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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Fire–precipitation interactions amplify the quasi-biennial variability in fires over southern Mexico and Central America

Fires have great ecological, social, and economic impact. However, fire prediction and management remain challenges due to a limited understanding of their roles in the Earth system. Fires over southern Mexico and Central America (SMCA) are a good example of this, greatly impacting local air quality and regional climate. Here we report that the spring peak (April–May) of fire activities in this region has a distinct quasi-biennial signal based on multiple satellite datasets measuring different fire characteristics. The variability is initially driven by quasi-biennial variations in precipitation. Composite analysis indicates that strong fire years correspond to suppressed ascending motion and weakened precipitation over the SMCA. The anomalous precipitation over the SMCA is further found to be mostly related to the East Pacific–North Pacific (EP-NP) pattern 2 months prior to the fire season. The positive phase of the EP-NP leads to enhanced precipitation over the eastern US but suppressed precipitation over the SMCA, similar to the spatial pattern of precipitation differences between strong and weak fire years. Meanwhile, the quasi-biennial signals in precipitation and fires appear to be amplified by their interactions through a positive feedback loop at short timescales. Model simulations show that in strong fire years, more aerosol particles are released and transported downstream over the Gulf of Mexico and the eastern US, where suspended light-absorbing aerosols warm the atmosphere and cause the ascending motion of the air aloft. Subsequently, a compensating downward motion is formed over the region of the fire source and ultimately suppresses precipitation and intensifies fires. Statistical analysis shows the different durations of the two-way interaction, where the fire suppression effect of precipitation lasts for more than 20 d, while fire leads to a decrease in precipitation at shorter timescales (3–5 d). This study demonstrates the importance of fire–climate interactions in shaping the fire activities on an interannual scale and highlights how precipitation–fire interactions at short timescales contribute to the interannual variability in both fire and precipitation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

On the Relationship Between Shallow Cumulus Cloud Field Properties and Surface Solar Irradiance

Abstract Shallow cumulus clouds exhibit highly three‐dimensional (3‐D) spatial structure leading to complex variability in the surface solar irradiance (SSI) beneath. This variability is captured by the typically bimodal shape of the SSI probability density function (PDF). Using large eddy simulation to generate well‐resolved cloud fields and Monte Carlo 3‐D radiative transfer to reproduce realistic associated SSI PDFs, we seek direct relationships between the cloud field properties and the SSI PDF shape. Applying both random forest and artificial neural network algorithms, we find variations in the two modes of the SSI PDF are well predicted by just a handful of cloud field properties. The two algorithms utilize cloud properties similarly, with indistinguishable performance despite their different architectures. These results offer a marked improvement in realism relative to one‐dimensional radiative transfer while bypassing computationally expensive 3‐D radiative transfer, with immediate application to renewable energy assessments, and potential for several other geophysical applications.

58 GEOSCIENCES↗
DOE OSTI2020

The Cost of Floating Offshore Wind Energy in California Between 2019 and 2032

California’s energy planning is centered around meeting the emissions reduction and renewable energy requirements of Senate Bill 350 by 2030. However, state power system planning is expected to eventually address California’s requirement to achieve 100% of total retail electricity sales from renewable energy and zero-carbon resources by 2045, as mandated by Senate Bill 100. To comply with these directives, California needs to investigate the further development of energy efficiency, storage, and a diverse range of renewable energy, zero-carbon emission, and transmission resources, including offshore wind. Wind resources off the coast of California have the potential to generate a significant portion of the state’s electric energy as it moves toward a zero-carbon economy and can help diversify its energy mix. Floating offshore wind technology, which is suitable for the deep waters along the California coast, is currently in a precommercial phase, with approximately 84 megawatts (MW) installed worldwide at the end of 2019. Globally there are over 7,000 MW in planning and permitting phases of development, with the first commercial-scale projects expected to be operational in 2024. This study provides site-specific cost and performance data for floating offshore wind to inform California’s long-term energy planning. The identification of new resources to meet California’s policy goals at least cost is part of the Integrated Resource Planning (IRP) process, which is coordinated by the California Public Utilities Commission (CPUC). In 2019–2020 IRP modeling, offshore wind was included for the first time as a candidate resource in some sensitivity cases (CPUC 2019). The data and information presented in this report can be used to update offshore wind inputs in future IRP cycles. The authors conducted a geospatial cost analysis over portions of the offshore wind resource area of California. The analyzed spatial domain includes sites with a mean wind speed of at least 7 meters per second and water depths between 40 meters (m) and 1,300 m. Costs and energy production vary across this analysis domain. We calculated these parameters on a grid layout with over 750 sites, with each site representing a 1,000-MW commercial offshore wind power plant. Levelized cost of energy (LCOE) was calculated at each site over the analysis domain. The resulting variation in LCOE across the analysis domain is illustrated through heat maps in this report. Five study areas were selected within the analysis domain where more detailed cost analysis was conducted and cost parameters, such as annual energy production, capital cost expenditures (CapEx), operational cost expenditures (OpEx), and net capacity factors are reported. These five study areas include Morro Bay, Diablo Canyon, Humboldt, Cape Mendocino and Del Norte.

