The Antarctica Peninsula (AP) has experienced more frequent and intense surface melting in recent years, jeopardizing the stability of ice shelves and ultimately leading to ice loss. Among the key phenomena that can initiate surface melting are atmospheric rivers (ARs) and leeside foehn; the combined impact of ARs and foehn led to moderate surface warming over the AP in December 2018 and record-breaking surface melting in February 2022. This study uses high-resolution Polar WRF simulations with advanced model configurations, Reference Elevation Model of Antarctica topography information, and surface observed albedo to improve our understanding of the relationship between ARs and foehn and their impacts on surface warming. With an intense AR (AR3) intrusion during the 2022 event, weak low-level blocking and heavy orographic precipitation on the upwind side resulted in latent heat release, which led to a more deep-foehn like case. On the leeside, sensible heat flux associated with the foehn magnitude was the major driver during the night and the secondary contributor during the day due to a stationary orographic gravity wave. Downward shortwave radiation was enhanced via cloud clearance, especially after the peak of the AR/foehn events, and dominated surface warming over the northeastern AP during the daytime. However, due to the complex terrain of the AP, ARs can complicate the foehn event by transporting extra moisture to the leeside via gap flows. During the peak of the 2022 foehn warming, cloud formation on the leeside hampered the downward shortwave radiation and slightly increased the downward longwave radiation.

The nighttime ionospheric response to a geomagnetic storm occurred on 23-29 September 2020 is investigated over the South American, Atlantic, and West African longitude sectors using NASA’s Global-scale Observations of the Limb and Disk (GOLD) measurements. On 27 September the solar wind conditions were favorable for prompt penetration electric fields (PPEF) to influence the equatorial ionosphere over extended longitudes. The equatorial ionization anomaly (EIA) crests were shifted 8o-10o poleward compared to the quiet time monthly mean across ~65o- 35oW during the main phase. Ionosonde hmF2 (peak electron density height) measurements from Fortaleza (GG: -3.9oN and -38.4oW) indicated a stronger prereversal enhancement this evening than other nights. As a result, Equatorial Plasma Bubbles (EPB) occurred at these longitudes on this evening. This is the first simultaneous investigation of EIA morphology and EPB occurrence rate over an extended longitude range from geostationary orbit during a geomagnetic storm.

Rotational temperatures in the Mesosphere-Lower Thermosphere region are estimated by utilizing the OH(6,2) Meinel band nightglow emission observed with an Ebert-Fastie Spectrometer (EFS) operated at Arecibo Observatory (AO), Puerto Rico (18.35oN, 66.75oW) during February-April 2005. To validate the estimated rotational temperatures, a comparison with temperatures obtained from a co-located Potassium Temperature Lidar (K-Lidar) and overhead passes of the Sounding of the Atmosphere by Broadband Emission Radiometry (SABER) instrument onboard NASA’s TIMED satellite are performed. Two types of weighting functions are applied on the K-Lidar temperatures to compare them with EFS temperatures. The first type has a fixed peak altitude and a fixed full width at half maximum (FWHM) for the whole night. In the second type, the peak altitude and FWHM vary with the local time. Average temperature difference between the EFS and K-Lidar obtained with both types of weighting functions are comparable with the previously published results from different latitude-longitude sectors. Further, it is found that temperature comparison improves when the time varying weighting functions are considered. On the other hand, we have shown that comparison of temperatures obtained from these two instruments could provide a better estimate of the OH(6,2) peak altitudes if a reference temporal trend of the OH(6,2) peak altitudes is available. Also, it is noticed that there are significant differences between the seasonal mean OH(6,2) peak altitudes obtained from SABER observation and model calculation. Such a detailed study using the AO EFS data has not previously been carried out.

Climate models still need to be improved in their capability of reproducing the present climate at both global and regional scale. The assessment of their performance depends on the datasets used as comparators. Reanalysis and gridded (homogenized or not homogenized) observational datasets have been frequently used for this purpose. However, none of these can be considered a reference dataset. Here, for the first time, using in-situ measurements from NOAA U.S. Climate Reference Network (USCRN), a network of 139 stations with high-quality instruments deployed across the continental U.S, daily temperature, and precipitation from a suite of dynamically downscaled regional climate models (RCMs; driven by ERA-Interim) involved in NA-CORDEX are assessed. The assessment is extended also to the most recent and modern widely used reanalysis (ERA5, ERA-Interim, MERRA2, NARR) and gridded observational datasets (Daymet, PRISM, Livneh, CPC). Results show that biases for the different datasets are mainly seasonal and subregional dependent. On average, reanalysis and in-situ-based datasets are generally warmer than USCRN year-round, while models are colder (warmer) in winter (summer). In-situ-based datasets provide the best performance in most of the CONUS regions compared to reanalysis and models, but still have biases in regions such as the Midwest mountains and the Northwestern Pacific. Results also highlight that reanalysis does not outperform RCMs in most of the U.S. subregions. Likewise, for both reanalysis and models, temperature and precipitation biases are also significantly depending on the orography, with larger temperature biases for coarser model resolutions and precipitation biases for reanalysis.

