A number of regional and national real-time flood forecasting systems are emerging for a variety of different flood-related applications. These new systems are taking advantage of new national hydrologic data standards, new advances in supercomputing availability and improvements in model parameterizations and meteorological forcing datasets. This session encourages contributions from all sectors of the AMS enterprise (academic, government and the private sector) who have built and deployed such systems. Additionally, contributions are welcome from researchers who have developed novel methodologies to sense and model flood generation dynamics at a variety of time and space scales. Research and application contributions from within the U.S. as well as internationally are also encouraged.

Please note that there is a different session in this conference on heavy precipitation events, flood risk under climate change (see "Heavy Precipitation and Flood Risk under a Changing Climate").

Land-atmosphere and land-ocean interactions play a key role in climate variability and climate/weather predictability across space and time. The land’s role in the earth system – its impact on atmospheric and ocean means and variability across a broad range of timescales, ranging from hours to centuries, for past, present, and future climates – has been the subject of much recent exploratory research. The meteorological, hydrological, biophysical, biogeochemical, ecosystem processes, as well as the boundary-layer processes that underlie the connections between surface and atmosphere are not yet fully understood. The scarcity of relevant observations, the complexity of the underlying processes and feedbacks, and the wide range of scales involved necessitate coordinated and exceedingly interdisciplinary investigations. This session focuses on (1) interfaces between climate, ecosystems, and the land branches of the energy, water, and carbon cycles and the impact of associated land processes, including land-use/land-cover change, on climate variability and change as well as on extreme events (such as droughts and flooding); (2) dynamic, physical, and biogeochemical mechanisms by which the land surface (e.g., soil moisture and temperature, albedo, snow, and vegetation) influences surface water, carbon, and energy balances, atmospheric and ocean processes, and climate; (3) predictability associated with land-surface/atmosphere/ocean interactions and land initialization (such as soil moisture, soil temperature, snow, aerosol in snow, etc.) at sub-seasonal to seasonal, to decadal time scales; and (4) application and analyses of large scale field data and observational networks (such as FLUXNET), satellite remote sensing, and reanalyses data for land model development and land/atmosphere/ocean interaction studies. We welcome papers addressing any of these topics.

A number of regional and national real-time flood forecasting systems are emerging for a variety of different flood-related applications. These new systems are taking advantage of new national hydrologic data standards, new advances in supercomputing availability and improvements in model parameterizations and meteorological forcing datasets. This session encourages contributions from all sectors of the AMS enterprise (academic, government and the private sector) who have built and deployed such systems. Additionally, contributions are welcome from researchers who have developed novel methodologies to sense and model flood generation dynamics at a variety of time and space scales. Research and application contributions from within the U.S. as well as internationally are also encouraged.

Please note that there is a different session in this conference on heavy precipitation events, flood risk under climate change (see "Heavy Precipitation and Flood Risk under a Changing Climate").

Land-atmosphere and land-ocean interactions play a key role in climate variability and climate/weather predictability across space and time. The land’s role in the earth system – its impact on atmospheric and ocean means and variability across a broad range of timescales, ranging from hours to centuries, for past, present, and future climates – has been the subject of much recent exploratory research. The meteorological, hydrological, biophysical, biogeochemical, ecosystem processes, as well as the boundary-layer processes that underlie the connections between surface and atmosphere are not yet fully understood. The scarcity of relevant observations, the complexity of the underlying processes and feedbacks, and the wide range of scales involved necessitate coordinated and exceedingly interdisciplinary investigations. This session focuses on (1) interfaces between climate, ecosystems, and the land branches of the energy, water, and carbon cycles and the impact of associated land processes, including land-use/land-cover change, on climate variability and change as well as on extreme events (such as droughts and flooding); (2) dynamic, physical, and biogeochemical mechanisms by which the land surface (e.g., soil moisture and temperature, albedo, snow, and vegetation) influences surface water, carbon, and energy balances, atmospheric and ocean processes, and climate; (3) predictability associated with land-surface/atmosphere/ocean interactions and land initialization (such as soil moisture, soil temperature, snow, aerosol in snow, etc.) at sub-seasonal to seasonal, to decadal time scales; and (4) application and analyses of large scale field data and observational networks (such as FLUXNET), satellite remote sensing, and reanalyses data for land model development and land/atmosphere/ocean interaction studies. We welcome papers addressing any of these topics.

A number of regional and national real-time flood forecasting systems are emerging for a variety of different flood-related applications. These new systems are taking advantage of new national hydrologic data standards, new advances in supercomputing availability and improvements in model parameterizations and meteorological forcing datasets. This session encourages contributions from all sectors of the AMS enterprise (academic, government and the private sector) who have built and deployed such systems. Additionally, contributions are welcome from researchers who have developed novel methodologies to sense and model flood generation dynamics at a variety of time and space scales. Research and application contributions from within the U.S. as well as internationally are also encouraged.

Please note that there is a different session in this conference on heavy precipitation events, flood risk under climate change (see "Heavy Precipitation and Flood Risk under a Changing Climate").

