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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS2022

Potential Link Between Ice Nucleation and Climate Model Spread in Arctic Amplification

Arctic amplification (AA) is simulated by all global climate models, however the spread in the degree of projected warming is large and the underlying mechanisms driving it are poorly understood. The impact of the temperature dependence of immersion freezing on cloud feedbacks and AA is studied using NASA's GEOS-5 model. Parameterizations that exhibit low ice-nucleating particle (INP) concentrations in the high Arctic during summer are found to weaken the cloud-phase feedback. This allows sunlight to readily melt sea-ice in the summer, which decreases the stability of the lower troposphere, causing a decrease in wintertime cloud fraction over open ocean. Arctic amplification was found to span from ∼1.4 to >2.6, which spans 30% of the spread in AA in the coupled model intercomparison project models, depending on the temperature dependence of immersion freezing. These results suggest that summertime INP concentrations may provide an observational constraint on AA.

Ice Nucleation↗
DOE OSTI2022

Impacts of Suppressing Excessive Light Rain on Aerosol Radiative Effects and Health Risks

Global climate models (GCMs) have been used widely to study radiative forcing and health risks of aerosols. A recent study using two GCMs found that light rain plays a dominant role in controlling aerosol loading. However, “too much light rain and too little heavy rain” is a longstanding bias in GCMs. It is unclear how much light rain affects aerosol-cloud-radiation interactions and health risks from air pollution. Here, in this work, we show that, with the correction of the rainfall intensity spectrum in the National Center for Atmospheric Research Community Atmosphere Model version 5.3 by introducing a stochastic deep convection scheme, the reduced frequency of light rain (1–20 mm d -1 ) results in changes of aerosol direct radiative effects (DRE) of up to -0.5 ± 0.03 W/m 2 and aerosol cloud radiative effects (CRE) of up to -0.9 ± 0.03 W/m 2 . The total (CRE + DRE) radiative effects of light rain-mediated aerosol changes exceed the present-day anthropogenic forcing of aerosols relative to preindustrial levels from the Coupled Model Intercomparison Project (CMIP5&6) models. However, the correction of the rainfall intensity spectrum has little effect on anthropogenic aerosol forcing (defined as the radiative perturbation due to changes in aerosol concentrations between the industrial era and preindustrial levels). Due to increased exposure to fine particulates (PM 2.5 ), the estimated global total premature mortality is much higher than previously estimated, by 300,000 ± 60,000 deaths per year, and is more severe in populous regions such as India and China. The findings in this study highlight the need to understand uncertainties in radiative effects and health risks of aerosols due to simulation biases of precipitation in GCMs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Extrapolation of the Rainflow-Counted Load Ranges for Fatigue Assessment of the Wind Turbine's Blades

Wind turbine design standards recommend the use of statistical modeling coupled with extrapolation of the short-term load data to long-term periods for fatigue reliability assessment. However, statistical error and computational expense can limit the accuracy of such approaches. In the case of wind turbine blades, the errors are more significant because of the high material fatigue exponent that makes the damage estimations more sensitive to variations. In addition, due to different excitation sources, the flapwise load range histogram is not unimodal, and thus its statistical modeling is complex. In the present work, we provide three methods for statistical modeling of the flapwise bending moment ranges including a novel approach based on frequency-based separation of the modes. The first two methods are simplified approaches for modeling the most crucial load ranges using unimodal distributions and the third method involves multimodal distribution fitting. The research is based on 3600 10-minute aeroelastic simulations of DTU 10MW case study wind turbine from which a benchmark damage equivalent load (DEL) is calculated. The DEL calculated by each of the three proposed methods is compared to this reference. The results show that the conventional approach based on using 6 seeds as well as using mixture models fitted on the limited data lead to under-conservative results with errors up to 23%. On the other hand, the simplified unimodal approaches provided in this work can provide conservative estimations of the fatigue damage with mean values 5% and 12% higher than the benchmark. However, the variability of the DEL estimates is higher when using unimodal extrapolation of the load ranges, and the data can be conservative by 17.5%. The proposed unimodal fits suggested for modeling and extrapolation of the blade's load ranges provide less errors relatively and most importantly conservative DEL estimations while maintaining computational efficiency.

