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At least 1,459 records · Page 81

Experimental evaluation of fluctuating density and radiated noise from a high temperature jet

An experimental investigation has been conducted to characterize the fluctuating density within a high-temperature (1100 K) subsonic jet and to characterize by the noise radiated to the surroundings. Cross correlations obtained by introducing time delay to the signals detected from spatially separated crossed laser beams set up as a Schlieren system were used to determine radial and axial distributions of the convection velocity of the moving noise sources (eddies). In addition, the autocorrelation of the fluctuating density was evaluated in the moving frame of reference of the eddies. Also, the autocorrelation of the radiated noise in the moving reference frame was evaluated from cross correlations by introducing time delay to the signals detected by spatially separated pairs of microphones. Radial distributions of the mean velocity were obtained from measurements of the stagnation temperature, and stagnation and static pressures with the use of probes.

Massier, P. F.↗

Experimental evaluation of fluctuating density and radiated noise from a high-temperature jet

An experimental investigation has been conducted to characterize the fluctuating density within a high temperature (1100 K) subsonic jet and to characterize the noise radiated to the surroundings. Cross correlations obtained by introducing time delay to the signals detected from spatially separated crossed laser beams set up as a schlieren system were used to determine radial and axial distributions of the convection velocity of the moving noise sources (eddies). In addition, the autocorrelation of the fluctuating density was evaluated in the moving frame of reference of the eddies. Also, the autocorrelation of the radiated noise in the moving reference frame was evaluated from cross correlations by introducing time delay to the signals detected by spatially separated pairs of microphones. The radiated noise results are compared with Lighthill's theory and with the data of Lush. Radial distributions of the mean velocity were obtained from measurements of the stagnation temperature, and stagnation and static pressures with the use of probes.

Massier, P. F.↗

Quantification of Deformation-Induced Concentration Fluctuations in Polymeric Liquids by Small-Angle Neutron Scattering

This study demonstrates how the large concentration fluctuations of polymeric liquids under deformation and flow can be quantitatively studied by applying the spherical harmonic expansion technique to small-angle neutron scattering. Using a series of binary polymer blends, it is shown that the emergence of the so-called butterfly patterns is caused by the change of sign in the leading anisotropic component of the small-angle spectrum, when the scattering is dominated by intermolecular correlation associated with flow-induced demixing. The increasing spatial fluctuations of concentration are evidenced by the enhancement of the isotropic component of the scattering spectrum in the zero-angle limit and peak shift of the leading anisotropic coefficients toward low Q. Additionally, the spherical harmonic expansion framework permits real-space analysis of anisotropic scattering length density correlation in a convenient form. The methodology described in this work provides a concrete venue for quantitative studies of phase behavior of fluids under deformation and flow via small-angle scattering techniques, where mainly qualitative approaches were previously employed.

Chemical structure↗

Spatial Effect on the Performance of Carboxylate Anode Materials in Na-Ion Batteries

Developing low-voltage carboxylate anode materials is critical for achieving low-cost, high-performance, and sustainable Na-ion batteries (NIBs). However, the structure design rationale and structure-performance correlation for organic carboxylates in NIBs remains elusive. Herein, the spatial effect on the performance of carboxylate anode materials is studied by introducing heteroatoms in the conjugation structure and manipulating the positions of carboxylate groups in the aromatic rings. Planar and twisted organic carboxylates are designed and synthesized to gain insight into the impact of geometric structures to the electrochemical performance of carboxylate anodes in NIBs. Among the carboxylates, disodium 2,2’-bipyridine-5,5’-dicarboxylate (2255-Na) with a planar structure outperforms the others in terms of highest specific capacity (210 mAh g -1 ), longest cycle life (2000 cycles), and best rate capability (up to 5 A g -1 ). Further, the cyclic stability and redox mechanism of 2255-Na in NIBs are exploited by various characterization techniques. Moreover, high-temperature (up to 100 °C) and all-organic batteries based on a 2255-Na anode, a polyaniline (PANI) cathode, and an ether-based electrolyte are achieved and exhibited exceptional electrochemical performance. Therefore, this work demonstrates that designing organic carboxylates with extended planar conjugation structures is an effective strategy to achieve high-performance and sustainable NIBs.