17 WIND ENERGY↗
DOE OSTI2022

[C ιι] Map of the Molecular Ring and Arms of the Spiral Galaxy NGC 7331*

We present the [C ιι] 157.7 μm map of galaxy NGC 7331 obtained with the Field-Imaging Far-Infrared Line Spectrometer on board the Stratospheric Observatory for Infrared Astronomy (SOFIA). This map extends an existent Herschel/Photodetector Array Camera and Spectrometer observation of the central strip of the galaxy to encompass the entire molecular ring and much of the disk, including multiple spiral arms with intense far-IR emission. We also present Herschel archival data of the [N ιι] 205 μm line, which covers a substantial part of the [C ιι] SOFIA observations and allows us to estimate the neutral fraction of the [C ιι] emission along the ring and disk of the galaxy. We find that the neutral fraction rises with the distance from the center. In addition, by tracing the azimuthal variation of the neutral fraction, we are able to see how our observing perspective affects this measurement. The high inclination of NGC 7331 allows us to glimpse the internal walls of the molecular ring. There, young bright stars emit UV radiation causing more [C ιι] emission to be produced in the ionized gas. On the outer walls, opaque dust shrouds the rest of the ring, making the neutral medium the dominant source of [C ιι] emission. Through spatial analysis comparing the [C ιι] emission to tracers of gas heating, we are able to investigate how the photoelectric heating efficiency varies throughout NGC 7331 and extend global measurements of the [C ιι] deficit to local environments. Since the origin of [C ιι] emission has typically been studied in face-on galaxies, our results shed a new light on the interpretation of [C ιι] emission, especially when studying distant galaxies with unknown inclination.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

In situ plant materials hyperspectral imaging by multimodal scattering near-field optical microscopy

Plant cells are elaborate three-dimensional polymer nano-constructs with complex chemistry. The bulk response of plants to light, in the far-field, is ultimately encoded by optical scattering from these nano-constructs. Their chemical and physical properties may be acquired through their interaction with a modulated nano-tip using scattering scanning near-field optical microscopy. Here, using this technique, we present 20 nm spatial resolution mechanical, spectral and optical mappings of plant cell walls. We first address the problem of plant polymers tracking through pretreatment and processing. Specifically, cellulose and lignin footprints are traced within a set of delignified specimen, establishing the factors hindering complete removal of lignin, an important industrial polymer. Furthermore, we determine the frequency dependent dielectric function ${\epsilon }(\omega)={(n+ik)}^{2}$ of plant material in the range 28 ≤ ω ≤ 58 THz, and show how the environmental chemical variation is imprinted in the nanoscale variability of n and k . This nanometrology is a promise for further progress in the development of plant-based (meta-)materials.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Nanoscale Mapping and Defect-Assisted Manipulation of Surface Plasmon Resonances in 2D Bi 2 Te 3 /Sb 2 Te 3 In-Plane Heterostructures

