2015 Vol. 21, No. 4
2015, 21(4): 311-325.
doi: 10.16555/j.1006-8775.2015.04.001
Abstract:
With the Weather Research and Forecasting model (WRFV3.2.1), the application of spectrum nudging techniques in numerical simulation of the genesis and development of typhoon Longwang (2005) is evaluated in this work via four numerical experiments with different nudging techniques. It is found that, due to the ability to capture the large-scale fields and to keep the meso-to small-scale features derived from the model dynamics, the experiment with spectrum nudging technique can simulate the formation, intensification and motion of Longwang properly. The improvement on the numerical simulation of Longwang induced by the spectrum nudging depends on the nudging coefficients. A weak spectrum nudging does not make significant improvement on the simulation of Longwang. Although the experiment with four-dimensional data assimilation, i.e., FDDA, also derives the genesis and movement of Longwang appropriately, it fails to simulate the intensifying process of Longwang properly. The reason is that, as the large-scale features derived from the model are nudged to the observational data, the meso- to small-processes produced by the model dynamics important to the intensification of typhoon are nearly smoothed by FDDA.
With the Weather Research and Forecasting model (WRFV3.2.1), the application of spectrum nudging techniques in numerical simulation of the genesis and development of typhoon Longwang (2005) is evaluated in this work via four numerical experiments with different nudging techniques. It is found that, due to the ability to capture the large-scale fields and to keep the meso-to small-scale features derived from the model dynamics, the experiment with spectrum nudging technique can simulate the formation, intensification and motion of Longwang properly. The improvement on the numerical simulation of Longwang induced by the spectrum nudging depends on the nudging coefficients. A weak spectrum nudging does not make significant improvement on the simulation of Longwang. Although the experiment with four-dimensional data assimilation, i.e., FDDA, also derives the genesis and movement of Longwang appropriately, it fails to simulate the intensifying process of Longwang properly. The reason is that, as the large-scale features derived from the model are nudged to the observational data, the meso- to small-processes produced by the model dynamics important to the intensification of typhoon are nearly smoothed by FDDA.
2015, 21(4): 326-336.
doi: 10.16555/j.1006-8775.2015.04.002
Abstract:
The impact of tropical intraseasonal oscillations on the precipitation of Guangdong in Junes and its physical mechanism are analyzed using 30-yr (1979 to 2008), 86-station observational daily precipitation of Guangdong and daily atmospheric data from NCEP-DOE Reanalysis. It is found that during the annually first rainy season (April to June), the modulating effect of the activity of intraseasonal oscillations propagating eastward along the equator (MJO) on the June precipitation in Guangdong is different from that in other months. The most indicative effect of MJO on positive (negative) anomalous precipitation over the whole or most of the province is phase 3 (phase 6) of strong MJO events in Junes. A Northwest Pacific subtropical high intensifies and extends westward during phase 3. Water vapor transporting along the edge of the subtropical high from Western Pacific enhances significantly the water vapor flux over Guangdong, resulting in the enhancement of the precipitation. The condition is reverse during phase 6. The mechanism for which the subtropical high intensifies and extends westward during phase 3 is related to the atmospheric response to the asymmetric heating over the eastern Indian Ocean. Analyses of two cases of sustained strong rainfall of Guangdong in June 2010 showed that both of them are closely linked with a MJO state which is both strong and in phase 3, besides the effect from a westerly trough. It is argued further that the MJO activity is indicative of strong rainfall of Guangdong in June. The results in the present work are helpful in developing strategies for forecasting severe rainfall in Guangdong and extending, combined with the outputs of dynamic forecast models, the period of forecasting validity.
