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Abstract
In the Bay of Bengal, the warm, dry boreal spring concludes with the onset of the summer monsoon and accompanying southwesterly winds, heavy rains, and variable air–sea fluxes. Here, we summarize the 2018 monsoon onset using observations collected through the multinational Monsoon Intraseasonal Oscillations in the Bay of Bengal (MISO-BoB) program between the United States, India, and Sri Lanka. MISO-BoB aims to improve understanding of monsoon intraseasonal variability, and the 2018 field effort captured the coupled air–sea response during a transition from active-to-break conditions in the central BoB. The active phase of the ∼20-day research cruise was characterized by warm sea surface temperature (SST > 30°C), cold atmospheric outflows with intermittent heavy rainfall, and increasing winds (from 2 to 15 m s−1). Accumulated rainfall exceeded 200 mm with 90% of precipitation occurring during the first week. The following break period was both dry and clear, with persistent 10–12 m s−1 wind and evaporation of 0.2 mm h−1. The evolving environmental state included a deepening ocean mixed layer (from ∼20 to 50 m), cooling SST (by ∼1°C), and warming/drying of the lower to midtroposphere. Local atmospheric development was consistent with phasing of the large-scale intraseasonal oscillation. The upper ocean stores significant heat in the BoB, enough to maintain SST above 29°C despite cooling by surface fluxes and ocean mixing. Comparison with reanalysis indicates biases in air–sea fluxes, which may be related to overly cool prescribed SST. Resolution of such biases offers a path toward improved forecasting of transition periods in the monsoon.
Abstract
In the Bay of Bengal, the warm, dry boreal spring concludes with the onset of the summer monsoon and accompanying southwesterly winds, heavy rains, and variable air–sea fluxes. Here, we summarize the 2018 monsoon onset using observations collected through the multinational Monsoon Intraseasonal Oscillations in the Bay of Bengal (MISO-BoB) program between the United States, India, and Sri Lanka. MISO-BoB aims to improve understanding of monsoon intraseasonal variability, and the 2018 field effort captured the coupled air–sea response during a transition from active-to-break conditions in the central BoB. The active phase of the ∼20-day research cruise was characterized by warm sea surface temperature (SST > 30°C), cold atmospheric outflows with intermittent heavy rainfall, and increasing winds (from 2 to 15 m s−1). Accumulated rainfall exceeded 200 mm with 90% of precipitation occurring during the first week. The following break period was both dry and clear, with persistent 10–12 m s−1 wind and evaporation of 0.2 mm h−1. The evolving environmental state included a deepening ocean mixed layer (from ∼20 to 50 m), cooling SST (by ∼1°C), and warming/drying of the lower to midtroposphere. Local atmospheric development was consistent with phasing of the large-scale intraseasonal oscillation. The upper ocean stores significant heat in the BoB, enough to maintain SST above 29°C despite cooling by surface fluxes and ocean mixing. Comparison with reanalysis indicates biases in air–sea fluxes, which may be related to overly cool prescribed SST. Resolution of such biases offers a path toward improved forecasting of transition periods in the monsoon.
ABSTRACT
Life on Earth vitally depends on the availability of water. Human pressure on freshwater resources is increasing, as is human exposure to weather-related extremes (droughts, storms, floods) caused by climate change. Understanding these changes is pivotal for developing mitigation and adaptation strategies. The Global Climate Observing System (GCOS) defines a suite of essential climate variables (ECVs), many related to the water cycle, required to systematically monitor Earth’s climate system. Since long-term observations of these ECVs are derived from different observation techniques, platforms, instruments, and retrieval algorithms, they often lack the accuracy, completeness, and resolution, to consistently characterize water cycle variability at multiple spatial and temporal scales. Here, we review the capability of ground-based and remotely sensed observations of water cycle ECVs to consistently observe the hydrological cycle. We evaluate the relevant land, atmosphere, and ocean water storages and the fluxes between them, including anthropogenic water use. Particularly, we assess how well they close on multiple temporal and spatial scales. On this basis, we discuss gaps in observation systems and formulate guidelines for future water cycle observation strategies. We conclude that, while long-term water cycle monitoring has greatly advanced in the past, many observational gaps still need to be overcome to close the water budget and enable a comprehensive and consistent assessment across scales. Trends in water cycle components can only be observed with great uncertainty, mainly due to insufficient length and homogeneity. An advanced closure of the water cycle requires improved model–data synthesis capabilities, particularly at regional to local scales.
