Engineering topics

Jain, Atul

Publications and source records attributed to Jain, Atul.

13 records

DOE OSTI2022

Process-oriented analysis of dominant sources of uncertainty in the land carbon sink

The observed global net land carbon sink is captured by current land models. All models agree that atmospheric CO 2 and nitrogen deposition driven gains in carbon stocks are partially offset by climate and land-use and land-cover change (LULCC) losses. However, there is a lack of consensus in the partitioning of the sink between vegetation and soil, where models do not even agree on the direction of change in carbon stocks over the past 60 years. This uncertainty is driven by plant productivity, allocation, and turnover response to atmospheric CO 2 (and to a smaller extent to LULCC), and the response of soil to LULCC (and to a lesser extent climate). Overall, differences in turnover explain ~70% of model spread in both vegetation and soil carbon changes. Further analysis of internal plant and soil (individual pools) cycling is needed to reduce uncertainty in the controlling processes behind the global land carbon sink.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Investigating the Impacts of Changes in Land Cover and Land Management on Climate Using ACME

The overall objective of our ACME project is to advance the treatment of land disturbance, particularly land use and land cover changes (LULCCs) and land management practices, and couple it with ALM to fully explore the potential contribution of LULCC and land management practices to future emissions and mitigation opportunities, and terrestrial carbon sources and sinks, and climate change. To achieve this objective, we have incorporated the advances made by DOE in IAM and ESM modeling efforts and our research at UIUC in global land disturbance, carbon management, and socioeconomic research.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Impacts of land use change and elevated CO 2 on the interannual variations and seasonal cycles of gross primary productivity in China

Climate change, rising CO 2 concentration, and landuse and land cover change (LULCC) are primary driving forces for terrestrialgross primary productivity (GPP), but their impacts on the temporal changesin GPP are uncertain. In this study, the effects of the three main factorson the interannual variation (IAV) and seasonal cycle amplitude (SCA) of GPPin China were investigated using 12 terrestrial biosphere models from theMulti-scale Synthesis and Terrestrial Model Intercomparison Project. Thesimulated ensemble mean value of China's GPP between 1981 and 2010, drivenby common climate forcing, LULCC and CO 2 data, was found to be7.4±1.8 Pg C yr -1 . In general, climate was the dominant controlfactor of the annual trends, IAV and seasonality of China's GPP. Theoverall rising CO2 led to enhanced plant photosynthesis, thusincreasing annual mean and IAV of China's total GPP, especially innortheastern and southern China, where vegetation is dense. LULCC decreasedthe IAV of China's total GPP by ~7%, whereas rising CO 2 induced an increase of 8 %. Compared to climate change andelevated CO 2 , LULCC showed less contributions to GPP's temporalvariation, and its impact acted locally, mainly in southwestern China.Furthermore, this study also examined subregional contributions to thetemporal changes in China's total GPP. Southern and southeastern Chinashowed higher contributions to China's annual GPP, whereas southwestern andcentral parts of China explained larger fractions of the IAV in China's GPP.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Response of Water Use Efficiency to Global Environmental Change Based on Output From Terrestrial Biosphere Models

Here, water use efficiency (WUE), defined as the ratio of gross primary productivity and evapotranspiration at the ecosystem scale, is a critical variable linking the carbon and water cycles. Incorporating a dependency on vapor pressure deficit, apparent underlying WUE (uWUE) provides a better indicator of how terrestrial ecosystems respond to environmental changes than other WUE formulations. Here we used 20th century simulations from four terrestrial biosphere models to develop a novel variance decomposition method. With this method, we attributed variations in apparent uWUE to both the trend and interannual variation of environmental drivers. The secular increase in atmospheric CO 2 explained a clear majority of total variation (66 ± 32%: mean ± one standard deviation), followed by positive trends in nitrogen deposition and climate, as well as a negative trend in land use change. In contrast, interannual variation was mostly driven by interannual climate variability. To analyze the mechanism of the CO 2 effect, we partitioned the apparent uWUE into the transpiration ratio (transpiration over evapotranspiration) and potential uWUE. The relative increase in potential uWUE parallels that of CO 2 , but this direct CO 2 effect was offset by 20 ± 4% by changes in ecosystem structure, that is, leaf area index for different vegetation types. However, the decrease in transpiration due to stomatal closure with rising CO 2 was reduced by 84% by an increase in leaf area index, resulting in small changes in the transpiration ratio. CO 2 concentration thus plays a dominant role in driving apparent uWUE variations over time, but its role differs for the two constituent components: potential uWUE and transpiration.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Global patterns of drought recovery

