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Abstract
The hurricane season of 2006 in the eastern North Pacific basin is summarized, and the individual tropical cyclones are described. Also, the official track and intensity forecasts of these cyclones are verified and evaluated. The 2006 eastern North Pacific season was an active one, in which 18 tropical storms formed. Of these, 10 became hurricanes and 5 became major hurricanes. A total of 2 hurricanes and 1 tropical depression made landfall in Mexico, causing 13 direct deaths in that country along with significant property damage. On average, the official track forecasts in the eastern Pacific for 2006 were quite skillful. No appreciable improvement in mean intensity forecasts was noted, however.
Abstract
The hurricane season of 2006 in the eastern North Pacific basin is summarized, and the individual tropical cyclones are described. Also, the official track and intensity forecasts of these cyclones are verified and evaluated. The 2006 eastern North Pacific season was an active one, in which 18 tropical storms formed. Of these, 10 became hurricanes and 5 became major hurricanes. A total of 2 hurricanes and 1 tropical depression made landfall in Mexico, causing 13 direct deaths in that country along with significant property damage. On average, the official track forecasts in the eastern Pacific for 2006 were quite skillful. No appreciable improvement in mean intensity forecasts was noted, however.
Abstract
The active 2020 Atlantic hurricane season produced 30 named storms, 14 hurricanes, and 7 major hurricanes (category 3+ on the Saffir–Simpson hurricane wind scale). Though the season was active overall, the final two months (October–November) raised 2020 into the upper echelon of Atlantic hurricane activity for integrated metrics such as accumulated cyclone energy (ACE). This study focuses on October–November 2020, when 7 named storms, 6 hurricanes, and 5 major hurricanes formed and produced ACE of 74 × 104 kt2 (1 kt ≈ 0.51 m s−1). Since 1950, October–November 2020 ranks tied for third for named storms, first for hurricanes and major hurricanes, and second for ACE. Six named storms also underwent rapid intensification (≥30 kt intensification in ≤24 h) in October–November 2020—the most on record. This manuscript includes a climatological analysis of October–November tropical cyclones (TCs) and their primary formation regions. In 2020, anomalously low wind shear in the western Caribbean and Gulf of Mexico, likely driven by a moderate-intensity La Niña event and anomalously high sea surface temperatures (SSTs) in the Caribbean, provided dynamic and thermodynamic conditions that were much more conducive than normal for late-season TC formation and rapid intensification. This study also highlights October–November 2020 landfalls, including Hurricanes Delta and Zeta in Louisiana and in Mexico and Hurricanes Eta and Iota in Nicaragua. The active late season in the Caribbean would have been anticipated by a statistical model using the July–September-averaged ENSO longitude index and Atlantic warm pool SSTs as predictors.
Abstract
The active 2020 Atlantic hurricane season produced 30 named storms, 14 hurricanes, and 7 major hurricanes (category 3+ on the Saffir–Simpson hurricane wind scale). Though the season was active overall, the final two months (October–November) raised 2020 into the upper echelon of Atlantic hurricane activity for integrated metrics such as accumulated cyclone energy (ACE). This study focuses on October–November 2020, when 7 named storms, 6 hurricanes, and 5 major hurricanes formed and produced ACE of 74 × 104 kt2 (1 kt ≈ 0.51 m s−1). Since 1950, October–November 2020 ranks tied for third for named storms, first for hurricanes and major hurricanes, and second for ACE. Six named storms also underwent rapid intensification (≥30 kt intensification in ≤24 h) in October–November 2020—the most on record. This manuscript includes a climatological analysis of October–November tropical cyclones (TCs) and their primary formation regions. In 2020, anomalously low wind shear in the western Caribbean and Gulf of Mexico, likely driven by a moderate-intensity La Niña event and anomalously high sea surface temperatures (SSTs) in the Caribbean, provided dynamic and thermodynamic conditions that were much more conducive than normal for late-season TC formation and rapid intensification. This study also highlights October–November 2020 landfalls, including Hurricanes Delta and Zeta in Louisiana and in Mexico and Hurricanes Eta and Iota in Nicaragua. The active late season in the Caribbean would have been anticipated by a statistical model using the July–September-averaged ENSO longitude index and Atlantic warm pool SSTs as predictors.
Abstract
The High-Resolution Rapid Refresh (HRRR) is a convection-allowing implementation of the Advanced Research version of the Weather Research and Forecasting (WRF-ARW) Model with hourly data assimilation that covers the conterminous United States and Alaska and runs in real time at the NOAA/National Centers for Environmental Prediction (NCEP). Implemented operationally at NOAA/NCEP in 2014, the HRRR features 3-km horizontal grid spacing and frequent forecasts (hourly for CONUS and 3-hourly for Alaska). HRRR initialization is designed for optimal short-range forecast skill with a particular focus on the evolution of precipitating systems. Key components of the initialization are radar-reflectivity data assimilation, hybrid ensemble-variational assimilation of conventional weather observations, and a cloud analysis to initialize stratiform cloud layers. From this initial state, HRRR forecasts are produced out to 18 h every hour, and out to 48 h every 6 h, with boundary conditions provided by the Rapid Refresh system. Between 2014 and 2020, HRRR development was focused on reducing model bias errors and improving forecast realism and accuracy. Improved representation of the planetary boundary layer, subgrid-scale clouds, and land surface contributed extensively to overall HRRR improvements. The final version of the HRRR (HRRRv4), implemented in late 2020, also features hybrid data assimilation using flow-dependent covariances from a 3-km, 36-member ensemble (“HRRRDAS”) with explicit convective storms. HRRRv4 also includes prediction of wildfire smoke plumes. The HRRR provides a baseline capability for evaluating NOAA’s next-generation Rapid Refresh Forecast System, now under development.