Land-atmosphere and land-ocean interactions play a key role in climate variability and climate/weather predictability across space and time. The land’s role in the earth system – its impact on atmospheric and ocean means and variability across a broad range of timescales, ranging from hours to centuries, for past, present, and future climates – has been the subject of much recent exploratory research. The meteorological, hydrological, biophysical, biogeochemical, ecosystem processes, as well as the boundary-layer processes that underlie the connections between surface and atmosphere are not yet fully understood. The scarcity of relevant observations, the complexity of the underlying processes and feedbacks, and the wide range of scales involved necessitate coordinated and exceedingly interdisciplinary investigations. This session focuses on (1) interfaces between climate, ecosystems, and the land branches of the energy, water, and carbon cycles and the impact of associated land processes, including land-use/land-cover change, on climate variability and change as well as on extreme events (such as droughts and flooding); (2) dynamic, physical, and biogeochemical mechanisms by which the land surface (e.g., soil moisture and temperature, albedo, snow, and vegetation) influences surface water, carbon, and energy balances, atmospheric and ocean processes, and climate; (3) predictability associated with land-surface/atmosphere/ocean interactions and land initialization (such as soil moisture, soil temperature, snow, aerosol in snow, etc.) at sub-seasonal to seasonal, to decadal time scales; and (4) application and analyses of large scale field data and observational networks (such as FLUXNET), satellite remote sensing, and reanalyses data for land model development and land/atmosphere/ocean interaction studies. We welcome papers addressing any of these topics.

During the last three decades many hydrometeorological field and numerical studies have been done in the Amazonia region by researchers from Brazil, Europe, and the United States. This conference session invites contributions related hydrometeorological processes in the Amazonia region. Contributions are welcome to report on analyses and interpretation of historical data sets. Results from numerical modeling studies are particularly welcome. Conference presentations that evaluate the water budget components and address the physical mechanisms involved in precipitation recycling in the Amazon basin are highly encouraged. Findings from studies that report on the interactions between surface processes and the hydrologic cycle, and effects of climate change and drought on the precipitation processes in the Amazon basin are of great interest.

Large reservoirs provide multiple benefits for water supply, downstream flood reduction, and environmental objectives.  Weather and climate forecasts play a critical role in helping reservoir operators balance multiple, often competing objectives. Accordingly, this session will highlight successful examples of collaborative development and application of forecasts to support reservoir management.

The practice of using forecast informed flood management to mitigate downstream flooding is well established and reservoir operators fully consider that information while managing releases through the dam. However, extreme events challenge both forecaster and operators to quickly determine how to manage designated flood storage and prevent failure of the dam, which include: early releases, increasing spillway releases, and storing water.  Incorrect forecasts can magnify the impacts to any one requirement. Interdisciplinary cooperation is necessary to understand the accuracy of the forecasts and improve lead time to optimize operational flood management releases and preventing dam failure. For water supply management, utilization of codified forecast informed flood management for reservoir operation and recent advancements in weather forecasts such as those underlying the National Weather Service’s Hydrologic Ensemble Forecasting System (HEFS) afford operators improved capability to develop probabilistic projections to support proactive and dynamic operational decisions, such as how much water to release or divert over the next several days.

As an example, New York City’s Operations Support Tool (OST) is a system simulation platform that integrates a water supply operations model, mechanistic reservoir water quality models, statistical and climatological hydrologic forecasts, and various near-real-time data sources. In addition to routine forecast-driven operating plans, near-term simulations are used to evaluate operational strategies to deal with infrastructure outages, downstream flood mitigation, and weather-driven episodes of degraded water quality. OST simulations are currently being used to support development of an operations plan for an extended shutdown of the City’s critical Delaware Aqueduct, which supplies roughly 60% of the City’s water, based on operational triggers that rely on HEFS forecasts. Critical in development and application of the OST has been collaboration among water supply managers and operators, water resources engineers, hydrologists, and meteorologists in developing a common understanding on end user needs and forecast capabilities.

A number of regional and national real-time flood forecasting systems are emerging for a variety of different flood-related applications. These new systems are taking advantage of new national hydrologic data standards, new advances in supercomputing availability and improvements in model parameterizations and meteorological forcing datasets. This session encourages contributions from all sectors of the AMS enterprise (academic, government and the private sector) who have built and deployed such systems. Additionally, contributions are welcome from researchers who have developed novel methodologies to sense and model flood generation dynamics at a variety of time and space scales. Research and application contributions from within the U.S. as well as internationally are also encouraged.

Please note that there is a different session in this conference on heavy precipitation events, flood risk under climate change (see "Heavy Precipitation and Flood Risk under a Changing Climate").

Land-atmosphere and land-ocean interactions play a key role in climate variability and climate/weather predictability across space and time. The land’s role in the earth system – its impact on atmospheric and ocean means and variability across a broad range of timescales, ranging from hours to centuries, for past, present, and future climates – has been the subject of much recent exploratory research. The meteorological, hydrological, biophysical, biogeochemical, ecosystem processes, as well as the boundary-layer processes that underlie the connections between surface and atmosphere are not yet fully understood. The scarcity of relevant observations, the complexity of the underlying processes and feedbacks, and the wide range of scales involved necessitate coordinated and exceedingly interdisciplinary investigations. This session focuses on (1) interfaces between climate, ecosystems, and the land branches of the energy, water, and carbon cycles and the impact of associated land processes, including land-use/land-cover change, on climate variability and change as well as on extreme events (such as droughts and flooding); (2) dynamic, physical, and biogeochemical mechanisms by which the land surface (e.g., soil moisture and temperature, albedo, snow, and vegetation) influences surface water, carbon, and energy balances, atmospheric and ocean processes, and climate; (3) predictability associated with land-surface/atmosphere/ocean interactions and land initialization (such as soil moisture, soil temperature, snow, aerosol in snow, etc.) at sub-seasonal to seasonal, to decadal time scales; and (4) application and analyses of large scale field data and observational networks (such as FLUXNET), satellite remote sensing, and reanalyses data for land model development and land/atmosphere/ocean interaction studies. We welcome papers addressing any of these topics.

