Volcanic aerosols over south east Asia have always been the trigger and sustaining cause of ENSO events. In recent decades this natural plume has been augmented by the anthropogenic plume which has intensified ENSO events especially in SON. Data from the Last Millennium Ensemble (13,972 months), and Large Ensemble (3,012 months) demonstrate this connection with three ENSO indices and aerosol data derived from the same datasets correlating at 1.00 (LME), 0.97 and 0.99 magnitude (segmented and averaged). ENSO events are the dominant mode of variability in the global climate responsible for Australian, Indian and Indonesian droughts, American floods and increased global temperatures. Understanding the mechanism which enables aerosols over SE Asia and only over SE Asia to create ENSO events is crucial to understanding the global climate. I show that the South East Asian aerosol Plume causes ENSO events by: reflecting/absorbing solar radiation which warms the upper troposphere; and reducing surface radiation which cools the surface under the plume. This inversion reduces convection in the region thereby suppressing the Walker Circulation and the Trade Winds which causes the SST to rise in the central Pacific Ocean and creates convection there. This further weakens/reverses the Walker Circulation driving the climate into an ENSO state which is maintained until the aerosols dissipate and the climate system relaxes into a non-ENSO state. Measured aerosol data from four NASA satellites, estimates of volcanic tephra from the Global Volcanism Program (GVP) for over 100 years and the NASA MERRA-2 reanalysis dataset all confirm this analysis.

The Last Millennium Ensemble, Large Ensemble, MERRA-2, four satellite data sets and the Global Volcanism Program database all show independently that drought in south eastern Australia (SEAus) is created by apparitions of the natural and anthropogenic aerosol plume over south east Asia which simultaneously create ENSO and IOD events. From 1997 to 2008 SEAus endured an exceptionally severe drought - the Millennium Drought. The River Murray, the major waterway in the region, experienced inflows at record low levels in 2006-07 which were more than 40% below the previous low. As the literature, Inter Governmental Panel on Climate Change (IPCC) and the USA Climate Change Science Program suggest that aerosols can affect the large-scale atmospheric circulation and hydrologic cycle I examine the relationship between aerosols and Australian droughts. The global aerosol coverage is highly inhomogeneous and variable at daily, monthly, annual and decadal scales. I show that the aerosol optical depth (AOD) and aerosol index (AI) of the South East Asian Plume (SEAP) and the volume of aerosols ejected by volcanoes (tephra) in south east Asia correlate with drought in Australia and conclude that the SEAP causes drought in Australia by Aerosol Regional Dimming (ARD), which, by altering the surface radiation budget under the plume and warming the upper atmosphere, forces the regional Inter Tropical Convergence Zone and Hadley Cells into abnormal seasonal positions. These effects alter the regional atmospheric circulation systems and hydrologic cycle thereby causing drought and, as the SEAP has intensified over time, created climate change.

The longitudinal structure and annual cycle of mean meridional and eddy momentum fluxes in the upper troposphere of the deep tropics are studied using ERA-Interim reanalysis over a 40 year period. In a zonal mean sense, these two terms oppose each other and peak during the Indian summer monsoon. This zonal mean character arises from a rich longitudinal structure revealed by splitting the globe into three zones, namely, the Asia-West Pacific, central Pacific-West Atlantic, and African sectors. The mean meridional convergence term is cohesive across these three regions; it has a single peak in the boreal summer and always acts to decelerate the zonal flow. On the other hand, eddy fluxes are much more varied and go from being small and seasonally invariant in the African sector to having large seasonal peaks of acceleration (deceleration) in the Asia-West Pacific (central Pacific-West Atlantic) sector. This longitudinal variation in eddy momentum fluxes presents interesting insights into the overturning circulation in these zonally limited sectors, which previously remained hidden in the zonal mean.

