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- Author or Editor: Hui Wan x
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Abstract
The idealized test case proposed by Held and Suarez is carried out with the atmospheric general circulation model ECHAM5 of the Max Planck Institute for Meteorology. The aim is to investigate the sensitivity of the solutions of the spectral dynamical core to spatial and temporal resolution, and to evaluate the numerical convergence of the solutions. Low-frequency fluctuations at time scales as long as thousands of days are found in ultralong integrations. To distinguish the effect of changed resolution from the fluctuations caused by the internal variability, the ensemble method is employed in experiments at resolutions ranging from T31 to T159 with 16 to 81 vertical levels. Significance of the differences between ensembles is assessed by three different statistical tests. Convergence property of the numerical solution is concisely summarized by a ratio index.
Results show that the simulated climate state in the Held–Suarez test is sensitive to spatial resolution. Increase of horizontal resolution leads to slight weakening and poleward shift of the westerly jets. Significant warming is detected in high latitudes, especially near the polar tropopause, while the tropical tropopause becomes cooler. The baroclinic wave activity intensifies considerably with increased horizontal resolution. Higher vertical resolution also leads to stronger eddy variances and cooling near the tropical tropopause, but equatorward shift of the westerly jets. The solutions show an indication of convergence at T85L31 resolution according to all the three statistical tests applied. Differences between integrations with various time steps are judged to be within the noise level induced by the inherent low-frequency variability.
Abstract
The idealized test case proposed by Held and Suarez is carried out with the atmospheric general circulation model ECHAM5 of the Max Planck Institute for Meteorology. The aim is to investigate the sensitivity of the solutions of the spectral dynamical core to spatial and temporal resolution, and to evaluate the numerical convergence of the solutions. Low-frequency fluctuations at time scales as long as thousands of days are found in ultralong integrations. To distinguish the effect of changed resolution from the fluctuations caused by the internal variability, the ensemble method is employed in experiments at resolutions ranging from T31 to T159 with 16 to 81 vertical levels. Significance of the differences between ensembles is assessed by three different statistical tests. Convergence property of the numerical solution is concisely summarized by a ratio index.
Results show that the simulated climate state in the Held–Suarez test is sensitive to spatial resolution. Increase of horizontal resolution leads to slight weakening and poleward shift of the westerly jets. Significant warming is detected in high latitudes, especially near the polar tropopause, while the tropical tropopause becomes cooler. The baroclinic wave activity intensifies considerably with increased horizontal resolution. Higher vertical resolution also leads to stronger eddy variances and cooling near the tropical tropopause, but equatorward shift of the westerly jets. The solutions show an indication of convergence at T85L31 resolution according to all the three statistical tests applied. Differences between integrations with various time steps are judged to be within the noise level induced by the inherent low-frequency variability.
Abstract
Based on a newly developed daily precipitation dataset of 740 stations in China and more robust trend detection techniques, trends in annual and seasonal total precipitation and in extreme daily precipitation, defined as those larger than its 95th percentile for the year, summer, and winter half years, have been assessed for the period 1951–2000. Possible links between changes in total precipitation and frequency of extremes have also been explored. The results indicate that there is little trend in total precipitation for China as a whole, but there are distinctive regional and seasonal patterns of trends. Annual total precipitation has significantly decreased over southern northeast China, north China, and over the Sichuan Basin but significantly increased in western China, the Yangtze River valley, and the southeastern coast. In western China, precipitation increase has been observed for both cold and warm seasons. However, trends differ from one season to another in eastern China. Spring precipitation has increased in southern northeast China and north China but decreased significantly in the midreach of the Yangzte River. The summer precipitation trend is very similar to that of annual totals. Autumn precipitation has generally decreased throughout eastern China. In winter, precipitation has significantly decreased over the northern part of eastern China but increased in the south. The number of rain days has significantly decreased throughout most parts of China with northwest China being an exception. Meanwhile, precipitation intensity has significantly increased. This suggests that the precipitation increase in western China is due to the increase in both precipitation frequency and intensity. In eastern China, the impact of reduced number of rain days seems to be more dominant in the north while the influence of enhanced intensity prevails in the south. Over regions with increasing precipitation trends, there have been much higher than normal frequency of precipitation extreme events. For example, significant increases in extreme precipitation have been found in western China, in the mid–lower reaches of the Yangtze River, and in parts of the southwest and south China coastal area. A significant decrease in extremes is observed in north China and the Sichuan Basin. Trends in the number of extremes and total precipitation from nonextreme events are generally in phase. An exception is southwest China where an increase of extreme events is associated with a decrease in total nonextreme precipitation.