Drought has major impacts on natural and human systems, and is especially important for land carbon sink variability due to its influence on terrestrial biosphere climate regulation. While 20th Century trends in drought regimes have been varied, “more extreme extremes”, including more frequent and severe droughts, are expected in the 21st Century. Recovery time, the length of time an ecosystem requires to revert to its pre-drought functional state, is a critical metric of drought impact. Yet the factors influencing drought recovery and its spatiotemporal patterns are largely unknown. Here we use three independent global data products of gross primary productivity to show that, across diverse terrestrial ecosystems, drought recovery times are strongly associated with climate and carbon cycle dynamics, with biodiversity and CO 2 fertilization as secondary factors. Our analysis also provides two key insights into the spatiotemporal patterns of drought recovery time: (1) Across the globe, recovery is longest in the tropics and high northern latitudes—critical tipping elements in Earth’s climate system. (2) Drought impacts, the area of ecosystems under active recovery and recovery times, have increased over the 20th century. If future droughts become more frequent, time between droughts may become shorter than drought recovery time, leading to chronically impacted ecosystems.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

Global land carbon sink response to temperature and precipitation varies with ENSO phase

Climate variability associated with the El Niño-Southern Oscillation (ENSO) and its consequent impacts on land carbon sink interannual variability have been used as a basis for investigating carbon cycle responses to climate variability more broadly, and to inform the sensitivity of the tropical carbon budget to climate change. Past studies have presented opposing views about whether temperature or precipitation is the primary factor driving the response of the land carbon sink to ENSO. We show that the dominant driver varies with ENSO phase. And whereas tropical temperature explains sink dynamics following El Niño conditions (r TG,P = 0.59, p < 0.01), the post La Niña sink is driven largely by tropical precipitation (r PG,T= -0.46, p = 0.04). This finding points to an ENSO-phase-dependent interplay between water availability and temperature in controlling the carbon uptake response to climate variations in tropical ecosystems. Furthermore, we find that none of a suite of ten contemporary terrestrial biosphere models captures these ENSO-phase-dependent responses, highlighting a key uncertainty in modeling climate impacts on the future of the global land carbon sink.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2016

Increased light-use efficiency in northern terrestrial ecosystems indicated by CO 2 and greening observations: INCREASE IN NH LIGHT USE EFFICIENCY

Observations show an increasing amplitude in the seasonal cycle of CO2 (ASC) north of 45°N of 56 ± 9.8% over the last 50 years and an increase in vegetation greenness of 7.5–15% in high northern latitudes since the 1980s. However, the causes of these changes remain uncertain. Historical simulations from terrestrial biosphere models in the Multiscale Synthesis and Terrestrial Model Intercomparison Project are compared to the ASC and greenness observations, using the TM3 atmospheric transport model to translate surface fluxes into CO2 concentrations. We find that the modeled change in ASC is too small but the mean greening trend is generally captured. Modeled increases in greenness are primarily driven by warming, whereas ASC changes are primarily driven by increasing CO2. We suggest that increases in ecosystem-scale light use efficiency (LUE) have contributed to the observed ASC increase but are underestimated by current models. We highlight potential mechanisms that could increase modeled LUE.

Thomas, Rebecca T.↗

DOE OSTI2016

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↗

DOE OSTI2016

Decadal trends in the seasonal-cycle amplitude of terrestrial CO 2 exchange resulting from the ensemble of terrestrial biosphere models