blade fatigue↗
DOE OSTI2018

Impacts of air pollutants from fire and non-fire emissions on the regional air quality in Southeast Asia

Abstract. Severe haze events in Southeast Asia caused by particulate pollution have become more intense and frequent in recent years. Widespread biomass burning occurrences and particulate pollutants from human activities other than biomass burning play important roles in degrading air quality in Southeast Asia. In this study, numerical simulations have been conducted using the Weather Research and Forecasting (WRF) model coupled with a chemistry component (WRF-Chem) to quantitatively examine the contributions of aerosols emitted from fire (i.e., biomass burning) versus non-fire (including fossil fuel combustion, and road dust, etc.) sources to the degradation of air quality and visibility over Southeast Asia. These simulations cover a time period from 2002 to 2008 and are driven by emissions from (a) fossil fuel burning only, (b) biomass burning only, and (c) both fossil fuel and biomass burning. The model results reveal that 39 % of observed low-visibility days (LVDs) can be explained by either fossil fuel burning or biomass burning emissions alone, a further 20 % by fossil fuel burning alone, a further 8 % by biomass burning alone, and a further 5 % by a combination of fossil fuel burning and biomass burning. Analysis of an 24 h PM 2.5 air quality index (AQI) indicates that the case with coexisting fire and non-fire PM 2.5 can substantially increase the chance of AQI being in the moderate or unhealthy pollution level from 23 to 34 %. The premature mortality in major Southeast Asian cities due to degradation of air quality by particulate pollutants is estimated to increase from ∼ 4110 per year in 2002 to ∼ 6540 per year in 2008. In addition, we demonstrate the importance of certain missing non-fire anthropogenic aerosol sources including anthropogenic fugitive and industrial dusts in causing urban air quality degradation. An experiment of using machine learning algorithms to forecast the occurrence of haze events in Singapore is also explored in this study. All of these results suggest that besides minimizing biomass burning activities, an effective air pollution mitigation policy for Southeast Asia needs to consider controlling emissions from non-fire anthropogenic sources.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1985

Viscous effects on transonic airfoil stability and response

Viscous effects on transonic airfoil stability and response are investigated using an integral boundary layer model coupled to the inviscid XTRAN2L transonic small disturbance code. Unsteady transonic airloads required for stability analyses are computed using a pulse transfer function analysis including viscous effects. The pulse analysis provides unsteady aerodynamic forces for a wide range of reduced frequency in a single flow field computation. Nonlinear time marching aeroelastic solutions are presented which show the effects of viscosity on airfoil response behavior and flutter. Effects of amplitude on time marching responses are demonstrated. A state space aeroelastic model employing Pade approximants to describe the unsteady airloads is used to study the effects of viscosity on transonic airfoil stability. State space dynamic pressure root loci are in good overall agreement with time marching damping and frequency estimates. Parallel sets of results with and without viscous effects reveal the effects of viscosity on transonic unsteady airloads and aeroelastic characteristics of airfoils.

Berry, H. M.↗
NASA NTRS2018

GEOS-CF Model Assessment of PM2.5 During Wildfires: Inferring the Impact of PM2.5 Exposure on Adverse Respiratory & Cardiovascular Conditions

Exposure to fine particulate matter (PM2.5) can aggravate pre-existing respiratory and cardiovascular conditions. When PM2.5 is inhaled it can cause damage to the lungs such as reduced lung function and shortness of breath. After being inhaled PM2.5 can enter the bloodstream and cause harm to the heart. One major natural source of PM2.5 exposure is from wildfire smoke. The particulates within the smoke from the wildfires can spread from the initial source region, potentially impacting communities both near and far. During and after wildfire events, PM2.5 levels can exceed the WHO air quality guidelines (10 gm^3 annual mean; 25 gm^3 daily mean), becoming hazardous to an individual's health. Global models can be used to simulate the emission and transport of these particulates and subsequently they can be valuable to air quality forecasting in highly polluted areas. The NASA Goddard Earth Observing System (GEOS) version 5 Composition Forecast (GEOS-CF) system has been used to produce near-real time air quality forecasts of atmospheric composition at a high global resolution of 25 km. The GEOS-CF system utilizes the GEOS weather forecast model coupled with GEOS-Chem (version 11) chemistry module to provide analyses and forecasts of various toxic air pollutants, including PM2.5. The GEOS-CF simulated high levels of PM2.5 (40 gm^3 to 250 gm^3 ), exceeding the WHO guidelines, during multiple recent regional and global wildfire seasons, including the 2017 Seattle, WA and Los Angeles, CA wildfire seasons, and biomass burning events in India. Furthermore, the GEOS-CF simulated PM2.5 applied to a human health assessment model, BenMAP (The Environmental Benefits Mapping and Analysis Program, version 1.3), estimates the impact on adverse respiratory health conditions due to PM2.5 exposure from wildfires. The GEOS-CF predicted PM2.5 during the wildfire season with the corresponding BenMAP results provides an assessment of the human health impact of PM2.5 exposure.