Here, the Bi 2 Te 3 /Sb 2 Te 3 in-plane heterostructure is reported as a low-dimensional tunable chalcogenide well suited as plasmonic building block for the visible-UV spectral range. Electron-driven plasmon excitations of low-dimensional Bi 2 Te 3 /Sb 2 Te 3 are investigated by monochromated electron energy loss spectroscopy spectrum imaging. To resolve the nanoscale spatial distribution of various local plasmonic resonances, singular value decomposition is used to disentangle the spectral data and identify the individual spectral contributions of various corner, edge, and face modes. Furthermore, defect-plasmon interactions are investigated both for nanoscale intrinsic and thermally induced extrinsic polygonal defects (in situ sublimation). Signature of defect-induced red shift ranging from a several hundreds of millielectronvolts to a few electronvolts, broadening of various plasmon response, together with selective enhancement and significant variations in their intensity are detected. This study highlights the presence of a heterointerface and identifies defects as physical tuning pathways to modulate the plasmonic response over a broad spectral range. Finally, the experimental observations are compared qualitatively and validated with numerical simulations using the electron-driven discrete dipole approximation. Low-dimensional Bi 2 Te 3 /Sb 2 Te 3 as a less explored plasmonic system holds great promises as emerging platform for integrated plasmonics. Furthermore, introducing controlled structural defects can open the door for nanoengineering of plasmonic properties in such systems.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Scaling of Floods With Geomorphologic Characteristics and Precipitation Variability Across the Conterminous United States

Abstract Accurate flood risk assessment requires a comprehensive understanding of flood sensitivity to regional drivers and climate factors. This paper presents the scaling of floods (duration, peak, volume) with geomorphologic characteristics of the basin (i.e., drainage area, slope, elevation) and precipitation patterns (rainfall accumulation, variability). Long‐term daily streamflow observations over the 20th and early 21st centuries from Hydro‐Climatic Data Network streamgages across the conterminous United States are used to create a flood event database based on their flood stage information. Antecedent daily rainfall accumulation and variability corresponding to these floods are computed using Global Historical Climatology Network daily data set. Two Bayesian scaling models are developed, and the spatial organization of scaling exponents is investigated. The baseline model quantifies the scaling of floods to geomorphologic characteristics. The dynamic model quantifies the scaling of floods to antecedent precipitation distribution which is further conditioned on geomorphologic characteristics. Results show that small and low‐elevation basins have a stronger response to antecedent rainfall distribution in amplifying flood peaks, while high‐elevation steeper basins have a lower response for flood duration and volume. The dynamic models demonstrate that there are significant variations in the flood scaling rates, with the largest rates up to 40% and 4.5% for flood duration, 64% and 44% for peak, and 98% and 40% for volume found across the Northeast, Coastal Southeast, and Northwest with intensifying rainfall accumulation and variability, respectively. This study advances flood predictions by better informing the flood attributes in the context of dynamical land‐atmosphere perturbations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Determining Spatial Scales of Soil Moisture—Cloud Coupling Pathways Using Semi-Idealized Simulations

The spatial scales of land-atmosphere interactions over heterogeneous, realistic soil moisture patterns are critical to improve our understanding of land-atmosphere interactions. However, these scales are poorly quantified. We use high-resolution numerical experiments to quantify the spatial scales for a selected day during the Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems (HI-SCALE) campaign in Oklahoma. A semi-idealized approach (removing background winds and surface topography while retaining the real-world data for other boundary conditions) enables examination of the local influence from the surface. Simulations that apply uniform surface, variable land cover with uniform soil moisture, and variable land cover with variable soil moisture are then compared. Land cover variations, especially water and urban surfaces, create two variance peaks in the surface sensible heat flux in the scales >10 km (meso-β) and <6 km (meso-γ). Both peaks are enhanced by the observation-based soil moisture distribution that has most of its variance in the meso-β scale. Atmospheric response in the meso-β scale is hydrostatic with weak vertical motion. The land cover variations induce secondary circulations in the scales of 2.5–6 km. The additional soil moisture variability intensifies extreme circulations over dry soil patches and sharp sensible heat flux gradients, slightly extending the characteristic scales to 2.5–9 km. While their areal coverage is small, soil moisture variations on such “hotspots” lead to substantially larger convective cloud structure and domain-mean rainfall, calling for a consideration of their non-linear effect in large-scale models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Diagnostic development for parallel wave-number measurement of lower hybrid waves in EAST

