Shouquan Cheng - Academia.edu (original) (raw)
Papers by Shouquan Cheng
Http Dx Doi Org 10 1175 2011jcli3764 1, Jul 1, 2011
ABSTRACT
J Appl Meteorol Climatol, 2010
ABSTRACT
Paddy and Water Environment, Aug 28, 2009
In this study, an automated synoptic weather typing was employed to identity the weather types mo... more In this study, an automated synoptic weather typing was employed to identity the weather types most likely associated with daily typhoon/typhoon-related heavy rainfall events for Chiayi, Taiwan. The synoptic weather typing was developed using principal components analysis, an average linkage clustering procedure, and discriminant function analysis. The classification results showed that the synoptic weather typing was successful at identifying typhoon-related weather types. Five synoptic weather types (Weather Types 1-5) were identified over the past 11-year period as the primary typhoon-related weather types. These five typhoon-related weather types can capture 34 out of 36 total typhoon-related heavy rainfall days ([50 mm/d) and all nine cases with typhoon-related daily rainfall [200 mm during the period March 1998-December 2008. This result suggests that synoptic weather typing can be useful to identify historical typhoon/typhoon-related heavy rainfall events. Moreover, the method has potential to assess climate change impacts on the frequency/intensity of future typhoon/typhoon-related heavy rainfall events using future downscaled GCM climate data.
Climatic Change, 2012
Synoptic weather typing and regression-based downscaling approaches have become popular in evalua... more Synoptic weather typing and regression-based downscaling approaches have become popular in evaluating the impacts of climate change on a variety of environmental problems, particularly those involving extreme impacts. One of the reasons for the popularity of these approaches is their ability to categorize a complex set of meteorological variables into a coherent index, facilitating the projection of changes in frequency and intensity of future daily extreme weather events and/or their impacts. This paper illustrated the capability of the synoptic weather typing and regression methods to analyze climatic change impacts on a number of extreme weather events and environmental problems for south-central Canada, such as freezing rain, heavy rainfall, high-/low-streamflow events, air pollution, and human health. These statistical approaches are helpful in analyzing extreme events and projecting their impacts into the future through three major steps or analysis procedures: (1) historical simulation modeling to identify extreme weather events or their impacts, (2) statistical downscaling to provide station-scale future hourly/daily climate data, and (3) projecting changes in the frequency and intensity of future extreme weather events and their impacts under a changing climate. To realize these steps, it is first necessary to conceptualize the modeling of the meteorology, hydrology and impacts model variables of significance and to apply a number of linear/nonlinear regression techniques. Because the climate/weather validation process is critical, a formal model result verification process has been built into each of these three steps. With carefully chosen physically consistent and relevant variables, the results of the verification, based on historical observations of the outcome variables simulated by the models, show a very good agreement in all applications and extremes tested to date. Overall, the modeled results from climate change studies indicate that the frequency and intensity of future extreme weather events and their impacts are generally projected to significantly increase late this century
... TO ASSESS CLIMATE CHANGE IMPACTS ON METEOROLOGICAL AND HYDROLOGICAL RISKS AT LOCAL SCALE IN S... more ... TO ASSESS CLIMATE CHANGE IMPACTS ON METEOROLOGICAL AND HYDROLOGICAL RISKS AT LOCAL SCALE IN SOUTH-CENTRAL CANADA CHAD SHOUQUAN CHENG ... 12. CS Cheng, M. Campbell, Q. Li, G. Li, H. Auld, N. Day, D. Pengelly, S. Gingrich and D. Yap, A ...
The synoptic weather typing approach has become popular in evaluating the impacts of climate chan... more The synoptic weather typing approach has become popular in evaluating the impacts of climate change on a variety of environmental problems. One of the reasons is its ability to categorize a complex set of meteorological variables as a coherent index, which can facilitate analyses of local climate change impacts. The weather typing method has been successfully applied in Environment Canada
Atmospheric and Climate Sciences, 2012
The paper forms the second part of an introduction to possible impacts of climate change on daily... more The paper forms the second part of an introduction to possible impacts of climate change on daily streamflow and extremes in the Province of Ontario, Canada. Daily streamflow simulation models developed in the companion paper (Part I) were used to project changes in frequency of future daily streamflow events. To achieve this goal, future climate information (including rainfall) at a local scale is needed. A regression-based downscaling method was employed to downscale eight global climate model (GCM) simulations (scenarios A2 and B1) to selected weather stations for various meteorological variables (except rainfall). Future daily rainfall quantities were projected using daily rainfall simulation models with downscaled future climate information. Following these projections, future daily streamflow volumes can be projected by applying daily streamflow simulation models.The frequency of future daily high-streamflow events in the warm season (May-November) was projected to increase by about 45% -55% late this century from the current condition, on average of eight-GCM A2 projections and four selected river basins. The corresponding increases for future daily low-streamflow events and future daily mean streamflow volume could be about 25% -90% and 10% -20%, respectively. In addition, the return values of annual one-day maximum streamflow volume for various return periods were projected to increase by 20% -40%, 20% -50%, and 30% -80%, respectively for the periods 2001-50, 2026-75, and 2051-2100. Inter-GCM and interscenario uncertainties of future streamflow projections were quantitatively assessed. On average, the projected percentage increases in frequency of future daily high-streamflow events are about 1.4 -2.2 times greater than inter-GCM and interscenario uncertainties.