Saunders, Emily↗
DOE OSTI2019

Changes in the dependence between global precipitation and temperature from observations and model simulations

Precipitation and temperature are physically related to each other with significant dependences that vary with seasons at regional and global scales. The dependence between precipitation and temperature (P–T dependence) plays a central role in characterizing the joint behaviour of the two variables. Along with extensive studies on the variation in the mean, variance, or extremes of precipitation and temperature under global warming, it is of particular interest to understand the climate–change impacts on the covariability of precipitation and temperature. The aim of this study therefore is to assess climate change impacts on the P–T dependence over global land areas from observations, and the performance of the current–generation Coupled Model Intercomparison Project (CMIP5) models in simulating these patterns. In general, the CMIP5 models correctly simulate the overall pattern of the P–T dependence (around 87–94% of global land areas). Furthermore, they capture both the sign and change of P–T dependence for relatively small regions (around 41–47% of global land areas). Results from this study may provide useful insights for the future development of climate models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Impacts of anthropogenic aerosols on fog in North China Plain

Fog poses a sever environmental problem in the North China Plain (NCP), China, which has been witnessing increases anthropogenic emission since the early 1980s. Here, this work first uses the WRF/Chem model coupled with the local anthropogenic emissions to simulate and evaluate a severe fog event occurring in NCP. Comparison of the simulations against observations shows that WRF/Chem well reproduces the general features of temporal evolution of PM 2.5 mass concentration, fog spatial distribution, visibility, and vertical profiles of temperature, water vapor content and relative humidity in the planetary boundary layer throughout the whole period of the fog event. Sensitivity studies are then performed with five different levels of anthropogenic emission as model inputs to systematically examine the comprehensive impacts of aerosols on fog microphysical, macrophysical, radiative, and dynamical properties. The results show that as aerosol concentration increases, fog droplet number concentration and liquid water content all increase nonlinearly; but effective radius decreases. Macrophysical properties (fog fraction, fog duration, fog height, and liquid water path) also increase nonlinearly with increasing aerosol concentration, with rates of changes smaller than microphysical properties. Further analysis reveals distinct aerosol effects on thermodynamic and dynamical conditions during different stages of fog evolution: increasing aerosols invigorate fog formation and development by enhancing longwave-induced instability, fog droplet condensation accompanying latent heat release, and thus turbulence, but delay fog dissipation by reducing surface solar radiation, surface sensible and latent heat fluxes, and thus suppressing turbulence during the dissipation stage.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Decoherence and energy relaxation in the quantum-classical dynamics for charge transport in organic semiconducting crystals: An instantaneous decoherence correction approach

We explore an instantaneous decoherence correction (IDC) approach for the decoherence and energy relaxation in the quantum-classical dynamics of charge transport in organic semiconducting crystals. These effects, originating from environmental fluctuations, are essential ingredients of the carrier dynamics. The IDC is carried out by measurement-like operations in the adiabatic representation. While decoherence is inherent in the IDC, energy relaxation is taken into account by considering the detailed balance through the introduction of energy-dependent reweighing factors, which could be either Boltzmann (IDC-BM) or Miller-Abrahams (IDC-MA) type. For a non-diagonal electron-phonon coupling model, it is shown that IDC tends to enhance diffusion while energy relaxation weakens this enhancement. As expected, both the IDC-BM and IDC-MA achieve a near-equilibrium distribution at finite temperatures in the diffusion process, while in the Ehrenfest dynamics the electronic system tends to infinite temperature limit. The resulting energy relaxation times with the two kinds of factors lie in different regimes and exhibit different dependences on temperature, decoherence time, and electron-phonon coupling strength, due to different dominant relaxation processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Quasi-stationary Planetary Scale Waves in Modern Climate Models

