2006 Vol. 23, No. 1
Display Method:
2006, 23(1): 1-13.
doi: 10.1007/s00376-006-0001-x
Abstract:
This paper compares monthly and seasonal rain rates derived from the Version 5 (V5) and Version 6 (V6) TRMM Precipitation Radar (TPR, TSDIS reference 2A25), TRMM Microwave Imager (TMI, 2A12), TRMM Combined Instrument (TCI, 2B31), TRMM calibrated IR rain estimates (3B42) and TRMM merged gauge and satellite analysis (3B43) algorithms over New Mexico (NM) with rain gauge analyses provided by the New Mexico water districts (WD). The average rain rates over the NM region for 1998–2002 are 0.91mmd?1 for WD and 0.75, 1.38, 1.49, 1.27, and 1.07mmd?1 for V5 3B43, 3B42, TMI, PR and TCA; and 0.74, 1.38, 0.87 and 0.97 mm d?1 for V6 3B43, TMI, TPR and TCA, respectively. Comparison of V5 3B43 with WD rain rates and the daily TRMM mission index (TPR and TMI) suggests that the low bias of V5 3B43 for the wet months (summer to early fall) may be due to the non-inclusion of some rain events in the operational gauge analyses that are used in the production of V5 3B43. Correlation analyses show that the WD rain rates vary in phase, with higher correlation between neighboring WDs. High temporal correlations (>0.8) exist between WD and the combined algorithms (3B42, 3B43 and TCA for both V5 and V6) while satellite instrument algorithms (PR, TMI and TCI) are correlated best among themselves at the monthly scale. Paired t-tests of the monthly time series show that V5 3B42 and TMI are statistically different from the WD rain rates while no significant difference exists between WD and the other products. The agreements between the TRMM satellite and WD gauge estimates are best for the spring and fall and worst for winter and summer. The reduction in V6 TMI (?7.4%) and TPR (?31%) rain rates (compared to V5) results in better agreement between WD estimates and TMI in winter and TPR during summer.
This paper compares monthly and seasonal rain rates derived from the Version 5 (V5) and Version 6 (V6) TRMM Precipitation Radar (TPR, TSDIS reference 2A25), TRMM Microwave Imager (TMI, 2A12), TRMM Combined Instrument (TCI, 2B31), TRMM calibrated IR rain estimates (3B42) and TRMM merged gauge and satellite analysis (3B43) algorithms over New Mexico (NM) with rain gauge analyses provided by the New Mexico water districts (WD). The average rain rates over the NM region for 1998–2002 are 0.91mmd?1 for WD and 0.75, 1.38, 1.49, 1.27, and 1.07mmd?1 for V5 3B43, 3B42, TMI, PR and TCA; and 0.74, 1.38, 0.87 and 0.97 mm d?1 for V6 3B43, TMI, TPR and TCA, respectively. Comparison of V5 3B43 with WD rain rates and the daily TRMM mission index (TPR and TMI) suggests that the low bias of V5 3B43 for the wet months (summer to early fall) may be due to the non-inclusion of some rain events in the operational gauge analyses that are used in the production of V5 3B43. Correlation analyses show that the WD rain rates vary in phase, with higher correlation between neighboring WDs. High temporal correlations (>0.8) exist between WD and the combined algorithms (3B42, 3B43 and TCA for both V5 and V6) while satellite instrument algorithms (PR, TMI and TCI) are correlated best among themselves at the monthly scale. Paired t-tests of the monthly time series show that V5 3B42 and TMI are statistically different from the WD rain rates while no significant difference exists between WD and the other products. The agreements between the TRMM satellite and WD gauge estimates are best for the spring and fall and worst for winter and summer. The reduction in V6 TMI (?7.4%) and TPR (?31%) rain rates (compared to V5) results in better agreement between WD estimates and TMI in winter and TPR during summer.
2006, 23(1): 14-22.
doi: 10.1007/s00376-006-0002-9
Abstract:
The effects of storm-induced sea surface temperature (SST) cooling on hurricane intensity are investigated using a 5-day cloud-resolving simulation of Hurricane Bonnie (1998). Two sensitivity simulations are performed in which the storm-induced cooling is either ignored or shifted close to the modeled storm track. Results show marked sensitivity of the model-simulated storm intensity to the magnitude and relative position with respect to the hurricane track. It is shown that incorporation of the storm-induced cooling, with an average value of 1.3C, causes a 25-hPa weakening of the hurricane, which is about 20 hPa per 1C change in SST. Shifting the SST cooling close to the storm track generates the weakest storm, accounting for about 47% reduction in the storm intensity. It is found that the storm intensity changes are well correlated with the air-sea temperature difference. The results have important implications for the use of coupled hurricane-ocean models for numerical prediction of tropical cyclones.
