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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Future Projections of the El Niño—Southern Oscillation and Tropical Pacific Mean State in CMIP6

Abstract The El Niño—Southern Oscillation (ENSO) is an important mode of tropical Pacific atmosphere‐ocean variability that drives teleconnections with weather and climate globally. However, prior studies using state‐of‐the‐art climate models lack consensus regarding future ENSO projections and are often impacted by tropical Pacific sea‐surface temperature (SST) biases. We used 173 simulations from 29 climate models participating in the Coupled Model Intercomparison Project, version 6 (CMIP6) to analyze model biases and future ENSO projections. We analyzed two ENSO indices, namely the ENSO Longitude Index (ELI), which measures zonal shifts in tropical Pacific deep convection and accounts for changes in background SST, and the Niño 3.4 index, which measures SST anomalies in the central‐eastern equatorial Pacific. We found that the warm eastern tropical‐subtropical Pacific SST bias typical of previous generations of climate models persists into many of the CMIP6 models. Future projections of ENSO shift toward more El Niño‐like conditions based on ELI in 48% of simulations and 55% of models, in association with a future weakening of the zonal equatorial Pacific SST gradient. On the other hand, none of the models project a significant shift toward La Niña‐like conditions. The standard deviation of the Niño 3.4 index indicates a lack of consensus on whether an increase or decrease in ENSO variability is expected in the future. Finally, we found a possible relationship between historical SST and low‐level cloud cover biases in the ENSO region and future changes in ELI; however, this result may be impacted by limitations in data availability.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Towards a Unified Setup to Simulate Mid‐Latitude and Tropical Mesoscale Convective Systems at Kilometer‐Scales

Abstract Mesoscale convective systems (MCSs) are the main source of precipitation in the tropics and parts of the mid‐latitudes and are responsible for high‐impact weather worldwide. Studies showed that deficiencies in simulating mid‐latitude MCSs in state‐of‐the‐art climate models can be alleviated by kilometer‐scale models. However, whether these models can also improve tropical MCSs and whether we can find model settings that perform well in both regions is understudied. We take advantage of high‐quality MCS observations collected over the Atmospheric Radiation Measurement (ARM) facilities in the US Southern Great Plains (SGP) and the Amazon basin near Manaus (MAO) to evaluate a perturbed physics ensemble of simulated MCSs with 4 km horizontal grid spacing. A new model evaluation method is developed that enables to distinguish biases stemming from spatiotemporal displacements of MCSs from biases in their reflectivity and cloud shield. Amazon MCSs are similarly well simulated across these evaluation metrics than SGP MCSs despite the challenges anticipated from weaker large‐scale forcing in the tropics. Generally, SGP MCSs are more sensitive to the choice of model microphysics, while Amazon cases are more sensitive to the planetary boundary layer (PBL) scheme. Although our tested model physics combinations had strengths and weaknesses, combinations that performed well for SGP simulations result in worse results in the Amazon basin and vice versa. However, we identified model settings that perform well at both locations, which include the Thompson and Morrison microphysics coupled with the Yonsei University (YSU) PBL scheme and the Thompson scheme coupled with the Mellor‐Yamada‐Janjic PBL scheme.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Cloud, Aerosol, and Radiative Properties Over the Western North Atlantic Ocean

This study examines the atmospheric properties of weather states (WSs) derived from the International Satellite Cloud Climatology Project (ISCCP) over the Western North Atlantic Ocean. In particular, radiation and aerosol data corresponding to two sites in the study domain, Pennsylvania State University and Bermuda, were examined to characterize the atmospheric properties of the various satellite-derived WSs. At both sites, the fair weather WS was most prevalent, followed by the cirrus WS. Differences in the seasonality of the various WSs were observed at the two sites. Fractional sky cover and effective shortwave cloud transmissivity derived from ground-based radiation measurements were able to capture differences among the satellite-derived WSs. Speciated aerosol optical thicknesses (AOT) from the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) were used to investigate potential differences in aerosol properties among the WSs. The clear sky WS exhibited below-average seasonal values of AOT at both sites year-round, as well as relatively high rates of occurrence with low AOT events. In addition, the clear sky WS showed above-average contributions from dust and black carbon to the total AOT year-round. Finally, transitions between various WSs were examined under low, high, and mid-range AOT conditions. The most common pathway was for the WSs to remain in the same state after a 3 hr interval. Some WSs, such as midlatitude storms, deep convection, middle top, and shallow cumulus, were more prevalent as ending states under high AOT conditions. This work motivates examining differences in aerosol properties between WSs in other regions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Mesoscale Convective Systems Tracking Method Intercomparison (MCSMIP): Application to DYAMOND Global km‐Scale Simulations