Journal of Water Resource and Protection, 2012
The objective of this paper was to project possible impacts of climate change on heavy rainfall-r... more The objective of this paper was to project possible impacts of climate change on heavy rainfall-related water damage insurance claims and incurred losses for four selected cites (Kitchener-Waterloo, London, Ottawa, and Toronto) located at Ontario, Canada. To achieve this goal, the future climate change scenarios and rainfall simulations, at local scale, were needed. A statistical downscaling method was used to downscale five global climate model (GCM) scenarios to selected weather stations. The downscaled meteorological variables included surface and upper-air hourly temperature, dew point, west-east and south-north winds, air pressure, and total cloud cover. These variables are necessary to project future daily rainfall quantities using within-weather-type rainfall simulation models. A model result verification process has been built into the whole exercise, including rainfall simulation modeling and the development of downscaling transfer functions. The results of the verification, based on historical observations of the outcome variables simulated by the models, showed a very good agreement. To effectively evaluate heavy rainfall-related water damage insurance claims and incurred losses, a rainfall index was developed considering rainfall intensity and duration. The index was evaluated to link with insurance data as to determination of a critical threshold of the rainfall index for triggering high numbers of rainfall-related water damage insurance claims and incurred losses. The relationship between rainfall index and insurance data was used with future rainfall simulations to project changes in future heavy rainfall-related sewer flood risks in terms of water damage insurance claims and incurred losses. The modeled results showed that, averaged over the five GCM scenarios and across the study area, both the monthly total number of rainfall-related water damage claims and incurred losses could increase by about 13%, 20% and 30% for the periods 2016-2035, 2046-2065, and 2081-2100, respectively (from the four-city seasonal average of 12 ± 1.7 thousand claims and 88±88 ± 88±21 million during April-September 1992. Within the context of this study, increases in the future number of insurance claims and incurred losses in the study area are driven by only increases in future heavy rainfall events.
Paddy and Water Environment, 2009
In this study, an automated synoptic weather typing was employed to identity the weather types mo... more In this study, an automated synoptic weather typing was employed to identity the weather types most likely associated with daily typhoon/typhoon-related heavy rainfall events for Chiayi, Taiwan. The synoptic weather typing was developed using principal components analysis, an average linkage clustering procedure, and discriminant function analysis. The classification results showed that the synoptic weather typing was successful at identifying typhoon-related weather types. Five synoptic weather types (Weather Types 1-5) were identified over the past 11-year period as the primary typhoon-related weather types. These five typhoon-related weather types can capture 34 out of 36 total typhoon-related heavy rainfall days ([50 mm/d) and all nine cases with typhoon-related daily rainfall [200 mm during the period March 1998-December 2008. This result suggests that synoptic weather typing can be useful to identify historical typhoon/typhoon-related heavy rainfall events. Moreover, the method has potential to assess climate change impacts on the frequency/intensity of future typhoon/typhoon-related heavy rainfall events using future downscaled GCM climate data.
