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Q.-S. Ge, J.-Y. Zheng, Z.-X. Hao, P.-Y. Zhang, and W.-C. Wang

Chinese historical documents that contain descriptions of weather conditions can be used for studying climate of the past hundreds or even thousands of years. In this study, the progress of reconstructing a 273-station quantitative precipitation dataset for 1736–1911—a period when records of the depth of rain infiltration (into the ground) and snow depth (above the surface) were kept in the Yu–Xue–Fen–Cun (which is part of memos routinely sent to the emperors during the Qing Dynasty) is reported. To facilitate the rainfall reconstruction, a field program of 29 sites covering different climate regimes and soil characteristics was designed for the purpose of establishing the transfer function between the rain infiltration depth and rainfall amount, while the relation between the snow depth and snowfall is obtained using instrumental measurements of recent decades. The results of the first site at Shijiazhuang (near Beijing) are reported here. The reconstruction shows that the summer and winter precipitation during 1736–1911 were generally greater than their respective 1961–90 means. Two years with extreme summer precipitation are identified—112 mm in 1792 and 1167 mm in 1801; the latter is larger than the 998 mm in 1996, which has been the most severe one of recent decades. The long-term high-resolution quantitative data can be used to study climate variability as well as to evaluate historical climate model simulations.

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Q. Duan, Z. Di, J. Quan, C. Wang, W. Gong, Y. Gan, A. Ye, C. Miao, S. Miao, X. Liang, and S. Fan

Abstract

Weather forecasting skill has been improved over recent years owing to advances in the representation of physical processes by numerical weather prediction (NWP) models, observational systems, data assimilation and postprocessing, new computational capability, and effective communications and training. There is an area that has received less attention so far but can bring significant improvement to weather forecasting—the calibration of NWP models, a process in which model parameters are tuned using certain mathematical methods to minimize the difference between predictions and observations. Model calibration of the NWP models is difficult because 1) there are a formidable number of model parameters and meteorological variables to tune, and 2) a typical NWP model is very expensive to run, and conventional model calibration methods require many model runs (up to tens of thousands) or cannot handle the high dimensionality of NWP models. This study demonstrates that a newly developed automatic model calibration platform can overcome these difficulties and improve weather forecasting through parameter optimization. We illustrate how this is done with a case study involving 5-day weather forecasting during the summer monsoon in the greater Beijing region using the Weather Research and Forecasting Model. The keys to automatic model calibration are to use global sensitivity analysis to screen out the most important parameters influencing model performance and to employ surrogate models to reduce the need for a large number of model runs. Through several optimization and validation studies, we have shown that automatic model calibration can improve precipitation and temperature forecasting significantly according to a number of performance measures.

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H. J. S. Fernando, I. Gultepe, C. Dorman, E. Pardyjak, Q. Wang, S. W Hoch, D. Richter, E. Creegan, S. Gaberšek, T. Bullock, C. Hocut, R. Chang, D. Alappattu, R. Dimitrova, D. Flagg, A. Grachev, R. Krishnamurthy, D. K. Singh, I. Lozovatsky, B. Nagare, A. Sharma, S. Wagh, C. Wainwright, M. Wroblewski, R. Yamaguchi, S. Bardoel, R. S. Coppersmith, N. Chisholm, E. Gonzalez, N. Gunawardena, O. Hyde, T. Morrison, A. Olson, A. Perelet, W. Perrie, S. Wang, and B. Wauer

Abstract

C-FOG is a comprehensive bi-national project dealing with the formation, persistence, and dissipation (life cycle) of fog in coastal areas (coastal fog) controlled by land, marine, and atmospheric processes. Given its inherent complexity, coastal-fog literature has mainly focused on case studies, and there is a continuing need for research that integrates across processes (e.g., air–sea–land interactions, environmental flow, aerosol transport, and chemistry), dynamics (two-phase flow and turbulence), microphysics (nucleation, droplet characterization), and thermodynamics (heat transfer and phase changes) through field observations and modeling. Central to C-FOG was a field campaign in eastern Canada from 1 September to 8 October 2018, covering four land sites in Newfoundland and Nova Scotia and an adjacent coastal strip transected by the Research Vessel Hugh R. Sharp. An array of in situ, path-integrating, and remote sensing instruments gathered data across a swath of space–time scales relevant to fog life cycle. Satellite and reanalysis products, routine meteorological observations, numerical weather prediction model (WRF and COAMPS) outputs, large-eddy simulations, and phenomenological modeling underpin the interpretation of field observations in a multiscale and multiplatform framework that helps identify and remedy numerical model deficiencies. An overview of the C-FOG field campaign and some preliminary analysis/findings are presented in this paper.

