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Much of Siberia experienced exceptional warmth during the spring of 2020, which followed an unusually warm winter over the same region. Here, we investigate the drivers of the spring warmth from the perspective of atmospheric dynamics and remote influences, focusing on monthly timescale features of the event. We find that the warm anomalies were associated with separate quasi-stationary Rossby wave trains emanating from the North Atlantic in April and May. The wave trains are shown to be extreme manifestations of the dominant modes of spring subseasonal meridional wind variability over the Northern Hemisphere. Using a large ensemble of simulations from NASA’s GEOS atmospheric model, in which the model is constrained to remain close to observations over selected regions, we further elucidate the remote drivers of the unusual spring temperatures in Siberia. In both April and May, the wave trains were likely forced from an upstream region including eastern North America and the western North Atlantic. Analysis with a stationary wave model shows that transient vorticity flux forcing over and downwind of the North Atlantic, which is strongly related to storm activity caused by internal variability, is key to generating the wave trains, suggesting limited subseasonal predictability of the Rossby waves and hence the exceptional Siberian warmth. Our observational and model analysis also suggests that anomalous tropical atmospheric heating contributed to the unusual warmth in Siberia through a teleconnection involving upper-troposphere dynamics and the mean meridional circulation. This tropical-extratropical teleconnection offers a possible physical mechanism by which anthropogenic climate change influenced the extreme Siberian warmth.

Tropical cyclone precipitation (TCP) contributes a significant fraction of total annual rainfall and also is a frequent cause of extreme precipitation in many parts of the tropics. The climatology of TCP in the S2S models is characterized by dry biases in the North Atlantic and wet biases in most other basins, specially in the Southern Indian Ocean and Australia. Biases in total precipitation (P), TCP and their ratio (TCP/P) are mostly positive in the multi-model ensemble mean and change very little with lead time. in these models the frequency biases are the dominant contribution to TCP biases. However, in some models, there are positive biases in average precipitation per each TC which contribute significantly to TCP biases at equatorial latitudes.The prediction skill of these reforecasts is evaluated using skill scores such as the ranked probability skill score for TCP and the Brier Skill score for genesis and occurrence. The implication of these results is discussed for their relevance to mean and extreme precipitation prediction skill using S2S models.

The heat wave in East Asia is examined by using empirical orthogonal function analysis to isolate dominant heat-wave patterns in the ground-based temperature observations over the Korean Peninsula and China and related large-scale atmospheric circulations obtained from the National Centers for Environmental Prediction–National Center for Atmospheric Research Reanalysis 1 during 1973–2012. This study focuses particularly on the interannual variability of heat waves and its decadal change. The analysis identifies two major atmospheric teleconnection patterns playing an important role in developing typical heat-wave patterns in East Asia—the Scandinavian (SCAND) and the circumglobal teleconnection (CGT) patterns, which exhibit a significant decadal change in the interannual variability in the mid-1990s. Before the mid-1990s, heat-wave occurrence was closely related to the CGT pattern, whereas the SCAND pattern is more crucial to explain heat-wave variability in the recent period. The stationary wave model experiments suggest an intensification of the SCAND pattern in the recent period driven by an increase in land–atmosphere interaction over Eurasia and decadal change in the dominant heat-wave patterns in East Asia.

This study investigates the diurnal variation of the warm season precipitation simulated by the Goddard Earth Observing System version 5 atmospheric general circulation model for 2 years (2005–2006) at a horizontal resolution of 10 km. The simulation was validated with the satellite-derived Tropical Rainfall Measuring Mission (TRMM) 3B42 precipitation data and the Modern-Era Retrospective analysis for Research and Applications atmospheric reanalysis for atmospheric winds and moisture. The simulation is compared with the coarse-resolution run in 50 km to examine the impacts driven by resolution change. Overall, the 10 km model tends to reproduce the important features of the observed diurnal variation, such as the amplitude and phase at which precipitation peaks in the evening on land and in the morning over the ocean, despite an excessive amplitude bias over land. The model also reproduces the realistic propagation patterns of precipitation in the vicinity of ocean coasts and major mountains. The regional characteristics of the diurnal precipitation over two regions, the Bay of Bengal and the Great Plains in North America, are examined in detail, where the observed diurnal cycle exhibits a systematic transition in the peak phase due to the development and propagation of regional-scale convective systems. The model is able to reproduce this pattern as well as the diurnal variation of low-level wind and moisture convergence; however, it is less effective at representing the nocturnal peak of precipitation over the Great Plains. The model results suggest that increasing the horizontal resolution of the model to 10 km substantially improves the representation of the diurnal precipitation cycle. However, intrinsic model deficiencies in topographical precipitation and the accurate representation of mesoscale convective systems remain a challenge.