The prevalence of mixing vs. precipitation processes in biomass burning aerosol (BBA) laden air over the southeast Atlantic is assessed during three intensive observation periods during the NASA ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) campaign. Air in the lower free troposphere (FT) and marine boundary layer (MBL) are treated as separate analyses, although connections are made where relevant. The study, centering on aircraft in-situ measurements of total water heavy isotope ratios, has two main objectives. The first is to gauge whether the atmospheric hydrology, and in particular precipitation, can be constrained primarily through visual assessment of the aircraft isotope ratio data plotted against total water concentration, similarly to several previous studies. However, regression of the data onto a simple model of convective detrainment is also used and alludes to the possibility of a precipitation data product derived from isotope ratios. The second objective is to connect variations in aerosol concentrations to the hydrology as diagnosed by the isotope ratio measurements, and determine whether aerosol variations are attributable to wet scavenging. First, joint water concentration (q) and H2O/HDO isotope measurements (δD) in the lower FT are combined with satellite and MERRA-2 data into simple analytical models to constrain hydrologic histories of BBA-laden air originating over Africa and flowing over the southeast Atlantic. We find that even simple models are capable of detecting and constraining the primary processes at play. Further, a strong correlation between isotopic evidence of precipitation in lower FT air masses and an in-situ indicator of wet scavenging of black carbon – the ratio of black carbon to carbon monoxide (BC/CO) – is shown. In comparison, the correlation between BC/CO and the water concentration itself is low. Since wet scavenging is the primary removal mechanism of black carbon, these findings suggest that isotope measurements could support studies constraining the lifetime of black carbon in the FT. Next, the ability of measurements interpreted with simple analytical models in (q, δD) space to distinguish cloud-top entrainment vs. precipitation signals in the MBL is tested. This proves more difficult than the lower FT analysis since signals are smaller. We find that the largest obstacle to this goal is the (q, δD) values of the entrained airmass at cloud-top. We also compare cloud condensation nuclei (CCN) concentrations in the sub-cloud layer to the isotopic measurements. In 2016 and 2018 IOPs, lower CCN concentrations coincide with isotope ratio evidence of precipitation, indicating aerosol scavenging. However, a more complex model simulating water, isotope ratios, and aerosols would be necessary to achieve more definitive conclusions. For the 2017 IOP, with the highest sub-cloud CCN concentrations, there is no connection between precipitation signals and CCN concentrations.

We show the first achievement of inferring the electron temperature in ionospheric conditions from synthetic data using fixed-bias Langmuir probes operating in the electron saturation region. This was done by using machine learning and altering the probe geometry. The electron temperature is inferred at the same rate as the currents are sampled by the probes. For inferring the electron temperature along with the electron density and the floating potential, a minimum number of three probes is required. Furthermore does one probe geometry need to be distinct from the other two, since otherwise the probe setup may be insensitive to temperature. This can be achieved by having either one shorter probe or a probe of a different geometry, e.g. two longer and a shorter cylindrical probe or two cylindrical probes and a spherical probe. We use synthetic plasma parameter data and calculate the synthetic collected probe currents to train a neural network and verify the results with a test set. We additionally verify the validity of the inferred temperature in altitudes ranging from about 100 km-500 km, using data from the International Reference Ionosphere model. Even minor changes in the probe sizing enable the temperature inference and result in root mean square relative errors between inferred and ground truth data of under 3%. When limiting the temperature inference to 120-450 km altitude an RMSRE of under 0.7% is achieved for all probe setups. In future, the multi-needle Langmuir Probe instrument dimensions can be adapted for higher temperature inference accuracy.

