High-impact hydro-meteorological events produce the most destructive and costly outcomes of any weather-driven phenomena world-wide. Furthermore, despite significant progress over the last several decades, forecasting and warning for these events still lacks the precision that could minimize loss of property and life, especially in developing nations. However, new observational platforms (in-situ, remote) and data-collection methods are improving our ability to assess ongoing events as well as forecast and distinguish those that could be destructive from those that probably will not be. Excessive precipitation or runoff associated with tropical cyclones/convection, land-based convection, atmospheric rivers, ENSO, wintertime snow-melt, rain-on-snow, etc. results in both flash-flooding and large-river system floods whose characteristics often depend on local soils, vegetation/agriculture, and topography. Conversely, severe droughts create deleterious impacts on crop/food production and the water supply. In this session, papers are invited that contribute to our ability to improve real-time/operational forecasts and warnings for these kinds of extremes, especially observational (as well as modeling) approaches that may vary depending upon differing societal contexts. In addition, papers that address promising and innovative methods of assessing and modeling the statistics of observed hydro-meteorological extremes as applied to real-time/operational forecasting/warning systems are encouraged. Papers that document forecast system performance vis-a-vis the effect of including new or additional observations are also encouraged. Please contact the session chair, Ana Barros (barros@duke.edu) or the session organizer, John McHenry (john.mchenry@baronweather.com) for additional information.

High-impact hydro-meteorological events produce the most destructive and costly outcomes of any weather-driven phenomena world-wide. Furthermore, despite significant progress over the last several decades, forecasting and warning for these events still lacks the precision that could minimize loss of property and life, especially in developing nations. However, new observational platforms (in-situ, remote) and data-collection methods are improving our ability to assess ongoing events as well as forecast and distinguish those that could be destructive from those that probably will not be. Excessive precipitation or runoff associated with tropical cyclones/convection, land-based convection, atmospheric rivers, ENSO, wintertime snow-melt, rain-on-snow, etc. results in both flash-flooding and large-river system floods whose characteristics often depend on local soils, vegetation/agriculture, and topography. Conversely, severe droughts create deleterious impacts on crop/food production and the water supply. In this session, papers are invited that contribute to our ability to improve real-time/operational forecasts and warnings for these kinds of extremes, especially observational (as well as modeling) approaches that may vary depending upon differing societal contexts. In addition, papers that address promising and innovative methods of assessing and modeling the statistics of observed hydro-meteorological extremes as applied to real-time/operational forecasting/warning systems are encouraged. Papers that document forecast system performance vis-a-vis the effect of including new or additional observations are also encouraged. Please contact the session chair, Ana Barros (barros@duke.edu) or the session organizer, John McHenry (john.mchenry@baronweather.com) for additional information.

High-impact hydro-meteorological events produce the most destructive and costly outcomes of any weather-driven phenomena world-wide. Furthermore, despite significant progress over the last several decades, forecasting and warning for these events still lacks the precision that could minimize loss of property and life, especially in developing nations. However, new observational platforms (in-situ, remote) and data-collection methods are improving our ability to assess ongoing events as well as forecast and distinguish those that could be destructive from those that probably will not be. Excessive precipitation or runoff associated with tropical cyclones/convection, land-based convection, atmospheric rivers, ENSO, wintertime snow-melt, rain-on-snow, etc. results in both flash-flooding and large-river system floods whose characteristics often depend on local soils, vegetation/agriculture, and topography. Conversely, severe droughts create deleterious impacts on crop/food production and the water supply. In this session, papers are invited that contribute to our ability to improve real-time/operational forecasts and warnings for these kinds of extremes, especially observational (as well as modeling) approaches that may vary depending upon differing societal contexts. In addition, papers that address promising and innovative methods of assessing and modeling the statistics of observed hydro-meteorological extremes as applied to real-time/operational forecasting/warning systems are encouraged. Papers that document forecast system performance vis-a-vis the effect of including new or additional observations are also encouraged. Please contact the session chair, Ana Barros (barros@duke.edu) or the session organizer, John McHenry (john.mchenry@baronweather.com) for additional information.

