2017 Vol. 34, No. 11
Display Method:
2017, 34(11): 1265-1281.
doi: 10.1007/s00376-017-6299-8
Abstract:
A new set of Infrared Atmospheric Sounding Interferometer (IASI) channels was re-selected from 314 EUMETSAT channels. In selecting channels, we calculated the impact of the individually added channel on the improvement in the analysis outputs from a one-dimensional variational analysis (1D-Var) for the Unified Model (UM) data assimilation system at the Met Office, using the channel score index (CSI) as a figure of merit. Then, 200 channels were selected in order by counting each individual channel's CSI contribution. Compared with the operationally used 183 channels for the UM at the Met Office, the new set shares 149 channels, while the other 51 channels are new. Also examined is the selection from the entropy reduction method with the same 1D-Var approach. Results suggest that channel selection can be made in a more objective fashion using the proposed CSI method. This is because the most important channels can be selected across the whole IASI observation spectrum. In the experimental trial runs using the UM global assimilation system, the new channels had an overall neutral impact in terms of improvement in forecasts, as compared with results from the operational channels. However, upper-tropospheric moist biases shown in the control run with operational channels were significantly reduced in the experimental trial with the newly selected channels. The reduction of moist biases was mainly due to the additional water vapor channels, which are sensitive to the upper-tropospheric water vapor.
A new set of Infrared Atmospheric Sounding Interferometer (IASI) channels was re-selected from 314 EUMETSAT channels. In selecting channels, we calculated the impact of the individually added channel on the improvement in the analysis outputs from a one-dimensional variational analysis (1D-Var) for the Unified Model (UM) data assimilation system at the Met Office, using the channel score index (CSI) as a figure of merit. Then, 200 channels were selected in order by counting each individual channel's CSI contribution. Compared with the operationally used 183 channels for the UM at the Met Office, the new set shares 149 channels, while the other 51 channels are new. Also examined is the selection from the entropy reduction method with the same 1D-Var approach. Results suggest that channel selection can be made in a more objective fashion using the proposed CSI method. This is because the most important channels can be selected across the whole IASI observation spectrum. In the experimental trial runs using the UM global assimilation system, the new channels had an overall neutral impact in terms of improvement in forecasts, as compared with results from the operational channels. However, upper-tropospheric moist biases shown in the control run with operational channels were significantly reduced in the experimental trial with the newly selected channels. The reduction of moist biases was mainly due to the additional water vapor channels, which are sensitive to the upper-tropospheric water vapor.
2017, 34(11): 1282-1289.
doi: 10.1007/s00376-017-7009-2
Abstract:
A robust decadal Indian Ocean dipolar variability (DIOD) is identified in observations and found to be related to tropical Pacific decadal variability (TPDV). A Pacific Ocean-global atmosphere (POGA) experiment, with fixed radiative forcing, is conducted to evaluate the DIOD variability and its relationship with the TPDV. In this experiment, the sea surface temperature anomalies are restored to observations over the tropical Pacific, but left as interactive with the atmosphere elsewhere. The TPDV-forced DIOD, represented as the ensemble mean of 10 simulations in POGA, accounts for one third of the total variance. The forced DIOD is triggered by anomalous Walker circulation in response to the TPDV and develops following Bjerknes feedback. Thermocline anomalies do not exhibit a propagating signal, indicating an absence of oceanic planetary wave adjustment in the subtropical Indian Ocean. The DIOD-TPDV correlation differs among the 10 simulations, with a low correlation corresponding to a strong internal DIOD independent of the TPDV. The variance of this internal DIOD depends on the background state in the Indian Ocean, modulated by the thermocline depth off Sumatra/Java.
