A mesoscale model is used to systematically investigate how the incoming flow incidence angle affects the development of atmospheric von Kármán vortex streets for non-axisymmetric islands. The analysis is focused on an event observed on the leeward side of Guadalupe Island. By keeping the synoptic conditions the same, several simulations are performed for rotated orientations of the island topography, which correspond to a change in the angle of attack relative to the upstream flow. The asymmetry of the vortex shedding and the role of the leading and trailing edge are in line with what was observed in laboratory von Kármán vortex streets past a flat plate. The eddies become larger with increasing angle of attack while the shedding frequency decreases, and the asymmetry between cyclonic and anticyclonic eddies weakens. Cyclonic vortices are more developed and stronger under typical conditions when they are shed from the trailing edge. However, the asymmetry favors anticyclonic vortices when the cyclonic vortices are shed from the leading edge.
We have analyzed TROPOMI data over the Copperbelt mining region (Democratic Republic of Congo and Zambia). Despite high background values, we find that annual 2019-2022 means of TROPOMI NO2 show local enhancements consistent with six point sources (mines and cities) where high-emission industrial activities take place. We have quantified annual NO2 emissions for the six sources, identified temporal trends in these emissions, and found strong correlations with mine/refinery production data. CAMS-GLOB-ANT v5 inventory emissions are lower than TROPOMI-derived emissions by 61-96 % and lack the temporal trends observed in TROPOMI and mine/oil refinery production. Lack of TROPOMI SO2 enhancements over the point sources analyzed indicates SO2 capture and transformation into sulfuric acid, a profitable byproduct. These results demonstrate the potential for satellite monitoring of mining/oil refining activity which impacts the air quality of local communities. This is particularly important for Africa, where mining is increasing aggressively.
The accuracy of initial conditions is an important driver of the forecast skill of numerical weather prediction models. Increases in the quantity of available measurements, in particular high-resolution remote sensing observational data products from satellites, are valuable inputs for improving those initial condition estimates. However, the data assimilation methods used for integrating observations into forecast models are computationally expensive. This makes incorporating dense observations into operational forecast systems challenging, and it is often prohibitively time-consuming. As a result, large quantities of data are discarded and not used for state initialization. We demonstrate, using the Lorenz-96 system for testing, that a simple machine learning method can be trained to assimilate high-resolution data. Using it to do so improves both initial conditions and forecast accuracy. Compared to using the Ensemble Kalman Filter with high-resolution observations ignored, our augmented method has an average root-mean-squared error reduced by 15%. Ensemble forecasts using initial conditions generated by the augmented method are more accurate and reliable at up to 10 days of forecast lead time.
ERA5 reanalysis is used to examine extreme precipitation using a spatially dependent precipitation threshold applied within a cyclone compositing framework. This is used to account for regional variation in precipitation generating processes within Southern Hemisphere mid-latitude cyclones across the cyclone lifecycle. The spatial extent of extreme precipitation is limited to a smaller region around the cyclone centre compared to non-extreme precipitation, though extreme precipitation displays a good spatial correlation with non-extreme precipitation. Extreme precipitation occurs more often during the deepening phase of the cyclone before it reaches a maximum depth. Precipitation occurrence at the 90th and 98th percentiles reduces to 46% and 30% of the deepening value across the cyclone lifecycle, averaged over the composite. Precipitation fraction at the 90th and 98th percentile reduces to 80% and 60% of the deepening value. Our methodology provides a quantitative assessment of precipitation extremes both spatially and temporally, within a cyclone compositing framework.
Accurately identifying liquid water layers in mixed-phase clouds is crucial for estimating cloud radiative effects. Lidar-based retrievals are limited in optically thick or multilayer clouds, leading to positive biases in simulated shortwave radiative fluxes. At the same time, general circulation models also tend to overestimate the downwelling shortwave radiation at the surface especially in the Southern Ocean regions. To reduce this SW radiation bias in models, we first need better observational-based retrievals for liquid detection which can later be used for model validation. To address this, a machine-learning-based liquid-layer detection method called VOODOO was employed in a proof-of-concept study using a single column radiative transfer model to compare shortwave cloud radiative effects of liquid-containing clouds detected by Cloudnet and VOODOO to ground-based and satellite observations. Results showed a reduction in shortwave radiation bias, indicating that liquid-layer detection with machine-learning retrievals can improve radiative transfer simulations.