Atmosphere-Ocean, 2014
ABSTRACT
The overarching purpose of this study was to project changes in the occurrence frequency and magn... more The overarching purpose of this study was to project changes in the occurrence frequency and magnitude of future wind gust events under downscaled future climate conditions over Ontario, Canada. Wind gust factors were employed to simulate hourly/daily wind gust based on hourly/daily wind speed. Regression-based downscaling methods were used to downscale future hourly/daily wind speed to each of the 14
Water, Air, and Soil Pollution, 2007
Automated synoptic weather typing and robust orthogonal stepwise regression analysis (via princip... more Automated synoptic weather typing and robust orthogonal stepwise regression analysis (via principal components analysis) were applied together to develop within-weather-type air pollution prediction models for a variety of pollutants (specifically, carbon monoxide -CO, nitrogen dioxide -NO 2 , ozone -O 3 , sulphur dioxide -SO 2 , and suspended particles -SP) for the period 1974-2000 in south-central Canada. The SAS robust regression procedure was used to limit the influence of outliers on air pollution prediction algorithms. Six-hourly Environment Canada surface observed meteorological data and 6-hourly US National Centers for Environmental Prediction (NCEP) reanalysis data of various weather elements were used in the analysis. The models were developed using twothirds of the total years for meteorological and air pollution data; the remaining one-third (randomly selected) was used for model validation. Robust stepwise regression analysis was performed to analytically determine the meteorological variables that might be used to predict air pollution concentrations. There was a significant correlation between observed daily mean air pollution concentrations and model predictions. About 20, 50, and 80% of the 80 prediction models across the study area possessed R 2 values ≥ 0.7, 0.6, and 0.5, respectively. The results of model validation were similar to those of model development, with slightly smaller model R 2 values.
Journal of Climate, 2012
ABSTRACT
Journal of Climate, 2011
... The current study employs the synoptic weather typing and a number of linear and nonlinear re... more ... The current study employs the synoptic weather typing and a number of linear and nonlinear regression techniques to downscale future daily rainfall from large-scale GCM simulations to the ... The downscaling scheme is built upon the previous studies (ie, Cheng et al. ...
Journal of Climate, 2014
ABSTRACT
Journal of Applied Meteorology and Climatology, 2010
ABSTRACT
Climatic Change, 2012
Synoptic weather typing and regression-based downscaling approaches have become popular in evalua... more Synoptic weather typing and regression-based downscaling approaches have become popular in evaluating the impacts of climate change on a variety of environmental problems, particularly those involving extreme impacts. One of the reasons for the popularity of these approaches is their ability to categorize a complex set of meteorological variables into a coherent index, facilitating the projection of changes in frequency and intensity of future daily extreme weather events and/or their impacts. This paper illustrated the capability of the synoptic weather typing and regression methods to analyze climatic change impacts on a number of extreme weather events and environmental problems for south-central Canada, such as freezing rain, heavy rainfall, high-/low-streamflow events, air pollution, and human health. These statistical approaches are helpful in analyzing extreme events and projecting their impacts into the future through three major steps or analysis procedures: (1) historical simulation modeling to identify extreme weather events or their impacts, (2) statistical downscaling to provide station-scale future hourly/daily climate data, and (3) projecting changes in the frequency and intensity of future extreme weather events and their impacts under a changing climate. To realize these steps, it is first necessary to conceptualize the modeling of the meteorology, hydrology and impacts model variables of significance and to apply a number of linear/nonlinear regression techniques. Because the climate/weather validation process is critical, a formal model result verification process has been built into each of these three steps. With carefully chosen physically consistent and relevant variables, the results of the verification, based on historical observations of the outcome variables simulated by the models, show a very good agreement in all applications and extremes tested to date. Overall, the modeled results from climate change studies indicate that the frequency and intensity of future extreme weather events and their impacts are generally projected to significantly increase late this century
Climate Research, 1997
This paper discusses the application of a year-round synoptic classification procedure to define ... more This paper discusses the application of a year-round synoptic classification procedure to define climatolog~cal seasons based upon the frequency occuiience of seasonal air masses The classification is developed through air inass 'seed day identification and discriminant function analysis, and assigns each day to 1 of 18 ail mass types for each of 14 stations along the East Coast of the United States Unlike the 'astronomical definitlon of seasons, which divides a year into 4 equal p e i~o d s , the length of wlnter ranges fiom about 1'4 mo in Mlami, Florida to more than 4 mo in Portland, hdaine as determined by air mass frequencies The suminer extends more than 5 mo in Flonda, whlle it only lasts 3 mo in Maine In the mld-Atlantic region, there ale 2 longer seasons (summer and wlntei, about 4 mo edch) and 2 shorter seasons (spnny and fall, about 2 mo each) The seasonal definitlon proposed here more closely corresponds to phenological responses than do t r a d~t~o n a l def~nitions The lnforination can be applied to numerous environmentdl assessment problems, including animal demographics and habitat distnbutions, plant phenology and subsequent pollen release, m~gration and hibernation patterns, human health and psychological iesponses to climate, and agncultural p l a n n~n g activities
Http Dx Doi Org 10 1175 2011jcli3764 1, Jul 1, 2011
ABSTRACT
J Appl Meteorol Climatol, 2010
ABSTRACT
Paddy and Water Environment, Aug 28, 2009
In this study, an automated synoptic weather typing was employed to identity the weather types mo... more In this study, an automated synoptic weather typing was employed to identity the weather types most likely associated with daily typhoon/typhoon-related heavy rainfall events for Chiayi, Taiwan. The synoptic weather typing was developed using principal components analysis, an average linkage clustering procedure, and discriminant function analysis. The classification results showed that the synoptic weather typing was successful at identifying typhoon-related weather types. Five synoptic weather types (Weather Types 1-5) were identified over the past 11-year period as the primary typhoon-related weather types. These five typhoon-related weather types can capture 34 out of 36 total typhoon-related heavy rainfall days ([50 mm/d) and all nine cases with typhoon-related daily rainfall [200 mm during the period March 1998-December 2008. This result suggests that synoptic weather typing can be useful to identify historical typhoon/typhoon-related heavy rainfall events. Moreover, the method has potential to assess climate change impacts on the frequency/intensity of future typhoon/typhoon-related heavy rainfall events using future downscaled GCM climate data.