The seasonal-cycle amplitude (SCA) of the atmosphere–ecosystem carbon dioxide (CO 2 ) exchange rate is a useful metric of the responsiveness of the terrestrial biosphere to environmental variations. It is unclear, however, what underlying mechanisms are responsible for the observed increasing trend of SCA in atmospheric CO 2 concentration. Using output data from the Multi-scale Terrestrial Model Intercomparison Project (MsTMIP), we investigated how well the SCA of atmosphere–ecosystem CO 2 exchange was simulated with 15 contemporary terrestrial ecosystem models during the period 1901–2010. Also, we made attempt to evaluate the contributions of potential mechanisms such as atmospheric CO 2 , climate, land-use, and nitrogen deposition, through factorial experiments using different combinations of forcing data. Under contemporary conditions, the simulated global-scale SCA of the cumulative net ecosystem carbon flux of most models was comparable in magnitude with the SCA of atmospheric CO 2 concentrations. Results from factorial simulation experiments showed that elevated atmospheric CO 2 exerted a strong influence on the seasonality amplification. When the model considered not only climate change but also land-use and atmospheric CO 2 changes, the majority of the models showed amplification trends of the SCAs of photosynthesis, respiration, and net ecosystem production (+0.19 % to +0.50 % yr -1 ). In the case of land-use change, it was difficult to separate the contribution of agricultural management to SCA because of inadequacies in both the data and models. The simulated amplification of SCA was approximately consistent with the observational evidence of the SCA in atmospheric CO 2 concentrations. Large inter-model differences remained, however, in the simulated global tendencies and spatial patterns of CO 2 exchanges. Further studies are required to identify a consistent explanation for the simulated and observed amplification trends, including their underlying mechanisms. Nevertheless, this study implied that monitoring of ecosystem seasonality would provide useful insights concerning ecosystem dynamics.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

Disentangling climatic and anthropogenic controls on global terrestrial evapotranspiration trends

Here, we examined natural and anthropogenic controls on terrestrial evapotranspiration (ET) changes from 1982-2010 using multiple estimates from remote sensing-based datasets and process-oriented land surface models. A significant increased trend of ET in each hemisphere was consistently revealed by observationally-constrained data and multi-model ensembles that considered historic natural and anthropogenic drivers. The climate impacts were simulated to determine the spatiotemporal variations in ET. Globally, rising CO 2 ranked second in these models after the predominant climatic influences, and yielded a decreasing trend in canopy transpiration and ET, especially for tropical forests and high-latitude shrub land. Increased nitrogen deposition slightly amplified global ET via enhanced plant growth. Land-use-induced ET responses, albeit with substantial uncertainties across the factorial analysis, were minor globally, but pronounced locally, particularly over regions with intensive land-cover changes. Our study highlights the importance of employing multi-stream ET and ET-component estimates to quantify the strengthening anthropogenic fingerprint in the global hydrologic cycle.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

Toward “optimal” integration of terrestrial biosphere models

Multimodel ensembles (MME) are commonplace in Earth system modeling. Here we perform MME integration using a 10-member ensemble of terrestrial biosphere models (TBMs) from the Multiscale synthesis and Terrestrial Model Intercomparison Project (MsTMIP). We contrast optimal (skill based for present-day carbon cycling) versus naive (one model-one vote) integration. MsTMIP optimal and naive mean land sink strength estimates (-1.16 versus -1.15 Pg C per annum respectively) are statistically indistinguishable. This holds also for grid cell values and extends to gross uptake, biomass, and net ecosystem productivity. TBM skill is similarly indistinguishable. The added complexity of skill-based integration does not materially change MME values. This suggests that carbon metabolism has predictability limits and/or that all models and references are misspecified. Finally, resolving this issue requires addressing specific uncertainty types (initial conditions, structure, and references) and a change in model development paradigms currently dominant in the TBM community.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

Using Ecosystem Experiments to Improve Vegetation Models

Ecosystem responses to rising CO2 concentrations are a major source of uncertainty in climate change projections. Data from ecosystem-scale Free-Air CO2 Enrichment (FACE) experiments provide a unique opportunity to reduce this uncertainty. The recent FACE Model–Data Synthesis project aimed to use the information gathered in two forest FACE experiments to assess and improve land ecosystem models. A new 'assumption-centred' model intercomparison approach was used, in which participating models were evaluated against experimental data based on the ways in which they represent key ecological processes. Identifying and evaluating the main assumptions caused differences among models, and the assumption-centered approach produced a clear roadmap for reducing model uncertainty. We explain this approach and summarize the resulting research agenda. We encourage the application of this approach in other model intercomparison projects to fundamentally improve predictive understanding of the Earth system.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1979

Super-resolution imaging system

The resolution of an imaging system is greatly enhanced by radiating an object with a plane wave field from a coherent source variable in either frequency, angle or distance from the object, detecting the wave field transmitted through, or reflected from, the object at some point on the image of the object, with or without heterodyne detection, and with or without a lens system. The heterodyne detected output of the detector is processed to obtain the Fourier transform as a function of the variable for a direct measurement of the amplitude and surface height structure of the object within a resolution cell centered at the corresponding point on the object. In the case of no heterodyne detection, only intensity data is obtained for a Fourier spectrum.

Jain, Atul↗