Abstract
Based on a newly developed daily precipitation dataset of 740 stations in China and more robust trend detection techniques, trends in annual and seasonal total precipitation and in extreme daily precipitation, defined as those larger than its 95th percentile for the year, summer, and winter half years, have been assessed for the period 1951–2000. Possible links between changes in total precipitation and frequency of extremes have also been explored. The results indicate that there is little trend in total precipitation for China as a whole, but there are distinctive regional and seasonal patterns of trends. Annual total precipitation has significantly decreased over southern northeast China, north China, and over the Sichuan Basin but significantly increased in western China, the Yangtze River valley, and the southeastern coast. In western China, precipitation increase has been observed for both cold and warm seasons. However, trends differ from one season to another in eastern China. Spring precipitation has increased in southern northeast China and north China but decreased significantly in the midreach of the Yangzte River. The summer precipitation trend is very similar to that of annual totals. Autumn precipitation has generally decreased throughout eastern China. In winter, precipitation has significantly decreased over the northern part of eastern China but increased in the south. The number of rain days has significantly decreased throughout most parts of China with northwest China being an exception. Meanwhile, precipitation intensity has significantly increased. This suggests that the precipitation increase in western China is due to the increase in both precipitation frequency and intensity. In eastern China, the impact of reduced number of rain days seems to be more dominant in the north while the influence of enhanced intensity prevails in the south. Over regions with increasing precipitation trends, there have been much higher than normal frequency of precipitation extreme events. For example, significant increases in extreme precipitation have been found in western China, in the mid–lower reaches of the Yangtze River, and in parts of the southwest and south China coastal area. A significant decrease in extremes is observed in north China and the Sichuan Basin. Trends in the number of extremes and total precipitation from nonextreme events are generally in phase. An exception is southwest China where an increase of extreme events is associated with a decrease in total nonextreme precipitation.
Abstract
Stochastic parameterizations are used in numerical weather prediction and climate modeling to help capture the uncertainty in the simulations and improve their statistical properties. Convergence issues can arise when time integration methods originally developed for deterministic differential equations are applied naively to stochastic problems. In previous studies, it has been demonstrated that a correction term, known in stochastic analysis as the Itô correction, can help improve solution accuracy for various deterministic numerical schemes and ensure convergence to the physically relevant solution without substantial computational overhead. The usual formulation of the Itô correction is valid only when the stochasticity is represented by white noise. In this study, a generalized formulation of the Itô correction is derived for noises of any color. The formulation is applied to a test problem described by an advection–diffusion equation forced with a spectrum of fast processes. We present numerical results for cases with both constant and spatially varying advection velocities to show that, for the same time step sizes, the introduction of the generalized Itô correction helps to substantially reduce time integration error and significantly improve the convergence rate of the numerical solutions when the forcing term in the governing equation is rough (fast varying); alternatively, for the same target accuracy, the generalized Itô correction allows for the use of significantly longer time steps and, hence, helps to reduce the computational cost of the numerical simulation.
Abstract
Stochastic parameterizations are used in numerical weather prediction and climate modeling to help capture the uncertainty in the simulations and improve their statistical properties. Convergence issues can arise when time integration methods originally developed for deterministic differential equations are applied naively to stochastic problems. In previous studies, it has been demonstrated that a correction term, known in stochastic analysis as the Itô correction, can help improve solution accuracy for various deterministic numerical schemes and ensure convergence to the physically relevant solution without substantial computational overhead. The usual formulation of the Itô correction is valid only when the stochasticity is represented by white noise. In this study, a generalized formulation of the Itô correction is derived for noises of any color. The formulation is applied to a test problem described by an advection–diffusion equation forced with a spectrum of fast processes. We present numerical results for cases with both constant and spatially varying advection velocities to show that, for the same time step sizes, the introduction of the generalized Itô correction helps to substantially reduce time integration error and significantly improve the convergence rate of the numerical solutions when the forcing term in the governing equation is rough (fast varying); alternatively, for the same target accuracy, the generalized Itô correction allows for the use of significantly longer time steps and, hence, helps to reduce the computational cost of the numerical simulation.