Climatic Change, 2012
Synoptic weather typing and regression-based downscaling approaches have become popular in evalua... more Synoptic weather typing and regression-based downscaling approaches have become popular in evaluating the impacts of climate change on a variety of environmental problems, particularly those involving extreme impacts. One of the reasons for the popularity of these approaches is their ability to categorize a complex set of meteorological variables into a coherent index, facilitating the projection of changes in frequency and intensity of future daily extreme weather events and/or their impacts. This paper illustrated the capability of the synoptic weather typing and regression methods to analyze climatic change impacts on a number of extreme weather events and environmental problems for south-central Canada, such as freezing rain, heavy rainfall, high-/low-streamflow events, air pollution, and human health. These statistical approaches are helpful in analyzing extreme events and projecting their impacts into the future through three major steps or analysis procedures: (1) historical simulation modeling to identify extreme weather events or their impacts, (2) statistical downscaling to provide station-scale future hourly/daily climate data, and (3) projecting changes in the frequency and intensity of future extreme weather events and their impacts under a changing climate. To realize these steps, it is first necessary to conceptualize the modeling of the meteorology, hydrology and impacts model variables of significance and to apply a number of linear/nonlinear regression techniques. Because the climate/weather validation process is critical, a formal model result verification process has been built into each of these three steps. With carefully chosen physically consistent and relevant variables, the results of the verification, based on historical observations of the outcome variables simulated by the models, show a very good agreement in all applications and extremes tested to date. Overall, the modeled results from climate change studies indicate that the frequency and intensity of future extreme weather events and their impacts are generally projected to significantly increase late this century
... TO ASSESS CLIMATE CHANGE IMPACTS ON METEOROLOGICAL AND HYDROLOGICAL RISKS AT LOCAL SCALE IN S... more ... TO ASSESS CLIMATE CHANGE IMPACTS ON METEOROLOGICAL AND HYDROLOGICAL RISKS AT LOCAL SCALE IN SOUTH-CENTRAL CANADA CHAD SHOUQUAN CHENG ... 12. CS Cheng, M. Campbell, Q. Li, G. Li, H. Auld, N. Day, D. Pengelly, S. Gingrich and D. Yap, A ...
The synoptic weather typing approach has become popular in evaluating the impacts of climate chan... more The synoptic weather typing approach has become popular in evaluating the impacts of climate change on a variety of environmental problems. One of the reasons is its ability to categorize a complex set of meteorological variables as a coherent index, which can facilitate analyses of local climate change impacts. The weather typing method has been successfully applied in Environment Canada
Atmospheric and Climate Sciences, 2012
The paper forms the second part of an introduction to possible impacts of climate change on daily... more The paper forms the second part of an introduction to possible impacts of climate change on daily streamflow and extremes in the Province of Ontario, Canada. Daily streamflow simulation models developed in the companion paper (Part I) were used to project changes in frequency of future daily streamflow events. To achieve this goal, future climate information (including rainfall) at a local scale is needed. A regression-based downscaling method was employed to downscale eight global climate model (GCM) simulations (scenarios A2 and B1) to selected weather stations for various meteorological variables (except rainfall). Future daily rainfall quantities were projected using daily rainfall simulation models with downscaled future climate information. Following these projections, future daily streamflow volumes can be projected by applying daily streamflow simulation models.The frequency of future daily high-streamflow events in the warm season (May-November) was projected to increase by about 45% -55% late this century from the current condition, on average of eight-GCM A2 projections and four selected river basins. The corresponding increases for future daily low-streamflow events and future daily mean streamflow volume could be about 25% -90% and 10% -20%, respectively. In addition, the return values of annual one-day maximum streamflow volume for various return periods were projected to increase by 20% -40%, 20% -50%, and 30% -80%, respectively for the periods 2001-50, 2026-75, and 2051-2100. Inter-GCM and interscenario uncertainties of future streamflow projections were quantitatively assessed. On average, the projected percentage increases in frequency of future daily high-streamflow events are about 1.4 -2.2 times greater than inter-GCM and interscenario uncertainties.
