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At least 1,207 records · Page 67
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

A WRF-Chem Analysis of Flash Rates, Lightning-NOx Production and Subsequent Trace Gas Chemistry of the 29-30 May 2012 Convective Event in Oklahoma During DC3

The Deep Convective Clouds and Chemistry (DC3) field campaign in 2012 provided a plethora of aircraft and ground-based observations (e.g., trace gases, lightning and radar) to study deep convective storms, their convective transport of trace gases, and associated lightning occurrence and production of nitrogen oxides (NOx). This is a continuation of previous work, which compared lightning observations (Oklahoma Lightning Mapping Array and National Lightning Detection Network) with flashes generated by various flash rate parameterization schemes (FRPSs) from the literature in a Weather Research and Forecasting Chemistry (WRF-Chem) model simulation of the 29-30 May 2012 Oklahoma thunderstorm. Based on the Oklahoma radar observations and Lightning Mapping Array data, new FRPSs are being generated and incorporated into the model. The focus of this analysis is on estimating the amount of lightning-generated nitrogen oxides (LNOx) produced per flash in this storm through a series of model simulations using different production per flash assumptions and comparisons with DC3 aircraft anvil observations. The result of this analysis will be compared with previously studied mid-latitude storms. Additional model simulations are conducted to investigate the upper troposphere transport, distribution, and chemistry of the LNOx plume during the 24 hours following the convective event to investigate ozone production. These model-simulated mixing ratios are compared against the aircraft observations made on 30 May over the southern Appalachians.

Cummings, Kristin A.↗
NASA NTRS2019

Diurnal Cycle of ASCAT-Identified Cold Pools and Associated Convective Systems in the Maritime Continent and South China Sea

Mesoscale convective cold pools are known to alter the turbulent air-sea fluxes in the regions of active convection such as maritime tropics. Satellite-based Ocean Vector Wind instruments have proven to be useful in observing these mesoscale outflows corresponding to convective cold pools. A new storm-centric, tensor-based wind-gradient identification algorithm identifies gradients associated with convective cold pools and other boundaries such as land-sea breeze fronts. We term these as Gradient Features or GFs; analyzed over tropical oceans (2007-2018) using horizontal winds from Advanced Scatterometer (ASCAT-A).

Nesbitt, Stephen W.↗
NASA NTRS2019

Use of Polarimetric Radar Measurements to Constrain Simulated Convective Cell Evolution: A Pilot Study with Lagrangian Tracking

To probe the potential value of a radar-driven field campaign to constrain simulation of isolated convection subject to a strong aerosol perturbation, convective cells observed by the operational KHGX weather radar in the vicinity of Houston, Texas, are examined individually and statistically. Cells observed in a single case study of onshore flow conditions during July 2013 are first examined and compared with cells in a regional model simulation. Observed and simulated cells are objectively identified and tracked from observed or calculated positive specific differential phase (K(sub DP)) above the melting level, which is related to the presence of supercooled liquid water. Several observed and simulated cells are subjectively selected for further examination. Below the melting level, we compare sequential cross sections of retrieved and simulated raindrop size distribution parameters. Above the melting level, we examine time series of KDP and radar differential reflectivity (Z(sub DR)) statistics from observations and calculated from simulated supercooled rain properties, alongside simulated vertical wind and supercooled rain mixing ratio statistics. Results indicate that the operational weather radar measurements offer multiple constraints on the properties of simulated convective cells, with substantial value added from derived K(sub DP) and retrieved rain properties. The value of collocated three-dimensional lightning mapping array measurements, which are relatively rare in the continental US, supports the choice of Houston as a suitable location for future field studies to improve the simulation and understanding of convective updraft physics. However, rapid evolution of cells between routine volume scans motivates consideration of adaptive scan strategies or radar imaging technologies to amend operational weather radar capabilities. A 3-year climatology of isolated cell tracks, prepared using a more efficient algorithm, yields additional relevant information. Isolated cells are found within the KHGX domain on roughly 40 % of days year-round, with greatest concentration in the northwest quadrant, but roughly 5-fold more cells occur during June through September. During this enhanced occurrence period, the cells initiate following a strong diurnal cycle that peaks in the early afternoon, typically follow a south-to-north flow, and dissipate within 1 h, consistent with the case study examples. Statistics indicate that ∼ 150 isolated cells initiate and dissipate within 70 km of the KHGX radar during the enhanced occurrence period annually, and roughly 10 times as many within 200 km, suitable for multi-instrument Lagrangian observation strategies. In addition to ancillary meteorological and aerosol measurements, robust vertical wind speed retrievals would add substantial value to a radar-driven field campaign.