The effects of storm-induced sea surface temperature (SST) cooling on hurricane intensity are investigated using a 5-day cloud-resolving simulation of Hurricane Bonnie (1998). Two sensitivity simulations are performed in which the storm-induced cooling is either ignored or shifted close to the modeled storm track. Results show marked sensitivity of the model-simulated storm intensity to the magnitude and relative position with respect to the hurricane track. It is shown that incorporation of the storm-induced cooling, with an average value of 1.3C, causes a 25-hPa weakening of the hurricane, which is about 20 hPa per 1C change in SST. Shifting the SST cooling close to the storm track generates the weakest storm, accounting for about 47% reduction in the storm intensity. It is found that the storm intensity changes are well correlated with the air-sea temperature difference. The results have important implications for the use of coupled hurricane-ocean models for numerical prediction of tropical cyclones.
2006, 23(1): 23-32.
doi: 10.1007/s00376-006-0003-8
Abstract:
In this study, the temporal structure of the variation of North Atlantic Oscillation (NAO) and its impact on regional climate variability are analyzed using various datasets. The results show that blocking formations in the Atlantic region are sensitive to the phase of the NAO. Sixty-seven percent more winter blocking days are observed during the negative phase compared to the positive phase of the NAO. The average length of blocking during the negative phase is about 11 days, which is nearly twice as long as the 6-day length observed during the positive phase of the NAO. The NAO-related differences in blocking frequency and persistence are associated with changes in the distribution of the surface air temperature anomaly, which, to a large extent, is determined by the phase of the NAO. The distribution of regional cloud amount is also sensitive to the phase of the NAO. For the negative phase, the cloud amounts are significant, positive anomalies in the convective zone in the Tropics and much less cloudiness in the mid latitudes. But for the positive phase of the NAO, the cloud amount is much higher in the mid-latitude storm track region. In the whole Atlantic region, the cloud amount shows a decrease with the increase of surface air temperature. These results suggest that there may be a negative feedback between the cloud amount and the surface air temperature in the Atlantic region.
In this study, the temporal structure of the variation of North Atlantic Oscillation (NAO) and its impact on regional climate variability are analyzed using various datasets. The results show that blocking formations in the Atlantic region are sensitive to the phase of the NAO. Sixty-seven percent more winter blocking days are observed during the negative phase compared to the positive phase of the NAO. The average length of blocking during the negative phase is about 11 days, which is nearly twice as long as the 6-day length observed during the positive phase of the NAO. The NAO-related differences in blocking frequency and persistence are associated with changes in the distribution of the surface air temperature anomaly, which, to a large extent, is determined by the phase of the NAO. The distribution of regional cloud amount is also sensitive to the phase of the NAO. For the negative phase, the cloud amounts are significant, positive anomalies in the convective zone in the Tropics and much less cloudiness in the mid latitudes. But for the positive phase of the NAO, the cloud amount is much higher in the mid-latitude storm track region. In the whole Atlantic region, the cloud amount shows a decrease with the increase of surface air temperature. These results suggest that there may be a negative feedback between the cloud amount and the surface air temperature in the Atlantic region.
2006, 23(1): 33-44.
doi: 10.1007/s00376-006-0004-7
Abstract:
In atmospheric data assimilation systems, the forecast error covariance model is an important component. However, the parameters required by a forecast error covariance model are difficult to obtain due to the absence of the truth. This study applies an error statistics estimation method to the Physical-space Statistical Analysis System (PSAS) height-wind forecast error covariance model. This method consists of two components: the first component computes the error statistics by using the National Meteorological Center (NMC) method, which is a lagged-forecast difference approach, within the framework of the PSAS height-wind forecast error covariance model; the second obtains a calibration formula to rescale the error standard deviations provided by the NMC method. The calibration is against the error statistics estimated by using a maximum-likelihood estimation (MLE) with rawindsonde height observed-minus-forecast residuals. A complete set of formulas for estimating the error statistics and for the calibration is applied to a one-month-long dataset generated by a general circulation model of the Global Model and Assimilation Office (GMAO), NASA. There is a clear constant relationship between the error statistics estimates of the NMC-method and MLE. The final product provides a full set of 6-hour error statistics required by the PSAS height-wind forecast error covariance model over the globe. The features of these error statistics are examined and discussed.