25 ENERGY STORAGE↗

Establishing a geochemical heterogeneity model for a contaminated vadose zone – Aquifer system

A large set of sediment samples from a 1600 m2 experimental plot within a 2.2 km2 vadose zone and groundwater uranium (VI) plume were subject to physical, chemical, and mineralogic characterization. The plot is being used for field experimentation on U(VI) recharge and transport processes within a persistent groundwater plume that exists in the groundwater-river interaction zone of the Columbia River at the U.S. DOE Hanford site. The samples were obtained during the installation of 35 tightly spaced (10 m separation) groundwater monitoring wells. The characterization measurements for each sample included total contaminant concentrations (U and Cu primarily), bicarbonate extractable U(VI), sequential 238U(VI) contaminant desorption Kd, 233U(VI) adsorption Kd, grain size distribution, surface area, extractable poorly crystalline Fe(III) oxides, and mineralogy. The characterization objective was to inform a conceptual model of coupled processes controlling the anomalous longevity of the plume, and to quantify the spatial heterogeneity of the contaminant inventory and the primary properties effecting reactive transport. Correlations were drawn between chemical, physical, and reaction properties, and Gaussian simulation was used to compute multiple 3-D realizations of extractable U(VI), the 233U(VI) adsorption Kd, and the distribution of the reactive < 2 mm fraction. Adsorbed contaminant U(VI) was highest in the vadose zone and the zone of seasonal water table fluctuation lying at its base. Adsorbed U(VI) was measureable, but low, in the groundwater plume region where very high hydraulic conductivities existed. The distribution of adsorbed U(VI) displayed no apparent correlation with sediment physical or chemical properties. Desorption [238U(IV)] and adsorption [233U(VI)] Kd values showed appreciable differences due to mass transfer controlled surface complexation and the effects of long subsurface residence times. The 233U(VI) adsorption Kd, a combined measure of surface complexation strength and site concentration, was relatively uniform throughout the domain, displaying correlation with fines distribution and surface area. The characterization results revealed U(VI) supplied to the groundwater plume through spatially heterogeneous recharge from residual contamination in the zone of seasonal water table fluctuation, and transport of U(VI) controlled by weak, kinetically-controlled surface complexation in the coarse-textured saturated zone. Geostatistical relationships for the adsorbed contaminant U distribution in the characterization domain allow an extrapolation to inventory at the plume scale, a critical unknown for remedial action.

contaminant heterogeniety, uranium groundwater plu↗

THE ROLE OF TURBULENCE IN NEUTRINO-DRIVEN CORE-COLLAPSE SUPERNOVA EXPLOSIONS

The neutrino-heated ''gain layer'' immediately behind the stalled shock in a core-collapse supernova is unstable to high-Reynolds-number turbulent convection. We carry out and analyze a new set of 19 high-resolution three-dimensional (3D) simulations with a three-species neutrino leakage/heating scheme and compare with spherically symmetric (one-dimensional, 1D) and axisymmetric (two-dimensional, 2D) simulations carried out with the same methods. We study the postbounce supernova evolution in a 15 M {sub ☉} progenitor star and vary the local neutrino heating rate, the magnitude and spatial dependence of asphericity from convective burning in the Si/O shell, and spatial resolution. Our simulations suggest that there is a direct correlation between the strength of turbulence in the gain layer and the susceptibility to explosion. 2D and 3D simulations explode at much lower neutrino heating rates than 1D simulations. This is commonly explained by the fact that nonradial dynamics allows accreting material to stay longer in the gain layer. We show that this explanation is incomplete. Our results indicate that the effective turbulent ram pressure exerted on the shock plays a crucial role by allowing multi-dimensional models to explode at a lower postshock thermal pressure and thus with less neutrino heating than 1D models. We connect the turbulent ram pressure with turbulent energy at large scales and in this way explain why 2D simulations are erroneously exploding more easily than 3D simulations.

