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DOE OSTI2024

The Thunderstorms With the Greatest Lightning Densities on Earth

The most intense thunderstorms on Earth were surveyed using the comprehensive meteorological instrumentation on the Tropical Rainfall Measuring Mission (TRMM) satellite. Expansive land-based Mesoscale Convective Systems (MCSs) were consistently identified among the Earth's most intense thunderstorms, with their organization into many convective cells spanning a large areal extent permitting exceptional overall flash rates for these storms. In this study, we identify a new class of extreme thunderstorm. Lightning-dense thunderstorms are relatively compact convective storms whose concentrated lightning activity hinders our ability to accurately measure their flash rates. The top storms have a flash rate of one flash spanning many seconds, as there is insufficient separation to distinguish one flash from another. While any particularly active convective cell could be capable of producing high lightning densities, we find that thunderstorms with the greatest lightning densities on Earth are found in maritime thunderstorms that have not been appreciated in prior work due to the inaccurate flash rate measurements. These storms that are mostly found throughout the Gulf of Mexico and east of South Africa (among other coastal and oceanic regions) have measured TRMM proxies for convective intensity that rival the top MCS thunderstorms, but their horizontal and vertical dimensions are small by comparison. Thus, the necessary microphysical elements for electrification processes are more highly concentrated, enabling the observed extreme lightning densities.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

The Thunderstorms With the Greatest Lightning Densities on Earth

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Convectively coupled Rossby–Gravity waves in a field campaign: How they are captured in reanalysis products

Abstract Convectively coupled equatorial waves are a significant source of atmospheric variability in the tropics. Current numerical models continue to struggle in simulating the coupled diabatic heating fields that are responsible for the development and maintenance of these waves. This study investigates how the diabatic fields associated with Mixed Rossby–Gravity waves (MRGs) are represented in four reanalysis products by using a unique observational dataset from the TRMM‐KWAJEX (Tropical Rainfall Measuring Mission‐Kwajalein Experiment) field campaign. These reanalyses include ERA5, Japanese 55‐year Reanalysis (JRA‐55), Climate Forecast System Reanalysis (CFSR), and Modern‐Era Retrospective Analysis for Research and Applications (MERRA). We found that all four reanalyses captured the MRG structures in winds and temperature, and to a lesser degree in the humidity field except in the boundary layer. However, only the ERA5 and MERRA reanalyses captured the gradual rise and succession of the diabatic heating from boundary layer turbulence, shallow convection, cumulus congestus, and deep convection within the waves. ERA5 is the only product that also captured the gradual rise of the subgrid‐scale vertical transport of moist static energy. All reanalysis products underestimated the diabatic heating from cumulus congestus. Results provide observational basis on what aspects of MRG can be trusted and what cannot in the reanalysis products.

Wang, Xiaocong↗

DOE OSTI2023

A biomass map of the Brazilian Amazon from multisource remote sensing

The Amazon Forest, the largest contiguous tropical forest in the world, stores a significant fraction of the carbon on land. Changes in climate and land use affect total carbon stocks, making it critical to continuously update and revise the best estimates for the region, particularly considering changes in forest dynamics. Forest inventory data cover only a tiny fraction of the Amazon region, and the coverage is not sufficient to ensure reliable data interpolation and validation. This paper presents a new forest above-ground biomass map for the Brazilian Amazon and the associated uncertainty both with a resolution of 250 meters and baseline for the satellite dataset the year of 2016 (i.e., the year of the satellite observation). A significant increase in data availability from forest inventories and remote sensing has enabled progress towards high-resolution biomass estimates. This work uses the largest airborne LiDAR database ever collected in the Amazon, mapping 360,000 km 2 through transects distributed in all vegetation categories in the region. The map uses airborne laser scanning (ALS) data calibrated by field forest inventories that are extrapolated to the region using a machine learning approach with inputs from Synthetic Aperture Radar (PALSAR), vegetation indices obtained from the Moderate-Resolution Imaging Spectroradiometer (MODIS) satellite, and precipitation information from the Tropical Rainfall Measuring Mission (TRMM). A total of 174 field inventories geolocated using a Differential Global Positioning System (DGPS) were used to validate the biomass estimations. The experimental design allowed for a comprehensive representation of several vegetation types, producing an above-ground biomass map varying from a maximum value of 518 Mg ha -1 , a mean of 174 Mg ha -1 , and a standard deviation of 102 Mg ha -1 . This unique dataset enabled a better representation of the regional distribution of the forest biomass and structure, providing further studies and critical information for decision-making concerning forest conservation, planning, carbon emissions estimate, and mechanisms for supporting carbon emissions reductions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Coupled model intercomparison project phase 6 (CMIP6) high resolution model intercomparison project (HighResMIP) bias in extreme rainfall drives underestimation of amazonian precipitation

