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Tian, Jingjing

Publications and source records attributed to Tian, Jingjing.

17 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Improving the Confidence in Retrievals of Vertical Distributions of Cloud Condensation Nuclei Number Concentration from ARM Supported by Aircraft In Situ Observations

Accurate quantification of the vertical distribution of cloud condensation nuclei (CCN) number concentrations is critical for improving our understanding of aerosol–cloud interactions. Ground-based Raman lidars operated by the Atmospheric Radiation Measurement (ARM) program, together with surface CCN measurements, are used to retrieve vertically resolved CCN number concentrations (Retrieved Number concentration of CCN, RNCCN). These retrievals rely on several assumptions, including that aerosol composition is vertically homogeneous. To assess this assumption, we developed and tested a framework to infer the dominant aerosol classes/types at different altitudes. This was done by applying a k-Nearest-Neighbors (kNN) algorithm to lidar ratio and linear depolarization ratio measurements from Raman lidar. We evaluated the framework using aircraft aerosol and CCN measurements from the ARM Holistic Interactions of Shallow Clouds, Aerosols, and Land Ecosystems (HI-SCALE) field campaign. The results show that RNCCN performance degrades as vertical aerosol complexity increases, i.e., RNCCN agrees with the aircraft CCN in vertically homogeneous conditions, but closure decreases in layered aerosol structures. To generalize beyond individual examples, we introduce a metric (heterogeneity index) that quantifies the vertical complexity by assessing the variation of inferred aerosol classes/types. Case-level statistics show a tendency for RNCCN and aircraft differences to increase with this metric. By detecting retrievals that are likely compromised by aerosol vertical heterogeneity, the proposed framework improves the interpretability and effective use of RNCCN used for long-term evaluation of models and aerosol–cloud interactions.

Tian, Jingjing↗
DOE OSTI2024

ARM FY2025 Radar Plan

The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility is dedicated to delivering high-quality radar data that significantly advance our understanding of cloud and precipitation processes, improving climate models. With radars operating across diverse frequencies, scanning modes, and global climate conditions, extensive staffing is essential for effective management. Due to current staffing constraints, achieving the expected level of operational excellence requires a more strategic approach. To address this challenge, ARM has developed an operational radar plan for the upcoming Fiscal Year 2025 (FY25) based on budget and staffing considerations. This report summarizes the Fiscal Year 2024 (FY24) ARM radar-related activities and outlines the strategic plan for FY25. It presents a comprehensive radar plan that includes detailed activities, priorities, and a projected timeline aligned with the ARM radar roadmap. Key tasks, detailed in Table 1, cover various radar operational stages and coordinated efforts among ARM teams.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

How Well Does the DOE Global Storm Resolving Model Simulate Clouds and Precipitation Over the Amazon?

This study assesses a 40-day 3.25-km global simulation of the Simple Cloud-Resolving E3SM Model (SCREAMv0) using high-resolution ground-based observations from the Atmospheric Radiation Measurement (ARM) Green Ocean Amazon (GoAmazon) field campaign. SCREAMv0 reasonably captures the diurnal timing of boundary layer clouds yet underestimates the boundary layer cloud fraction and mid-level congestus. SCREAMv0 well replicates the precipitation diurnal cycle, however it exhibits biases in the precipitation cluster size distribution compared to scanning radar observations. Specifically, SCREAMv0 overproduces clusters smaller than 128 km, and does not form enough large clusters. Such biases suggest an inhibition of convective upscale growth, preventing isolated deep convective clusters from evolving into larger mesoscale systems. This model bias is partially attributed to the misrepresentation of land-atmosphere coupling. This study highlights the potential use of high-resolution ground-based observations to diagnose convective processes in global storm resolving model simulations, identify key model deficiencies, and guide future process-oriented model sensitivity tests and detailed analyses.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

How Does Land Cover and Its Heterogeneity Length Scales Affect the Formation of Summertime Shallow Cumulus Clouds in Observations From the US Southern Great Plains?

This study investigates the effects of heterogeneous land covers on shallow cumulus (ShCu) clouds at the US Southern Great Plains using high-resolution satellite and land cover data. During late summer, ShCu occurs over cities the most frequently and over open waters the least frequently, and more often over forest than over grassland. The preferential occurrence of ShCu over forest relative to grassland is consistent with surface measurements showing larger heat fluxes over forests. This preferential occurrence also varies with the length scales of land patches with the largest cloud occurrence difference shifting from smaller length scales (<9 km) during midday to larger scales (>9 km) in the early afternoon. Consistent with theory, these signals are more pronounced under low wind conditions. The preferential length scale shift with time suggests the existence of secondary circulations that strengthen and promote convergence over larger spatial scales as the differential land surface heating intensifies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Summertime Continental Shallow Cumulus Cloud Detection Using GOES-16 Satellite and Ground-Based Stereo Cameras at the DOE ARM Southern Great Plains Site

