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Abstract

Sea surface temperature (SST) anomalies over the North Tropical Atlantic (NTA) during the early boreal spring can trigger El Niño-Southern Oscillation (ENSO) events in the following boreal winter. However, the future changes in the impact of the NTA on ENSO remain controversial. Here, we show distinct changes in the strength of the NTA−ENSO relationship due to global warming by comparing models from the Coupled Model Intercomparison Project (CMIP) 5 and CMIP6. The impact of the NTA on ENSO under greenhouse warming is notably enhanced in CMIP6 compared to CMIP5. A wetter mean state over the subtropical eastern North Pacific and increased oceanic sensitivity over the equatorial central Pacific are key factors that enhance the impact of the NTA SST on ENSO. Therefore, differences in the mean state under greenhouse warming between the CMIP5 and CMIP6 models can modulate the strength of the NTA−ENSO relationship.

Abstract

The Surface Water and Ocean Topography (SWOT) mission provides a good opportunity to study fine-scale processes in the global ocean but whether it can detect balanced submesoscale eddies is uncertain due to the “contamination” by unbalanced inertial gravity waves. Here, based on concurrent observations from SWOT and a mooring array in the northwestern Pacific, we successfully captured two submesoscale cyclonic eddies with negative sea level anomalies (SLAs) in spring 2023. We find that the SLA amplitude and equivalent radius of the first (second) eddy are 2.5 cm and 16.0 km (2.0 cm and 18.8 km), respectively. For both eddies, their vertical scales are around 150 m and their horizontal velocities and Rossby numbers exceed 15.0 cm/s and 0.4, respectively. Further analysis suggests that similar submesoscale eddies can commonly occur in the northwestern Pacific and that SWOT is capable to detect larger submesoscale eddies with scales greater than ∼10 km.

Abstract

In this study, we evaluated the performance of machine learning (ML) models (XGBoost) in predicting low-cloud fraction (LCF), compared to two generations of the community atmospheric model (CAM5 and CAM6) and ERA5 reanalysis data, each having a different cloud scheme. ML models show a substantial enhancement in predicting LCF regarding root mean squared errors and correlation coefficients. The good performance is consistent across the full spectrums of atmospheric stability and large-scale vertical velocity. Employing an explainable ML approach, we revealed the importance of including the amount of available moisture in ML models for representing spatiotemporal variations in LCF in the midlatitudes. Also, ML models demonstrated marked improvement in capturing the LCF variations during the stratocumulus-to-cumulus transition (SCT). This study suggests ML models' great potential to address the longstanding issues of “too few” low clouds and “too rapid” SCT in global climate models.

Abstract

The impact of land variables on temperature forecasts in atmospheric cycling is often underestimated or overlooked. This oversight primarily occurs due to the abundance of meteorological measurements available for assimilation and partly because soil states are assumed to be quickly reset by atmospheric forcing, such as precipitation, justifying no spin-ups or no updates of soil states during cycling. In this study, by updating soil moisture every 6 hr using different analysis data sets for May 2019, considerable discrepancies were found, highlighting large uncertainties in soil moisture analysis. Different soil moisture analyses produced systematically different temperature forecasts, with errors growing over cycles to be comparable to a typical error magnitude of 2-m temperature observations (∼2°K). This study demonstrates that temperature forecasts are significantly influenced by whether and how soil moisture is updated, not only near the surface but also up to the low-mid troposphere and throughout the cycles.

Abstract

Variations in southern African precipitation have a major impact on local communities, increasing climate-related risks and affecting water and food security, as well as natural ecosystems. However, future changes in southern African precipitation are uncertain, with climate models showing a wide range of responses from near-term projections (2020–2040) to the end of the 21st century (2080–2100). Here, we assess the uncertainty in southern African precipitation change using five Ocean-Atmosphere General Circulation single model initial-condition large ensembles (30–50 ensemble members) and four emissions scenarios. We show that the main source of uncertainty in 21st Century projections of southern African precipitation is the internal climate variability. In addition, we find that differences between ensemble members in simulating future changes in the location of the Angola Low explain a large proportion (∼60%) of the uncertainty in precipitation change. Together, the internal variations in the large-scale circulation over the Pacific Ocean and the Angola Low explain ∼64% of the uncertainty in southern African precipitation change. We suggest that a better understanding of the future evolutions of the southern African precipitation may be achieved by understanding better the model's ability to simulate the Angola Low and its effects on precipitation.