During NASA’s Apollo missions, inhalation of dust particles from lunar regolith was identified as a potential occupational hazard for astronauts. These fine particles adhered tightly to spacesuits and were brought accidentally into the living areas of the spacecraft. Apollo astronauts reported that exposure to the dust caused intense respiratory and ocular irritation. This problem is a potential challenge for the Artemis Program, which aims to return humans to the Moon for extended stays in this decade. Since lunar dust is “weathered” by space radiation, solar wind, and the incessant bombardment of micrometeorites, we investigated whether treatment of lunar regolith simulants to mimic space weathering enhanced their toxicity. Two such simulants were employed in this research, Lunar Mare Simulant-1 (LMS-1), and Lunar Highlands Simulant-1 (LHS-1), which were applied to human lung epithelial cells (A549). In addition to pulverization, previously shown to increase dust toxicity sharply, the simulants were exposed to hydrogen gas at high temperature as a proxy for solar wind exposure. This treatment further increased the toxicity of both simulants, as measured by the disruption of mitochondrial function, and damage to DNA both in mitochondria and in the nucleus. By testing the effects of supplementing the cells with an antioxidant (N-acetylcysteine), we showed that a substantial component of this toxicity arises from free radicals. It remains to be determined to what extent the radicals arise from the dust itself, as opposed to their active generation by inflammatory processes in the treated cells.
We present an application of quantile generalised additive models (QGAMs) to study spatially compounding climate extremes, namely extremes that occur (near-) simultaneously in geographically remote regions. We take as an example wintertime cold spells in North America and co-occurring wet or windy extremes in Western Europe, which we collectively term Pan-Atlantic compound extremes. QGAMS are largely novel in climate science applications and present a number of key advantages over conventional statistical models of weather extremes. Specifically, they remove the need for a direct identification and parametrisation of the extremes themselves, since they model all quantiles of the distributions of interest. They thus make use of all information available, and not only of a small number of extreme values. Moreover, they do not require any a priori knowledge of the functional relationship between the predictors and the dependent variable. Here, we use QGAMs to both characterise the co-occurrence statistics and investigate the role of possible dynamical drivers of the Pan-Atlantic compound extremes. We find that cold spells in North America are a useful predictor of subsequent wet or windy extremes in Western Europe, and that QGAMs can predict those extremes more accurately than conventional peak-over-threshold models.
Water vapor and cirrus clouds in the Tropical Tropopause Layer (TTL) are important for the climate and are largely controlled by temperature in the TTL. On interannual timescales, both stratospheric and tropospheric modes of variability affect temperatures in the TTL. In this study, we use satellite observations to investigate the explained variance in cold point temperature (CPT), 83 hPa water vapor (WV83), and TTL cirrus cloud fraction (TTLCCF) over the equatorial region (15°N - 15°S) using a multiple linear regression (MLR) model where predictors are stratospheric and tropospheric modes of variability. The MLR model can explain 68%, 60%, and 52% of the variance in CPT, WV83, and TTLCCF. The model suggests that these variables are dominated by stratospheric ‘top-down’ processes associated with the Quasi-Biennial Oscillation (QBO) and Brewer Dobson Circulation (BDC) as opposed to tropospheric ‘bottom-up’ processes associated with the El Nino Southern Oscillation (ENSO) and the Madden-Julian Oscillation (MJO). Although cold point temperature is controlled by ‘top-down’ mechanisms, the cold point tropopause height is related to both ‘top-down’ stratospheric and ‘bottom-up’ tropospheric processes. Our MLR model explains more variance during boreal winter. We also investigate how these modes of variability correlate with zonal mean temperature, water vapor, and cloud fraction globally in the upper troposphere and lower stratosphere (UTLS) and find significant relationships between clouds and the modes of variability.
Quantifying sector-resolved methane fluxes in complex emissions environments is challenging yet necessary for inventory validations. We separate energy and agriculture sector methane using a dynamic linear model of methane, ethane, and ammonia mixing ratios measured at a Northern Colorado site from November 2021 to January 2022. Combining observations with spatially resolved inventories and inverse methods, energy and agriculture methane fluxes are constrained across a ~850 km2 area. Optimized energy sector fluxes were 22% lower than the inventory despite a ~360% increase in regional energy production since the inventory was constructed, suggesting a regional decline in emissions factors. In contrast, optimized agriculture fluxes were 3× larger than the inventory; we demonstrate this discrepancy is consistent with the spatial distribution of agricultural sources. These results highlight the utility of sector-apportioned methane observations for multi-sector inventory optimization in complex environments, which may prove valuable for national and global quantification of sector-resolved methane fluxes.