In atmospheric data assimilation systems, the forecast error covariance model is an important component. However, the parameters required by a forecast error covariance model are difficult to obtain due to the absence of the truth. This study applies an error statistics estimation method to the Physical-space Statistical Analysis System (PSAS) height-wind forecast error covariance model. This method consists of two components: the first component computes the error statistics by using the National Meteorological Center (NMC) method, which is a lagged-forecast difference approach, within the framework of the PSAS height-wind forecast error covariance model; the second obtains a calibration formula to rescale the error standard deviations provided by the NMC method. The calibration is against the error statistics estimated by using a maximum-likelihood estimation (MLE) with rawindsonde height observed-minus-forecast residuals. A complete set of formulas for estimating the error statistics and for the calibration is applied to a one-month-long dataset generated by a general circulation model of the Global Model and Assimilation Office (GMAO), NASA. There is a clear constant relationship between the error statistics estimates of the NMC-method and MLE. The final product provides a full set of 6-hour error statistics required by the PSAS height-wind forecast error covariance model over the globe. The features of these error statistics are examined and discussed.
2006, 23(1): 45-53.
doi: 10.1007/s00376-006-0005-6
Abstract:
The role of halted “baroclinic modes” in the central equatorial Pacific is analyzed. It is found that dominant anomaly signals corresponding to “baroclinic modes” occur in the upper layer of the equatorial Pacific, in a two-and-a-half layer oceanic model, in assimilated results of a simple OGCM and in the ADCP observation of TAO. A second “baroclinic mode” is halted in the central equatorial Pacific corresponding to a positive SST anomaly while the first “baroclinic mode” propagates eastwards in the eastern equatorial Pacific. The role of the halted second “baroclinic mode” in the central equatorial Pacific is explained by a staged ocean-atmosphere interaction mechanism in the formation of El Ni?no: the westerly bursts in boreal winter over the western equatorial Pacific generate the halted second “baroclinic mode” in the central equatorial Pacific, leading to the increase of heat content and temperature in the upper layer of the central Pacific which induces the shift of convection from over the western equatorial Pacific to the central equatorial Pacific; another wider, westerly anomaly burst is induced over the western region of convection above the central equatorial Pacific and the westerly anomaly burst generates the first “baroclinic mode” propagating to the eastern equatorial Pacific, resulting in a warm event in the eastern equatorial Pacific. The mechanism presented in this paper reveals that the central equatorial Pacific is a key region in detecting the possibility of ENSO and, by analyzing TAO observation data of ocean currents and temperature in the central equatorial Pacific, in predicting the coming of an El Ni?no several months ahead.
The role of halted “baroclinic modes” in the central equatorial Pacific is analyzed. It is found that dominant anomaly signals corresponding to “baroclinic modes” occur in the upper layer of the equatorial Pacific, in a two-and-a-half layer oceanic model, in assimilated results of a simple OGCM and in the ADCP observation of TAO. A second “baroclinic mode” is halted in the central equatorial Pacific corresponding to a positive SST anomaly while the first “baroclinic mode” propagates eastwards in the eastern equatorial Pacific. The role of the halted second “baroclinic mode” in the central equatorial Pacific is explained by a staged ocean-atmosphere interaction mechanism in the formation of El Ni?no: the westerly bursts in boreal winter over the western equatorial Pacific generate the halted second “baroclinic mode” in the central equatorial Pacific, leading to the increase of heat content and temperature in the upper layer of the central Pacific which induces the shift of convection from over the western equatorial Pacific to the central equatorial Pacific; another wider, westerly anomaly burst is induced over the western region of convection above the central equatorial Pacific and the westerly anomaly burst generates the first “baroclinic mode” propagating to the eastern equatorial Pacific, resulting in a warm event in the eastern equatorial Pacific. The mechanism presented in this paper reveals that the central equatorial Pacific is a key region in detecting the possibility of ENSO and, by analyzing TAO observation data of ocean currents and temperature in the central equatorial Pacific, in predicting the coming of an El Ni?no several months ahead.
2006, 23(1): 54-60.
doi: 10.1007/s00376-006-0006-5
Abstract:
There are a number of sources of uncertainty in regional climate change scenarios. When statistical downscaling is used to obtain regional climate change scenarios, the uncertainty may originate from the uncertainties in the global climate models used, the skill of the statistical model, and the forcing scenarios applied to the global climate model. The uncertainty associated with global climate models can be evaluated by examining the differences in the predictors and in the downscaled climate change scenarios based on a set of different global climate models. When standardized global climate model simulations such as the second phase of the Coupled Model Intercomparison Project (CMIP2) are used, the difference in the downscaled variables mainly reflects differences in the climate models and the natural variability in the simulated climates. It is proposed that the spread of the estimates can be taken as a measure of the uncertainty associated with global climate models. The proposed method is applied to the estimation of global-climate-model-related uncertainty in regional precipitation change scenarios in Sweden. Results from statistical downscaling based on 17 global climate models show that there is an overall increase in annual precipitation all over Sweden although a considerable spread of the changes in the precipitation exists. The general increase can be attributed to the increased large-scale precipitation and the enhanced westerly wind. The estimated uncertainty is nearly independent of region. However, there is a seasonal dependence. The estimates for winter show the highest level of confidence, while the estimates for summer show the least.
