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Abstract. Fires have influenced atmospheric composition and climate since the rise of vascular plants, and satellite data have shown the overall global extent of fires. Our knowledge of historic fire emissions has progressively improved over the past decades due mostly to the development of new proxies and the improvement of fire models. Currently, there is a suite of proxies including sedimentary charcoal records, measurements of fire-emitted trace gases and black carbon stored in ice and firn, and visibility observations. These proxies provide opportunities to extrapolate emission estimates back in time based on satellite data starting in 1997, but each proxy has strengths and weaknesses regarding, for example, the spatial and temporal extents over which they are representative. We developed a new historic biomass burning emissions dataset starting in 1750 that merges the satellite record with several existing proxies and uses the average of six models from the Fire Model Intercomparison Project (FireMIP) protocol to estimate emissions when the available proxies had limited coverage. According to our approach, global biomass burning emissions were relatively constant, with 10-year averages varying between 1.8 and 2.3 Pg C yr −1 . Carbon emissions increased only slightly overPublished by Copernicus Publications on behalf of the European Geosciences Union. the full time period and peaked during the 1990s after which they decreased gradually. There is substantial uncertainty in these estimates, and patterns varied depending on choices regarding data representation, especially on regional scales. The observed pattern in fire carbon emissions is for a large part driven by African fires, which accounted for 58 % of global fire carbon emissions. African fire emissions declined since about 1950 due to conversion of savanna to cropland, and this decrease is partially compensated for by increasing emissions in deforestation zones of South America and Asia. These global fire emission estimates are mostly suited for global analyses and will be used in the Coupled Model Intercomparison Project Phase 6 (CMIP6) simulations.

The measurement and simulation of water vapor isotopic composition has matured rapidly over the last decade, with long‐term data sets and comprehensive modeling capabilities now available. Theories for water vapor isotopic composition have been developed by extending the theories that have been used for the isotopic composition of precipitation to include a more nuanced understanding of evaporation, large‐scale mixing, deep convection, and kinetic fractionation. The technologies for in situ and remote sensing measurements of water vapor isotopic composition have developed especially rapidly over the last decade, with discrete water vapor sampling methods, based on mass spectroscopy, giving way to laser spectroscopic methods and satellite‐ and ground‐based infrared absorption techniques. The simulation of water vapor isotopic composition has evolved from General Circulation Model (GCM) methods for simulating precipitation isotopic composition to sophisticated isotope‐enabled microphysics schemes using higher‐order moments for water and ice size distributions. The incorporation of isotopes into GCMs has enabled more detailed diagnostics of the water cycle and has led to improvements in its simulation. The combination of improved measurement and modeling of water vapor isotopic composition opens the door to new advances in our understanding of the atmospheric water cycle, in processes ranging from the marine boundary layer, through deep convection and tropospheric mixing, and into the water cycle of the stratosphere. Finally, studies of the processes governing modern water vapor isotopic composition provide an improved framework for the interpretation of paleoclimate proxy records of the hydrological cycle.

Results from simulations performed for the Atmospheric Chemistry and Climate Modeling Intercomparison Project (ACCMIP) are analysed to examine how OH and methane lifetime may change from present day to the future, under different climate and emissions scenarios. Present day (2000) mean tropospheric chemical lifetime derived from the ACCMIP multi-model mean is 9.8 ± 1.6 yr (9.3 ± 0.9 yr when only including selected models), lower than a recent observationally-based estimate, but with a similar range to previous multi-model estimates. Future model projections are based on the four Representative Concentration Pathways (RCPs), and the results also exhibit a large range. Decreases in global methane lifetime of 4.5 ± 9.1% are simulated for the scenario with lowest radiative forcing by 2100 (RCP 2.6), while increases of 8.5 ± 10.4% are simulated for the scenario with highest radiative forcing (RCP 8.5). In this scenario, the key driver of the evolution of OH and methane lifetime is methane itself, since its concentration more than doubles by 2100 and it consumes much of the OH that exists in the troposphere. Stratospheric ozone recovery, which drives tropospheric OH decreases through photolysis modifications, also plays a partial role. In the other scenarios, where methane changes are less drastic, the interplay between various competing drivers leads to smaller and more diverse OH and methane lifetime responses, which are difficult to attribute. For all scenarios, regional OH changes are even more variable, with the most robust feature being the large decreases over the remote oceans in RCP8.5. Through a regression analysis, we suggest that differences in emissions of non-methane volatile organic compounds and in the simulation of photolysis rates may be the main factors causing the differences in simulated present day OH and methane lifetime. Diversity in predicted changes between present day and future OH was found to be associated more strongly with differences in modelled temperature and stratospheric ozone changes. Finally, through perturbation experiments we calculated an OH feedback factor (F) of 1.24 from present day conditions (1.50 from 2100 RCP8.5 conditions) and a climate feedback on methane lifetime of 0.33 ± 0.13 yr K⁻¹, on average. Models that did not include interactive stratospheric ozone effects on photolysis showed a stronger sensitivity to climate, as they did not account for negative effects of climate-driven stratospheric ozone recovery on tropospheric OH, which would have partly offset the overall OH/methane lifetime response to climate change

