Atmospheric ice-nucleating particles (INPs) from mineral dust and non-proteinaceous biological sources can influence cloud formation, precipitation, and Earth’s radiation budget due to their efficient freezing abilities. The ambient aerosol particles from these sources are abundant with ambient concentrations exceeding a few µg m^-3 for each type. Thus, the characterization of INPs and aerosol particles from these sources is important. We typically characterize their specific surface area (SSA), which is the primary variable to estimate their ice-nucleation active surface site density, using a sorbate gas, such as nitrogen. However, it is still uncertain how these particles interact with water vapor under subzero temperatures. To fill this gap, we used the 3Flex instrument (Micromeritics Instrument Corp.) with multiple sorbates to comprehensively characterize the nanoscale surface structure, pore size distribution, and accessibility to water molecules of a commercially available model proxy of mineral dust (illite NX) and cellulose materials. To date, we have completed more than 60 physisorption 3Flex experiments with various sorbates, such as CO2, H2O, Kr, and N2, for each sorbent. In particular, we examined SSA by water vapor sorption at temperatures relevant to atmospheric heterogeneous freezing (~ 0 to -20 °C). We will present our results as physisorption isotherms. In addition, our preliminary results of temperature-dependent SSA observed for micro- and nano-crystalline cellulose materials as well as illite NX will be discussed. Our preliminary result suggests that the SSA of illite NX is less temperature-dependent compared to the cellulose materials, which may be potentially swelling while interacting with water. Therefore, illite NX may be suitable for an INP test proxy.

The system of trade wind cumulus clouds observed during the RICO field project was simulated by an LES model over a 50x50 km2 domain size. Parameters of latent heat release were analyzed with the goal of parameterizing their effects on grids typical for NWP and large-scale models. Over 2000 clouds were examined focusing on relationship between parameters of latent heat release (phase transition rates) and dynamical/microphysical cloud characteristics. The phase transition rates (Tr), which in warm tropical clouds are represented by processes of condensation/evaporation, were analyzed by stratifying the clouds by their size/stage of maturity. The analyzed parameters included, among others, integral mass and buoyancy fluxes, cloud and rain water parameters. In our previous investigation we found that a remarkably strong correlation exists between Tr and upward mass flux (ℳ). The strong dependence of phase transition rates on ℳ, as well as linear relationship between Tr and ℳ, was explained by applying the condensation theory and the concept of “quasi-steady” supersaturation. The LES derived slope of the linear fit agreed with its theoretically predicted value with an error less than 5%. This result implies that supersaturation in clouds, on average, varies within a few percentage points of its quasi-steady value. The theory, as well as LES data, show that the Tr - ℳ linear fit is valid for local variables, and, therefore, may be integrated to obtain horizontal mean parameters. Expanding the Tr - ℳ relationship for vertically dependent horizontal mean variables, may provide the framework for development of sub-grid scale (SGS) latent heat release parameterization. It was also suggested that calculating the slope of the linear fit from concurrent measurements of temperature and vertical velocity, and comparing it with the theoretical slope based on the quasi-steady supersaturation assumption, may offer a method for estimating the supersaturation in clouds.

