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The Earth’s climate has traditionally been studied by statistical analysis of observations of particular weather elements such as temperature, wind and rainfall. Climatological information, usually expressed as long-term averages and variability, is then presented over a geographical area or at a single location and time series of these quantities or of the observations themselves are examined for evidence of warming, more-frequent severe storms, and so on.

A powerful new approach to climate analysis has emerged in recent years. It applies the tools and techniques of modern everyday weather forecasting in a process called reanalysis. The products, reanalyses, have applicability far beyond that of traditional climate information. Reanalyses have become established as an important and widely utilized resource for the study of atmospheric and oceanic processes and predictability also over the data sparse polar regions. They are used in a range of applications that require a comprehensive record of the state of either the atmosphere or its underlying land and ocean surfaces. The reanalysis products, unlike their operational counterparts, do not suffer from inhomogeneities introduced by changes in the data assimilation system. Thus they are in principle better suited for use in studies of low frequency variability and climate trends that complement studies of climate change based on individual instrumental records and climate-model simulations.

Climate quality requirements can be met by reanalyses for the decades with good upper-air data coverage by satellites or at least radiosonde data. The possibility of extending reanalyses to cover earlier periods when only surface observations are available in reasonable numbers (e.g., from the 1850s to the 1930s) is nevertheless of interest, and has been explored in pilot studies comparing analyses with good coverage of satellite and other upper-air data with analyses using only surface-pressure observations.

The Earth’s climate has traditionally been studied by statistical analysis of observations of particular weather elements such as temperature, wind and rainfall. Climatological information, usually expressed as long-term averages and variability, is then presented over a geographical area or at a single location and time series of these quantities or of the observations themselves are examined for evidence of warming, more-frequent severe storms, and so on.

A powerful new approach to climate analysis has emerged in recent years. It applies the tools and techniques of modern everyday weather forecasting in a process called reanalysis. The products, reanalyses, have applicability far beyond that of traditional climate information. Reanalyses have become established as an important and widely utilized resource for the study of atmospheric and oceanic processes and predictability also over the data sparse polar regions. They are used in a range of applications that require a comprehensive record of the state of either the atmosphere or its underlying land and ocean surfaces. The reanalysis products, unlike their operational counterparts, do not suffer from inhomogeneities introduced by changes in the data assimilation system. Thus they are in principle better suited for use in studies of low frequency variability and climate trends that complement studies of climate change based on individual instrumental records and climate-model simulations.

Climate quality requirements can be met by reanalyses for the decades with good upper-air data coverage by satellites or at least radiosonde data. The possibility of extending reanalyses to cover earlier periods when only surface observations are available in reasonable numbers (e.g., from the 1850s to the 1930s) is nevertheless of interest, and has been explored in pilot studies comparing analyses with good coverage of satellite and other upper-air data with analyses using only surface-pressure observations.

The Earth’s climate has traditionally been studied by statistical analysis of observations of particular weather elements such as temperature, wind and rainfall. Climatological information, usually expressed as long-term averages and variability, is then presented over a geographical area or at a single location and time series of these quantities or of the observations themselves are examined for evidence of warming, more-frequent severe storms, and so on.

A powerful new approach to climate analysis has emerged in recent years. It applies the tools and techniques of modern everyday weather forecasting in a process called reanalysis. The products, reanalyses, have applicability far beyond that of traditional climate information. Reanalyses have become established as an important and widely utilized resource for the study of atmospheric and oceanic processes and predictability also over the data sparse polar regions. They are used in a range of applications that require a comprehensive record of the state of either the atmosphere or its underlying land and ocean surfaces. The reanalysis products, unlike their operational counterparts, do not suffer from inhomogeneities introduced by changes in the data assimilation system. Thus they are in principle better suited for use in studies of low frequency variability and climate trends that complement studies of climate change based on individual instrumental records and climate-model simulations.

Climate quality requirements can be met by reanalyses for the decades with good upper-air data coverage by satellites or at least radiosonde data. The possibility of extending reanalyses to cover earlier periods when only surface observations are available in reasonable numbers (e.g., from the 1850s to the 1930s) is nevertheless of interest, and has been explored in pilot studies comparing analyses with good coverage of satellite and other upper-air data with analyses using only surface-pressure observations.

The Earth’s climate has traditionally been studied by statistical analysis of observations of particular weather elements such as temperature, wind and rainfall. Climatological information, usually expressed as long-term averages and variability, is then presented over a geographical area or at a single location and time series of these quantities or of the observations themselves are examined for evidence of warming, more-frequent severe storms, and so on.