During the last three decades many hydrometeorological field and numerical studies have been done in the Amazonia region by researchers from Brazil, Europe, and the United States. This conference session invites contributions related hydrometeorological processes in the Amazonia region. Contributions are welcome to report on analyses and interpretation of historical data sets. Results from numerical modeling studies are particularly welcome. Conference presentations that evaluate the water budget components and address the physical mechanisms involved in precipitation recycling in the Amazon basin are highly encouraged. Findings from studies that report on the interactions between surface processes and the hydrologic cycle, and effects of climate change and drought on the precipitation processes in the Amazon basin are of great interest.

Large reservoirs provide multiple benefits for water supply, downstream flood reduction, and environmental objectives.  Weather and climate forecasts play a critical role in helping reservoir operators balance multiple, often competing objectives. Accordingly, this session will highlight successful examples of collaborative development and application of forecasts to support reservoir management.

The connection between extreme rainfall and hydrologic extremes seems obvious, but recent research has shown the relationship to be complex and location-specific.  New observing technologies and real-time hydrologic models are improving our ability to monitor and predict droughts and floods.  Meanwhile, broad-brush assumptions about climate-driven trends in frequency and intensity of hydrologic extremes fail to capture the interplay between location characteristics, meteorology, soil conditions, and vegetation.  This session invites papers on all aspects of extreme rainfall, including their relationships to floods and to the termination of droughts, encompassing observations, modeling, short-term and seasonal prediction, climate change, and risk assessment.  Papers exploring the causes and consequences of individual extreme rainfall events that cause floods or terminate droughts, as well as the causes and consequences of changing drought, extreme rainfall, and flood risk are particularly encouraged.

This session highlights advances in the development and application of land data assimilation systems (LDAS), which merge ground- or satellite-based observations with estimates from land surface models. Contributions may include studies that evaluate or refine land DA methods, and/or assess the impact of the assimilation on the quality of LDAS products.  These LDAS products may focus on the simulation of the land surface itself, or dependent processes, and could include simulation of surface hydrology, the atmosphere, drought, agriculture, and/or water resources.  Contributions focussed on transition of research to operations are particularly encouraged, as are studies that explore assimilation of novel and/or multiple observation types. 

The connection between extreme rainfall and hydrologic extremes seems obvious, but recent research has shown the relationship to be complex and location-specific.  New observing technologies and real-time hydrologic models are improving our ability to monitor and predict droughts and floods.  Meanwhile, broad-brush assumptions about climate-driven trends in frequency and intensity of hydrologic extremes fail to capture the interplay between location characteristics, meteorology, soil conditions, and vegetation.  This session invites papers on all aspects of extreme rainfall, including their relationships to floods and to the termination of droughts, encompassing observations, modeling, short-term and seasonal prediction, climate change, and risk assessment.  Papers exploring the causes and consequences of individual extreme rainfall events that cause floods or terminate droughts, as well as the causes and consequences of changing drought, extreme rainfall, and flood risk are particularly encouraged.

This session highlights advances in the development and application of land data assimilation systems (LDAS), which merge ground- or satellite-based observations with estimates from land surface models. Contributions may include studies that evaluate or refine land DA methods, and/or assess the impact of the assimilation on the quality of LDAS products.  These LDAS products may focus on the simulation of the land surface itself, or dependent processes, and could include simulation of surface hydrology, the atmosphere, drought, agriculture, and/or water resources.  Contributions focussed on transition of research to operations are particularly encouraged, as are studies that explore assimilation of novel and/or multiple observation types.

This session covers broad topics such as integration of remote sensing data with land modeling, land model development, land cover/land use change. Invited keynote speaker: Inez Fung (UC-Berkeley). Session Chair: Xubin Zeng (Univ. of Arizona).

The connection between extreme rainfall and hydrologic extremes seems obvious, but recent research has shown the relationship to be complex and location-specific.  New observing technologies and real-time hydrologic models are improving our ability to monitor and predict droughts and floods.  Meanwhile, broad-brush assumptions about climate-driven trends in frequency and intensity of hydrologic extremes fail to capture the interplay between location characteristics, meteorology, soil conditions, and vegetation.  This session invites papers on all aspects of extreme rainfall, including their relationships to floods and to the termination of droughts, encompassing observations, modeling, short-term and seasonal prediction, climate change, and risk assessment.  Papers exploring the causes and consequences of individual extreme rainfall events that cause floods or terminate droughts, as well as the causes and consequences of changing drought, extreme rainfall, and flood risk are particularly encouraged.

Over the last several decades, substantial progress has been achieved in probabilistic hydrometeorological forecasting theories and applications. However, significant challenges still exist in assessing the uncertainty of complex hydrometeorological processes and improving hydrometeorological predictions, especially extreme hydrometeorological events. This session solicits papers that focus on, but not limit to, (1) addressing uncertainty in hydrometeorological forecasting from a number of sources in both offline and couple systems, and (2) innovative methods in hydrometeorological ensemble forecasting. The former includes uncertainties in forcing data (e.g., quantitative precipitation estimation and meteorological forcing data), initial conditions (e.g., soil moisture and snow status), parameters (e.g., land use and soil texture), model structure (e.g., assumptions, formulations and numerical solutions), and calibration (e.g., single-objective optimization and multi-objective optimizations).  The latter emphasizes integrated ensemble methods to improve hydrometeorological forecasting, verification methods to evaluate probabilistic forecasting, and statistical postprocessing techniques to generate hydrometeorological data products.

