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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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At least 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

The Role of Ice Splintering on Microphysics of Deep Convective Clouds Forming Under Different Aerosol Conditions: Simulations Using the Model With Spectral Bin Microphysics

Observations during the Ice in Clouds Experiment-Tropical (ICE-T) field experiment show that the ice particles concentration in a developing deep convective clouds at the level of T = -15 °C reached about 500 L -1 , that is, many orders higher than that of ice-nucleating particle. To simulate microphysics of these clouds, the 2-D Hebrew University Cloud model (HUCM) with spectral bin microphysics was used in which two main types of ice multiplication mechanisms were included in addition to the Hallet-Mossop mechanism. In the first ice multiplication mechanism ice splinters form by drop freezing and drop-ice collisions. Ice multiplication of this type dominates during developing stage of cloud evolution, when liquid water content is significant. At later stage when clouds become nearly glaciated, ice crystals are produced largely by ice splintering during ice-ice collisions (the second ice multiplication mechanism). Simulations show that droplet size distributions, as well as size distributions of ice particles, agree well with the measurements during ICE-T. Simulations with different cloud condensation nuclei concentrations show the existence of the “optimum” cloud condensation nuclei concentration (or droplet concentration), at which concentration of ice splinters reaches maximum. In these simulations ice nucleation caused by the direct formation of ice crystals upon ice-nucleating particles, as well as the Hallett-Mossop process, has a negligible contribution to the ice crystal concentration.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Simulations of Winter Arctic Clouds and Associated Radiation Fluxes Using Different Cloud Microphysics Schemes in the Polar WRF: Comparisons With CloudSat, CALIPSO, and CERES

Clouds are important for the Arctic climate, but simulating such clouds with numerical models is still challenging. The accuracy of model clouds has not been sufficiently examined due to the harsh Arctic environment obstructing cloud observations, especially during Arctic winters experiencing polar nights. This study compares the Arctic winter clouds simulated by a weather forecast model to cloud observations from active (lidar and radar) satellite instruments. The model successfully produced cloud patterns similar to the satellite observations. However, the choice of the cloud physics module in the model can modify the amount of cloud water significantly enough to affect the simulated surface climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Cloud and Precipitation Properties of MCSs Along the Meiyu Frontal Zone in Central and Southern China and Their Associated Large-Scale Environments

This study focuses on investigating the cloud and precipitation features of Meiyu mesoscale convective systems (MCSs) and their relation to the large-scale environments in central and southern China using satellite observations and reanalysis data during the period 2014–2018. MCSs from two different locations, the Yangtze River Basin (YRB) and Southern China (SC), are examined separately. The Meiyu MCSs have a mean precipitation rate of 3.6 mm/hr and contribute 20% to 60% of the total precipitation during the Meiyu period. The diurnal cycle of Meiyu MCSs shows a maximum precipitation amount in the morning, which is associated with the enhanced nocturnal low-level jet (LLJ) overnight. Although the synoptic setups in YRB and SC are found to be similar when normalized around the MCS initiation locations, MCSs exhibit some differences in terms of the cloud top height, precipitation rate, and duration, which are likely by the differences in the local forcing. Large interannual variations are found in MCSs' number, cloud size, lifetime, and rainfall intensity, which is found to be associated with the interannual variabilities in the large-scale environments. By comparing the large-scale environments with climatological mean states, we find that the year with the most intense MCS activity during the study period is characterized by an intensified southwesterly LLJ, which increases the moisture transport from the Indian Ocean and an enhancement of the midtropospheric westerly jet, which induces adiabatic ascent along the Meiyu front, creating more favorable conditions for convection.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Robust Multiyear Climate Impacts of Volcanic Eruptions in Decadal Prediction Systems

Abstract Major tropical volcanic eruptions have a large impact on climate, but there have only been three major eruptions during the recent relatively well‐observed period. Models are therefore an important tool to understand and predict the impacts of an eruption. This study uses five state‐of‐the‐art decadal prediction systems that have been initialized with the observed state before volcanic aerosols are introduced. The impact of the volcanic aerosols is found by subtracting the results of a reference experiment where the volcanic aerosols are omitted. We look for the robust impact across models and volcanoes by combining all the experiments, which helps reveal a signal even if it is weak in the models. The models used in this study simulate realistic levels of warming in the stratosphere, but zonal winds are weaker than the observations. As a consequence, models can produce a pattern similar to the North Atlantic Oscillation in the first winter following the eruption, but the response and impact on surface temperatures are weaker than in observations. Reproducing the pattern, but not the amplitude, may be related to a known model error. There are also impacts in the Pacific and Atlantic Oceans. This work contributes toward improving the interpretation of decadal predictions in the case of a future large tropical volcanic eruption.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Subseasonal Variability of Elevated Dust Concentrations Over South Florida

