Journal cover Journal topic
Atmospheric Chemistry and Physics An interactive open-access journal of the European Geosciences Union
Atmos. Chem. Phys., 17, 13967-13982, 2017
https://doi.org/10.5194/acp-17-13967-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Research article
23 Nov 2017
Potential influences of neglecting aerosol effects on the NCEP GFS precipitation forecast
Mengjiao Jiang1,2, Jinqin Feng3, Zhanqing Li1,2, Ruiyu Sun4, Yu-Tai Hou4, Yuejian Zhu4, Bingcheng Wan5, Jianping Guo6, and Maureen Cribb2 1State Key Laboratory of Earth Surface Processes and Resource Ecology, College of Global Change and Earth System Science, Beijing Normal University, Beijing, China
2Department of Atmospheric and Oceanic Science and ESSIC, University of Maryland, College Park, Maryland, USA
3Longyan Meteorological Office of Fujian Province, Longyan, Fujian, China
4Environmental Modeling Center, National Centers for Environmental Prediction, National Oceanic and Atmospheric Administration, College Park, Maryland, USA
5State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
6State Key Laboratory of Severe Weather, Chinese Academy of Meteorological Sciences, Beijing, China
Abstract. Aerosol–cloud interactions (ACIs) have been widely recognized as a factor affecting precipitation. However, they have not been considered in the operational National Centers for Environmental Predictions Global Forecast System model. We evaluated the potential impact of neglecting ACI on the operational rainfall forecast using ground-based and satellite observations and model reanalysis. The Climate Prediction Center unified gauge-based precipitation analysis and the Modern-Era Retrospective analysis for Research and Applications Version 2 aerosol reanalysis were used to evaluate the forecast in three countries for the year 2015. The overestimation of light rain (47.84 %) and underestimation of heavier rain (31.83, 52.94, and 65.74 % for moderate rain, heavy rain, and very heavy rain, respectively) from the model are qualitatively consistent with the potential errors arising from not accounting for ACI, although other factors cannot be totally ruled out. The standard deviation of the forecast bias was significantly correlated with aerosol optical depth in Australia, the US, and China. To gain further insight, we chose the province of Fujian in China to pursue a more insightful investigation using a suite of variables from gauge-based observations of precipitation, visibility, water vapor, convective available potential energy (CAPE), and satellite datasets. Similar forecast biases were found: over-forecasted light rain and under-forecasted heavy rain. Long-term analyses revealed an increasing trend in heavy rain in summer and a decreasing trend in light rain in other seasons, accompanied by a decreasing trend in visibility, no trend in water vapor, and a slight increasing trend in summertime CAPE. More aerosols decreased cloud effective radii for cases where the liquid water path was greater than 100 g m−2. All findings are consistent with the effects of ACI, i.e., where aerosols inhibit the development of shallow liquid clouds and invigorate warm-base mixed-phase clouds (especially in summertime), which in turn affects precipitation. While we cannot establish rigorous causal relations based on the analyses presented in this study, the significant rainfall forecast bias seen in operational weather forecast model simulations warrants consideration in future model improvements.

Citation: Jiang, M., Feng, J., Li, Z., Sun, R., Hou, Y.-T., Zhu, Y., Wan, B., Guo, J., and Cribb, M.: Potential influences of neglecting aerosol effects on the NCEP GFS precipitation forecast, Atmos. Chem. Phys., 17, 13967-13982, https://doi.org/10.5194/acp-17-13967-2017, 2017.
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Short summary
Aerosol–cloud interactions have been recognized as playing an important role in precipitation. As a benchmark evaluation of model results that exclude aerosol effects, the operational precipitation forecast (before any aerosol effects included) is evaluated using multiple datasets with the goal of determining if there is any link between the model bias and aerosol loading. The forecast model overestimates light and underestimates heavy rain. Aerosols suppress light rain and enhance heavy rain.
Aerosol–cloud interactions have been recognized as playing an important role in precipitation....
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