High-impact hydro-meteorological events produce the most destructive and costly outcomes of any weather-driven phenomena world-wide. Furthermore, despite significant progress over the last several decades, forecasting and warning for these events still lacks the precision that could minimize loss of property and life, especially in developing nations. However, new observational platforms (in-situ, remote) and data-collection methods are improving our ability to assess ongoing events as well as forecast and distinguish those that could be destructive from those that probably will not be. Excessive precipitation or runoff associated with tropical cyclones/convection, land-based convection, atmospheric rivers, ENSO, wintertime snow-melt, rain-on-snow, etc. results in both flash-flooding and large-river system floods whose characteristics often depend on local soils, vegetation/agriculture, and topography. Conversely, severe droughts create deleterious impacts on crop/food production and the water supply. In this session, papers are invited that contribute to our ability to improve real-time/operational forecasts and warnings for these kinds of extremes, especially observational (as well as modeling) approaches that may vary depending upon differing societal contexts. In addition, papers that address promising and innovative methods of assessing and modeling the statistics of observed hydro-meteorological extremes as applied to real-time/operational forecasting/warning systems are encouraged. Papers that document forecast system performance vis-a-vis the effect of including new or additional observations are also encouraged. Please contact the session chair, Ana Barros (barros@duke.edu) or the session organizer, John McHenry (john.mchenry@baronweather.com) for additional information.

The 31st Conference on Hydrology is hosting a session joint with the Probability and Statistics committee on diagnostic model evaluation and improvement of land models. Advancements in earth system modeling require coupling of the atmosphere, hydrologic, land surface, ocean and cryosphere systems. Correspondingly, there are significant challenges in the systematic evaluation of each of the system components and their interactions. This session seeks to move beyond traditional verification studies that document accuracy of land models, and instead ask questions if models are adequately using the information available to them, what are specific weaknesses in land models, and how can models be improved. As such, the particular interest of this session is to explore the model evaluation challenges in hydrology, land processes and the corresponding impact on coupled land-atmosphere processes and hydrometeorological prediction. With the increase in the variety of model developers and users, more integrated approaches that encapsulate the key water cycle component are needed to improve individual model components and coupled earth system component interactions. In addition, the development of a common, systematic set of measures will improve the “observability” of various model outputs from these systems. This session solicits contributions on integrated diagnostic evaluation and benchmarking techniques and metrics that promote systematic error and uncertainty quantification across complex modeling components. The session also solicits contributions that pinpoint model weaknesses and introduce innovative modeling approaches to address long-standing challenges simulating heterogeneity, emergent behavior, and process coupling across a range of different space and time scales. A key focus of the session, supporting the conference theme of “observations lead the way” is contributions that use multivariate and multiscale observations to diagnose model weaknesses and evaluate the fidelity of competing modeling approaches. This session will also address the significant challenges associated with assessing the quality and informativeness of both models and data products that are largely related to scale, heterogeneity, complexity, and representativeness. These challenges compound when assessing spatially and temporally distributed products and the fusion of models and data via approaches such as parameter estimation and data assimilation. This session therefore also solicits contributions related to innovative methods for assessing quality of model-data fusion and assessing the fidelity of models of complex terrestrial hydrologic systems in both offline and coupled modes.

