based on accelerated test results. The analysis serves as an example of developing a predictive approach to PV reliability using physics of failure.

14 SOLAR ENERGY↗

A New View of Radiation-Induced Cancer: Integrating Short- and Long-Term Processes. Part II: Second Cancer Risk Estimation

As the number of cancer survivors grows, prediction of radiotherapy-induced second cancer risks becomes increasingly important. Because the latency period for solid tumors is long, the risks of recently introduced radiotherapy protocols are not yet directly measurable. In the accompanying article, we presented a new biologically based mathematical model, which, in principle, can estimate second cancer risks for any protocol. The novelty of the model is that it integrates, into a single formalism, mechanistic analyses of pre-malignant cell dynamics on two different time scales: short-term during radiotherapy and recovery; long-term during the entire life span. Here, we apply the model to nine solid cancer types (stomach, lung, colon, rectal, pancreatic, bladder, breast, central nervous system, and thyroid) using data on radiotherapy-induced second malignancies, on Japanese atomic bomb survivors, and on background US cancer incidence. Potentially, the model can be incorporated into radiotherapy treatment planning algorithms, adding second cancer risk as an optimization criterion.

Shuryak, Igor↗

On the Sensitivity of Atmospheric Ensembles to Cloud Microphysics in Long-Term Cloud-Resolving Model Simulations

Month-long large-scale forcing data from two field campaigns are used to drive a cloud-resolving model (CRM) and produce ensemble simulations of clouds and precipitation. Observational data are then used to evaluate the model results. To improve the model results, a new parameterization of the Bergeron process is proposed that incorporates the number concentration of ice nuclei (IN). Numerical simulations reveal that atmospheric ensembles are sensitive to IN concentration and ice crystal multiplication. Two- (2D) and three-dimensional (3D) simulations are carried out to address the sensitivity of atmospheric ensembles to model dimensionality. It is found that the ensembles with high IN concentration are more sensitive to dimensionality than those with low IN concentration. Both the analytic solutions of linear dry models and the CRM output show that there are more convective cores with stronger updrafts in 3D simulations than in 2D, which explains the differing sensitivity of the ensembles to dimensionality at different IN concentrations.

Zeng, Xiping↗

Land Long Term Climate Data Record

AVHRR data record is well alive and continue to improve and be used by a large land user community.Most of the improvement are due to the overlapping with MODIS Aqua, Terra.We recommend operating missions as long as possible to enable overlap of at least a few years (especially for applications).

Long term climate data record↗

Mechanism-based Modeling of Long-term Degradation

The use of composites in high temperature, long lifetime applications requires a basic understanding of composite degradation mechanisms, advances in analytical capabilities, and accurate accelerated and scaled tests. To advance all of these goals, models are proposed based on a variety of fundamental material mechanisms. Thermal, oxygen, and moisture diffusion, chemical reactions, composite micromechanics; modified laminated plate theory, and future mechanics based damage models are used. All models attempt to stay as simple and fundamental as possible. All are coupled, so that interactions between various effects are modeled implicitly. Ongoing efforts at MIT are reviewed here, with some reference to other work, but no attempt is made to do a comprehensive review. Mechanism based models are yielding understanding of the mechanisms behind observed degradation phenomena, are helping to design accelerated tests, and are the first steps towards a predictive capability.

McManus, H. L.↗