A robust decadal Indian Ocean dipolar variability (DIOD) is identified in observations and found to be related to tropical Pacific decadal variability (TPDV). A Pacific Ocean-global atmosphere (POGA) experiment, with fixed radiative forcing, is conducted to evaluate the DIOD variability and its relationship with the TPDV. In this experiment, the sea surface temperature anomalies are restored to observations over the tropical Pacific, but left as interactive with the atmosphere elsewhere. The TPDV-forced DIOD, represented as the ensemble mean of 10 simulations in POGA, accounts for one third of the total variance. The forced DIOD is triggered by anomalous Walker circulation in response to the TPDV and develops following Bjerknes feedback. Thermocline anomalies do not exhibit a propagating signal, indicating an absence of oceanic planetary wave adjustment in the subtropical Indian Ocean. The DIOD-TPDV correlation differs among the 10 simulations, with a low correlation corresponding to a strong internal DIOD independent of the TPDV. The variance of this internal DIOD depends on the background state in the Indian Ocean, modulated by the thermocline depth off Sumatra/Java.
2017, 34(11): 1290-1300.
doi: 10.1007/s00376-017-7003-8
Abstract:
It is widely recognized that rainfall over the Yangtze River valley (YRV) strengthens considerably during the decaying summer of El Niño, as demonstrated by the catastrophic flooding suffered in the summer of 1998. Nevertheless, the rainfall over the YRV in the summer of 2016 was much weaker than that in 1998, despite the intensity of the 2016 El Niño having been as strong as that in 1998. A thorough comparison of the YRV summer rainfall anomaly between 2016 and 1998 suggests that the difference was caused by the sub-seasonal variation in the YRV rainfall anomaly between these two years, principally in August. The precipitation anomaly was negative in August 2016——different to the positive anomaly of 1998. Further analysis suggests that the weaker YRV rainfall in August 2016 could be attributable to the distinct circulation anomalies over the midlatitudes. The intensified "Silk Road Pattern" and upper-tropospheric geopotential height over the Urals region, both at their strongest since 1980, resulted in an anticyclonic circulation anomaly over midlatitude East Asia with anomalous easterly flow over the middle-to-lower reaches of the YRV in the lower troposphere. This easterly flow reduced the climatological wind, weakened the water vapor transport, and induced the weaker YRV rainfall in August 2016, as compared to that in 1998. Given the unique sub-seasonal variation of the YRV rainfall in summer 2016, more attention should be paid to midlatitude circulation——besides the signal in the tropics——to further our understanding of the predictability and variation of YRV summer rainfall.
It is widely recognized that rainfall over the Yangtze River valley (YRV) strengthens considerably during the decaying summer of El Niño, as demonstrated by the catastrophic flooding suffered in the summer of 1998. Nevertheless, the rainfall over the YRV in the summer of 2016 was much weaker than that in 1998, despite the intensity of the 2016 El Niño having been as strong as that in 1998. A thorough comparison of the YRV summer rainfall anomaly between 2016 and 1998 suggests that the difference was caused by the sub-seasonal variation in the YRV rainfall anomaly between these two years, principally in August. The precipitation anomaly was negative in August 2016——different to the positive anomaly of 1998. Further analysis suggests that the weaker YRV rainfall in August 2016 could be attributable to the distinct circulation anomalies over the midlatitudes. The intensified "Silk Road Pattern" and upper-tropospheric geopotential height over the Urals region, both at their strongest since 1980, resulted in an anticyclonic circulation anomaly over midlatitude East Asia with anomalous easterly flow over the middle-to-lower reaches of the YRV in the lower troposphere. This easterly flow reduced the climatological wind, weakened the water vapor transport, and induced the weaker YRV rainfall in August 2016, as compared to that in 1998. Given the unique sub-seasonal variation of the YRV rainfall in summer 2016, more attention should be paid to midlatitude circulation——besides the signal in the tropics——to further our understanding of the predictability and variation of YRV summer rainfall.