Dust mass concentrations have been measured daily at Miami, Florida, in the summer months, and biweekly throughout the remaining months, since 1974. The 43-year record of dust mass concentrations indicate large daily, seasonal, and interannual variations, with most of the dust arriving within 5–8 episodes each summer. On average, dust arrives to Miami, Florida, 10 days after emission from North Africa, with measured concentrations depending on characteristics of the lower free-tropospheric winds due to the vast travel distance. Daily dust mass concentrations from July and August, the months that contribute the most to the annual mean, are used to characterize the synoptic conditions most favorable for dust transport. Two key regions are linked with the highest daily dust mass concentrations above Miami: (i) easterly winds, averaged over 850–500 mb, over the Tropical West Atlantic [15–25°N, 45–80°W], and (ii) southerly winds, similarly averaged, over the Florida Peninsula [20–30°N,75–80°W]. Winds within these two regions are enhanced when the North Atlantic subtropical high is displaced south and zonally elongated, relocating the western edge over Florida. A dust-transport-efficiency index, based on the maximum potential for dust to arrive above Miami with limited loss to deposition or mixing, identifies high-dust loading cases on the subseasonal scale. Monthly dust-transport-efficiency values agree well with the monthly dust trends over the 43-year time span. While seasonal dust loadings have been decreasing over Florida in the past decade, the transport efficiency has been increasing, possibly due to trends in the North Atlantic subtropical high.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

The Contributions of Shear and Turbulence to Cloud Overlap for Cumulus Clouds

The causes of vertical cloud overlap, the ratio between the cloud fraction by area and the cloud fraction by volume, are studied for fields of cumulus convection. Using large-eddy simulations, the structure of individual clouds within the cloud field is inspected and connected to the overall cloud cover of the entire cloud field. First, it is shown that the cloud overlap of the entire field can be well approximated by the total cloud overlap of the individual clouds. It is then shown that a simple maximum overlap assumption, which is commonly used for cloud fields with small layer depth, can only account for roughly half of the overlap inefficiency. This is due to the fact that maximum overlap only represents variations in cloud width as a function of depth but does not take other factors into account, most notably shear or turbulence. The effects of turbulence and wind shear on the overlap of individual clouds are first estimated as a function of cloud depth, which closes the discrepancy between observed cloud overlap and the maximum overlap assumption. Then, an empirical model is developed for the shear and turbulence contributions on overlap as a function of cloud depth and of synoptic conditions. Finally, it is shown that our model is capable of accurately predicting overlap for a large number of cloud fields and under a variety of meteorological conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

On the Relationship Between the Marine Cold Air Outbreak M Parameter and Low-Level Cloud Heights in the Midlatitudes

Focusing on conditions of subsidence when low clouds are present, ground-based observations in both the North Atlantic and the Southern Ocean reveal strong relationships between cloud boundary (base and top heights) and different measures of lower tropospheric instability. The difference in potential temperature between the surface and 800 hPa (a metric called M) provides a stronger relationship than measures of inversion strength such as the lower tropospheric stability and estimated inversion strength. This is because (1) inversion strength itself does not correlate well with cloud boundaries, and (2) M contains information that appears important for cloud boundaries. These include the surface forcing through the use of sea surface rather than near-surface air temperature and an upper level close to the real cloud top. These results expand upon previous work on the importance of M as a predictor of cloud morphology. However, important differences are found in low-cloud conditions for the North Atlantic as compared to the Southern Ocean (for a given value of M): stronger inversions, deeper boundary layers, and much larger sea level pressures. Therefore, the relationship between cloud boundaries and M differs between the two regions. A general circulation model provides similar relationships as observed between M and both cloud top height and temperature but tends to place clouds higher and at colder temperatures than observed for a given M. This might cause issues with the representation of precipitation, cloud cover and radiation in the Southern Ocean.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

The Global Teleconnection Signature of the Madden-Julian Oscillation and Its Modulation by the Quasi-Biennial Oscillation