The 31st Conference on Hydrology is hosting a session joint with the Probability and Statistics committee on diagnostic model evaluation and improvement of land models. Advancements in earth system modeling require coupling of the atmosphere, hydrologic, land surface, ocean and cryosphere systems. Correspondingly, there are significant challenges in the systematic evaluation of each of the system components and their interactions. This session seeks to move beyond traditional verification studies that document accuracy of land models, and instead ask questions if models are adequately using the information available to them, what are specific weaknesses in land models, and how can models be improved. As such, the particular interest of this session is to explore the model evaluation challenges in hydrology, land processes and the corresponding impact on coupled land-atmosphere processes and hydrometeorological prediction. With the increase in the variety of model developers and users, more integrated approaches that encapsulate the key water cycle component are needed to improve individual model components and coupled earth system component interactions. In addition, the development of a common, systematic set of measures will improve the “observability” of various model outputs from these systems. This session solicits contributions on integrated diagnostic evaluation and benchmarking techniques and metrics that promote systematic error and uncertainty quantification across complex modeling components. The session also solicits contributions that pinpoint model weaknesses and introduce innovative modeling approaches to address long-standing challenges simulating heterogeneity, emergent behavior, and process coupling across a range of different space and time scales. A key focus of the session, supporting the conference theme of “observations lead the way” is contributions that use multivariate and multiscale observations to diagnose model weaknesses and evaluate the fidelity of competing modeling approaches. This session will also address the significant challenges associated with assessing the quality and informativeness of both models and data products that are largely related to scale, heterogeneity, complexity, and representativeness. These challenges compound when assessing spatially and temporally distributed products and the fusion of models and data via approaches such as parameter estimation and data assimilation. This session therefore also solicits contributions related to innovative methods for assessing quality of model-data fusion and assessing the fidelity of models of complex terrestrial hydrologic systems in both offline and coupled modes.

The 31st Conference on Hydrology is hosting a session joint with the Probability and Statistics committee on diagnostic model evaluation and improvement of land models. Advancements in earth system modeling require coupling of the atmosphere, hydrologic, land surface, ocean and cryosphere systems. Correspondingly, there are significant challenges in the systematic evaluation of each of the system components and their interactions. This session seeks to move beyond traditional verification studies that document accuracy of land models, and instead ask questions if models are adequately using the information available to them, what are specific weaknesses in land models, and how can models be improved. As such, the particular interest of this session is to explore the model evaluation challenges in hydrology, land processes and the corresponding impact on coupled land-atmosphere processes and hydrometeorological prediction. With the increase in the variety of model developers and users, more integrated approaches that encapsulate the key water cycle component are needed to improve individual model components and coupled earth system component interactions. In addition, the development of a common, systematic set of measures will improve the “observability” of various model outputs from these systems. This session solicits contributions on integrated diagnostic evaluation and benchmarking techniques and metrics that promote systematic error and uncertainty quantification across complex modeling components. The session also solicits contributions that pinpoint model weaknesses and introduce innovative modeling approaches to address long-standing challenges simulating heterogeneity, emergent behavior, and process coupling across a range of different space and time scales. A key focus of the session, supporting the conference theme of “observations lead the way” is contributions that use multivariate and multiscale observations to diagnose model weaknesses and evaluate the fidelity of competing modeling approaches. This session will also address the significant challenges associated with assessing the quality and informativeness of both models and data products that are largely related to scale, heterogeneity, complexity, and representativeness. These challenges compound when assessing spatially and temporally distributed products and the fusion of models and data via approaches such as parameter estimation and data assimilation. This session therefore also solicits contributions related to innovative methods for assessing quality of model-data fusion and assessing the fidelity of models of complex terrestrial hydrologic systems in both offline and coupled modes.

Recent years have seen the proliferation of remote-sensing measurement systems that have application to hydro-meteorology and hydrology, from the ability to better assess regional drought conditions, to improved global snow/ice pack estimates, to higher resolution soil-moisture (active/passive) and QPE estimation, among others. This session solicits papers that overlap these and related remote-sensing applications with the broader overall meeting theme "Observations Lead the Way" while focusing on both situational awareness and hydrological forecasting. Papers that report on statistical and dynamic-model uses of the data (e.g. data-assimilation) as well as the novel use of very recent measurement methods encouraged, as well as scales that may range from small basin hydrology to regional/continental applications. Please contact the program organizer, John McHenry (john.mchenry@baronams.com) for additional information.