ABSTRACT
Life on Earth vitally depends on the availability of water. Human pressure on freshwater resources is increasing, as is human exposure to weather-related extremes (droughts, storms, floods) caused by climate change. Understanding these changes is pivotal for developing mitigation and adaptation strategies. The Global Climate Observing System (GCOS) defines a suite of essential climate variables (ECVs), many related to the water cycle, required to systematically monitor Earth’s climate system. Since long-term observations of these ECVs are derived from different observation techniques, platforms, instruments, and retrieval algorithms, they often lack the accuracy, completeness, and resolution, to consistently characterize water cycle variability at multiple spatial and temporal scales. Here, we review the capability of ground-based and remotely sensed observations of water cycle ECVs to consistently observe the hydrological cycle. We evaluate the relevant land, atmosphere, and ocean water storages and the fluxes between them, including anthropogenic water use. Particularly, we assess how well they close on multiple temporal and spatial scales. On this basis, we discuss gaps in observation systems and formulate guidelines for future water cycle observation strategies. We conclude that, while long-term water cycle monitoring has greatly advanced in the past, many observational gaps still need to be overcome to close the water budget and enable a comprehensive and consistent assessment across scales. Trends in water cycle components can only be observed with great uncertainty, mainly due to insufficient length and homogeneity. An advanced closure of the water cycle requires improved model–data synthesis capabilities, particularly at regional to local scales.
Abstract
Uncertainty is everywhere and understanding how individuals understand and use forecast information to make decisions given varying levels of certainty is crucial for effectively communicating risks and weather hazards. To advance prior research about how various audiences use and understand probabilistic and deterministic hydrologic forecast information, a social science study involving multiple scenario-based focus groups and surveys at four locations (Eureka, California; Gunnison, Colorado; Durango, Colorado; Owego, New York) across the United States was conducted with professionals and residents. Focusing on the Hydrologic Ensemble Forecast System, the Advanced Hydrologic Prediction Service, and briefings, this research investigated how users tolerate divergence in probabilistic and deterministic forecasts and how deterministic and probabilistic river level forecasts can be presented simultaneously without causing confusion. This study found that probabilistic forecasts introduce a tremendous amount of new, yet valuable, information but can quickly overwhelm users based on how they are conveyed and communicated. Some were unaware of resources available, or how to find, sort, and prioritize among all the data and information. Importantly, when presented with a divergence between deterministic and probabilistic forecasts, most sought out more information while some others reported diminished confidence in the products. Users in all regions expressed a desire to “ground truth” the accuracy of probabilistic forecasts, understand the drivers of the forecasts, and become more familiar with them. In addition, a prototype probabilistic product that includes a deterministic forecast was tested, and suggestions for communicating probabilistic information through the use of briefing packages is proposed.