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X. Y. Zhang, Y. Q. Wang, W. L. Lin, Y. M. Zhang, X. C. Zhang, S. Gong, P. Zhao, Y. Q. Yang, J. Z. Wang, Q. Hou, X. L. Zhang, H. Z. Che, J. P. Guo, and Y. Li

Before and during the 2008 Beijing Olympics from June to September, ground-based and satellite monitoring were carried out over Beijing and its vicinity (BIV) in a campaign to quantify the outcomes of various emission control measures. These include hourly surface PM10 and PM2.5 and their fraction of black carbon (BC), organics, nitrate, sulfate, ammonium, and daily aerosol optical depth (AOD), together with hourly reactive gases, surface ozone, and daily columnar NO2 from satellite. The analyses, excluding the estimates from weather contributions, demonstrate that after the control measures, including banning ~300,000 “yellow-tag” vehicles from roads, the even–odd turn of motor vehicles on the roads, and emission reduction aiming at coal combustion, were implemented, air quality in Beijing improved substantially. The levels of NO, NO2, NOx, CO, SO2, BC, organics, and nitrate dropped by about 30%–60% and the ozone moderately increased by ~40% while the sulfate and ammonium exhibited different patterns during various control stages. Weather conditions have a great impact on the summertime secondary aerosol (~80% of total PM) and O3 formations over BIV. During the Olympic Game period, various atmospheric components decreased dramatically at Beijing compared to the same period in the previous years. This decrease was related not only to the implementation of rigorous control measures, but also to the favorable weather processes. The subtropical high was located to the south so that Beijing's weather was dominated by the interaction between a frequently eastward shifting trough in the westerlies and a cold continental high with clear to cloudy days or showery weather.

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David M. L. Sills, Gregory A. Kopp, Lesley Elliott, Aaron L. Jaffe, Liz Sutherland, Connell S. Miller, Joanne M. Kunkel, Emilio Hong, Sarah A. Stevenson, and William Wang

Abstract

Canada is a vast country with most of its population located along its southern border. Large areas are sparsely populated and/or heavily forested, and severe weather reports are rare when thunderstorms occur there. Thus, it has been difficult to accurately assess the true tornado climatology and risk. It is also important to establish a reliable baseline for tornado-related climate change studies. The Northern Tornadoes Project (NTP), led by Western University, is an ambitious multidisciplinary initiative aimed at detecting and documenting every tornado that occurs across Canada. A team of meteorologists and wind engineers collects research-quality data during each damage investigation via thorough ground surveys and high-resolution satellite, aircraft, and drone imaging. Crowdsourcing through social media is also key to tracking down events. In addition, NTP conducts research to improve our ability to detect and accurately assess tornadoes that affect forests, cropland, and grassland. An open data website allows sharing of resulting datasets and analyses. Pilot investigations were carried out during the warm seasons of 2017 and 2018, with the scope expanding from the detection of any tornadoes in heavily forested regions of central Canada in 2017 to the detection of all EF1+ tornadoes in Ontario plus all significant events outside of Ontario in 2018. The 2019 season was the first full campaign, systematically collecting research-quality tornado data across the entire country. To date, the project has found 89 tornadoes that otherwise would not have been identified, and increased the national tornado count in 2019 by 78%.

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R. J. Barthelmie, P. Crippa, H. Wang, C. M. Smith, R. Krishnamurthy, A. Choukulkar, R. Calhoun, D. Valyou, P. Marzocca, D. Matthiesen, G. Brown, and S. C. Pryor

The 3D wind and turbulence characteristics of the atmospheric boundary layer experiment (3D Wind) was conducted to evaluate innovative remote sensing and in situ platforms for measurements of wind and turbulence regimes. The experiment is part of a planned series that focuses on quantifying wind and turbulence characteristics at the scales of modern wind turbines and wind farms and was conducted in northern Indiana in May 2012. 3D Wind had the following specific objectives: (i) intercomparison experiments evaluating wind speed profiles across the wind turbine rotor plane from traditional cup anemometers and wind vanes on a meteorological mast and from a tethered balloon, sonic anemometers (mast mounted and on an unmanned aerial vehicle), three vertical-pointing (continuous wave) lidars and a pulsed scanning lidar, and (ii) integrate these measurements and output from 3-km-resolution (over the inner domain) simulations with the Weather Research and Forecasting Model to develop a detailed depiction of the atmospheric flow, upwind, within, and downwind of a large, irregularly spaced wind farm. This paper provides an overview of the measurement techniques, their advantages and disadvantages focusing on the integration of wind and turbulence characteristics that are necessary for wind farm development and operation. Analyses of the measurements are summarized to characterize instrument cross comparison, wind profiles, and spatial gradients and wind turbine wakes.

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D. H. Bromwich, A. B. Wilson, L. Bai, Z. Liu, M. Barlage, C.-F. Shih, S. Maldonado, K. M. Hines, S.-H. Wang, J. Woollen, B. Kuo, H.-C. Lin, T.-K. Wee, M. C. Serreze, and J. E. Walsh

Abstract

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.