The 31st Conference on Hydrology is hosting a session joint with the Probability and Statistics committee on diagnostic model evaluation and improvement of land models. Advancements in earth system modeling require coupling of the atmosphere, hydrologic, land surface, ocean and cryosphere systems. Correspondingly, there are significant challenges in the systematic evaluation of each of the system components and their interactions. This session seeks to move beyond traditional verification studies that document accuracy of land models, and instead ask questions if models are adequately using the information available to them, what are specific weaknesses in land models, and how can models be improved. As such, the particular interest of this session is to explore the model evaluation challenges in hydrology, land processes and the corresponding impact on coupled land-atmosphere processes and hydrometeorological prediction. With the increase in the variety of model developers and users, more integrated approaches that encapsulate the key water cycle component are needed to improve individual model components and coupled earth system component interactions. In addition, the development of a common, systematic set of measures will improve the “observability” of various model outputs from these systems. This session solicits contributions on integrated diagnostic evaluation and benchmarking techniques and metrics that promote systematic error and uncertainty quantification across complex modeling components. The session also solicits contributions that pinpoint model weaknesses and introduce innovative modeling approaches to address long-standing challenges simulating heterogeneity, emergent behavior, and process coupling across a range of different space and time scales. A key focus of the session, supporting the conference theme of “observations lead the way” is contributions that use multivariate and multiscale observations to diagnose model weaknesses and evaluate the fidelity of competing modeling approaches. This session will also address the significant challenges associated with assessing the quality and informativeness of both models and data products that are largely related to scale, heterogeneity, complexity, and representativeness. These challenges compound when assessing spatially and temporally distributed products and the fusion of models and data via approaches such as parameter estimation and data assimilation. This session therefore also solicits contributions related to innovative methods for assessing quality of model-data fusion and assessing the fidelity of models of complex terrestrial hydrologic systems in both offline and coupled modes.

Recent years have seen the proliferation of remote-sensing measurement systems that have application to hydro-meteorology and hydrology, from the ability to better assess regional drought conditions, to improved global snow/ice pack estimates, to higher resolution soil-moisture (active/passive) and QPE estimation, among others. This session solicits papers that overlap these and related remote-sensing applications with the broader overall meeting theme "Observations Lead the Way" while focusing on both situational awareness and hydrological forecasting. Papers that report on statistical and dynamic-model uses of the data (e.g. data-assimilation) as well as the novel use of very recent measurement methods encouraged, as well as scales that may range from small basin hydrology to regional/continental applications. Please contact the program organizer, John McHenry (john.mchenry@baronams.com) for additional information.

Recent years have seen the proliferation of remote-sensing measurement systems that have application to hydro-meteorology and hydrology, from the ability to better assess regional drought conditions, to improved global snow/ice pack estimates, to higher resolution soil-moisture (active/passive) and QPE estimation, among others. This session solicits papers that overlap these and related remote-sensing applications with the broader overall meeting theme "Observations Lead the Way" while focusing on both situational awareness and hydrological forecasting. Papers that report on statistical and dynamic-model uses of the data (e.g. data-assimilation) as well as the novel use of very recent measurement methods encouraged, as well as scales that may range from small basin hydrology to regional/continental applications. Please contact the program organizer, John McHenry (john.mchenry@baronams.com) for additional information.