Tropical cyclogenesis can be influenced by convectively coupled equatorial waves; yet, existing datasets prevent a complete analysis of the multi-scale processes governing both tropical cyclones (TCs) and equatorial waves. This study introduces a convection-permitting aquaplanet simulation that can be used as a laboratory to study TCs, equatorial waves, and their interactions. The simulation was produced with the Model for Prediction Across Scales-Atmosphere (MPAS-A) using a variable resolution mesh with convection-permitting resolution (i.e., 3-km cell spacing) between 10oS–30oN. The underlying sea-surface temperature is given by a zonally symmetric profile with a peak at 10oN, which allows for the formation of TCs. A comparison between the simulation and satellite, reanalysis, and airborne dropsonde data is presented to determine the realism of the simulated phenomena. The simulation captures a realistic TC intensity distribution, including major hurricanes, but their lifetime maximum intensities may be limited by the stronger vertical wind shear in the simulation compared to the observed tropical Pacific region. The simulation also captures convectively coupled equatorial waves, including Kelvin waves and easterly waves. Despite the idealization of the aquaplanet setup, the simulated three-dimensional structure of both groups of waves is consistent with their observed structure as deduced from satellite and reanalysis data. Easterly waves, however, have peak rotation and meridional winds at a slightly higher altitude than in the reanalysis. Future studies may use this simulation to understand how convectively coupled equatorial waves influence the multi-scale processes leading to tropical cyclogenesis.
Although adequately detailed kerosene chemical-combustion Arrhenius reaction-rate suites were not readily available for combustion modeling until ca. the 1990’s (e.g., Marinov ), it was already known from mass-spectrometer measurements during the early Apollo era that fuel-rich liquid oxygen + kerosene (RP-1) gas generators yield large quantities (e.g., several percent of total fuel flows) of complex hydrocarbons such as benzene, butadiene, toluene, anthracene, fluoranthene, etc. (Thompson ), which are formed concomitantly with soot (Pugmire ). By the 1960’s, virtually every fuel-oxidizer combination for liquid-fueled rocket engines had been tested, and the impact of gas phase combustion-efficiency governing the rocket-nozzle efficiency factor had been empirically well-determined (Clark ). Up until relatively recently, spacelaunch and orbital-transfer engines were increasingly designed for high efficiency, to maximize orbital parameters while minimizing fuels and structural masses: Preburners and high-energy atomization have been used to pre-gasify fuels to increase (gas-phase) combustion efficiency, decreasing the yield of complex/aromatic hydrocarbons (which limit rocket-nozzle efficiency and overall engine efficiency) in hydrocarbon-fueled engine exhausts, thereby maximizing system launch and orbital-maneuver capability (Clark; Sutton; Sutton/Yang). The combustion community has been aware that the choice of Arrhenius reaction-rate suite is critical to computer engine-model outputs. Specific combustion suites are required to estimate the yield of high-molecular-weight/reactive/toxic hydrocarbons in the rocket engine combustion chamber, nonetheless such GIGO errors can be seen in recent documents. Low-efficiency launch vehicles also need larger fuels loads to achieve the same launched mass, further increasing the yield of complex hydrocarbons and radicals deposited by low-efficiency rocket engines along launch trajectories and into the stratospheric ozone layer, the mesosphere, and above. With increasing launch rates from low-efficiency systems, these persistent (Ross/Sheaffer ; Sheaffer ), reactive chemical species must have a growing impact on critical, poorly-understood upper-atmosphere chemistry systems.
Although adequately detailed kerosene chemical-combustion Arrhenius reaction-rate suites were not readily available for combustion modeling until ca. the 1990’s (e.g., Marinov ), it was already known from mass-spectrometer measurements during the early Apollo era that fuel-rich liquid oxygen + kerosene (RP-1) gas generators yield large quantities (e.g., several percent of total fuel flows) of complex hydrocarbons such as benzene, butadiene, toluene, anthracene, fluoranthene, etc. (Thompson ), which are formed concomitantly with soot (Pugmire ). By the 1960’s, virtually every fuel-oxidizer combination for liquid-fueled rocket engines had been tested, and the impact of gas phase combustion-efficiency governing the rocket-nozzle efficiency factor had been empirically well-determined (Clark ). Up until relatively recently, spacelaunch and orbital-transfer engines were increasingly designed for high efficiency, to maximize orbital parameters while minimizing fuels and structural masses: Preburners and high-energy atomization have been used to pre-gasify fuels to increase (gas-phase) combustion efficiency, decreasing the yield of complex/aromatic hydrocarbons (which limit rocket-nozzle efficiency and overall engine efficiency) in hydrocarbon-fueled engine exhausts, thereby maximizing system launch and orbital-maneuver capability (Clark; Sutton; Sutton/Yang). The rocket combustion community has been aware that the choice of Arrhenius reaction-rate suite is critical to computer engine-model outputs. Specific combustion suites are required to estimate the yield of high-molecular-weight/reactive/toxic hydrocarbons in the rocket engine combustion chamber, nonetheless such GIGO errors can be seen in recent documents. Low-efficiency launch vehicles (SpaceX, Hanwha) therefore also need larger fuels loads to achieve the same launched/transferred mass, further increasing the yield of complex hydrocarbons and radicals deposited by low-efficiency rocket engines along launch trajectories and into the stratospheric ozone layer, the mesosphere, and above. With increasing launch rates from low-efficiency systems, these persistent (Ross/Sheaffer ; Sheaffer ), reactive chemical species must have a growing impact on critical, poorly-understood upper-atmosphere chemistry systems.