A new generation of operational atmospheric models operating at horizontal resolutions in the range 200 m ~ 2 km is becoming increasingly popular for operational use in numerical weather prediction and climate applications. Such grid spacings are becoming sufficiently fine to resolve a fraction of the turbulent transports. Here we analyze LES results of a convective boundary layer obtained by coarsening horizontal grid spacings up to 800 m. The aim is to explore the dependency of the mean state and turbulent fluxes on the grid resolution. Both isotropic and anisotropic eddy diffusion approaches are evaluated, where in the latter case the horizontal and vertical eddy diffusivities differ in accord with their horizontal and vertical grid spacings. For coarsening horizontal grid sizes entrainment at the top of the boundary layer tends to get slightly enhanced for isotropic diffusion. An analysis of the energy spectrum shows that anisotropic diffusion causes relatively more dissipation of variance at smaller length scales. This leads, in turn, to a shift of spectral energy towards larger length scales. This can also be clearly seen from the different kinds of spatial organization. The present study therefore suggests that details with regards to the representation of processes at small scales might impact the organization at length scales much larger than the smallest scales that can be resolved by the model.

The U.S. Midwest, with its intensive agriculture, is a prominent source of nitrous oxide (N2O) but top-down and bottom-up N2O emission estimates differ significantly. We quantify Midwest N2O emissions by combining observations from the Atmospheric Carbon and Transport-America campaign with model simulations to scale the Emissions Database for Global Atmospheric Research (EDGAR). In October 2017 we increased agricultural EDGAR version 4.3.2/5.0 emissions by a factor of 6.3±4.6/3.5±2.7, resulting in Midwest N2O emissions of 0.42±0.28 nmol m-2 s-1. In June/July 2019, a period when extreme flooding was occurring in the Midwest, EDGAR was increased by a factor of 11.4±6.6/9.9±5.7, resulting in N2O emissions of 1.06±0.57 nmol m-2 s-1. Agricultural emissions estimated with the process-based model DayCent (Daily version of the CENTURY ecosystem model) were larger than in EDGAR but still substantially smaller than our estimates. Due to the complexity of N2O emissions, further studies are necessary to fully characterize Midwest emissions.

An improved understanding of the seasonality of the Arctic snowpack properties related to the timing and intensity of snowmelt processes is the key driver to better quantify atmosphere-ice-ocean interactions, and in particular the seasonal energy and mass budgets of the ice-covered polar oceans. Various satellite data products over the last decades have shown a trend towards an earlier snowmelt onset in the Arctic, thus contributing to Arctic amplification and sea-ice decline, underlining the need to better understand these processes. We present here the physical snow properties from spring 2020 examined during the “Multidisciplinary drifting Observatory for the Study of Arctic Climate” (MOSAiC). We focus on southerly air mass advection events in mid-April that were associated with near-surface air temperatures near freezing at the MOSAiC floe. In doing so, we emphasize a single sampling site that was revisited daily-to-weekly throughout the spring. At the sampling site, snow depth ranged from 10 to 14 cm with the bulk density varying between 200 to 350 kg m-3, mainly driven by freshly fallen snow. The vertical snow structure prior to the warm event was characterized by large pores with distinct snow crystal structures and widespread depth hoar crystals, both related to the strong temperature gradient in the snowpack. During the warm air intrusion, increasing temperatures temporarily reversed the thermal gradient in the snow. The warm snow surface, now above a relatively cold snow/ice interface, resulted temporary negative vertical heat flux values observed to be up to -12 Wm-2. Because the snow/ice interface is close to freezing, the negative flux is an indicator that melt may have occurred. Once temperatures dropped again, the vertical temperature and heat flux gradients returned back to the previous patterns. However, the decreased snow grain sizes throughout the snowpack due to the warming and the associated compacted lower layers now dominated the snowpack. Such a temporary warm spell event has decisive impacts on the sea-ice energy and mass budget of the MOSAiC floe. Understanding this effect on a local scale will help to transfer that knowledge to larger spatial scales, and thus to quantify the influence of warm air intrusions during winter and/or spring in the ice-covered Arctic basin.