During the last ice age, the western United States was covered by large lakes, sustained partly by higher levels of precipitation. Increased rainfall was driven by the atmospheric circulation associated with the presence of large North American ice sheets, yet Pleistocene lakes generally reached their highstands not at glacial maximum but during deglaciation. Prior modeling studies, however, showed nearly monotonic drying since the last glacial maximum. Here I show that iTraCE, a new transient climate simulation of the last deglaciation, reproduces a robust peak in winter rainfall over the Great Basin near 16 ka. The simulated peak is driven by a transient strengthening and southward shift of the midlatitude jet. While meltwater forcing is an important driver of changes to the North Pacific Jet, changing orbital conditions and rising atmospheric CO2 also shift the jet south and contribute to wetter conditions over the western US during deglaciation.

On December 04, 2021, a total solar eclipse occurred over west Antarctica. Nearly an hour beforehand, a geomagnetic substorm onset was observed in the northern hemisphere. Eclipses are suggested to influence magnetosphere-ionosphere (MI) coupling dynamics by altering the conductivity structure of the ionosphere by reducing photoionization. This sudden and dramatic change in conductivity is not only likely to alter global MI coupling, but it may also introduce a variety of localized instabilities that appear in both hemispheres. Global navigation satellite system (GNSS) based observations of the total electron content (TEC) in the southern high latitude ionosphere during the December 2021 eclipse show signs of wave activity coincident with the eclipse peak totality. Ground magnetic observations in the same region show similar activity, and our analysis suggest that these observations are due to an “eclipse effect” rather than the prior substorm. We present the first multi-point interhemispheric study of a total south polar eclipse with local TEC observational context in support of this conclusion.

We test the application of a rare event simulation algorithm to accelerate the sampling of extreme winter rainfall over Europe in a climate model. The genealogical particle analysis algorithm, an ensemble method that interrupts the simulation at intermediate times to clone realizations in which an extreme event is developing, is applied to the intermediate complexity general circulation model PlaSim. We show that the algorithm strongly reduces the numerical effort required to estimate probabilities of extremes, demonstrating the potential of rare event simulation of seasonal precipitation extremes.

Our longest, stable record of cloud-top pressure (CTP) and cloud-top height (CTH) are derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Multi-Angle Imaging Spectroradiometer (MISR) on Terra. Because of single cloud-layer assumptions in their standard algorithms, they provide only single CTP/CTH retrievals in multi-layered situations. In the predominant multi-layered regime of thin cirrus over low clouds, MODIS significantly overestimates cirrus CTP and emissivity, while MISR accurately retrieves low-cloud CTH. Utilizing these complementary capabilities, we develop a retrieval algorithm for accurately determining both-layer CTP and cirrus emissivity for such 2-layered clouds, by applying the MISR low-cloud CTH as a boundary condition to a modified MODIS CO2-slicing retrieval. We evaluate our 2-layered retrievals against collocated Cloud-Aerosol Transport System (CATS) lidar observations. Relative to CATS, the mean bias of the upper cloud CTP and emissivity are reduced by ~90% and ~75% respectively in the new technique, compared to standard MODIS products. We develop an error model for the 2-layered retrieval accounting for systematic and random errors. We find up to 88% of all residuals lie within modeled 95% confidence intervals, indicating a near-closure of error budget. This reduction in error leads to a reduction in modeled atmospheric longwave radiative flux biases ranging between 5-40 Wm-2, depending on the position and optical properties of the layers. Given this large radiative impact, we recommend that the pixel-level 2-layered MODIS+MISR fusion algorithm be applied over the entire MISR swath for the 22-year Terra record, leading to a first-of-its-kind 2-layered cloud climatology from Terra’s morning orbit.

Many chemical processes depend non-linearly on temperature. Gravity-wave-induced temperature perturbations have been previously shown to affect atmospheric chemistry, but accounting for this process in chemistry-climate models has been a challenge because many gravity waves have scales smaller than the typical model resolution. Here, we present a method to account for subgrid-scale orographic gravity-wave-induced temperature perturbations on the global scale for the Whole Atmosphere Community Climate Model (WACCM). The method consists of deriving the temperature perturbation amplitude $\hat{T}$ consistent with the model’s subgrid-scale gravity wave parametrization, and imposing $\hat{T}$ as a sinusiodal temperature perturbation in the model’s chemistry solver. Because of limitations in the gravity wave parameterization, scaling factors may be necessary to maintain a realistic wave amplitude. We explore scaling factors between 0.6 and 1 based on comparisons to altitude-dependent $\hat{T}$ distributions in two observational datasets. We probe the impact on the chemistry from the grid-point to global scales, and show that the parametrization is able to represent mountain wave events as reported by previous literature. The gravity waves for example lead to increased surface area densities of stratospheric aerosols. This in turn increases chlorine activation, with impacts on the associated chemical composition. We obtain large local changes in some chemical species (e.g., active chlorine, NOx, N2O5) which are likely to be important for comparisons to airborne or satellite observations, but find that the changes to ozone loss are more modest. This approach enables the chemistry-climate modeling community to account for subgrid-scale gravity wave temperature perturbations in a consistent way.