Researchers and end users using climate data face a challenge when they analyze the data they need. Data volumes are increasing very rapidly, and the ability to download all needed data is often no longer possible. Most of the climate analysis tools for research and application needs must use very large datasets, often distributed among several data centres and into a large quantity of files. This is especially true when they are stored in a federated architecture like the ESGF. One of these tools is icclim (https://github.com/cerfacs-globc/icclim ), a flexible python software package to calculate climate indices and indicators. This tool adhere as much as possible to metadata conventions such as CF, implementing also provenance information. It also aims at providing increasing support for all FAIR aspects. It is designed with performance and optimisation in mind, because the goal is to provide on-demand calculations for users. It provides the implementation of most of the international standard climate indices such as ECAD, ETCCDI, ET-SCI, including the correct methodology for calculating percentile indices using the bootstrapping method. It has been validated against R.Climdex as well (https://cran.r-project.org/web/packages/climdex.pcic/index.html ). The new 5.x version of icclim is now based on functions from the xclim python library, which was inspired by earlier versions of icclim, but using xarray and dask for data access and processing. icclim is also a candidate as the software to calculate climate indices for the C3S toolbox (https://cds.climate.copernicus.eu/cdsapp#!/toolbox ). icclim is integrated in the IS-ENES C4I 2.0 platform (https://climate4impact.eu/ ), using a Jupyter notebook collection in a SWIRRL environment (Software for Interactive Reproducible Research Labs https://gitlab.com/KNMI-OSS/swirrl ). Having access to this type of analysis tool is very useful, and seamless integration with front-ends like C4I enable the use of those tools by a larger number of researchers and end users. This project (IS-ENES3) has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement N°824084.

Using 42 years of reanalysis data, we investigate the characteristics of intensifying Atlantic tropical cyclones, especially rapid intensification (RI) events. 52% of initial RI onsets occurred when the intensity was ≤35 kt. Probability density functions were distinct between intensification categories for vertical wind shear, sea surface temperature (SST), and radius of maximum winds (RMW), but less so for relative humidity. In the Gulf of Mexico and southern North Atlantic, shear and RMW were good predictors. In the open Atlantic, north of 22.5°N, shear and SST were the best predictors. In the Caribbean, weaker relationships suggest low statistical predictability in a region where RI cases are increasing. Comparing 1980-2000 versus 2001-2021, total number of RI events increased by 36%, and the shear and SST distributions shifted higher for RI events. Given the variability across regions, periods, and variables, a nuanced approach for research and forecasting of RI is necessary.

We synthesized N2O emissions over North America using 17 bottom-up (BU) estimates from 1980-2016 and five top-down (TD) estimates from 1998-2016. The BU-based total emission shows a slight increase owing to U.S. agriculture, while no consistent trend is shown in TD estimates. During 2007-2016, North American N2O emissions are estimated at 1.7 (1.0-3.0) Tg N yr-1 (BU) and 1.3 (0.9-1.5) Tg N yr-1 (TD). Anthropogenic emissions were twice larger than natural fluxes from soil and water. Direct agricultural and industrial activities accounted for 68% of total anthropogenic emissions, 71% of which was contributed by the U.S. Our estimates of U.S. agricultural emissions are comparable to the EPA greenhouse gas (GHG) inventory, which includes estimates from IPCC tier 1 (emission factor) and tier 3 (process-based modeling) approaches. Conversely, our estimated agricultural emissions for Canada and Mexico are twice as large as the respective national GHG inventories based on tier 1 approaches.

The PRISM Data Library (DL) is designed to optimize the display, analysis, and retrieval of multiple domains datasets. Originally created for climate data, we aggregated data from agriculture and hydrology domains, as well as non-traditional domains for the DL such as ecology, finance, power outage and space weather data. These datasets range from simple geospatial point observations, to spatially gridded data products, to high-resolution satellite measurements, to GIS representation of administrative or domain-specific geographic entities. These datasets are represented in a consistent multi-dimensional (most often spatial and temporal) framework. As a result, dimension-wise comparisons are easily enabled through selection or transformation. Gridded data can be averaged over discrete geometrical entities (e.g. Counties, Bird Conservation Regions). The DL can be used in a browser, by connecting to servers at San Diego Supercomputing Center (SDSC) over the internet. Data selection, processing, and analysis are performed by the SDSC DL servers, and the resulting images or data files are sent back to the client’s desktop. This model optimizes the use of internet bandwidth.

We have used the LOw-Frequency ARray (LOFAR) to image a few lightning flashes during a particularly severe thunderstorm. The images show an exceptional amount of VHF activity at altitudes above 10 km. Much of this is in the form of small-scale discharges occurring seemingly randomly around the centers of active storm cells. Because of their small and incidental structure we refer to these as ‘speckles’. A detailed investigation shows strong evidence that these speckles are indicative of positive leader channels and that they are equivalent to the needle activity seen around positive leader tracks at lower altitudes.