Key Points:  The HRRR model near surface thermodynaic biases are seasonally dependent. A systematic warm and dry bias present during the warm season.  The summer warm and dry biases over farmland are consistently larger than forest.  Hydrological bias of spring snow melt might eventually lead to the summer warm and dry biases over farmland. Abstract The High-Resolution Rapid Refresh (HRRR) model version 3 meteorological fields were examined using data from New York State Mesonet (NYSM) sites from an entire year. In this work, the land surface, atmosphere and cloud coupling systems are evaluated as an integrated system. The physical processes influencing soil hydrological, surface thermodynamic processes from surface fluxes to boundary layer convection are investigated from both temporal (seasonal and diurnal) and spatial perspectives. Results show that the model 2m surface biases are seasonally dependent, with warm and dry bias present during the warm season, and an extreme cold bias during the night in winter. The summer warm bias includes both a land-surface-induced bias and a cloud-induced bias. Inacurate representation of energy partition and soil hydrological process across different land use types and hydrological bias of spring snow melt in the land surface model is the main source of the land-surface induced bias. A feedback loop linking cloud presence, radiative flux changes and temperature contributes to the cloud-induced bias. The positive solar radiation bias increases from clear sky to overcast sky conditions, beyond simply the lack of aerosols in the current version. The most significant bias occurs during overcast and thick cloud conditions associated with frontal passage and thunderstorms.

Atmospheric CO2 inversion typically relies on the specification of prior flux and atmospheric model transport errors, which have large uncertainties. Here, we use ACT-America 30 airborne observations to compare total CO 2 model-observation mismatch in the eastern U.S. and during four climatological seasons for the mesoscale WRF(-Chem) and global scale CarbonTracker/TM5 (CT) models. Models used identical surface carbon fluxes, and CT was used as CO 2 boundary condition for WRF. Both models show reasonable agreement with observations, and CO 2 residuals follow near symmetric peaked (i.e. non-Gaussian) distribution with near zero bias of both models (CT: −0.34 +/- 3.12 ppm; WRF: 0.82 +/- 4.37 ppm). We also encountered large magnitude residuals at the tails of the distribution that contribute considerably to overall bias. Atmospheric boundary-layer biases (1-10 ppm) were much larger than free tropospheric biases (0.5-1 ppm) and were of same magnitude as model-model differences, whereas free tropospheric biases were mostly governed by CO2 background conditions. Results revealed systematic differences in atmospheric transport, most pronounced in the warm and cold sectors of synoptic systems, highlighting the importance of transport for CO2 residuals. While CT could reproduce the principal CO2 dynamics associated with synoptic systems, WRF showed a clearer distinction for CO2 differences across fronts. Variograms were used to quantify spatial coherence of residuals and showed characteristic residual length scales of approximately 100 km to 300 km. Our findings suggest that inclusion of synoptic weather-dependent and non-Gaussian error structure may benefit inversion systems.

Mesoscale convective systems (MCSs) are the main source of precipitation in the tropics and parts of the mid-latitudes and are responsible for high-impact weather worldwide. Studies showed that deficiencies in simulating mid-latitude MCSs in state-of-the-art climate models can be alleviated by kilometer-scale models. However, whether these models can also improve tropical MCSs and weather we can find model settings that perform well in both regions is understudied. We take advantage of high-quality MCS observations collected over the Atmospheric Radiation Measurement (ARM) facilities in the U.S. Southern Great Plains (SGP) and the Amazon basin near Manaus (MAO) to evaluate a perturbed physics ensemble of simulated MCSs with 4\,km horizontal grid spacing. A new model evaluation method is developed that enables to distinguish biases stemming from spatiotemporal displacements of MCSs from biases in their reflectivity and cloud shield. Amazon MCSs are similarly well simulated across these evaluation metrics than SGP MCSs despite the challenges anticipated from weaker large-scale forcing in the tropics. Generally, SGP MCSs are more sensitive to the choice of model microphysics, while Amazon cases are more sensitive to the planetary boundary layer (PBL) scheme. Although our tested model physics combinations had strengths and weaknesses, combinations that performed well for SGP simulations result in worse results in the Amazon basin and vice versa. However, we identified model settings that perform well at both locations, which include the Thompson and Morrison microphysics coupled with the Yonsei University (YSU) PBL scheme and the Thompson scheme coupled with the Mellorâ\euro“Yamadaâ\euro“Janjic (MYJ) PBL scheme.