Journal of Water Resource and Protection, 2012
The objective of this paper was to project possible impacts of climate change on heavy rainfall-r... more The objective of this paper was to project possible impacts of climate change on heavy rainfall-related water damage insurance claims and incurred losses for four selected cites (Kitchener-Waterloo, London, Ottawa, and Toronto) located at Ontario, Canada. To achieve this goal, the future climate change scenarios and rainfall simulations, at local scale, were needed. A statistical downscaling method was used to downscale five global climate model (GCM) scenarios to selected weather stations. The downscaled meteorological variables included surface and upper-air hourly temperature, dew point, west-east and south-north winds, air pressure, and total cloud cover. These variables are necessary to project future daily rainfall quantities using within-weather-type rainfall simulation models. A model result verification process has been built into the whole exercise, including rainfall simulation modeling and the development of downscaling transfer functions. The results of the verification, based on historical observations of the outcome variables simulated by the models, showed a very good agreement. To effectively evaluate heavy rainfall-related water damage insurance claims and incurred losses, a rainfall index was developed considering rainfall intensity and duration. The index was evaluated to link with insurance data as to determination of a critical threshold of the rainfall index for triggering high numbers of rainfall-related water damage insurance claims and incurred losses. The relationship between rainfall index and insurance data was used with future rainfall simulations to project changes in future heavy rainfall-related sewer flood risks in terms of water damage insurance claims and incurred losses. The modeled results showed that, averaged over the five GCM scenarios and across the study area, both the monthly total number of rainfall-related water damage claims and incurred losses could increase by about 13%, 20% and 30% for the periods 2016-2035, 2046-2065, and 2081-2100, respectively (from the four-city seasonal average of 12 ± 1.7 thousand claims and 88±88 ± 88±21 million during April-September 1992. Within the context of this study, increases in the future number of insurance claims and incurred losses in the study area are driven by only increases in future heavy rainfall events.
Paddy and Water Environment, 2009
In this study, an automated synoptic weather typing was employed to identity the weather types mo... more In this study, an automated synoptic weather typing was employed to identity the weather types most likely associated with daily typhoon/typhoon-related heavy rainfall events for Chiayi, Taiwan. The synoptic weather typing was developed using principal components analysis, an average linkage clustering procedure, and discriminant function analysis. The classification results showed that the synoptic weather typing was successful at identifying typhoon-related weather types. Five synoptic weather types (Weather Types 1-5) were identified over the past 11-year period as the primary typhoon-related weather types. These five typhoon-related weather types can capture 34 out of 36 total typhoon-related heavy rainfall days ([50 mm/d) and all nine cases with typhoon-related daily rainfall [200 mm during the period March 1998-December 2008. This result suggests that synoptic weather typing can be useful to identify historical typhoon/typhoon-related heavy rainfall events. Moreover, the method has potential to assess climate change impacts on the frequency/intensity of future typhoon/typhoon-related heavy rainfall events using future downscaled GCM climate data.