Abstract
Uncertainty is everywhere and understanding how individuals understand and use forecast information to make decisions given varying levels of certainty is crucial for effectively communicating risks and weather hazards. To advance prior research about how various audiences use and understand probabilistic and deterministic hydrologic forecast information, a social science study involving multiple scenario-based focus groups and surveys at four locations (Eureka, California; Gunnison, Colorado; Durango, Colorado; Owego, New York) across the United States was conducted with professionals and residents. Focusing on the Hydrologic Ensemble Forecast System, the Advanced Hydrologic Prediction Service, and briefings, this research investigated how users tolerate divergence in probabilistic and deterministic forecasts and how deterministic and probabilistic river level forecasts can be presented simultaneously without causing confusion. This study found that probabilistic forecasts introduce a tremendous amount of new, yet valuable, information but can quickly overwhelm users based on how they are conveyed and communicated. Some were unaware of resources available, or how to find, sort, and prioritize among all the data and information. Importantly, when presented with a divergence between deterministic and probabilistic forecasts, most sought out more information while some others reported diminished confidence in the products. Users in all regions expressed a desire to “ground truth” the accuracy of probabilistic forecasts, understand the drivers of the forecasts, and become more familiar with them. In addition, a prototype probabilistic product that includes a deterministic forecast was tested, and suggestions for communicating probabilistic information through the use of briefing packages is proposed.
Abstract
In 1976, a pilot experiment, called first Equatorial Mooring (EQUA-1), tested an innovative technique for anchoring a taut-line surface mooring at 0°, 150°W where the water depth is 4.5 km. The 36-day deployment contained a wind recorder and fixed-level current meters at 50 and 100 m in the Equatorial Undercurrent (EUC). The following year, in a second pilot experiment, named EQUA-2, a similar mooring was deployed at 0°, 125°W for 99 days. EQUA-2, with current meters at 10, 50, 100, 150, and 200 m, recorded a surge in EUC transport during April 1977 when 3-day-averaged eastward current speeds at 50-m depth reached 2 m s−1. The associated eastward transport per unit meridional width over the 50–200-m layer was 190 m2 s−1. Based on observations recorded in April 1980, the EQUA-2 pulse would correspond to a total EUC transport surge of about 38 Sv (1 Sv ≡ 106 m3 s−1) and would represent an equatorially trapped first-mode baroclinic Kelvin wave. This paper describes EQUA Project observations and why and how I created the high-risk-of-failure opportunity to record pioneering time series measurements at the equator. The enduring legacy of the EQUA Project is the sustained maintenance of in situ surface wind and upper-ocean current and temperature measurements at numerous sites in the equatorial oceans, starting in the Pacific to improve forecasts of the El Niño and La Niña phenomenon. For example, the 40-yr records of surface wind and upper-ocean current and temperature measurements at 0°, 110°W and 0°, 140°W are some of oceanography’s longest time series recorded far from land.
Abstract
In 1976, a pilot experiment, called first Equatorial Mooring (EQUA-1), tested an innovative technique for anchoring a taut-line surface mooring at 0°, 150°W where the water depth is 4.5 km. The 36-day deployment contained a wind recorder and fixed-level current meters at 50 and 100 m in the Equatorial Undercurrent (EUC). The following year, in a second pilot experiment, named EQUA-2, a similar mooring was deployed at 0°, 125°W for 99 days. EQUA-2, with current meters at 10, 50, 100, 150, and 200 m, recorded a surge in EUC transport during April 1977 when 3-day-averaged eastward current speeds at 50-m depth reached 2 m s−1. The associated eastward transport per unit meridional width over the 50–200-m layer was 190 m2 s−1. Based on observations recorded in April 1980, the EQUA-2 pulse would correspond to a total EUC transport surge of about 38 Sv (1 Sv ≡ 106 m3 s−1) and would represent an equatorially trapped first-mode baroclinic Kelvin wave. This paper describes EQUA Project observations and why and how I created the high-risk-of-failure opportunity to record pioneering time series measurements at the equator. The enduring legacy of the EQUA Project is the sustained maintenance of in situ surface wind and upper-ocean current and temperature measurements at numerous sites in the equatorial oceans, starting in the Pacific to improve forecasts of the El Niño and La Niña phenomenon. For example, the 40-yr records of surface wind and upper-ocean current and temperature measurements at 0°, 110°W and 0°, 140°W are some of oceanography’s longest time series recorded far from land.