Abstract

Interplanetary (IP) shocks are perturbations observed in the solar wind. IP shocks correlate well with solar activity, being more numerous during times of high sunspot numbers. Earth-bound IP shocks cause many space weather effects that are promptly observed in geospace and on the ground. Such effects can pose considerable threats to human assets in space and on the ground, including satellites in the upper atmosphere and power infrastructure. Thus, it is of great interest to the space weather community to (a) keep an accurate catalog of shocks observed near Earth, and (b) be able to forecast shock occurrence as a function of the solar cycle (SC). In this work, we use a supervised machine learning regression model to predict the number of shocks expected in SC25 using three previously published sunspot predictions for the same cycle. We predict shock counts to be around 275 ± 10, which is ∼47% higher than the shock occurrence in SC24 (187 ± 8), but still smaller than the shock occurrence in SC23 (343 ± 12). With the perspective of having more IP shocks on the horizon for SC25, we briefly discuss many opportunities in space weather research for the remainder years of SC25. The next decade or so will bring unprecedented opportunities for research and forecasting effects in the solar wind, magnetosphere, ionosphere, and on the ground. As a result, we predict SC25 will offer excellent opportunities for shock occurrences and data availability for conducting space weather research and forecasting.

No abstract is available for this article.

Abstract

This study investigates the effects of sea spray on extreme precipitation forecast in Beijing of China between 28 July and 2 August 2023 as a case test. In this case, fully coupled model increased upward moisture in the Bohai and Yellow Seas and increased accumulated rainfall by 21% in North China. For the extreme precipitation events with the 5-day accumulated precipitation exceeding 500 mm, the atmosphere-only model did not forecast the events; the coupled model without sea spray performed well with the 0.29 threat score (TS) and 88 mm root mean square error (RMSE); in the fully coupled model, the effects of sea spray increased atmospheric instability, which increased the precipitation around Beijing and yielded a more accurate forecast with the 0.37 TS and 65 mm RMSE. This paper suggests a scientific clue to improve numerical simulation for extreme rainfall events, however, more cases are still needed for statistical evaluation.

Abstract

Although solar wind-driven convection is expected to dominate magnetospheric circulation at Mercury, its exact pattern remains poorly characterized by observations. Here we present BepiColombo Mio observations during the third Mercury flyby indicative of convection-driven transport of low-energy dense ions into the deep magnetosphere. During the flyby, Mio observed an energy-dispersed ion population from the duskside magnetopause to the deep region of the midnight magnetosphere. A comparison of the observations with backward test particle simulations suggests that the observed energy dispersion structure can be explained in terms of energy-selective transport by convection from the duskside tail magnetopause. We also discuss the properties and origins of more energetic ions observed in the more dipole-like field regions of the magnetosphere in comparison to previously reported populations of the plasma sheet horn and ring current ions. Additionally, forward test particle simulations predict that most of the observed ions on the nightside will precipitate onto relatively low-latitude regions of the nightside surface of Mercury for a typical convection case. The presented observations and simulation results reveal the critical role of magnetospheric convection in determining the structure of Mercury's magnetospheric plasma. The upstream driver dependence of magnetospheric convection and its effects on other magnetospheric processes and plasma-surface interactions should be further investigated by in-orbit BepiColombo observations.

Abstract

The heliosphere is full of galactic cosmic rays (GCR), high-energy charged particles coming isotropically from the galaxy. The GCR interact with the solar wind blown by the Sun carrying out plasma, magnetic fields and transient structures such as interplanetary coronal mass ejections (ICMEs) and their associated magnetic flux ropes (MFR). The GCR interaction with ICMEs has been extensively studied particularly the GCR flux attenuation (known as Forbush decreases) as a result of interacting with the ICME sheath and magnetic field. In this work, we investigate the opposite effect: the MFR's ability to generate GCR anisotropies which an observer may detect as an increase in the GCR flux. To achieve this, we simulated a flux of protons with energies in the 10–160 GeV range arriving from all directions to a cylindrical MFR (with and without sheath) with plasma, magnetic field, and spatial dimensions found in average ICMEs observed at 1 au. By following the individual trajectories of the injected particles we found that the MFR deviates the charged particles preferentially in one direction parallel to the MFR–axis. We also found that the peak of this anisotropic GCR flux depends on: the angle between the MFR and ambient magnetic fields; the presence or not of the sheath region; the energy of the incident particles and the observer location inside the MFR.