The impact of tropical intraseasonal oscillations on the precipitation of Guangdong in Junes and its physical mechanism are analyzed using 30-yr (1979 to 2008), 86-station observational daily precipitation of Guangdong and daily atmospheric data from NCEP-DOE Reanalysis. It is found that during the annually first rainy season (April to June), the modulating effect of the activity of intraseasonal oscillations propagating eastward along the equator (MJO) on the June precipitation in Guangdong is different from that in other months. The most indicative effect of MJO on positive (negative) anomalous precipitation over the whole or most of the province is phase 3 (phase 6) of strong MJO events in Junes. A Northwest Pacific subtropical high intensifies and extends westward during phase 3. Water vapor transporting along the edge of the subtropical high from Western Pacific enhances significantly the water vapor flux over Guangdong, resulting in the enhancement of the precipitation. The condition is reverse during phase 6. The mechanism for which the subtropical high intensifies and extends westward during phase 3 is related to the atmospheric response to the asymmetric heating over the eastern Indian Ocean. Analyses of two cases of sustained strong rainfall of Guangdong in June 2010 showed that both of them are closely linked with a MJO state which is both strong and in phase 3, besides the effect from a westerly trough. It is argued further that the MJO activity is indicative of strong rainfall of Guangdong in June. The results in the present work are helpful in developing strategies for forecasting severe rainfall in Guangdong and extending, combined with the outputs of dynamic forecast models, the period of forecasting validity.
2015, 21(4): 337-351.
doi: 10.16555/j.1006-8775.2015.04.003
Abstract:
By using barotropic model equations, this article analyzed the characteristics of Rossby waves, the propagation features of wave energy and the influence of dynamic and thermal effects of the Tibetan Plateau on Rossby waves, and the focus is on discussing the plateau's topographic gradient effects on atmospheric Rossby waves. Then based on the WRF3.2 and the NCEP/NCAR FNL reanalysis data, we devised comparative tests of changing the plateau's topographic gradient and simulated a process of persistent heavy rain that happened in May 2010 in South China. The results are shown as follows. The Tibetan Plateau’s topography is conducive to the formation of atmospheric Rossby waves. while the plateau's terrain, its friction and heating effects can all make the atmospheric Rossby waves develop into the planetary waves; The effects of plateau's north and south slopes on the Rossby wave’ phase velocity is opposite, and when the slope reached a certain value can the quasi-steady normal fluctuations be generated; Simultaneously, due to the plateau's topographic gradient, descending motion appears at the west side of the plateau while ascending motion appears at the east side, and the vertical movement increased with the amplification of topographic gradients. The plateau's topographic gradient also obviously amplified the precipitation in South China, and the rainfall area increased with the amplification of topographic gradients and gradually moved from south to north and from west to east, which is conducive to the occurrence and development of convective activities in the downstream areas of the Tibetan Plateau; Moreover, for the plateau’s dynamic and thermal effects, the Rossby wave’ propagation shows upstream effects of energy dispersion, so the plateau can then affect the weather in downstream areas. Moreover, the wave group velocity increased with the degree of topographic slope.
By using barotropic model equations, this article analyzed the characteristics of Rossby waves, the propagation features of wave energy and the influence of dynamic and thermal effects of the Tibetan Plateau on Rossby waves, and the focus is on discussing the plateau's topographic gradient effects on atmospheric Rossby waves. Then based on the WRF3.2 and the NCEP/NCAR FNL reanalysis data, we devised comparative tests of changing the plateau's topographic gradient and simulated a process of persistent heavy rain that happened in May 2010 in South China. The results are shown as follows. The Tibetan Plateau’s topography is conducive to the formation of atmospheric Rossby waves. while the plateau's terrain, its friction and heating effects can all make the atmospheric Rossby waves develop into the planetary waves; The effects of plateau's north and south slopes on the Rossby wave’ phase velocity is opposite, and when the slope reached a certain value can the quasi-steady normal fluctuations be generated; Simultaneously, due to the plateau's topographic gradient, descending motion appears at the west side of the plateau while ascending motion appears at the east side, and the vertical movement increased with the amplification of topographic gradients. The plateau's topographic gradient also obviously amplified the precipitation in South China, and the rainfall area increased with the amplification of topographic gradients and gradually moved from south to north and from west to east, which is conducive to the occurrence and development of convective activities in the downstream areas of the Tibetan Plateau; Moreover, for the plateau’s dynamic and thermal effects, the Rossby wave’ propagation shows upstream effects of energy dispersion, so the plateau can then affect the weather in downstream areas. Moreover, the wave group velocity increased with the degree of topographic slope.