In-situ measurements from the Magnetospheric Multiscale (MMS) mission are used to estimate electron density from spacecraft potential and investigate compressive turbulence in the Earth’s magnetosheath. During the MMS Solar Wind Turbulence Campaign in February 2019, the four MMS spacecraft were arranged in a logarithmic line constellation enabling the study of measurements from multiple spacecraft at varying distances. We estimate the electron density from spacecraft potential for a time interval in which the ion emitters actively control the potential. The derived electron density data product has a higher temporal resolution than the plasma instruments, enabling the examination of fluctuation for scales down to the sub-ion range. The inter-spacecraft separations range from 132 km to 916 km; this corresponds to scales of 3.5 to 24.1 ion inertial lengths. The derived density and magnetic field data are used to study fluctuations in the magnetosheath through time lags on a single spacecraft and spatial lags between pairs of spacecraft over almost one decade in scale. The results show an increase in anisotropy as the scale decreases.

Deforestation alters the exchange of heat, moisture, and momentum between the Earth's surface and the atmosphere, which can significantly affect the surface energy balance and water budget. However, changes in surface heat fluxes in response to deforestation are diverse among multi-model simulations. Changes in surface heat fluxes may lead to further energy partitioning and different land-atmosphere interactions. This study explores factors that might cause different changes in surface fluxes under tropical deforestation. The mediating effect of the Bowen ratio on changes in turbulent surface fluxes in response to the removal of tropical rainforests is examined with the Community Earth System Model of the National Center for Atmospheric Research. Different flux partitioning in the mean state of the Bowen ratio is associated with various flux changes under deforestation. When the mean Bowen ratio is smaller, deforestation tends to increase sensible heat fluxes and reduce latent heat fluxes. Our research further indicates that the simulated mean-state Bowen ratios in the Land Use Model Intercomparison Project model archive might modulate changes in surface heat fluxes that provide some clues for the land surface model developments.

Large-scale convection associated with the Madden-Julian Oscillation (MJO) initiates over the Indian Ocean and propagates eastward across the Maritime Continent (MC). Over the MC, MJO events are generally weakened due to complex interactions between the large-scale MJO and the MC landmass. The MC barrier effect is responsible for the dissipation of 40-50\% of observed MJO events and is often exaggerated in weather and climate models. We examine how MJO propagation over the MC is affected by two aspects of the MC - its land-sea contrast and its terrain. To isolate the effects of mountains and land-sea contrast on MJO propagation, we conduct three high-resolution coupled atmosphere-ocean model experiments: 1) control simulation (CTRL) of the 2011 November-December MJO event, 2) flattened terrain without MC mountains (FLAT), and 3) no-land simulation (WATER) in which the MC islands are replaced with 50 m deep ocean. CTRL captures the general properties of the diurnal cycle of precipitation and MJO propagation across the MC. The WATER simulation produces a more intense and smoother-propagating MJO compared with that of CTRL. In contrast, the FLAT simulation produces much more convection and precipitation over land (without mountains) than CTRL, which results in a stronger barrier effect on MJO propagation. The land-sea contrast induced land-locked convection weakens the MJO’s convective organization. The land-locked convective systems over land in FLAT are more intense, grow larger, and last longer, which is more detrimental to MJO propagation over the MC, than the mountains that are present in CTRL.

The results of a study aimed at assessing the utility of transionospheric 35 MHz scintillation measurements toward cosmic radio sources for estimating the level of spatial coherence in high frequency (HF) skywave systems are presented. This was done using an array of four antennas in southern Maryland called the Deployable Low-band Ionosphere and Transient Experiment (DLITE). Two of the antennas within a ~350-m north/south baseline were used to monitor 35-MHz intensity variations of two bright cosmic sources, Cynus A and Cassiopeia A. The other two antennas, which were within a ~420-m east/west baseline, recorded the 7.85 MHz skywave from the CHU radio station near Ottawa, Ontario. These HF measurements were used to quantify the level of spatial coherence by measuring the amplitudes of the cross correlation of the two antennas’ recorded voltages relative to the received power, which were typically ~0.5-0.9, but occasionally near zero. A method was developed to estimate the expected cross-correlation amplitude based on the 35-MHz scintillations. This method assumes the case of weak scattering, which is generally appropriate for mid-latitudes, and that the irregularity distribution follows that of the background electron density. These calculations typically captured the day-to-day variations in spatial coherence quite well (correlation coefficient r≈0.6) while only marginally reproducing hour-to-hour variations (r≈0.2). Thus, this method holds promise as an economical and passive means to assess the spatial coherence expected for skywave propagation within a given mid-latitude region.