79 ASTRONOMY AND ASTROPHYSICS↗

Analysis of the Amplitude Response of a Two-Point and a Two-Line/Multi-Point Focused Laser Differential Interferometer

Experiments were performed with two different focused laser differential interferometer (FLDI) instruments to assess the amplitude response of each instrument to a traveling shock-wave generated by a laser spark. The first FLDI instrument generated two measurement points, with each measurement point providing sensitivity to density fluctuations induced by the shockwave. By performing a cross-correlation between the signals obtained from each measurement point, the phase velocity of density fluctuations can be obtained. The second FLDI instrument generated two measurement lines that are oriented either parallel or orthogonal to the shockwave direction of travel with the resulting interference pattern sampled at multiple equally-spaced points along each line. As a result, this instrument provides density fluctuation measurement capability at multiple points simultaneously. When the measurement lines are oriented parallel to the shockwave direction of travel, the phase velocity, rate of change of the phase velocity, and acceleration of density fluctuations traveling along each line can be obtained by performing a cross-correlation between points along a single line. When the measurement lines are oriented orthogonal to the shockwave direction of travel, the spatially-varying phase velocity can be obtained by performing a cross-correlation between points at the same relative location on each measurement line. Computations of the shockwave generated by the laser spark are used to simulate the response of each instrument and are compared to the experimental results. High-speed Schlieren imaging has also been performed and is compared with the FLDI measurements and computational results.

Focused Laser Differential Interferometer↗

Characterization of mesoscopic turbulent transport events with long-radial-range correlation in DIII-D H-mode plasmas

A dimensionless collisionality scan has been performed in H-mode plasmas on DIII-D tokamak, with detailed measurements of intermediate-to-high wavenumber turbulence using Doppler backscattering systems. Furthermore, it is found that the shorter wavelength turbulence develops into spatially asymmetric turbulent structures with a long-radial-range correlation (LRRC) in the mid-radius region of high collisionality discharges. Linear cgyro simulations indicate that the underlying turbulence is likely driven by the electron-temperature-gradient mode.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

L1448-MM OBSERVATIONS BY THE HERSCHEL KEY PROGRAM, ''DUST, ICE, AND GAS IN TIME'' (DIGIT)

We present Herschel/Photodetector Array Camera and Spectrometer (PACS) observations of L1448-MM, a Class 0 protostar with a prominent outflow. Numerous emission lines are detected at 55 <λ < 210 μm including CO, OH, H{sub 2}O, and [O I]. We investigate the spatial distribution of each transition to find that lines from low energy levels tend to distribute along the outflow direction while lines from high energy levels peak at the central spatial pixel. Spatial maps reveal that OH emission lines are formed in a relatively small area, while [O I] emission is extended. According to the rotational diagram analysis, the CO emission can be fitted by two (warm and hot) temperature components. For H{sub 2}O, the ortho-to-para ratio is close to 3. The non-LTE large velocity gradient (LVG) calculations suggest that CO and H{sub 2}O lines could instead be formed in a high kinetic temperature (T > 1000 K) environment, indicative of a shock origin. For OH, IR-pumping processes play an important role in the level population. The molecular emission in L1448-MM is better explained with a C-shock model, but the atomic emission of PACS [O I] and Spitzer/Infrared Spectrograph [Si II] emission is not consistent with C-shocks, suggesting multiple shocks in this region. Water is the major line coolant of L1448-MM in the PACS wavelength range, and the best-fit LVG models predict that H{sub 2}O and CO emit (50%-80%) of their line luminosity in the PACS wavelength range.