2015, 21(4): 352-360.
doi: 10.16555/j.1006-8775.2015.04.004
Abstract:
NCEP/NCAR reanalysis data and a 30-year precipitation dataset of observed daily rainfall from 109 gauge stations are utilized in this paper. Using the REOF we analyzed the spatial distribution of precipitation in the 109 stations in the Yangtze River Basin in Meiyu periods from 1978 to 2007. The result showed that the spatial distribution of precipitation in the Yangtze River Basin can be divided into the south and north part. As a result, relationships between an atmospheric heating source (hereafter called ) over the Asian region and the precipitation on the south and north side of Yangtze River in Meiyu periods were separately studied in this paper. The results are shown as follows. The flood/drought to the north of Yangtze River (NYR) was mainly related to the over the East Asia summer monsoon region: when the over the Philippines through Western Pacific and the south China was weakened (strengthened), it would probably result in the flood (drought) in NYR; and the precipitation on the south side of Yangtze River (SYR) was related to the over the east Asia and Indian summer monsoon region: when the over the areas from south China to the northern East China Sea and Yellow Sea and south-eastern Japan was strengthened (weakened), and the over the areas from the Bay of Bengal to south-eastern Tibetan Plateau was weakened (strengthened), it will lead to flood (drought) in SYR.
NCEP/NCAR reanalysis data and a 30-year precipitation dataset of observed daily rainfall from 109 gauge stations are utilized in this paper. Using the REOF we analyzed the spatial distribution of precipitation in the 109 stations in the Yangtze River Basin in Meiyu periods from 1978 to 2007. The result showed that the spatial distribution of precipitation in the Yangtze River Basin can be divided into the south and north part. As a result, relationships between an atmospheric heating source (hereafter called ) over the Asian region and the precipitation on the south and north side of Yangtze River in Meiyu periods were separately studied in this paper. The results are shown as follows. The flood/drought to the north of Yangtze River (NYR) was mainly related to the over the East Asia summer monsoon region: when the over the Philippines through Western Pacific and the south China was weakened (strengthened), it would probably result in the flood (drought) in NYR; and the precipitation on the south side of Yangtze River (SYR) was related to the over the east Asia and Indian summer monsoon region: when the over the areas from south China to the northern East China Sea and Yellow Sea and south-eastern Japan was strengthened (weakened), and the over the areas from the Bay of Bengal to south-eastern Tibetan Plateau was weakened (strengthened), it will lead to flood (drought) in SYR.
2015, 21(4): 361-373.
doi: 10.16555/j.1006-8775.2015.04.005
Abstract:
Using the 1979-2009 NCEP/NACR reanalysis data and precipitation records in East China, research is performed of the climatological features of low-frequency oscillation (LFO) in OLR over the Maritime Continent (MC) as well as their associations with precipitation disturbance in the eastern part of China. Results suggest that in the MC there is significant climatological low-frequency oscillation (CLFO) in outgoing long-wave radiation (OLR), with the intraseasonal oscillation (30-60 days) being the strongest for April-September, and the MC acting as a high-value region of percentage contributions of low-frequency OLR variance. On the low-frequency time scale there occur four events of more intense active OLR during this time interval. In the January-April (May-August) phase, MC convection is relatively weak (vigorous). The CLFO makes pronounced eastward displacement at tropics, with phase propagation seen longitudinally, too. There occur low-frequency disturbance circulations similar to the EAP wavetrain or P-J teleconnection, starting from the MC via the South China Sea and the Philippines to the Yangtze valley of China. At different phases, the variation in the low-frequency circulations and heating fields shows that the rainfall disturbance in eastern China is likely to be under possible effects of the CLFO from the MC in April-September, and the low-frequency heating variation exhibits a meridional pattern as an EAP wavetrain or P-J teleconnection. As the OLR CLFO is in a peak (valley) phase the low-level divergence or convergence with the reversal at high levels over the MC is related to relatively feeble (robust) low frequency convection, thereby exciting an EAP or P-J wavetrain from the MC to the Sea of Japan. At the higher levels, the South-Asian high is eastward (westward) of normal due to effects of low-frequency cyclones (anticyclones), resulting in less (more) rainfall in the Jiangnan (areas in the middle and lower reaches of Yangtze and to the south of the river) and Hetao (the Great Bend of Yellow River) areas, and increased (decreased) rainfall in SW China, Qinghai Plateau and Gansu. At the conversion phases, low-frequency convection becomes more active in parts of the MC, consequently exciting low-frequency wavetrain of cyclones-anticyclones-cyclones at low levels, making the South-Asian high southward of the mean, so that strong convergent zones emerge in the upper and middle Yangtze basins and Jilin of NE China, responsible for plentiful precipitation there in sharp contrast to the rainfall over the band between the Yellow and Huaihe Rivers and the Yunnan-Guizhou Plateau. These results help understand in depth the climatological LFO characteristics and the phase-locked feature, thereby further improving our understanding of the causes of rainfall disturbances in different parts of the country.
