科研成果 by Type: 期刊论文

2022
Wang F, Notaro M, Yu Y, Mao J. Deficient precipitation sensitivity to Sahel land surface forcings among CMIP5 models. International Journal of Climatology [Internet]. 2022. 访问链接Abstract
Abstract The overall performance of the simulated seasonal precipitation response to local terrestrial forcings, namely vegetation abundance and soil moisture, in the Sahel among the Coupled Model Intercomparison Project Phase Five (CMIP5) Earth System Models (ESMs) is systematically investigated and compared with its observational counterpart using a multivariate statistical method. The observed seasonal precipitation response is evaluated against a large ensemble of observational, reanalysis, and satellite data sets to provide quantification of uncertainties. The behaviour of models with and without a Dynamic Global Vegetation Model (DGVM) component is also explored, along with the mechanisms responsible for terrestrial feedback on rainfall. In general, the CMIP5 models can reasonably capture the seasonal evolution of Sahel precipitation and soil moisture, albeit with wet biases during the pre-monsoon period and dry biases during the peak monsoon period. The non-DGVM ESMs simulate comparable leaf area indices (LAIs) with observations, while DGVM-enabled ESMs simulate too much year-round LAI. The variance of precipitation that is attributed to oceanic forcings in CMIP5 is comparable with observations; however, the variance of precipitation that is attributed to terrestrial forcings is smaller in CMIP5 models than observed, especially for non-DGVM ESMs. CMIP5 models, especially those without DGVMs, undervalue precipitation's observed response strength to soil moisture anomalies. In both observations and CMIP5 models, none of the atmospheric variables show significant responses to direct vegetation forcing, except for the response in transpiration. Although vegetation has minimal direct effect on the atmospheric state, it can affect the atmosphere by modifying soil moisture and transpiration rate indirectly, which helps explain the more realistic simulation of rainfall in DGVM-enabled ESMs than non-DGVM ESMs. Coupling of an ESM to a DGVM is critical in generating reasonable land–atmosphere feedback and examining future ecological and climatic changes over the Sahel.
Yu Y, Mao J, Wullschleger SD, Chen A, Shi X, Wang Y, Hoffman FM, Zhang Y, Pierce E. Machine learning–based observation-constrained projections reveal elevated global socioeconomic risks from wildfire. Nature communications. 2022;13:1–11.
2021
Wang S, Yu Y, Zhang X-X, Lu H, Zhang X-Y, Xu Z. Weakened dust activity over China and Mongolia from 2001-2020 associated with climate change and land-use management. Environmental Research Letters. 2021.
Yu Y, Ginoux P. Assessing the contribution of the ENSO and MJO to Australian dust activity based on satellite-and ground-based observations. Atmospheric Chemistry and Physics. 2021;21:8511–8530.
Yu Y, Kalashnikova OV, Garay MJ, Lee H, Choi M, Okin GS, Yorks JE, Campbell JR, Marquis J. A global analysis of diurnal variability in dust and dust mixture using CATS observations. Atmospheric Chemistry and Physics. 2021;21:1427–1447.
Yu Y, Dunne JP, Shevliakova E, Ginoux P, Malyshev S, John JG, Krasting JP. Increased risk of the 2019 Alaskan July fires due to anthropogenic activity. Bulletin of American Meteorological Society. 2021;102(1):S1-S7.
2020
Notaro M, Wang F, Yu Y, Mao J. Projected changes in the terrestrial and oceanic regulators of climate variability across sub-Saharan Africa. Climate Dynamics. 2020;55:1031–1057.
Yu Y, Mao J, Thornton PE, Notaro M, Wullschleger SD, Shi X, Hoffman FM, Wang Y. Quantifying the drivers and predictability of seasonal changes in African fire. Nature communications. 2020;11:1–8.
Yu Y, Notaro M. Observed land surface feedbacks on the Australian monsoon system. Climate Dynamics. 2020;54:3021–3040.
Yu Y, Kalashnikova OV, Garay MJ, Lee H, Notaro M, Campbell JR, Marquis J, Ginoux P, Okin GS. Disproving the Bodélé depression as the primary source of dust fertilizing the Amazon Rainforest. Geophysical Research Letters. 2020;47:e2020GL088020.
Garay MJ, Witek ML, Kahn RA, Seidel FC, Limbacher JA, Bull MA, Diner DJ, Hansen EG, Kalashnikova OV, Lee H, et al. Introducing the 4.4 km spatial resolution Multi-Angle Imaging SpectroRadiometer (MISR) aerosol product. Atmospheric Measurement Techniques. 2020;13:593–628.
2019
Notaro M, Wang F, Yu Y. Elucidating observed land surface feedbacks across sub-Saharan Africa. Climate Dynamics. 2019;53:1741–1763.
Yu Y, Kalashnikova OV, Garay MJ, Notaro M. Climatology of Asian dust activation and transport potential based on MISR satellite observations and trajectory analysis. Atmospheric Chemistry and Physics. 2019;19:363–378.
2018
Lee H, Garay MJ, Kalashnikova OV, Yu Y, Gibson PB. How long should the MISR record be when evaluating aerosol optical depth climatology in climate models?. Remote Sensing. 2018;10:1326.
Yu Y, Notaro M, Wang F, Mao J, Shi X, Wei Y. Validation of a statistical methodology for extracting vegetation feedbacks: focus on North African ecosystems in the Community Earth System Model. Journal of Climate. 2018;31:1565–1586.
Yu Y, Kalashnikova OV, Garay MJ, Lee H, Notaro M. Identification and characterization of dust source regions across North Africa and the Middle East using MISR satellite observations. Geophysical Research Letters. 2018;45:6690–6701.

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