2010 Vol. 27, No. 6
Display Method:
2010, 27(6): 1221-1232.
doi: 10.1007/s00376-010-9151-y
Abstract:
Climate research relies heavily on good quality instrumental data; for modeling efforts gridded data are needed. So far, relatively little effort has been made to create gridded climate data for China. This is especially true for high-resolution daily data. This work, focuses on identifying an accurate method to produce gridded daily precipitation in China based on the observed data at 753 stations for the period 1951--2005. Five interpolation methods, including ordinary nearest neighbor, local polynomial, radial basis function, inverse distance weighting, and ordinary kriging, have been used and compared. Cross-validation shows that the ordinary kriging based on seasonal semi-variograms gives the best performance, closely followed by the inverse distance weighting with a power of 2. Finally the ordinary kriging is chosen to interpolate the station data to a 18 km×18 km grid system covering the whole country. Precipitation for each 0.5o×0.5o latitude-longitude block is then obtained by averaging the values at the grid nodes within the block. Owing to the higher station density in the eastern part of the country, the interpolation errors are much smaller than those in the west (west of 100oE). Excluding 145 stations in the western region, the daily, monthly, and annual relative mean absolute errors of the interpolation for the remaining 608 stations are 74%, 29%, and 16%, respectively. The interpolated daily precipitation has been made available on the internet for the scientific community.
Climate research relies heavily on good quality instrumental data; for modeling efforts gridded data are needed. So far, relatively little effort has been made to create gridded climate data for China. This is especially true for high-resolution daily data. This work, focuses on identifying an accurate method to produce gridded daily precipitation in China based on the observed data at 753 stations for the period 1951--2005. Five interpolation methods, including ordinary nearest neighbor, local polynomial, radial basis function, inverse distance weighting, and ordinary kriging, have been used and compared. Cross-validation shows that the ordinary kriging based on seasonal semi-variograms gives the best performance, closely followed by the inverse distance weighting with a power of 2. Finally the ordinary kriging is chosen to interpolate the station data to a 18 km×18 km grid system covering the whole country. Precipitation for each 0.5o×0.5o latitude-longitude block is then obtained by averaging the values at the grid nodes within the block. Owing to the higher station density in the eastern part of the country, the interpolation errors are much smaller than those in the west (west of 100oE). Excluding 145 stations in the western region, the daily, monthly, and annual relative mean absolute errors of the interpolation for the remaining 608 stations are 74%, 29%, and 16%, respectively. The interpolated daily precipitation has been made available on the internet for the scientific community.
2010, 27(6): 1233-1245.
doi: 10.1007/s00376-010-9175-3
Abstract:
The cloud phase composition of cold clouds in the Antarctic atmosphere is explored using data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instruments for the period 2000--2006. We used the averaged fraction of liquid-phase clouds out of the total cloud amount at the cloud tops since the value is comparable in the two measurements. MODIS data for the winter months (June, July, and August) reveal liquid cloud fraction out of the total cloud amount significantly decreases with decreasing cloud-top temperature below 0oC. In addition, the CALIOP vertical profiles show that below the ice clouds, low-lying liquid clouds are distributed over ～20% of the area. With increasing latitude, the liquid cloud fraction decreases as a function of the local temperature. The MODIS-observed relation between the cloud-top liquid fraction and cloud-top temperature is then applied to evaluate the cloud phase parameterization in climate models, in which condensed cloud water is repartitioned between liquid water and ice on the basis of the grid point temperature. It is found that models assuming overly high cut-offs (》-40oC) for the separation of ice clouds from mixed-phase clouds may significantly underestimate the liquid cloud fraction in the winter Antarctic atmosphere. Correction of the bias in the liquid cloud fraction would serve to reduce the large uncertainty in cloud radiative effects.
The cloud phase composition of cold clouds in the Antarctic atmosphere is explored using data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instruments for the period 2000--2006. We used the averaged fraction of liquid-phase clouds out of the total cloud amount at the cloud tops since the value is comparable in the two measurements. MODIS data for the winter months (June, July, and August) reveal liquid cloud fraction out of the total cloud amount significantly decreases with decreasing cloud-top temperature below 0oC. In addition, the CALIOP vertical profiles show that below the ice clouds, low-lying liquid clouds are distributed over ～20% of the area. With increasing latitude, the liquid cloud fraction decreases as a function of the local temperature. The MODIS-observed relation between the cloud-top liquid fraction and cloud-top temperature is then applied to evaluate the cloud phase parameterization in climate models, in which condensed cloud water is repartitioned between liquid water and ice on the basis of the grid point temperature. It is found that models assuming overly high cut-offs (》-40oC) for the separation of ice clouds from mixed-phase clouds may significantly underestimate the liquid cloud fraction in the winter Antarctic atmosphere. Correction of the bias in the liquid cloud fraction would serve to reduce the large uncertainty in cloud radiative effects.
2010, 27(6): 1246-1258.
doi: 10.1007/s00376-010-9096-1
Abstract:
The Tropical Cyclone Genesis Potential Index (GPI) was employed to investigate possible impacts of global warming on tropical cyclone genesis over the western North Pacific (WNP). The outputs of 20th century climate simulation by eighteen GCMs were used to evaluate the models' ability to reproduce tropical cyclone genesis via the GPI. The GCMs were found in general to reasonably reproduce the observed spatial distribution of genesis. Some of the models also showed ability in capturing observed temporal variation. Based on the evaluation, the models (CGCM3.1-T47 and IPSL-CM4) found to perform best when reproducing both spatial and temporal features were chosen to project future GPI. Results show that both of these models project an upward trend of the GPI under the SRES A2 scenario, however the rate of increase differs between them.