Abstract

The migrating diurnal tide (DW1) is derived by fitting Hough Mode Extensions to the TIMED/TIDI near-global wind measurements within the mesosphere and lower thermosphere between 85 and 100 km from 2004 to 2014. The tidal amplitude peaks around the equinoxes with a large interannual variability of up to 50%. The correlation coefficients between the tidal amplitude variability and the solar cycle as represented by F10.7, stratospheric Quasi-Biennial Oscillation (QBO), and El Niño-Southern Oscillation (ENSO) are calculated every 10 days revealing seasonal dependencies. The interannual variability is positively correlated with QBO from spring to fall, maximizing around the equinoxes; anti-correlated to the solar cycle in early winter; and anti-correlated to ENSO in early winter and slightly in March. Multivariate linear regressions are performed to quantitatively analyze the linear relationships between the DW1 amplitude and those factors. The fittings perform best with the QBO at 30 and 50 hPa both being considered. The contribution of QBO peaks around January and October may be related to the polar vortex modulated by QBO in the northern and southern hemispheres, respectively. The correlation between the DW1 amplitude and ENSO is negative with time lags <∼5 months during early winter and spring.

Abstract

The impact of upstream conditions on magnetopause reconnection has been an intriguing question in solar wind-magnetosphere coupling. In this study, we conduct a statistical analysis of plasma properties in the reconnection outflow region and the associated upstream solar wind/magnetosheath. We observe that the normalized ion density (N/N sw ) decreases and the flow speed (V/V sw ) increases in the upstream magnetosheath with distance from the subsolar point, consistent with previous models and observations. The magnetic field strength (|B|), ion density (N), and ion bulk speed (|V|) in the upstream magnetosheath exhibit close correlations with those in the reconnection outflow region. This upstream-downstream correlation likely arises from the process of forming reconnection outflows, where most upstream ions cross the separatrix and mix with ion outflow already accelerated near the X-line. High-speed part of reconnection outflow is mostly located on the magnetosphere side of the magnetopause current layer, with outflow velocities peaking close to the upstream magnetosheath Alfvén speed. The spatial extent of high-speed outflow is greater in conditions of lower solar wind Alfvén Mach number (M A,sw ). Additionally, the southward magnetic field in the magnetosheath and |B| of magnetopause current layer are larger in the cases of lower M A,sw . These findings indicate a close connection of plasma properties between the outflow region of magnetopause reconnection and the upstream magnetosheath.

Abstract

We investigate the unique magnetosphere of Uranus and its interaction with the solar wind. Following the work of Masters (2014), https://doi.org/10.1002/2014ja020077 and others, we developed and validated a simple yet valuable and illustrative model of Uranus' offset, tilted, and rapidly-spinning magnetic field and magnetopause (nominal and fit to the Voyager-2 inbound crossing point) in three-dimensional space. With this model, we investigated details of the seasonal and interplanetary magnetic field (IMF) orientation dependencies of dayside and flank reconnection along the Uranian magnetopause. We found that anti-parallel (magnetic field shear angle greater than 170°) reconnection occurs nearly continuously along the Uranian dayside and/or flank magnetopause under all seasons of the 84 (Earth) year Uranian orbit and the most likely IMF orientations. Such active and continuous driving of the Uranian magnetosphere should result in constant loading and unloading of the Uranian magnetotail, which may be further complicated and destabilized by sudden changes in the IMF orientation and solar wind conditions plus the reconfigurations from the rotation of Uranus itself. We demonstrate that unlike the other magnetospheric systems that are Dungey-cycle driven (i.e., Mercury and Earth) or rotationally driven (Jupiter and Saturn), global magnetospheric convection of plasma, magnetic flux, and energy flow may occur via three distinct cycles, two of which are unique to Uranus (and possibly also Neptune). Our simple model is also used to map signatures of dayside and flank reconnection down to the Uranian ionosphere, as a function of planetary latitude and longitude. Such mapping demonstrates that “spot-like” auroral features should be very common on the Uranian dayside, consistent with observations from Hubble Space Telescope. We further detail how the combination of Uranus' rapid rotation and unique and very active global magnetospheric convection should be consistent with fueling of the surprisingly intense trapped radiation environment observed by Voyager-2 during its single flyby. Summarizing, Uranus is a very interesting magnetosphere that offers new insights on the nature, complexity, and diversity of planetary magnetospheric systems and the acceleration of particles in space plasmas, which might have important analogs to exoplanetary magnetospheric systems. Our hypotheses can be tested with further work involving more advanced models, new auroral observations, and unprecedented missions to explore the in situ environment from orbit around Uranus, which should include a complement of magnetospheric instruments in the payload.