Recent research has suggested that the tropical and extratropical character of the Madden-Julian oscillation (MJO) depends on the state of the stratospheric quasi-biennial oscillation (QBO). With this in mind, we use both reanalysis and a global climate model (CESM2-WACCM) to analyze the global character of upper tropospheric-lower stratospheric geopotential height anomalies connected with the MJO and quantify dependencies of these teleconnections on the state of the QBO. We find that the global teleconnection signature of the MJO depends upon the state of the QBO. Globally, within reanalysis the fraction of 20- to 90-day 250-hPa geopotential height variance linked to the MJO is largest during boreal winter and summer for easterly QBO phases and smallest during westerly QBO phases of boreal winter. The difference between QBO phases is mostly driven by changes in the tropical signature of the MJO, although during boreal winter the Northern Hemispheric teleconnections are particularly more prominent during easterly QBO phases. Otherwise, the QBO modulation of extratropical MJO teleconnections is mainly realized through changes in the locations of the teleconnections. A QBO-MJO relationship is also apparent within CESM2-WACCM but is weaker than that observed. This extratropical modulation implies that the regions that benefit from increased subseasonal predictability due to the MJO may also change as a function of the QBO. In a broader sense, these findings emphasize that knowledge of the tropical stratospheric state, particularly as it relates to the QBO, is important for understanding the connections between the MJO and the extratropics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Impacts of Latent Energy and Snow Fall Speed on a Wintertime Midlatitude Cyclone

This study aimed to understand the impacts of latent energy as well as snow fall speeds on precipitation properties and synoptic-scale storm characteristics of a wintertime midlatitude cyclone. Simulations of a potent winter storm that impacted the Rocky Mountains and northern Great Plains of the United States in February 2017 were performed using the Weather Research and Forecasting model with latent heating or cooling from individual microphysical processes systematically turned off and fall speeds adjusted by ±50%. Results indicated substantial impacts on the microphysical characteristics of the simulated storm to fall speed, cooling from sublimation, and warming from deposition. The impacts of cooling and warming were manifested as differences in accumulated snowfall. Increased (decreased) fall speeds led to smaller (larger) ice crystals and total mass, resulting in offsetting effects on the precipitation flux, and thus minimal impacts on snowfall and large-scale characteristics of the storm. Warming and cooling associated with deposition and sublimation, respectively, impacted the synoptic-scale dynamics, whereby removing warming from deposition resulted in an increased meridional temperature gradient near the jet stream, thus increasing the jet strength and causing it to be more westerly with less curvature aloft. This in turn limited upper-level divergence, creating a weaker surface low and shifting the precipitation shield southward. The opposite occurred with the removal of latent cooling due to sublimation. This study highlights the potential importance of latent energy associated with ice sublimation and deposition and fall speeds in the larger-scale characteristics of winter storms.

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

Understanding Differences in California Climate Projections Produced by Dynamical and Statistical Downscaling

Abstract We compare historical and end‐of‐century temperature and precipitation patterns over California from one dynamically downscaled simulation using the Weather Research and Forecast (WRF) model and two simulations statistically downscaled using Localized Constructed Analogs (LOCA). We uniquely separate causes of differences between dynamically and statistically based future climate projections into differences in historical climate (gridded observations versus regional climate model output) and differences in how these downscaling techniques explicitly handle future climate changes (numerical modeling versus analogs). In these methods, solutions between different downscaling techniques differ more in the future compared to the historical period. Changes projected by LOCA are insensitive to the choice of driving data. Only through dynamical downscaling can we simulate physically consistent regional springtime warming patterns across the Sierra Nevada, while the statistical simulations inherit an unphysical signal from their parent Global Climate Model (GCM) or gridded data. The results of our study clarify why these different techniques produce different outcomes and may also provide guidance on which downscaled products to use for certain impact analyses in California and perhaps other Mediterranean regimes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

New Particle Formation and Growth to Climate-Relevant Aerosols at a Background Remote Site in the Western Himalaya

New particle formation (NPF) can influence the Earth’s radiative budget when the newly formed particles grow to climate-relevant sizes. Here, we present analysis of 21-months of continuous aerosol size distribution measurements at a background remote site in the western Himalaya and provide observational evidence that newly formed particles grow to cloud condensation nuclei (CCN)-active sizes (i.e. >20-100 nm in diameter). Out of total 55 NPF events, 38 (66%) events occurred in the pre-monsoon season (March-May). NPF events were classified into those with and without pollution influence as polluted and cleaner, respectively, using black carbon data. The analysis of air mass age, based on the ratio of number concentration of Aitken to accumulation mode aerosols, indicated that NPF occurred in the relatively cleaner air masses reaching to the site. The median formation rate of 10 nm particles and particle growth rates for cleaner events were three-fold and two-fold, respectively, higher than polluted events. We present the first estimates of the survival probability of newly formed particles to 50 nm and 100 nm size, which was not attempted in an Indian environment previously. The survival probability to 50 nm particles ranged from 44 to 98%, with a mean and standard deviation of 82 ± 18%. On average, ~60% of the particles surviving to 50 nm survived to 100 nm, making the overall survival probability of 100 nm to 53 ± 31%. This indicates that the probability of nucleated particles growing to CCN-active sizes under a large source of condensing vapor (transported from nearby lower-altitude regions) and low pre-existing particle concentrations (background mountain site) is high compared to the previous studies. These findings highlight the importance of the efficiency of nucleation events for producing CCN, which is a critical basis of aerosol indirect effects.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