The Tropical Cyclone Genesis Potential Index (GPI) was employed to investigate possible impacts of global warming on tropical cyclone genesis over the western North Pacific (WNP). The outputs of 20th century climate simulation by eighteen GCMs were used to evaluate the models' ability to reproduce tropical cyclone genesis via the GPI. The GCMs were found in general to reasonably reproduce the observed spatial distribution of genesis. Some of the models also showed ability in capturing observed temporal variation. Based on the evaluation, the models (CGCM3.1-T47 and IPSL-CM4) found to perform best when reproducing both spatial and temporal features were chosen to project future GPI. Results show that both of these models project an upward trend of the GPI under the SRES A2 scenario, however the rate of increase differs between them.
2010, 27(6): 1259-1275.
doi: 10.1007/s00376-010-8192-6
Abstract:
The microphysical properties of a long-lasting heavy fog event are examined based on the results from a comprehensive field campaign conducted during the winter of 2006 at Pancheng (32.2N, 118.7E), Jiangsu Province, China. It is demonstrated that the key microphysical properties (liquid water content, fog droplet concentration, mean radius and standard deviation) exhibited positive correlations with one another in general, and that the 5-min-average maximum value of fog liquid water content was sometimes greater than 0.5 g m-3. Further analysis shows that the unique combination of positive correlations likely arose from the simultaneous supply of moist air and fog condensation nuclei associated with the advection of warm air, which further led to high liquid water content. High values of liquid water content and droplet concentration conspired to cause low visibility (<50 m) for a prolonged period of about 40 h. Examination of the microphysical relationships conditioned by the corresponding autoconversion threshold functions shows that the collision-coalescence process was sometimes likely to occur, weakening the positive correlations induced by droplet activation and condensational growth. Statistical analysis shows that the observed droplet size distribution can be described well by the Gamma distribution.
The microphysical properties of a long-lasting heavy fog event are examined based on the results from a comprehensive field campaign conducted during the winter of 2006 at Pancheng (32.2N, 118.7E), Jiangsu Province, China. It is demonstrated that the key microphysical properties (liquid water content, fog droplet concentration, mean radius and standard deviation) exhibited positive correlations with one another in general, and that the 5-min-average maximum value of fog liquid water content was sometimes greater than 0.5 g m-3. Further analysis shows that the unique combination of positive correlations likely arose from the simultaneous supply of moist air and fog condensation nuclei associated with the advection of warm air, which further led to high liquid water content. High values of liquid water content and droplet concentration conspired to cause low visibility (<50 m) for a prolonged period of about 40 h. Examination of the microphysical relationships conditioned by the corresponding autoconversion threshold functions shows that the collision-coalescence process was sometimes likely to occur, weakening the positive correlations induced by droplet activation and condensational growth. Statistical analysis shows that the observed droplet size distribution can be described well by the Gamma distribution.
2010, 27(6): 1276-1288.
doi: 10.1007/s00376-010-9188-y
Abstract:
In this paper, the RIEMS 2.0 model is used to simulate the distribution of sulfate, black carbon, and organic carbon aerosols over China (16.2--44.1N, 93.4--132.4E) in 1998. The climate effects of these three anthropogenic aerosols are also simulated. The results are summarized as follows: (1) The regional average column burdens of sulfate, BC, OC, and SOC were 5.9, 0.24, 2.4, and 0.49 mg m-2, with maxima of 33.9, 1.48, 7.3, and 1.1 mg m-2, respectively. The column burden and surface concentration of secondary organic carbon accounted for about 20% and 7%, respectively, of the total organic carbon in eastern China. (2) The radiative forcings of sulfate, organic carbon, and black carbon at the top of the atmosphere were -1.24, -0.6, and 0.16 W m-2, respectively, with extremes of -5.25, -2.6, and 0.91 W m-2. (3) The surface air temperature changes caused by sulfate, organic carbon, and black carbon were -0.07, -0.04, and 0.01 K, respectively. The air temperature increase caused by black carbon at 850 hPa was higher than that at the surface. The net effect of the three kinds of anthropogenic aerosols together decreased the annual average temperature by -0.075 K; the maximum value was -0.3 K. (4) Black carbon can reduce the precipitation in arid and semi-arid areas of northern China and increase the precipitation in wet and semi-wet areas of southern China. The average precipitation increase caused by black carbon in China was 0.003 mm d-1. The net effect of the three kinds of anthropogenic aerosols was to decrease the precipitation over China by 0.008 mm d-1.
In this paper, the RIEMS 2.0 model is used to simulate the distribution of sulfate, black carbon, and organic carbon aerosols over China (16.2--44.1N, 93.4--132.4E) in 1998. The climate effects of these three anthropogenic aerosols are also simulated. The results are summarized as follows: (1) The regional average column burdens of sulfate, BC, OC, and SOC were 5.9, 0.24, 2.4, and 0.49 mg m-2, with maxima of 33.9, 1.48, 7.3, and 1.1 mg m-2, respectively. The column burden and surface concentration of secondary organic carbon accounted for about 20% and 7%, respectively, of the total organic carbon in eastern China. (2) The radiative forcings of sulfate, organic carbon, and black carbon at the top of the atmosphere were -1.24, -0.6, and 0.16 W m-2, respectively, with extremes of -5.25, -2.6, and 0.91 W m-2. (3) The surface air temperature changes caused by sulfate, organic carbon, and black carbon were -0.07, -0.04, and 0.01 K, respectively. The air temperature increase caused by black carbon at 850 hPa was higher than that at the surface. The net effect of the three kinds of anthropogenic aerosols together decreased the annual average temperature by -0.075 K; the maximum value was -0.3 K. (4) Black carbon can reduce the precipitation in arid and semi-arid areas of northern China and increase the precipitation in wet and semi-wet areas of southern China. The average precipitation increase caused by black carbon in China was 0.003 mm d-1. The net effect of the three kinds of anthropogenic aerosols was to decrease the precipitation over China by 0.008 mm d-1.