Abstract

It has been hypothesized that the olivine- and carbonate-bearing units within Jezero crater are part of the broader olivine-carbonate rock unit found in the Nili Fossae region. Further, it is commonly proposed that olivine and carbonate are closely associated with each other in Jezero crater based on visible/near-infrared spectral data. In this work, we investigate the olivine- and carbonate-rich units in Jezero crater using spectral, thermophysical, and morphological analyses to determine the relationship between olivine- and carbonate-rich units. Thermal infrared spectral data indicate largely weak to absent olivine signatures in the marginal carbonates. Our analyses suggest a decoupled relationship between olivine and carbonate in Jezero. The distinct appearances of olivine and carbonate in Jezero crater compared to the regional olivine-carbonate rocks in Nili Fossae may imply unique formation mechanisms for olivine and carbonate in Jezero or variable levels of olivine alteration across the broader region.

Probabilistic flood inundation mapping through copula Bayesian multi-modeling of precipitation products
Francisco Javier Gomez, Keighobad Jafarzadegan, Hamed Moftakhari, and Hamid Moradkhani
Nat. Hazards Earth Syst. Sci., 24, 2647–2665, https://doi.org/10.5194/nhess-24-2647-2024, 2024
This study utilizes the global copula Bayesian model averaging technique for accurate and reliable flood modeling, especially in coastal regions. By integrating multiple precipitation datasets within this framework, we can effectively address sources of error in each dataset, leading to the generation of probabilistic flood maps. The creation of these probabilistic maps is essential for disaster preparedness and mitigation in densely populated areas susceptible to extreme weather events.

Quantitative Error Analysis on Polarimetric Phased Array Radar Weather Measurements to Reveal Radar Performance and Configuration Potential
Junho Ho, Zhe Li, and Guifu Zhang
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2024-118,2024
Preprint under review for AMT (discussion: open, 0 comments)
This study quantitatively analyzes and compares weather measurements from planar (PPPAR) and cylindrical polarimetric phased array radars (CPPAR). It examines data quality, potential problems, and clarifies misunderstandings between the configurations. The findings highlight 2D PPPAR’s challenges in making accurate weather measurements when the beam steers off broadside. CPPAR shows promise in obtaining high-quality polarimetric data because of its azimuthal scan invariant beam characteristics.

Abstract

In this study, we employ the Conformal Cubic Atmospheric Model (CCAM), a variable-resolution global atmospheric model, driven by two distinct sea surface temperature (SST) data sets: the 0.25° Optimum Interpolation Sea Surface Temperature (CCAM_OISST) version 2.1 and the 2° Extended Reconstruction SSTs Version 5 (CCAM_ERSST5). Model performance is assessed using a benchmarking framework, revealing good agreement between both simulations and the climatological rainfall spatial pattern, seasonality, and annual trends obtained from the Australian Gridded Climate Data (AGCD). Notably, wet biases are identified in both simulations, with CCAM_OISST displaying a more pronounced bias. Furthermore, we have examined CCAM’s ability to capture El Niño-Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) correlations with rainfall during Austral spring (SON) utilizing a novel hit rate metric. Results indicate that only CCAM_OISST successfully replicates observed SON ENSO- and IOD-rainfall correlations, achieving hit rates of 86.6% and 87.5%, respectively, compared to 52.7% and 41.8% for CCAM_ERSST5. Large SST differences are found surrounding the Australian coastline between OISST and ERSST5 (termed the “Coastal Effect”). Differences can be induced by the spatial interpolation error due to the discrepancy between model and driving SST. An additional CCAM experiment, employing OISST with SST masked by ERSST5 in 5° proximity to the Australian continent, underscores the “Coastal Effect” has a significant impact on IOD-Australian rainfall simulations. In contrast, its influence on ENSO-Australian rainfall is limited. Therefore, simulations of IOD-Australian rainfall teleconnection are sensitive to local SST representation along coastlines, probably dependent on the spatial resolution of driving SST.