Abstract Global kilometer‐scale models represent the future of Earth system modeling, enabling explicit simulation of organized convective storms and their associated extreme weather. Here, we comprehensively evaluate tropical mesoscale convective system (MCS) characteristics in the DYAMOND (DYnamics of the atmospheric general circulation modeled on non‐hydrostatic domains) simulations for both summer and winter phases. Using 10 different feature trackers applied to simulations and satellite observations, we assess MCS frequency, precipitation, and other key characteristics. Substantial differences (a factor of 2–3) arise among trackers in observed MCS frequency and their precipitation contribution, but model‐observation differences in MCS statistics are more consistent across trackers. DYAMOND models are generally skillful in simulating tropical mean MCS frequency, with multi‐model mean biases ranging from −2%–8% over land and −8%–8% over ocean (summer vs. winter). However, most DYAMOND models underestimate MCS precipitation amount (23%) and their contribution to total precipitation (17%). Biases in precipitation contributions are generally smaller over land (13%) than over ocean (21%), with moderate inter‐model variability. While models better simulate MCS diurnal cycles and cloud shield characteristics, they overestimate MCS precipitation intensity and underestimate stratiform rain contributions (up to a factor of 2), particularly over land, albeit observational uncertainties exist. Additionally, models exhibit a wide range of precipitable water in the tropics compared to reanalysis and satellite observations, with many models showing exaggerated sensitivity of MCS precipitation intensity to precipitable water. The MCS metrics developed here provide process‐oriented diagnostics to guide future model development.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Simulation of radioactive plume transport in the atmosphere including dynamics of particle aggregation and breakup

Accurate prediction of the atmospheric transport of debris particles relies heavily on our knowledge of the size distribution of the particles within a debris cloud. Assuming a fixed particle size during simulations is not always viable since the size distribution of the debris can change during transport. Various microphysical processes, such as aggregation and breakup, influence debris particles and dictate any changes to the size distribution. To track those changes that can occur, a population balance model can be adopted and instituted within a model framework. Nonetheless, many of the models that simulate the transport of radioactive debris following a device-driven fission incident have historically neglected to consider these processes. As such, this work describes our effort to develop a modeling framework capable of simulating the transport and deposition of a radioactive plume generated from a fission incident with a dynamic population balance including particle aggregation and breakup. Herein the impact of aggregation and breakup, individually and collectively, on the particle size distribution is explored using the developed framework. When simulating aggregation, for example, six mechanisms, including Brownian coagulation, the convective enhancement to Brownian coagulation, van der Waals-viscous force correction for Brownian coagulation, gravitational collection, turbulent inertial motion, and turbulent shear, are considered. Brownian coagulation and its corrections have, as one would expect, a large impact on relatively small aggregates. Aggregates with a diameter that is less than or equal to 1.0 μm, for instance, comprise 50.6 vol % of all aggregates in the absence of aggregation and 31.2 vol % when Brownian coagulation and its corrections are considered. Gravitational collection and, to a much lesser extent, turbulent shear and turbulent inertial motion are, conversely, of great importance to relatively large aggregates (i.e., diameter greater than 3.0 μm). Additionally, the individual effects of atmospheric and particle parameters, such as wind speed and particle density, are examined. Of the parameters examined, turbulent energy dissipation and aggregate fractal dimension (i.e., aggregate shape with lower values representing more irregular particles) were of substantial importance since both terms directly impact aggregate stability and, by extension, the breakup rate. Large-scale transport and deposition simulations in a dry atmosphere are also presented and discussed as a proof of concept.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2024

A Case Study Investigating the Low Summertime CAPE Behavior in the Global Forecast System