Abstract
In this study a comprehensive quality assurance (QA) system, which includes the hydrostatic check combined with a statistical homogeneity test, is designed and applied to hourly pressure records (for 1953–2002) from 761 Canadian stations, to produce a high-quality database of hourly station and sea level pressures for various climate studies. The main principles of the QA system are described in detail, followed by a brief emphasis on the error correction algorithms. The general performance of the QA system and the main problems in the Canadian historical hourly pressure database are discussed and illustrated through various examples. The results show that there are serious systematic errors (i.e., sudden changes in the mean, or mean shifts) in the Canadian hourly pressure database, which are caused either by the use of incorrect station elevation values in the reduction of barometer readings to station or sea level pressure values (e.g., the “50-ft rule” or station relocation without updates to the station elevation), by transposing/swapping station and sea level pressure values, or by mistakes made in the archive data ingestion or data recording/digitization processes (e.g., use of a wrong base number). Random errors also exist and are mainly due to the transposition of two digits or miscoding of one or two digits. These errors must be corrected before the data are used in various climate studies, especially climate change–related studies.
Abstract
In this study a comprehensive quality assurance (QA) system, which includes the hydrostatic check combined with a statistical homogeneity test, is designed and applied to hourly pressure records (for 1953–2002) from 761 Canadian stations, to produce a high-quality database of hourly station and sea level pressures for various climate studies. The main principles of the QA system are described in detail, followed by a brief emphasis on the error correction algorithms. The general performance of the QA system and the main problems in the Canadian historical hourly pressure database are discussed and illustrated through various examples. The results show that there are serious systematic errors (i.e., sudden changes in the mean, or mean shifts) in the Canadian hourly pressure database, which are caused either by the use of incorrect station elevation values in the reduction of barometer readings to station or sea level pressure values (e.g., the “50-ft rule” or station relocation without updates to the station elevation), by transposing/swapping station and sea level pressure values, or by mistakes made in the archive data ingestion or data recording/digitization processes (e.g., use of a wrong base number). Random errors also exist and are mainly due to the transposition of two digits or miscoding of one or two digits. These errors must be corrected before the data are used in various climate studies, especially climate change–related studies.
Abstract
Near-surface wind speeds recorded at 117 stations in Canada for the period from 1953 to 2006 were analyzed in this study. First, metadata and a logarithmic wind profile were used to adjust hourly wind speeds measured at nonstandard anemometer heights to the standard 10-m level. Monthly mean near-surface wind speed series were then derived and subjected to a statistical homogeneity test, with homogeneous monthly mean geostrophic wind (geowind) speed series being used as reference series. Homogenized monthly mean near-surface wind speed series were obtained by adjusting all significant mean shifts, using the results of the statistical test and modeling along with all available metadata, and were used to assess the long-term trends.
This study shows that station relocation and anemometer height change are the main causes for discontinuities in the near-surface wind speed series, followed by instrumentation problems or changes, and observing environment changes. It also shows that the effects of artificial mean shifts on the results of trend analysis are remarkable, and that the homogenized near-surface wind speed series show good spatial consistency of trends, which are in agreement with long-term trends estimated from independent datasets, such as surface winds in the United States and cyclone activity indices and ocean wave heights in the region. These indicate success in the homogenization of the wind data. During the period analyzed, the homogenized near-surface wind speed series show significant decreases throughout western Canada and most parts of southern Canada (except the Maritimes) in all seasons, with significant increases in the central Canadian Arctic in all seasons and in the Maritimes in spring and autumn.
Abstract
Near-surface wind speeds recorded at 117 stations in Canada for the period from 1953 to 2006 were analyzed in this study. First, metadata and a logarithmic wind profile were used to adjust hourly wind speeds measured at nonstandard anemometer heights to the standard 10-m level. Monthly mean near-surface wind speed series were then derived and subjected to a statistical homogeneity test, with homogeneous monthly mean geostrophic wind (geowind) speed series being used as reference series. Homogenized monthly mean near-surface wind speed series were obtained by adjusting all significant mean shifts, using the results of the statistical test and modeling along with all available metadata, and were used to assess the long-term trends.