The connection between extreme rainfall and hydrologic extremes seems obvious, but recent research has shown the relationship to be complex and location-specific.  New observing technologies and real-time hydrologic models are improving our ability to monitor and predict droughts and floods.  Meanwhile, broad-brush assumptions about climate-driven trends in frequency and intensity of hydrologic extremes fail to capture the interplay between location characteristics, meteorology, soil conditions, and vegetation.  This session invites papers on all aspects of extreme rainfall, including their relationships to floods and to the termination of droughts, encompassing observations, modeling, short-term and seasonal prediction, climate change, and risk assessment.  Papers exploring the causes and consequences of individual extreme rainfall events that cause floods or terminate droughts, as well as the causes and consequences of changing drought, extreme rainfall, and flood risk are particularly encouraged.

Over the last several decades, substantial progress has been achieved in probabilistic hydrometeorological forecasting theories and applications. However, significant challenges still exist in assessing the uncertainty of complex hydrometeorological processes and improving hydrometeorological predictions, especially extreme hydrometeorological events. This session solicits papers that focus on, but not limit to, (1) addressing uncertainty in hydrometeorological forecasting from a number of sources in both offline and couple systems, and (2) innovative methods in hydrometeorological ensemble forecasting. The former includes uncertainties in forcing data (e.g., quantitative precipitation estimation and meteorological forcing data), initial conditions (e.g., soil moisture and snow status), parameters (e.g., land use and soil texture), model structure (e.g., assumptions, formulations and numerical solutions), and calibration (e.g., single-objective optimization and multi-objective optimizations).  The latter emphasizes integrated ensemble methods to improve hydrometeorological forecasting, verification methods to evaluate probabilistic forecasting, and statistical postprocessing techniques to generate hydrometeorological data products.

The economic impacts of hydrologic extremes (such as droughts or floods) are extensive and difficult to capture, however products such as the NCEI Billion dollar disasters report and map have greatly improved our ability to assess these damages and to help society appreciate the magnitude of these impacts by putting a dollar value on them. The human health impacts of hydrologic extremes are also extensive and difficult to capture, and we know that health maintenance is essential to a thriving society, yet there is no commensurate systemic assessment of the health impacts of hydrologic extremes. In this session, speakers should examine the myriad health impacts of these extremes--primarily droughts and floods--and examine what this means at a personal level. From this session, we hope to inspire a community effort to work toward understanding the health disaster of hydrologic extremes. One guiding question, to consider is: how do different groups communicate and manage public health risks related to flood and drought? This session will also put a human face on hydrologic extremes by also inviting practitioners to speak to their lived experiences in coping with recent disasters.

Over the last several decades, substantial progress has been achieved in probabilistic hydrometeorological forecasting theories and applications. However, significant challenges still exist in assessing the uncertainty of complex hydrometeorological processes and improving hydrometeorological predictions, especially extreme hydrometeorological events. This session solicits papers that focus on, but not limit to, (1) addressing uncertainty in hydrometeorological forecasting from a number of sources in both offline and couple systems, and (2) innovative methods in hydrometeorological ensemble forecasting. The former includes uncertainties in forcing data (e.g., quantitative precipitation estimation and meteorological forcing data), initial conditions (e.g., soil moisture and snow status), parameters (e.g., land use and soil texture), model structure (e.g., assumptions, formulations and numerical solutions), and calibration (e.g., single-objective optimization and multi-objective optimizations).  The latter emphasizes integrated ensemble methods to improve hydrometeorological forecasting, verification methods to evaluate probabilistic forecasting, and statistical postprocessing techniques to generate hydrometeorological data products.

Advances in the estimation of evapotranspiration (ET) and atmospheric evaporative demand (Eo) are made across a broad range of scales and techniques, from in-situ observations to remote sensing and modeling. Specific topics for this session may include but are not limited to: (1) estimating ET from various perspectives: remote sensing platforms, ground-based point observations and parameterizations, plant-based experimentation, and water budgets; (2) operational ET estimation; (3) land surface-atmosphere feedbacks; (4) future remote sensing missions and needs for ET; (5) Eo as an input to operational LSMs to derive ET, schedule crop irrigation, and as a metric of hydroclimatic trends and variability. New methods are emerging to more robustly partition total ET between evaporation and transpiration fluxes from both a modeling and a measurement perspective. We encourage papers with a focus on information conveyed by E and T, as well as ET. This year, recognizing that transpiration is regulated through vegetation hydrodynamics, we are particularly seeking submissions relating to both experimental and theoretical work linking plant hydrodynamics, ecology, hydrology, and meteorology. Understanding and simulating these hydraulic behaviors of vegetation and their outcomes, in terms of water and carbon flux, is key to improving land-surface and hydrologic models. Advances in remote sensing of water content and new databases compiling extensive monitoring records of site- and plant-level water flux and hydraulic trait data are poised for incorporation into such models through an emerging body of vegetation hydrodynamics modeling frameworks.

The connection between extreme rainfall and hydrologic extremes seems obvious, but recent research has shown the relationship to be complex and location-specific.  New observing technologies and real-time hydrologic models are improving our ability to monitor and predict droughts and floods.  Meanwhile, broad-brush assumptions about climate-driven trends in frequency and intensity of hydrologic extremes fail to capture the interplay between location characteristics, meteorology, soil conditions, and vegetation.  This session invites papers on all aspects of extreme rainfall, including their relationships to floods and to the termination of droughts, encompassing observations, modeling, short-term and seasonal prediction, climate change, and risk assessment.  Papers exploring the causes and consequences of individual extreme rainfall events that cause floods or terminate droughts, as well as the causes and consequences of changing drought, extreme rainfall, and flood risk are particularly encouraged.