2010, 27(6): 1289-1302.
doi: 10.1007/s00376-010-9155-7
Abstract:
Based on station observations, The European Centre for Medium-Range Weather Forecasts reanalysis (ERA40), the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis and Princeton University's global meteorological forcing data set (Princeton), four atmospheric forcing fields were constructed for use in driving the Community Land Model version 3.5 (CLM3.5). Simulated soil moisture content throughout the period 1951--2000 in the Yellow River basin was validated via comparison with corresponding observations in the upper, middle, and lower reaches. The results show that CLM3.5 is capable of reproducing not only the characteristics of intra-annual and annual variations of soil moisture, but also long-term variation trends, with different statistical significance in the correlations between the observations and simulations from different forcing fields in various reaches. The simulations modeled with station-based atmospheric forcing fields are the most consistent with observed soil moisture, and the simulations based on the Princeton data set are the second best, on average. The simulations from ERA40 and NCEP/NCAR are close to each other in quality, but comparatively worse to the other sources of forcing information that were evaluated. Regionally, simulations are most consistent with observations in the lower reaches and less so in the upper reaches, with the middle reaches in between. In addition, the soil moisture simulated by CLM3.5 is systematically greater than the observations in the Yellow River basin. Comparisons between the simulations by CLM3.5 and CLM3.0 indicate that simulation errors are primarily caused by deficiencies within CLM3.5 and are also associated with the quality of atmospheric forcing field applied.
Based on station observations, The European Centre for Medium-Range Weather Forecasts reanalysis (ERA40), the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis and Princeton University's global meteorological forcing data set (Princeton), four atmospheric forcing fields were constructed for use in driving the Community Land Model version 3.5 (CLM3.5). Simulated soil moisture content throughout the period 1951--2000 in the Yellow River basin was validated via comparison with corresponding observations in the upper, middle, and lower reaches. The results show that CLM3.5 is capable of reproducing not only the characteristics of intra-annual and annual variations of soil moisture, but also long-term variation trends, with different statistical significance in the correlations between the observations and simulations from different forcing fields in various reaches. The simulations modeled with station-based atmospheric forcing fields are the most consistent with observed soil moisture, and the simulations based on the Princeton data set are the second best, on average. The simulations from ERA40 and NCEP/NCAR are close to each other in quality, but comparatively worse to the other sources of forcing information that were evaluated. Regionally, simulations are most consistent with observations in the lower reaches and less so in the upper reaches, with the middle reaches in between. In addition, the soil moisture simulated by CLM3.5 is systematically greater than the observations in the Yellow River basin. Comparisons between the simulations by CLM3.5 and CLM3.0 indicate that simulation errors are primarily caused by deficiencies within CLM3.5 and are also associated with the quality of atmospheric forcing field applied.
2010, 27(6): 1303-1310.
doi: 10.1007/s00376-010-9067-6
Abstract:
A four dimensional variational data assimilation (4DVar) based on a dimension-reduced projection (DRP-4DVar) has been developed as a hybrid of the 4DVar and Ensemble Kalman filter (EnKF) concepts. Its good flow-dependent features are demonstrated in single-point experiments through comparisons with adjoint-based 4DVar and three-dimensional variational data (3DVar) assimilations using the fifth-generation Pennsylvania State University-National Center for Atmospheric Research Mesoscale Model (MM5). The results reveal that DRP-4DVar can reasonably generate a background error covariance matrix (simply B-matrix) during the assimilation window from an initial estimation using a number of initial condition dependent historical forecast samples. In contrast, flow-dependence in the B-matrix of MM5 4DVar is barely detectable. It is argued that use of diagonal estimation in the B-matrix of the MM5 4DVar method at the initial time leads to this failure. The experiments also show that the increments produced by DRP-4DVar are anisotropic and no longer symmetric with respect to observation location due to the effects of the weather trends captured in its B-matrix. This differs from the MM5 3DVar which does not consider the influence of heterogeneous forcing on the correlation structure of the B-matrix, a condition that is realistic for many situations. Thus, the MM5 3DVar assimilation could only present an isotropic and homogeneous structure in its increments.
A four dimensional variational data assimilation (4DVar) based on a dimension-reduced projection (DRP-4DVar) has been developed as a hybrid of the 4DVar and Ensemble Kalman filter (EnKF) concepts. Its good flow-dependent features are demonstrated in single-point experiments through comparisons with adjoint-based 4DVar and three-dimensional variational data (3DVar) assimilations using the fifth-generation Pennsylvania State University-National Center for Atmospheric Research Mesoscale Model (MM5). The results reveal that DRP-4DVar can reasonably generate a background error covariance matrix (simply B-matrix) during the assimilation window from an initial estimation using a number of initial condition dependent historical forecast samples. In contrast, flow-dependence in the B-matrix of MM5 4DVar is barely detectable. It is argued that use of diagonal estimation in the B-matrix of the MM5 4DVar method at the initial time leads to this failure. The experiments also show that the increments produced by DRP-4DVar are anisotropic and no longer symmetric with respect to observation location due to the effects of the weather trends captured in its B-matrix. This differs from the MM5 3DVar which does not consider the influence of heterogeneous forcing on the correlation structure of the B-matrix, a condition that is realistic for many situations. Thus, the MM5 3DVar assimilation could only present an isotropic and homogeneous structure in its increments.