Abstract

In August 2017, a smoke plume from wildfires in British Columbia and the Northwest Territories recirculated and persisted over northern Canada for over two weeks. We compared a full-factorial set of NASA Goddard Institute for Space Studies ModelE simulations of the plume to satellite retrievals of aerosol optical depth and carbon monoxide, finding that ModelE performance was dependent on the model configuration, and more so on the choice of injection height approach, aerosol scheme and biomass burning emissions estimates than to the choice of horizontal winds for nudging. In particular, ModelE simulations with free-tropospheric smoke injection, a mass-based aerosol scheme and comparatively high fire NOx emissions led to unrealistically high aerosol optical depth. Using paired simulations with and without fire emissions, we estimated that for 16 days over an 850,000 km2 region, the smoke decreased planetary boundary layer heights by between 253 and 547 m, decreased downward shortwave radiation by between 52 and 172 Wm−2, and decreased surface temperature by between 1.5°C and 4.9°C, the latter spanning an independent estimate from operational weather forecasts of a 3.7°C cooling. The strongest surface climate effects were for ModelE configurations with more detailed aerosol microphysics that led to a stronger first indirect effect.

Abstract

Satellite remote sensing of aerosol is largely conducted at moderate or coarse spatial resolution around 1–10 km. Nevertheless, at urban areas with high human activity, aerosol can originate from complex emission sources and may also vary strongly in space. Therefore, aerosol characterization at fine spatial resolution is essential for air quality study and assessment of anthropogenic pollution as well as climate effects. However, space-borne instruments with high spatial resolution are usually limited in swath width or spectral coverage which result in lowering information content required for aerosol and surface retrieval. Based on the Generalized Retrieval of Atmosphere and Surface Properties (GRASP) algorithm, we propose a hybrid approach by combining fine and coarse spatial resolution measurements to retrieve aerosol and surface properties simulataneously at fine spatial resolution. The instruments with coarse spatial resolution and high revisting time can provide advanced aerosol characterization. At the same time, the instruments with fine spatial resolution are sensitive to spatial variability of aerosol nearby sources. In this study, the GRASP/Hybrid approach is demonstrated and tested based on the European Space Agency Sentinel-5p/TROPOMI together with the Italian Space Agency PRISMA satellite data. Specifically, the detailed aerosol microphysical properties from Sentinel-5p/TROPOMI 10 km retrievals are used as a priori information for PRISMA to derive aerosol loading and surface properties at 100 meter (m) spatial resolution. The PRISMA 100 m aerosol and surface retrieval based on the developed GRASP/Hybrid approach are evaluated using available ground-based and satellite measurements, including AERONET, VIIRS/DB aerosol and PRISMA Level 2 surface reflectance products.

Abstract

The Paluch diagram is a widely used tool for interpreting aircraft measurements of shallow cumulus clouds. A prior study conducted by Heus et al. (2008, https://doi.org/10.1175/2008jas2572.1) concluded that the source levels of in-cloud air inferred from the Paluch diagram exhibit biases, sometimes of several hundred meters, in comparison to those derived from Lagrangian particle tracking. In this short study we revisit this comparison. The results indicate that the upper source levels of in-cloud air determined from the Lagrangian Particle Tracking and the Paluch diagram are consistent, and the choice of statistical methods is crucial. The significance of this research lies in confirming the reliability of the Paluch analysis, enabling its confident application to aircraft data.