Significance Statement
NOAA’s operational hourly updating, convection-allowing model, the High-Resolution Rapid Refresh (HRRR), is a key tool for short-range weather forecasting and situational awareness. Improvements in assimilation of weather observations, as well as in physics parameterizations, have led to improvements in simulated radar reflectivity and quantitative precipitation forecasts since the initial implementation of HRRR in September 2014. Other targeted development has focused on improved representation of the diurnal cycle of the planetary boundary layer, resulting in improved near-surface temperature and humidity forecasts. Additional physics and data assimilation changes have led to improved treatment of the development and erosion of low-level clouds, including subgrid-scale clouds. The final version of HRRR features storm-scale ensemble data assimilation and explicit prediction of wildfire smoke plumes.
Abstract
The High-Resolution Rapid Refresh (HRRR) is a convection-allowing implementation of the Advanced Research version of the Weather Research and Forecasting (WRF-ARW) Model with hourly data assimilation that covers the conterminous United States and Alaska and runs in real time at the NOAA/National Centers for Environmental Prediction (NCEP). Implemented operationally at NOAA/NCEP in 2014, the HRRR features 3-km horizontal grid spacing and frequent forecasts (hourly for CONUS and 3-hourly for Alaska). HRRR initialization is designed for optimal short-range forecast skill with a particular focus on the evolution of precipitating systems. Key components of the initialization are radar-reflectivity data assimilation, hybrid ensemble-variational assimilation of conventional weather observations, and a cloud analysis to initialize stratiform cloud layers. From this initial state, HRRR forecasts are produced out to 18 h every hour, and out to 48 h every 6 h, with boundary conditions provided by the Rapid Refresh system. Between 2014 and 2020, HRRR development was focused on reducing model bias errors and improving forecast realism and accuracy. Improved representation of the planetary boundary layer, subgrid-scale clouds, and land surface contributed extensively to overall HRRR improvements. The final version of the HRRR (HRRRv4), implemented in late 2020, also features hybrid data assimilation using flow-dependent covariances from a 3-km, 36-member ensemble (“HRRRDAS”) with explicit convective storms. HRRRv4 also includes prediction of wildfire smoke plumes. The HRRR provides a baseline capability for evaluating NOAA’s next-generation Rapid Refresh Forecast System, now under development.
Significance Statement
NOAA’s operational hourly updating, convection-allowing model, the High-Resolution Rapid Refresh (HRRR), is a key tool for short-range weather forecasting and situational awareness. Improvements in assimilation of weather observations, as well as in physics parameterizations, have led to improvements in simulated radar reflectivity and quantitative precipitation forecasts since the initial implementation of HRRR in September 2014. Other targeted development has focused on improved representation of the diurnal cycle of the planetary boundary layer, resulting in improved near-surface temperature and humidity forecasts. Additional physics and data assimilation changes have led to improved treatment of the development and erosion of low-level clouds, including subgrid-scale clouds. The final version of HRRR features storm-scale ensemble data assimilation and explicit prediction of wildfire smoke plumes.
Abstract
The Southern Ocean plays a critical role in the global climate system by mediating atmosphere–ocean partitioning of heat and carbon dioxide. However, Earth system models are demonstrably deficient in the Southern Ocean, leading to large uncertainties in future air–sea CO2 flux projections under climate warming and incomplete interpretations of natural variability on interannual to geologic time scales. Here, we describe a recent aircraft observational campaign, the O2/N2 Ratio and CO2 Airborne Southern Ocean (ORCAS) study, which collected measurements over the Southern Ocean during January and February 2016. The primary research objective of the ORCAS campaign was to improve observational constraints on the seasonal exchange of atmospheric carbon dioxide and oxygen with the Southern Ocean. The campaign also included measurements of anthropogenic and marine biogenic reactive gases; high-resolution, hyperspectral ocean color imaging of the ocean surface; and microphysical data relevant for understanding and modeling cloud processes. In each of these components of the ORCAS project, the campaign has significantly expanded the amount of observational data available for this remote region. Ongoing research based on these observations will contribute to advancing our understanding of this climatically important system across a range of topics including carbon cycling, atmospheric chemistry and transport, and cloud physics. This article presents an overview of the scientific and methodological aspects of the ORCAS project and highlights early findings.