In this study, an eight-channel magnetic probe diagnostic system has been designed and installed adjacent to the 4.6 GHz lower hybrid (LH) grill antenna in the low-field side of the Experimental Advanced Superconducting Tokamak (EAST) in order to study the n ∥ evolution of LH waves in the first pass from the launcher to the core plasma. The magnetic probes are separated by 6.6 mm, which allows measurement of the dominant parallel refractive index n ∥ up to n ∥ = 5 for 4.6 GHz LH waves. The magnetic probes are designed to be sensitive to the magnetic field component perpendicular to the background magnetic field with a slit on the casing that encloses the probe. The intermediate frequency stage, which consists of two mixing stages, down-coverts the frequency of the measured wave signals at 4.6 GHz to 20 MHz. A bench test demonstrates the phase stability of the magnetic probe diagnostic system. By evaluating the phase variation of the measured signals along the background magnetic field, the dominant n ∥ of the LH wave in the scrape-off layer has been deduced during the 2019 experimental campaign. In the low density plasma, the measured dominant n ∥ of the LH waves is about 2.1, corresponding to the main peak 2.04 of the launched n ∥ spectrum. n ∥ deduced by the least-squares linear fit method remains near this value in the low density plasma with a high spatial correlation magnitude of 0.9. With an eight-channel probe system, a wave-number spectrum has also been deduced, which has a peak near to the measured dominant n ∥ .

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

The ALMaQUEST Survey X: what powers merger induced star formation?

ABSTRACT Galaxy mergers are known to trigger both extended and central star formation. However, what remains to be understood is whether this triggered star formation is facilitated by enhanced star formation efficiencies (SFEs), or an abundance of molecular gas fuel. This work presents spatially resolved measurements of CO emission collected with the Atacama Large Millimetre Array (ALMA) for 20 merging galaxies (either pairs or post-mergers) selected from the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey. Eleven additional merging galaxies are selected from the ALMA MaNGA QUEnching and STar formation (ALMaQUEST) survey, resulting in a set of 31 mergers at various stages of interaction and covering a broad range of star formation rates (SFRs). We investigate galaxy-to-galaxy variations in the resolved Kennicutt–Schmidt relation, (rKS: $\Sigma _{\textrm {H}_2}$ versus ΣSFR), the resolved molecular gas main sequence (rMGMS: Σ⋆ versus $\Sigma _{\textrm {H}_2}$), and the resolved star-forming main sequence (rSFMS: Σ⋆ versus ΣSFR). We quantify offsets from these resolved relations to determine if SFR, molecular gas fraction, or/and SFE is/are enhanced in different regions of an individual galaxy. By comparing offsets in all three parameters, we can discern whether gas fraction or SFE powers an enhanced ΣSFR. We find that merger-induced star formation can be driven by a variety of mechanisms, both within a galaxy and between different mergers, regardless of interaction stage.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Spatially Dependent Seismic Wavefield Scattering from an Underground Chemical Explosion: Analysis of the Source Physics Experiment Dry Alluvium Geology Large- N Array

Explosion sources have been observed to generate significant shear‐wave energy despite their isotropic nature. To investigate this phenomenon, we conduct an analysis of the seismic data collected as part of the Source Physics Experiment (SPE): Dry Alluvium Geology (DAG) and investigate the generation of shear‐wave energy via scattering. The data were produced by three underground chemical explosions and consist of three‐component seismograms, which were recorded by the DAG Large‐N array. Synthetic tests suggest that for the DAG experiments, small‐scale stochastic heterogeneities, defined as features with correlation lengths of 10–100s of meters, are more effective than large‐scale geologic structure (scales >1–10 km) at reproducing the scattering of explosion generated wavefields observed at DAG. We analyze the seismic data for spatially variable ratios between transversely and radially polarized seismic energy, and then estimate the mean free path of P and S waves. All analyses are conducted within a frequency band of 5–50 Hz. The ratio of transversely to radially polarized energy is the highest in the east and west portion of the Large‐N array. In addition, the magnitude of the estimated S‐wave mean free path is shorter in the eastern portion of the Large‐N array. This variation indicates that the eastern area of the DAG array is where more scattering is occurring, suggesting azimuthal dependence of P‐to‐P and P‐to‐S scattering. Furthermore, this azimuthal dependence of P‐to‐S scattering can have implications for explosion discrimination based on spectral ratios of seismic wave types, because the general assumption is that explosions do not generate shear‐wave energy. Synthetic tests modeling only larger‐scale geologic structure had lower transversely polarized energy (only four stations showing a transversely to radially polarized energy ratio greater than 1) and fewer stations (<10) displaying shorter (<300 m) mean free paths than what was observed in the DAG data results.