While it is known that the Pacific Decadal Oscillation (PDO) leads the Indian Ocean Basin Mode (IOBM) with the same phase via the atmospheric bridge, we found that the relationship of PDO-IOBM during boreal winter is not stationary. Here, we investigated the PDO-IOBM relationship changes on low-frequency timescales by analyzing the observations, a long-term simulation of climate model with its large ensembles as well as the pacemaker experiments. A long-term simulation of climate model with its large ensemble simulations indicated that the non-stationary relationship of PDO-IOBM is intrinsic in a climate system and it could be at least partly due to internal climate variability. In details, we compared the PDO structures during the entire period with those during the period when the PDO-IOBM relationship was weak (i.e., 1976-2006). We found that the structures of sea surface temperature (SST) as well as its associated tropical Pacific convective forcing during the negative phase of PDO for 1976-2006 are far away from the typical structures of the negative PDO phase during the entire period, which were responsible for the weakening relationship of the PDO-IOBM in the observation. The results of the two pacemaker experiments support that a non-stationary relationship of PDO-IOBM is primarily due to the SST forcing in the Pacific.

Recent changes in Earth’s climate system have significantly affected the radiation budget and its year-to-year variations at top of the atmosphere (TOA). Observing high-latitude TOA fluxes is still challenging from space, because spatial inhomogeneity of surface/atmospheric radiative processes and spectral variability can reflect sunlight very differently. In this study we analyze the 20-year TOA flux and albedo data from CERES and MISR over the Arctic, the Antarctic, and Tibetan Plateau (TP), and found overall great consistency in the TOA albedo trend and interannual variations. The observations reveal a lagged correlation between the Arctic and subarctic albedo fluctuations. The observed year-to-year variations are further used to evaluate the reanalysis data, which exhibit substantial shortcomings in representing the polar TOA flux variability. The observed Arctic flux variations are highly correlated with cloud fraction (CF), except in the regions where CF > 90% or where the surface is covered by ice. An empirical orthogonal function (EOF) analysis shows that the first five EOFs can account for ~50% of the Arctic TOA variance, whereas the correlation with climate indices suggests that Sea Ice Extent (SIE), North Atlantic Oscillation (NAO) and 55°N–65°N cloudiness are the most influential processes in driving the TOA flux variabilities.

The Global Modeling and Assimilation Office (GMAO) has recently released a new version of the Goddard Earth Observing System (GEOS) Sub-seasonal to Seasonal prediction (S2S) system, GEOS-S2S-2, that represents a substantial improvement in performance and infrastructure over the previous system. The system is described here in detail, and results are presented from forecasts, climate equillibrium simulations and data assimilation experiments. The climate or equillibrium state of the atmosphere and ocean showed a substantial reduction in bias relative to GEOS-S2S-1. The GEOS-S2S-2 coupled reanalysis also showed substantial improvements, attributed to the assimilation of along-track Absolute Dynamic Topography. The forecast skill on subseasonal scales showed a much-improved prediction of the Madden-Julian Oscillation in GEOS-S2S-2, and on a seasonal scale the tropical Pacific forecasts show substantial improvement in the east and comparable skill to GEOS-S2S-1 in the central Pacific. GEOS-S2S-2 anomaly correlations of both land surface temperature and precipitation were comparable to GEOS-S2S-1, and showed substantially reduced root mean square error of surface temperature. The remaining issues described here are being addressed in the development of GEOS-S2S Version 3, and with that system GMAO will continue its tradition of maintaining a state of the art seasonal prediction system for use in evaluating the impact on seasonal and decadal forecasts of assimilating newly available satellite observations, as well as to evaluate additional sources of predictability in the earth system through the expanded coupling of the earth system model and assimilation components.