79 ASTRONOMY AND ASTROPHYSICS↗

Multi-element effects on arsenate accumulation in a geochemical matrix determined using µ-XRF, µ-XANES and spatial statistics

Soils regulate the environmental impacts of trace elements, but direct measurements of reaction mechanisms in these complex, multi-component systems can be challenging. The objective of this work was to develop approaches for assessing effects of co-localized geochemical matrix elements on the accumulation and chemical speciation of arsenate applied to a soil matrix. Synchrotron X-ray fluorescence microprobe (µ-XRF) images collected across 100 µm × 100 µm and 10 µm × 10 µm regions of a naturally weathered soil sand-grain coating before and after treatment with As(V) solution showed strong positive partial correlations ( r ' = 0.77 and 0.64, respectively) between accumulated As and soil Fe, with weaker partial correlations ( r ' > 0.1) between As and Ca, and As and Zn in the larger image. Spatial and non-spatial regression models revealed a dominant contribution of Fe and minor contributions of Ca and Ti in predicting accumulated As, depending on the size of the sample area analyzed. Time-of-flight secondary ion mass spectrometry analysis of an area of the sand grain showed a significant correlation ( r = 0.51) between Fe and Al, so effects of Fe versus Al (hydr)oxides on accumulated As could not be separated. Fitting results from 25 As K -edge microscale X-ray absorption near-edge structure (µ-XANES) spectra collected across a separate 10 µm × 10 µm region showed ~60% variation in proportions of Fe(III) and Al(III)-bound As(V) standards, and fits to µ-XANES spectra collected across the 100 µm × 100 µm region were more variable. We find that, consistent with insights from studies on model systems, the results obtained here indicate a dominance of Fe and possibly Al (hydr)oxides in controlling As(V) accumulation within microsites of the soil matrix analyzed, but the analyses inferred minor augmentation from co-localized Ti, Ca and possibly Zn.

58 GEOSCIENCES↗

Kinetic theory of particle-in-cell simulation plasma and the ensemble averaging technique

Abstract We derive the kinetic theory of fluctuations in physically and numerically stable particle-in-cell (PIC) simulations of electrostatic plasmas. The starting point is the single-time correlation at the start of the simulation between the statistical fluctuations of the weighted densities of macroparticle centers in the plasma particle phase-space. The fluctuations are associated with different initial conditions, typically due to the random initial conditions (in velocity space) of the macroparticles/simulation plasma, assigned according to their initial distribution of probability. The single-time correlations at all time steps and in each spatial grid cell are then determined from the Laplace–Fourier transforms of the discretized Klimontovich-like equation for the macroparticles and Maxwell’s equations for the fields, as computed by modern PIC codes. We recover the expressions for the electrostatic field and the plasma particle density fluctuation autocorrelation spectra as well as the kinetic equations describing the average evolution of PIC-simulated plasma particles, first derived by Langdon (1970b Proc. 4th Conf. Numerical Simulation of Plasmas ) using a test macroparticle approach perturbing a discretized Vlasovian plasma and then averaging the obtained physical quantity over the initial macroparticle velocity distribution. We generalize and extend these results to the modern algorithms in PIC codes using arbitrary macroparticle weights. Analytical estimates of statistical fluctuation amplitudes are derived as a function of the plasma simulation parameters, using the central limit theorem in the limit of a large number of macroparticles per cell. The theory is then used to analyze the ensemble averaging technique of PIC simulations where statistical averages are performed over ensembles of PIC simulations, modeling the same plasma physics problem but using different statistical realizations of the initial distribution functions of the macroparticles. This method is illustrated by linear Landau damping uncovering (from noise, which is usually considered numerical) the physical fluctuations driven by a single small amplitude electrostatic wave perturbing a PIC simulation plasma in equilibrium.

fluctuations correlations↗

The Richness Dependence of Galaxy Cluster Correlations: Results From A Redshift Survey Of Rich APM Clusters

