2016 Vol. 33, No. 9
Display Method:
2016, 33(9): 1005-1023.
doi: 10.1007/s00376-016-5247-3
Abstract:
This study investigated the drivers and physical processes for the abrupt decadal summer surface warming and increases in hot temperature extremes that occurred over Northeast Asia in the mid-1990s. Observations indicate an abrupt increase in summer mean surface air temperature (SAT) over Northeast Asia since the mid-1990s. Accompanying this abrupt surface warming, significant changes in some temperature extremes, characterized by increases in summer mean daily maximum temperature (Tmax), daily minimum temperature (Tmin), annual hottest day temperature (TXx), and annual warmest night temperature (TNx) were observed. There were also increases in the frequency of summer days (SU) and tropical nights (TR). Atmospheric general circulation model experiments forced by changes in sea surface temperature (SST)/ sea ice extent (SIE), anthropogenic greenhouse gas (GHG) concentrations, and anthropogenic aerosol (AA) forcing, relative to the period 1964-93, reproduced the general patterns of observed summer mean SAT changes and associated changes in temperature extremes, although the abrupt decrease in precipitation since the mid-1990s was not simulated. Additional model experiments with different forcings indicated that changes in SST/SIE explained 76% of the area-averaged summer mean surface warming signal over Northeast Asia, while the direct impact of changes in GHG and AA explained the remaining 24% of the surface warming signal. Analysis of physical processes indicated that the direct impact of the changes in AA (through aerosol-radiation and aerosol-cloud interactions), mainly related to the reduction of AA precursor emissions over Europe, played a dominant role in the increase in TXx and a similarly important role as SST/SIE changes in the increase in the frequency of SU over Northeast Asia via AA-induced coupled atmosphere-land surface and cloud feedbacks, rather than through a direct impact of AA changes on cloud condensation nuclei. The modelling results also imply that the abrupt summer surface warming and increases in hot temperature extremes over Northeast Asia since the mid-1990s will probably sustain in the next few decades as GHG concentrations continue to increase and AA precursor emissions over both North America and Europe continue to decrease.
This study investigated the drivers and physical processes for the abrupt decadal summer surface warming and increases in hot temperature extremes that occurred over Northeast Asia in the mid-1990s. Observations indicate an abrupt increase in summer mean surface air temperature (SAT) over Northeast Asia since the mid-1990s. Accompanying this abrupt surface warming, significant changes in some temperature extremes, characterized by increases in summer mean daily maximum temperature (Tmax), daily minimum temperature (Tmin), annual hottest day temperature (TXx), and annual warmest night temperature (TNx) were observed. There were also increases in the frequency of summer days (SU) and tropical nights (TR). Atmospheric general circulation model experiments forced by changes in sea surface temperature (SST)/ sea ice extent (SIE), anthropogenic greenhouse gas (GHG) concentrations, and anthropogenic aerosol (AA) forcing, relative to the period 1964-93, reproduced the general patterns of observed summer mean SAT changes and associated changes in temperature extremes, although the abrupt decrease in precipitation since the mid-1990s was not simulated. Additional model experiments with different forcings indicated that changes in SST/SIE explained 76% of the area-averaged summer mean surface warming signal over Northeast Asia, while the direct impact of changes in GHG and AA explained the remaining 24% of the surface warming signal. Analysis of physical processes indicated that the direct impact of the changes in AA (through aerosol-radiation and aerosol-cloud interactions), mainly related to the reduction of AA precursor emissions over Europe, played a dominant role in the increase in TXx and a similarly important role as SST/SIE changes in the increase in the frequency of SU over Northeast Asia via AA-induced coupled atmosphere-land surface and cloud feedbacks, rather than through a direct impact of AA changes on cloud condensation nuclei. The modelling results also imply that the abrupt summer surface warming and increases in hot temperature extremes over Northeast Asia since the mid-1990s will probably sustain in the next few decades as GHG concentrations continue to increase and AA precursor emissions over both North America and Europe continue to decrease.