Convective available potential energy (CAPE) is an important index for storm forecasting. Recent versions (v15.2 and v16) of the Global Forecast System (GFS) predict lower values of CAPE during summertime in the continental United States than analysis and observation. We conducted an evaluation of the GFS in simulating summertime CAPE using an example from the Unified Forecast System Case Study collection to investigate the factors that lead to the low CAPE bias in GFS. Specifically, we investigated the surface energy budget, soil properties, and near-surface and upper-level meteorological fields. Results show that the GFS simulates smaller surface latent heat flux and larger surface sensible heat flux than the observations. This can be attributed to the slightly drier-than-observed soil moisture in the GFS that comes from an offline global land data assimilation system. The lower simulated CAPE in GFS v16 is related to the early drop of surface net radiation with excessive boundary layer cloud after midday when compared with GFS v15.2. A moisture-budget analysis indicates that errors in the large-scale advection of water vapor does not contribute to the dry bias in the GFS at low levels. Common Community Physics Package single-column model (SCM) experiments suggest that with realistic initial vertical profiles, SCM simulations generate a larger CAPE than runs with GFS IC. SCM runs with an active LSM tend to produce smaller CAPE than that with prescribed surface fluxes. Note that the findings are only applicable to this case study. Including more warm-season cases would enhance the generalizability of our findings.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

A High‐Resolution Tropical Mesoscale Convective System Reanalysis (TMeCSR)

Abstract Modern global reanalysis products have greatly accelerated meteorological research in synoptic‐to‐planetary‐scale phenomena. However, their use in studying tropical mesoscale convective systems (MCSs) and their regional‐to‐global impact has mostly been limited to supplying initial and boundary conditions for MCS‐resolving simulations and providing information about the large‐scale environments of MCSs. These limitations are due to difficulties in resolving tropical MCS dynamics in the relatively low‐resolution global models and that tropical MCSs often occur over poorly observed regions. In this work, a Tropical MCS‐resolving Reanalysis product (TMeCSR) was created over a region with frequent tropical MCSs. This region spans the tropical Indian Ocean, tropical continental Asia, Maritime Continent, and Western Pacific. TMeCSR is produced by assimilating all‐sky infrared radiances from geostationary satellites and other conventional observations into an MCS‐resolving regional model using the Ensemble Kalman Filter. The resulting observation‐constrained high‐resolution (9‐km grid spacing) data set is available hourly during the boreal summer (June‐August) of 2017, during which widespread severe flooding occurred. Comparisons of TMeCSR and European Center for Medium Range Weather Forecast Reanalysis version 5 (ERA5) against independent satellite retrievals indicate that TMeCSR's cloud and multiscale rain fields are better than those of ERA5. Furthermore, TMeCSR better captured the diurnal variability of rainfall and the statistical characteristics of MCSs. Forecasts initialized from TMeCSR also have more accurate rain and clouds than those initialized from ERA5. The TMeCSR and ERA5 forecasts have similar performances with respect to sounding and surface observations. These results indicate that TMeCSR is a promising MCS‐resolving data set for tropical MCS studies.

Chan, Man‐Yau↗
DOE OSTI2022

The Illumination of Thunderclouds by Lightning: 3. Retrieving Optical Source Altitude

Abstract Optical space‐based lightning sensors such as the Geostationary Lightning Mapper (GLM) detect and geolocate lightning by recording rapid changes in cloud top illumination. While lightning locations can be determined to within a pixel on the GLM imaging array, these instruments are not individually able to natively report lightning altitude. It has previously been shown that thunderclouds are illuminated differently based on the altitude of the optical source. In this study, we examine how altitude information can be extracted from the spatial distributions of GLM energy recorded from each optical pulse. We match GLM “groups” with Lightning Mapping Array (LMA) source data that accurately report the 3‐D positions of coincident Radio‐Frequency (RF) emitters. We then use machine learning methods to predict the mean LMA source altitudes matched to GLM groups using metrics from the optical data that describe the amplitude, breadth, and texture of the group spatial energy distribution. The resulting model can predict the LMA mean source altitude from GLM group data with a median absolute error of <1.5 km, which is sufficient to determine the location of the charge layer where the optical energy originated. This model is able to capture changes to the source altitude distribution in response to convective processes in the thunderstorm, and the GLM predictions can reveal the vertical structure of individual flashes ‐ enabling 3‐D flash geolocation with GLM for the first time. Future work will account for differences in thunderstorm charge/precipitation structures and viewing angle across the GLM Field of View.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Can the GPM IMERG Final Product Accurately Represent MCSs’ Precipitation Characteristics over the Central and Eastern United States?