The ablation of phosphorus from interplanetary dust particles entering the Earth’s atmosphere is a potentially significant source of this key bio-element. In this study, the atmospheric chemistry of phosphorus is explored by developing a reaction network of possible routes from PO, the major ablation product in the upper mesosphere/lower thermosphere region, to the stable reservoirs H3PO3 and H3PO4 that become incorporated into meteoric smoke particles as metal phosphites and phosphates, respectively. The network is constructed with reactions whose kinetics have been measured experimentally, together with reactions where theoretical rate coefficients are estimated using a combination of electronic structure theory calculations and a Rice-Ramsperger-Kassel-Markus master equation treatment. The network is then incorporated into a global chemistry-climate model, together with a phosphorus meteoric input function. The estimated global mean P deposition flux, in the form of sub-micron sized meteoric smoke particles, is 1 × 10-8 g m-2 yr-1, with a maximum of ~5 × 10-8 g m-2 yr-1 over the northern Rockies, Himalayas and southern Andes. The estimated fraction of ablated phosphorus forming bio-available metal phosphites is 11%, which results from the very large concentrations of O and H compared to OH in the upper mesosphere. A layer of OPO is predicted to occur at 90 km with a peak of concentration of ~50 cm-3; this is the counterpart of the well-known layers of meteoric metals such as Na and Fe, and may be observable spectroscopically.

We discuss results on plasma density profile modifications in the F-region ionosphere caused by HF heating with the frequency f0 in the range [(-150 kHz)-(+75 kHz)] around the 4th electron gyroharmonic 4fc. The experiments were conducted at the HAARP facility on June 2014. The multi-frequency Doppler Sounder (MDS) which measures the phase and amplitude of reflected sounding radio waves complemented by the observations of the Stimulated Electromagnetic Emission (SEE) were used for the diagnostics of the plasma perturbations. We detected noticeable plasma expulsion from the reflection region of the pumping wave, and from the upper hybrid region, the expulsion from the latter one had been strongly suppressed for f0≈4fc. The plasma expulsion from the upper hybrid region was accompanied with the sounding wave’s anomalous absorption slower developing for f0≈4fc. Also, slower developing and weaker expulsion was detected for the height region between the pump wave reflection and upper hybrid altitudes.

In 2020, global atmospheric methane (CH4) levels increased by 14.7 parts-per-billion (ppb) - the largest annual increase since atmospheric records began in 1983 (https://research.noaa.gov/article/ArtMID/587/ArticleID/2742/Despite-pandemic-shutdowns-carbon-dioxide-and-methane-surged-in-2020) continuing an upward trend since 2007. This is concerning since CH4 is the second most important long-lived greenhouse after CO2 and has global warming potential 28 times that of CO2 per unit mass on a 100-year time scale (Myhre et al. 2013). Moreover, pathways to limit global warming to 1.5°C, or even 2.0°C, require non-CO2 emissions and, in particular, CH4 emissions, to be reduced by 35% with respect to 2010 levels by 2050 (Forster et al. 2018).

High-resolution climate models (~28 km grid spacing) can permit realistic simulations of tropical cyclones (TCs), thus enabling their investigation in relation to the climate system. On the global scale, previous works have demonstrated that the Community Atmosphere Model (CAM) version 5 presents a reasonable TC climatology under prescribed present-day (1980-2005) forcing. However, for the Western North Pacific (WNP) region, known biases in simulated TC genesis frequency and location under-represent the basin’s dominant share in observation. This study addresses these model biases in WNP by evaluating WNP TCs in a decadal simulation, and exploring potential improvements through nudging experiments. Among the major environmental controls of TC genesis, the lack of mid-level moisture is identified as the leading cause of the deficit in simulated WNP TC genesis over the Pacific Warm Pool. Subsequent seasonal experiments explore the effect of constraining the large-scale environment on TC development by nudging WNP temperature field towards reanalysis at various strengths. Temperature nudging elicits significant response in TC genesis and intensity development, as well as in moisture and convection over the Warm Pool. These responses are sensitive to the choice of nudging timescale. Overall, the nudging experiments demonstrate that improvements in the large-scale environment can lead to improvements in simulated TCs. The verification of the environmental controls for simulated TC genesis suggests future model developments in relation to model physics. The potential improvements will contribute to the understanding of how the mean state of current or future climates may give rise to extremes such as TCs.