Atmosphere-Ocean, 2014
ABSTRACT
The overarching purpose of this study was to project changes in the occurrence frequency and magn... more The overarching purpose of this study was to project changes in the occurrence frequency and magnitude of future wind gust events under downscaled future climate conditions over Ontario, Canada. Wind gust factors were employed to simulate hourly/daily wind gust based on hourly/daily wind speed. Regression-based downscaling methods were used to downscale future hourly/daily wind speed to each of the 14
Water, Air, and Soil Pollution, 2007
Automated synoptic weather typing and robust orthogonal stepwise regression analysis (via princip... more Automated synoptic weather typing and robust orthogonal stepwise regression analysis (via principal components analysis) were applied together to develop within-weather-type air pollution prediction models for a variety of pollutants (specifically, carbon monoxide -CO, nitrogen dioxide -NO 2 , ozone -O 3 , sulphur dioxide -SO 2 , and suspended particles -SP) for the period 1974-2000 in south-central Canada. The SAS robust regression procedure was used to limit the influence of outliers on air pollution prediction algorithms. Six-hourly Environment Canada surface observed meteorological data and 6-hourly US National Centers for Environmental Prediction (NCEP) reanalysis data of various weather elements were used in the analysis. The models were developed using twothirds of the total years for meteorological and air pollution data; the remaining one-third (randomly selected) was used for model validation. Robust stepwise regression analysis was performed to analytically determine the meteorological variables that might be used to predict air pollution concentrations. There was a significant correlation between observed daily mean air pollution concentrations and model predictions. About 20, 50, and 80% of the 80 prediction models across the study area possessed R 2 values ≥ 0.7, 0.6, and 0.5, respectively. The results of model validation were similar to those of model development, with slightly smaller model R 2 values.
Journal of Climate, 2012
ABSTRACT
Journal of Climate, 2011
... The current study employs the synoptic weather typing and a number of linear and nonlinear re... more ... The current study employs the synoptic weather typing and a number of linear and nonlinear regression techniques to downscale future daily rainfall from large-scale GCM simulations to the ... The downscaling scheme is built upon the previous studies (ie, Cheng et al. ...
Journal of Climate, 2014
ABSTRACT
Journal of Applied Meteorology and Climatology, 2010
ABSTRACT
Climatic Change, 2012
Synoptic weather typing and regression-based downscaling approaches have become popular in evalua... more Synoptic weather typing and regression-based downscaling approaches have become popular in evaluating the impacts of climate change on a variety of environmental problems, particularly those involving extreme impacts. One of the reasons for the popularity of these approaches is their ability to categorize a complex set of meteorological variables into a coherent index, facilitating the projection of changes in frequency and intensity of future daily extreme weather events and/or their impacts. This paper illustrated the capability of the synoptic weather typing and regression methods to analyze climatic change impacts on a number of extreme weather events and environmental problems for south-central Canada, such as freezing rain, heavy rainfall, high-/low-streamflow events, air pollution, and human health. These statistical approaches are helpful in analyzing extreme events and projecting their impacts into the future through three major steps or analysis procedures: (1) historical simulation modeling to identify extreme weather events or their impacts, (2) statistical downscaling to provide station-scale future hourly/daily climate data, and (3) projecting changes in the frequency and intensity of future extreme weather events and their impacts under a changing climate. To realize these steps, it is first necessary to conceptualize the modeling of the meteorology, hydrology and impacts model variables of significance and to apply a number of linear/nonlinear regression techniques. Because the climate/weather validation process is critical, a formal model result verification process has been built into each of these three steps. With carefully chosen physically consistent and relevant variables, the results of the verification, based on historical observations of the outcome variables simulated by the models, show a very good agreement in all applications and extremes tested to date. Overall, the modeled results from climate change studies indicate that the frequency and intensity of future extreme weather events and their impacts are generally projected to significantly increase late this century
Climate Research, 1997
This paper discusses the application of a year-round synoptic classification procedure to define ... more This paper discusses the application of a year-round synoptic classification procedure to define climatolog~cal seasons based upon the frequency occuiience of seasonal air masses The classification is developed through air inass 'seed day identification and discriminant function analysis, and assigns each day to 1 of 18 ail mass types for each of 14 stations along the East Coast of the United States Unlike the 'astronomical definitlon of seasons, which divides a year into 4 equal p e i~o d s , the length of wlnter ranges fiom about 1'4 mo in Mlami, Florida to more than 4 mo in Portland, hdaine as determined by air mass frequencies The suminer extends more than 5 mo in Flonda, whlle it only lasts 3 mo in Maine In the mld-Atlantic region, there ale 2 longer seasons (summer and wlntei, about 4 mo edch) and 2 shorter seasons (spnny and fall, about 2 mo each) The seasonal definitlon proposed here more closely corresponds to phenological responses than do t r a d~t~o n a l def~nitions The lnforination can be applied to numerous environmentdl assessment problems, including animal demographics and habitat distnbutions, plant phenology and subsequent pollen release, m~gration and hibernation patterns, human health and psychological iesponses to climate, and agncultural p l a n n~n g activities