Mesoscale convective systems (MCSs) play an important role in water and energy cycles as they produce heavy rainfall and modify the radiative profile in the tropics and midlatitudes. An accurate representation of MCSs’ rainfall is therefore crucial in understanding their impact on the climate system. The V06B Integrated Multisatellite Retrievals from Global Precipitation Measurement (IMERG) half-hourly precipitation final product is a useful tool to study the precipitation characteristics of MCSs because of its global coverage and fine spatiotemporal resolutions. However, errors and uncertainties in IMERG should be quantified before applying it to hydrology and climate applications. This study evaluates IMERG performance on capturing and detecting MCSs’ precipitation in the central and eastern United States during a 3-yr study period against the radar-based Stage IV product. The tracked MCSs are divided into four seasons and are analyzed separately for both datasets. IMERG shows a wet bias in total precipitation but a dry bias in hourly mean precipitation during all seasons due to the false classification of nonprecipitating pixels as precipitating. These false alarm events are possibly caused by evaporation under the cloud base or the misrepresentation of MCS cold anvil regions as precipitating clouds by the algorithm. IMERG agrees reasonably well with Stage IV in terms of the seasonal spatial distribution and diurnal cycle of MCSs precipitation. A relative humidity (RH)-based correction has been applied to the IMERG precipitation product, which helps reduce the number of false alarm pixels and improves the overall performance of IMERG with respect to Stage IV.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Assessing the Atmospheric Response to Subgrid Surface Heterogeneity in the Single-Column Community Earth System Model, Version 2 (CESM2)

Land-atmosphere interactions are central to the evolution of the atmospheric boundary layer and the subsequent formation of clouds and precipitation. Existing global climate models represent these connections with bulk approximations on coarse spatial scales, but observations suggest that small-scale variations in surface characteristics and co-located turbulent and momentum fluxes can significantly impact the atmosphere. Recent model development efforts have attempted to capture this phenomenon by coupling existing representations of subgrid-scale (SGS) heterogeneity between land and atmosphere models. Such approaches are in their infancy and it is not yet clear if they can produce a realistic atmospheric response to surface heterogeneity. Here, we implement a parameterization to capture the effects of SGS heterogeneity in the Community Earth System Model (CESM2), and compare single-column simulations against high-resolution Weather Research and Forecasting (WRF) large-eddy simulations (LESs), which we use as a proxy for observations. The CESM2 experiments increase the temperature and humidity variances in the lowest atmospheric levels, but the response is weaker than in WRF-LES. In part, this is attributed to an underestimate of surface heterogeneity in the land model due to a lack of SGS meteorology, a separation between deep and shallow convection schemes in the atmosphere, and a lack of explicitly represented mesoscale secondary circulations. These results highlight the complex processes involved in capturing the effects of SGS heterogeneity and suggest the need for parameterizations that communicate their influence not only at the surface but also vertically.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Km‐Scale Simulations of Mesoscale Convective Systems Over South America—A Feature Tracker Intercomparison

Mesoscale convective systems (MCSs) are clusters of thunderstorms that are important in Earth's water and energy cycle. Additionally, they are responsible for extreme events such as large hail, strong winds, and extreme precipitation. Automated object-based analyses that track MCSs have become popular since they allow us to identify and follow MCSs over their entire life cycle in a Lagrangian framework. This rise in popularity was accompanied by an increasing number of MCS tracking algorithms, however, little is known about how sensitive analyses are concerning the MCS tracker formulation. Here, we assess differences between six MCS tracking algorithms on South American MCS characteristics and evaluate MCSs in kilometer-scale simulations with observational-based MCSs over 3 years. All trackers are run with a common set of MCS classification criteria to isolate tracker formulation differences. The tracker formulation substantially impacts MCS characteristics such as frequency, size, duration, and contribution to total precipitation. The evaluation of simulated MCS characteristics is less sensitive to the tracker formulation and all trackers agree that the model can capture MCS characteristics well across different South American climate zones. Dominant sources of uncertainty are the segmentation of cloud systems in space and time and the treatment of how MCSs are linked in time. Our results highlight that comparing MCS analyses that use different tracking algorithms is challenging. We provide general guidelines on how MCS characteristics compare between trackers to facilitate a more robust assessment of MCS statistics in future studies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Exploring the elevated water vapor signal associated with the free tropospheric biomass burning plume over the southeast Atlantic Ocean