We investigate the relationship between NO infrared radiation and x-ray radiation at different local time (LT) and latitudes of NO average fluxes. The NO volume emission rates obtained by SABER instrument on board TIMED satellite and x-ray fluxes on long (0.1-0.8 nm) and short (0.05-0.4) channels measured by GOES 12 satellite were used. NO rates were vertically integrated to obtain fluxes, which are then separated into day (8

The MMS spacecraft routinely observe electron “microinjections” at energies in the 10s-100s keV range across the nightside magnetosphere at distances <20 Re. Microinjections are typically observed in clusters where multiple dispersed injection signatures are recorded in succession over a short time interval (e.g., ~10 in one hour) and may be related to surface wave activity at the magnetopause. Recent work has shown that microinjections have distinctive features in the angular distributions, where field-aligned distributions are observed near dusk, while trapped distributions are observed near dawn. Due to their recent discovery, the origin and generation of microinjections has yet to be conclusively identified and detailed studies thus far have largely been done on a case-by-case basis. In an effort to elucidate more general properties and characteristics of microinjections, we describe an automated routine designed to identify microinjection signatures in the MMS/FEEPS measurements. The algorithm uses image processing techniques (the radon transform) and is based on a similar method developed to identify whistler-mode chorus elements in Van Allen Probes wave observations (Sen Gupta et al., [2017]). We present an initial set of results from a statistical database of microinjection events obtained from the automated algorithm to further our understanding of this intriguing phenomenon.

Jovian moist convection has been the study of both observational and modelling attempts for several decades. In the Pioneer and Voyager era, plumes of volatiles were observed to erupt from the deep atmosphere regularly, prompting the question of the strength of the internal heat flux within Jupiter’s atmosphere. Later, Galileo observed towering convective storms coinciding with the presence of lightning. Analysis of cloud formation on Jupiter considering the abundances of various condensible species revealed that the most likely source of these convective events was the deep water cloud which contains both the high density of volatiles and necessary convective potential to breach the upper cloud deck. In this study, we use the Explicit Planetary Isentropic Coordinate (EPIC) atmospheric 3-dimensional general circulation model (GCM) to study the formation of Jovian moist convective events, using an active cloud microphysics scheme. We focus on the region centered on the 24° N jet where plume formation has been observed several times. We initiate cloud formation assuming different initial deep abundance values of both water and ammonia to test the sensitivity on the strength of plume formation and the buildup of convective potential energy (CAPE). We find that convective activity is affected by the thermal properties of the environment – the jet and the North Equatorial Belt are conducive of convection while the North North Tropical Zone is not.

Recent previous research has established the “sharpest gradient” approach to defining the circumpolar vortex and has identified correlations of the area and circularity of the Northern Hemisphere’s circumpolar vortex (NHCPV) to important atmospheric-oceanic teleconnections. However, because geographical shifts in the NHCPV, independent of area or circularity changes, could affect surface environmental conditions, this research addresses the question of the extent to which the NHCPV centroid undergoes such shifts, both intra- and inter-annually. Results show that during the 1979–2017 period, the centroid has moved less on a daily basis in more recent years, perhaps indicative of a stabilization in circulation, with semi-annual and seasonal periodicities in the daily distance moved. A consistent preference toward the Eastern Hemisphere is evident by the displacement of the centroids toward the Pacific basin throughout the study period. Collectively, these results indicate the mid-tropospheric response to the near-surface warming.

