Based on the extreme forecast index (EFI) of ECMWF, the “observed” EFI (OEFI) of observation is defined and the EFI is calibrated. Then the EFI equivalent percentile (EFIEP) and EFI equivalent quantile (EFIEQ) are d...Based on the extreme forecast index (EFI) of ECMWF, the “observed” EFI (OEFI) of observation is defined and the EFI is calibrated. Then the EFI equivalent percentile (EFIEP) and EFI equivalent quantile (EFIEQ) are designed to forecast the daily extreme precipitation quantitatively. The formulation indicates that the EFIEP is correlated not only to the EFI but also to the proportion of no precipitation. This characteristic is prominent as two areas with nearly same EFIs but different proportions of no precipitation. Cases study shows that the EFIEP can forecast reliable percentile of daily precipitation and 100% percentiles are forecasted for over max extreme events. The EFIEQ is a considerable tool for quantitative precipitation forecast (QPF). Compared to the probabilistic forecast of ensemble prediction system (EPS), it is quantitative and synthesizes the advantage of extreme precipitation location forecast of EPS. Using the observations of 2311 stations of China in 2016 to verify the EFIEP and EFIEQ, the results show that the forecast biases are around 1. The threat scores (TS) for 20 years return period events are about 0.21 and 0.07 for 36 and 180 hours lead times respectively. The equivalent threat scores (ETS) are all larger than 0 and nearly equal to the TS. The TS for heavy rainfall are 0.23 and 0.07 for 36 and 180 lead times respectively. The scores are better than those of high resolution deterministic model (HRDet) and show significant forecast skills for quantitative forecast of extreme daily precipitation.展开更多
Aerosol-cloud-radiation interactions represent one of the largest uncertainties in the current climate assessment. Much of the complexity arises from the non-monotonic responses of clouds, precipitation and radiative ...Aerosol-cloud-radiation interactions represent one of the largest uncertainties in the current climate assessment. Much of the complexity arises from the non-monotonic responses of clouds, precipitation and radiative fluxes to aerosol perturbations under various meteorological conditions. In this study, an aerosol-aware WRF model is used to investigate the microphysical and radiative effects of aerosols in three weather systems during the March 2000 Cloud Intensive Observational Period campaign at the US Southern Great Plains. Three simulated cloud ensembles include a low-pressure deep convective cloud system, a collection of less-precipitating stratus and shallow cumulus, and a cold frontal passage. The WRF simulations are evaluated by several ground-based measurements. The microphysical properties of cloud hydrometeors, such as their mass and number concentrations, generally show monotonic trends as a function of cloud condensation nuclei concentrations. Aerosol radiative effects do not influence the trends of cloud microphysics, except for the stratus and shallow cumulus cases where aerosol semi-direct effects are identified. The precipitation changes by aerosols vary with the cloud types and their evolving stages, with a prominent aerosol invigoration effect and associated enhanced precipitation from the convective sources. The simulated aerosol direct effect suppresses precipitation in all three cases but does not overturn the aerosol indirect effect. Cloud fraction exhibits much smaller sensitivity （typically less than 2%） to aerosol perturbations, and the responses vary with aerosol concentrations and cloud regimes. The surface shortwave radiation shows a monotonic decrease by increasing aerosols, while the magnitude of the decrease depends on the cloud type.展开更多
内循环降水率是本地蒸发产生的降水与总降水量的比值,可以表征陆气相互作用的强度。本研究使用准等熵拉格朗日后向轨迹追踪模型(Quasi-isentropic backward trajectory,QIBT),基于全球陆面数据同化产品(Global Land Data Assimilation S...内循环降水率是本地蒸发产生的降水与总降水量的比值,可以表征陆气相互作用的强度。本研究使用准等熵拉格朗日后向轨迹追踪模型(Quasi-isentropic backward trajectory,QIBT),基于全球陆面数据同化产品(Global Land Data Assimilation Systems,GLDAS)的降水和蒸发数据,以及ERA-Interim再分析资料(ERAI),选取降水量与气候平均态相当的2001年,研究了青藏高原内循环降水率。其次,使用2001年ERAI降水和蒸发数据替换GLDAS数据,分析地表数据不确定性对内循环降水率的影响,最后,选取30年降水和蒸发量的极端情况,探讨了极端干湿年对内循环降水率的影响。结果表明,青藏高原内循环降水率东南部小于西北部,年平均内循环降水率为0.42。极端干年大于2001年,极端湿年小于2001年。使用再分析资料的降水和蒸发数据后,内循环降水率减小为0.28,与再分析资料对青藏高原降水量的高估有关。展开更多