Summertime continental shallow cumulus clouds (ShCu) are detected using Geostationary Operational Environmental Satellite (GOES)-16 reflectance data, with cross-validation by observations from ground-based stereo cameras at the Department of Energy Atmospheric Radiation Measurement Southern Great Plains site. A ShCu cloudy pixel is identified when the GOES reflectance exceeds the clear-sky surface reflectance by a reflectance detection threshold of ShCu, ΔR. We firstly construct diurnally varying clear-sky surface reflectance maps and then estimate the ΔR. A GOES simulator is designed, projecting the clouds reconstructed by stereo cameras towards the surface along the satellite’s slanted viewing direction. The dynamic ShCu detection threshold ΔR is determined by making the GOES cloud fraction (CF) equal to the CF from the GOES simulator. Although there are temporal variabilities in ΔR, cloud fractions and cloud size distributions can be well reproduced using a constant ΔR value of 0.045. The method presented in this study enables daytime ShCu detection, which is usually falsely reported as clear sky in the GOES-16 cloud mask data product. Using this method, a new ShCu dataset can be generated to bridge the observational gap in detecting ShCu, which may transition into deep precipitating clouds, and to facilitate further studies on ShCu development over heterogenous land surface.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Characteristics of Ice Cloud–Precipitation of Warm Season Mesoscale Convective Systems over the Great Plains

Abstract In this study, the mesoscale convective systems (MCSs) are tracked using high-resolution radar and satellite observations over the U.S. Great Plains during April–August from 2010 to 2012. The spatiotemporal variability of MCS precipitation is then characterized using the Stage IV product. We found that the spatial variability and nocturnal peaks of MCS precipitation are primarily driven by the MCS occurrence rather than the precipitation intensity. The tracked MCSs are further classified into convective core (CC), stratiform rain (SR), and anvil clouds regions. The spatial variability and diurnal cycle of precipitation in the SR regions of MCSs are not as significant as those of MCS precipitation. In the SR regions, the high-resolution, long-term ice cloud microphysical properties [ice water content (IWC) and ice water paths (IWPs)] are provided. The IWCs generally decrease with height. Spatially, the IWC, IWP, and precipitation are all higher over the southern Great Plains than over the northern Great Plains. Seasonally, those ice and precipitation properties are all higher in summer than in spring. Comparing the peak timings of MCS precipitation and IWPs from the diurnal cycles and their composite evolutions, it is found that when using the peak timing of IWPSR as a reference, the heaviest precipitation in the MCS convective core occurs earlier, while the strongest SR precipitation occurs later. The shift of peak timings could be explained by the stratiform precipitation formation process. The IWP and precipitation relationships are different at MCS genesis, mature, and decay stages. The relationships and the transition processes from ice particles to precipitation also depend on the low-level humidity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Prediction of Tropical Cyclone Intensity Change using Advance Machine Learning Techniques

A tropical cyclone (TC) is a rapidly rotating storm system characterized by a lowpressure center, a closed low-level atmospheric circulation, strong winds, and a spiral arrangement of thunderstorms that produce heavy rain or squalls. TC occurs when the sea temperatures are high, and the air above the warm ocean is heated and rises quickly, causing an area of very low pressure, and then drawing more warm moist air, leading to strong winds. The air cools and condenses when rising, so that cumulonimbus clouds formed and produce heavy rainfall. These high winds, excessive rainfall and flooding threaten lives and property.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Estimation of liquid water path below the melting layer in stratiform precipitation systems using radar measurements during MC3E

In this study, the liquid water path (LWP) below the melting layer in stratiform precipitation systems is retrieved, which is a combination of rain liquid water path (RLWP) and cloud liquid water path (CLWP). The retrieval algorithm uses measurements from the vertically pointing radars (VPRs) at 35 and 3 GHz operated by the US Department of Energy Atmospheric Radiation Measurement (ARM) and National Oceanic and Atmospheric Administration (NOAA) during the field campaign Midlatitude Continental Convective Clouds Experiment (MC3E). The measured radar reflectivity and mean Doppler velocity from both VPRs and spectrum width from the 35 GHz radar are utilized. With the aid of the cloud base detected by a ceilometer, the LWP in the liquid layer is retrieved under two different situations: (I) no cloud exists below the melting base, and (II) cloud exists below the melting base. In (I), LWP is primarily contributed from raindrops only, i.e., RLWP, which is estimated by analyzing the Doppler velocity differences between two VPRs. In (II), cloud particles and raindrops coexist below the melting base. The CLWP is estimated using a modified attenuation-based algorithm. Two stratiform precipitation cases (20 and 11 May 2011) during MC3E are illustrated for two situations, respectively. With a total of 13 h of samples during MC3E, statistical results show that the occurrence of cloud particles below the melting base is low (9 %); however, the mean CLWP value can be up to 0.56 kg m -2 , which is much larger than the RLWP (0.10 kg m -2 ). When only raindrops exist below the melting base, the average RLWP value is larger (0.32 kg m -2 ) than the with-cloud situation. The overall mean LWP below the melting base is 0.34 kg m -2 for stratiform systems during MC3E.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Understanding ice cloud-precipitation properties of three modes of mesoscale convective systems during PECAN