Abstract
Cities increasingly recognize the importance of shade to reduce heat stress and adopt urban forestry plans with ambitious canopy goals. Yet, the implementation of tree and shade plans often faces maintenance, water use, and infrastructure challenges. Understanding the performance of natural and nonnatural shade is critical to support active shade management in the built environment. We conducted hourly transects in Tempe, Arizona, with the mobile human-biometeorological station MaRTy on hot summer days to quantify the efficacy of various shade types. We sampled sun-exposed reference locations and shade types grouped by urban form, lightweight/engineered shade, and tree species over multiple ground surfaces. We investigated shade performance during the day, at peak incoming solar, at peak air temperature, and after sunset using three thermal metrics: the difference between a shaded and sun-exposed location in air temperature (∆T a ), surface temperature (∆T s ), and mean radiant temperature (∆T MRT). Air temperature did not vary significantly between shade groups, but ∆T MRT spanned a 50°C range across observations. At daytime, shade from urban form most effectively reduced T s and T MRT, followed by trees and lightweight structures. Shade from urban form performed differently with changing orientation. Tree shade performance varied widely; native and palm trees were least effective, while nonnative trees were most effective. All shade types exhibited heat retention (positive ∆T MRT) after sunset. Based on the observations, we developed characteristic shade performance curves that will inform the City of Tempe’s design guidelines toward using “the right shade in the right place” and form the basis for the development of microclimate zones (MCSz).
Abstract
Cities increasingly recognize the importance of shade to reduce heat stress and adopt urban forestry plans with ambitious canopy goals. Yet, the implementation of tree and shade plans often faces maintenance, water use, and infrastructure challenges. Understanding the performance of natural and nonnatural shade is critical to support active shade management in the built environment. We conducted hourly transects in Tempe, Arizona, with the mobile human-biometeorological station MaRTy on hot summer days to quantify the efficacy of various shade types. We sampled sun-exposed reference locations and shade types grouped by urban form, lightweight/engineered shade, and tree species over multiple ground surfaces. We investigated shade performance during the day, at peak incoming solar, at peak air temperature, and after sunset using three thermal metrics: the difference between a shaded and sun-exposed location in air temperature (∆T a ), surface temperature (∆T s ), and mean radiant temperature (∆T MRT). Air temperature did not vary significantly between shade groups, but ∆T MRT spanned a 50°C range across observations. At daytime, shade from urban form most effectively reduced T s and T MRT, followed by trees and lightweight structures. Shade from urban form performed differently with changing orientation. Tree shade performance varied widely; native and palm trees were least effective, while nonnative trees were most effective. All shade types exhibited heat retention (positive ∆T MRT) after sunset. Based on the observations, we developed characteristic shade performance curves that will inform the City of Tempe’s design guidelines toward using “the right shade in the right place” and form the basis for the development of microclimate zones (MCSz).
Abstract
To address the need to map precipitation on a global scale, a collection of satellites carrying passive microwave (PMW) radiometers has grown over the last 20 years to form a constellation of about 10–12 sensors at any one time. Over the same period, a broad range of science and user communities has become increasingly dependent on the precipitation products provided by these sensors. The constellation presently consists of both conical and cross-track-scanning precipitation-capable multichannel instruments, many of which are beyond their operational and design lifetime but continue to operate through the cooperation of the responsible agencies. The Group on Earth Observations and the Coordinating Group for Meteorological Satellites (CGMS), among other groups, have raised the issue of how a robust, future precipitation constellation should be constructed. The key issues of current and future requirements for the mapping of global precipitation from satellite sensors can be summarized as providing 1) sufficiently fine spatial resolutions to capture precipitation-scale systems and reduce the beam-filling effects of the observations; 2) a wide channel diversity for each sensor to cover the range of precipitation types, characteristics, and intensities observed across the globe; 3) an observation interval that provides temporal sampling commensurate with the variability of precipitation; and 4) precipitation radars and radiometers in low-inclination orbit to provide a consistent calibration source, as demonstrated by the first two spaceborne radar–radiometer combinations on the Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Measurement (GPM) mission Core Observatory. These issues are critical in determining the direction of future constellation requirements while preserving the continuity of the existing constellation necessary for long-term climate-scale studies.