Fridlind, Ann M.↗
NASA NTRS2019

The Diurnal Cycle of Precipitation and Organized Convection in a Set of Global Mesoscale Simulations with the NASA GEOS AGCM

The NASA Global Modeling and Assimilation Office (GMAO) has conducted a series of 40-day nonhydrostatic global simulations with horizontal grid spacing ranging from 200 km to 3 km, as part of the DYAMOND model intercomparison project. The Goddard Earth Observing System (GEOS) model was run with the Grell-Freitas scale-aware convection scheme, which smoothly reduces parameterized deep convection with increasing resolution. Here we evaluate the diurnal cycle and other statistics of precipitation and organized convection as a function of resolution. For validation we use the 0.1 degree IMERG precipitation and 4 km Merged IR brightness temperature datasets, focusing on four regions: the continental United States, Amazonia, the equatorial Indian ocean, and the Maritime Continent. Early results indicate good phase agreement but excessive magnitude of the continental diurnal cycle of precipitation at coarser resolutions, with improved magnitude as resolution increases and the role of parameterization is reduced. Convective cloud clusters are identified with a brightness temperature threshold, and we find realistic numbers of the largest clusters (>10^4 km sq) at all resolutions, while the number of smaller clusters increases with resolution, approaching observations when dx=3 km. The observed diurnal cycle in the cluster size distribution is also reproduced, with realistic magnitude in the highest resolution runs. Precipitation characteristics across cluster sizes are also examined. The results show the potential for global mesoscale simulations as a community science resource, and we invite collaboration to explore these runs in greater detail.

Arnold, Nathan↗
NASA NTRS2020

Cascading toward a Kilometer‐scale GCM: Impacts of a Scale‐aware Convection Parameterization in the Goddard Earth Observing System GCM.

The NASA Goddard Earth Observing System global model is evaluated through a cascade of simulations with increasing horizontal resolution. This model employs a non-hydrostatic dynamical core and includes a scale-aware, deep convection parameterization (DPCP). 40-daysimulations at six resolutions (100km to 3km) with unvarying model formulation were produced. At the highest resolution, extreme experiments were carried out; one with no DPCP, and one with its scale-awareness eliminated. Simulated precipitation, radiative balance, and atmospheric thermodynamic and dynamical variables are well reproduced with respect to both observational and reanalysis data. As model resolution increases, the convective precipitation smoothly transitions from being mostly produced by the convection parameterization to the cloud microphysics parameterization. However, contrary to current thought, these extreme cases argue for maintaining, to some extent, the scale-aware deep convection parameterization even at 3kmscale, as the run relying solely on explicit grid-scale production of rainfall performs more poorly at this resolution.

Saulo Freitas↗
NASA NTRS2021

Land-Atmosphere Coupling at the U.S. Southern Great Plains: A Comparison on Local Convective Regimes Between ARM Observations, Reanalysis, and Climate Model Simulations