Open access
D. D. Turner, A. M. Vogelmann, R. T. Austin, J. C. Barnard, K. Cady-Pereira, J. C. Chiu, S. A. Clough, C. Flynn, M. M. Khaiyer, J. Liljegren, K. Johnson, B. Lin, C. Long, A. Marshak, S. Y. Matrosov, S. A. McFarlane, M. Miller, Q. Min, P. Minimis, W. O'Hirok, Z. Wang, and W. Wiscombe

Many of the clouds important to the Earth's energy balance, from the Tropics to the Arctic, contain small amounts of liquid water. Longwave and shortwave radiative fluxes are very sensitive to small perturbations of the cloud liquid water path (LWP), when the LWP is small (i.e., < 100 g m−2; clouds with LWP less than this threshold will be referred to as “thin”). Thus, the radiative properties of these thin liquid water clouds must be well understood to capture them correctly in climate models. We review the importance of these thin clouds to the Earth's energy balance, and explain the difficulties in observing them. In particular, because these clouds are thin, potentially mixed phase, and often broken (i.e., have large 3D variability), it is challenging to retrieve their microphysical properties accurately. We describe a retrieval algorithm intercomparison that was conducted to evaluate the issues involved. The intercomparison used data collected at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site and included 18 different algorithms to evaluate their retrieved LWP, optical depth, and effective radii. Surprisingly, evaluation of the simplest case, a single-layer overcast stratocumulus, revealed that huge discrepancies exist among the various techniques, even among different algorithms that are in the same general classification. This suggests that, despite considerable advances that have occurred in the field, much more work must be done, and we discuss potential avenues for future research.)

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J. Fishman, L. T. Iraci, J. Al-Saadi, K. Chance, F. Chavez, M. Chin, P. Coble, C. Davis, P. M. DiGiacomo, D. Edwards, A. Eldering, J. Goes, J. Herman, C. Hu, D. J. Jacob, C. Jordan, S. R. Kawa, R. Key, X. Liu, S. Lohrenz, A. Mannino, V. Natraj, D. Neil, J. Neu, M. Newchurch, K. Pickering, J. Salisbury, H. Sosik, A. Subramaniam, M. Tzortziou, J. Wang, and M. Wang

The Geostationary Coastal and Air Pollution Events (GEO-CAPE) mission was recommended by the National Research Council's (NRC's) Earth Science Decadal Survey to measure tropospheric trace gases and aerosols and coastal ocean phytoplankton, water quality, and biogeochemistry from geostationary orbit, providing continuous observations within the field of view. To fulfill the mandate and address the challenge put forth by the NRC, two GEO-CAPE Science Working Groups (SWGs), representing the atmospheric composition and ocean color disciplines, have developed realistic science objectives using input drawn from several community workshops. The GEO-CAPE mission will take advantage of this revolutionary advance in temporal frequency for both of these disciplines. Multiple observations per day are required to explore the physical, chemical, and dynamical processes that determine tropospheric composition and air quality over spatial scales ranging from urban to continental, and over temporal scales ranging from diurnal to seasonal. Likewise, high-frequency satellite observations are critical to studying and quantifying biological, chemical, and physical processes within the coastal ocean. These observations are to be achieved from a vantage point near 95°–100°W, providing a complete view of North America as well as the adjacent oceans. The SWGs have also endorsed the concept of phased implementation using commercial satellites to reduce mission risk and cost. GEO-CAPE will join the global constellation of geostationary atmospheric chemistry and coastal ocean color sensors planned to be in orbit in the 2020 time frame.

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Z. Q. Li, H. Xu, K. T. Li, D. H. Li, Y. S. Xie, L. Li, Y. Zhang, X. F. Gu, W. Zhao, Q. J. Tian, R. R. Deng, X. L. Su, B. Huang, Y. L. Qiao, W. Y. Cui, Y. Hu, C. L. Gong, Y. Q. Wang, X. F. Wang, J. P. Wang, W. B. Du, Z. Q. Pan, Z. Z. Li, and D. Bu

Abstract

An overview of Sun–Sky Radiometer Observation Network (SONET) measurements in China is presented. Based on observations at 16 distributed SONET sites in China, atmospheric aerosol parameters are acquired via standardization processes of operational measurement, maintenance, calibration, inversion, and quality control implemented since 2010. A climatology study is performed focusing on total columnar atmospheric aerosol characteristics, including optical (aerosol optical depth, ÅngstrÖm exponent, fine-mode fraction, single-scattering albedo), physical (volume particle size distribution), chemical composition (black carbon; brown carbon; fine-mode scattering component, coarse-mode component; and aerosol water), and radiative properties (aerosol radiative forcing and efficiency). Data analyses show that aerosol optical depth is low in the west but high in the east of China. Aerosol composition also shows significant spatial and temporal variations, leading to noticeable diversities in optical and physical property patterns. In west and north China, aerosols are generally affected by dust particles, while monsoon climate and human activities impose remarkable influences on aerosols in east and south China. Aerosols in China exhibit strong light-scattering capability and result in significant radiative cooling effects.

Open access