The 2015/16 El Niño is analyzed using atmospheric and oceanic analysis produced using the Goddard Earth Observing System (GEOS) data assimilation systems. As well as describing the structure of the event, a theme of this work is to compare and contrast it with two other strong El Niños, in 1982/83 and 1997/98. These three El Niño events are included in the Modern-Era Retrospective Analysis for Research and Applications (MERRA) and in the more recent MERRA-2 reanalyses. MERRA-2 allows a comparison of fields derived from the underlying GEOS model, facilitating a more detailed comparison of physical forcing mechanisms in the El Niño events. Various atmospheric and oceanic structures indicate that the 2015/16 El Niño maximized in the Niño-3.4 region, with a large region of warming over most of the Pacific and Indian Oceans. The eastern tropical Indian Ocean, Maritime Continent, and western tropical Pacific are found to be less dry in boreal winter, compared to the earlier two strong events. Whereas the 2015/16 El Niño had an earlier occurrence of the equatorial Pacific warming and was the strongest event on record in the central Pacific, the 1997/98 event exhibited a more rapid growth due to stronger westerly wind bursts and the Madden–Julian oscillation during spring, making it the strongest El Niño in the eastern Pacific. Compared to 1982/83 and 1997/98, the 2015/16 event had a shallower thermocline over the eastern Pacific with a weaker zonal contrast of subsurface water temperatures along the equatorial Pacific. While the three major ENSO events have similarities, each is unique when looking at the atmosphere and ocean surface and subsurface.

Besides its negative trend, the interannual and the interdecadal changes in the Arctic sea ice have also been pronounced in recent decades. The three leading modes in the sea level pressure (SLP) variability in the Arctic (70–90∘ N) – the Arctic Oscillation (AO), the Arctic Dipole (AD), and the third mode (A3) – are analyzed to understand the linkage between sea ice variability and large-scale atmospheric circulation in boreal summer (June–August). This study also compares the decadal changes of the modes between the early (1982–1997) and the recent (1998–2017) periods and their influences on the Arctic sea ice extent (SIE). Only the AD mode shows a significant correlation increase with SIE in summer (JJA) from −0.05 in the early period to 0.57 in the recent period. The AO and the A3 modes show a less significant relationship with SIE for the two periods. The AD is characterized by a dipole pattern of SLP, which modulates the strength of meridional surface winds and the Transpolar Drift Stream (TDS). The major circulation change in the late 1990s is that the direction of the wind has been changed more meridionally over the exit region of the Fram Strait, which causes sea ice drift and discharge through that region. In addition, the response of surface albedo and the net surface heat flux becomes larger and much clearer, suggesting a positive sea-ice–albedo feedback in the sea ice variability associated with the AD. The analysis also reveals that the zonal shift of the centers of SLP anomalies and associated circulation change affects a significant reduction in sea ice concentration over the Pacific sector of the Arctic Ocean. This study further suggests that the Pacific Decadal Oscillation (PDO) phase change could influence the spatial pattern change in the AD.

December through February 2015-2016 defines the warmest winter season over the Arctic in the observational record. Positive 2 m temperature anomalies were focused over regions of reduced sea ice cover in the Kara and Barents Seas, and southwestern Alaska. A third region is found over the ice-covered central Arctic Ocean. The period is marked by a strong synoptic pattern which produced melting temperatures in close proximity to the North Pole in late December, and anomalous high pressure near the Taymyr Peninsula. Atmospheric teleconnections from the Atlantic contributed to warming over Eurasian high-latitude land surfaces, and El Nino-related teleconnections explain warming over southwestern Alaska and British Columbia, while warm anomalies over the central Arctic are associated with physical processes including the presence of enhanced atmospheric water vapor and an increased downwelling longwave radiative flux. Preconditioning of sea ice conditions by warm temperatures affected the ensuing spring extent.

An assessment of simulations of the interannual variability of tropical cyclones (TCs) over the western North Pacific (WNP) and its association with El Niño–Southern Oscillation (ENSO), as well as a subsequent diagnosis for possible causes of model biases generated from simulated large-scale climate conditions, are documented in the paper. The model experiments are carried out by the Hurricane Work Group under the U.S. Climate Variability and Predictability Research Program (CLIVAR) using five global climate models (GCMs) with a total of 16 ensemble members forced by the observed sea surface temperature and spanning the 28-yr period from 1982 to 2009. The results show GISS and GFDL model ensemble means best simulate the interannual variability of TCs, and the multimodel ensemble mean (MME) follows. Also, the MME has the closest climate mean annual number of WNP TCs and the smallest root-mean-square error to the observation. Most GCMs can simulate the interannual variability of WNP TCs well, with stronger TC activities during two types of El Niño—namely, eastern Pacific (EP) and central Pacific (CP) El Niño—and weaker activity during La Niña. However, none of the models capture the differences in TC activity between EP and CP El Niño as are shown in observations. The inability of models to distinguish the differences in TC activities between the two types of El Niño events may be due to the bias of the models in response to the shift of tropical heating associated with CP El Niño.