The 2015 fire season and related smoke pollution in Indonesia was more severe than the major 2006 episode, making it the most severe season observed by the NASA Earth Observing System satellites that go back to the early 2000s, namely active fire detections from the Terra and Aqua Moderate Resolution Imaging Spectroradiometers (MODIS), MODIS aerosol optical depth, Terra Measurement of Pollution in the Troposphere (MOPITT) carbon monoxide (CO), Aqua Atmospheric Infrared Sounder (AIRS) CO, Aura Ozone Monitoring Instrument (OMI) aerosol index, and Aura Microwave Limb Sounder (MLS) CO. The MLS CO in the upper troposphere showed a plume of pollution stretching from East Africa to the western Pacific Ocean that persisted for 2 mo. Longer-term records of airport visibility in Sumatra and Kalimantan show that 2015 ranked after 1997 and alongside 1991 and 1994 as among the worst episodes on record. Analysis of yearly dry season rainfall from the Tropical Rainfall Measurement Mission (TRMM) and rain gauges shows that, due to the continued use of fire to clear and prepare land on degraded peat, the Indonesian fire environment continues to have nonlinear sensitivity to dry conditions during prolonged periods with less than 4 mm/d of precipitation, and this sensitivity appears to have increased over Kalimantan. Without significant reforms in land use and the adoption of early warning triggers tied to precipitation forecasts, these intense fire episodes will reoccur during future droughts, usually associated with El Niño events.

The formation of topologically closed packed (TCP) phase was studied for a series of nickel base superalloys containing rhenium. The alloys were found to form three types of TCP phases: rhombohedral mu, tetragonal sigma and a relatively unknown orthorhomic phase, P. The crystal structures of these phases are closely related. They often coexist in the alloy, even within the same precipitate. The segmented appearance of the precipitates is due to a "basket weave" morphology, consisting of ribbons of precipitates, overlapping at 90 degree angles. Computer programs such as PHACOMP which are used to predict alloy stability do not necessarily provide good correlation with TCP formation in Re containing alloys. The paper describes in detail the nature and formation of TCP phases in one specific alloy composition. Superalloys 1988

[1] Drought and sea surface temperature were examined as the causes of severe biomass burning C emissions in Indonesia for [1997][1998][1999][2000][2001][2002][2003][2004][2005][2006], obtained from the Global Fire Emissions Database. Eighteen predictor variables were considered under log linear and piecewise regression models. The predictor variables considered were precipitation totals of up to 6 months, output from two soil moisture models, and sea surface temperature (SST) indicators reflecting El Niño and Indian Ocean Dipole strength. Nonparametric bootstrap techniques were used to estimate confidence intervals for predictability and thresholds below which severe C emissions are likely. Across equatorial Southeast Asia, the best predictor was 3-month total precipitation, which explained 79% of variance in C emissions. When considered individually, and with the incorporation of satellite precipitation estimates, predictability for southern Sumatra and southern Kalimantan improved to 97% and 92%, respectively, using 4-month total precipitation. There is a high risk of severe burning when 4-month precipitation falls below thresholds of 350 mm in southern Sumatra and 650 mm in southern Kalimantan and when 6-month precipitation falls below 900 mm in Papua. In general, simple precipitation totals outperformed more complicated soil moisture models and SST-based indices. Physically, seasonal precipitation controls fire emissions through its regulation of groundwater level and, hence, the amount of peat available for drying. Seasonal precipitation, in turn, is strongly influenced by SST patterns in the tropical Pacific and Indian oceans. The most severe drought and fire events appear equally influenced by Indian Ocean Dipole events and El Niño events.

Northwestern India is known as the “breadbasket” of the country producing two-thirds of food grains, with wheat and rice as the principal crops grown under the crop rotation system. Agricultural data from India indicates a 25% increase in the post-monsoon rice crop production in Punjab during 2002–2016. NASA’s A-train satellite sensors detect a consistent increase in the vegetation index (net 21%) and post-harvest agricultural fire activity (net ~60%) leading to nearly 43% increase in aerosol loading over the populous Indo-Gangetic Plain in northern India. The ground-level particulate matter (PM2.5) downwind over New Delhi shows a concurrent uptrend of net 60%. The effectiveness of a robust satellite-based relationship between vegetation index—a proxy for crop amounts, and post-harvest fires—a precursor of extreme air pollution events, has been further demonstrated in predicting the seasonal agricultural burning. An efficient crop residue management system is critically needed towards eliminating open field burning to mitigate episodic hazardous air quality over northern India.