Using the 1979-2009 NCEP/NACR reanalysis data and precipitation records in East China, research is performed of the climatological features of low-frequency oscillation (LFO) in OLR over the Maritime Continent (MC) as well as their associations with precipitation disturbance in the eastern part of China. Results suggest that in the MC there is significant climatological low-frequency oscillation (CLFO) in outgoing long-wave radiation (OLR), with the intraseasonal oscillation (30-60 days) being the strongest for April-September, and the MC acting as a high-value region of percentage contributions of low-frequency OLR variance. On the low-frequency time scale there occur four events of more intense active OLR during this time interval. In the January-April (May-August) phase, MC convection is relatively weak (vigorous). The CLFO makes pronounced eastward displacement at tropics, with phase propagation seen longitudinally, too. There occur low-frequency disturbance circulations similar to the EAP wavetrain or P-J teleconnection, starting from the MC via the South China Sea and the Philippines to the Yangtze valley of China. At different phases, the variation in the low-frequency circulations and heating fields shows that the rainfall disturbance in eastern China is likely to be under possible effects of the CLFO from the MC in April-September, and the low-frequency heating variation exhibits a meridional pattern as an EAP wavetrain or P-J teleconnection. As the OLR CLFO is in a peak (valley) phase the low-level divergence or convergence with the reversal at high levels over the MC is related to relatively feeble (robust) low frequency convection, thereby exciting an EAP or P-J wavetrain from the MC to the Sea of Japan. At the higher levels, the South-Asian high is eastward (westward) of normal due to effects of low-frequency cyclones (anticyclones), resulting in less (more) rainfall in the Jiangnan (areas in the middle and lower reaches of Yangtze and to the south of the river) and Hetao (the Great Bend of Yellow River) areas, and increased (decreased) rainfall in SW China, Qinghai Plateau and Gansu. At the conversion phases, low-frequency convection becomes more active in parts of the MC, consequently exciting low-frequency wavetrain of cyclones-anticyclones-cyclones at low levels, making the South-Asian high southward of the mean, so that strong convergent zones emerge in the upper and middle Yangtze basins and Jilin of NE China, responsible for plentiful precipitation there in sharp contrast to the rainfall over the band between the Yellow and Huaihe Rivers and the Yunnan-Guizhou Plateau. These results help understand in depth the climatological LFO characteristics and the phase-locked feature, thereby further improving our understanding of the causes of rainfall disturbances in different parts of the country.