The Convective-To-Total Precipitation Ratio and the “Drizzling” Bias in Climate Models

Overestimation of precipitation frequency and duration while underestimating intensity, that is, the “drizzling” bias, has been a long-standing problem of global climate models. Here we explore this issue from the perspective of precipitation partitioning. We found that most models in the Climate Model Intercomparison Project Phase 5 (CMIP5) have high convective-to-total precipitation (PC/PR) ratios in low latitudes. Convective precipitation has higher frequency and longer duration but lower intensity than non-convective precipitation in many models. As a result, the high PC/PR ratio contributes to the “drizzling” bias over low latitudes. The PC/PR ratio and associated “drizzling” bias increase as model resolution coarsens from 0.5° to 2.0°, but the resolution's effect weakens as the grid spacing increases from 2.0° to 3.0°. Some of the CMIP6 models show reduced “drizzling” bias associated with decreased PC/PR ratio. Thus, more reasonable precipitation partitioning, along with finer model resolution should alleviate the “drizzling” bias within current climate models.

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

Indicator Patterns of Forced Change Learned by an Artificial Neural Network

Abstract Many problems in climate science require the identification of signals obscured by both the “noise” of internal climate variability and differences across models. Following previous work, we train an artificial neural network (ANN) to predict the year of a given map of annual‐mean temperature (or precipitation) from forced climate model simulations. This prediction task requires the ANN to learn forced patterns of change amidst a background of climate noise and model differences. We then apply a neural network visualization technique (layerwise relevance propagation) to visualize the spatial patterns that lead the ANN to successfully predict the year. These spatial patterns thus serve as “reliable indicators” of the forced change. The architecture of the ANN is chosen such that these indicators vary in time, thus capturing the evolving nature of regional signals of change. Results are compared to those of more standard approaches like signal‐to‐noise ratios and multilinear regression in order to gain intuition about the reliable indicators identified by the ANN. We then apply an additional visualization tool (backward optimization) to highlight where disagreements in simulated and observed patterns of change are most important for the prediction of the year. This work demonstrates that ANNs and their visualization tools make a powerful pair for extracting climate patterns of forced change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Comparison of Arctic and Antarctic Stratospheric Climates in Chemistry Versus No‐Chemistry Climate Models

Using nine chemistry-climate and eight associated no-chemistry models, we investigate the persistence and timing of cold episodes occurring in the Arctic and Antarctic stratosphere during the period 1980–2014. We find systematic differences in behavior between members of these model pairs. In a first group of chemistry models whose dynamical configurations mirror their no-chemistry counterparts, we find an increased persistence of such cold polar vortices, such that these cold episodes often start earlier and last longer, relative to the times of occurrence of the lowest temperatures. Also the date of occurrence of the lowest temperatures, both in the Arctic and the Antarctic, is often delayed by 1–3 weeks in chemistry models, versus their no-chemistry counterparts. This behavior exacerbates a widespread problem occurring in most or all models, a delayed occurrence, in the median, of the most anomalously cold day during such cold winters. In a second group of model pairs there are differences beyond just ozone chemistry. In particular, here the chemistry models feature more levels in the stratosphere, a raised model top, and differences in non-orographic gravity wave drag versus their no-chemistry counterparts. Such additional dynamical differences can completely mask the above influence of ozone chemistry. The results point toward a need to retune chemistry-climate models versus their no-chemistry counterparts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Aerosol Indirect Effects on Water Vapor in the UTLS of Typhoon Saomai (2006)