This session highlights advances in the development and application of land data assimilation systems (LDAS), which merge ground- or satellite-based observations with estimates from land surface models. Contributions may include studies that evaluate or refine land DA methods, and/or assess the impact of the assimilation on the quality of LDAS products.  These LDAS products may focus on the simulation of the land surface itself, or dependent processes, and could include simulation of surface hydrology, the atmosphere, drought, agriculture, and/or water resources.  Contributions focussed on transition of research to operations are particularly encouraged, as are studies that explore assimilation of novel and/or multiple observation types.

Advances in the estimation of evapotranspiration (ET) and atmospheric evaporative demand (Eo) are made across a broad range of scales and techniques, from in-situ observations to remote sensing and modeling. Specific topics for this session may include but are not limited to: (1) estimating ET from various perspectives: remote sensing platforms, ground-based point observations and parameterizations, plant-based experimentation, and water budgets; (2) operational ET estimation; (3) land surface-atmosphere feedbacks; (4) future remote sensing missions and needs for ET; (5) Eo as an input to operational LSMs to derive ET, schedule crop irrigation, and as a metric of hydroclimatic trends and variability. New methods are emerging to more robustly partition total ET between evaporation and transpiration fluxes from both a modeling and a measurement perspective. We encourage papers with a focus on information conveyed by E and T, as well as ET. This year, recognizing that transpiration is regulated through vegetation hydrodynamics, we are particularly seeking submissions relating to both experimental and theoretical work linking plant hydrodynamics, ecology, hydrology, and meteorology. Understanding and simulating these hydraulic behaviors of vegetation and their outcomes, in terms of water and carbon flux, is key to improving land-surface and hydrologic models. Advances in remote sensing of water content and new databases compiling extensive monitoring records of site- and plant-level water flux and hydraulic trait data are poised for incorporation into such models through an emerging body of vegetation hydrodynamics modeling frameworks.

The economic impacts of hydrologic extremes (such as droughts or floods) are extensive and difficult to capture, however products such as the NCEI Billion dollar disasters report and map have greatly improved our ability to assess these damages and to help society appreciate the magnitude of these impacts by putting a dollar value on them. The human health impacts of hydrologic extremes are also extensive and difficult to capture, and we know that health maintenance is essential to a thriving society, yet there is no commensurate systemic assessment of the health impacts of hydrologic extremes. In this session, speakers should examine the myriad health impacts of these extremes--primarily droughts and floods--and examine what this means at a personal level. From this session, we hope to inspire a community effort to work toward understanding the health disaster of hydrologic extremes. One guiding question, to consider is: how do different groups communicate and manage public health risks related to flood and drought? This session will also put a human face on hydrologic extremes by also inviting practitioners to speak to their lived experiences in coping with recent disasters.

Advances in the estimation of evapotranspiration (ET) and atmospheric evaporative demand (Eo) are made across a broad range of scales and techniques, from in-situ observations to remote sensing and modeling. Specific topics for this session may include but are not limited to: (1) estimating ET from various perspectives: remote sensing platforms, ground-based point observations and parameterizations, plant-based experimentation, and water budgets; (2) operational ET estimation; (3) land surface-atmosphere feedbacks; (4) future remote sensing missions and needs for ET; (5) Eo as an input to operational LSMs to derive ET, schedule crop irrigation, and as a metric of hydroclimatic trends and variability. New methods are emerging to more robustly partition total ET between evaporation and transpiration fluxes from both a modeling and a measurement perspective. We encourage papers with a focus on information conveyed by E and T, as well as ET. This year, recognizing that transpiration is regulated through vegetation hydrodynamics, we are particularly seeking submissions relating to both experimental and theoretical work linking plant hydrodynamics, ecology, hydrology, and meteorology. Understanding and simulating these hydraulic behaviors of vegetation and their outcomes, in terms of water and carbon flux, is key to improving land-surface and hydrologic models. Advances in remote sensing of water content and new databases compiling extensive monitoring records of site- and plant-level water flux and hydraulic trait data are poised for incorporation into such models through an emerging body of vegetation hydrodynamics modeling frameworks.

In snow-dominated basins across the globe, efficient water resource management requires accurate, timely estimates of both snow water equivalent (SWE) and snow melt onset. Melting snow provides a reliable water supply and can also produce wide-scale flooding hazards, particularly when combined with rainfall. An accurate estimate of snow volume, melt timing and the spatial distribution of both parameters is important for predicting runoff response for water resource and hydropower management as well as providing insight into important ecological and biogeochemical processes.  Remote sensing and modeling techniques provide methods for observing and detecting snow evolution, onset of snowmelt, spatial extent of melt processes, and vulnerability to extreme flood hazards that may result.  Both existing and novel remote sensing techniques have been developed to estimate snow evolution timing including the detection of liquid water in the snowpack.  Snow reconstruction and energy balance snow models have shown the ability to estimate snow properties, such as snow volume, liquid water content and melt. Observational, in-situ datasets that drive these models with meteorological inputs and modify the model through data assimilation techniques are critical in accurately portraying the natural phenomena of snow evolution. Reanalysis datasets have also proven valuable to forensically investigate large flooding events caused by snow melt. This session invites interdisciplinary research on existing and novel methods for remote sensing, modeling, and data assimilation of snow evolution, particularly snow melt timing and efforts linked to increased volume of discharge for water resource and hydropower management as well as resiliency and vulnerability to extreme flood events.

