Browse
Abstract
Forecast verification is critical for continuous improvement in meteorological organizations. The Jive verification system was originally developed to assess the accuracy of public weather forecasts issued by the Australian Bureau of Meteorology. It started as a research project in 2015 and gradually evolved to be a Bureau operational verification system in 2022. The system includes daily verification dashboards for forecasters to visualize recent forecast performance and “Evidence Targeted Automation” dashboards for exploring the performance of competing forecast systems. Additionally, Jive includes a Jupyter Notebook server with the Jive Python library which supports research experiments, case studies, and the development of new verification metrics and tools.
This paper describes the Jive verification system and how it helped bring verification to the forefront at the Bureau of Meteorology, leading to more accurate, streamlined forecasts. Jive has provided evidence to support forecast automation decisions and has helped to understand the evolving role of meteorologists in the forecast process. It has given operational meteorologists tools for evaluating forecast processes, including identifying when and how manual interventions lead to superior predictions. Work on Jive led to new verification science, including novel metrics that are decision-focused, including diagnostics for extreme conditions. Jive also provided the Bureau with an enterprise-wide data analysis environment and has prompted a clarification of forecast definitions.
These collective impacts have resulted in more accurate forecasts, ultimately benefiting society, and building trust with forecast users. These positive outcomes highlight the importance of meteorological organizations investing in verification science and technology.
Abstract
Forecast verification is critical for continuous improvement in meteorological organizations. The Jive verification system was originally developed to assess the accuracy of public weather forecasts issued by the Australian Bureau of Meteorology. It started as a research project in 2015 and gradually evolved to be a Bureau operational verification system in 2022. The system includes daily verification dashboards for forecasters to visualize recent forecast performance and “Evidence Targeted Automation” dashboards for exploring the performance of competing forecast systems. Additionally, Jive includes a Jupyter Notebook server with the Jive Python library which supports research experiments, case studies, and the development of new verification metrics and tools.
This paper describes the Jive verification system and how it helped bring verification to the forefront at the Bureau of Meteorology, leading to more accurate, streamlined forecasts. Jive has provided evidence to support forecast automation decisions and has helped to understand the evolving role of meteorologists in the forecast process. It has given operational meteorologists tools for evaluating forecast processes, including identifying when and how manual interventions lead to superior predictions. Work on Jive led to new verification science, including novel metrics that are decision-focused, including diagnostics for extreme conditions. Jive also provided the Bureau with an enterprise-wide data analysis environment and has prompted a clarification of forecast definitions.
These collective impacts have resulted in more accurate forecasts, ultimately benefiting society, and building trust with forecast users. These positive outcomes highlight the importance of meteorological organizations investing in verification science and technology.
Abstract
The Year of Polar Prediction in the Southern Hemisphere (YOPP-SH) held seven targeted observing periods (TOPs) during the 2022 austral winter to enhance atmospheric predictability over the Southern Ocean and Antarctica. The TOPs of 5–10-day duration each featured the release of additional radiosonde balloons, more than doubling the routine sounding program at the 24 participating stations run by 14 nations, together with process-oriented observations at selected sites. These extra sounding data are evaluated for their impact on forecast skill via data denial experiments with the goal of refining the observing system to improve numerical weather prediction for winter conditions. Extensive observations focusing on clouds and precipitation primarily during atmospheric river (AR) events are being applied to refine model microphysical parameterizations for the ubiquitous mixed-phase clouds that frequently impact coastal Antarctica. Process studies are being facilitated by high-time-resolution series of observations and forecast model output via the YOPP Model Intercomparison and Improvement Project (YOPPsiteMIIP). Parallel investigations are broadening the scope and impact of the YOPP-SH winter TOPs. Studies of the Antarctic tourist industry’s use of weather services show the scope for much greater awareness of the availability of forecast products and the skill they exhibit. The Sea Ice Prediction Network South (SIPN South) analysis of predictions of the sea ice growth period reveals that the forecast skill is superior to the sea ice retreat phase.
Abstract
The Year of Polar Prediction in the Southern Hemisphere (YOPP-SH) held seven targeted observing periods (TOPs) during the 2022 austral winter to enhance atmospheric predictability over the Southern Ocean and Antarctica. The TOPs of 5–10-day duration each featured the release of additional radiosonde balloons, more than doubling the routine sounding program at the 24 participating stations run by 14 nations, together with process-oriented observations at selected sites. These extra sounding data are evaluated for their impact on forecast skill via data denial experiments with the goal of refining the observing system to improve numerical weather prediction for winter conditions. Extensive observations focusing on clouds and precipitation primarily during atmospheric river (AR) events are being applied to refine model microphysical parameterizations for the ubiquitous mixed-phase clouds that frequently impact coastal Antarctica. Process studies are being facilitated by high-time-resolution series of observations and forecast model output via the YOPP Model Intercomparison and Improvement Project (YOPPsiteMIIP). Parallel investigations are broadening the scope and impact of the YOPP-SH winter TOPs. Studies of the Antarctic tourist industry’s use of weather services show the scope for much greater awareness of the availability of forecast products and the skill they exhibit. The Sea Ice Prediction Network South (SIPN South) analysis of predictions of the sea ice growth period reveals that the forecast skill is superior to the sea ice retreat phase.