Using the 9-yr warm-season observations at the Atmospheric Radiation Measurement Southern Great Plains site, we assess the land-atmosphere (L-A) coupling in North American Regional Reanalysis (NARR) and two climate models: hindcasts with the Community Atmosphere Model version 5.1 by Cloud-Associated Parameterizations Testbed (CAM5-CAPT) and nudged runs with the Energy Exascale Earth System Model Atmosphere Model version 1 Regionally Refined Model (EAMv1-RRM). We focus on three local convective regimes and diagnose model behaviors using the Local Coupling metrics (Santanello et al. 2018). NARR agrees well with observations except a slightly warmer and drier surface with higher downwelling shortwave radiation and lower evaporative fraction. On clear-sky days, it shows warmer and drier early-morning conditions in both models with significant underestimates in surface evaporation by EAMv1-RRM. On the majority of the ARM-observed shallow cumulus days, there is no or little low-level clouds in either model. When captured in models, the simulated shallow cumulus shows much less cloud fraction and lower cloud bases than observed. On the days with late-afternoon deep convection, models tend to present a stable early-morning lower atmosphere more frequently than the observations, suggesting that the deep convection is triggered more often by elevated instabilities. Generally, CAM5-CAPT can reproduce the local L-A coupling processes to some extent due to the constrained early-morning conditions and large-scale winds. EAMv1-RRM exhibits large precipitation deficits and warm and dry biases towards mid-to-late summers, which may be an amplification through a positive L-A feedback among initial atmosphere and land states, convection triggering and large-scale circulations.

land-atmosphere↗
NASA NTRS2021

The GF Convection Parameterization: Recent Developments, Extensions, and Applications

Recent developments and options in the GF (Grell and Freitas, 2014, Freitas et al.,2018) convection parameterization are presented. The parameterization has been expanded to atrimodal spectral size to simulate three convection modes: shallow, congestus and deep. Incontrast to usual entrainment/detrainment assumptions, we assume that Beta Functions (BFs),commonly applied to represent Probability Density Functions (PDF’s), can be used tocharacterize the vertical mass flux profiles for the three modes, and use the BFs to deriveentrainment and detrainment rates. We also added a new closure for non-equilibrium convectionthat improved the simulation of the diurnal cycle of convection, with a better representation ofthe transition from shallow to deep convection regimes over land. The transport of chemicalconstituents (including wet deposition) can be treated inside the GF scheme. The tracer transportis handled in flux form and is mass conserving. Finally, the cloud microphysics has beenextended to include the ice phase to simulate the conversion from liquid water to ice in updraftswith resulting additional heat release and the melting from snow to rain.

Saulo R De Freitas↗
NASA NTRS2021

Assimilation of DAWN Doppler Wind Lidar Data During the 2017 Convective Processes Experiment (CPEX): Impact on Precipitation and Flow Structure

An improved representation of 3-D air motion and precipitation structure through forecast models and assimilation of observations is vital for improvements in weather forecasting capabilities. However, there are few independent data to properly validate a model forecast of precipitation structure when the underlying dynamics are evolving on short convective timescales. Using data from the JPL Ku/Ka-band Airborne Precipitation Radar (APR-2) and the 2 μmDoppler Aerosol Wind (DAWN) lidar collected during the2017 Convective Processes Experiment (CPEX), the NASA Unified Weather Research and Forecasting (WRF) Ensemble Data Assimilation System (EDAS) modeling system was used to quantify the impact of high-resolution sparsely sampled DAWN measurements on the analyzed variables and on the forecast when the DAWN winds were assimilated. Over-all, the assimilation of the DAWN wind profiles had a discernible impact on the wind field as well as the evolution and timing of the 3-D precipitation structure. Analysis of individual variables revealed that the assimilation of the DAWN winds resulted in important and coherent modifications of the environment. It led to an increase in the near-surface convergence, temperature, and water vapor, creating more favorable conditions for the development of convection exactly where it was observed (but not present in the control run). Comparison to APR-2 and observations by the Global Precipitation Measurement (GPM) satellite shows a much-improved forecast after the assimilation of the DAWN winds – development of precipitation where there was none, more organized precipitation where there was some, and a much more intense and organized cold pool, similar to the analysis of the dropsonde data. The onset of the vertical evolution of the precipitation showed similar radar-derived cloud-top heights, but delayed in time. While this investigation was limited to a single CPEX flight date, the investigation design is appropriate for further investigation of the impact of airborne Doppler wind lidar observations upon short-term convective precipitation forecasts

DAWN↗
NASA NTRS2022

Measurement report: Closure Analysis of Aerosol–cloud Composition in Tropical Maritime Warm Convection