2017, 34(11): 1301-1315.
doi: 10.1007/s00376-016-6262-0
Abstract:
SUNFLUX is a fast parameterization scheme for determination of the solar radiation at the Earth's surface. In this paper, SUNFLUX is further modified in the treatment of aerosols. A new aerosol parameterization scheme is developed for five aerosol species. Observational data from Baseline Surface Radiation Network (BSRN), Surface Radiation Budget Network (SURFRAD) and Aerosol Robotic Network (AERONET) stations are used to evaluate the accuracy of the original and modified SUNFLUX schemes. General meteorological data are available at SURFRAD stations, but not at BSRN stations. Therefore, the total precipitable water content and aerosol data are obtained from AERONET stations. Fourteen stations are selected from both BSRN and AERONET. Cloud fraction data from MODIS are further used to screen the cloud. Ten-year average aerosol mixing ratios simulated by the CAM-chem system are used to calculate the fractions of aerosol optical depth for each aerosol species, and these fractions are further used to convert the observed total aerosol optical depth into the components of individual species for use in the evaluations. The proper treatment of multiple aerosol types in the model is discussed. The evaluation results using SUNFLUX with the new aerosol scheme, in terms of the BSRN dataset, are better than those using the original aerosol scheme under clear-sky conditions. However, the results using the SURFRAD dataset are slightly worse, attributable to the differences in the input water vapor and aerosol optical depth. Sensitivity tests are conducted to investigate the error response of the SUNFLUX scheme to the errors in the input variables.
SUNFLUX is a fast parameterization scheme for determination of the solar radiation at the Earth's surface. In this paper, SUNFLUX is further modified in the treatment of aerosols. A new aerosol parameterization scheme is developed for five aerosol species. Observational data from Baseline Surface Radiation Network (BSRN), Surface Radiation Budget Network (SURFRAD) and Aerosol Robotic Network (AERONET) stations are used to evaluate the accuracy of the original and modified SUNFLUX schemes. General meteorological data are available at SURFRAD stations, but not at BSRN stations. Therefore, the total precipitable water content and aerosol data are obtained from AERONET stations. Fourteen stations are selected from both BSRN and AERONET. Cloud fraction data from MODIS are further used to screen the cloud. Ten-year average aerosol mixing ratios simulated by the CAM-chem system are used to calculate the fractions of aerosol optical depth for each aerosol species, and these fractions are further used to convert the observed total aerosol optical depth into the components of individual species for use in the evaluations. The proper treatment of multiple aerosol types in the model is discussed. The evaluation results using SUNFLUX with the new aerosol scheme, in terms of the BSRN dataset, are better than those using the original aerosol scheme under clear-sky conditions. However, the results using the SURFRAD dataset are slightly worse, attributable to the differences in the input water vapor and aerosol optical depth. Sensitivity tests are conducted to investigate the error response of the SUNFLUX scheme to the errors in the input variables.
2017, 34(11): 1316-1332.
doi: 10.1007/s00376-017-6318-9
Abstract:
Since the interaction between atmospheric synoptic eddy (SE) (2-8 days) activity and low-frequency (LF) (monthly) flow (referred to as SELF) plays an essential role in generating and maintaining dominant climate modes, an evaluation of the performance of BCC_CSM1.1(m) in simulating the SE feedback onto the LF flow is given in this paper. The model captures well the major spatial features of climatological eddy vorticity forcing, eddy-induced growth rate, and patterns of SELF feedback for the climate modes with large magnitudes in cold seasons and small magnitudes in warm seasons for both the Northern and Southern Hemisphere. As in observations, the eddy-induced growth rate and SELF feedback patterns in the model also show positive SE feedback. Overall, the relationships between SE and LF flow show that BCC_CSM1.1(m) satisfactorily captures the basic features of positive SE feedback, which demonstrates the simulation skill of the model for LF variability. Specifically, such an evaluation can help to find model biases of BCC_CSM1.1(m) in simulating SE feedback, which will provide a reference for the model's application.