2010, 27(6): 1311-1321.
doi: 10.1007/s00376-010-9088-1
Abstract:
The conditional nonlinear optimal perturbation (CNOP), which is a nonlinear generalization of the linear singular vector (LSV), is applied in important problems of atmospheric and oceanic sciences, including ENSO predictability, targeted observations, and ensemble forecast. In this study, we investigate the computational cost of obtaining the CNOP by several methods. Differences and similarities, in terms of the computational error and cost in obtaining the CNOP, are compared among the sequential quadratic programming (SQP) algorithm, the limited memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) algorithm, and the spectral projected gradients (SPG2) algorithm. A theoretical grassland ecosystem model and the classical Lorenz model are used as examples. Numerical results demonstrate that the computational error is acceptable with all three algorithms. The computational cost to obtain the CNOP is reduced by using the SQP algorithm. The experimental results also reveal that the L-BFGS algorithm is the most effective algorithm among the three optimization algorithms for obtaining the CNOP. The numerical results suggest a new approach and algorithm for obtaining the CNOP for a large-scale optimization problem.
The conditional nonlinear optimal perturbation (CNOP), which is a nonlinear generalization of the linear singular vector (LSV), is applied in important problems of atmospheric and oceanic sciences, including ENSO predictability, targeted observations, and ensemble forecast. In this study, we investigate the computational cost of obtaining the CNOP by several methods. Differences and similarities, in terms of the computational error and cost in obtaining the CNOP, are compared among the sequential quadratic programming (SQP) algorithm, the limited memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) algorithm, and the spectral projected gradients (SPG2) algorithm. A theoretical grassland ecosystem model and the classical Lorenz model are used as examples. Numerical results demonstrate that the computational error is acceptable with all three algorithms. The computational cost to obtain the CNOP is reduced by using the SQP algorithm. The experimental results also reveal that the L-BFGS algorithm is the most effective algorithm among the three optimization algorithms for obtaining the CNOP. The numerical results suggest a new approach and algorithm for obtaining the CNOP for a large-scale optimization problem.
2010, 27(6): 1322-1330.
doi: 10.1007/s00376-010-9212-2
Abstract:
The accurate measurement of concentration is the basis for determining emission sources and sinks of nitrous oxide (N2O). The detection of N2O showed that the presence of carbon dioxide (CO2 biased the N2O response when pure nitrogen (N2) was used as a carrier gas for gas chromatography (GC) equipped with an electron capture detector (GC-ECD). In this study, laboratory experiments were carried out to explore how the presence of CO2 interferes with the accurate determination of N2O. The aims were to address the extent of the influence to try and explain the underlying mechanism, and to uncover technical options for solving the problem. Three GC carrier gases are discussed: pure nitrogen (DN); a mixture of argon and methane (AM); and a high concentration CO2, which was introduced into the ECD cell with a low flow rate based on DN (DN-CO2). The results show that when DN was used, the existence of CO2 in the ECD cell greatly enhanced the response of N2O, which increased with CO2 content and remained constant when the content reached a limit. Comparisons between the three methods show that the DN method is defective for the accurate determination of N2O. The bias is caused by ifferent electron capture mechanisms of CO2 and N2O and depends heavily on the detector temperature. New GC carrier gas types with make-up gases that can remove the CO2-induced influence, such as the DN-CO2 and DN-CH4 methods reported in this paper, are recommended for the accurate measurement of N2O.
The accurate measurement of concentration is the basis for determining emission sources and sinks of nitrous oxide (N2O). The detection of N2O showed that the presence of carbon dioxide (CO2 biased the N2O response when pure nitrogen (N2) was used as a carrier gas for gas chromatography (GC) equipped with an electron capture detector (GC-ECD). In this study, laboratory experiments were carried out to explore how the presence of CO2 interferes with the accurate determination of N2O. The aims were to address the extent of the influence to try and explain the underlying mechanism, and to uncover technical options for solving the problem. Three GC carrier gases are discussed: pure nitrogen (DN); a mixture of argon and methane (AM); and a high concentration CO2, which was introduced into the ECD cell with a low flow rate based on DN (DN-CO2). The results show that when DN was used, the existence of CO2 in the ECD cell greatly enhanced the response of N2O, which increased with CO2 content and remained constant when the content reached a limit. Comparisons between the three methods show that the DN method is defective for the accurate determination of N2O. The bias is caused by ifferent electron capture mechanisms of CO2 and N2O and depends heavily on the detector temperature. New GC carrier gas types with make-up gases that can remove the CO2-induced influence, such as the DN-CO2 and DN-CH4 methods reported in this paper, are recommended for the accurate measurement of N2O.
