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Sub-seasonal to seasonal (S2S) prediction, especially the prediction of extreme hydroclimate events such as droughts and floods, is not only scientifically challenging but has substantial societal impacts. Motivated by preliminary studies, the Global Energy and Water Exchanges (GEWEX)/Global Atmospheric System Study (GASS) has launched a new initiative called Impact of initialized Land Surface temperature and Snowpack on Sub-seasonal to Seasonal Prediction (LS4P), as the first international grass-root effort to introduce spring land surface temperature (LST)/subsurface temperature (SUBT) anomalies over high mountain areas as a crucial factor that can lead to significant improvement in precipitation prediction through the remote effects of land/atmosphere interactions. LS4P focuses on process understanding and predictability, hence it is different from, and complements, other international projects that focus on the operational S2S prediction. More than forty groups worldwide have participated in this effort, including 21 Earth System Models, 9 regional climate models, and 7 data groups. This paper overviews the history and objectives of LS4P, provides the first phase experimental protocol (LS4P-I) which focuses on the remote effect of the Tibetan Plateau, discusses the LST/SUBT initialization, and presents the preliminary results. Multi-model ensemble experiments and analyses of observational data have revealed that the hydroclimatic effect of the spring LST in the Tibetan Plateau is not limited to the Yangtze River basin but may have a significant large-scale impact on summer precipitation and its S2S prediction. LS4P models are unable to preserve the initialized LST anomalies in producing the observed anomalies largely for two main reasons: i) inadequacies in the land models arising from total soil depths which are too shallow and the use of simplified parameterizations which both tend to limit the soil memory; and ii) reanalysis data, that are used for initial conditions, have large discrepancies from the observed mean state and anomalies of LST over the Tibetan Plateau. Innovative approaches have been developed to largely overcome these problems. [ABSTRACT FROM AUTHOR]

We investigated the ozone pollution trend and its sensitivity to key precursors from 1990 to 2015 in the United States using long-term EPA Air Quality System (AQS) observations and mesoscale simulations. The modeling system, a coupled regional climate–air quality model (CWRF-CMAQ; Climate-Weather Research Forecast and the Community Multiscale Air Quality), captured well the summer surface ozone pollution during the past decades, having a mean slope of linear regression with AQS observations of ∼0.75. While the AQS network has limited spatial coverage and measures only a few key chemical species, CWRF-CMAQ provides comprehensive simulations to enable a more rigorous study of the change in ozone pollution and chemical sensitivity. Analysis of seasonal variations and diurnal cycle of ozone observations showed that peak ozone concentrations in the summer afternoon decreased ubiquitously across the United States, up to 0.5 ppbv yr -1 in major non-attainment areas such as Los Angeles, while concentrations at certain hours such as the early morning and late afternoon increased slightly. Consistent with the AQS observations, CMAQ simulated a similar decreasing trend of peak ozone concentrations in the afternoon, up to 0.4 ppbv yr -1 , and increasing ozone trends in the early morning and late afternoon. A monotonically decreasing trend (up to 0.5 ppbv yr -1) in the odd oxygen (Ox=O3+NO2) concentrations are simulated by CMAQ at all daytime hours. This result suggests that the increased ozone in the early morning and late afternoon was likely caused by reduced NO– O3 titration, driven by continuous anthropogenic NOx emission reductions in the past decades. Furthermore, the CMAQ simulations revealed a shift in chemical regimes of ozone photochemical production. From 1990 to 2015, surface ozone production in some metropolitan areas, such as Baltimore, has transited from a VOC-sensitive environment (>50 % probability) to a NOx -sensitive regime. Our results demonstrated that the long-term CWRF-CMAQ simulations can provide detailed information of the ozone chemistry evolution under a changing climate and may partially explain the US ozone pollution responses to regional and national regulations. [ABSTRACT FROM AUTHOR]