We have developed a model that simulates the power density profile of the Saskatoon Super Dual Auroral Radar Network (SuperDARN) radar at ionospheric altitudes. The model uses ray tracing software to project the radar system’s vacuum power profile to ionospheric altitudes, taking into account the influence of the ionospheric medium on the propagation characteristics of the High Frequency radio waves. Measurements of the radar’s transmissions by the Radio Receiver Instrument (RRI) in low-Earth orbit are used to validate the model during five experiments which occurred between August 4-8, 2017. Comparisons between simulated and measured RRI antenna voltages show good agreement, although there are clear instances in which the model underperforms. Nevertheless, the model demonstrates its utility as a tool for interpreting several RRI measurements of SuperDARN radars. The model also helps address a lack of knowledge of a SuperDARN radar’s power profile at ionospheric altitudes. In particular, we assess the assumption that SuperDARN’s scattering volume lies along the great-circle path of the transmitting beam’s bearing. Comparisons between the model and RRI’s measurements show that this assumption is reasonable for the five experiments investigated in this work. The model presents a new way of carrying out SuperDARN and HF radio science investigations.

India implemented stay-at-home order (i.e. lockdown) on 24 March 2020 to decrease the spread of novel COVID-19, which reduced air pollutant emissions in different sectors. The Weather Research and Forecasting model with Chemistry (WRF-Chem) was used to study the changes in air pollutants during the lockdown period in 2020 compared with similar period in 2019. We found that both meteorology and lockdown emissions contributed to daytime PM2.5 (-6% and -11%, respectively) and ozone (-6% and -8%, respectively) reduction averaged in April 2020 in the Indo-Gangetic Plain. However, the ozone concentration response to reductions in its precursors (i.e. NO2 and VOCs) due to the lockdown emissions was not constant over the domain. While ozone concentration decreased in most parts of the domain, it slightly increased in major cities like Delhi and in regions with many power plants. We utilized the reaction rates information in WRF-Chem to study the ozone chemistry. We found carbon monoxide, formaldehyde, isoprene, acetaldehyde, and ethylene as the major VOCs that contribute to the ozone formation in India. We used the ratio of chemical loss of radicals with radicals and NOx, and its corresponding formaldehyde to NO2 ratio (FNR) to find the ozone chemical regimes. Using the upper limit of FNR transition region (1.3), we found that most parts of India are within NOx-limited regime while urban regions and the regions with many power plants are in a VOC-limited regime. As a result, policy makers should study the characteristics of a region before implementing mitigation strategies.

In winter, the Northwest Tropical Atlantic Ocean can be characterized by various regimes of interactions among ocean current, surface wind, and wind waves, which are critical for accurately describing surface wind stress. In this work, coupled wave-ocean-atmosphere model simulations are conducted using two different wave roughness parameterizations within COARE3.5, including one that relies solely on wind speed and another that uses wave age and wave slope as inputs. Comparisons with the directly measured momentum fluxes during the ATOMIC/EUREC4A experiments in winter 2020 show that, for sea states dominated by short wind waves under moderate to strong winds, the wave-based formulation increases the surface roughness length by 40\% compared to the wind-speed-based approach. For sea states dominated by remotely generated swells under moderate to strong wind intensity, the wave-based formulation predicts significantly lower roughness length and surface stress (~20%), resulting in increased near-surface wind speed above the constant flux layer (~5%). Further investigation of the mixed sea states in the model and data indicates that the impact of swell on wind stress is over-emphasized in the COARE3.5 wave-based formulation, especially under moderate wind regimes. Various approaches are explored to alleviate this deficiency by either introducing directional alignment between wind and waves or using the mean wave period instead of the wave period corresponding to the spectral peak to compute the wave age.