2015, 21(4): 374-388.
doi: 10.16555/j.1006-8775.2015.04.006
Abstract:
In the previous study, the influences of introducing larger- and smaller-scale errors on the background error covariances estimated at the given scales were investigated, respectively. This study used the covariances obtained in the previous study in the data assimilation and model forecast system based on three-dimensional variational method and the Weather Research and Forecasting model. In this study, analyses and forecasts from this system with different covariances for a period of one month were compared, and the causes for differing results were presented. The variations of analysis increments with different-scale errors are consistent with those of variances and correlations of background errors that were reported in the previous paper. In particular, the introduction of smaller-scale errors leads to greater amplitudes in analysis increments for medium-scale wind at the heights of both high- and low-level jets. Temperature and humidity analysis increments are greater at the corresponding scales at the middle- and upper-levels. These analysis increments could improve the intensity of the jet-convection system that includes jets at different levels and the coupling between them that is associated with latent heat release. These changes in analyses will contribute to more accurate wind and temperature forecasts in the corresponding areas. When smaller-scale errors are included, humidity analysis increments are significantly enhanced at large scales and lower levels, to moisten southern analyses. Thus, dry bias can be corrected, which will improve humidity forecasts. Moreover, the inclusion of larger- (smaller-) scale errors will be beneficial for the accuracy of forecasts of heavy (light) precipitation at large (small) scales because of the amplification (diminution) of the intensity and area in precipitation forecasts.
In the previous study, the influences of introducing larger- and smaller-scale errors on the background error covariances estimated at the given scales were investigated, respectively. This study used the covariances obtained in the previous study in the data assimilation and model forecast system based on three-dimensional variational method and the Weather Research and Forecasting model. In this study, analyses and forecasts from this system with different covariances for a period of one month were compared, and the causes for differing results were presented. The variations of analysis increments with different-scale errors are consistent with those of variances and correlations of background errors that were reported in the previous paper. In particular, the introduction of smaller-scale errors leads to greater amplitudes in analysis increments for medium-scale wind at the heights of both high- and low-level jets. Temperature and humidity analysis increments are greater at the corresponding scales at the middle- and upper-levels. These analysis increments could improve the intensity of the jet-convection system that includes jets at different levels and the coupling between them that is associated with latent heat release. These changes in analyses will contribute to more accurate wind and temperature forecasts in the corresponding areas. When smaller-scale errors are included, humidity analysis increments are significantly enhanced at large scales and lower levels, to moisten southern analyses. Thus, dry bias can be corrected, which will improve humidity forecasts. Moreover, the inclusion of larger- (smaller-) scale errors will be beneficial for the accuracy of forecasts of heavy (light) precipitation at large (small) scales because of the amplification (diminution) of the intensity and area in precipitation forecasts.
2015, 21(4): 389-399.
doi: 10.16555/j.1006-8775.2015.04.007
Abstract:
This study investigates multi-model ensemble forecasts of track and intensity of tropical cyclones over the western Pacific, based on forecast outputs from the China Meteorological Administration, European Centre for Medium-Range Weather Forecasts, Japan Meteorological Agency and National Centers for Environmental Prediction in the THORPEX Interactive Grand Global Ensemble (TIGGE) datasets. The multi-model ensemble schemes, namely the bias-removed ensemble mean (BREM) and superensemble (SUP), are compared with the ensemble mean (EMN) and single-model forecasts. Moreover, a new model bias estimation scheme is investigated and applied to the BREM and SUP schemes. The results showed that, compared with single-model forecasts and EMN, the multi-model ensembles of the BREM and SUP schemes can have smaller errors in most cases. However, there were also circumstances where BREM was less skillful than EMN, indicating that using a time-averaged error as model bias is not optimal. A new model bias estimation scheme of the biweight mean is introduced. Through minimizing the negative influence of singular errors, this scheme can obtain a more accurate model bias estimation and improve the BREM forecast skill. The application of the biweight mean in the bias calculation of SUP also resulted in improved skill. The results indicate that the modification of multi-model ensemble schemes through this bias estimation method is feasible.