We evaluate climate model simulations of geopotential height at the largest space-time scales, considering the first Fourier components (in longitude) of long-term climatological means. Quasi-stationary planetary scale waves emerge from this analysis. Variations of these waves are important components of climate change, for example associated with regional drought. Systematic examination of their long-term climatology provides context for understanding their evolution in time. We compare four reanalysis datasets with “historical runs” from the latest version of the Coupled Model Intercomparison Project (CMIP) and find general agreement, but we also identify model errors outside the range of both observational uncertainty and the uncertainty implied by interannual variability. Errors in wave phase have possible implications for climate model projections of regional climate and of shifting weather patterns. One model in the set we examine, originally created nearly 20 years before the others, exhibits noticeably greater errors.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

The Southern Ocean as a constraint to reduce uncertainty in future ocean carbon sinks

Earth system model (ESM) simulations exhibit large biases compares to observation-based estimates of the present ocean CO 2 sink. The inter-model spread in projections increases nearly 2-fold by the end of the 21st century and therefore contributes significantly to the uncertainty of future climate projections. In this study, the Southern Ocean (SO) is shown to be one of the hot-spot regions for future uptake of anthropogenic CO 2 , characterized by both the solubility pump and biologically mediated carbon drawdown in the spring and summer. Here, we show, by analyzing a suite of fully interactive ESMs simulations from the Coupled Model Intercomparison Project phase 5 (CMIP5) over the 21st century under the high-CO 2 Representative Concentration Pathway (RCP) 8.5 scenario, that the SO is the only region where the atmospheric CO 2 uptake rate continues to increase toward the end of the 21st century. Furthermore, our study discovers a strong inter-model link between the contemporary CO 2 uptake in the Southern Ocean and the projected global cumulated uptake over the 21st century. This strong correlation suggests that models with low (high) carbon uptake rate in the contemporary SO tend to simulate low (high) uptake rate in the future. None the less, our analysis also shows that none of the models fully capture the observed biophysical mechanisms governing the CO 2 fluxes in the SO. The inter-model spread for the contemporary CO 2 uptake in the Southern Ocean is attributed to the variations in the simulated seasonal cycle of surface p CO 2 . Two groups of model behavior have been identified. The first one simulates anomalously strong SO carbon uptake, generally due to both too strong a net primary production and too low a surface p CO 2 in December–January. The second group simulates an opposite CO 2 flux seasonal phase, which is driven mainly by the bias in the sea surface temperature variability. Furthermore, we show that these biases are persistent throughout the 21st century, which highlights the urgent need for a sustained and comprehensive biogeochemical monitoring system in the Southern Ocean to better constrain key processes represented in current model systems.

58 GEOSCIENCES↗
NASA NTRS1991

Composite load spectra for select space propulsion structural components

The objective of this program is to develop generic load models with multiple levels of progressive sophistication to simulate the composite (combined) load spectra that are induced in space propulsion system components, representative of Space Shuttle Main Engines (SSME), such as transfer ducts, turbine blades, and liquid oxygen posts and system ducting. The first approach will consist of using state of the art probabilistic methods to describe the individual loading conditions and combinations of these loading conditions to synthesize the composite load spectra simulation. The second approach will consist of developing coupled models for composite load spectra simulation which combine the deterministic models for composite load dynamic, acoustic, high pressure, and high rotational speed, etc., load simulation using statistically varying coefficients. These coefficients will then be determined using advanced probabilistic simulation methods with and without strategically selected experimental data.