Abstract
To address the need to map precipitation on a global scale, a collection of satellites carrying passive microwave (PMW) radiometers has grown over the last 20 years to form a constellation of about 10–12 sensors at any one time. Over the same period, a broad range of science and user communities has become increasingly dependent on the precipitation products provided by these sensors. The constellation presently consists of both conical and cross-track-scanning precipitation-capable multichannel instruments, many of which are beyond their operational and design lifetime but continue to operate through the cooperation of the responsible agencies. The Group on Earth Observations and the Coordinating Group for Meteorological Satellites (CGMS), among other groups, have raised the issue of how a robust, future precipitation constellation should be constructed. The key issues of current and future requirements for the mapping of global precipitation from satellite sensors can be summarized as providing 1) sufficiently fine spatial resolutions to capture precipitation-scale systems and reduce the beam-filling effects of the observations; 2) a wide channel diversity for each sensor to cover the range of precipitation types, characteristics, and intensities observed across the globe; 3) an observation interval that provides temporal sampling commensurate with the variability of precipitation; and 4) precipitation radars and radiometers in low-inclination orbit to provide a consistent calibration source, as demonstrated by the first two spaceborne radar–radiometer combinations on the Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Measurement (GPM) mission Core Observatory. These issues are critical in determining the direction of future constellation requirements while preserving the continuity of the existing constellation necessary for long-term climate-scale studies.
Abstract
The development of high-resolution, fully coupled, regional Earth system model systems is important for improving our understanding of climate variability, future projections, and extreme events at regional scales. Here we introduce and present an overview of the newly developed Regional Community Earth System Model (R-CESM). Different from other existing regional climate models, R-CESM is based on the Community Earth System Model version 2 (CESM2) framework. We have incorporated the Weather Research and Forecasting (WRF) Model and Regional Ocean Modeling System (ROMS) into CESM2 as additional components. As such, R-CESM can be conveniently used as a regional dynamical downscaling tool for the global CESM solutions or/and as a standalone high-resolution regional coupled model. The user interface of R-CESM follows that of CESM, making it readily accessible to the broader community. Among countless potential applications of R-CESM, we showcase here a few preliminary studies that illustrate its novel aspects and value. These include 1) assessing the skill of R-CESM in a multiyear, high-resolution, regional coupled simulation of the Gulf of Mexico; 2) examining the impact of WRF and CESM ocean–atmosphere coupling physics on tropical cyclone simulations; and 3) a convection-permitting simulation of submesoscale ocean–atmosphere interactions. We also discuss capabilities under development such as (i) regional refinement using a high-resolution ROMS nested within global CESM and (ii) “online” coupled data assimilation. Our open-source framework (publicly available at https://github.com/ihesp/rcesm1) can be easily adapted to a broad range of applications that are of interest to the users of CESM, WRF, and ROMS.
Abstract
The development of high-resolution, fully coupled, regional Earth system model systems is important for improving our understanding of climate variability, future projections, and extreme events at regional scales. Here we introduce and present an overview of the newly developed Regional Community Earth System Model (R-CESM). Different from other existing regional climate models, R-CESM is based on the Community Earth System Model version 2 (CESM2) framework. We have incorporated the Weather Research and Forecasting (WRF) Model and Regional Ocean Modeling System (ROMS) into CESM2 as additional components. As such, R-CESM can be conveniently used as a regional dynamical downscaling tool for the global CESM solutions or/and as a standalone high-resolution regional coupled model. The user interface of R-CESM follows that of CESM, making it readily accessible to the broader community. Among countless potential applications of R-CESM, we showcase here a few preliminary studies that illustrate its novel aspects and value. These include 1) assessing the skill of R-CESM in a multiyear, high-resolution, regional coupled simulation of the Gulf of Mexico; 2) examining the impact of WRF and CESM ocean–atmosphere coupling physics on tropical cyclone simulations; and 3) a convection-permitting simulation of submesoscale ocean–atmosphere interactions. We also discuss capabilities under development such as (i) regional refinement using a high-resolution ROMS nested within global CESM and (ii) “online” coupled data assimilation. Our open-source framework (publicly available at https://github.com/ihesp/rcesm1) can be easily adapted to a broad range of applications that are of interest to the users of CESM, WRF, and ROMS.