This study investigates multi-model ensemble forecasts of track and intensity of tropical cyclones over the western Pacific, based on forecast outputs from the China Meteorological Administration, European Centre for Medium-Range Weather Forecasts, Japan Meteorological Agency and National Centers for Environmental Prediction in the THORPEX Interactive Grand Global Ensemble (TIGGE) datasets. The multi-model ensemble schemes, namely the bias-removed ensemble mean (BREM) and superensemble (SUP), are compared with the ensemble mean (EMN) and single-model forecasts. Moreover, a new model bias estimation scheme is investigated and applied to the BREM and SUP schemes. The results showed that, compared with single-model forecasts and EMN, the multi-model ensembles of the BREM and SUP schemes can have smaller errors in most cases. However, there were also circumstances where BREM was less skillful than EMN, indicating that using a time-averaged error as model bias is not optimal. A new model bias estimation scheme of the biweight mean is introduced. Through minimizing the negative influence of singular errors, this scheme can obtain a more accurate model bias estimation and improve the BREM forecast skill. The application of the biweight mean in the bias calculation of SUP also resulted in improved skill. The results indicate that the modification of multi-model ensemble schemes through this bias estimation method is feasible.
2015, 21(4): 400-407.
doi: 10.16555/j.1006-8775.2015.04.008
Abstract:
A hybrid GSI (Grid-point Statistical Interpolation)-ETKF (Ensemble Transform Kalman Filter) data assimilation system has been recently developed for the WRF (Weather Research and Forecasting) model and tested with simulated observations for tropical cyclone (TC) forecast. This system is based on the existing GSI but with ensemble background information incorporated. As a follow-up, this work extends the new system to assimilate real observations to further understand the hybrid scheme. As a first effort to explore the system with real observations, relatively coarse grid resolution (27 km) is used. A case study of typhoon Muifa (2011) is performed to assimilate real observations including conventional in-situ and satellite data. The hybrid system with flow-dependent ensemble covariance shows significant improvements with respect to track forecast compared to the standard GSI system which in theory is three dimensional variational analysis (3DVAR). By comparing the analyses, analysis increments and forecasts, the hybrid system is found to be potentially able to recognize the existence of TC vortex, adjust its position systematically, better describe the asymmetric structure of typhoon Muifa and maintain the dynamic and thermodynamic balance in typhoon initial field. In addition, a cold-start hybrid approach by using the global ensembles to provide flow-dependent error is tested and similar results are revealed with those from cycled GSI-ETKF approach.
A hybrid GSI (Grid-point Statistical Interpolation)-ETKF (Ensemble Transform Kalman Filter) data assimilation system has been recently developed for the WRF (Weather Research and Forecasting) model and tested with simulated observations for tropical cyclone (TC) forecast. This system is based on the existing GSI but with ensemble background information incorporated. As a follow-up, this work extends the new system to assimilate real observations to further understand the hybrid scheme. As a first effort to explore the system with real observations, relatively coarse grid resolution (27 km) is used. A case study of typhoon Muifa (2011) is performed to assimilate real observations including conventional in-situ and satellite data. The hybrid system with flow-dependent ensemble covariance shows significant improvements with respect to track forecast compared to the standard GSI system which in theory is three dimensional variational analysis (3DVAR). By comparing the analyses, analysis increments and forecasts, the hybrid system is found to be potentially able to recognize the existence of TC vortex, adjust its position systematically, better describe the asymmetric structure of typhoon Muifa and maintain the dynamic and thermodynamic balance in typhoon initial field. In addition, a cold-start hybrid approach by using the global ensembles to provide flow-dependent error is tested and similar results are revealed with those from cycled GSI-ETKF approach.
2015, 21(4): 408-416.