Although rainfall accounts for 25% of tropical cyclone-related fatalities in the United States, the threat of rainfall is somewhat underestimated in comparison to other hazards. Furthermore, rainfall is an interdisciplinary hazard, from the remaining unknowns in the underlying physics, to the effect on downstream hazards, and the difficulties associated with decision making. In terms of physical processes, rainfall is a complex mixture of drop creation, growth, and seeding by frozen hydrometeors, where the kinematic and thermodynamic environment determine the relative contributions of warm rain and ice phase microphysical processes and the ultimate particle trajectories. In addition, external influences such as vertical wind shear and topography can modify the azimuthal distribution of rainfall intensity and microphysical processes. After the rain reaches the ground, flooding, landslides, and river runoff are dangerous hazards that cause both fatalities and economic losses. Other indirect consequences of heavy rainfall, such as disruption of local transit networks, can negatively affect response and recovery efforts. Finally, forecast uncertainty due to model error, insufficient model resolution, and microphysical deficiencies make the communication of the rainfall threat challenging.

The proposed session would solicit abstracts on the aforementioned topics, with a specific interest in recent tropical cyclones (e.g., Hurricanes Harvey 2017, Florence 2018, Maria 2017, Lane 2018, Typhoon Mangkhut 2018, Tropical Cyclone Idai 2019). Ideally, the session would solicit abstracts on a variety of topics, including but not limited to: observational and modeling research, emergency management and decision-making studies, and forecasting successes and failures. We hope to take advantage of the diverse attendees to have a conversation about the complicated and interdisciplinary nature of tropical cyclone rainfall understanding, prediction, and mitigation.

This session will advance the use of satellite and airborne Earth observations, ground observational networks and modeling tools to support decision in agriculture and food security. Topics of interest include, but are not limited to crop monitoring, yield estimation, crop modeling, agricultural water availability and use, food security, irrigation and fertilization management, land use change impact, climate sensitive regions, sustainable development, natural resource optimization, multi-spectral/resolution/platform remote sensing data, big Earth data solutions and cloud-computing. Presentations and open discussions will highlight stakeholder and end-users engagement in research and applications to strengthen co-development, innovation and the wider application of research.

Global warming is expected to intensify the hydrological cycle and lead to more frequent and intense precipitation events. Projections of more intense rainfall events naturally lead to assumptions that flooding in human communities will also increase, but flood response to precipitation events can vary widely. While urban areas have many impervious surfaces and thus high runoff ratios, river response to rainfall events over rural and natural land cover is strongly mediated by watershed antecedent conditions. For example, heavy precipitation may not produce flooding during warm season months when soil moisture is low and evapotranspiration is high. Conversely, moderate rain events can generate large floods if they fall on snow and frozen ground, or on saturated ground during leaf-off conditions. Further complicating our ability to predict how changes in precipitation will translate to river floods is the potential for climate change to affect these mediating influences—like changing the phenology of deciduous plants or reducing snow cover. Human communities and infrastructure are found across watersheds with a wide range of land cover types from natural to urban, and thus are exposed to both urban and river flooding. Thus a major challenge for developing flood-resilient communities in response to future climate change is understanding both kinds of flood response to heavy precipitation, and how they may interact in different environments. This session seeks contributions addressing recent research advances, technological developments, and management practices associated with flood response to heavy precipitation events expected with climate change. Topics of interest include (but are not limited to): understanding urban flooding dynamics under heavy precipitation, examining the relationship between precipitation magnitude or intensity and river flood magnitude, predicting urban and more natural river floods under climate change, understanding and/or predicting compound flood risks in urban settings, and flooding risk assessment and communication.

Global warming is expected to intensify the hydrological cycle and lead to more frequent and intense precipitation events. Projections of more intense rainfall events naturally lead to assumptions that flooding in human communities will also increase, but flood response to precipitation events can vary widely. While urban areas have many impervious surfaces and thus high runoff ratios, river response to rainfall events over rural and natural land cover is strongly mediated by watershed antecedent conditions. For example, heavy precipitation may not produce flooding during warm season months when soil moisture is low and evapotranspiration is high. Conversely, moderate rain events can generate large floods if they fall on snow and frozen ground, or on saturated ground during leaf-off conditions. Further complicating our ability to predict how changes in precipitation will translate to river floods is the potential for climate change to affect these mediating influences—like changing the phenology of deciduous plants or reducing snow cover. Human communities and infrastructure are found across watersheds with a wide range of land cover types from natural to urban, and thus are exposed to both urban and river flooding. Thus a major challenge for developing flood-resilient communities in response to future climate change is understanding both kinds of flood response to heavy precipitation, and how they may interact in different environments. This session seeks contributions addressing recent research advances, technological developments, and management practices associated with flood response to heavy precipitation events expected with climate change. Topics of interest include (but are not limited to): understanding urban flooding dynamics under heavy precipitation, examining the relationship between precipitation magnitude or intensity and river flood magnitude, predicting urban and more natural river floods under climate change, understanding and/or predicting compound flood risks in urban settings, and flooding risk assessment and communication.

This session will advance the use of satellite and airborne Earth observations, ground observational networks and modeling tools to support decision in agriculture and food security. Topics of interest include, but are not limited to crop monitoring, yield estimation, crop modeling, agricultural water availability and use, food security, irrigation and fertilization management, land use change impact, climate sensitive regions, sustainable development, natural resource optimization, multi-spectral/resolution/platform remote sensing data, big Earth data solutions and cloud-computing. Presentations and open discussions will highlight stakeholder and end-users engagement in research and applications to strengthen co-development, innovation and the wider application of research.