This study analyzes the precipitation and ice cloud microphysical features of three common modes of linear mesoscale convective systems (MCSs) during the Plains Elevated Convection at Night (PECAN) campaign. Three cases, one for each linear MCS archetype (trailing stratiform (TS), leading stratiform (LS), and parallel stratiform (PS) precipitation), are selected. We focus primarily on analyzing ice cloud microphysical properties and precipitation rates over the classified convective core (CC) and stratiform rain (SR) regions, as well as the two stratiform regions that developed behind (SR1) and ahead (SR2) of the convective line relative to the storm motion. In the three selected cases, the ice water path (IWP) and precipitation rate (PR) have strong correlations in the CC, but not in the SR. In terms of the temporal evolution of the mean IWPs and PRs, both CC and SR IWPs, as well as CC PRs, reach peaks quickly, but take a longer time to dissipate than the increase period. For all three cases, both SR1 and SR2 IWPs are 20-70% of their corresponding CC values in both the LS and PS cases, and up to 95% for the TS case, while all of their PRs are only 7-25% of their CC values. These values suggest that the SR PRs may not only depend on IWPs, but also that the microphysical properties of ice particles such as habit and size distribution may play an important role. Utilizing cloud resolving simulations of these systems may provide better understanding of the physical meanings behind the results in the future.

Cui, Wenjun↗
DOE OSTI2018

AIM2 accelerates the atherosclerotic plaque progressions in ApoE−/− mice

Highlights: • Our study demonstrated that AIM2 plays an important role in atherosclerosis. • We found that AIM2 could mediate GSDMD-N and pyroptosis in VSMCs for the first time. • We first found that AIM2 could affect ICAM-1 and macrophage recruitment in atherosclerosis. • We first found that ox-LDL can promote AIM2 expression through NF-κB signaling. Plaque formation is initiated and triggered by cell death in the vascular wall, which gradually leads to the progression of atherosclerosis. Pyroptosis is a newly discovered form of programmed cell death. Absent in melanoma 2 (AIM2), a member of the HIN-200 protein family, plays an important role in activating inflammasomes. However, the role and mechanism of AIM2 in atherosclerotic plaque progression has not been thoroughly elucidated to date. The effect of pyroptosis and the mechanism for this effect were investigated in apolipoprotein E-deficient (ApoE−/−) mice. AIM2 overexpression and inhibition were studied in ApoE−/− mice that were fed a high-fat diet. The specific role of AIM2 in vascular smooth muscle cells (VSMCs) was explored in vitro. The results showed that high fat diet increases the expression of AIM2, ICMA-1, GSDMD-N, which could be mediated by AIM2 expression. The plaque lesion area is lager with AIM2 overexpression. Moreover, TUNEL-positive cells were increased when AIM2 was overexpressed. With increased AIM2, macrophages were enhanced. In vitro studies showed that AIM2 and GSDMD-N expression correlated with ox-LDL levels in a concentration dependent manner. AIM2 expression is associated with NF-κB signaling activity and can be inhibited by NF-κB inhibitor. AIM2 mediated GSDMD activity through ASC, caspase1 pathway. EthD-III and TUNEL staining showed that AIM2 mediates pyroptosis in VSMCs. Our study suggests that AIM2 is not only a regular of inflammasome but also an active participant in atherosclerosis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

AIM2 regulates vascular smooth muscle cell migration in atherosclerosis

Highlights: • Our study demonstrated that AIM2 is involved in the progression of atherosclerosis in ApoE−/− mice for the first time. • We first found AIM2 could affect VSMCs migration and MMP2 expression. • We first found that AIM2 could active the TGF-β/SMAD signaling in VSMCs. Atherosclerosis (AS) is a common pathological basis of various cardiovascular and cerebrovascular diseases. Plaque formation is initiated and triggered by vascular smooth musclecells (VSMCs) migration in vascular wall, which gradually aggravates atherosclerosis progression. Absent in melanoma 2 (AIM2), a member of HIN-200 family, plays an important role in activating inflammasome. However, the role of AIM2 in atherosclerotic plaque progression outside of the inflammasome has not yet been reported.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Comparisons of Ice Water Path in Deep Convective Systems Among Ground-Based, GOES, and CERES-MODIS Retrievals