Cloud droplet chemical composition is a key observable property that can aid understanding of how aerosols and clouds interact. As part of the Clouds, Aerosols and Monsoon Processes – Philippines Experiment (CAMP2Ex), three case studies were analyzed involving collocated airborne sampling of relevant clear and cloudy air masses associated with maritime warm convection. Two of the cases represented a polluted marine background, with signatures of transported East Asian regional pollution, aged over water for several days, while the third case comprised a major smoke transport event from Kalimantan fires. Sea salt was a dominant component of cloud droplet composition, in spite of fine particulate enhancement from regional anthropogenic sources. Furthermore, the proportion of sea salt was enhanced relative to sulfate in rainwater and may indicate both a propensity for sea salt to aid warm rain production and an increased collection efficiency of large sea salt particles by rain in subsaturated environments. Amongst cases, as precipitation became more significant, so too did the variability in the sea salt to (non-sea salt) sulfate ratio. Across cases, nitrate and ammonium were fractionally greater in cloud water than fine-mode aerosol particles; however, a strong covariability in cloud water nitrate and sea salt was suggestive of prior uptake of nitrate on large salt particles. A mass-based closure analysis of non-sea salt sulfate compared the cloud water air-equivalent mass concentration to the concentration of aerosol particles serving as cloud condensation nuclei for droplet activation. While sulfate found in cloud was generally constrained by the sub-cloud aerosol concentration, there was significant intra-cloud variability that was attributed to entrainment – causing evaporation of sulfate-containing droplets –and losses due to precipitation. In addition, precipitation tended to promote mesoscale variability in the sub-cloud aerosol through a combination of removal, convective downdrafts, and dynamically driven convergence. Physical mechanisms exerted such strong control over the cloud water compositional budget that it was not possible to isolate any signature of chemical production/loss using in-cloud observations. The cloud-free environment surrounding the non-precipitating smoke case indicated sulfate enhancement compared to convective mixing quantified by a stable gas tracer; however, this was not observed in the cloud water (either through use of ratios or the mass closure), perhaps implying that the warm convective cloud timescale was too short for chemical production to be a leading-order budgetary term and because precursors had already been predominantly exhausted. Closure of other species was truncated by incomplete characterization of coarse aerosol (e.g., it was found that only 10 %–50% of sea salt mass found in cloud was captured during clear-air sampling) and unmeasured gasphase abundances affecting closure of semi-volatile aerosol species (e.g., ammonium, nitrate and organic) and soluble volatile organic compound contributions to total organic carbon in cloud water.

Ewan Crosbie↗
NASA NTRS2023

Wind Profiling With the Airborne Doppler Aerosol Wind Lidar During the 2022 Convective Processes Experiment

The 2017 Decadal Survey for Earth Science and Applications from Space (ESAS 2017) identifies a critical need for improving our understanding of Planetary Boundary Layer (PBL) processes and air-surface fluxes as well as why clouds, convection, and heavy precipitation occur when and where they do. Lidars are uniquely capable of collecting high precision and high spatio-temporal observations that have been used for atmospheric process studies from the ground, aircraft, and space. The wind lidar team at the NASA Langley Research Center (LaRC) started the development of Doppler wind lidar more than a decade ago to demonstrate technologies required for an Earth-orbiting system to globally measure wind profiles. Since then, an airborne Doppler Aerosol WiNd (DAWN) lidar system has been developed and participated in a series of field campaigns. The Doppler Aerosol WiNd (DAWN) lidar uses atmospheric aerosol motion to derive vertical profiles of horizontal wind speed and direction beneath the aircraft. In September 2022, DAWN, along with a suite of other instruments, was flown on a NASA DC-8 as part of The Convective Processes EXperiment – Cabo Verde (CPEX-CV) field campaign. A main objective of CPEX was to obtain a comprehensive set of temperature, humidity and, particularly, wind observations over tropical waters in undisturbed conditions, Saharan dust outbreaks, and in the vicinity of scattered through organized deep convection in all phases of the convective life cycle. DAWN collected data for approximately 90 hours across 13 CPEX-CV science flights. Airborne Vertical Atmospheric Profiling System (AVAPS) dropsondes were dropped throughout the flight for profiling the atmosphere and validating the DAWN instrument. DAWN had co-located data with 347 AVAPS NRD41 dropsondes, providing 32,117 vertical levels for a comprehensive validation of DAWN wind retrievals. DAWN showed very good agreement with dropsondes of ~0.2 m/s bias and ~1.8 m/s RMS. Given this agreement, DAWN is considered to be a worthy reference dataset, and its retrievals have been compared to winds derived from GOES Atmospheric Motion Vectors (AMVs), Advanced Scatterometer winds (ASCAT), and model data from GFS, GEOS, and MERRA-2 to better understand the quality of our current models and satellite wind observations. The proposed presentation will provide a brief description of the DAWN instrument, discuss the synergistic observations collected across a wide range of atmospheric conditions sampled during the CPEX-CV flights, and a summary of comparisons between DAWN, GOES AMV, ASCAT, and model analyses/predictions, with an emphasis on the PBL.