Abstract
The Southern Ocean plays a critical role in the global climate system by mediating atmosphere–ocean partitioning of heat and carbon dioxide. However, Earth system models are demonstrably deficient in the Southern Ocean, leading to large uncertainties in future air–sea CO2 flux projections under climate warming and incomplete interpretations of natural variability on interannual to geologic time scales. Here, we describe a recent aircraft observational campaign, the O2/N2 Ratio and CO2 Airborne Southern Ocean (ORCAS) study, which collected measurements over the Southern Ocean during January and February 2016. The primary research objective of the ORCAS campaign was to improve observational constraints on the seasonal exchange of atmospheric carbon dioxide and oxygen with the Southern Ocean. The campaign also included measurements of anthropogenic and marine biogenic reactive gases; high-resolution, hyperspectral ocean color imaging of the ocean surface; and microphysical data relevant for understanding and modeling cloud processes. In each of these components of the ORCAS project, the campaign has significantly expanded the amount of observational data available for this remote region. Ongoing research based on these observations will contribute to advancing our understanding of this climatically important system across a range of topics including carbon cycling, atmospheric chemistry and transport, and cloud physics. This article presents an overview of the scientific and methodological aspects of the ORCAS project and highlights early findings.
Abstract
The National Hurricane Center issues analyses, forecasts, and warnings over large parts of the North Atlantic and Pacific Oceans, and in support of many nearby countries. Advances in observational capabilities, operational numerical weather prediction, and forecaster tools and support systems over the past 15–20 yr have enabled the center to make more accurate forecasts, extend forecast lead times, and provide new products and services. Important limitations, however, persist. This paper discusses the current workings and state of the nation’s hurricane warning program, and highlights recent improvements and the enabling science and technology. It concludes with a look ahead at opportunities to address challenges.
Abstract
The National Hurricane Center issues analyses, forecasts, and warnings over large parts of the North Atlantic and Pacific Oceans, and in support of many nearby countries. Advances in observational capabilities, operational numerical weather prediction, and forecaster tools and support systems over the past 15–20 yr have enabled the center to make more accurate forecasts, extend forecast lead times, and provide new products and services. Important limitations, however, persist. This paper discusses the current workings and state of the nation’s hurricane warning program, and highlights recent improvements and the enabling science and technology. It concludes with a look ahead at opportunities to address challenges.
Abstract
This article provides an overview of the NASA Atmospheric Tomography (ATom) mission and a summary of selected scientific findings to date. ATom was an airborne measurements and modeling campaign aimed at characterizing the composition and chemistry of the troposphere over the most remote regions of the Pacific, Southern, Atlantic, and Arctic Oceans, and examining the impact of anthropogenic and natural emissions on a global scale. These remote regions dominate global chemical reactivity and are exceptionally important for global air quality and climate. ATom data provide the in situ measurements needed to understand the range of chemical species and their reactions, and to test satellite remote sensing observations and global models over large regions of the remote atmosphere. Lack of data in these regions, particularly over the oceans, has limited our understanding of how atmospheric composition is changing in response to shifting anthropogenic emissions and physical climate change. ATom was designed as a global-scale tomographic sampling mission with extensive geographic and seasonal coverage, tropospheric vertical profiling, and detailed speciation of reactive compounds and pollution tracers. ATom flew the NASA DC-8 research aircraft over four seasons to collect a comprehensive suite of measurements of gases, aerosols, and radical species from the remote troposphere and lower stratosphere on four global circuits from 2016 to 2018. Flights maintained near-continuous vertical profiling of 0.15–13-km altitudes on long meridional transects of the Pacific and Atlantic Ocean basins. Analysis and modeling of ATom data have led to the significant early findings highlighted here.
Abstract
This article provides an overview of the NASA Atmospheric Tomography (ATom) mission and a summary of selected scientific findings to date. ATom was an airborne measurements and modeling campaign aimed at characterizing the composition and chemistry of the troposphere over the most remote regions of the Pacific, Southern, Atlantic, and Arctic Oceans, and examining the impact of anthropogenic and natural emissions on a global scale. These remote regions dominate global chemical reactivity and are exceptionally important for global air quality and climate. ATom data provide the in situ measurements needed to understand the range of chemical species and their reactions, and to test satellite remote sensing observations and global models over large regions of the remote atmosphere. Lack of data in these regions, particularly over the oceans, has limited our understanding of how atmospheric composition is changing in response to shifting anthropogenic emissions and physical climate change. ATom was designed as a global-scale tomographic sampling mission with extensive geographic and seasonal coverage, tropospheric vertical profiling, and detailed speciation of reactive compounds and pollution tracers. ATom flew the NASA DC-8 research aircraft over four seasons to collect a comprehensive suite of measurements of gases, aerosols, and radical species from the remote troposphere and lower stratosphere on four global circuits from 2016 to 2018. Flights maintained near-continuous vertical profiling of 0.15–13-km altitudes on long meridional transects of the Pacific and Atlantic Ocean basins. Analysis and modeling of ATom data have led to the significant early findings highlighted here.