2010, 27(6): 1331-1343.
doi: 10.1007/s00376-010-9114-3
Abstract:
In the Mexican Intertropical Convergence Zone, particle size distributions within 500 m of cloud boundaries at altitudes of 1000, 2500, and 4200 m, were compared against size distributions at the same levels but 1500 m away from the clouds. The differences in the distributions near and far from the cloud are related to processes that may change particle properties inside the cloud. Chemical changes in the aerosols are deduced from the particles' refractive index, as derived from comparisons with the scattering coefficient measured by a nephelometer. An analysis of ten cloud systems indicates that vertical transport of cloud base aerosol followed by entrainment/detrainment is the cloud processing signature most frequently observed in the comparisons (65%). Changes in the chemical composition are observed in approximately 20{\%} of the cases and another 20% of the cases showed removal by precipitation. About 5% of the comparisons showed clear evidence of changes by coalescence. The principal effect of these cloud-processed aerosols is observed in the increase of optical depth in the layer from 30 m to 4200 m in the near-cloud regions, in comparison with the atmosphere further from clouds.
In the Mexican Intertropical Convergence Zone, particle size distributions within 500 m of cloud boundaries at altitudes of 1000, 2500, and 4200 m, were compared against size distributions at the same levels but 1500 m away from the clouds. The differences in the distributions near and far from the cloud are related to processes that may change particle properties inside the cloud. Chemical changes in the aerosols are deduced from the particles' refractive index, as derived from comparisons with the scattering coefficient measured by a nephelometer. An analysis of ten cloud systems indicates that vertical transport of cloud base aerosol followed by entrainment/detrainment is the cloud processing signature most frequently observed in the comparisons (65%). Changes in the chemical composition are observed in approximately 20{\%} of the cases and another 20% of the cases showed removal by precipitation. About 5% of the comparisons showed clear evidence of changes by coalescence. The principal effect of these cloud-processed aerosols is observed in the increase of optical depth in the layer from 30 m to 4200 m in the near-cloud regions, in comparison with the atmosphere further from clouds.
2010, 27(6): 1344-1360.
doi: 10.1007/s00376-010-9129-9
Abstract:
A springtime tropopause fold event, found to be related to a cold trough intrusion from the north, was detected in the northeastern Tibetan Plateau (TP) based on various observations. A nested high-resolution mesoscale model was employed to investigate the effect of orography on the stratosphere--troposphere exchange. The model was found to be able to capture plausible tropopause fold properties. The propagation of the tropopause fold changed significantly when the terrain height in the model was altered. However, decreasing the terrain height had no significant effect on the morphology of folds. When a fold passed over an elevated surface, a leeside jet stream and a layer of humid air in the middle troposphere tended to develop. This strong leeside descent of air masses and high mid-level potential instability (PI) could give rise to deep upward motions in the leeside and inject tropospheric air into the lower stratosphere. Besides, when the flow encounters an elevated surface, forced lifting together with mid-level PI can trigger deep convective motions on the windward slope. The troposphere to stratosphere transport was found to be persistent and almost stationary over the windward slope of the TP during the evolution of the fold.
A springtime tropopause fold event, found to be related to a cold trough intrusion from the north, was detected in the northeastern Tibetan Plateau (TP) based on various observations. A nested high-resolution mesoscale model was employed to investigate the effect of orography on the stratosphere--troposphere exchange. The model was found to be able to capture plausible tropopause fold properties. The propagation of the tropopause fold changed significantly when the terrain height in the model was altered. However, decreasing the terrain height had no significant effect on the morphology of folds. When a fold passed over an elevated surface, a leeside jet stream and a layer of humid air in the middle troposphere tended to develop. This strong leeside descent of air masses and high mid-level potential instability (PI) could give rise to deep upward motions in the leeside and inject tropospheric air into the lower stratosphere. Besides, when the flow encounters an elevated surface, forced lifting together with mid-level PI can trigger deep convective motions on the windward slope. The troposphere to stratosphere transport was found to be persistent and almost stationary over the windward slope of the TP during the evolution of the fold.
2010, 27(6): 1361-1371.
doi: 10.1007/s00376-010-9161-9
Abstract:
Using a statistical model for simulating tropical cyclone (TC) formation and a trajectory model for simulating TC tracks, the influence of the El Nino-Southern Oscillation (ENSO) on the peak-season (July--September) TC prevailing tracks in the western North Pacific basin is assessed based on 14 selected El Nino and 14 selected La Nina years during the period 1950--2007. It is found that the combination of statistical formation model and a trajectory model can simulate well the primary features of TC prevailing tracks on the interannual timescale. In the El Nino years, the significant enhancement of TC activity primarily occurs south of 20N, especially east of 130E. TCs that take the northwestward prevailing track and affect East Asia, including Taiwan Island, the Chinese mainland, Korea, and Japan, tend to move more westward in the El Nino years, while taking a more northward track in the La Nina years. Numerical simulations confirm that the ENSO-related changes in large-scale steering flows and TC formation locations can have a considerable influence on TC prevailing tracks.
Using a statistical model for simulating tropical cyclone (TC) formation and a trajectory model for simulating TC tracks, the influence of the El Nino-Southern Oscillation (ENSO) on the peak-season (July--September) TC prevailing tracks in the western North Pacific basin is assessed based on 14 selected El Nino and 14 selected La Nina years during the period 1950--2007. It is found that the combination of statistical formation model and a trajectory model can simulate well the primary features of TC prevailing tracks on the interannual timescale. In the El Nino years, the significant enhancement of TC activity primarily occurs south of 20N, especially east of 130E. TCs that take the northwestward prevailing track and affect East Asia, including Taiwan Island, the Chinese mainland, Korea, and Japan, tend to move more westward in the El Nino years, while taking a more northward track in the La Nina years. Numerical simulations confirm that the ENSO-related changes in large-scale steering flows and TC formation locations can have a considerable influence on TC prevailing tracks.