The 3rd-order upstream advection scheme for scalars on the Voronoi C-grid, once introduced by Skamarock and Gassmann (2011), is applied to horizontal momentum advection. A prerequisite is that the 2nd-order momentum advection is available in advection form for a trivariate coordinate system, so that the higher order terms can be formulated as an add-on. Three key ingredients for a successful application are (i) the determination of the advecting velocity, (ii) the determination of directional Laplacians of wind components and (iii) the determination of the upstream direction. The scheme is tested in two settings, a shallow water framework on the regular hexagonal mesh and the baroclinic wave test on the sphere, where the mesh is slightly deformed. In both cases, the trailing ripples and waves known to represent dispersion errors are impressively reduced. If they are not removed, they can lead to spurious excitation of gravity waves or wavy vorticity patterns. After upscale error growth, they can no longer be identified as a result of numerical errors. The effects of the 3rd-order upstream add-on and a Smagorinsky diffusion are compared. The Smagorinsky model reduces the amplitude of the mentioned waves, but does not erase them. With regard to the dissipation properties, the Smagorinsky diffusion is in accordance with the 2nd law of thermodynamics and dissipation is locally only positive. In contrast, dissipation can be locally negative in runs with the 3rd-order upstream add-on. Therefore, physical and numerical requirements cannot be fulfilled simultaneously.

The Mars Environmental Dynamics Analyzer (MEDA) on board Perseverance includes first-of-their-kind sensors measuring the incident and reflected solar flux, the downwelling atmospheric IR flux, and the upwelling IR flux emitted by the surface. We use these measurements for the first 350 sols of the Mars 2020 mission (Ls ~ 6-174 deg; in Martian Year 36) to determine the surface radiative budget on Mars, and to calculate the broadband albedo (0.3-3 μm) as a function of the illumination and viewing geometry. Together with MEDA measurements of ground temperature, we calculate the thermal inertia for homogeneous terrains without the need for numerical models. We found that: (1) the observed downwelling atmospheric IR flux is significantly lower than model predictions. This is likely caused by the strong diurnal variation in aerosol opacity measured by MEDA, which is not accounted for by numerical models. (2) The albedo presents a marked non-Lambertian behavior, with lowest values near noon and highest values corresponding to low phase angles (i.e., Sun behind the observer). (3) Thermal inertia values ranged between 180 (sand dune) and 605 (bedrock-dominated material) SI units. (4) Averages across Perseverance’ traverse of albedo and thermal inertia (spatial resolution of ~3-4 m2) are in very good agreement with collocated retrievals of thermal inertia from THEMIS (spatial resolution of 100 m per pixel) and of bolometric albedo in the 0.25-2.9 μm range from (spatial resolution of ~300 km2). The results presented here are important to validate model predictions and provide ground-truth to orbital measurements.

COVID-19 caused an historic collapse in fossil fuel demand, a general decline in economic activity and hydrocarbon price volatility. This resulted in an unprecedent scenario to evaluate the contribution of the oil and gas industry (O&G) to methane (CH4) and nitrogen dioxide (NO2) emissions in the Permian basin (U.S.), currently the second largest hydrocarbon-bearing area on Earth. TROPOMI (Tropospheric Monitoring Instrument), on board the Sentinel-5P satellite, has captured the impact of the oil and gas industry during the COVID-19 lockdown. Production and drilling declined (13 % and 68 % respectively) during the lockdown, causing a generalized drop (~30 %) of NO2emissions derived using the divergence method in comparison with 2019. NO2 tropospheric columns were less impacted with a smaller decrease (~4 %) across the basins. On the other hand, the impact of the lockdown in methane (increase of 0.1 % to 0.3 % across the basins) was not as evident as in the NO2, because of the large background cause by the long lifetime (12 years), the variability of the meteorology, and the limited temporal sampling due to the strict thresholds of the retrieval algorithm. This study demonstrates that the impact of the COVID-19 lockdown on NO2 and CH4emissions was not only present in urban areas but also in vast O&G production regions, which shows the potential of TROPOMI to assess future pollution mitigation strategies for this industry.