There are a number of sources of uncertainty in regional climate change scenarios. When statistical downscaling is used to obtain regional climate change scenarios, the uncertainty may originate from the uncertainties in the global climate models used, the skill of the statistical model, and the forcing scenarios applied to the global climate model. The uncertainty associated with global climate models can be evaluated by examining the differences in the predictors and in the downscaled climate change scenarios based on a set of different global climate models. When standardized global climate model simulations such as the second phase of the Coupled Model Intercomparison Project (CMIP2) are used, the difference in the downscaled variables mainly reflects differences in the climate models and the natural variability in the simulated climates. It is proposed that the spread of the estimates can be taken as a measure of the uncertainty associated with global climate models. The proposed method is applied to the estimation of global-climate-model-related uncertainty in regional precipitation change scenarios in Sweden. Results from statistical downscaling based on 17 global climate models show that there is an overall increase in annual precipitation all over Sweden although a considerable spread of the changes in the precipitation exists. The general increase can be attributed to the increased large-scale precipitation and the enhanced westerly wind. The estimated uncertainty is nearly independent of region. However, there is a seasonal dependence. The estimates for winter show the highest level of confidence, while the estimates for summer show the least.
2006, 23(1): 61-68.
doi: 10.1007/s00376-006-0007-4
Abstract:
This paper provides a concise description of the philosophy, mathematics, and algorithms for estimating, detecting, and attributing climate changes. The estimation follows the spectral method by using empirical orthogonal functions, also called the method of reduced space optimal averaging. The detection follows the linear regression method, which can be found in most textbooks about multivariate statistical techniques. The detection algorithms are described by using the space-time approach to avoid the non-stationarity problem. The paper includes (1) the optimal averaging method for minimizing the uncertainties of the global change estimate, (2) the weighted least square detection of both single and multiple signals, (3) numerical examples, and (4) the limitations of the linear optimal averaging and detection methods.
This paper provides a concise description of the philosophy, mathematics, and algorithms for estimating, detecting, and attributing climate changes. The estimation follows the spectral method by using empirical orthogonal functions, also called the method of reduced space optimal averaging. The detection follows the linear regression method, which can be found in most textbooks about multivariate statistical techniques. The detection algorithms are described by using the space-time approach to avoid the non-stationarity problem. The paper includes (1) the optimal averaging method for minimizing the uncertainties of the global change estimate, (2) the weighted least square detection of both single and multiple signals, (3) numerical examples, and (4) the limitations of the linear optimal averaging and detection methods.
2006, 23(1): 69-79.
doi: 10.1007/s00376-006-0008-3
Abstract:
The Moderate Resolution Imaging Spectroradiometer (MODIS) is one of the key instruments for NASA’s Earth Observing System (EOS), currently operating on both the Terra and Aqua satellites. The MODIS is a major advance over the previous generation of sensors in terms of its spectral, spatial, and temporal resolutions. It has 36 spectral bands: 20 reflective solar bands (RSB) with center wavelengths from 0.41 to 2.1 μm and 16 thermal emissive bands (TEB) with center wavelengths from 3.7 to 14.4 μm, making observations at three spatial resolutions: 250 m (bands 1–2), 500 m (bands 3–7), and 1km (bands 8-36). MODIS is a cross-track scanning radiometer with a wide field-of-view, providing a complete global coverage of the Earth in less than 2 days. Both Terra and Aqua MODIS went through extensive pre-launch calibration and characterization at various levels. In orbit, the calibration and characterization tasks are performed using its on-board calibrators (OBCs) that include a solar diffuser (SD) and a solar diffuser stability monitor (SDSM), a v-grooved flat panel blackbody (BB), and a spectro-radiometric calibration assembly (SRCA). In this paper, we present an overview of MODIS calibration and characterization activities, methodologies, and lessons learned from pre-launch characterization and in-orbit operation. Key issues discussed in this paper include in-orbit efforts of monitoring the noise characteristics of the detectors, tracking the solar diffuser and optics degradations, and updating the sensor’s response versus scan angle. The experiences and lessons learned through MODIS have played and will continue to play major roles in the design and characterization of future sensors.