Darrh, Andréa Nicole↗
DOE OSTI2023

Relationship between isotope ratios in precipitation and stream water across watersheds of the National Ecological Observation Network

The timescales associated with precipitation moving through watersheds reveal processes that are critical to understanding many hydrologic systems. Measurements of environmental stable water isotope ratios (δ 2 H and δ 18 O) have been used as tracers to study hydrologic timescales by examining how long it takes for incoming precipitation tracers become stream discharge, yet limited measurements both spatially and temporally have bounded macroscale evaluations so far. Here in this observation driven study across North American biomes within the National Ecological Observation Network (NEON), we examined δ 18 O and δ 2 H stable water isotope in precipitation (δP) and stream water (δQ) at 26 co-located sites. With an average 54 precipitation samples and 139 stream water samples per site collected over 2014–2022, assessment of local meteoric water lines and local stream water lines showed geographic variation across North America. Taking the ratio of estimated seasonal amplitudes of δP and δQ to calculate young water fractions (F yw ), showed a Fyw range from 1% to 93% with most sites having F yw below 20%. Calculate d mean transit times (MTT) based on a gamma convolution model showed a MTT range from 0.10 to 13.2 years, with half of the sites having MTT estimates lower than 2 years. Significant correlations were found between the F yw and watershed area, longest flow length, and the longest flow length/slope. Significant correlations were found between MTT and site latitude, longitude, slope, clay fraction, temperature, precipitation magnitude, and precipitation frequency. The significant correlations between water timescale metrics and the environmental characteristics we report share some similarities with those reported in prior studies, demonstrating that these quantities are primarily driven by site or area specific factors. The analysis of isotope data presented here provides important constraints on isotope variation in North American biomes and the timescales of water movement through NEON study sites.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Nanoscale Photoexcited Carrier Dynamics in Perovskites

The optoelectronic properties of lead halide perovskite thin films can be tuned through compositional variations and strain, but the associated nanocrystalline structure makes it difficult to untangle the link between composition, processing conditions, and ultimately material properties and degradation. Here, we study the effect of processing conditions and degradation on the local photoconductivity dynamics in [(CsPbI 3 ) 0.05 (FAPbI 3 ) 0.85 (MAPbBr 3 ) 0.15 ] and (FA 0.7 Cs 0.3 PbI 3 ) perovskite thin films using temporally and spectrally resolved microwave near-field microscopy with a temporal resolution as high as 5 ns and a spatial resolution better than 50 nm. For the latter FACs formulation, we find a clear effect of the process annealing temperature on film morphology, stability, and spatial photoconductivity distribution. After exposure of samples to ambient conditions and illumination, we find spectral evidence of halide segregation-induced degradation below the instrument resolution limit for the mixed halide formulation, while we find a clear spatially inhomogeneous increase in the carrier lifetime for the FACs formulation annealed at 180 degrees C.

14 SOLAR ENERGY↗
DOE OSTI2025

Predicting weather impacts on corn production in a data-limited region using a transfer learning approach

The stability of food supply and prices may depend more on annual changes in yields from year-to-year variability in weather than on longer-term average changes from changing climatic conditions. However, the absence of high-quality data on crop yields at fine spatial resolutions in many regions of the world makes it challenging to statistically model their response to interannual variability in weather patterns. Therefore, there is a need for empirical methods that can project annual crop yield changes even in limited data regions. Here, we propose a transfer learning algorithm that uses high spatial resolution data from one region to project yields in another region with more limited data. The goal of our work is to understand what data types can be beneficial for transferring learning from a source region to a very different target region with more limited data. We utilize Long Short-Term Memory to develop a transfer learning model that is trained on historical county-level corn yield in the United States and predicts district-level corn yield variations in India. Even using smaller amounts of data in India, simulating a data-scarce region, we achieve an average root mean square error of 0.48 bu acre−1 in predicting interannual yield variations. Using Shapley values to interpret results, we explore the contribution of the different weather parameters to interannual yield variability and find a larger influence of precipitation-related variables. Our study demonstrates the usefulness of this method for transferring models of weather impacts on crop yields trained on a data-rich country to one with more limited data. It suggests the potential of applying the transfer learning model to mitigate the need for extensive raw data globally.