Since the interaction between atmospheric synoptic eddy (SE) (2-8 days) activity and low-frequency (LF) (monthly) flow (referred to as SELF) plays an essential role in generating and maintaining dominant climate modes, an evaluation of the performance of BCC_CSM1.1(m) in simulating the SE feedback onto the LF flow is given in this paper. The model captures well the major spatial features of climatological eddy vorticity forcing, eddy-induced growth rate, and patterns of SELF feedback for the climate modes with large magnitudes in cold seasons and small magnitudes in warm seasons for both the Northern and Southern Hemisphere. As in observations, the eddy-induced growth rate and SELF feedback patterns in the model also show positive SE feedback. Overall, the relationships between SE and LF flow show that BCC_CSM1.1(m) satisfactorily captures the basic features of positive SE feedback, which demonstrates the simulation skill of the model for LF variability. Specifically, such an evaluation can help to find model biases of BCC_CSM1.1(m) in simulating SE feedback, which will provide a reference for the model's application.
2017, 34(11): 1333-1345.
doi: 10.1007/s00376-017-7019-0
Abstract:
The presence of light-absorbing aerosols (LAA) in snow profoundly influence the surface energy balance and water budget. However, most snow-process schemes in land-surface and climate models currently do not take this into consideration. To better represent the snow process and to evaluate the impacts of LAA on snow, this study presents an improved snow albedo parameterization in the Snow-Atmosphere-Soil Transfer (SAST) model, which includes the impacts of LAA on snow. Specifically, the Snow, Ice and Aerosol Radiation (SNICAR) model is incorporated into the SAST model with an LAA mass stratigraphy scheme. The new coupled model is validated against in-situ measurements at the Swamp Angel Study Plot (SASP), Colorado, USA. Results show that the snow albedo and snow depth are better reproduced than those in the original SAST, particularly during the period of snow ablation. Furthermore, the impacts of LAA on snow are estimated in the coupled model through case comparisons of the snowpack, with or without LAA. The LAA particles directly absorb extra solar radiation, which accelerates the growth rate of the snow grain size. Meanwhile, these larger snow particles favor more radiative absorption. The average total radiative forcing of the LAA at the SASP is 47.5 W m-2. This extra radiative absorption enhances the snowmelt rate. As a result, the peak runoff time and "snow all gone" day have shifted 18 and 19.5 days earlier, respectively, which could further impose substantial impacts on the hydrologic cycle and atmospheric processes.
The presence of light-absorbing aerosols (LAA) in snow profoundly influence the surface energy balance and water budget. However, most snow-process schemes in land-surface and climate models currently do not take this into consideration. To better represent the snow process and to evaluate the impacts of LAA on snow, this study presents an improved snow albedo parameterization in the Snow-Atmosphere-Soil Transfer (SAST) model, which includes the impacts of LAA on snow. Specifically, the Snow, Ice and Aerosol Radiation (SNICAR) model is incorporated into the SAST model with an LAA mass stratigraphy scheme. The new coupled model is validated against in-situ measurements at the Swamp Angel Study Plot (SASP), Colorado, USA. Results show that the snow albedo and snow depth are better reproduced than those in the original SAST, particularly during the period of snow ablation. Furthermore, the impacts of LAA on snow are estimated in the coupled model through case comparisons of the snowpack, with or without LAA. The LAA particles directly absorb extra solar radiation, which accelerates the growth rate of the snow grain size. Meanwhile, these larger snow particles favor more radiative absorption. The average total radiative forcing of the LAA at the SASP is 47.5 W m-2. This extra radiative absorption enhances the snowmelt rate. As a result, the peak runoff time and "snow all gone" day have shifted 18 and 19.5 days earlier, respectively, which could further impose substantial impacts on the hydrologic cycle and atmospheric processes.