In southern Africa, widespread agricultural fires produce substantial biomass burning (BB) emissions over the region. The seasonal smoke plumes associated with these emissions are then advected westward over the persistent stratocumulus cloud deck in the southeast Atlantic (SEA) Ocean, resulting in aerosol effects which vary with time and location. Much work has focused on the effects of these aerosol plumes, but previous studies have also described an elevated free tropospheric water vapor signal over the SEA. Water vapor influences climate in its own right, and it is especially important to consider atmospheric water vapor when quantifying aerosol-cloud interactions and aerosol radiative effects. Here we present airborne observations made during the NASA ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) campaign over the SEA Ocean. In observations collected from multiple independent instruments on the NASA P-3 aircraft (from near-surface to 6-7 km), we observe a strongly linear correlation between pollution indicators (carbon monoxide (CO) and aerosol loading) and atmospheric water vapor content, seen at all altitudes above the boundary layer. The focus of the current study is on the especially strong correlation observed during the ORACLES-2016 deployment (out of Walvis Bay, Namibia), but a similar relationship is also observed in the August 2017 and October 2018 ORACLES deployments. Using reanalyses from the European Centre for Medium-Range Weather Forecasts (ECMWF) and Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), and specialized WRF-Chem simulations, we trace the plume-vapor relationship to an initial humid, smoky continental source region, where it mixes with clean, dry upper tropospheric air and then is subjected to conditions of strong westward advection, namely the southern African easterly jet (AEJ-S). Our analysis indicates that air masses likely left the continent with the same relationship between water vapor and carbon monoxide as was observed by aircraft. This linear relationship developed over the continent due to daytime convection within a deep continental boundary layer (up to ~5-6 km) and mixing with higher-altitude air, which resulted in fairly consistent vertical gradients in CO and water vapor, decreasing with altitude and varying in time, but this water vapor does not originate as a product of the BB combustion itself. Due to a combination of conditions and mixing between the smoky, moist continental boundary layer and the dry and fairly clean upper-troposphere air above (~6 km), the smoky, humid air is transported by strong zonal winds and then advected over the SEA (to the ORACLES flight region) following largely isentropic trajectories. Hybrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT) back trajectories support this interpretation. This work thus gives insights into the conditions and processes which cause water vapor to covary with plume strength. Better understanding of this relationship, including how it varies spatially and temporally, is important to accurately quantify direct, semi-direct, and indirect aerosol effects over this region.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Precipitation Probability and Its Future Changes From a Global Cloud-Resolving Model and CMIP6 Simulations

This study investigates precipitation probability and its future changes using simulations from the Non-hydrostatic Icosahedral Atmospheric Model (NICAM), a global cloud-resolving model, and Coupled Model Intercomparison Project Phase 6 (CMIP6) models. For the precipitation probability comparison between models and Tropical Rainfall Measuring Mission (TRMM) during 1998–2008, the difference is greatly reduced by regridding to a common coarser resolution, but the difference signs largely remain. Both NICAM and CMIP6 model ensemble mean show less global-mean nonprecipitation fractions than observations, but NICAM agrees better with observations. For global-mean light precipitation probability, NICAM (CMIP6 model ensemble mean) is smaller (larger) than TRMM. NICAM shows higher heavy precipitation probability than TRMM in native resolutions, but it is close to TRMM and falls in the CMIP6 model range after regridding. For the precipitation probability changes from 1979–2008 to 2075–2104, NICAM predicts an increase in nonprecipitation and extreme heavy (>100 mm/day) precipitation probability but a slight decrease in the probability for precipitation <100 mm/day. After regridding to 2.5°, the precipitation intensity where the probability starts to increase becomes ~20 mm/day and the relative increases in nonprecipitation and heavy precipitation probability become much larger. Future heavy precipitation probability relative increases from CMIP6 models are much larger than NICAM at their native resolutions, but NICAM falls in the CMIP6 model range after regridding, indicating robust future increase (decrease) in heavy (light) precipitation probability regardless of underlying convection treatments. Discrepancy, however, exists in the projected nonprecipitation fraction changes: NICAM shows that nonprecipitation probability will increase over most of low and middle latitudes where CMIP6 models show less increases and even decreases.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Raindrop Size Spectrum in Deep Convective Regions of the Americas