The environmental and economic consequences of drought are among the most serious of all natural disasters. However, not all droughts are the same. The onset and intensification of drought can occur at exceptionally rapid rates. Such events, called flash droughts can precede long term drought with both types of drought resulting in devastating impacts on agriculture, depletion of water resources, and through placing excessive moisture stress on both managed and natural ecosystems. In a warming climate, drought is expected to increase in frequency, duration, and intensity at both regional and global scales. Improving analysis and prediction of all drought types requires the combination of multiple data sources, including remote sensing data, surface observations, and even indicators of societal impact. Satellite hydrological variables and vegetation indices have contributed dramatically to understand the mechanisms of drought occurrence and development, as well as de-couple the drought signals from normal hydrological conditions and vegetation status. Remotely sensed land observations are used to force or parameterize models, and the hydrological outputs provide the foundation for existing drought indicators. However, taking drought monitoring and prediction to the next level not only requires advances in understanding drought mechanisms, but also the societal impacts and how to better manage water resources. There are still many open scientific questions related to data fusion, integration of drought indicators, emerging social media data sources and the optimal combination of these data sets for providing insights to climate, environmental and societal changes with respect to drought events. This session invites submissions that advance our understanding of the causes and characteristics of both flash drought and long term drought, through climatological analyses, case studies of recent events, impacts of land-atmosphere interactions, and numerical simulations. Application of remote sensing land observations, social media data or the fusion of the two for understanding, monitoring and predicting drought are especially encouraged.

The precipitation session focuses on precipitation observation, modeling, estimation, and applications of in-situ and remotely sensed precipitation products. Topics include, but are not limited to (1) precipitation processes and modeling; (2) advances in remote sensing of precipitation from satellite, airborne, and ground-based platforms; (3) recent development pertaining to fusion and downscaling of precipitation products; (4) assimilation of precipitation and precipitation-related variables in weather or water models; (5) impact of uncertainties associated with precipitation observations on hydrologic design and modeling, (6) assessment of precipitation variability, including extremes, across scales.

In snow-dominated basins across the globe, efficient water resource management requires accurate, timely estimates of both snow water equivalent (SWE) and snow melt onset. Melting snow provides a reliable water supply and can also produce wide-scale flooding hazards, particularly when combined with rainfall. An accurate estimate of snow volume, melt timing and the spatial distribution of both parameters is important for predicting runoff response for water resource and hydropower management as well as providing insight into important ecological and biogeochemical processes.  Remote sensing and modeling techniques provide methods for observing and detecting snow evolution, onset of snowmelt, spatial extent of melt processes, and vulnerability to extreme flood hazards that may result.  Both existing and novel remote sensing techniques have been developed to estimate snow evolution timing including the detection of liquid water in the snowpack.  Snow reconstruction and energy balance snow models have shown the ability to estimate snow properties, such as snow volume, liquid water content and melt. Observational, in-situ datasets that drive these models with meteorological inputs and modify the model through data assimilation techniques are critical in accurately portraying the natural phenomena of snow evolution. Reanalysis datasets have also proven valuable to forensically investigate large flooding events caused by snow melt. This session invites interdisciplinary research on existing and novel methods for remote sensing, modeling, and data assimilation of snow evolution, particularly snow melt timing and efforts linked to increased volume of discharge for water resource and hydropower management as well as resiliency and vulnerability to extreme flood events.

This session will advance the use of satellite and airborne Earth observations, ground observational networks and modeling tools to support decision in agriculture and food security. Topics of interest include, but are not limited to crop monitoring, yield estimation, crop modeling, agricultural water availability and use, food security, irrigation and fertilization management, land use change impact, climate sensitive regions, sustainable development, natural resource optimization, multi-spectral/resolution/platform remote sensing data, big Earth data solutions and cloud-computing. Presentations and open discussions will highlight stakeholder and end-users engagement in research and applications to strengthen co-development, innovation and the wider application of research.

Global warming is expected to intensify the hydrological cycle and lead to more frequent and intense precipitation events. Projections of more intense rainfall events naturally lead to assumptions that flooding in human communities will also increase, but flood response to precipitation events can vary widely. While urban areas have many impervious surfaces and thus high runoff ratios, river response to rainfall events over rural and natural land cover is strongly mediated by watershed antecedent conditions. For example, heavy precipitation may not produce flooding during warm season months when soil moisture is low and evapotranspiration is high. Conversely, moderate rain events can generate large floods if they fall on snow and frozen ground, or on saturated ground during leaf-off conditions. Further complicating our ability to predict how changes in precipitation will translate to river floods is the potential for climate change to affect these mediating influences—like changing the phenology of deciduous plants or reducing snow cover. Human communities and infrastructure are found across watersheds with a wide range of land cover types from natural to urban, and thus are exposed to both urban and river flooding. Thus a major challenge for developing flood-resilient communities in response to future climate change is understanding both kinds of flood response to heavy precipitation, and how they may interact in different environments. This session seeks contributions addressing recent research advances, technological developments, and management practices associated with flood response to heavy precipitation events expected with climate change. Topics of interest include (but are not limited to): understanding urban flooding dynamics under heavy precipitation, examining the relationship between precipitation magnitude or intensity and river flood magnitude, predicting urban and more natural river floods under climate change, understanding and/or predicting compound flood risks in urban settings, and flooding risk assessment and communication.