A powerful new approach to climate analysis has emerged in recent years. It applies the tools and techniques of modern everyday weather forecasting in a process called reanalysis. The products, reanalyses, have applicability far beyond that of traditional climate information. Reanalyses have become established as an important and widely utilized resource for the study of atmospheric and oceanic processes and predictability also over the data sparse polar regions. They are used in a range of applications that require a comprehensive record of the state of either the atmosphere or its underlying land and ocean surfaces. The reanalysis products, unlike their operational counterparts, do not suffer from inhomogeneities introduced by changes in the data assimilation system. Thus they are in principle better suited for use in studies of low frequency variability and climate trends that complement studies of climate change based on individual instrumental records and climate-model simulations.

Climate quality requirements can be met by reanalyses for the decades with good upper-air data coverage by satellites or at least radiosonde data. The possibility of extending reanalyses to cover earlier periods when only surface observations are available in reasonable numbers (e.g., from the 1850s to the 1930s) is nevertheless of interest, and has been explored in pilot studies comparing analyses with good coverage of satellite and other upper-air data with analyses using only surface-pressure observations.

The Earth’s climate has traditionally been studied by statistical analysis of observations of particular weather elements such as temperature, wind and rainfall. Climatological information, usually expressed as long-term averages and variability, is then presented over a geographical area or at a single location and time series of these quantities or of the observations themselves are examined for evidence of warming, more-frequent severe storms, and so on.

A powerful new approach to climate analysis has emerged in recent years. It applies the tools and techniques of modern everyday weather forecasting in a process called reanalysis. The products, reanalyses, have applicability far beyond that of traditional climate information. Reanalyses have become established as an important and widely utilized resource for the study of atmospheric and oceanic processes and predictability also over the data sparse polar regions. They are used in a range of applications that require a comprehensive record of the state of either the atmosphere or its underlying land and ocean surfaces. The reanalysis products, unlike their operational counterparts, do not suffer from inhomogeneities introduced by changes in the data assimilation system. Thus they are in principle better suited for use in studies of low frequency variability and climate trends that complement studies of climate change based on individual instrumental records and climate-model simulations.

Climate quality requirements can be met by reanalyses for the decades with good upper-air data coverage by satellites or at least radiosonde data. The possibility of extending reanalyses to cover earlier periods when only surface observations are available in reasonable numbers (e.g., from the 1850s to the 1930s) is nevertheless of interest, and has been explored in pilot studies comparing analyses with good coverage of satellite and other upper-air data with analyses using only surface-pressure observations.

The Earth’s climate has traditionally been studied by statistical analysis of observations of particular weather elements such as temperature, wind and rainfall. Climatological information, usually expressed as long-term averages and variability, is then presented over a geographical area or at a single location and time series of these quantities or of the observations themselves are examined for evidence of warming, more-frequent severe storms, and so on.

A powerful new approach to climate analysis has emerged in recent years. It applies the tools and techniques of modern everyday weather forecasting in a process called reanalysis. The products, reanalyses, have applicability far beyond that of traditional climate information. Reanalyses have become established as an important and widely utilized resource for the study of atmospheric and oceanic processes and predictability also over the data sparse polar regions. They are used in a range of applications that require a comprehensive record of the state of either the atmosphere or its underlying land and ocean surfaces. The reanalysis products, unlike their operational counterparts, do not suffer from inhomogeneities introduced by changes in the data assimilation system. Thus they are in principle better suited for use in studies of low frequency variability and climate trends that complement studies of climate change based on individual instrumental records and climate-model simulations.

Climate quality requirements can be met by reanalyses for the decades with good upper-air data coverage by satellites or at least radiosonde data. The possibility of extending reanalyses to cover earlier periods when only surface observations are available in reasonable numbers (e.g., from the 1850s to the 1930s) is nevertheless of interest, and has been explored in pilot studies comparing analyses with good coverage of satellite and other upper-air data with analyses using only surface-pressure observations.

The Earth’s climate has traditionally been studied by statistical analysis of observations of particular weather elements such as temperature, wind and rainfall. Climatological information, usually expressed as long-term averages and variability, is then presented over a geographical area or at a single location and time series of these quantities or of the observations themselves are examined for evidence of warming, more-frequent severe storms, and so on.

A powerful new approach to climate analysis has emerged in recent years. It applies the tools and techniques of modern everyday weather forecasting in a process called reanalysis. The products, reanalyses, have applicability far beyond that of traditional climate information. Reanalyses have become established as an important and widely utilized resource for the study of atmospheric and oceanic processes and predictability also over the data sparse polar regions. They are used in a range of applications that require a comprehensive record of the state of either the atmosphere or its underlying land and ocean surfaces. The reanalysis products, unlike their operational counterparts, do not suffer from inhomogeneities introduced by changes in the data assimilation system. Thus they are in principle better suited for use in studies of low frequency variability and climate trends that complement studies of climate change based on individual instrumental records and climate-model simulations.