This study compared drop size distribution (DSD) measurements on the surfaces, the corresponding properties, and the precipitation modes among three deep convective regions within the Americas. The measurement compilation corresponded to two sites in the midlatitudes: the U.S. Southern Great Plains and Córdoba Province in subtropical South America, as well as to one site in the tropics: Manacapuru in central Amazonia; these are all areas where intense rain-producing systems contribute to the majority of rainfall in the Americas’ largest river basins. This compilation included two types of disdrometers (Parsivel and 2D-Video Disdrometer) that were used at the midlatitude sites and one type of disdrometer (Parsivel) that was deployed at the tropical site. The distributions of physical parameters (such as rain rate R, mass-weighted mean diameter D m , and normalized droplet concentration N w ) for the raindrop spectra without rainfall mode classification seemed similar, except for the much broader N w distributions in Córdoba. The raindrop spectra were then classified into a light precipitation mode and a precipitation mode by using a cutoff at 0.5 mm h -1 based on previous studies that characterized the full drop size spectra. These segregated rain modes are potentially unique relative to previously studied terrain-influenced sites. In the light precipitation and precipitation modes, the dominant higher frequency observed in a broad distribution of N w in both types of disdrometers and the identification of shallow light precipitation in vertically pointing cloud radar data represent unique characteristics of the Córdoba site relative to the others. As a result, the co-variability between the physical parameters of the DSD indicates that the precipitation observed in Córdoba may confound existing methods of determining the rain type by using the drop size distribution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Polarimetric Signatures in Landfalling Tropical Cyclones

Polarimetric radar observations from the NEXRAD WSR-88D operational radar network in the contiguous United States, routinely available since 2013, are used to reveal three prominent microphysical signatures in landfalling tropical cyclones: 1) hydrometeor size sorting within the eyewall convection, 2) vertical displacement of the melting layer within the inner core, and 3) dendritic growth layers within stratiform regions of the inner core. Size sorting signatures within eyewall convection are observed with greater frequency and prominence in more intense hurricanes, and are observed predominantly within the deep-layer environmental wind shear vector-relative quadrants that harbor the greatest frequency of deep convection (i.e., downshear and left-of-shear). Melting-layer displacements are shown that exceed 1 km in altitude compared to melting-layer altitudes in outer rainbands and are complemented by analyses of archived dropsonde data. Dendritic growth and attendant snow aggregation signatures in the inner core are found to occur more often when echo-top altitudes are low (≤10 km MSL), nearer the -15°C isotherm commonly associated with dendritic growth. These signatures, uniquely observed by polarimetric radar, provide greater insight into the physical structure and thermodynamic characteristics of tropical cyclones, which are important for improving rainfall estimation and the representation of tropical cyclones in numerical models.

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

Bridging Land-Surface Fluxes and Aerosol Concentrations to Triggering Convective Rainfall

During the period August 24-28, 2016, a delayed component the GO-Amazon Project, we launched nine altitude-controlled free balloons (CMET). Smaller than typical rawinsondes, CMET are equipped with altitude control, global communication via Iridium satellite, and aspirated sensors. The aims of our effort were to examine the interactions among convective boundary layer and dual river breeze circulations near the confluence of the Tapajos and Amazon Rivers in the eastern Basin. The week-long field campaign was timed to examine the reestablishment of the breeze circulations shortly after the passage of a strong instability line on August 22. Nine CMET were launched at the Curua-Una hydroelectric dam (2.8S; 54.3W), timed to encounter the Tapajos river breeze front by late afternoon. Soundings were made to establish the thickness of interface between the easterly trade and westerly Tapajos breeze circulation. Careful use of sounding strategies allowed these free balloons to track along the northerly channeled flow in the lowest 300 m above the River. Following the river encounter, balloons tracked to the west, sounding to describe the diurnal course of boundary layer in the forest west of the Tapajos River. The longest flight traveled more than 770 km over three days and twice rested overnight in the rain forest canopy. Ancillary data from surface climate and flux stations as well as the Santarem radiosonde, satellite images will be used to illustrate how the breeze circulations are seen near the surface and how they were disrupted by larger-scale events. Comparisons with HYSPLIT trajectories illustrate how sensitive real trajectories are to the refraction that the encounter with the breeze effects. A second effort was intensive analyses of data from the eddy flux tower at the Tapajós National Forest near Santarém Pará Brazil, with special emphasis on the role of clouds and canopy presence on light absorbance and photosynthetic activity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Chemical properties and single-particle mixing state of soot aerosol in Houston during the TRACER campaign