The motivation and objective of the EarthScope Transportable Array (TA) is to record earthquake signals and image the structure of the North American plate, however the observations collected by this National Science Foundation funded project have enabled unanticipated discoveries, innovative data analysis techniques, and ongoing investigations across many disciplines in the Earth and space sciences. The Transportable Array utilized a survey approach to collect data in which high-quality stations were systematically installed in a dense geospatial grid. From the very beginning of the deployment, this strategy allowed for data-driven discovery, such as using seismic data to map out extensive travel time curves for acoustic waves in the atmosphere (Hedlin et al., 2010). While the emplacement of the seismic sensors was kept uniform along with the core components for power and communications, the Transportable Array station design evolved over time to include additional barometric pressure and infrasound sensors and, eventually, meteorological sensors measuring external temperature, wind, and precipitation. As the array rolled across the Lower 48 and the TA became more recognized outside of seismology, collaborations were forged and strengthened with researchers in the infrasound and meteorological communities. Along with standard approaches using direct measurements, inventive techniques were used to apply environmental data for observing tectonic phenomena as well as applying seismic data for observing environmental phenomena. The value of integrated scientific infrastructure became even more apparent with the Transportable Array deployment in Alaska and western Canada, with autonomous and telemetered stations occupying sites within large swaths of previously unmonitored and inaccessible terrain. The majority of Alaska TA stations collect weather data and a subset also include a detached soil temperature probe. As a result, data collected by the Alaska Transportable Array have been used to observe throughout the ‘spheres: the lithosphere (earthquakes, volcanoes, landslides), the cryosphere (sea ice), the hydrosphere (precipitation, fire preparation), the atmosphere and biosphere (weather forecasting, storm systems, bolides), and even into the magnetosphere (space weather).

In this study, we examine the ability of the data assimilation of global satellite-based carbon monoxide (CO) observations to constrain high-latitude boreal wildfire emissions. We compare the optimized emissions from inversions using CO measurements from the Measurement of Pollution in the Troposphere (MOPITT) and Infrared Atmospheric Sounding Interferometer (IASI). We found that both inversions yield generally consistent posterior CO emissions globally; however, distinct differences are observed for the episodic 2017 Canadian wildfires. The 3-day global coverage of MOPITT limits its ability to accurately optimize emissions, while the daily global coverage of IASI provides a moderate improvement despite its lower surface sensitivity. Through a series of observing system simulation experiments (OSSEs), we show that the temporal coverage of IASI most strongly influenced the posterior estimates, while the differences in vertical sensitivities of MOPITT and IASI have a minor contribution.

Linear dipole type DC electric field sensor was newly developed, and continuous observations by means of 3-D sensor system composed of three sensors installed orthogonally with each other have been conducting since 2017. However, their measured intensities have been remained uncertain, because they could not be calibrated from a reason that, at present, there dose not exist any facility for making uniform electric field in a wide area. So, in order to establish a method for obtaining reliable electric field intensity from output voltage of the sensor system, fundamental function of the sensor system has been examined. Since resistor R which is to be connected to input terminals of differential pre-amplifier is a key parameter in the sensor system, it was needed to examine a characteristic curve of the output voltage as a function of R. For this purpose, simultaneous observations of natural electric fields were conducted by means of plural sensor systems installed in parallel. From obtained characteristic curve, an optimum value of R could be decided, and a formula showing a relation between reliable electric field intensity and output voltage of the sensor system was found. Validity of the formula has been verified by results of simultaneous observations of a lightning pulse by means of two vertical sensor systems whose element lengths were different. Their results have shown same electric field intensity. As the result, the linear dipole type DC electric field sensor system with the formula has been perfectly established as a practically useful sensor system.

Previous study has shown that atmospheric conductivity variations are larger in amplitude than can be explained by current models. Several possible explanations for these variations have been proposed. However, recent conductivity research has been sparse, and no definitive explanations have been found. The latest iteration of the Undergraduate Student Instrument Project (USIP) at University of Houston seeks to add to previous work and explore possible contributing factors to these unexplained variations. To achieve this goal, the Conductivity team within USIP is designing and constructing an instrument that will be launched in Alaska. The data collected will be compared to measurements by other instruments launched during the same project. These include instruments studying microplastics, high energy particles, VLF waves, and gaseous compounds. In addition to contributing to the effort to understand the global electric circuit, the Conductivity team hopes to develop a low-cost kit that can be used by school groups to collect their own conductivity data. In the face of the COVID-19 pandemic, this student-led research project has overcome the challenges of distance, disrupted schedules, and uncertain funding by fostering a learning and working environment that can adapt to a variety of situations. In response to these challenges, USIP shifted towards the virtual resources that were already in use as a supplement to in-person work. The team uses Microsoft Teams and Zoom for virtual meetings, Slack for regular communication between members, and email to regularly coordinate with resources outside of the students in the research group. Diligent communication and adaptable budget, construction, and organization planning have been critical to maintaining the momentum of this project. Although the future remains uncertain, the Conductivity team continues to hope and prepare for the originally planned March 2021 launch.