We analyze the spatial clustering properties of a new catalog of very rich galaxy clusters selected from the APM Galaxy Survey. These clusters are of comparable richness and space density to Abell Richness Class greater than or equal to 1 clusters, but selected using an objective algorithm from a catalog demonstrably free of artificial inhomogeneities. Evaluation of the two-point correlation function xi(sub cc)(r) for the full sample and for richer subsamples reveals that the correlation amplitude is consistent with that measured for lower richness APM clusters and X-ray selected clusters. We apply a maximum likelihood estimator to find the best fitting slope and amplitude of a power law fit to x(sub cc)(r), and to estimate the correlation length r(sub 0) (the value of r at which xi(sub cc)(r) is equal to unity). For clusters with a mean space density of 1.6 x 10(exp -6) h(exp 3) MpC(exp -3) (equivalent to the space density of Abell Richness greater than or equal to 2 clusters), we find r(sub 0) = 21.3(+11.1/-9.3) h(exp -1) Mpc (95% confidence limits). This is consistent with the weak richness dependence of xi(sub cc)(r) expected in Gaussian models of structure formation. In particular, the amplitude of xi(sub cc)(r) at all richnesses matches that of xi(sub cc)(r) for clusters selected in N-Body simulations of a low density Cold Dark Matter model.

Croft, R. A. C.↗

Early season prediction of within-field crop yield variability by assimilating CubeSat data into a crop model

Accurate early season predictions of crop yield at the within-field scale can be used to address a range of crop production, management, and precision agricultural challenges. While the remote sensing of within-field insights has been a research goal for many years, it is only recently that observations with the required spatio-temporal resolutions, together with efficient assimilation methods to integrate these into modeling frameworks, have become available to advance yield prediction efforts. Here we explore a yield prediction approach that combines daily high-resolution CubeSat imagery with the APSIM crop model. The approach employs APSIM to train a linear regression that relates simulated yield to simulated leaf area index (LAI). That relationship is then used to identify the optimal regression date at which the LAI provides the best prediction of yield: in this case, approximately 14 weeks prior to harvest. Instead of applying the regression on satellite imagery that is coincident, or closest to, the regression date, our method implements a particle filter that integrates CubeSat-based LAI into APSIM to provide end-of-season high-resolution (3 m) yield maps weeks before the optimal regression date. The approach is demonstrated on a rainfed maize field located in Nebraska, USA, where suitable collections of both imagery and in-situ data were available for assessment. The procedure does not require in-field data to calibrate the regression model, with results showing that even with a single assimilation step, it is possible to provide yield estimates with good accuracy up to 21 days before the optimal regression date. Yield spatial variability was reproduced reasonably well, with a strong correlation to independently collected measurements (R 2 = 0.73 and rRMSE = 12%). When the field averaged yield was compared, our approach reduced yield prediction error from 1 Mg/ha (control case based on a calibrated APSIM model), to 0.5 Mg/ha (using satellite imagery alone), and then to 0.2 Mg/ha (results with assimilation up to three weeks prior to the optimal regression date). Such a capacity to provide spatially explicit yield predictions early in the season has considerable potential to enhance digital agricultural goals and improve end-of-season yield predictions.

54 ENVIRONMENTAL SCIENCES↗

Decoupling of greenness and gross primary productivity as aridity decreases

Ecosystem primary productivity is a key ecological process influencing many ecosystem services, including carbon storage. Thus, clarifying how primary productivity in terrestrial ecosystems responds to climatic variability can reveal key mechanisms that will drive future changes in the global carbon budget. Satellite products of canopy greenness are widely used as proxies for vegetation productivity to evaluate how ecosystems respond to climate variability. However, to what degree inter-annual variations in productivity are consistent with greenness and how this relationship varies spatially remains unclear. Here we investigated the strength of the coupling between inter-annual variations in leaf area index (LAI, a measure of greenness) and ecosystem gross primary productivity (GPP) derived from eddy covariance towers, i.e., the r2 of the LAI-GPP relationship. Overall, inter-annual GPP and LAI were highly coupled (i.e., high r2) in arid grasslands, but were fully decoupled in mesic evergreen broadleaf forests, indicating that this relationship varies strongly along aridity gradients. A possible mechanism of the spatial variation in the LAI-GPP relationship is that the tradeoff between ecosystem structure (LAI) and physiology (photosynthesis per unit leaf area) becomes stronger in more humid climates. Land models overestimated the r2 of LAI-GPP correlation for most ecosystem types and failed to capture the spatial pattern along aridity gradients. We conclude that relying on greenness products for evaluating inter-annual changes in vegetation productivity may bias assessments, especially in tropical rainforest ecosystems. Our findings may also reconcile observed disparities between responses in greenness and GPP during drought in Amazon forests.