DAWN↗
NASA NTRSDate not supplied

A Census of Severe Weather as Observed From Aqua: Visible/IR and Passive-Microwave Perspectives of Severe Convection

Severe weather phenomena represent the extreme upper end of the spectrum of convection and precipitation and tend to be highly localized and relatively rare compared to the rest of the distribution, but they can cause damage and loss disproportionate to their scale and frequency. Fortunately, severe convection exhibits distinct signatures in spaceborne remote-sensing datasets (e.g. overshooting cloud tops in visible/IR, or brightness temperature depressions in passive-microwave imagery). Leveraging these signatures individually has become a long-established practice to detect, analyze and establish climatologies of severe thunderstorms, especially in instances where traditional ground-based data may be unavailable. Spaceborne visible/IR and passive-microwave approaches are not without their pitfalls, however: passive-microwave channels have large footprints and exhibit non-uniform beam filling. Visible/IR instruments have fine horizontal resolution but are limited by their insensitivity to processes occurring below cloud top. To address this, we investigate the nearly simultaneous and colocated MODIS (visible/IR) and AMSR-E (passive-microwave) onboard the Aqua satellite to leverage both datasets together and assess the extent to which these datasets can be combined to improve severe thunderstorm detection. We pair AMSR-E and MODIS signatures of severe convection with ground-based weather radar, severe weather reports, and environmental parameters defined by the MERRA-2 reanalysis in six different geographical regimes throughout the Aqua domain. We present a census of potentially severe convective storms and their environments as seen by multiple instruments simultaneously, investigating how MODIS and AMSR-E signatures may be used together to diagnose storm properties and processes, and how the interrelationships between the signatures varies seasonally and geographically. Using statistical machine learning analysis, we aim to quantify the optimal MODIS and AMSR-E parameter sets for discriminating severe from non-severe storm cells and assess what improvement (if any) in detection results from combining the IR, visible, and microwave datasets.

Sarah Bang↗
NASA NTRSDate not supplied

Relating Lightning Flash Characteristics to Convective Structure in Tropical Cyclones

For decades, lightning has been used with some success as an indicator of tropical cyclone (TC) intensity change. An increase in inner-core lightning is usually associated with TC intensification, but this is not always the case. Significant lightning outbreaks have been observed in weakening storms, and hurricanes can rapidly intensify in the total absence of inner-core lightning. These conflicting results arise because lightning production depends on convective and microphysical characteristics that can arise during both intensification and weakening phases in TCs. Recent work using flash size and energy metrics provided by the Geostationary Lightning Mapper (GLM) aboard the GOES-R series of satellites shows some promise in distinguishing between lightning outbreaks that correspond to intensification and those that correspond to weakening. If a hurricane is rapidly intensifying in the presence of inner-core lightning, the size and optical energy of the flashes generally increases as intensification proceeds. It is hypothesized that this relationship is governed by changes in the TC-scale circulation that produce enhanced upper-level outflow and large, strongly helical convective updrafts in the inner core. These changes increase the quantity and spatial extent of charged upper-level ice, which allows large intracloud flashes to occur when electric field breakdown occurs. This presentation will present objective diagnostics of convective asymmetry using azimuthal wavenumber decomposition of GOES-R Advanced Baseline Imager brightness temperatures. The degree of symmetry will be related to GLM flash characteristics to better understand how changes in the symmetry of TC inner-core convection relates to flash rate, size, and energy. It will also show how the evolution of inner-core asymmetries relates to the spatial distribution and characteristics of lightning flashes in the inner core.