A new multi-static meteor radar (CONDOR) has recently been installed in northern Chile. This CONDOR meteor radar (30.3°S, 70.7°W) and the Adelaide meteor radar (35°S, 138°E) have provided longitudinally spaced observations of the mean winds, tides and planetary waves of the PW-tides interaction cases we present here. We have observed a Quasi-6-Day Wave (Q6DW) enhancement in MLT winds at the middle latitudes (30.3°S, 35°S) during the unusual minor South Hemisphere SSW 2019 by the ground-based meteor radars. Tidal analysis also indicates modulation of the Q6DW w/ amplitude ~15 [m/s] and diurnal tides w/ amplitude ~60 [m/s]. Another case we present here is a dominant Quasi-2-Day Wave (Q2DW) with up to 50 [km/s] amplitude occurring in SH summer 2020 and its interaction with the diurnal and semidiurnal tides. The period of this Q2DW activity changes from ~50hr to ~48hr since Jan 19, which suggests the phase locking mechanism [McCormack et al., 2010]. The 24hr-feature and 12hr-feature show off-phase variations during the Q2DW enhancement time with amplitude of ~40 [m/s].

The collection of high temporal resolution radar observations without compromising data quality requires adaptability and agility. So far, radar beam steering has been mostly guided by i) the expert judgment or ii) stand-alone automated identification and tracking algorithms operating on measurements collected by the radar itself. The current study proposes a new paradigm, where external observations are used to optimize a radar’s sampling strategy. Here the sampling strategy of a phased-array radar and a polarimetric scanning cloud radar, two different yet uniquely complementary systems, is guided by an algorithm that uses observations from a geostationary satellite, a surface camera and the radars themselves to identify and track atmospheric phenomena. The tailored pointing and increase in sensitivity realized through this framework enables the steered radars to sample a diverse set of atmospheric phenomena such as shallow cumuli, lightning-induced ice crystal orientation and a series of waterspouts.

Cyclonic low-pressure systems (LPS) produce abundant rainfall in South Asia, where they are traditionally categorized as monsoon lows, monsoon depressions, and more intense cyclonic storms. The India Meteorological Department (IMD) has tracked monsoon depressions for over a century, finding a large decline in their number in recent decades, but their methods have changed over time and do not include monsoon lows. This study presents a fast, objective algorithm for identifying monsoon LPS in high-resolution datasets. Variables and thresholds used in the algorithm are selected to best match a subjectively analyzed LPS dataset while minimizing disagreement between four atmospheric reanalyses in a training period. The streamfunction of the 850 hPa horizontal wind is found to be the best variable for tracking LPS; it is less noisy than vorticity and represents the complete non-divergent wind, even when flow is not geostrophic. Using this algorithm, LPS statistics are computed for five reanalyses, and none show a detectable trend in monsoon depression counts since 1979. Both the Japanese 55-year Reanalysis (JRA-55) and the IMD dataset show a step-like reduction in depression counts when they began using geostationary satellite data, in 1979 and 1982 respectively; the 1958-2018 linear trend in JRA-55, however, is smaller than in the IMD dataset and its error bar includes zero. There are more LPS in seasons with above-average monsoon rainfall and also in La Nin ̵̃a years, but few other large-scale modes of interannual climate variability are found to modulate LPS counts, lifetimes, or track length consistently across all reanalyses.