Newell, J. F.↗
NASA NTRS2011

Influence of Aerosol Heating on the Stratospheric Transport of the Mt. Pinatubo Eruption

On June 15th, 1991 the eruption of Mt. Pinatubo (15.1 deg. N, 120.3 Deg. E) in the Philippines injected about 20 Tg of sulfur dioxide in the stratosphere, which was transformed into sulfuric acid aerosol. The large perturbation of the background aerosol caused an increase in temperature in the lower stratosphere of 2-3 K. Even though stratospheric winds climatological]y tend to hinder the air mixing between the two hemispheres, observations have shown that a large part of the SO2 emitted by Mt. Pinatubo have been transported from the Northern to the Southern Hemisphere. We simulate the eruption of Mt. Pinatubo with the Goddard Earth Observing System (GEOS) version 5 global climate model, coupled to the aerosol module GOCART and the stratospheric chemistry module StratChem, to investigate the influence of the eruption of Mt. Pinatubo on the stratospheric transport pattern. We perform two ensembles of simulations: the first ensemble consists of runs without coupling between aerosol and radiation. In these simulations the plume of aerosols is treated as a passive tracer and the atmosphere is unperturbed. In the second ensemble of simulations aerosols and radiation are coupled. We show that the set of runs with interactive aerosol produces a larger cross-equatorial transport of the Pinatubo cloud. In our simulations the local heating perturbation caused by the sudden injection of volcanic aerosol changes the pattern of the stratospheric winds causing more intrusion of air from the Northern into the Southern Hemisphere. Furthermore, we perform simulations changing the injection height of the cloud, and study the transport of the plume resulting from the different scenarios. Comparisons of model results with SAGE II and AVHRR satellite observations will be shown.

Aquila, Valentina↗
DOE OSTI2023

Isolating the effect of biomass burning aerosol emissions on 20th century hydroclimate in South America and Southeast Asia

Abstract Biomass burning is a significant source of aerosol emissions in some regions and has a considerable impact on regional climate. Earth system model simulations indicate that increased biomass burning aerosol emissions contributed to statistically significant decreases in tropical precipitation over the 20th century. In this study, we use the Community Earth System Model version 1 Large Ensemble (CESM1-LENS) experiment to evaluate the mechanisms by which biomass burning aerosol contributed to decreased tropical precipitation, with a focus on South America and Southeast Asia. We analyze the all-but-one forcing simulations in which biomass burning aerosol emissions are held constant while other forcings (e.g., greenhouse gas concentrations) vary throughout the 20th century. This allows us to isolate the influence of biomass burning aerosol on processes that contribute to decreasing precipitation, including cloud microphysics, the radiative effects of absorbing aerosol particles, and alterations in regional circulation. We also show that the 20th century reduction in precipitation identified in the CESM1-LENS historical and biomass burning experiments is consistent across Coupled Model Intercomparison Project Phase 5 models with interactive aerosol schemes and the CESM2 single-forcing experiment. Our results demonstrate that higher concentrations of biomass burning aerosol increases the quantity of cloud condensation nuclei and cloud droplets, limiting cloud droplet size and precipitation formation. Additionally, absorbing aerosols (e.g., black carbon) contribute to a warmer cloud layer, which promotes cloud evaporation, increases atmospheric stability, and alters regional circulation patterns. Corresponding convectively coupled circulation responses, particularly over the tropical Andes, contribute to further reducing the flow of moisture and moisture convergence over tropical land. These results elucidate the processes that affect the water cycle in regions prone to biomass burning and inform our understanding of how future changes in aerosol emissions may impact tropical precipitation over the 21st century.

Environmental Sciences & Ecology↗
DOE OSTI2025

Evaluation of CMIP6 Streamflow in the Arctic

Earth system models (ESMs) serve as the primary basis for projecting future streamflow changes, but they are biased in terms of the their ability to reproduce historical observations of streamflow. Rigorous downscaling and bias-correction procedures, which are time-consuming and introduce uncertainties, are commonly used to address these biases in streamflow or runoff. However, the applicable limits of streamflow projections remain largely untested through direct comparisons with observations. In this work, we compare historical streamflow time series observations with a suite of Coupled Model Intercomparison Project phase 6 (CMIP6) ESMs to assess the space and time scales at which each ESM represents historic streamflow observations. We focus our analysis on streamflow across the Arctic given the higher degree of warming experienced over this region, underscoring its importance for understanding the future changes. A series of metrics—volume, seasonality, extreme capturing streamflow variability, drought, and flooding is tested to assess ESM simulation skill for total events and overall distributions. Our results indicate that although improvements are necessary in ESM runoff and streamflow projections, the use of temporal averaging and targeting the best-fit model for comparison to observations when a suite of ESMs is considered can provide robust streamflow projections. Moreover, this work provides a basis for contextualizing the limits of ESM applicability for studies aiming to assess streamflow in the future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Temporal and Spatial Variation in Peatland Carbon Cycling and Implications for Interpreting Responses of an Ecosystem-Scale Warming Experiment