54 ENVIRONMENTAL SCIENCES↗

Temporal decorrelation in repeat pass-radar interferometry

Correlation in pass-to-pass, interferometric radar can be degraded by thermal noise, lack of parallelism between the radar flight tracks, spatial baseline noise, and surficial change. The effects of decorrelation due to thermal noise can be easily evaluated and removed, while those due slight angular changes between flight tracks are negligible for data acquired using near-repeat orbits. Empirical results obtained using images of Death Valley confirm that as the baseline increases, the overall correlation decreases due to spatial baseline noise. It is shown that areas of Cottonball Basin in Death Valley remained unchanged over the three-week period for which data was obtained, while a heavily forested area in Oregon exhibited significant temporal decorrelation. Lava in central Oregon also appeared to decorrelate. The results demonstrate that generation of height maps of heavily vegetated areas using pass-to-pass interferometry is practical, provided that the time between passes is at most several weeks.

Villasenor, John↗

Validation of Remotely Sensed and Modeled Soil Moisture at Forested and Unforested Sites

Soil moisture is an important driver for forest ecosystems, influencing fire occurrence and extent, insect and pathogen impacts, and tree growth, which creates a need for regular, globally extensive soil moisture information that only satellite-based sensors or models can achieve. However, the reliability of soil moisture measurements in forests is not well understood due to a lack of suitable validation sites (especially relative to unforested ecosystems) and interference caused by high vegetation water content on remotely sensed measurements; although recent studies have started to address this gap [1], [2], [3], [4]. Here we validate the performance of multiyear remotely sensed (SMAP/Sentinel), remotely sensed data assimilation modelled (SMAP-L4), and modelled (NLDAS) surface and root zone (0-1 m) soil moisture datasets with data from in-situ sensors at 39 National Ecological Observatory Network (NEON) sites throughout the contiguous US. Due to differences in spatial resolution, NEON soil moisture (~0.2 km measurement zone) correlations were expected to be stronger with the SMAP/Sentinel product (3 km resolution) than with coarser resolution SMAP-L4 (9 km resolution) or NLDAS products (13 km resolution). However, given the sensitivity of satellite measurements to vegetation water content we expected a deterioration in the correlations based on remotely sensed measurements (SMAP/Sentinel and SMAP-L4) as aboveground biomass increased, whereas the model-based data (NLDAS) was expected to be largely insensitive to vegetation type. We recognize that the SMAP/Sentinel product was developed for unforested regions, therefore our application is outside its primary use case. Soil moisture is measured at up to 8 depths in five soil plots spaced up to 40 m apart at each NEON terrestrial site. Correlation parameters were calculated for the three remotely sensed and modelled data products relative to in-situ measurement following Entekhabi et al. [5]. The datasets comprised 94 (SMAP-L4), 28 (SMAP/Sentinel), and 106 (NLDAS) sites-years for surface soils and 13 (SMAP-L4) and 14 (NLDAS) site-years for the root zone. At unforested sites, the performance of the three remotely sensed and modelled data products was similar for surface soils (Table 1). For example, unbiased RMSD (ubRMSD), which SMAP uses as its primary performance metric [6], ranged from 0.05 to 0.06 m3 m-3 (Table 1), indicating the ability of all three products to track changes in soil moisture over time. The performance of the three products deteriorated at forested sites, however, while the difference in performance was modest for SMAP-L4 and NLDAS, the deterioration in SMAP/Sentinel performance was substantial. For instance, SMAP/Sentinel ubRMSD increased from 0.06 to 0.11 m3 m-3 and absolute mean difference (Abs MD; which includes measurement bias and spatial representativeness errors) increased from 0.06 to 0.16 m3 m-3, indicating both a reduction in ability to track temporal changes and absolute amounts of soil moisture in forest ecosystems. SMAP-L4 and NLDAS had lower unbiased RMSD for root zone (0-1 m) than surface soils at both forested and unforested sites (Tables 1 and 2; SMAP/Sentinel does not produce a root zone measurement). However, in most cases the correlation coefficient (r) was lower for the root zone than surface soils, suggesting the lower unbiased RMSD may be attributed to greater temporal stability of soil moisture in the root zone rather than improved data product performance. Mean difference and absolute mean difference, which encompass measurement bias and spatial representativeness errors, were greater for root zone than surface soils at unforested sites for both data products, but the opposite was generally true at forested sites. As with surface soils, there was relatively little change in the performance of SMAP-L4 and NLDAS between the unforested and forested sites. In summary, all three data products were able to adequately represent soil moisture at unforested sites, at least when aggregating across sites. However, while the performance of all three products deteriorated at forested sites, SMAP-L4 and NLDAS maintained sufficient performance to remain suitable for some use cases (ubRMSD <0.06 m3 m-3 and RMSD <0.13 m3 m-3). In contrast, the relatively poorer performance of the SMAP/Sentinel product at forested sites seems insufficient for most use cases (ubRMSD >0.1 m3 m-3 and RMSD >0.2 m3 m-3). We attribute the large reduction in the performance of the SMAP/Sentinel product in forests to its use of C-band wavelengths, which are particularly sensitive to vegetation interference, and apparently outweighed any gains provided by its higher spatial resolution. A combined SMAP/NISAR soil moisture product may provide improved performance relative to SMAP/Sentinel due to NISAR’s use of L-band wavelengths, which are less sensitive to vegetation (NISAR is scheduled for launch in early 2024).