MPEG-2 transport stream (TS), standardized by the ISO/IEC as part of the well-known MPEG-2 standards family, is the most widely deployed standard for multimedia services in traditional broadcast industry, such as ATSC and DVB-T. MPEG standards have been designed to specify essential features for multimedia broadcast applications, such as the structure of multimedia content composed of multiple audio-visual streams and temporal relationships among those streams. One of the new MPEG standards that was recently developed and published, namely MPEG media transport (MMT), has catered for the emerging convergence of digital broadcasting and the Internet. MMT inherits major advantageous features of MPEG-2 TS and adds advanced and innovative features to support broadcast services in the new converged environment. IP-based broadcast standards, e.g., ATSC 3.0, has gained significant attention by the broadcast industries as IP-based broadcast provides more flexible and enriched multimedia broadcast services to users. The ATSC 3.0 has adopted MMT as its one of media delivery technology to strengthen hybrid delivery of multimedia services which could be consumed on multiple devices simultaneously. This paper discusses the use of MMT in ATSC 3.0 service delivery. Important features of MMT will be described together with their restrictions and extensions that are needed to enable efficient delivery of ATSC 3.0 services.

The factors impacting western U.S. winter precipitation during the 2015/16 El Niño are investigated using the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), data, and simulations with the Goddard Earth Observing System, version 5 (GEOS-5), atmospheric general circulation model forced with specified sea surface temperatures (SSTs). Results reveal that the simulated response to the tropical Pacific SST associated with the 2015/16 El Niño was to produce wetter than normal conditions over much of the North American west coast including California—a result at odds with the negative precipitation anomalies observed over much of the southwestern United States. It is shown that two factors acted to partly counter the canonical ENSO response in that region. First, a potentially predictable but modest response to the unusually strong and persistent warm SST in the northeastern Pacific decreased precipitation in the southwestern United States by increasing sea level pressure, driving anticyclonic circulation and atmospheric descent, and reducing moisture transport into that region. Second, large-scale unforced (by SST) components of atmospheric variability (consisting of the leading modes of unpredictable intraensemble variability) resembling the positive phase of the North Atlantic Oscillation and Arctic Oscillation are found to be an important contributor to the drying over the western United States. While a statistical reconstruction of the precipitation from our simulations that account for internal atmospheric variability does much to close the gap between the ensemble-mean and observed precipitation in the southwestern United States, some differences remain, indicating that model error is also playing a role.

The 2015/2016 El Niño is analyzed using atmospheric/oceanic analysis produced using the Goddard Earth Observing System (GEOS) data assimilation systems. As well as describing the structure of the event, a theme of the work is to compare and contrast it with two other strong El Niños, in 1982/1983 and 1997/1998. These three El Niño events are included in the Modern-Era Retrospective analysis for Research and Applications (MERRA) and in the more recent MERRA-2 reanalyses. MERRA-2 allows a comparison of fields derived from the underlying GEOS model, facilitating a more detailed comparison of physical forcing mechanisms in the El Niño events. Various atmospheric/oceanic structures indicate that the 2015/2016 El Niño maximized in the Niño3.4 region, with the large region of warming over most of the Pacific and Indian Ocean. The eastern tropical Indian Ocean, Maritime Continent, and western tropical Pacific are found to be less dry in boreal winter, compared to the earlier two strong events. While the 2015/2016 El Niño had an earlier occurrence of the equatorial Pacific warming and was the strongest event on record in the central Pacific, the 1997/1998 event exhibited a more rapid growth due to stronger westerly wind bursts and Madden-Julian Oscillation during spring, making it the strongest El Niño in the eastern Pacific. Compared to 1982/1983 and 1997/1998, the 2015/2016 event has a shallower thermocline over the eastern Pacific with a weaker zonal contrast of sub-surface water temperatures along the equatorial Pacific. While the three major ENSO events have similarities, each are unique when looking at the atmosphere and ocean surface and sub-surface.