Retrievals of convective cloud microphysical properties based on passive satellite imagery are difficult. To help quantify their uncertainties, ice water paths (IWPs) retrieved from the NASA Clouds and the Earth's Radiant Energy System project using Geostationary Operational Environmental Satellite (GOES) and Terra/Aqua MODerate-resolution Imaging Spectroradiometer observations are compared with IWPs retrieved from Next-Generation Radar (NEXRAD) observations over a large domain (32°N to 40°N and 105°W to 91°W) during the 2011 Midlatitude Continental Convective Clouds Experiment field campaign. Based on comparisons of pixel-level (4 km × 4 km) daytime IWP retrievals from NEXRAD and GOES, it is found that NEXRAD- and GOES-retrieved mean IWPs are 2.03 and 1.83 kg m -2 , respectively, for ice-phase cloud in thick anvil area. Their mean difference of 0.20 kg m -2 (with 95% confidence interval: 0.14-0.26 kg m -2 ) is within the uncertainty of NEXRAD retrievals. However, the low correlation between pixel-to-pixel comparisons indicates a large variation in GOES-retrieved IWP. For mixed-phase clouds in thick anvil areas, in addition to IWPs, total water paths (TWPs, sum of ice and liquid water path) are estimated with aid of aircraft measurements for NEXRAD retrievals and corrected using a TWP parameterization for GOES retrievals. The mean values of estimated TWPs from NEXRAD (corrected using aircraft in situ measurements) and GOES are similar. GOES and Clouds and the Earth's Radiant Energy System-MODerate-resolution Imaging Spectroradiometer-retrieved IWPs/TWPs generally do not exceed 5 kg m - 2. Large differences and low correlations exist between satellite and NEXRAD retrievals in stratiform rain areas. Possible reasons for the differences between retrievals are discussed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Retrievals of ice cloud microphysical properties of deep convective systems using radar measurements: Convective Cloud Microphysical Retrieval

This study presents new algorithms for retrieving ice cloud microphysical properties (ice water content (IWC) and median mass diameter (Dm)) for the stratiform and thick anvil regions of Deep Convective Systems (DCSs) using Next-Generation Radar (NEXRAD) reflectivity and recently developed empirical relationships from aircraft in situ measurements during the Midlatitude Continental Convective Clouds Experiment (MC3E). A classic DCS case on 20 May 2011 is used to compare the retrieved IWC profiles with other retrieval and cloud-resolving model simulations. The mean values of each retrieved and simulated IWC fall within one standard derivation of the other two. The statistical results from six selected cases during MC3E show that the aircraft in situ derived IWC and Dm are 0.47 ± 0.29 g m-3 and 2.02 ± 1.3 mm, while the mean values of retrievals have a positive bias of 0.16 g m-3 (34%) and a negative bias of 0.39 mm (19%). To validate the newly developed retrieval algorithms from this study, IWC and Dm are performed with other DCS cases during Bow Echo and Mesoscale Convective Vortex Experiment (BAMEX) field campaign using composite gridded NEXRAD reflectivity and compared with in situ IWC and Dm from aircraft. A total of 64 1-min collocated aircraft and radar samples are available for comparisons, and the averages of radar retrieved and aircraft in situ measured IWCs are 1.22 g m-3 and 1.26 g m-3 with a correlation of 0.5, and their averaged Dm values are 2.15 and 1.80 mm. These comparisons have shown that the retrieval algorithms 45 developed during MC3E can retrieve similar ice cloud microphysical properties of DCS to aircraft in situ measurements during BAMEX with median errors of ~40% and ~25% for IWC and Dm retrievals, respectively. This is indicating our retrieval algorithms are suitable for other midlatitude continental DCS ice clouds, especially at stratiform rain and thick anvil regions. In addition, based on the averaged IWC and Dm values during MC3E and BAMEX, the DCS IWC values over midlatitude are significantly different, while their Dm values are close to each other. On the other hand, these DCS IWC and Dm values are 1-2 orders of magnitude larger than those of single-layered cirrus clouds over midlatitudes.

Tian, Jingjing↗
DOE OSTI2015

hsrlcfad

The ARM lidar simulator is developed to facilitate direct comparison of climate model output with the ARM ground-based lidar measurements. The ARM user facility provides lidar SR-height joint histograms (CFADs) to compare with outputs from lidar simulators (e.g., EMC2 and COSP2.0). The CFADs were generated from the lidar measurements (hsrlM1.a1). The dataset contains vertical calculated profiles of lidar scattering ratio (SR) and SR-height joint histograms.

54 ENVIRONMENTAL SCIENCES↗