Edward Ayres↗

Role of CO 2 , climate and land use in regulating the seasonal amplitude increase of carbon fluxes in terrestrial ecosystems: A multimodel analysis

We examined the net terrestrial carbon flux to the atmosphere (F TA ) simulated by nine models from the TRENDY dynamic global vegetation model project for its seasonal cycle and amplitude trend during 1961-2012. While some models exhibit similar phase and amplitude compared to atmospheric inversions, with spring drawdown and autumn rebound, others tend to rebound early in summer. The model ensemble mean underestimates the magnitude of the seasonal cycle by 40g% compared to atmospheric inversions. Global F TA amplitude increase (19 ± 8%) and its decadal variability from the model ensemble are generally consistent with constraints from surface atmosphere observations. However, models disagree on attribution of this long-term amplitude increase, with factorial experiments attributing 83 ± 56%, -3 ± 74 and 20 ± 30% to rising CO 2 , climate change and land use/cover change, respectively. Seven out of the nine models suggest that CO 2 fertilization is the strongest control -with the notable exception of VEGAS, which attributes approximately equally to the three factors. Generally, all models display an enhanced seasonality over the boreal region in response to high-latitude warming, but a negative climate contribution from part of the Northern Hemisphere temperate region, and the net result is a divergence over climate change effect. Six of the nine models show that land use/cover change amplifies the seasonal cycle of global < i > F TA : some are due to forest regrowth, while others are caused by crop expansion or agricultural intensification, as revealed by their divergent spatial patterns. We also discovered a moderate cross-model correlation between < i > F TA amplitude increase and increase in land carbon sink ( < i > R 2 Combining double low line 0.61). Our results suggest that models can show similar results in some benchmarks with different underlying mechanisms; therefore, the spatial traits of CO 2 fertilization, climate change and land use/cover changes are crucial in determining the right mechanisms in seasonal carbon cycle change as well as mean sink change.

54 ENVIRONMENTAL SCIENCES↗