2016, 33(9): 1024-1035.
doi: 10.1007/s00376-016-5183-2
Abstract:
The sensitivity of the simulation of tropical cyclone (TC) size to microphysics schemes is studied using the Advanced Hurricane Weather Research and Forecasting Model (WRF). Six TCs during the 2013 western North Pacific typhoon season and three mainstream microphysics schemes-Ferrier (FER), WRF Single-Moment 5-class (WSM5) and WRF Single-Moment 6-class (WSM6)-are investigated. The results consistently show that the simulated TC track is not sensitive to the choice of microphysics scheme in the early simulation, especially in the open ocean. However, the sensitivity is much greater for TC intensity and inner-core size. The TC intensity and size simulated using the WSM5 and WSM6 schemes are respectively higher and larger than those using the FER scheme in general, which likely results from more diabatic heating being generated outside the eyewall in rainbands. More diabatic heating in rainbands gives higher inflow in the lower troposphere and higher outflow in the upper troposphere, with higher upward motion outside the eyewall. The lower-tropospheric inflow would transport absolute angular momentum inward to spin up tangential wind predominantly near the eyewall, leading to the increment in TC intensity and size (the inner-core size, especially). In addition, the inclusion of graupel microphysics processes (as in WSM6) may not have a significant impact on the simulation of TC track, intensity and size.
The sensitivity of the simulation of tropical cyclone (TC) size to microphysics schemes is studied using the Advanced Hurricane Weather Research and Forecasting Model (WRF). Six TCs during the 2013 western North Pacific typhoon season and three mainstream microphysics schemes-Ferrier (FER), WRF Single-Moment 5-class (WSM5) and WRF Single-Moment 6-class (WSM6)-are investigated. The results consistently show that the simulated TC track is not sensitive to the choice of microphysics scheme in the early simulation, especially in the open ocean. However, the sensitivity is much greater for TC intensity and inner-core size. The TC intensity and size simulated using the WSM5 and WSM6 schemes are respectively higher and larger than those using the FER scheme in general, which likely results from more diabatic heating being generated outside the eyewall in rainbands. More diabatic heating in rainbands gives higher inflow in the lower troposphere and higher outflow in the upper troposphere, with higher upward motion outside the eyewall. The lower-tropospheric inflow would transport absolute angular momentum inward to spin up tangential wind predominantly near the eyewall, leading to the increment in TC intensity and size (the inner-core size, especially). In addition, the inclusion of graupel microphysics processes (as in WSM6) may not have a significant impact on the simulation of TC track, intensity and size.
2016, 33(9): 1036-1046.
doi: 10.1007/s00376-016-6003-4
Abstract:
The breeding method has been widely used to generate ensemble perturbations in ensemble forecasting due to its simple concept and low computational cost. This method produces the fastest growing perturbation modes to catch the growing components in analysis errors. However, the bred vectors (BVs) are evolved on the same dynamical flow, which may increase the dependence of perturbations. In contrast, the nonlinear local Lyapunov vector (NLLV) scheme generates flow-dependent perturbations as in the breeding method, but regularly conducts the Gram-Schmidt reorthonormalization processes on the perturbations. The resulting NLLVs span the fast-growing perturbation subspace efficiently, and thus may grasp more components in analysis errors than the BVs. In this paper, the NLLVs are employed to generate initial ensemble perturbations in a barotropic quasi-geostrophic model. The performances of the ensemble forecasts of the NLLV method are systematically compared to those of the random perturbation (RP) technique, and the BV method, as well as its improved version——the ensemble transform Kalman filter (ETKF) method. The results demonstrate that the RP technique has the worst performance in ensemble forecasts, which indicates the importance of a flow-dependent initialization scheme. The ensemble perturbation subspaces of the NLLV and ETKF methods are preliminarily shown to catch similar components of analysis errors, which exceed that of the BVs. However, the NLLV scheme demonstrates slightly higher ensemble forecast skill than the ETKF scheme. In addition, the NLLV scheme involves a significantly simpler algorithm and less computation time than the ETKF method, and both demonstrate better ensemble forecast skill than the BV scheme.
The breeding method has been widely used to generate ensemble perturbations in ensemble forecasting due to its simple concept and low computational cost. This method produces the fastest growing perturbation modes to catch the growing components in analysis errors. However, the bred vectors (BVs) are evolved on the same dynamical flow, which may increase the dependence of perturbations. In contrast, the nonlinear local Lyapunov vector (NLLV) scheme generates flow-dependent perturbations as in the breeding method, but regularly conducts the Gram-Schmidt reorthonormalization processes on the perturbations. The resulting NLLVs span the fast-growing perturbation subspace efficiently, and thus may grasp more components in analysis errors than the BVs. In this paper, the NLLVs are employed to generate initial ensemble perturbations in a barotropic quasi-geostrophic model. The performances of the ensemble forecasts of the NLLV method are systematically compared to those of the random perturbation (RP) technique, and the BV method, as well as its improved version——the ensemble transform Kalman filter (ETKF) method. The results demonstrate that the RP technique has the worst performance in ensemble forecasts, which indicates the importance of a flow-dependent initialization scheme. The ensemble perturbation subspaces of the NLLV and ETKF methods are preliminarily shown to catch similar components of analysis errors, which exceed that of the BVs. However, the NLLV scheme demonstrates slightly higher ensemble forecast skill than the ETKF scheme. In addition, the NLLV scheme involves a significantly simpler algorithm and less computation time than the ETKF method, and both demonstrate better ensemble forecast skill than the BV scheme.