The large-scale impacts of the Arctic Oscillation (AO) and the Eurasian teleconnection (EU) on the East Asian winter climate are compared for the past 34 winters, focusing on (1) interannual monthly to seasonal temperature variability, (2) East Asian winter monsoon (EAWM), and (3) the Siberian high (SH) and cold surge. Regression analysis reveals warming by AO and cooling by EU over mid-latitude East Asia during their positive phase and vice versa (i.e., warm phase: +AO, −EU; cold phase: −AO, +EU). The EU impact was found to be comparable to the AO impact. For example, warm (cold) months during the warm (cold) AO phase are found clearly when the AO is in the same warm (cold) EU phase. No significant correlation was found between East Asian temperature and the AO when the warm (cold) AO coincided with the cold (warm) EU. The well-known relationship of strong (weak) SH during the cold (warm) AO phase was observed significantly more often when the AO was in the same cold (warm) EU phase. Also, the indices of EAWM, cold surge, and SH were more highly correlated with the EU than with the AO. The advective temperature change and associated circulation demonstrate that the large-scale field including the SH over the mid-latitude Asian inland is better represented by the EU, influencing the East Asian climate. These results suggest that the impact of EU should be considered more important than previously thought for a better understanding of East Asian winter temperature and monsoon variability.

The proliferation of new capabilities in affordable smart devices capable of capturing, processing, and rendering audiovisual media content triggers a need for coordination and orchestration between these devices and their capabilities and of the content flowing from and to such devices. The upcoming Moving Picture Experts Group (MPEG) Media Orchestration standard (MORE, ISO/IEC 23001-13) enables the temporal and spatial orchestration of multiple media and metadata streams. The temporal orchestration is about time synchronization of media and sensor captures, processing, and renderings, for which the MORE standard uses and extends a Digital Video Broadcasting standard. The spatial orchestration is about the alignment of (global) position, altitude, and orientation for which the MORE standard provides dedicated timed metadata. Other types of orchestration involve timed metadata for the region of interest, perceptual quality of media, audio-feature extraction, and media timeline correlation. This paper presents the status of the MORE standard as well as the associated technical and experimental support materials. We also link MORE to the recently initiated MPEG immersive project. © 2018 Society of Motion Picture and Television Engineers, Inc.

The sensitivity of tropical cyclones (TCs) to changes in parameterized convection is investigated to improve the simulation of TCs in the North Atlantic. Specifically, the impact of reducing the influence of the Relaxed Arakawa–Schubert (RAS) scheme-based parameterized convection is explored using the Goddard Earth Observing System version 5 (GEOS-5) model at 0.25° horizontal grid spacing. The years 2005 and 2006, characterized by very active and inactive hurricane seasons, respectively, are selected for simulation. A reduction in parameterized deep convection results in an increase in TC activity (e.g., TC number and longer life cycle) to more realistic levels compared to the baseline control configuration. The vertical and horizontal structure of the strongest simulated hurricane shows the maximum wind speed greater than 60 m s−1 and the minimum sea level pressure reaching ~940 mb, which are never achieved by the control configuration. The radius of the maximum wind of ~50 km, the location of the warm core exceeding 10°C, and the horizontal compactness of the hurricane center are all quite realistic without any negatively affecting the atmospheric mean state. This study reveals that an increase in the threshold of minimum entrainment suppresses parameterized deep convection by entraining more dry air into the typical plume. This leads to cooling and drying at the mid to upper troposphere, along with the positive latent heat flux and moistening in the lower troposphere. The resulting increase in conditional instability provides an environment that is more conducive to TC vortex development and upward moisture flux convergence by dynamically resolved moist convection, thereby increasing TC activity.

International audience; As part of a new MPEG-A standardization activity, called Visual Identity Management Application Format(VIMAF), this paper presents an end-to-end encryption solution of Region of Interest (ROI) in both AVC and HEVC encodedstreams for privacy protection applications. This solution uses a selective encryption method that encrypts only the most sensitive information of the video and proposes a new adapted syntax in order to facilitate interoperability between equipments. Objective video quality measurements have shown the robustness of the proposed selective encryption solution with only a slight bitrate increase.

The global characteristics of tropical cyclones (TCs) simulated by several climate models are analyzed and compared with observations. The global climate models were forced by the same sea surface temperature (SST) fields in two types of experiments, using climatological SST and interannually varying SST. TC tracks and intensities are derived from each model's output fields by the group who ran that model, using their own preferred tracking scheme; the study considers the combination of model and tracking scheme as a single modeling system, and compares the properties derived from the different systems. Overall, the observed geographic distribution of global TC frequency was reasonably well reproduced. As expected, with the exception of one model, intensities of the simulated TC were lower than in observations, to a degree that varies considerably across models.