2010, 27(6): 1372-1379.
doi: 10.1007/s00376-010-9218-9
Abstract:
CO2 efflux was estimated using different regression methods in static chamber observation from an alpine meadow on the Qinghai-Tibetan Plateau. The CO2 efflux showed a seasonal pattern, with the maximun flux occurring in the middle of July. The temperature sensitivity of CO2 efflux (Q10> was 3.9, which was at the high end of the range of global values. CO2 emissions calculated by linear and nonlinear regression were significantly different (p<0.05). Compared with the linear regression, CO2 emissions calculated by exponential regression and quadratic regression were 12.7% and 11.2% larger, respectively. However, there were no significant differences in temperature sensitivity values estimated by the three methods. In the entire growing season, the CO2 efflux estimated by linear regression may be underestimated by up to 25% compared to the real CO2 efflux. Consequently, great caution should be taken when using published flux data obtained by linear regression of static chamber observations to estimate the regional CO2 flux in alpine meadows on the Qinghai-Tibetan Plateau.
CO2 efflux was estimated using different regression methods in static chamber observation from an alpine meadow on the Qinghai-Tibetan Plateau. The CO2 efflux showed a seasonal pattern, with the maximun flux occurring in the middle of July. The temperature sensitivity of CO2 efflux (Q10> was 3.9, which was at the high end of the range of global values. CO2 emissions calculated by linear and nonlinear regression were significantly different (p<0.05). Compared with the linear regression, CO2 emissions calculated by exponential regression and quadratic regression were 12.7% and 11.2% larger, respectively. However, there were no significant differences in temperature sensitivity values estimated by the three methods. In the entire growing season, the CO2 efflux estimated by linear regression may be underestimated by up to 25% compared to the real CO2 efflux. Consequently, great caution should be taken when using published flux data obtained by linear regression of static chamber observations to estimate the regional CO2 flux in alpine meadows on the Qinghai-Tibetan Plateau.
2010, 27(6): 1380-1388.
doi: 10.1007/s00376-010-9204-2
Abstract:
A long-term dataset of photosynthetically active radiation (Qp) is reconstructed from a broadband global solar radiation (Rs) dataset through an all-weather reconstruction model. This method is based on four years' worth of data collected in Beijing. Observation data of Rs and Qp from 2005--2008 are used to investigate the temporal variability of Qp and its dependence on the clearness index and solar zenith angle. A simple and efficient all-weather empirically derived reconstruction model is proposed to reconstruct Qp from Rs. This reconstruction method is found to estimate instantaneous Qp with high accuracy. The annual mean of the daily values of Qp during the period 1958--2005 period is 25.06 mol m-2 d-1. The magnitude of the long-term trend for the annual averaged Qp is presented (-0.19 mol m-2 yr-1 from 1958--1997 and -0.12 mol m-2 yr-1 from 1958--2005). The trend in Qp exhibits sharp decreases in the spring and summer and more gentle decreases in the autumn and winter.
A long-term dataset of photosynthetically active radiation (Qp) is reconstructed from a broadband global solar radiation (Rs) dataset through an all-weather reconstruction model. This method is based on four years' worth of data collected in Beijing. Observation data of Rs and Qp from 2005--2008 are used to investigate the temporal variability of Qp and its dependence on the clearness index and solar zenith angle. A simple and efficient all-weather empirically derived reconstruction model is proposed to reconstruct Qp from Rs. This reconstruction method is found to estimate instantaneous Qp with high accuracy. The annual mean of the daily values of Qp during the period 1958--2005 period is 25.06 mol m-2 d-1. The magnitude of the long-term trend for the annual averaged Qp is presented (-0.19 mol m-2 yr-1 from 1958--1997 and -0.12 mol m-2 yr-1 from 1958--2005). The trend in Qp exhibits sharp decreases in the spring and summer and more gentle decreases in the autumn and winter.
2010, 27(6): 1389-1398.
doi: 10.1007/s00376-010-9181-5
Abstract:
The relationship between dust weather frequency (DWF), which denotes the number of days of dust weather events, over Beijing and the East Asian Monsoon (EAM) was studied using DWF data for Beijing during the period 1951--2006. Results show that, during this period, the blowing-dust weather frequency (BDWF), as well as the indices of East Asian winter monsoon (EAWM) and East Asian summer monsoon (EASM), all decreased considerably, with a t-test confidence level of 99%. The correlation coefficients between the chosen EAWM index and BDWF over Beijing in winter and the following spring were 0.34 and 0.33, respectively, with significance levels of 0.01 and 0.02, respectively. For the chosen EASM index and BDWF, these correlation coefficients were 0.51 and 0.45, respectively, with both at a confidence level exceeding 99.9%. With the linear trends removed, the values (in the same order as above) were 0.14, 0.14, -0.12, and -0.09, all not significant at the 95% confidence level. Clearly, the EAM relates mainly to DWF over long timescales. To a certain extent, the EAM might have some impact on DWF by affecting the associated surface air temperature and precipitation during the corresponding time period in sand-dust source regions at the interannual scale. A stronger (weaker) EAWM might advance (suppress) the occurrence of DWF, and the opposite for the EASM.