El Niño-Southern Oscillation (ENSO) is the most prominent interannual climate variability in the tropics and exhibits diverse features in spatiotemporal patterns. This paper develops a simple multiscale intermediate coupled stochastic model to capture the ENSO diversity and complexity. The model starts with a deterministic and linear coupled interannual atmosphere, ocean, and sea surface temperature (SST) system. It can generate two dominant linear solutions representing the eastern Pacific (EP) and the central Pacific (CP) El Niños, respectively. In addition to adopting a stochastic model for characterizing the intraseasonal wind bursts, another simple stochastic process is developed to describe the decadal variation of the background Walker circulation. The latter links the two dominant modes in a simple nonlinear fashion and advances the modulation of the strength and occurrence frequency of the EP and the CP events. Finally, cubic nonlinear damping is adopted to parameterize the relationship between subsurface temperatures and thermocline depth. The model succeeds in reproducing the spatiotemporal dynamical evolution of different types of ENSO events. It also accurately recovers the strongly non-Gaussian probability density function, the seasonal phase locking, the power spectrum, and the temporal autocorrelation function of the SST anomalies in all the three Niño regions (3, 3.4 and 4) across the equatorial Pacific. Furthermore, both the composites of the SST anomalies for various ENSO events and the strength-location bivariate distribution of equatorial Pacific SST maxima for the El Niño events from the model simulation highly resemble those from the observations.

Jet streams are important sources of non-orographic internal gravity waves and clear air turbulence (CAT). We analyze non-orographic gravity waves and CAT during a merging of the polar front jet stream (PFJ) with the subtropical jet stream (STJ) above the southern Atlantic. Thereby, we use a novel combination of airborne observations covering the meso-scale and turbulent scale in combination with high-resolution deterministic short-term forecasts. Coherent phase fronts stretching along a highly sheared tropopause fold are found in the ECMWF IFS (integrated forecast system) forecasts. During the merging event, the PFJ reverses its direction from antiparallel to parallel with respect to the STJ, going along with strong wind shear and horizontal deformation. Temperature perturbations in limb-imaging and lidar observations onboard the research aircraft HALO in the framework of the SouthTRAC campaign show remarkable agreement with the IFS data. Ten hours earlier, the IFS data show a new “X-shaped” phase line pattern emanating from the sheared tropopause fold. The analysis of tendencies in the IFS wind components shows that these gravity waves are excited by a local body force as the PFJ impinges the STJ. In situ observations of temperature and wind components at 100 Hz confirm upward propagation of the probed portion of the gravity waves. They furthermore reveal embedded episodes of light-to-moderate CAT, Kelvin Helmholtz waves, and indications for partial wave reflection. Patches of low gradient Richardson numbers in the IFS data coincide with episodes where CAT was observed, suggesting that this event was well accessible to turbulence forecasting.

We investigate a set of Energy Exascale Earth System Model Multi-scale Modeling Framework (E3SM-MMF) simulations that vary the dimensionality and momentum transport configurations of the embedded cloud-resolving models (CRMs), including unusually ambitious 3D configurations. Issues endemic to all MMF simulations include too much ITCZ rainfall and too little over the Amazon. Systematic MMF improvements include more on-equatorial rainfall across the Warm Pool. Interesting sensitivities to CRM domain are found in the regional time-mean precipitation pattern over the tropics. The 2D E3SM-MMF produces an unrealistically rainy region over the northwestern tropical Pacific; this is reduced in computationally ambitious 3D configurations that use 1024 embedded CRM grid columns per host cell. Trajectory analysis indicates that these regional improvements are associated with desirably fewer tropical cyclones and less extreme precipitation rates. To understand why and how the representation of precipitation improved in 3D, we propose a framework that dilution is stronger in 3D. This viewpoint is supported by multiple indirect lines of evidence, including a delayed moisture-precipitation pickup, smaller precipitation efficiency, and amplified convective mass flux profiles and more high clouds. We also demonstrate that the effects of varying embedded CRM dimensionality and momentum transport on precipitation can be identified during the first few simulated days, providing an opportunity for rapid model tuning without high computational cost. Meanwhile the results imply that other less computationally intensive ways to enhance dilution within MMF CRMs may also be strategic tuning targets.