The evolution of landfalling Typhoon Saomai (2006) is simulated using the Weather Research and Forecasting model with spectral bin microphysics scheme, showing tropical cyclone (TC) could vertically transport water vapor from troposphere to upper troposphere and lower stratosphere (UTLS). Three aerosol sensitivity experiments are conducted to explore the indirect effects of aerosol served as cloud condensation nuclei (CCN) on overshooting convection (OTC) and water vapor content in UTLS, namely MAR (maritime), MIX (semi‐continental) and CON (continental). Results revealed that CON simulation with high initial aerosol concentration showing invigorated convection at the periphery of the TC, which interfered with the reformation of TC eyewall, leading to TC weakening finally. In addition, CON simulated the least water content in UTLS through suppressing the number of convection overshooting the tropopause level. Most overshooting events take place during TC developing stage in the eyewall region before landfall. Higher levels of CCN concentration could lead to decreased number of OTC in TC, consistently reduced the water vapor content in UTLS. CON and MIX experiments simulated respectively 21.9% (16.2%) and 9.96% (1.5%) less OTC (water vapor content in UTLS) than MAR simulation. Further, water vapor content in UTLS is affected by the interaction of OTC and ice‐phase microphysics. The interesting point is that the CCN sensitivity experiments show that water vapor content in UTLS of a TC is sensitive to the CCN concentration in the boundary layer.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Future Projections of EURO‐CORDEX Raw and Bias‐Corrected Daily Maximum Wind Speeds Over Scandinavia

Twenty historical and future Coordinated Regional Climate Downscaling Experiment ensemble for Europe simulations are bias corrected to investigate the future changes in the daily maximum wind speed over Scandinavia. We use quantile mapping to adjust the wind for the historical period (1985–2014) and quantile delta mapping for two future periods (2041–2070, 2071–2100, RCP8.5) with the 3-km spatial resolution NORA3 hindcast as the reference data set. Decomposing the variance, we find that most of the inter-model spread in the bias and the response to climate change is due to the regional climate model over land and mainly to the general climate model over sea. On average, the mean daily maximum wind speed is projected to increase everywhere except along the western coast of Norway and Denmark. In summer, we see an opposite sign over Sweden and Finland. The Norwegian Sea experiences weaker mean and high wind whereas the Baltic Sea experiences a strengthening. Bias correction influences the amplitude of the response, not the response pattern. Wind speed distributions can have different shapes in the future, with, for example, a flattening of the distribution off the coast of Norway with more frequent weak and very strong winds. Apart from a few locations in Norway, we find an increase in the number of days in the local highest historical wind category. Overall, summer exhibits opposite signals compared to the three other seasons. At country scale, the sign of the change in the mean and 98th percentile varies greatly depending on the region and among the simulations, especially for Norway.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Large Ensemble Particle Filter for Spatial Climate Reconstructions Using a Linear Inverse Model

Proxy records that document the last 2000 years of climate provide evidence for the wide range of the natural climate variability from inter-annual to secular timescales not captured by the short window of recent direct observations. Assessing climate models ability to reproduce such natural variations is crucial to understand climate sensitivity and impacts of future climate change. Paleoclimate data assimilation (PDA) offers a powerful way to extend the short instrumental period by optimally combining the physics described by General Circulation Climate Models (GCMs) with information from available proxy records while taking into account their uncertainties. Here we present a new PDA approach based on a sequential importance resampling (SIR) Particle filter (PF) that uses Linear Inverse Modeling (LIM) as an emulator of several CMIP-class GCMs. We examine in a perfect-model framework the skill of the various LIMs to forecast the dynamics of the surface temperatures and provide spatial field reconstructions over the last millennium in a SIR PF. Our results show that the LIMs allow for skillful ensemble forecasts at 1-year lead-time based on GCMs dynamical knowledge with best prediction in the tropics and the North Atlantic. The PDA further provides a set of physically consistent spatial fields allowing robust uncertainty quantification related to climate models biases and proxy spatial sampling. Our results indicate that the LIM yields dynamical memory improving climate variability reconstructions and support the use of the LIM as a GCM-emulator in real reconstruction to propagate large ensembles of particles at low cost in SIR PF.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Spanning the Gap From Bulk to Bin: A Novel Spectral Microphysics Method

Microphysics methods for climate models and numerical weather prediction typically track one, two, or three moments of a droplet size distribution for various categories of liquid, ice, and aerosol. Such methods rely on conversion parameters between these categories, which introduces uncertainty into predictions. While higher-fidelity options such as bin and Lagrangian schemes exist, they require too many degrees of freedom for climate modeling applications and introduce numerical challenges. Here we introduce a flexible spectral microphysics method based on collocation of basis functions. This method generalizes to a linear bulk scheme when using few basis functions and to a smoothed bin scheme with more degrees of freedom. Tested in an idealized box setting, the method improves spectral accuracy for droplet collision-coalescence and may eliminate the need for precipitation autoconversion rates required by bulk methods; furthermore, it generalizes well to multimodal distributions with less complexity than a bin method. The potential to extend this collocation representation to multiple hydrometeor classes suggests a path forward to unify liquid, ice, and aerosol microphysics in a single, flexible, computational framework for climate modeling.

54 ENVIRONMENTAL SCIENCES↗