Key Points: 10 • We improve a long-standing stratocumulus (Sc) dim bias in a high-resolution Mul-11 tiscale Modeling Framework. 12 • Incorporating intra-CRM hypervisocity hedges against the numerics of its momen-13 tum solver, reducing entrainment vicinity. 14 • Further adding sedimentation boosts Sc brightness close to observed, opening path 15 to more faithful low cloud feedback analysis. Abstract 17 High-Resolution Multi-scale Modeling Frameworks (HR)-global climate models that 18 embed separate, convection-resolving models with high enough resolution to resolve bound-19 ary layer eddies-have exciting potential for investigating low cloud feedback dynam-20 ics due to reduced parameterization and ability for multidecadal throughput on mod-21 ern computing hardware. However low clouds in past HR have suffered a stubborn prob-22 lem of over-entrainment due to an uncontrolled source of mixing across the marine sub-23 tropical inversion manifesting as stratocumulus dim biases in present-day climate, lim-24 iting their scientific utility. We report new results showing that this over-entrainment 25 can be partly offset by using hyperviscosity and cloud droplet sedimentation. Hypervis-26 cosity damps small-scale momentum fluctuations associated with the formulation of the 27 momentum solver of the embedded LES. By considering the sedimentation process ad-28 jacent to default one-moment microphysics in HR, condensed phase particles can be re-29 moved from the entrainment zone, which further reduces entrainment efficiency. The re-30 sult is an HR that is able to produce more low clouds with a higher liquid water path 31 and a reduced stratocumulus dim bias. Associated improvements in the explicitly sim-32 ulated sub-cloud eddy spectrum are observed. We report these sensitivities in multi-week 33 tests and then explore their operational potential alongside microphysical retuning in 34 decadal simulations at operational 1.5 degree exterior resolution. The result is a new HR 35 having desired improvements in the baseline present-day low cloud climatology, and a 36 reduced global mean bias and root mean squared error of absorbed shortwave radiation. 37 We suggest it should be promising for examining low cloud feedbacks with minimal ap-38 proximation. 39 Plain Language Summary 40 Stratocumulus clouds cover a large fraction of the globe but are very challenging 41 to reproduce in computer simulations of Earth's atmosphere because of their unique com-42 plexity. Previous studies find the model produces too few Stratocumulus clouds as we 43 increase the model resolution, which, in theory, should improve the simulation of impor-44 tant motions for the clouds. This is because the clouds are exposed to more conditions 45 that make them evaporate away. On Earth, stratocumulus clouds reflect a lot of sun-46 light. In the computer model of Earth, too much sunlight reaches the surface because 47 of too few stratocumulus clouds, which makes it warmer. This study tests two methods 48 to thicken Stratocumulus clouds in the computer model Earth. The first method smooths 49 out some winds, which helps reduce the exposure of clouds to the conditions that make 50 them evaporate. The second method moves water droplets in the cloud away from the 51 conditions that would otherwise make them evaporate. In long simulations, combining 52 these methods helps the model produce thicker stratocumulus clouds with more water. 53
The urban morphology determined by urban canopy parameters (UCPs) plays an important role in simulating the interaction of urban land surface and atmosphere. The impact of urbanization on a typical summer rainfall event in Hangzhou, China, is investigated using the integrated WRF/urban modelling system. Three groups of numerical experiments are designed to assess the uncertainty in parameterization schemes, the sensitivity of urban canopy parameters (UCPs), and the individual and combined impacts of thermal and dynamical effects of urbanization, respectively. The results suggest that the microphysics scheme has the highest level of uncertainty in simulating precipitation, followed by the planetary boundary layer scheme, whereas the land surface and urban physics schemes have minimal impacts. The choices of the physical parameterization schemes for simulating precipitation are much more sensitive than those for simulating temperature, mixing ratio, and wind speed. Of the eight selected UCPs, changes in heat capacity, thermal conductivity, surface albedo, and roughness length have a greater impact on temperature, mixing ratio, and precipitation, while changes in building height, roof width, and road width affect the wind speed more. The total urban impact could lead to higher temperature, less mixing ratio, lower wind speed, and more precipitation in and around the urban area. Comparing the thermal and dynamical effects of urbanization separately, both of them contribute to an increase in temperature and precipitation and the thermal effect plays a major role. However, their impacts are opposite in changes of mixing ratio and wind speed, and each play a major role respectively.