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The Arctic is a vital component of the global climate, and its rapid environmental evolution is an important element of climate change around the world. To detect and diagnose the changes occurring to the coupled Arctic climate system, a state-of-the-art synthesis for assessment and monitoring is imperative. This paper presents the Arctic System Reanalysis, version 2 (ASRv2), a multiagency, university-led retrospective analysis (reanalysis) of the greater Arctic region using blends of the polar-optimized version of the Weather Research and Forecasting (Polar WRF) Model and WRF three-dimensional variational data assimilated observations for a comprehensive integration of the regional climate of the Arctic for 2000-12. New features in ASRv2 compared to version 1 (ASRv1) include 1) higher-resolution depiction in space (15-km horizontal resolution), 2) updated model physics including subgrid-scale cloud fraction interaction with radiation, and 3) a dual outer-loop routine for more accurate data assimilation. ASRv2 surface and pressure-level products are available at 3-hourly and monthly mean time scales at the National Center for Atmospheric Research (NCAR). Analysis of ASRv2 reveals superior reproduction of near-surface and tropospheric variables. Broadscale analysis of forecast precipitation and site-specific comparisons of downward radiative fluxes demonstrate significant improvement over ASRv1. The high-resolution topography and land surface, including weekly updated vegetation and realistic sea ice fraction, sea ice thickness, and snow-cover depth on sea ice, resolve finescale processes such as topographically forced winds. Thus, ASRv2 permits a reconstruction of the rapid change in the Arctic since the beginning of the twenty-first century-complementing global reanalyses. ASRv2 products will be useful for environmental models, verification of regional processes, or siting of future observation networks. [ABSTRACT FROM AUTHOR]

This paper presents the background, scientific objectives, experimental design, and preliminary achievements of the Third Tibetan Plateau (TP) Atmospheric Scientific Experiment (TIPEX-III) for 8-10 years. It began in 2013 and has expanded plateau-scale observation networks by adding observation stations in data-scarce areas; executed integrated observation missions for the land surface, planetary boundary layer, cloud-precipitation, and troposphere-stratosphere exchange processes by coordinating ground-based, air-based, and satellite facilities; and achieved noticeable progress in data applications. A new estimation gives a smaller bulk transfer coefficient of surface sensible heat over the TP, which results in a reduction of the possibly overestimated heat intensity found in previous studies. Summer cloud-precipitation microphysical characteristics and cloud radiative effects over the TP are distinguished from those over the downstream plains. Warm rain processes play important roles in the development of cloud and precipitation over the TP. The lower-tropospheric ozone maximum over the northeastern TP is attributed to the regional photochemistry and long-range ozone transports, and the heterogeneous chemical processes of depleting ozone near the tropopause might not be a dominant mechanism for the summer upper-tropospheric-lower-stratospheric ozone valley over the southeastern TP. The TP thermodynamic function not only affects the local atmospheric water maintenance and the downstream precipitation and haze events but also modifies extratropical atmospheric teleconnections like the Asia-Pacific Oscillation, subtropical anticyclones over the North Pacific and Atlantic, and temperature and precipitation over Africa, Asia, and North America. These findings provide new insights into understanding land-atmosphere coupled processes over the TP and their effects, improving model parameterization schemes, and enhancing weather and climate forecast skills. [ABSTRACT FROM AUTHOR]

The 2021 northwest Pacific marine heatwave was favored by the atmospheric and oceanic conditions; changes in the mean climate due to anthropogenic warming made the event 43 times more likely. [ABSTRACT FROM AUTHOR]

To better understand variability in weather and climate, it is vital to address past atmospheric circulation. This need requires meteorological information not just from the surface but also at upper levels. Current global upper-level datasets only reach back to the 1940s or 1950s and do not cover some important periods in the first half of the twentieth century. Extending the observational record is therefore considered important in order to analyze climate variability in the past and verify global climate models used to predict future climate change. Although earlier upper-air data from platforms such as radio-sondes, aircraft, pilot balloons, registering balloons, and kites are available from various sources, no systematic compilation and quality assessment of upper-level data prior to the International Geophysical Year (1957/58) has ever been performed. Here we present the Comprehensive Historical Upper-Air Network (CHUAN). It is a consistent global historical upper-air dataset that has been derived from heterogeneous data available from various sources as well as from newly digitized data. This paper describes the CHUAN dataset, the metadata, the quality control procedures, and the relationship to existing datasets. Some examples are given of its usefulness for analyzing weather and climate during the first half of the twentieth century. The CHUAN dataset comprises 3987 station records worldwide or about 16.4 million profiles (of which 12.6 million are before 1958 and 5.3 million, primarily from pilot balloons, are before 1948). A monthly mean version can be downloaded from the World Wide Web (). A supplement to this article is available online: DOI: [ABSTRACT FROM AUTHOR]

The article presents research into the application of regional dynamical downscaling for the evaluation of air quality. Meteorologists' ability to answer questions regarding the impact of climate change on air quality and vice versa depends on the ability of climatology models to simulate meteorological conditions. One atmospheric simulation is driven by a global circulation model (GCM) control simulation while a second atmospheric simulation is driven by a global reanalysis. A comparison is made of selected meteorological variables, namely diurnal wind patterns, unvented hours, precipitation, and 500-hPa heights.