Abstract Extreme rainfall events drive the amount and spatial distribution of rainfall in the Amazon and are a key driver of forest dynamics across the basin. This study investigates how the 3-hourly predictions in the High Resolution Model Intercomparison Project (HighResMIP, a component of the recent Coupled Model Intercomparison Project, CMIP6) represent extreme rainfall events at annual, seasonal, and sub-daily time scales. TRMM 3B42 (Tropical Rainfall Measuring Mission) 3 h data were used as observations. Our results showed that eleven out of seventeen HighResMIP models showed the observed association between rainfall and number of extreme events at the annual and seasonal scales. Two models captured the spatial pattern of number of extreme events at the seasonal and annual scales better (higher correlation) than the other models. None of the models captured the sub-daily timing of extreme rainfall, though some reproduced daily totals. Our results suggest that higher model resolution is a crucial factor for capturing extreme rainfall events in the Amazon, but it might not be the sole factor. Improving the representation of Amazon extreme rainfall events in HighResMIP models can help reduce model rainfall biases and uncertainties and enable more reliable assessments of the water cycle and forest dynamics in the Amazon.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Influence of covariance of aerosol and meteorology on co-located precipitating and non-precipitating clouds over the Indo-Gangetic Plain

Aerosol–cloud–precipitation interaction (ACPI) plays a pivotal role in the global and regional water cycle and the earth's energy budget; however, it remains highly uncertain due to the different underlying physical mechanisms. Therefore, this study aims to systematically analyze the effects of aerosols and meteorological factors on ACPI in the co-located precipitating clouds (PCs) and non-precipitating clouds (NPCs) in winter and summer seasons by employing the long-term (2001–2021) retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Tropical Rainfall Measuring Mission (TRMM) coupled with the National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis-II datasets over the Indo-Gangetic Plain (IGP). The results exhibit a decadal increase in aerosol optical depth (AOD) over Lahore (5.2 %), Delhi (9 %), Kanpur (10.7 %), and Gandhi College (22.7 %) and a decrease over Karachi (-1.9 %) and Jaipur (-0.5 %). The most stable meteorology with high values of lower-tropospheric stability (LTS) is found in both seasons over Karachi. In the summer season, the occurrence frequency of clouds is high (74 %) over Gandhi College, 60 % of which are PCs. Conversely, the lowest number of PCs is found over Karachi. Similarly, in the winter season, the frequency of cloud occurrence is low over Karachi and high over Lahore and Gandhi College. The analysis of cloud top pressure (CTP) and cloud optical thickness (COT) indicates high values of cloud fraction (CF) for thick and high-level clouds over all study areas except Karachi. The microphysical properties such as cloud effective radius (CER) and cloud droplet number concentration (CDNC) bear high values (CER ≳ 15 µm and CDNC ≳ 50 cm -3 ) for both NPCs and PCs in summer. The AOD–CER correlation is good (weak) for PCs (NPCs) in winter. Similarly, the sensitivity value of the first indirect effect (FIE) is high (ranging from 0.2 ± 0.13 to 0.3 ± 0.01 in winter and from 0.19 ± 0.03 to 0.32 ± 0.05 in summer) for PCs and low for NPCs. The sensitivity value for the second indirect effect (SIE) is relatively higher (such as 0.6 ± 0.14 in winter and 0.4 ± 0.04 in summer) than FIE. Sensitivity values of the aerosol-cloud interaction (ACI) are low (i.e., -0.06 ± 0.09) for PCs in summer. Furthermore, the precipitation rate (PR) exhibits high values in the summer season, primarily due to the significant contribution from optically thick clouds with lower CDNC (≲ 50 cm -3 ) and larger CER and the intermediate contribution from optically thick clouds with higher CDNC ( ≳ 50 cm -3 ).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Interactions Between Lightning and Ship Traffic

It is important to understand connections between society and the natural environment for anticipating hazards and anthropogenic effects on the Earth system. In this study, we conduct a detailed exploration of interactions between oceanic thunderstorms and maritime traffic. Shipping traffic produces aerosols that perturb the otherwise “clean” ocean environment. Prior work proposed these aerosol effects as the cause of increased lightning over certain shipping lanes. However, introducing tall grounded objects into a high electric field environment might also facilitate lightning discharges, as we see with upward lightning over land. We consider both possibilities. Our analyses of the thunderstorms responsible for enhanced lightning activity over the shipping lane with the clearest anthropogenic signal indicate that the enhancement results from an increased frequency of lightning-producing storms. Observed variations in thunderstorm microphysics between the shipping lane and nearby oceans are small compared to natural factors such as the Indian monsoon, and are on the same scale as the local variability in the data. By contrast, matching lightning stroke data with ship transponder events in oceanic regions where public data are available reveals a strong signal from direct ship interactions. Lightning is 15× (66×) more likely to occur at a ship location compared to 2 km (25 km) away. These results highlight the central role of direct ship interactions in explaining lightning enhancements over shipping lanes. We also document the frequency of these direct lightning interactions across various categories of vessels and on individual ships present in the public data.

54 ENVIRONMENTAL SCIENCES↗