The relationship between dust weather frequency (DWF), which denotes the number of days of dust weather events, over Beijing and the East Asian Monsoon (EAM) was studied using DWF data for Beijing during the period 1951--2006. Results show that, during this period, the blowing-dust weather frequency (BDWF), as well as the indices of East Asian winter monsoon (EAWM) and East Asian summer monsoon (EASM), all decreased considerably, with a t-test confidence level of 99%. The correlation coefficients between the chosen EAWM index and BDWF over Beijing in winter and the following spring were 0.34 and 0.33, respectively, with significance levels of 0.01 and 0.02, respectively. For the chosen EASM index and BDWF, these correlation coefficients were 0.51 and 0.45, respectively, with both at a confidence level exceeding 99.9%. With the linear trends removed, the values (in the same order as above) were 0.14, 0.14, -0.12, and -0.09, all not significant at the 95% confidence level. Clearly, the EAM relates mainly to DWF over long timescales. To a certain extent, the EAM might have some impact on DWF by affecting the associated surface air temperature and precipitation during the corresponding time period in sand-dust source regions at the interannual scale. A stronger (weaker) EAWM might advance (suppress) the occurrence of DWF, and the opposite for the EASM.
2010, 27(6): 1399-1414.
doi: 10.1007/s00376-010-9087-2
Abstract:
The characteristics of moisture transport and budget of widespread heavy rain and local heavy rain events in Northeast China are studied using the NCEP--NCAR reanalysis 6-hourly and daily data and daily precipitation data of 200 stations in Northeast China from 1961--2005. The results demonstrate that during periods with widespread heavy rain in Northeast China, the Asian monsoon is very active and the monsoonal northward moisture transport is strengthened significantly. The widespread heavy rainfall obtains enhanced water vapor supply from large regions where the water vapor mainly originates from the Asian monsoon areas, which include the East Asian subtropical monsoon area, the South China Sea, and the southeast and southwest tropical monsoon regions. There are several branches of monsoonal moisture current converging on East China and its coastal areas, where they are strengthened and then continue northward into Northeast China. Thus, the enhanced northward monsoonal moisture transport is the key to the widespread heavy rain in Northeast China. In contrast, local heavy rainfall in Northeast China derives water vapor from limited areas, transported by the westerlies. Local evaporation also plays an important role in the water vapor supply and local recycling process of moisture. In short, the widespread heavy rains of Northeast China are mainly caused by water vapor advection brought by the Asian monsoon, whereas local heavy rainfall is mainly caused by the convergence of the westerly wind field.
The characteristics of moisture transport and budget of widespread heavy rain and local heavy rain events in Northeast China are studied using the NCEP--NCAR reanalysis 6-hourly and daily data and daily precipitation data of 200 stations in Northeast China from 1961--2005. The results demonstrate that during periods with widespread heavy rain in Northeast China, the Asian monsoon is very active and the monsoonal northward moisture transport is strengthened significantly. The widespread heavy rainfall obtains enhanced water vapor supply from large regions where the water vapor mainly originates from the Asian monsoon areas, which include the East Asian subtropical monsoon area, the South China Sea, and the southeast and southwest tropical monsoon regions. There are several branches of monsoonal moisture current converging on East China and its coastal areas, where they are strengthened and then continue northward into Northeast China. Thus, the enhanced northward monsoonal moisture transport is the key to the widespread heavy rain in Northeast China. In contrast, local heavy rainfall in Northeast China derives water vapor from limited areas, transported by the westerlies. Local evaporation also plays an important role in the water vapor supply and local recycling process of moisture. In short, the widespread heavy rains of Northeast China are mainly caused by water vapor advection brought by the Asian monsoon, whereas local heavy rainfall is mainly caused by the convergence of the westerly wind field.
2010, 27(6): 1415-1424.
doi: 10.1007/s00376-010-9213-1
Abstract:
The mesoscale moist adjoint sensitivities related to the initiation of mesoscale convective systems (MCSs) are evaluated for a mei-yu heavy rainfall event. The sensitivities were calculated on a realistic background gained from a four-dimensional variational data assimilation of precipitation experiment to make the sensitivity computation possible and reasonable within a strong moist convective event at the mesoscale. The results show that the computed sensitivities at the mesoscale were capable of capturing the factors affecting MCS initiation. The sensitivities to the initial temperature and moisture are enhanced greatly by diabatic processes, especially at lower levels, and these sensitivities are much larger than those stemming from the horizontal winds, which implies that initiation of MCSs is more sensitive to low-level temperature and moisture perturbations rather than the horizontal winds. Moreover, concentration of sensitivities at low levels reflects the characteristics of the mei-yu front. The results provide some hints about how to improve quantitative precipitation forecasts of mei-yu heavy rainfall, such as by conducting mesoscale targetted observations via the adjoint-based method to reduce the low-level errors in the initial temperature and moisture.
The mesoscale moist adjoint sensitivities related to the initiation of mesoscale convective systems (MCSs) are evaluated for a mei-yu heavy rainfall event. The sensitivities were calculated on a realistic background gained from a four-dimensional variational data assimilation of precipitation experiment to make the sensitivity computation possible and reasonable within a strong moist convective event at the mesoscale. The results show that the computed sensitivities at the mesoscale were capable of capturing the factors affecting MCS initiation. The sensitivities to the initial temperature and moisture are enhanced greatly by diabatic processes, especially at lower levels, and these sensitivities are much larger than those stemming from the horizontal winds, which implies that initiation of MCSs is more sensitive to low-level temperature and moisture perturbations rather than the horizontal winds. Moreover, concentration of sensitivities at low levels reflects the characteristics of the mei-yu front. The results provide some hints about how to improve quantitative precipitation forecasts of mei-yu heavy rainfall, such as by conducting mesoscale targetted observations via the adjoint-based method to reduce the low-level errors in the initial temperature and moisture.