doi: 10.16555/j.1006-8775.2015.04.009
Abstract:
The variation of the atmospheric Carbon Dioxide (CO2) concentration plays an important role in global climate and agriculture. We analyzed the spatial-temporal characteristics of CO2 in the China region and around the globe with the CO2 column mixing ratios observed by the Japanese GOSAT satellite (Greenhouse Gases Observing Satellite). In order to make sure that the accuracy of the CO2 data retrieved by the satellite meets the needs of the climate characteristics analyses, we ran a validation on the CO2 column mixing ratios retrieved by the satellite against the ground-based TCCON (Total Carbon Column Observing Network) observation data. The result shows that the two sets of data have a correlation coefficient of higher than 0.7, and a bias of within 2.2 ppmv. Therefore, the GOSAT CO2 data can be used for the climate characteristics analysis of global CO2. Our analysis on the spatial-temporal characteristics of the CO2 column mixing ratios observed during the period of June 2009 through January 2014 proved that, with the impact of the natural emission of near ground CO2 and human activities, the global CO2 concentration has a significant latitudinal characteristics with its highest level averaging 390 ppmv in the 0-40oN latitudinal zone in the Northern Hemisphere, and 387 ppmv in the Southern Hemisphere. China has a relatively higher CO2 concentration with the highest level exceeding 398 ppmv, and the eastern area higher than the western area. The variation of global CO2 concentration shows a seasonal pattern, i.e. the CO2 concentration reaches its highest in spring in the Northern Hemisphere averaging more than 392 ppmv, second highest in winter, and lowest in summer averaging less than 387 ppmv. It fluctuates the most in the Northern Hemisphere with an average concentration of 392.5 ppmv in April, and 385.5 ppmv in July. While in the Southern Hemisphere, the seasonal fluctuation is smaller with the highest concentration occurring in July. Over the recent years, the global CO2 concentration has shown an elevating trend with an average annual increase rate of 1.58 ppmv per year. It is a challenge that the human kind has to face to slow down the increase of the CO2 concentration.
The variation of the atmospheric Carbon Dioxide (CO2) concentration plays an important role in global climate and agriculture. We analyzed the spatial-temporal characteristics of CO2 in the China region and around the globe with the CO2 column mixing ratios observed by the Japanese GOSAT satellite (Greenhouse Gases Observing Satellite). In order to make sure that the accuracy of the CO2 data retrieved by the satellite meets the needs of the climate characteristics analyses, we ran a validation on the CO2 column mixing ratios retrieved by the satellite against the ground-based TCCON (Total Carbon Column Observing Network) observation data. The result shows that the two sets of data have a correlation coefficient of higher than 0.7, and a bias of within 2.2 ppmv. Therefore, the GOSAT CO2 data can be used for the climate characteristics analysis of global CO2. Our analysis on the spatial-temporal characteristics of the CO2 column mixing ratios observed during the period of June 2009 through January 2014 proved that, with the impact of the natural emission of near ground CO2 and human activities, the global CO2 concentration has a significant latitudinal characteristics with its highest level averaging 390 ppmv in the 0-40oN latitudinal zone in the Northern Hemisphere, and 387 ppmv in the Southern Hemisphere. China has a relatively higher CO2 concentration with the highest level exceeding 398 ppmv, and the eastern area higher than the western area. The variation of global CO2 concentration shows a seasonal pattern, i.e. the CO2 concentration reaches its highest in spring in the Northern Hemisphere averaging more than 392 ppmv, second highest in winter, and lowest in summer averaging less than 387 ppmv. It fluctuates the most in the Northern Hemisphere with an average concentration of 392.5 ppmv in April, and 385.5 ppmv in July. While in the Southern Hemisphere, the seasonal fluctuation is smaller with the highest concentration occurring in July. Over the recent years, the global CO2 concentration has shown an elevating trend with an average annual increase rate of 1.58 ppmv per year. It is a challenge that the human kind has to face to slow down the increase of the CO2 concentration.
2015, 21(4): 417-427.
doi: 10.16555/j.1006-8775.2015.04.010
Abstract:
This paper further explores the estimating and expressing of dynamic balance constraints using statistical methods in GRAPES-3DVAR (Version GM). Unlike the single-level scheme which only considers the coupling between mass and wind at one level, the multi-level scheme considers the coupling between their vertical profiles and calculates the balanced mass field at each layer using the rotational wind at all model levels. A reformed ridge regression method is used in the new scheme to avoid the multicollinearity problem and reduce the noises caused by unbalanced mesoscale disturbances. The results of numerical experiments show that the new scheme can get more reasonable vertical mass field, reduce the magnitude of the adjustment by the initialization, and improve the potential temperature analysis performance. Furthermore, the results of forecast verification in January (winter) and July (summer) both confirm that the new scheme can significantly improve the temperature forecast accuracy and bring slight positive effects to the pressure and wind forecast.