This study shows that station relocation and anemometer height change are the main causes for discontinuities in the near-surface wind speed series, followed by instrumentation problems or changes, and observing environment changes. It also shows that the effects of artificial mean shifts on the results of trend analysis are remarkable, and that the homogenized near-surface wind speed series show good spatial consistency of trends, which are in agreement with long-term trends estimated from independent datasets, such as surface winds in the United States and cyclone activity indices and ocean wave heights in the region. These indicate success in the homogenization of the wind data. During the period analyzed, the homogenized near-surface wind speed series show significant decreases throughout western Canada and most parts of southern Canada (except the Maritimes) in all seasons, with significant increases in the central Canadian Arctic in all seasons and in the Maritimes in spring and autumn.
Abstract
This paper improves an extreme-value-theory-based detection and attribution method and then applies it to four types of extreme temperatures, annual minimum daily minimum (TNn) and maximum (TXn) and annual maximum daily minimum (TNx) and maximum (TXx), using the HadEX2 observation and the CMIP5 multimodel simulation datasets of the period 1951–2010 at 17 subcontinent regions. The methodology is an analog of the fingerprinting method adapted to extremes using the generalized extreme value (GEV) distribution. The signals are estimated as the time-dependent location parameters of GEV distributions fitted to extremes simulated by multimodel ensembles under anthropogenic (ANT), natural (NAT), or combined anthropogenic and natural (ALL) external forcings. The observed extremes are modeled by GEV distributions whose location parameters incorporate the signals as covariates. A coordinate descent algorithm improves both computational efficiency and accuracy in comparison to the existing method, facilitating detection of multiple signals simultaneously. An overall goodness-of-fit test was performed at the regional level. The ANT signal was separated from the NAT signal in four to six regions. In these analyses, the waiting times of the 1951–55 20-yr return level in the 2006–10 climate for the temperature of the coldest night and day were found to have increased to over 20 yr; the corresponding waiting times for the warmest night and day were found to have dropped below 20 yr in a majority of the regions.
Abstract
This paper improves an extreme-value-theory-based detection and attribution method and then applies it to four types of extreme temperatures, annual minimum daily minimum (TNn) and maximum (TXn) and annual maximum daily minimum (TNx) and maximum (TXx), using the HadEX2 observation and the CMIP5 multimodel simulation datasets of the period 1951–2010 at 17 subcontinent regions. The methodology is an analog of the fingerprinting method adapted to extremes using the generalized extreme value (GEV) distribution. The signals are estimated as the time-dependent location parameters of GEV distributions fitted to extremes simulated by multimodel ensembles under anthropogenic (ANT), natural (NAT), or combined anthropogenic and natural (ALL) external forcings. The observed extremes are modeled by GEV distributions whose location parameters incorporate the signals as covariates. A coordinate descent algorithm improves both computational efficiency and accuracy in comparison to the existing method, facilitating detection of multiple signals simultaneously. An overall goodness-of-fit test was performed at the regional level. The ANT signal was separated from the NAT signal in four to six regions. In these analyses, the waiting times of the 1951–55 20-yr return level in the 2006–10 climate for the temperature of the coldest night and day were found to have increased to over 20 yr; the corresponding waiting times for the warmest night and day were found to have dropped below 20 yr in a majority of the regions.