The Moderate Resolution Imaging Spectroradiometer (MODIS) is one of the key instruments for NASA’s Earth Observing System (EOS), currently operating on both the Terra and Aqua satellites. The MODIS is a major advance over the previous generation of sensors in terms of its spectral, spatial, and temporal resolutions. It has 36 spectral bands: 20 reflective solar bands (RSB) with center wavelengths from 0.41 to 2.1 μm and 16 thermal emissive bands (TEB) with center wavelengths from 3.7 to 14.4 μm, making observations at three spatial resolutions: 250 m (bands 1–2), 500 m (bands 3–7), and 1km (bands 8-36). MODIS is a cross-track scanning radiometer with a wide field-of-view, providing a complete global coverage of the Earth in less than 2 days. Both Terra and Aqua MODIS went through extensive pre-launch calibration and characterization at various levels. In orbit, the calibration and characterization tasks are performed using its on-board calibrators (OBCs) that include a solar diffuser (SD) and a solar diffuser stability monitor (SDSM), a v-grooved flat panel blackbody (BB), and a spectro-radiometric calibration assembly (SRCA). In this paper, we present an overview of MODIS calibration and characterization activities, methodologies, and lessons learned from pre-launch characterization and in-orbit operation. Key issues discussed in this paper include in-orbit efforts of monitoring the noise characteristics of the detectors, tracking the solar diffuser and optics degradations, and updating the sensor’s response versus scan angle. The experiences and lessons learned through MODIS have played and will continue to play major roles in the design and characterization of future sensors.
2006, 23(1): 80-90.
doi: 10.1007/s00376-006-0009-2
Abstract:
Sensor calibration, including its definition, purpose, traceability options, methodology, complexity, and importance, is examined in this paper in the context of supporting NOAA’s satellite mission. Common understanding of sensor calibration is essential for the effective communication among sensor vendors, calibration scientists, satellite operators, program managers, and remote sensing data users, who must cooperate to ensure that a nation’s strategic investment in a sophisticated operational environmental satellite system serves the nation’s interest and enhances the human lives around the world. Examples of calibration activities at NOAA/NESDIS/ORA are selected to further illustrate these concepts and to demonstrate the lessons learned from the past experience.
Sensor calibration, including its definition, purpose, traceability options, methodology, complexity, and importance, is examined in this paper in the context of supporting NOAA’s satellite mission. Common understanding of sensor calibration is essential for the effective communication among sensor vendors, calibration scientists, satellite operators, program managers, and remote sensing data users, who must cooperate to ensure that a nation’s strategic investment in a sophisticated operational environmental satellite system serves the nation’s interest and enhances the human lives around the world. Examples of calibration activities at NOAA/NESDIS/ORA are selected to further illustrate these concepts and to demonstrate the lessons learned from the past experience.
2006, 23(1): 91-105.
doi: 10.1007/s00376-006-0010-9
Abstract:
This paper describes explicit and parameterized simulations of midsummer precipitation over the continental United States for two distinct episodes: moderate large-scale forcing and weak forcing. The objective is to demonstrate the capability of explicit convection at currently affordable grid-resolution and compare it with parameterized realizations. Under moderate forcing, 3-km grid-resolution explicit simulations represent rainfall coherence remarkably well. The observed daily convective generation near the Continental Divide and the subsequent organization and propagation are reproduced qualitatively. The propagation speed, zonal extent and duration of the rainfall streaks compare favorably with their observed counterparts, although the streak frequency is underestimated. The simulations at 10-km grid-resolution applying conventional convective parameterization schemes also replicate reasonably well the diurnal convective regeneration in moderate forcing. The performance of the 3-km grid-resolution model demonstrates the potential of 1-km-resolution explicit cloud-resolving models for the prediction of warm season precipitation for moderately forced environments. In weak forcing conditions, however, predictions of precipitation coherence and diurnal variability are much poorer. This suggests that an even finer resolution explicit model is required to adequately treat convective initiation and upscale organization typical of the warm season over the continental U.S.
This paper describes explicit and parameterized simulations of midsummer precipitation over the continental United States for two distinct episodes: moderate large-scale forcing and weak forcing. The objective is to demonstrate the capability of explicit convection at currently affordable grid-resolution and compare it with parameterized realizations. Under moderate forcing, 3-km grid-resolution explicit simulations represent rainfall coherence remarkably well. The observed daily convective generation near the Continental Divide and the subsequent organization and propagation are reproduced qualitatively. The propagation speed, zonal extent and duration of the rainfall streaks compare favorably with their observed counterparts, although the streak frequency is underestimated. The simulations at 10-km grid-resolution applying conventional convective parameterization schemes also replicate reasonably well the diurnal convective regeneration in moderate forcing. The performance of the 3-km grid-resolution model demonstrates the potential of 1-km-resolution explicit cloud-resolving models for the prediction of warm season precipitation for moderately forced environments. In weak forcing conditions, however, predictions of precipitation coherence and diurnal variability are much poorer. This suggests that an even finer resolution explicit model is required to adequately treat convective initiation and upscale organization typical of the warm season over the continental U.S.