Themed session: The 2016 AMS Annual Meeting Theme is entitled 'Observations Lead the Way'. This theme recognizes that many of our scientific advances in atmospheric and related sciences are founded on collection and analysis of new, innovative observations. In keeping with this theme a special session entitled "Innovative Water Cycle Observations" is being coordinated to highlight emerging observational capabilities making their way into hydrometeorological practice. Contributions from those conducting innovative measurements of terrestrial hydrologic variable such as soil moisture, snowpack, runoff, groundwater, streamflow, inundation and others are sought. Also encouraged are submissions describing new and planned instrumentation networks that stem either from recent field campaigns or new operational networks as such networks provide a backbone for advances predictive sciences. For more information please contact the session organizer, David Gochis (gochis@ucar.edu)

Drought is a multi-faceted phenomenon that challenges our current prediction capabilities. Taking drought prediction and hydrological applications to the next level requires advances in understanding, monitoring, communications and water resources management. Specific topics addressed by presenters could include but are not limited to: Current drought prediction science and skill at various lead times; innovative management uses of that science; and case studies illustrating advances in understanding, monitoring and prediction of drought and drought impacts. Further, papers addressing gaps and deficiencies in our current methods for predicting droughts and estimating its effects on vegetation, water resources, and human populations are also invited.

Both public (e.g. emergency management, NOAA) and commercial (e.g. weather sensitive businesses, private-sector weather service providers) entities are involved in the distribution and use of hydrometeorological products and services. Private-sector firms often focus on "niche" applications or develop/implement technologies of interest to public-sector providers such as National Meteorological and Hydrological Services (NMHS's). The types of decision-support systems (DSS's) range from water management applications (impoundments, reservoir/hydro-power, urban runoff/drainage); to water resources applications (irrigation, potable water, water pollution mitigation, regional water supply management; to heavy precipitation and flash-flood/flood awareness and forecast services. All rely on high-quality observations as a starting-point. DSS’s range in complexity from the highly-sophisticated to consumer-oriented and include products for emergency management, broadcast television and application developers (e.g. Web data services/APIs), while also covering a broad range of both space and time scales. On the other hand, consumers of such products and services seek to minimize impacts or maximize resources while looking to both commercial and government entities to provide the needed information. Thus, there is a natural overlap between the provision of hydrological products and services and consumers of those services. We invite contributions from both provider and consumer vantage points as a basis for dialogue toward the development and application of “next-generation" products and services. Papers with a special focus on the integration of new observations that show promise in improving the reliability (statistical) of the DSS for its particular application area are encouraged. For more information, please contact the program organizer, John McHenry, at john.mchenry@baronweather.com.

Numerical simulation of hydrologic processes has be practiced for many years. Although HPC is widely utilized in atmospheric modeling, its role in hydrological modeling has been less profound. In this joint session, we are seeking abstracts that focus on hydrological modeling processes which require, and utilize HPC resources to improve the overall understanding of the extremes of flood and drought. More specifically, we are interested in abstracts which demonstrate improved coupling of hydrologic and atmospheric models (supported on the same computing platform); support large-scale hydrologic models at increased spatial resolutions; instances of coupled modeling systems running in an ensemble system to better express model uncertainty; and, abilities to process large datasets (multiterabyte volumes).

This session is a follow-on to last year's session co-hosted by the AI committee. This year, we invite submissions on topics related to machine learning and statistical methods applied to hydrologic problems, with a focus on real-world forecasting applications, and in particular the problem of quantitative precipitation estimation in real-time. Overlapping closely with this year's annual meeting theme "Observations Lead the Way," the QPE problem includes all observational methods: in-situ, radar-derived, satellite-derived, multi-sensor; together with objective analysis approaches. In-short -- what combinations of observations and classes of observations seem to "do best;" how do we determine what "doing best" really is (space and time scales); and how can and do AI methods (machine learning, optimal statistics, etc.) applied to the observations improve our QPE estimates? What challenges still remain? For additional information, please contact the program organizers, Valliappa Lakshmanan (lak@vlakshman.com) or John McHenry (john.mchenry@baronweather.com).