Here, we are conducting a large-scale, long-term climate change response experiment in an ombrotrophic peat bog in Minnesota to evaluate the effects of warming and elevated CO 2 on ecosystem processes using empirical and modeling approaches. To better frame future assessments of peatland responses to climate change, we characterized and compared spatial vs. temporal variation in measured C cycle processes and their environmental drivers. We also conducted a sensitivity analysis of a peatland C model to identify how variation in ecosystem parameters contributes to model prediction uncertainty. High spatial variability in C cycle processes resulted in the inability to determine if the bog was a C source or sink, as the 95% confidence interval ranged from a source of 50 g C m –2 yr –1 to a sink of 67 g C m –2 yr –1 . Model sensitivity analysis also identified that spatial variation in tree and shrub photosynthesis, allocation characteristics, and maintenance respiration all contributed to large variations in the pretreatment estimates of net C balance. Variation in ecosystem processes can be more thoroughly characterized if more measurements are collected for parameters that are highly variable over space and time, and especially if those measurements encompass environmental gradients that may be driving the spatial and temporal variation (e.g., hummock vs. hollow microtopographies, and wet vs. dry years). Together, the coupled modeling and empirical approaches indicate that variability in C cycle processes and their drivers must be taken into account when interpreting the significance of experimental warming and elevated CO 2 treatments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Impact of I/O and Data Management in Ensemble Large Scale Climate Forecasting Using EC-Earth3

The EC-Earth climate model is a seamless Earth System Model (ESM) used to carry out climate research in 24 academic institutions and meteorological services from 11 countries in Europe. This model couples several components and it is continuously under development. In this work we present a study regarding the impact of the I/O and data management when using EC-Earth in well-known supercomputing environments. Most large-scale and long-term climate simulators have been developed bearing in mind the paramount importance of its scalability. However, the computational capabilities of the High Performance Computing (HPC) environments increase at so great speed that it is almost impossible to re-implement the whole models so that they are able to exploit efficiently the new features. Therefore, it is necessary to design different strategies to take advantage of them. In this work we present an operational framework to run ensemble simulations in HPC platforms. A set of experiments are presented in order to validate the suitability of this technique. Moreover, the derived impact regarding the I/O and data management aspects is analyzed.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Predicting Near-Term Changes in the Earth System: A Large Ensemble of Initialized Decadal Prediction Simulations Using the Community Earth System Model

The objective of near-term climate prediction is to improve our fore-knowledge, from years to a decade or more in advance, of impactful climate changes that can in general be attributed to a combination of internal and externally forced variability. Predictions initialized using observations of past climate states are tested by comparing their ability to reproduce past climate evolution with that of uninitialized simulations in which the same radiative forcings are applied. A new set of decadal prediction (DP) simulations has recently been completed using the Community Earth System Model (CESM) and is now available to the community. This new large-ensemble (LE) set (CESM-DPLE) is composed of historical simulations that are integrated forward for 10 years following initialization on 1 November of each year between 1954 and 2015. CESM-DPLE represents the “initialized” counterpart to the widely studied CESM Large Ensemble (CESM-LE); both simulation sets have 40-member ensembles, and they use identical model code and radiative forcings. Comparing CESM-DPLE to CESM-LE highlights the impacts of initialization on prediction skill and indicates that robust assessment and interpretation of DP skill may require much larger ensembles than current protocols recommend. CESM-DPLE exhibits significant and potentially useful prediction skill for a wide range of fields, regions, and time scales, and it shows widespread improvement over simpler benchmark forecasts as well as over a previous initialized system that was submitted to phase 5 of the Coupled Model Intercomparison Project (CMIP5). Finally, the new DP system offers new capabilities that will be of interest to a broad community pursuing Earth system prediction research.

54 ENVIRONMENTAL SCIENCES↗