Patrick Duran↗
NASA NTRS2026

Ice in Convective Storm Environments: Assessing Impacts of Microphysics on Simulated Reflectivities

Satellite radar retrievals of clouds and precipitation rely on assumptions about the microphysical properties of hydrometeors such as particle size distributions (PSDs) and massdimensional relationships, which have been shown to vary in distinct environments. A deeper understanding of linkages between mass-dimensional relationships, ice crystal shape, and radar reflectivities across cloud and precipitation regimes is necessary for developing new retrievals for upcoming satellite radar missions, including the INvestigation of Convective UpdraftS (INCUS), as well as future missions that will feature space-borne radars observing clouds, convection, and precipitation. This study investigates ice microphysical characteristics through aircraft in-situ and remote sensing observations from two convective events during the Mid-latitude Continental Convective Clouds Experiment (MC3E) in the Southern Great Plains, and tests implications for ice particle habit in forward modeled radar observations. During MC3E, the Ka/Ku- band High Altitude Imaging Wind and Rain Airborne Profiler (HIWRAP) was onboard the NASA ER-2 aircraft, while in-situ measurements were taken onboard the University of North Dakota Citation. In-situ PSDs and particle shape information from optical array probe data are used to forward model radar reflectivities from particle scattering databases and are compared against HIWRAP reflectivities. Various particle combinations can be used to find agreement with HIWRAP observations, and the forward modeled reflectivities were sensitive to particle type. Varying the riming on the aggregate and graupel particles resulted in larger than 10 dB differences in reflectivities. The in-situ and radar observations imply the occurrence of aggregation, size sorting and lofting particles.

Julia A. Shates↗
DOE OSTI2022

Technoeconomic Analysis of Changing PV System Layout and Convection Heat Transfer

This work includes analysis of potential economic improvements for PV systems for changing system parameters such as ground coverage ratio that alter the convective cooling consideration on PV modules through a newly proposed convective curve fit. Accounting for the spatial layout of the system in the convection heat transfer calculations allows for more accuracy in convective cooling load and subsequent module temperature calculations. The changing heat transfer considerations can be shown to improve system LCOE along with improved incident irradiance from increased row spacing despite the additional system costs incurred with increased module spacing. State-level analyses show that the impact of decreasing system GCR is greatest for climates with cold average annual ambient temperatures and moderate to high average annual wind speeds. Further waterfall analysis of changing system parameters reveals that the changing heat transfer dynamics have a non-negligible impact on system LCOE when compared to the changes in incident irradiance that serve as the primary driver of annual energy performance changes.

ENERGY PLANNING, POLICY, AND ECONOMY,SOLAR ENERGY↗
DOE OSTI2024

Sensitivity Analyses of Natural Convection in the AP1000 Passive Containment Cooling System Following LBLOCA Using CFD

The AP1000 power plant has implemented multiple layers of passive safety systems to enhance reactor safety and ensure system integrity during postulated scenarios, such as loss of coolant accident (LOCA) and main steam line break (MSLB). Among these, the passive containment cooling system (PCCS) is a safety-related system designed to prevent the containment from exceeding the design limits of both pressure and temperature following a postulated design basis accident, by transferring heat from the steel containment vessel to the atmosphere. During LOCA, natural air convection plays a vital role in removing heat from the steel containment vessel to the atmosphere. This is integrated with the condensate film from the Passive Containment Cooling Water Storage Tank (PCCWST). Air natural convection is also the only heat removal mechanism after the dry-out of the PCCWST and during the loss of shutdown decay heat removal (LOSDHR) event. Therefore, it is essential to investigate the thermal hydraulics behavior of the containment under transient conditions to ensure its safety and integrity. This paper presents a simplified CFD/ANSYS FLUENT model developed to analyze the impact of different parameters, such as air relative humidity, air temperature, and steel containment temperature, on the natural convection capability to remove the decay heat following LOCA. The model aims to examine the thermal behavior of the containment and provides a comprehensive understanding of the system's natural convection capability during postulated accidents. The results obtained from the model can be used to improve the safety and integrity of the containment system and provide valuable insights for future research in the field.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Mesoscale Convective Systems in a Superparameterized E3SM Simulation at High Resolution