Recent work has suggested that tropical Pacific decadal variability and external forcings have had a comparable influence on the observed changes in the Southern Hemisphere (SH) summertime eddy-driven jet over the satellite era. Here we contrast the zonally asymmetric response of the SH eddy-driven jet to tropical Pacific decadal variability using ensembles of the Community Earth System Model version 1 (CESM1) in a pacemaker framework, where sea surface temperatures (SSTA) in the tropical Pacific are nudged to observations. In both coupled and uncoupled experiments, the observed South Pacific jet intensification is found in all seasons, indicating the tropical Pacific SST cooling anomaly impacts the South Pacific jet mainly via direct atmospheric processes. By contrast, only the coupled pacemaker reproduces the South Atlantic-Indian jet poleward shift in the summertime, suggesting that the air-sea coupling is essential in driving the teleconnections between tropical Pacific SSTA and South Atlantic-Indian jet variations.

Selective water release from the deeper pools of reservoirs for energy generation alters the temperature of downstream rivers. Thermal destabilization of downstream rivers can be detrimental to riverine ecosystem by potentially disturbing the growth stages of various aquatic species. To predict this impact of planned hydropower dams worldwide, we developed, tested and implemented a framework called ‘FUture Temperatures Using River hISTory’ (FUTURIST). The framework used historical records of in-situ river temperatures from 107 dams in the U.S. to train an artificial neural network (ANN) model to predict temperature change between upstream and downstream rivers. The model was then independently validated over multiple existing hydropower dams in Southeast Asia. Application of the model over 216 planned dam sites afforded the prediction of their likely thermal impacts. Results predicted a consistent shift toward lower temperatures during summers and higher temperatures during winters. During Jun-Aug, 80% of the selected planned sites are likely to cool downstream rivers out of which 15% are expected to reduce temperatures by more than 6˚C. Reservoirs that experience strong thermal stratification tend to cool severely during warm seasons. Over the months of Dec-Feb, a relatively consistent pattern of moderate warming was observed with a likely temperature change varying between 1.0 to 4.5˚C. Such impacts, homogenized over time, raise concerns for the ecological biodiversity and native species. The presented outlook to future thermal pollution will help design sustainable hydropower expansion plans so that the upcoming dams do not face and cause the same problems identified with the existing ones.

There are records of past Earth climates that were ice-free all the way to the poles (Barron 1983), which can be described as “hothouse” climates. These hothouse climates can be contrasted with an “all-tropics” planet, where the tropics are defined by the atmospheric dynamics, i.e. the Hadley Cell extent (Faulk et al. 2017). This classification is thus primarily dependent on a planet’s rotation, rather than its ice-free extent or surface temperatures. We investigate the parameter space between Earth and an all-tropics world using the open-source GCM Isca, developed by Vallis et al (2018). We take an Earth analog and perform a parameter sweep in two dimensions: global reservoir depth (10m, 1m, 1cm) and rotation period (8 days, 4 days, 1 day). The sweep will allow us to explore the effects of surface liquid coverage and large-scale atmospheric circulation on an Earth-like climate. To better represent the distribution of surface water, we utilize the surface hydrology scheme developed by Faulk et al. (2020) for the Titan Atmosphere Model. In this presentation we provide a status report and analysis of initial findings.