2010, 27(6): 1425-1437.
doi: 10.1007/s00376-009-9153-6
Abstract:
Rank Histograms are suitable tools to assess the quality of ensembles within an ensemble prediction system or framework. By counting the rank of a given variable in the ensemble, we are basically making a sample analysis, which does not allow us to distinguish if the origin of its variability is external noise or comes from chaotic sources. The recently introduced Mean to Variance Logarithmic (MVL) Diagram accounts for the spatial variability, being very sensitive to the spatial localization produced by infinitesimal perturbations of spatiotemporal chaotic systems. By using as a benchmark a simple model subject to noise, we show the distinct information given by Rank Histograms and MVL Diagrams. Hence, the main effects of the external noise can be visualized in a graphic. From the MVL diagram we clearly observe a reduction of the amplitude growth rate and of the spatial localization (chaos suppression), while from the Rank Histogram we observe changes in the reliability of the ensemble. We conclude that in a complex framework including spatiotemporal chaos and noise, both provide a more complete forecasting picture.
Rank Histograms are suitable tools to assess the quality of ensembles within an ensemble prediction system or framework. By counting the rank of a given variable in the ensemble, we are basically making a sample analysis, which does not allow us to distinguish if the origin of its variability is external noise or comes from chaotic sources. The recently introduced Mean to Variance Logarithmic (MVL) Diagram accounts for the spatial variability, being very sensitive to the spatial localization produced by infinitesimal perturbations of spatiotemporal chaotic systems. By using as a benchmark a simple model subject to noise, we show the distinct information given by Rank Histograms and MVL Diagrams. Hence, the main effects of the external noise can be visualized in a graphic. From the MVL diagram we clearly observe a reduction of the amplitude growth rate and of the spatial localization (chaos suppression), while from the Rank Histogram we observe changes in the reliability of the ensemble. We conclude that in a complex framework including spatiotemporal chaos and noise, both provide a more complete forecasting picture.
2010, 27(6): 1438-1452.
doi: 10.1007/s00376-010-9215-z
Abstract:
Understanding changes in land surface processes over the past several decades requires knowledge of trends and interannual variability in surface energy fluxes in response to climate change. In our study, the Community Land Model version 3.5 (CLM3.5), driven by the latest updated hybrid reanalysis-observational surface climate data from Princeton University, is used to obtain global distributions of surface energy fluxes during 1948 to 2000. Based on the climate data and simulation results, long-term trends and interannual variability (IAV) of both climatic variables and surface energy fluxes for this span of 50+ years are derived and analyzed. Regions with strong long-term trends and large IAV for both climatic variables and surface energy fluxes are identified. These analyses reveal seasonal variations in the spatial patterns of climate and surface fluxes; however, spatial patterns in trends and IAV for surface energy fluxes over the past ～50 years do not fully correspond to those for climatic variables, indicating complex responses of land surfaces to changes in the climatic forcings.
Understanding changes in land surface processes over the past several decades requires knowledge of trends and interannual variability in surface energy fluxes in response to climate change. In our study, the Community Land Model version 3.5 (CLM3.5), driven by the latest updated hybrid reanalysis-observational surface climate data from Princeton University, is used to obtain global distributions of surface energy fluxes during 1948 to 2000. Based on the climate data and simulation results, long-term trends and interannual variability (IAV) of both climatic variables and surface energy fluxes for this span of 50+ years are derived and analyzed. Regions with strong long-term trends and large IAV for both climatic variables and surface energy fluxes are identified. These analyses reveal seasonal variations in the spatial patterns of climate and surface fluxes; however, spatial patterns in trends and IAV for surface energy fluxes over the past ～50 years do not fully correspond to those for climatic variables, indicating complex responses of land surfaces to changes in the climatic forcings.
2010, 27(6): 1453-1472.
doi: 10.1007/s00376-010-9178-0
Abstract:
Climate and forecast mode simulations with the regional climate model HIRlam-ECHAM(HIRHAM) are evaluated over a pan-Antarctic domain. The ability of the model to simulate temperature and wind profiles in the troposphere is quantified by comparing its results with radiosonde data acquired from the Davis station for January and July 2007. Compared to the climate mode, the forecast mode was found to deliver improved results for temperature and wind simulations at the near surface and in the lower troposphere. The main remaining model bias found was the under-representation of low-level wind jets. Based on ensemble simulations, it is shown that a distinct internal variability is inherent in the climate mode simulations, and associated areas of reduced predictability over Antarctica are identified.
Climate and forecast mode simulations with the regional climate model HIRlam-ECHAM(HIRHAM) are evaluated over a pan-Antarctic domain. The ability of the model to simulate temperature and wind profiles in the troposphere is quantified by comparing its results with radiosonde data acquired from the Davis station for January and July 2007. Compared to the climate mode, the forecast mode was found to deliver improved results for temperature and wind simulations at the near surface and in the lower troposphere. The main remaining model bias found was the under-representation of low-level wind jets. Based on ensemble simulations, it is shown that a distinct internal variability is inherent in the climate mode simulations, and associated areas of reduced predictability over Antarctica are identified.
AAS Website 
AAS WeChat 