Abstract
Convective afternoon rainfall (CAR) events, which tend to generate a local rainfall typically in the afternoon, are among the most frequently observed local weather patterns over Southeast Asia during summer. Using satellite precipitation estimations as an observational base for model evaluation, this study examines the applicability of 10 global climate models provided by phase 6 of the Coupled Model Intercomparison Project (CMIP6) in simulating the CAR activities over Southeast Asia. Analyses also focus on exploring the characteristics and maintenance mechanisms of related projections of CAR activities in the future. Our analyses of the historical simulation indicate that EC-Earth3 and EC-Earth3-Veg are the two best models for simulating CAR activities (including amount, frequency, and intensity) over Southeast Asia. Analyses also demonstrate that EC-Earth3 and EC-Earth3-Veg outperform their earlier version (i.e., EC-Earth) in CMIP5 owing to the improvement in its spatial resolution in CMIP6. For future projections, our examinations of the differences in CAR activities between the future (2071–2100, under the SSP858 run) and the present (1985–2014, under the historical run) indicate that CAR events will become fewer but more intense over most land areas of Southeast Asia. Possible causes of the projected increase (decrease) in CAR intensity (frequency) are attributed to the projected increase (decrease) in the local atmospheric humidity (sea breeze convergence and daytime thermal instability). These findings provide insight into how the local weather/climate over Southeast Asia is likely to change under global warming.
Abstract
Convective afternoon rainfall (CAR) events, which tend to generate a local rainfall typically in the afternoon, are among the most frequently observed local weather patterns over Southeast Asia during summer. Using satellite precipitation estimations as an observational base for model evaluation, this study examines the applicability of 10 global climate models provided by phase 6 of the Coupled Model Intercomparison Project (CMIP6) in simulating the CAR activities over Southeast Asia. Analyses also focus on exploring the characteristics and maintenance mechanisms of related projections of CAR activities in the future. Our analyses of the historical simulation indicate that EC-Earth3 and EC-Earth3-Veg are the two best models for simulating CAR activities (including amount, frequency, and intensity) over Southeast Asia. Analyses also demonstrate that EC-Earth3 and EC-Earth3-Veg outperform their earlier version (i.e., EC-Earth) in CMIP5 owing to the improvement in its spatial resolution in CMIP6. For future projections, our examinations of the differences in CAR activities between the future (2071–2100, under the SSP858 run) and the present (1985–2014, under the historical run) indicate that CAR events will become fewer but more intense over most land areas of Southeast Asia. Possible causes of the projected increase (decrease) in CAR intensity (frequency) are attributed to the projected increase (decrease) in the local atmospheric humidity (sea breeze convergence and daytime thermal instability). These findings provide insight into how the local weather/climate over Southeast Asia is likely to change under global warming.
Abstract
The annual-mean position errors (PE) of tropical cyclone (TC) track forecasts from three forecast agencies [WMO Regional Specialized Meteorological Center in Tokyo (RSMC-Tokyo), China Meteorological Administration (CMA), and Joint Typhoon Warning Center of the United States (JTWC)] are analyzed to document the past improvements and project future tendency in track forecast accuracy for TCs in the western North Pacific. An improvement of 48 h (2 days) in lead time has been achieved in the past 30 years, but with noticeable stepwise periods of improvements with superposed short-term fluctuations. The stepwise improvement features differ among the three forecast agencies, but are highly related to the development of objective forecast guidance and the application strategy. As demonstrated by an exponential model for the growth of PEs with lead time for TCs of tropical storm category and above, the improvements in the past 10 years have mainly been due to the reduction in analysis errors rather than the reduction in the error growth rate. If the current trend continues, a further 2-day improvement in TC track forecast lead times may be projected for the coming 15 years up to 2035, and we certainly have not reached yet the limit of TC track predictability in the western North Pacific.
Abstract
The annual-mean position errors (PE) of tropical cyclone (TC) track forecasts from three forecast agencies [WMO Regional Specialized Meteorological Center in Tokyo (RSMC-Tokyo), China Meteorological Administration (CMA), and Joint Typhoon Warning Center of the United States (JTWC)] are analyzed to document the past improvements and project future tendency in track forecast accuracy for TCs in the western North Pacific. An improvement of 48 h (2 days) in lead time has been achieved in the past 30 years, but with noticeable stepwise periods of improvements with superposed short-term fluctuations. The stepwise improvement features differ among the three forecast agencies, but are highly related to the development of objective forecast guidance and the application strategy. As demonstrated by an exponential model for the growth of PEs with lead time for TCs of tropical storm category and above, the improvements in the past 10 years have mainly been due to the reduction in analysis errors rather than the reduction in the error growth rate. If the current trend continues, a further 2-day improvement in TC track forecast lead times may be projected for the coming 15 years up to 2035, and we certainly have not reached yet the limit of TC track predictability in the western North Pacific.