2016, 33(9): 1047-1060.
doi: 10.1007/s00376-016-5226-8
Abstract:
Roots are responsible for the uptake of water and nutrients by plants and have the plasticity to dynamically respond to different environmental conditions. However, most land surface models currently prescribe rooting profiles as a function only of vegetation type, with no consideration of the surroundings. In this study, a dynamic rooting scheme, which describes root growth as a compromise between water and nitrogen availability, was incorporated into CLM4.5 with carbon-nitrogen (CN) interactions (CLM4.5-CN) to investigate the effects of a dynamic root distribution on eco-hydrological modeling. Two paired numerical simulations were conducted for the Tapajos National Forest km83 (BRSa3) site and the Amazon, one using CLM4.5-CN without the dynamic rooting scheme and the other including the proposed scheme. Simulations for the BRSa3 site showed that inclusion of the dynamic rooting scheme increased the amplitudes and peak values of diurnal gross primary production (GPP) and latent heat flux (LE) for the dry season, and improved the carbon (C) and water cycle modeling by reducing the RMSE of GPP by 0.4 g C m-2 d-1, net ecosystem exchange by 1.96 g C m-2 d-1, LE by 5.0 W m-2, and soil moisture by 0.03 m3 m-3, at the seasonal scale, compared with eddy flux measurements, while having little impact during the wet season. For the Amazon, regional analysis also revealed that vegetation responses (including GPP and LE) to seasonal drought and the severe drought of 2005 were better captured with the dynamic rooting scheme incorporated.
Roots are responsible for the uptake of water and nutrients by plants and have the plasticity to dynamically respond to different environmental conditions. However, most land surface models currently prescribe rooting profiles as a function only of vegetation type, with no consideration of the surroundings. In this study, a dynamic rooting scheme, which describes root growth as a compromise between water and nitrogen availability, was incorporated into CLM4.5 with carbon-nitrogen (CN) interactions (CLM4.5-CN) to investigate the effects of a dynamic root distribution on eco-hydrological modeling. Two paired numerical simulations were conducted for the Tapajos National Forest km83 (BRSa3) site and the Amazon, one using CLM4.5-CN without the dynamic rooting scheme and the other including the proposed scheme. Simulations for the BRSa3 site showed that inclusion of the dynamic rooting scheme increased the amplitudes and peak values of diurnal gross primary production (GPP) and latent heat flux (LE) for the dry season, and improved the carbon (C) and water cycle modeling by reducing the RMSE of GPP by 0.4 g C m-2 d-1, net ecosystem exchange by 1.96 g C m-2 d-1, LE by 5.0 W m-2, and soil moisture by 0.03 m3 m-3, at the seasonal scale, compared with eddy flux measurements, while having little impact during the wet season. For the Amazon, regional analysis also revealed that vegetation responses (including GPP and LE) to seasonal drought and the severe drought of 2005 were better captured with the dynamic rooting scheme incorporated.
2016, 33(9): 1061-1070.
doi: 10.1007/s00376-016-5215-y
Abstract:
Using model results from the first phase of the Pliocene Model Intercomparison Project (PlioMIP) and four experiments with CAM4, the intensified African summer monsoon (ASM) in the mid-Piacenzian and corresponding mechanisms are analyzed. The results from PlioMIP show that the ASM intensified and summer precipitation increased in North Africa during the mid-Piacenzian, which can be explained by the increased net energy in the atmospheric column above North Africa. Further experiments with CAM4 indicated that the combined changes in the mid-Piacenzian of atmospheric CO2 concentration and SST, as well as the vegetation change, could have substantially increased the net energy in the atmospheric column over North Africa and further intensified the ASM. The experiments also demonstrated that topography change had a weak effect. Overall, the combined changes of atmospheric CO2 concentration and SST were the most important factor that brought about the intensified ASM in the mid-Piacenzian.