2006, 23(1): 106-117.
doi: 10.1007/s00376-006-0011-8
Abstract:
It is well known that retrieval of parameters is usually ill-posed and highly nonlinear, so parameter retrieval problems are very difficult. There are still many important theoretical issues under research, although great success has been achieved in data assimilation in meteorology and oceanography. This paper reviews the recent research on parameter retrieval, especially that of the authors. First, some concepts and issues of parameter retrieval are introduced and the state-of-the-art parameter retrieval technology in meteorology and oceanography is reviewed briefly, and then atmospheric and oceanic parameters are retrieved using the variational data assimilation method combined with the regularization techniques in four examples: retrieval of the vertical eddy diffusion coefficient; of the turbulivity of the atmospheric boundary layer; of wind from Doppler radar data, and of the physical process parameters. Model parameter retrieval with global and local observations is also introduced.
It is well known that retrieval of parameters is usually ill-posed and highly nonlinear, so parameter retrieval problems are very difficult. There are still many important theoretical issues under research, although great success has been achieved in data assimilation in meteorology and oceanography. This paper reviews the recent research on parameter retrieval, especially that of the authors. First, some concepts and issues of parameter retrieval are introduced and the state-of-the-art parameter retrieval technology in meteorology and oceanography is reviewed briefly, and then atmospheric and oceanic parameters are retrieved using the variational data assimilation method combined with the regularization techniques in four examples: retrieval of the vertical eddy diffusion coefficient; of the turbulivity of the atmospheric boundary layer; of wind from Doppler radar data, and of the physical process parameters. Model parameter retrieval with global and local observations is also introduced.
2006, 23(1): 118-126.
doi: 10.1007/s00376-006-0012-7
Abstract:
In the first paper in this series, a variational data assimilation of ideal tropical cyclone (TC) tracks was performed for the statistical-dynamical prediction model SD–90 by the adjoint method, and a prediction of TC tracks was made with good accuracy for tracks containing no sharp turns. In the present paper, the cases of real TC tracks are studied. Due to the complexity of TC motion, attention is paid to the diagnostic research of TC motion. First, five TC tracks are studied. Using the data of each entire TC track, by the adjoint method, five TC tracks are fitted well, and the forces acting on the TCs are retrieved. For a given TC, the distribution of the resultant of the retrieved force and Coriolis force well matches the corresponding TC track, i.e., when a TC turns, the resultant of the retrieved force and Coriolis force acts as a centripetal force, which means that the TC indeed moves like a particle; in particular, for TC 9911, the clockwise looping motion is also fitted well. And the distribution of the resultant appears to be periodic in some cases. Then, the present method is carried out for a portion of the track data for TC 9804, which indicates that when the amount of data for a TC track is sufficient, the algorithm is stable. And finally, the same algorithm is implemented for TCs with a double-eyewall structure, namely Bilis (2000) and Winnie (1997), and the results prove the applicability of the algorithm to TCs with complicated mesoscale structures if the TC track data are obtained every three hours.
In the first paper in this series, a variational data assimilation of ideal tropical cyclone (TC) tracks was performed for the statistical-dynamical prediction model SD–90 by the adjoint method, and a prediction of TC tracks was made with good accuracy for tracks containing no sharp turns. In the present paper, the cases of real TC tracks are studied. Due to the complexity of TC motion, attention is paid to the diagnostic research of TC motion. First, five TC tracks are studied. Using the data of each entire TC track, by the adjoint method, five TC tracks are fitted well, and the forces acting on the TCs are retrieved. For a given TC, the distribution of the resultant of the retrieved force and Coriolis force well matches the corresponding TC track, i.e., when a TC turns, the resultant of the retrieved force and Coriolis force acts as a centripetal force, which means that the TC indeed moves like a particle; in particular, for TC 9911, the clockwise looping motion is also fitted well. And the distribution of the resultant appears to be periodic in some cases. Then, the present method is carried out for a portion of the track data for TC 9804, which indicates that when the amount of data for a TC track is sufficient, the algorithm is stable. And finally, the same algorithm is implemented for TCs with a double-eyewall structure, namely Bilis (2000) and Winnie (1997), and the results prove the applicability of the algorithm to TCs with complicated mesoscale structures if the TC track data are obtained every three hours.
2006, 23(1): 127-140.
doi: 10.1007/s00376-006-0013-6
Abstract:
This paper investigates the hydrological interactions in the atmosphere-evegetation-soil system by using the bucket model and several new simplified intermediately complex models. The results of mathematical analysis and numerical simulations show that these models, despite their simplicity, can very clearly reveal the essential features of the rather complex hydrological system of atmosphere-ecosystem-soil. For given atmospheric variables, these models clearly demonstrate multiple timescales, the “red shift” of response spectra, multi-equilibria and limit cycles, bifurcation, abrupt change, self-organization, recovery, “desertification”, and chaos. Most of these agree with observations. Especially, the weakening of “shading effect” of living canopy and the wilted biomass might be a major mechanism leading to the desertification in a relatively short period due to overgrazing, and the desertification in a relatively long period or in climate of change might be due to both Charney’s mechanism and the shading effect. These ideas could be validated with further numerical simulations. In the paper, some methods for improving the estimation of timescales in the soil water evolution responding to the forcing are also proposed.