This paper further explores the estimating and expressing of dynamic balance constraints using statistical methods in GRAPES-3DVAR (Version GM). Unlike the single-level scheme which only considers the coupling between mass and wind at one level, the multi-level scheme considers the coupling between their vertical profiles and calculates the balanced mass field at each layer using the rotational wind at all model levels. A reformed ridge regression method is used in the new scheme to avoid the multicollinearity problem and reduce the noises caused by unbalanced mesoscale disturbances. The results of numerical experiments show that the new scheme can get more reasonable vertical mass field, reduce the magnitude of the adjustment by the initialization, and improve the potential temperature analysis performance. Furthermore, the results of forecast verification in January (winter) and July (summer) both confirm that the new scheme can significantly improve the temperature forecast accuracy and bring slight positive effects to the pressure and wind forecast.
2015, 21(4): 428-428.
doi: 10.16555/j.1006-8775.2015.04.011
Abstract:
Based on the number of foggy days in Nanjing in December from 1980 to 2011, we analyzed the surface temperature and atmospheric circulation characteristics of foggy years and less-foggy years. Positive anomalies of the Arctic Oscillation (AO) were found to weaken the East Asian trough, which is not conducive to the southward migration of cold air. Simultaneously, this atmospheric condition favors stability as a result of a high-pressure anomaly from the middle Yangtze River Delta region. A portion of La Niña events increases the amount of water vapor in the South China Sea region, so this phenomenon could provide the water vapor condition required for foggy days in Nanjing. Based on the data in December 2007, which contained the greatest number of foggy days for the years studied, the source of fog vapor in Nanjing was primarily from southern China and southwest Taiwan Island based on a synoptic scale study. The water vapor in southern China and in the southwestern flow increased, and after a period of 2-3 days, the humidity in Nanjing increased. Simultaneously, the water vapor from the southwestern of Taiwan Island was directly transported to Nanjing by the southerly wind. Therefore, these two areas are the most important sources of water vapor that results in heavy fog in Nanjing. Using the bivariate Empirical Orthogonal Function (EOF) mode on the surface temperature and precipitable water vapor, the first mode was found to reflect the seasonal variation from early winter to late winter, which reduced the surface temperature on a large scale. The second mode was found to reflect a large-scale, northward, warm and humid airflow that was accompanied by the enhancement of the subtropical high, particularly between December 15-21, which is primarily responsible for the consecutive foggy days in Nanjing.
Based on the number of foggy days in Nanjing in December from 1980 to 2011, we analyzed the surface temperature and atmospheric circulation characteristics of foggy years and less-foggy years. Positive anomalies of the Arctic Oscillation (AO) were found to weaken the East Asian trough, which is not conducive to the southward migration of cold air. Simultaneously, this atmospheric condition favors stability as a result of a high-pressure anomaly from the middle Yangtze River Delta region. A portion of La Niña events increases the amount of water vapor in the South China Sea region, so this phenomenon could provide the water vapor condition required for foggy days in Nanjing. Based on the data in December 2007, which contained the greatest number of foggy days for the years studied, the source of fog vapor in Nanjing was primarily from southern China and southwest Taiwan Island based on a synoptic scale study. The water vapor in southern China and in the southwestern flow increased, and after a period of 2-3 days, the humidity in Nanjing increased. Simultaneously, the water vapor from the southwestern of Taiwan Island was directly transported to Nanjing by the southerly wind. Therefore, these two areas are the most important sources of water vapor that results in heavy fog in Nanjing. Using the bivariate Empirical Orthogonal Function (EOF) mode on the surface temperature and precipitable water vapor, the first mode was found to reflect the seasonal variation from early winter to late winter, which reduced the surface temperature on a large scale. The second mode was found to reflect a large-scale, northward, warm and humid airflow that was accompanied by the enhancement of the subtropical high, particularly between December 15-21, which is primarily responsible for the consecutive foggy days in Nanjing.
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