Vishwakarma, Srishti [ORNL] (ORCID:000000031674419↗
DOE OSTI2022

Continental United States may lose 1.8 petagrams of soil organic carbon under climate change by 2100

Abstract Aims High‐resolution information on soils’ vulnerability to climate‐induced soil organic carbon (SOC) loss can enable environmental scientists, land managers, and policy makers to develop targeted mitigation strategies. This study aims to estimate baseline and decadal changes in continental US surface SOC stocks under future emission scenarios. Location Continental United States. Time period 2014–2100. Methods We used recent SOC field observations ( n = 6,213 sites), environmental factors ( n = 32), and an ensemble machine learning (ML) approach to estimate baseline SOC stocks in surface soils across the continental United States at 100‐m spatial resolution, and decadal changes under the projected climate scenarios of Coupled Model Intercomparison Project Phase Six (CMIP6) earth system models (ESMs). Results Baseline SOC projections from ML approaches captured more than 50% of variability in SOC observations, whereas ESMs represented only 6–16% of observed SOC variability. ML estimates showed a mean total loss of 1.8 Pg C from US surface soils under the high‐emission scenario by 2100, whereas ESMs showed no significant change in SOC stocks with wide variation among ESMs. Both ML and ESM predictions agree on the direction of SOC change (net emissions or sequestration) across 46–51% of continental US land area. These differences are attributable to the high‐resolution site‐specific data used in the ML models compared to the relatively coarse grid represented in CMIP6 ESMs. Main conclusions Our high‐resolution estimates of baseline SOC stocks, identification of key environmental controllers, and projection of SOC changes from US land cover types under future climate scenarios suggest the need for high‐resolution simulations of SOC in ESMs to represent the heterogeneity of SOC. We found that the SOC change is sensitive to key soil related factors (e.g. soil drainage and soil order) that have not been historically considered as input parameters in ESMs, because currently more than 95% variability in the SOC of CMIP6 ESMs is controlled by net primary productivity, temperature, and precipitation. Using additional environmental factors to estimate the baseline SOC stocks and predict the future trajectory of SOC change can provide more accurate results.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Improving Subsurface Stress Characterization for Carbon Dioxide Storage Projects

Researchers at New Mexico Tech, Los Alamos National Laboratory (LANL), Sandia National Laboratory (SNL), and other collaborators are developing a methodology to improve characterization of stress in the subsurface by means of a model-based inversion of reservoir engineering data, time lapse seismic measurements, and microseismicity. Historically, various geophysical techniques have been used in efforts to understand the state of stress in the subsurface through direct and indirect imaging of stress sensitive features (faults and fractures) and observations of transient stress related observations (time variant elastic moduli and microseismicity). Standard direct and indirect techniques for seismic fault and fracture imaging suffer from detectability limits due to reliance on high data quality and multiplicity. Variations in effective elastic properties from inversion of high quality seismic (Vertical Seismic Profile (VSP)) data may be used to infer stress near the wellbore through integration with independent experimental characterization of the stress-velocity relationship. Given a sufficiently robust observation network, microseismic emissions may be inverted to characterize focal mechanisms which, together with supporting assumptions and constraints, inform estimates of in-situ stress. While each of these techniques contributes in part to the characterization of stress within limited spatial and temporal domains, no one method provides an unambiguous stress measurement or a predictive capability over a site scale spatial extent. Challenges associated with solution non-uniqueness, measurement ambiguity, and irregular sampling may be greatly minimized through combination of one or more of independent measurements within a common framework in which realistic geological, hydrodynamic, geomechanical, and seismological constituent process models may act as constraints.

02 PETROLEUM↗
DOE OSTI2022

Understanding Air-Sea Feedbacks to the MJO through Process Evaluation of Observations and Models (Final Report)

The goal of our project was to enhance our understanding of the role of coupling in the simulation of the Madden Julian Oscillation (MJO) in coupled climate models. We developed diagnostics of precipitation and Sea Surface Temperature variability in climate models and investigated how they are related to metrics of MJO simulation performance. We found a relationship between models with a high spatial coherence of precipitation and a good propagation of the MJO through the Maritime Continent region, but no relationship between metrics of precipitation organisation and intensity. Analysis of coupled and uncoupled model simulations from the Sixth Coupled Model Intercomparison Project (CMIP6) shows that coupling systematically improved the MJO simulation in both metrics that we investigated. We analysed the role of background moisture gradients in the MJO simulation performance following Lim et al. (2018) and found that although the model to model variation in moisture gradients to the west of Indonesia was related to model MJO performance, in general no single moisture gradient was as good at explaining a large fraction of MJO performance across the models as compared to a linear combination of those metrics, which was able to explain a significant fraction of the variance in the MJO performance. Those relationships were much stronger for coupled simulations than uncoupled simulations and stronger for those metrics that measured propagation of the MJO across the Maritime Continent than for overall MJO activity.

54 ENVIRONMENTAL SCIENCES↗