This paper investigates the hydrological interactions in the atmosphere-evegetation-soil system by using the bucket model and several new simplified intermediately complex models. The results of mathematical analysis and numerical simulations show that these models, despite their simplicity, can very clearly reveal the essential features of the rather complex hydrological system of atmosphere-ecosystem-soil. For given atmospheric variables, these models clearly demonstrate multiple timescales, the “red shift” of response spectra, multi-equilibria and limit cycles, bifurcation, abrupt change, self-organization, recovery, “desertification”, and chaos. Most of these agree with observations. Especially, the weakening of “shading effect” of living canopy and the wilted biomass might be a major mechanism leading to the desertification in a relatively short period due to overgrazing, and the desertification in a relatively long period or in climate of change might be due to both Charney’s mechanism and the shading effect. These ideas could be validated with further numerical simulations. In the paper, some methods for improving the estimation of timescales in the soil water evolution responding to the forcing are also proposed.
2006, 23(1): 141-148.
doi: 10.1007/s00376-006-0014-5
Abstract:
An ideal and simple formulation is successfully derived that well represents a quasi-linear relationship found between the domain-averaged water vapor, Q (mm), and temperature, T (K), fields for the three tropical oceans (i.e., the Pacific, Atlantic and Indian Oceans) based on eleven GEOS-3 [Goddard Earth Observing System (EOS) Version-3] global re-analysis monthly products. A Q ? T distribution analysis is also performed for the tropical and extra-tropical regions based on in-situ sounding data and numerical simulations [GEOS-3 and the Goddard Cumulus Ensemble (GCE) model]. A similar positively correlated Q ? T distribution is found over the entire oceanic and tropical regions; however, Q increases faster with T for the former region. It is suspected that the tropical oceans may possess a moister boundary layer than the Tropics. The oceanic regime falls within the lower bound of the tropical regime embedded in a global, curvilinear Q ? T relationship. A positive correlation is also found between T and sea surface temperature (SST); however, for one degree of increase in T, SST is found to increase 1.1 degrees for a warmer ocean, which is slightly less than an increase of 1.25 degrees for a colder ocean. This seemingly indicates that more (less) heat is needed for an open ocean to maintain an air mass above it with a same degree of temperature rise during a colder (warmer) season [or in a colder (warmer) region]. Q and SST are also found to be positively correlated. Relative humidity (RH) exhibits similar behaviors for oceanic and tropical regions. RH increases with increasing SST and T over oceans, while it increases with increasing T in the Tropics. RH, however, decreases with increasing temperature in the extratropics. It is suspected that the tropical and oceanic regions may possess a moister local boundary layer than the extratropics so that a faster moisture increase than a saturated moisture increase is favored for the former regions. T,Q, saturated water vapor, RH, and SST are also examined with regard to the warm and cold “seasons” over individual oceans. The Indian Ocean warm season dominates in each of the five quantities, while the Atlantic Ocean cold season has the lowest values in most categories. The higher values for the Indian Ocean may be due to its relatively high percentage of tropical coverage compared to the other two oceans. However, Q is found to increase faster for colder months from individual oceans, which differs from the general finding in the global Q?T relationship that Q increases slower for a colder climate. The modified relationship may be attributed to a possible seasonal (warm and cold) variability in boundary layer depth over oceans, or to the small sample size used in each individual oceanic group.