Synoptic-scale cyclonic vortices produce abundant rainfall in South Asia, where these low pressure systems (LPS) are traditionally categorized as monsoon lows, monsoon depressions, and more intense cyclonic storms. The India Meteorological Department has tracked monsoon depressions for over a century, finding a large decline in the number of those storms in recent decades; their tracking methods, however, seem to have changed over time and do not include monsoon lows, which can produce intense rainfall despite their weak winds. This study presents a fast and objective tracking algorithm that can identify monsoon LPS in high-resolution datasets with a variety of grid structures. A sensitivity analysis has been performed to select a set of atmospheric variables and their corresponding thresholds for optimal tracking of LPS. Approximately 250 combinations of variables and thresholds are used to identify LPS over roughly a decade (the training period) in each of four atmospheric reanalyses, and these combinations are ranked using a skill score that compares the reanalyses with each other and with a preexisting track dataset that was compiled by subjective identification of LPS. This procedure finds the streamfunction of the 850 hPa horizontal wind to be the best variable for tracking LPS. The streamfunction is smoother than the vorticity field and represents the complete non-divergent component of the wind even when the flow is not geostrophic, unlike the geopotential height or sea level pressure. Using this tracking algorithm, LPS statistics are then computed in five reanalysis products that each span at least 40 years, with a primary goal being to determine whether the large decrease in monsoon depressions seen in the India Meteorological Department track dataset since the 1970s can be found in any reanalysis. This trend assessment is particularly relevant for the ERA5 reanalysis, which extends back to 1950 and which contains explicit climate forcings. In addition to secular trends, this study assesses the decadal variation of LPS, as well as interannual changes in LPS activity that are associated with the El Niño-Southern Oscillation and the Indian Ocean Dipole.

Energy exchange at the snow-atmosphere interface in winter is important for the evolution of temperature at the surface and within the snow, preconditioning the snowpack for melt during spring. This study illustrates a set of diagnostic tools that are useful for evaluating the energy exchange at the Earth’s surface in an Earth System Model, from a process-based perspective, using in-situ observations. In particular, a new way to measure model improvement using the response of the surface temperature and other surface energy budget (SEB) terms to radiative forcing is presented. These process-oriented diagnostics also provide a measure of the coupling strength between the incoming radiation and the various terms in the SEB, which can be used to ensure that improvements in predictions of user relevant properties, such as 2m temperature, are happening for the right reasons. Correctly capturing such process relationships is a necessary step towards achieving more skilful weather forecasts and climate projections. These diagnostic techniques are applied to assess the impact of a new multi-layer snow scheme in the European Centre for Medium-Range Weather Forecasts’-Integrated Forecast System at two high-Arctic sites (Summit, Greenland and Sodankylä, Finland). The multi-layer scheme is expected to replace a single layer snow scheme in the operational forecasting system, enhancing the 2m temperature forecast reliability and skill across the northern hemisphere in boreal winter.

The Quasi-Biennial Oscillation (QBO) dominates the interannual variability in the tropical lower stratosphere and is characterized by the descent of alternating easterly and westerly zonal winds. The QBO impact on tropical clouds and convection has received great attention in recent years due to its implications for weather and climate. In this study, a 15-year record of high vertical resolution observations from CALIPSO are used to document the QBO impact on equatorial (10°S-10°N) clouds. Observations from radio occultations, the CERES instrument, and the ERA5 reanalysis are also used to document the QBO impact on temperature, radiative energy budget, and zonal wind. It is shown that the QBO impact on zonal mean equatorial cloud fraction has a strong seasonality. The strongest cloud fraction response to the QBO occurs in boreal spring and early summer extending down to ~12 km and results in a significant longwave cloud radiative effect anomaly. The seasonality of the cloud fraction changes is synchronized with those of temperature and zonal wind in the tropical upper troposphere.

The Stratospheric Aerosol and Gas Experiment operating on the International Space Station (SAGE III/ISS) is an occultation instrument that retrieves aerosol extinction and ozone, water vapor, and other trace gas concentrations. Water vapor in the stratosphere plays a significant role in ozone depletion and global temperature regulation making it an important species to monitor. The new SAGE III/ISS instrument provides high quality, vertically resolved profiles of water vapor throughout the stratosphere and upper troposphere. A discussion is presented on the sensitivity of the SAGE III/ISS instrument to water vapor and provide an early evaluation of the retrieved profiles.