Both public (e.g. emergency management, NOAA) and commercial (e.g. weather sensitive businesses, private-sector weather service providers) entities are involved in the distribution and use of hydrometeorological products and services. Private-sector firms often focus on "niche" applications or develop/implement technologies of interest to public-sector providers such as National Meteorological and Hydrological Services (NMHS's). The types of decision-support systems (DSS's) range from water management applications (impoundments, reservoir/hydro-power, urban runoff/drainage); to water resources applications (irrigation, potable water, water pollution mitigation, regional water supply management; to heavy precipitation and flash-flood/flood awareness and forecast services. All rely on high-quality observations as a starting-point. DSS’s range in complexity from the highly-sophisticated to consumer-oriented and include products for emergency management, broadcast television and application developers (e.g. Web data services/APIs), while also covering a broad range of both space and time scales. On the other hand, consumers of such products and services seek to minimize impacts or maximize resources while looking to both commercial and government entities to provide the needed information. Thus, there is a natural overlap between the provision of hydrological products and services and consumers of those services. We invite contributions from both provider and consumer vantage points as a basis for dialogue toward the development and application of “next-generation" products and services. Papers with a special focus on the integration of new observations that show promise in improving the reliability (statistical) of the DSS for its particular application area are encouraged. For more information, please contact the program organizer, John McHenry, at john.mchenry@baronweather.com.

Both public (e.g. emergency management, NOAA) and commercial (e.g. weather sensitive businesses, private-sector weather service providers) entities are involved in the distribution and use of hydrometeorological products and services. Private-sector firms often focus on "niche" applications or develop/implement technologies of interest to public-sector providers such as National Meteorological and Hydrological Services (NMHS's). The types of decision-support systems (DSS's) range from water management applications (impoundments, reservoir/hydro-power, urban runoff/drainage); to water resources applications (irrigation, potable water, water pollution mitigation, regional water supply management; to heavy precipitation and flash-flood/flood awareness and forecast services. All rely on high-quality observations as a starting-point. DSS’s range in complexity from the highly-sophisticated to consumer-oriented and include products for emergency management, broadcast television and application developers (e.g. Web data services/APIs), while also covering a broad range of both space and time scales. On the other hand, consumers of such products and services seek to minimize impacts or maximize resources while looking to both commercial and government entities to provide the needed information. Thus, there is a natural overlap between the provision of hydrological products and services and consumers of those services. We invite contributions from both provider and consumer vantage points as a basis for dialogue toward the development and application of “next-generation" products and services. Papers with a special focus on the integration of new observations that show promise in improving the reliability (statistical) of the DSS for its particular application area are encouraged. For more information, please contact the program organizer, John McHenry, at john.mchenry@baronweather.com.

Drought is a multi-faceted phenomenon that challenges our current prediction capabilities. Taking drought prediction and hydrological applications to the next level requires advances in understanding, monitoring, communications and water resources management. Specific topics addressed by presenters could include but are not limited to: Current drought prediction science and skill at various lead times; innovative management uses of that science; and case studies illustrating advances in understanding, monitoring and prediction of drought and drought impacts. Further, papers addressing gaps and deficiencies in our current methods for predicting droughts and estimating its effects on vegetation, water resources, and human populations are also invited.

Drought is a multi-faceted phenomenon that challenges our current prediction capabilities. Taking drought prediction and hydrological applications to the next level requires advances in understanding, monitoring, communications and water resources management. Specific topics addressed by presenters could include but are not limited to: Current drought prediction science and skill at various lead times; innovative management uses of that science; and case studies illustrating advances in understanding, monitoring and prediction of drought and drought impacts. Further, papers addressing gaps and deficiencies in our current methods for predicting droughts and estimating its effects on vegetation, water resources, and human populations are also invited.

Drought is a multi-faceted phenomenon that challenges our current prediction capabilities. Taking drought prediction and hydrological applications to the next level requires advances in understanding, monitoring, communications and water resources management. Specific topics addressed by presenters could include but are not limited to: Current drought prediction science and skill at various lead times; innovative management uses of that science; and case studies illustrating advances in understanding, monitoring and prediction of drought and drought impacts. Further, papers addressing gaps and deficiencies in our current methods for predicting droughts and estimating its effects on vegetation, water resources, and human populations are also invited.