Abstract
Established primarily to improve weather monitoring across the agricultural regions of the province, the Manitoba Agriculture Weather Program (MAWP) began officially in 2005 with funding from the provincial government for the establishment of a network of 28 automated weather monitoring stations. The network steadily grew to 46 stations between 2007 and 2014 as a result of partnership with local commodity and research groups. In response to the Manitoba flood of 2011, more stations were installed and the network grew to 108 weather stations in 2019. The stations are solar powered, and scheduled maintenance is conducted at each station twice per year. Weather parameters monitored include air temperature, barometric pressure, precipitation, relative humidity, soil moisture, soil temperature, solar radiation, wind speed, and wind direction using research-grade sensors. The observations are transmitted via cellular telemetry every 15 min in the spring, summer, and fall but hourly in the winter to conserve energy supply due to reduced daylight and below-freezing temperatures. The data can be viewed by the public within 1 min of data collection. The data are used to generate agronomic-related maps such as thermal unit computation of growing degree-days and corn heat units as well as disease risk maps such as Fusarium head blight. Beyond agriculture, the data have been used for aviation investigation and for undergraduate course instruction among other applications.
Abstract
Established primarily to improve weather monitoring across the agricultural regions of the province, the Manitoba Agriculture Weather Program (MAWP) began officially in 2005 with funding from the provincial government for the establishment of a network of 28 automated weather monitoring stations. The network steadily grew to 46 stations between 2007 and 2014 as a result of partnership with local commodity and research groups. In response to the Manitoba flood of 2011, more stations were installed and the network grew to 108 weather stations in 2019. The stations are solar powered, and scheduled maintenance is conducted at each station twice per year. Weather parameters monitored include air temperature, barometric pressure, precipitation, relative humidity, soil moisture, soil temperature, solar radiation, wind speed, and wind direction using research-grade sensors. The observations are transmitted via cellular telemetry every 15 min in the spring, summer, and fall but hourly in the winter to conserve energy supply due to reduced daylight and below-freezing temperatures. The data can be viewed by the public within 1 min of data collection. The data are used to generate agronomic-related maps such as thermal unit computation of growing degree-days and corn heat units as well as disease risk maps such as Fusarium head blight. Beyond agriculture, the data have been used for aviation investigation and for undergraduate course instruction among other applications.
Abstract
Extensive expansion in irrigated agriculture has taken place over the last half century. Due to increased irrigation and resultant land-use–land-cover change, the central United States has seen a decrease in temperature and changes in precipitation during the second half of the twentieth century. To investigate the impacts of widespread commencement of irrigation at the beginning of the growing season and continued irrigation throughout the summer on local and regional weather, the Great Plains Irrigation Experiment (GRAINEX) was conducted in the spring and summer of 2018 in southeastern Nebraska. GRAINEX consisted of two 15-day intensive observation periods. Observational platforms from multiple agencies and universities were deployed to investigate the role of irrigation in surface moisture content, heat fluxes, diurnal boundary layer evolution, and local precipitation. This article provides an overview of the data collected and an analysis of the role of irrigation in land–atmosphere interactions on time scales from the seasonal to the diurnal. The analysis shows that a clear irrigation signal was apparent during the peak growing season in mid-July. This paper shows the strong impact of irrigation on surface fluxes, near-surface temperature and humidity, and boundary layer growth and decay.