Using model results from the first phase of the Pliocene Model Intercomparison Project (PlioMIP) and four experiments with CAM4, the intensified African summer monsoon (ASM) in the mid-Piacenzian and corresponding mechanisms are analyzed. The results from PlioMIP show that the ASM intensified and summer precipitation increased in North Africa during the mid-Piacenzian, which can be explained by the increased net energy in the atmospheric column above North Africa. Further experiments with CAM4 indicated that the combined changes in the mid-Piacenzian of atmospheric CO2 concentration and SST, as well as the vegetation change, could have substantially increased the net energy in the atmospheric column over North Africa and further intensified the ASM. The experiments also demonstrated that topography change had a weak effect. Overall, the combined changes of atmospheric CO2 concentration and SST were the most important factor that brought about the intensified ASM in the mid-Piacenzian.
2016, 33(9): 1071-7084.
doi: 10.1007/s00376-016-5251-7
Abstract:
A timescale decomposed threshold regression (TSDTR) downscaling approach to forecasting South China early summer rainfall (SCESR) is described by using long-term observed station rainfall data and NOAA ERSST data. It makes use of two distinct regression downscaling models corresponding to the interannual and interdecadal rainfall variability of SCESR. The two models are developed based on the partial least squares (PLS) regression technique, linking SCESR to SST modes in preceding months on both interannual and interdecadal timescales. Specifically, using the datasets in the calibration period 1915-84, the variability of SCESR and SST are decomposed into interannual and interdecadal components. On the interannual timescale, a threshold PLS regression model is fitted to interannual components of SCESR and March SST patterns by taking account of the modulation of negative and positive phases of the Pacific Decadal Oscillation (PDO). On the interdecadal timescale, a standard PLS regression model is fitted to the relationship between SCESR and preceding November SST patterns. The total rainfall prediction is obtained by the sum of the outputs from both the interannual and interdecadal models. Results show that the TSDTR downscaling approach achieves reasonable skill in predicting the observed rainfall in the validation period 1985-2006, compared to other simpler approaches. This study suggests that the TSDTR approach, considering different interannual SCESR-SST relationships under the modulation of PDO phases, as well as the interdecadal variability of SCESR associated with SST patterns, may provide a new perspective to improve climate predictions.
A timescale decomposed threshold regression (TSDTR) downscaling approach to forecasting South China early summer rainfall (SCESR) is described by using long-term observed station rainfall data and NOAA ERSST data. It makes use of two distinct regression downscaling models corresponding to the interannual and interdecadal rainfall variability of SCESR. The two models are developed based on the partial least squares (PLS) regression technique, linking SCESR to SST modes in preceding months on both interannual and interdecadal timescales. Specifically, using the datasets in the calibration period 1915-84, the variability of SCESR and SST are decomposed into interannual and interdecadal components. On the interannual timescale, a threshold PLS regression model is fitted to interannual components of SCESR and March SST patterns by taking account of the modulation of negative and positive phases of the Pacific Decadal Oscillation (PDO). On the interdecadal timescale, a standard PLS regression model is fitted to the relationship between SCESR and preceding November SST patterns. The total rainfall prediction is obtained by the sum of the outputs from both the interannual and interdecadal models. Results show that the TSDTR downscaling approach achieves reasonable skill in predicting the observed rainfall in the validation period 1985-2006, compared to other simpler approaches. This study suggests that the TSDTR approach, considering different interannual SCESR-SST relationships under the modulation of PDO phases, as well as the interdecadal variability of SCESR associated with SST patterns, may provide a new perspective to improve climate predictions.
2016, 33(9): 1085-1095.
doi: 10.1007/s00376-016-5229-5
Abstract:
Based on idealized numerical simulations, the impacts of the diurnal cycle of solar radiation on the diurnal variation of outer rainbands in a tropical cyclone are examined. It is found that cold pools associated with precipitation-driven downdrafts are essential for the growth and propagation of spiral rainbands. The downdrafts result in surface outflows, which act as a lifting mechanism to trigger the convection cell along the leading edge of the cold pools. The diurnal cycle of solar radiation may modulate the diurnal behavior of the spiral rainbands. In the daytime, shortwave radiation will suppress the outer convection and thus weaken the cold pools. Meanwhile, the limited cold pool activity leads to a strong modification of the moisture field, which in turn inhibits further convection development.
Based on idealized numerical simulations, the impacts of the diurnal cycle of solar radiation on the diurnal variation of outer rainbands in a tropical cyclone are examined. It is found that cold pools associated with precipitation-driven downdrafts are essential for the growth and propagation of spiral rainbands. The downdrafts result in surface outflows, which act as a lifting mechanism to trigger the convection cell along the leading edge of the cold pools. The diurnal cycle of solar radiation may modulate the diurnal behavior of the spiral rainbands. In the daytime, shortwave radiation will suppress the outer convection and thus weaken the cold pools. Meanwhile, the limited cold pool activity leads to a strong modification of the moisture field, which in turn inhibits further convection development.
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