This session will advance the use of satellite and airborne Earth observations, ground observational networks and modeling tools to support decision in agriculture and food security. Topics of interest include, but are not limited to crop monitoring, yield estimation, crop modeling, agricultural water availability and use, food security, irrigation and fertilization management, land use change impact, climate sensitive regions, sustainable development, natural resource optimization, multi-spectral/resolution/platform remote sensing data, big Earth data solutions and cloud-computing. Presentations and open discussions will highlight stakeholder and end-users engagement in research and applications to strengthen co-development, innovation and the wider application of research.

The precipitation session focuses on precipitation observation, modeling, estimation, and applications of in-situ and remotely sensed precipitation products. Topics include, but are not limited to (1) precipitation processes and modeling; (2) advances in remote sensing of precipitation from satellite, airborne, and ground-based platforms; (3) recent development pertaining to fusion and downscaling of precipitation products; (4) assimilation of precipitation and precipitation-related variables in weather or water models; (5) impact of uncertainties associated with precipitation observations on hydrologic design and modeling, (6) assessment of precipitation variability, including extremes, across scales.

The environmental and economic consequences of drought are among the most serious of all natural disasters. However, not all droughts are the same. The onset and intensification of drought can occur at exceptionally rapid rates. Such events, called flash droughts can precede long term drought with both types of drought resulting in devastating impacts on agriculture, depletion of water resources, and through placing excessive moisture stress on both managed and natural ecosystems. In a warming climate, drought is expected to increase in frequency, duration, and intensity at both regional and global scales. Improving analysis and prediction of all drought types requires the combination of multiple data sources, including remote sensing data, surface observations, and even indicators of societal impact. Satellite hydrological variables and vegetation indices have contributed dramatically to understand the mechanisms of drought occurrence and development, as well as de-couple the drought signals from normal hydrological conditions and vegetation status. Remotely sensed land observations are used to force or parameterize models, and the hydrological outputs provide the foundation for existing drought indicators. However, taking drought monitoring and prediction to the next level not only requires advances in understanding drought mechanisms, but also the societal impacts and how to better manage water resources. There are still many open scientific questions related to data fusion, integration of drought indicators, emerging social media data sources and the optimal combination of these data sets for providing insights to climate, environmental and societal changes with respect to drought events. This session invites submissions that advance our understanding of the causes and characteristics of both flash drought and long term drought, through climatological analyses, case studies of recent events, impacts of land-atmosphere interactions, and numerical simulations. Application of remote sensing land observations, social media data or the fusion of the two for understanding, monitoring and predicting drought are especially encouraged.

The precipitation session focuses on precipitation observation, modeling, estimation, and applications of in-situ and remotely sensed precipitation products. Topics include, but are not limited to (1) precipitation processes and modeling; (2) advances in remote sensing of precipitation from satellite, airborne, and ground-based platforms; (3) recent development pertaining to fusion and downscaling of precipitation products; (4) assimilation of precipitation and precipitation-related variables in weather or water models; (5) impact of uncertainties associated with precipitation observations on hydrologic design and modeling, (6) assessment of precipitation variability, including extremes, across scales.

The environmental and economic consequences of drought are among the most serious of all natural disasters. However, not all droughts are the same. The onset and intensification of drought can occur at exceptionally rapid rates. Such events, called flash droughts can precede long term drought with both types of drought resulting in devastating impacts on agriculture, depletion of water resources, and through placing excessive moisture stress on both managed and natural ecosystems. In a warming climate, drought is expected to increase in frequency, duration, and intensity at both regional and global scales. Improving analysis and prediction of all drought types requires the combination of multiple data sources, including remote sensing data, surface observations, and even indicators of societal impact. Satellite hydrological variables and vegetation indices have contributed dramatically to understand the mechanisms of drought occurrence and development, as well as de-couple the drought signals from normal hydrological conditions and vegetation status. Remotely sensed land observations are used to force or parameterize models, and the hydrological outputs provide the foundation for existing drought indicators. However, taking drought monitoring and prediction to the next level not only requires advances in understanding drought mechanisms, but also the societal impacts and how to better manage water resources. There are still many open scientific questions related to data fusion, integration of drought indicators, emerging social media data sources and the optimal combination of these data sets for providing insights to climate, environmental and societal changes with respect to drought events. This session invites submissions that advance our understanding of the causes and characteristics of both flash drought and long term drought, through climatological analyses, case studies of recent events, impacts of land-atmosphere interactions, and numerical simulations. Application of remote sensing land observations, social media data or the fusion of the two for understanding, monitoring and predicting drought are especially encouraged.

The precipitation session focuses on precipitation observation, modeling, estimation, and applications of in-situ and remotely sensed precipitation products. Topics include, but are not limited to (1) precipitation processes and modeling; (2) advances in remote sensing of precipitation from satellite, airborne, and ground-based platforms; (3) recent development pertaining to fusion and downscaling of precipitation products; (4) assimilation of precipitation and precipitation-related variables in weather or water models; (5) impact of uncertainties associated with precipitation observations on hydrologic design and modeling, (6) assessment of precipitation variability, including extremes, across scales.

This will be a joint session between the 26th Conference on Numerical Weather Prediction (26NWP) and 34th Conference on Hydrology (34HYDRO).  We welcome abstracts on topics including (but not limited to) coupled atmosphere-hydrological models and automated guidance for atmospheric rivers, flash floods, and other hydrometeorological extremes.