Abstract
Extensive expansion in irrigated agriculture has taken place over the last half century. Due to increased irrigation and resultant land-use–land-cover change, the central United States has seen a decrease in temperature and changes in precipitation during the second half of the twentieth century. To investigate the impacts of widespread commencement of irrigation at the beginning of the growing season and continued irrigation throughout the summer on local and regional weather, the Great Plains Irrigation Experiment (GRAINEX) was conducted in the spring and summer of 2018 in southeastern Nebraska. GRAINEX consisted of two 15-day intensive observation periods. Observational platforms from multiple agencies and universities were deployed to investigate the role of irrigation in surface moisture content, heat fluxes, diurnal boundary layer evolution, and local precipitation. This article provides an overview of the data collected and an analysis of the role of irrigation in land–atmosphere interactions on time scales from the seasonal to the diurnal. The analysis shows that a clear irrigation signal was apparent during the peak growing season in mid-July. This paper shows the strong impact of irrigation on surface fluxes, near-surface temperature and humidity, and boundary layer growth and decay.
Abstract
The Atmospheric Carbon and Transport (ACT)-America NASA Earth Venture Suborbital Mission set out to improve regional atmospheric greenhouse gas (GHG) inversions by exploring the intersection of the strong GHG fluxes and vigorous atmospheric transport that occurs within the midlatitudes. Two research aircraft instrumented with remote and in situ sensors to measure GHG mole fractions, associated trace gases, and atmospheric state variables collected 1,140.7 flight hours of research data, distributed across 305 individual aircraft sorties, coordinated within 121 research flight days, and spanning five 6-week seasonal flight campaigns in the central and eastern United States. Flights sampled 31 synoptic sequences, including fair-weather and frontal conditions, at altitudes ranging from the atmospheric boundary layer to the upper free troposphere. The observations were complemented with global and regional GHG flux and transport model ensembles. We found that midlatitude weather systems contain large spatial gradients in GHG mole fractions, in patterns that were consistent as a function of season and altitude. We attribute these patterns to a combination of regional terrestrial fluxes and inflow from the continental boundaries. These observations, when segregated according to altitude and air mass, provide a variety of quantitative insights into the realism of regional CO2 and CH4 fluxes and atmospheric GHG transport realizations. The ACT-America dataset and ensemble modeling methods provide benchmarks for the development of atmospheric inversion systems. As global and regional atmospheric inversions incorporate ACT-America’s findings and methods, we anticipate these systems will produce increasingly accurate and precise subcontinental GHG flux estimates.
Abstract
The Atmospheric Carbon and Transport (ACT)-America NASA Earth Venture Suborbital Mission set out to improve regional atmospheric greenhouse gas (GHG) inversions by exploring the intersection of the strong GHG fluxes and vigorous atmospheric transport that occurs within the midlatitudes. Two research aircraft instrumented with remote and in situ sensors to measure GHG mole fractions, associated trace gases, and atmospheric state variables collected 1,140.7 flight hours of research data, distributed across 305 individual aircraft sorties, coordinated within 121 research flight days, and spanning five 6-week seasonal flight campaigns in the central and eastern United States. Flights sampled 31 synoptic sequences, including fair-weather and frontal conditions, at altitudes ranging from the atmospheric boundary layer to the upper free troposphere. The observations were complemented with global and regional GHG flux and transport model ensembles. We found that midlatitude weather systems contain large spatial gradients in GHG mole fractions, in patterns that were consistent as a function of season and altitude. We attribute these patterns to a combination of regional terrestrial fluxes and inflow from the continental boundaries. These observations, when segregated according to altitude and air mass, provide a variety of quantitative insights into the realism of regional CO2 and CH4 fluxes and atmospheric GHG transport realizations. The ACT-America dataset and ensemble modeling methods provide benchmarks for the development of atmospheric inversion systems. As global and regional atmospheric inversions incorporate ACT-America’s findings and methods, we anticipate these systems will produce increasingly accurate and precise subcontinental GHG flux estimates.