In 2019 sprite observations appeared on You-Tube showing green emissions in the top of some sprites and after the main sprite. The emissions were named green ghosts. We present here similar color camera observations made on 24 and 25 May 2020 from Lamy, NM. The recordings were made at 30 fps. The green ghost increased in brightness for 3 to 4 frames after the main ‘jellyfish’ sprite and decayed thereafter. The delayed green emissions are likely from atomic oxygen at 557.7 nm, the auroral green line, which is a forbidden atomic oxygen emission with a radiative life time of 0.7 s. In the atmosphere the emissions are affected by quenching and at the altitude of the green ghost the decay time constant is substantially less. We suggest that the green ghost is generated by super thermal electrons exciting ambient atomic oxygen (only 4.1 eV required). The electrons are energized by the large-scale sprite electric field, which initially caused the sprite, and decays over some time after the sprite. We present a simple model based on this idea. The model assumes an exponentially decaying sprite E-field and reproduces the observed delayed peak in the green emissions and the subsequent decay of the emissions.

Atmospheric dust is a more extreme modifier of weather and climate on Mars than water vapor is on Earth. Global dust storms enshroud Mars in a veil of dust for months and have major implications for past and present climate, geologic history, habitability, and exploration. Yet their mysterious origins mean we remain unable to realistically simulate or predict them. In this White Paper, we find that key Knowledge Gaps are: A. how dust is lifted; B. constraints on near-surface winds and boundary-layer processes; C. the distribution of mobile surface dust; and D. the key processes and feedbacks by which dust storms begin and evolve. To make progress in the next decade, we make four Recommendations in order of priority: #1. Properly accommodate a minimum payload of meteorological and aeolian sensors on future Mars surface missions; #2. Continue orbital monitoring of the evolving surface dust distribution; #3. Expand orbital measurements to include winds and full diurnal coverage; and #4. Continue orbital monitoring and add surface measurements of aerosols during dust storms.

Solar eruptions cause geomagnetic storms in the near-Earth environment, creating spectacular aurorae visible to the human eye and invisible dynamic changes permeating all of geospace. Just equatorward of the aurora, radars and satellites often observe intense westward plasma flows called subauroral polarization streams (SAPS) in the dusk-to-midnight ionosphere. SAPS occur across a narrow latitudinal range and lead to intense frictional heating of the ionospheric plasma and atmospheric neutral gas. SAPS also generate small-scale plasma waves and density irregularities that interfere with radio communications. As opposed to the commonly observed duskside SAPS, intense eastward subauroral plasma flows in the morning sector were recently discovered to have occurred during a super storm on 20 November 2003. However, the origin of these flows termed “dawnside SAPS” could not be explained by the same mechanism that causes SAPS on the duskside and has remained a mystery. Through real-event global geospace simulations, here we demonstrate that dawnside SAPS can only occur during major storm conditions. During these times the magnetospheric plasma convection is so strong as to effectively transport ions to the dawnside, whereas they are typically deflected to the dusk by the energy-dependent drifts. Ring current pressure then builds up on the dawnside and drives field-aligned currents that connect to the subauroral ionosphere, where eastward SAPS are generated. The origin of dawnside SAPS explicated in this study advances our understanding of how the geospace system responds to strongly disturbed solar wind driving conditions that can have severe detrimental impacts on human society and infrastructure.

Intense convection (updrafts exceeding 10 m∙s-1) plays an essential role in severe weather and Earth’s energy balance. Despite its importance, how the global pattern of intense convection changes in response to warmed climates remains unclear, as simulations from traditional climate models are too coarse to simulate intense convection. Here we take advantage of a kilometer-scale global storm resolving model and conduct year-long simulations of a control run, forced by analyzed sea surface temperature (SST), and one with a 4-K increase in SST for comparison. Comparisons show that the increased SST enhances the frequency of intense convection globally with large spatial and seasonal variations. Increases in the intense convection frequency do not necessarily reflect increases in convective available potential energy (CAPE). Results are also compared with traditional climate model projections. Changes in the spatial pattern of intense convection are associated with changes in planetary circulation.