2017, 34(11): 1346-1357.
doi: 10.1007/s00376-017-6272-6
Abstract:
That a model has sensitivity responses to parameter uncertainties is a key concept in implementing model parameter estimation using filtering theory and methodology. Depending on the nature of associated physics and characteristic variability of the fluid in a coupled system, the response time scales of a model to parameters can be different, from hourly to decadal. Unlike state estimation, where the update frequency is usually linked with observational frequency, the update frequency for parameter estimation must be associated with the time scale of the model sensitivity response to the parameter being estimated. Here, with a simple coupled model, the impact of model sensitivity response time scales on coupled model parameter estimation is studied. The model includes characteristic synoptic to decadal scales by coupling a long-term varying deep ocean with a slow-varying upper ocean forced by a chaotic atmosphere. Results show that, using the update frequency determined by the model sensitivity response time scale, both the reliability and quality of parameter estimation can be improved significantly, and thus the estimated parameters make the model more consistent with the observation. These simple model results provide a guideline for when real observations are used to optimize the parameters in a coupled general circulation model for improving climate analysis and prediction initialization.
That a model has sensitivity responses to parameter uncertainties is a key concept in implementing model parameter estimation using filtering theory and methodology. Depending on the nature of associated physics and characteristic variability of the fluid in a coupled system, the response time scales of a model to parameters can be different, from hourly to decadal. Unlike state estimation, where the update frequency is usually linked with observational frequency, the update frequency for parameter estimation must be associated with the time scale of the model sensitivity response to the parameter being estimated. Here, with a simple coupled model, the impact of model sensitivity response time scales on coupled model parameter estimation is studied. The model includes characteristic synoptic to decadal scales by coupling a long-term varying deep ocean with a slow-varying upper ocean forced by a chaotic atmosphere. Results show that, using the update frequency determined by the model sensitivity response time scale, both the reliability and quality of parameter estimation can be improved significantly, and thus the estimated parameters make the model more consistent with the observation. These simple model results provide a guideline for when real observations are used to optimize the parameters in a coupled general circulation model for improving climate analysis and prediction initialization.
2017, 34(11): 1358-1379.
doi: 10.1007/s00376-017-6339-4
Abstract:
There is increasing evidence of the possible role of extratropical forcing in the evolution of ENSO. The Southern Hemisphere Annular Mode (SAM) is the dominant mode of atmospheric circulation in the Southern Hemisphere extratropics. This study shows that the austral summer (December-January-February; DJF) SAM may also influence the amplitude of ENSO decay during austral autumn (March-April-May; MAM). The mechanisms associated with this SAM-ENSO relationship can be briefly summarized as follows: The SAM is positively (negatively) correlated with SST in the Southern Hemisphere middle (high) latitudes. This dipole-like SST anomaly pattern is referred to as the Southern Ocean Dipole (SOD). The DJF SOD, caused by the DJF SAM, could persist until MAM and then influence atmospheric circulation, including trade winds, over the Niño3.4 area. Anomalous trade winds and SST anomalies over the Niño3.4 area related to the DJF SAM are further developed through the Bjerkness feedback, which eventually results in a cooling (warming) over the Niño3.4 area followed by the positive (negative) DJF SAM.
There is increasing evidence of the possible role of extratropical forcing in the evolution of ENSO. The Southern Hemisphere Annular Mode (SAM) is the dominant mode of atmospheric circulation in the Southern Hemisphere extratropics. This study shows that the austral summer (December-January-February; DJF) SAM may also influence the amplitude of ENSO decay during austral autumn (March-April-May; MAM). The mechanisms associated with this SAM-ENSO relationship can be briefly summarized as follows: The SAM is positively (negatively) correlated with SST in the Southern Hemisphere middle (high) latitudes. This dipole-like SST anomaly pattern is referred to as the Southern Ocean Dipole (SOD). The DJF SOD, caused by the DJF SAM, could persist until MAM and then influence atmospheric circulation, including trade winds, over the Niño3.4 area. Anomalous trade winds and SST anomalies over the Niño3.4 area related to the DJF SAM are further developed through the Bjerkness feedback, which eventually results in a cooling (warming) over the Niño3.4 area followed by the positive (negative) DJF SAM.
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