Earth's climate is strongly influenced by energy deficits at the poles that emit more thermal energy than they receive from the sun. Energy exchanges between the surface and atmosphere influence the local environment while heat transport from lower latitudes drives midlatitude atmospheric and oceanic circulations. In the Arctic, in particular, local energy imbalances induce strong seasonality in surface–atmosphere heat exchanges and an acute sensitivity to forced climate variations. Despite these important local and global influences, the largest contributions to the polar atmospheric and surface energy budgets have not been fully characterized. The spectral variation of far-infrared radiation that makes up 60% of polar thermal emission has never been systematically measured impeding progress toward consensus in predicted rates of Arctic warming, sea ice decline, and ice sheet melt. Enabled by recent advances in sensor miniaturization and CubeSat technology, the Polar Radiant Energy in the Far Infrared Experiment (PREFIRE) mission will document, for the first time, the spectral, spatial, and temporal variations of polar far-infrared emission. Selected under NASA's Earth Ventures Instrument (EVI) program, PREFIRE will utilize new lightweight, low-power, ambient temperature detectors capable of measuring at wavelengths up to 50 μm to quantify Earth's far-infrared spectrum. Estimates of spectral surface emissivity, water vapor, cloud properties, and the atmospheric greenhouse effect derived from these measurements offer the potential to advance our understanding of the factors that modulate thermal fluxes in the cold, dry conditions characteristic of the polar regions. [ABSTRACT FROM AUTHOR]

Recent studies have indicated the importance of fall climate forcings and teleconnections in influencing the climate of the northern mid- to high latitudes. Here, we present some exploratory analyses using observational data and seasonal hindcasts, with the aim of highlighting the potential of the El Niño–Southern Oscillation (ENSO) as a driver of climate variability during boreal late fall and early winter (November and December) in the North Atlantic–European sector, and motivating further research on this relatively unexplored topic. The atmospheric ENSO teleconnection in November and December is reminiscent of the east Atlantic pattern and distinct from the well-known arching extratropical Rossby wave train found from January to March. Temperature and precipitation over Europe in November are positively correlated with the Niño-3.4 index, which suggests a potentially important ENSO climate impact during late fall. In particular, the ENSO-related temperature anomaly extends over a much larger area than during the subsequent winter months. We discuss the implications of these results and pose some research questions. [ABSTRACT FROM AUTHOR]

The article offers information on the global climatic conditions in 2014. Various topics discussed include global surface temperature, hydrological cycle, atmospheric circulation, temperature in the North Atlantic region, air temperature in Arctic region, history of floods in Balkan Peninsula and upper ocean stratification.

The Second Global Soil Wetness Project (GSWP-2) is an initiative to compare and evaluate 10-year simulations by a broad range of land surface models under controlled conditions. A major product of GSWP-2 is the first global gridded multimodel analysis of land surface state variables and fluxes for use by meteorologists, hydrologists, engineers, biogeochemists, agronomists, botanists, ecologists, geographers, climatologists, and educators. Simulations by 13 land models from five nations have gone into production of the analysis. The models are driven by forcing data derived from a combination of gridded atmospheric reanalyses and observations. The resulting analysis consists of multimodel means and standard deviations on the monthly time scale, including profiles of soil moisture and temperature at six levels, as well as daily and climatological (mean annual cycle) fields for over 50 land surface variables. The monthly standard deviations provide a measure of model agreement that may be used as a quality metric. An overview of key characteristics of the analysis is presented here, along with information on obtaining the data. [ABSTRACT FROM AUTHOR]

The article reports on the study on the variability of coastally trapped wind reversals, or southerly surges, that occur along the U.S. West Coast during the warm season. An analysis of coastal buoy observations for three years indicated that different types of events occur. Several distinct differences occur that suggest a direct link between the coastal dynamics and the synoptic-scale forcing. The dynamic link between the synoptic-scale forcing and coastal response will be examined more thoroughly in future work using numerical simulations.