Abstract. A high-resolution soot particle aerosol mass spectrometer (SP-AMS) was used to selectively measure refractory black carbon (rBC) and its associated coating material using both the ensemble size-resolved mass spectral mode and the event trigger single particle (ETSP) mode in Houston, Texas, in summer 2022. This study was conducted as part of the Department of Energy Atmospheric Radiation Measurement (ARM) program's TRacking Aerosol Convection interactions ExpeRiment (TRACER) field campaign. The study revealed an average (±1σ) rBC concentration of 103 ± 176 ng m−3. Additionally, the coatings on the BC particles were primarily composed of organics (59 %; 219 ± 260 ng m−3) and sulfate (26 %; 94 ± 55 ng m−3). Positive matrix factorization (PMF) analysis of the ensemble mass spectra of BC-containing particles resolved four distinct types of soot aerosol, including an oxidized organic aerosol (OOABC,PMF) factor associated with processed primary organic aerosol, an inorganic sulfate factor (SO4,BC,PMF), an oxidized rBC factor (O-BCPMF), and a mixed mineral dust–biomass burning aerosol factor with significant contribution from potassium (K-BBBC,PMF). Additionally, K-means clustering analysis of the single-particle mass spectra identified eight different clusters, including soot particles enriched in hydrocarbon-like organic aerosol (HOABC,ETSP), sulfate (SO4,BC,ETSP), two types of rBC, OOA (OOABC,ETSP), chloride (ClBC,ETSP), and nitrate (NO3,BC,ETSP). The single-particle measurements demonstrate substantial variation in BC coating thickness with coating-to-rBC mass ratios ranging from 0.1 to 100. The mixing state index (χ), which denotes the degree of homogeneity of the soot aerosol, varied from 4 % to 94 % with a median of 40 %, indicating that the aerosol population lies in between internal and external mixing but has large temporal and source type variability. In addition, a significant fraction of BC-containing particles, a majority enriched with oxidized organics and sulfate, exhibit sufficiently high κ values and diameters conducive to activation as cloud nuclei under atmospherically relevant supersaturation conditions. This finding bears significance in comprehending the aging processes of rBC-containing particles and their activation into cloud droplets. Our analysis highlights the complex nature of soot aerosol and underscores the need to comprehend its variability across different environments for accurate assessment of climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

How much information on precipitation is contained in satellite infrared imagery?

Satellite infrared (IR) brightness temperature providing information on the characteristics of cloud tops is one of the primary input data used for estimating precipitation from satellites. Thus, the natural questions to ask are: Does IR imagery contain more information about precipitation in some regions more than others? What are the factors that lead to such differences? Should we expect the amount of information provided by IR imagery to change with respect to temporal or spatial aggregation? Comprehensive analysis of the accuracy of satellite-based precipitation estimates obtained from any given algorithm may provide qualitative answers to the above questions. However, such an approach only offers conclusions within the limited context of the algorithm used to obtain precipitation estimates; that is, patterns caused by the inherent information content of IR imagery are inextricable from those induced by assumptions embedded in the precipitation estimation algorithm. Here, we address the abovementioned questions from a different perspective using an information-theoretic measure, free of structural assumptions and general to a wide range of relationships, to characterize the average and seasonal dependence between IR imagery provided by satellite sensors in the spectral range (10.7–11.5 μm) and precipitation rates in the contiguous United States (CONUS) across distinct temporal and spatial scales. We analyze a total of more than 1.3 billion pairs of IR and precipitation observations over CONUS, and we observe interesting patterns. First, we show that there is a strong inverse relationship (ρ = - 0.73) between the information content of IR data and the number of no-rain observations; however, its robustness varies regionally and seasonally with less significant correlation during the warm season. Second, we demonstrate that the intuitive relationship of increasing dependence between IR and precipitation as a result of temporal or spatial aggregation exhibits a diminishing returns behavior. For instance, temporal aggregation from 1 to 3 h increases the dependence approximately 7 times as much as temporal aggregation from 12 to 24 h. Furthermore, we quantitatively examine and re-confirm several statements previously reported in the literature such as the strong association between IR and precipitation in convective storms and the low association in orographic rainfall. Finally, we conclude by illustrating the potential of the analysis in diagnosis of operational algorithms for estimating precipitation from IR brightness temperature. The findings of this study pinpoint spatial domains and time scales at which IR is not an adequate proxy for estimating precipitation. Thus, they can potentially guide the development of operational algorithms that utilize satellite Infrared imagery for estimating, downscaling and data fusion of precipitation. Finally, the analysis presented here opens up the possibility of developing new methodologies for diagnosis of satellite-based precipitation estimation algorithms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