文摘Based on the extreme forecast index (EFI) of ECMWF, the “observed” EFI (OEFI) of observation is defined and the EFI is calibrated. Then the EFI equivalent percentile (EFIEP) and EFI equivalent quantile (EFIEQ) are designed to forecast the daily extreme precipitation quantitatively. The formulation indicates that the EFIEP is correlated not only to the EFI but also to the proportion of no precipitation. This characteristic is prominent as two areas with nearly same EFIs but different proportions of no precipitation. Cases study shows that the EFIEP can forecast reliable percentile of daily precipitation and 100% percentiles are forecasted for over max extreme events. The EFIEQ is a considerable tool for quantitative precipitation forecast (QPF). Compared to the probabilistic forecast of ensemble prediction system (EPS), it is quantitative and synthesizes the advantage of extreme precipitation location forecast of EPS. Using the observations of 2311 stations of China in 2016 to verify the EFIEP and EFIEQ, the results show that the forecast biases are around 1. The threat scores (TS) for 20 years return period events are about 0.21 and 0.07 for 36 and 180 hours lead times respectively. The equivalent threat scores (ETS) are all larger than 0 and nearly equal to the TS. The TS for heavy rainfall are 0.23 and 0.07 for 36 and 180 lead times respectively. The scores are better than those of high resolution deterministic model (HRDet) and show significant forecast skills for quantitative forecast of extreme daily precipitation.
基金support provided by NASA ROSES14-ACMAPNSF (Award No. 1700727)+1 种基金supported by the US DOE ASR programsupport of the Jet Propulsion Laboratory, California Institute of Technology, under contract with NASA
文摘Aerosol-cloud-radiation interactions represent one of the largest uncertainties in the current climate assessment. Much of the complexity arises from the non-monotonic responses of clouds, precipitation and radiative fluxes to aerosol perturbations under various meteorological conditions. In this study, an aerosol-aware WRF model is used to investigate the microphysical and radiative effects of aerosols in three weather systems during the March 2000 Cloud Intensive Observational Period campaign at the US Southern Great Plains. Three simulated cloud ensembles include a low-pressure deep convective cloud system, a collection of less-precipitating stratus and shallow cumulus, and a cold frontal passage. The WRF simulations are evaluated by several ground-based measurements. The microphysical properties of cloud hydrometeors, such as their mass and number concentrations, generally show monotonic trends as a function of cloud condensation nuclei concentrations. Aerosol radiative effects do not influence the trends of cloud microphysics, except for the stratus and shallow cumulus cases where aerosol semi-direct effects are identified. The precipitation changes by aerosols vary with the cloud types and their evolving stages, with a prominent aerosol invigoration effect and associated enhanced precipitation from the convective sources. The simulated aerosol direct effect suppresses precipitation in all three cases but does not overturn the aerosol indirect effect. Cloud fraction exhibits much smaller sensitivity （typically less than 2%） to aerosol perturbations, and the responses vary with aerosol concentrations and cloud regimes. The surface shortwave radiation shows a monotonic decrease by increasing aerosols, while the magnitude of the decrease depends on the cloud type.
文摘内循环降水率是本地蒸发产生的降水与总降水量的比值,可以表征陆气相互作用的强度。本研究使用准等熵拉格朗日后向轨迹追踪模型(Quasi-isentropic backward trajectory,QIBT),基于全球陆面数据同化产品(Global Land Data Assimilation Systems,GLDAS)的降水和蒸发数据,以及ERA-Interim再分析资料(ERAI),选取降水量与气候平均态相当的2001年,研究了青藏高原内循环降水率。其次,使用2001年ERAI降水和蒸发数据替换GLDAS数据,分析地表数据不确定性对内循环降水率的影响,最后,选取30年降水和蒸发量的极端情况,探讨了极端干湿年对内循环降水率的影响。结果表明,青藏高原内循环降水率东南部小于西北部,年平均内循环降水率为0.42。极端干年大于2001年,极端湿年小于2001年。使用再分析资料的降水和蒸发数据后,内循环降水率减小为0.28,与再分析资料对青藏高原降水量的高估有关。