Climate quality requirements can be met by reanalyses for the decades with good upper-air data coverage by satellites or at least radiosonde data. The possibility of extending reanalyses to cover earlier periods when only surface observations are available in reasonable numbers (e.g., from the 1850s to the 1930s) is nevertheless of interest, and has been explored in pilot studies comparing analyses with good coverage of satellite and other upper-air data with analyses using only surface-pressure observations.

The Earth’s climate has traditionally been studied by statistical analysis of observations of particular weather elements such as temperature, wind and rainfall. Climatological information, usually expressed as long-term averages and variability, is then presented over a geographical area or at a single location and time series of these quantities or of the observations themselves are examined for evidence of warming, more-frequent severe storms, and so on.

A powerful new approach to climate analysis has emerged in recent years. It applies the tools and techniques of modern everyday weather forecasting in a process called reanalysis. The products, reanalyses, have applicability far beyond that of traditional climate information. Reanalyses have become established as an important and widely utilized resource for the study of atmospheric and oceanic processes and predictability also over the data sparse polar regions. They are used in a range of applications that require a comprehensive record of the state of either the atmosphere or its underlying land and ocean surfaces. The reanalysis products, unlike their operational counterparts, do not suffer from inhomogeneities introduced by changes in the data assimilation system. Thus they are in principle better suited for use in studies of low frequency variability and climate trends that complement studies of climate change based on individual instrumental records and climate-model simulations.

Climate quality requirements can be met by reanalyses for the decades with good upper-air data coverage by satellites or at least radiosonde data. The possibility of extending reanalyses to cover earlier periods when only surface observations are available in reasonable numbers (e.g., from the 1850s to the 1930s) is nevertheless of interest, and has been explored in pilot studies comparing analyses with good coverage of satellite and other upper-air data with analyses using only surface-pressure observations.

The Earth’s climate has traditionally been studied by statistical analysis of observations of particular weather elements such as temperature, wind and rainfall. Climatological information, usually expressed as long-term averages and variability, is then presented over a geographical area or at a single location and time series of these quantities or of the observations themselves are examined for evidence of warming, more-frequent severe storms, and so on.

A powerful new approach to climate analysis has emerged in recent years. It applies the tools and techniques of modern everyday weather forecasting in a process called reanalysis. The products, reanalyses, have applicability far beyond that of traditional climate information. Reanalyses have become established as an important and widely utilized resource for the study of atmospheric and oceanic processes and predictability also over the data sparse polar regions. They are used in a range of applications that require a comprehensive record of the state of either the atmosphere or its underlying land and ocean surfaces. The reanalysis products, unlike their operational counterparts, do not suffer from inhomogeneities introduced by changes in the data assimilation system. Thus they are in principle better suited for use in studies of low frequency variability and climate trends that complement studies of climate change based on individual instrumental records and climate-model simulations.

Climate quality requirements can be met by reanalyses for the decades with good upper-air data coverage by satellites or at least radiosonde data. The possibility of extending reanalyses to cover earlier periods when only surface observations are available in reasonable numbers (e.g., from the 1850s to the 1930s) is nevertheless of interest, and has been explored in pilot studies comparing analyses with good coverage of satellite and other upper-air data with analyses using only surface-pressure observations.

The Earth’s climate has traditionally been studied by statistical analysis of observations of particular weather elements such as temperature, wind and rainfall. Climatological information, usually expressed as long-term averages and variability, is then presented over a geographical area or at a single location and time series of these quantities or of the observations themselves are examined for evidence of warming, more-frequent severe storms, and so on.

A powerful new approach to climate analysis has emerged in recent years. It applies the tools and techniques of modern everyday weather forecasting in a process called reanalysis. The products, reanalyses, have applicability far beyond that of traditional climate information. Reanalyses have become established as an important and widely utilized resource for the study of atmospheric and oceanic processes and predictability also over the data sparse polar regions. They are used in a range of applications that require a comprehensive record of the state of either the atmosphere or its underlying land and ocean surfaces. The reanalysis products, unlike their operational counterparts, do not suffer from inhomogeneities introduced by changes in the data assimilation system. Thus they are in principle better suited for use in studies of low frequency variability and climate trends that complement studies of climate change based on individual instrumental records and climate-model simulations.

Climate quality requirements can be met by reanalyses for the decades with good upper-air data coverage by satellites or at least radiosonde data. The possibility of extending reanalyses to cover earlier periods when only surface observations are available in reasonable numbers (e.g., from the 1850s to the 1930s) is nevertheless of interest, and has been explored in pilot studies comparing analyses with good coverage of satellite and other upper-air data with analyses using only surface-pressure observations.