An ideal and simple formulation is successfully derived that well represents a quasi-linear relationship found between the domain-averaged water vapor, Q (mm), and temperature, T (K), fields for the three tropical oceans (i.e., the Pacific, Atlantic and Indian Oceans) based on eleven GEOS-3 [Goddard Earth Observing System (EOS) Version-3] global re-analysis monthly products. A Q ? T distribution analysis is also performed for the tropical and extra-tropical regions based on in-situ sounding data and numerical simulations [GEOS-3 and the Goddard Cumulus Ensemble (GCE) model]. A similar positively correlated Q ? T distribution is found over the entire oceanic and tropical regions; however, Q increases faster with T for the former region. It is suspected that the tropical oceans may possess a moister boundary layer than the Tropics. The oceanic regime falls within the lower bound of the tropical regime embedded in a global, curvilinear Q ? T relationship. A positive correlation is also found between T and sea surface temperature (SST); however, for one degree of increase in T, SST is found to increase 1.1 degrees for a warmer ocean, which is slightly less than an increase of 1.25 degrees for a colder ocean. This seemingly indicates that more (less) heat is needed for an open ocean to maintain an air mass above it with a same degree of temperature rise during a colder (warmer) season [or in a colder (warmer) region]. Q and SST are also found to be positively correlated. Relative humidity (RH) exhibits similar behaviors for oceanic and tropical regions. RH increases with increasing SST and T over oceans, while it increases with increasing T in the Tropics. RH, however, decreases with increasing temperature in the extratropics. It is suspected that the tropical and oceanic regions may possess a moister local boundary layer than the extratropics so that a faster moisture increase than a saturated moisture increase is favored for the former regions. T,Q, saturated water vapor, RH, and SST are also examined with regard to the warm and cold “seasons” over individual oceans. The Indian Ocean warm season dominates in each of the five quantities, while the Atlantic Ocean cold season has the lowest values in most categories. The higher values for the Indian Ocean may be due to its relatively high percentage of tropical coverage compared to the other two oceans. However, Q is found to increase faster for colder months from individual oceans, which differs from the general finding in the global Q?T relationship that Q increases slower for a colder climate. The modified relationship may be attributed to a possible seasonal (warm and cold) variability in boundary layer depth over oceans, or to the small sample size used in each individual oceanic group.
2006, 23(1): 149-155.
doi: 10.1007/s00376-006-0015-4
Abstract:
The variability of the summer rainfall over China is analyzed using the EOF procedure with a new parameter (namely, mode station variance percentage) based on 1951-2000 summer rainfall data from 160 stations in China. Compared with mode variance friction, the mode station variance percentage not only reveals more localized characteristics of the variability of the summer rainfall, but also helps to distinguish the regions with a high degree of dominant EOF modes representing the analyzed observational variable. The atmospheric circulation diagnostic studies with the NCEP/NCAR reanalysis daily data from 1966 to 2000 show that in summer, abundant (scarce) rainfall in the belt-area from the upper-middle reaches of the Yangtze River northeastward to the Huaihe River basin is linked to strong (weak) heat sources over the eastern Tibetan Plateau, while the abundant (scarce) rainfall in the area to the south of the middle-lower reaches of the Yangtze River is closely linked to the weak (strong) heat sources over the tropical western Pacific.
The variability of the summer rainfall over China is analyzed using the EOF procedure with a new parameter (namely, mode station variance percentage) based on 1951-2000 summer rainfall data from 160 stations in China. Compared with mode variance friction, the mode station variance percentage not only reveals more localized characteristics of the variability of the summer rainfall, but also helps to distinguish the regions with a high degree of dominant EOF modes representing the analyzed observational variable. The atmospheric circulation diagnostic studies with the NCEP/NCAR reanalysis daily data from 1966 to 2000 show that in summer, abundant (scarce) rainfall in the belt-area from the upper-middle reaches of the Yangtze River northeastward to the Huaihe River basin is linked to strong (weak) heat sources over the eastern Tibetan Plateau, while the abundant (scarce) rainfall in the area to the south of the middle-lower reaches of the Yangtze River is closely linked to the weak (strong) heat sources over the tropical western Pacific.
2006, 23(1): 156-164.
doi: 10.1007/s00376-006-0016-3
Abstract:
Based on instability theory and some former studies, the Simple Ocean Data Assimilation (SODA) data are analyzed to further study the difference between the propagation of the ENSO-related oceanic anomaly in the off-equatorial North Pacific Ocean before and after 1976. The investigation shows that after 1976 in the off-equatorial North Pacific Ocean, there is a larger area where the necessary conditions for baroclinic and/or barotropic instability are satisfied, which may help oceanic anomaly signals propagating in the form of Rossby waves to absorb energy from the mean currents so that they can grow and intensify. The baroclinic energy conversion rate in the North Pacific after 1976 is much higher than before 1976, which indicates that the baroclinic instability has intensified since 1976. From another perspective, the instability analysis gives an explanation of the phenomena that the ENSO-related oceanic anomaly signal in the North Pacific has intensified since 1976.
Based on instability theory and some former studies, the Simple Ocean Data Assimilation (SODA) data are analyzed to further study the difference between the propagation of the ENSO-related oceanic anomaly in the off-equatorial North Pacific Ocean before and after 1976. The investigation shows that after 1976 in the off-equatorial North Pacific Ocean, there is a larger area where the necessary conditions for baroclinic and/or barotropic instability are satisfied, which may help oceanic anomaly signals propagating in the form of Rossby waves to absorb energy from the mean currents so that they can grow and intensify. The baroclinic energy conversion rate in the North Pacific after 1976 is much higher than before 1976, which indicates that the baroclinic instability has intensified since 1976. From another perspective, the instability analysis gives an explanation of the phenomena that the ENSO-related oceanic anomaly signal in the North Pacific has intensified since 1976.
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