Accurately representing mesoscale convective systems (MCSs) is crucial to simulating the energy and water cycles in global climate models. Using a novel MCS identification and tracking algorithm applied to observations and model simulations, we evaluate how well the Energy Exascale Earth System Model simulates MCSs over the central US. Simulations performed by E3SM at 25 km grid spacing with (SP-E3SM) and without (E3SM) superparameterization are compared and evaluated against observations using multiple metrics highlighting important MCS characteristics. Compared to E3SM, SP-E3SM better simulates MCS number and MCS precipitation amount, diurnal cycle, propagation, and the probability distribution of precipitation rate in both spring and summer. The improvement from SP is partly contributed by improvement in simulating the large-scale environments, featuring enhanced atmospheric low-level moisture and larger moisture transport to the central US relative to E3SM. However, SP-E3SM still underestimates MCS precipitation amount, particularly in summer. This underestimation is closely related to the negative bias in MCS precipitation intensity, although the drier environments simulated during summer also contributes to underestimation of MCS frequency. Without SP, the larger bias in MCS precipitation amount is closely related to the negative bias in MCS frequency, while the substantial dry bias in the large-scale environments also contributes to underestimation of MCS intensity. Our results suggest that SP improves MCS simulation by improving modeling of the large-scale environments and convection initiation, which are both major limiting factors in E3SM even at 25 km grid spacing where deep convection is represented by a cumulus parameterization.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Summertime Near-Surface Temperature Biases Over the Central United States in Convection-Permitting Simulations

Convection-Permitting Model (CPM) simulations of the Central United States climate for the summer of 2011 are studied to understand the causes of warm biases in 2-m air temperature (T 2m ) and related underestimates of precipitation including that from mesoscale convective systems (MCSs). Based on 10 CPM simulations and 9 coarser-resolution model simulations, we quantify contributions from evaporative fraction (EF) and radiation to the T 2m bias with both types of models overestimating T 2m largely because they underestimate EF. The performance of CPMs in capturing MCS characteristics (frequency, rainfall, propagation) varies. The pre-summer precipitation bias has large correlation with mean summertime T 2m bias but the relationship between summertime MCS mean rainfall bias and T 2m bias is non-monotonic. Analysis of lifting condensation level deficit and convective available potential energy suggests that models with T 2m warm biases and low EF have too dry and stable boundary layers, inhibiting the formation of clouds, precipitation and MCSs. Among the CPMs with differing model formulations (e.g., transpiration, infiltration, cloud macrophysics and microphysics), evidence suggests that altering the land-surface model is more effective than altering the atmospheric model in reducing T 2m biases. In conclusion, these results demonstrate that land-atmosphere interactions play a very important role in determining the summertime climate of the Central United States.

2-m air temperature↗
DOE OSTI2025

Factors Controlling Precipitation Onset and Maintenance: Inferences From Large Eddy Simulations of Two Afternoon Deep Convective Regimes Over Amazon

To investigate the environmental factors controlling the onset and maintenance of afternoon precipitation over tropical rainforests, two contrasting cases are created for large eddy simulations (LES) using GoAmazon observations: one features a single-pulse rain dissipating quickly in earlier afternoon, while the other shows double pulses lasting until evening. For these two specific cases under consideration, LES confirms that early-morning relative humidity dominates afternoon rain patterns. The attributed impacts are distinct: moisture determines the rain onset timing while temperature affects the peak rain intensity. Single-pulse day observes one round of strong precipitation and cold pools, which further suppresses convection. On double-pulse day, the first precipitation peak results from an intermediate development of congestus clouds, whose detrainment leads to a gradual moistening of the lower-to-middle troposphere. This behavior of convection favors a second pulse of stronger precipitation with more convective organization, whose development decouples from surface fluxes and sustains until evening.

Amazon↗