Abstract
The 2023 Atlantic hurricane season was above normal, producing 20 named storms, 7 hurricanes, 3 major hurricanes, and seasonal accumulated cyclone energy that exceeded the 1991–2020 average. Hurricane Idalia was the most damaging hurricane of the year, making landfall as a Category 3 hurricane in Florida, resulting in eight direct fatalities and 3.6 billion U.S. dollars in damage. The above-normal 2023 hurricane season occurred during a strong El Niño event. El Niño events tend to be associated with increased vertical wind shear across the Caribbean and tropical Atlantic, yet vertical wind shear during the peak hurricane season months of August–October was well below normal. The primary driver of the above-normal season was likely record warm tropical Atlantic sea surface temperatures (SSTs), which effectively counteracted some of the canonical impacts of El Niño. The extremely warm tropical Atlantic and Caribbean were associated with weaker-than-normal trade winds driven by an anomalously weak subtropical ridge, resulting in a positive wind–evaporation–SST feedback. We tested atmospheric circulation sensitivity to SSTs in both the tropical and subtropical Pacific and the Atlantic using the atmospheric component of the Community Earth System Model, version 2.3. We found that the extremely warm Atlantic was the primary driver of the reduced vertical wind shear relative to other moderate/strong El Niño events. The concentrated warmth in the eastern tropical Pacific in August–October may have contributed to increased levels of vertical wind shear than if the warming had been more evenly spread across the eastern and central tropical Pacific.
Abstract
The 2023 Atlantic hurricane season was above normal, producing 20 named storms, 7 hurricanes, 3 major hurricanes, and seasonal accumulated cyclone energy that exceeded the 1991–2020 average. Hurricane Idalia was the most damaging hurricane of the year, making landfall as a Category 3 hurricane in Florida, resulting in eight direct fatalities and 3.6 billion U.S. dollars in damage. The above-normal 2023 hurricane season occurred during a strong El Niño event. El Niño events tend to be associated with increased vertical wind shear across the Caribbean and tropical Atlantic, yet vertical wind shear during the peak hurricane season months of August–October was well below normal. The primary driver of the above-normal season was likely record warm tropical Atlantic sea surface temperatures (SSTs), which effectively counteracted some of the canonical impacts of El Niño. The extremely warm tropical Atlantic and Caribbean were associated with weaker-than-normal trade winds driven by an anomalously weak subtropical ridge, resulting in a positive wind–evaporation–SST feedback. We tested atmospheric circulation sensitivity to SSTs in both the tropical and subtropical Pacific and the Atlantic using the atmospheric component of the Community Earth System Model, version 2.3. We found that the extremely warm Atlantic was the primary driver of the reduced vertical wind shear relative to other moderate/strong El Niño events. The concentrated warmth in the eastern tropical Pacific in August–October may have contributed to increased levels of vertical wind shear than if the warming had been more evenly spread across the eastern and central tropical Pacific.
Abstract
The NASA Convective Processes Experiment - Cabo Verde (CPEX-CV) field campaign took place in September 2022 out of Sal Island, Cabo Verde. A unique payload aboard the NASA DC-8 aircraft equipped with advanced remote sensing and in situ instrumentation, in conjunction with radiosonde launches and satellite observations, allowed CPEX-CV to target the coupling between atmospheric dynamics, marine boundary layer properties, convection, and the dust-laden Saharan Air Layer in the data-sparse tropical East Atlantic region. CPEX-CV provided measurements of African Easterly Wave environments, diurnal cycle impacts on convective lifecycle, and several Saharan dust outbreaks, including the highest dust optical depth observed by the DC-8 interacting with what would become Tropical Storm Hermine. Preliminary results from CPEX-CV underscore the positive impact of dedicated tropical East Atlantic observations on downstream forecast skill, including sampling environmental forcings impacting the development of several non-developing and developing convective systems such as Hurricanes Fiona and Ian. Combined airborne radar, lidar, and radiometer measurements uniquely provide near-storm environments associated with convection on various spatiotemporal scales and, with in situ observations, insights into controls on Saharan dust properties with transport. The DC-8 also collaborated with the European Space Agency to perform coordinated validation flights under the Aeolus spaceborne wind lidar and over the Mindelo ground site, highlighting the enhanced sampling potential through partnership opportunities. CPEX-CV engaged in professional development through dedicated team building exercises that equipped the team with a cohesive approach for targeting CPEX-CV science objectives and promoted active participation of scientists across all career stages.
Abstract
The NASA Convective Processes Experiment - Cabo Verde (CPEX-CV) field campaign took place in September 2022 out of Sal Island, Cabo Verde. A unique payload aboard the NASA DC-8 aircraft equipped with advanced remote sensing and in situ instrumentation, in conjunction with radiosonde launches and satellite observations, allowed CPEX-CV to target the coupling between atmospheric dynamics, marine boundary layer properties, convection, and the dust-laden Saharan Air Layer in the data-sparse tropical East Atlantic region. CPEX-CV provided measurements of African Easterly Wave environments, diurnal cycle impacts on convective lifecycle, and several Saharan dust outbreaks, including the highest dust optical depth observed by the DC-8 interacting with what would become Tropical Storm Hermine. Preliminary results from CPEX-CV underscore the positive impact of dedicated tropical East Atlantic observations on downstream forecast skill, including sampling environmental forcings impacting the development of several non-developing and developing convective systems such as Hurricanes Fiona and Ian. Combined airborne radar, lidar, and radiometer measurements uniquely provide near-storm environments associated with convection on various spatiotemporal scales and, with in situ observations, insights into controls on Saharan dust properties with transport. The DC-8 also collaborated with the European Space Agency to perform coordinated validation flights under the Aeolus spaceborne wind lidar and over the Mindelo ground site, highlighting the enhanced sampling potential through partnership opportunities. CPEX-CV engaged in professional development through dedicated team building exercises that equipped the team with a cohesive approach for targeting CPEX-CV science objectives and promoted active participation of scientists across all career stages.
Abstract
The National Science Foundation-sponsored Lake-Effect Electrification (LEE) field campaign intensive observation periods occurred between November and early February 2022-23 across the eastern Lake Ontario region. Project LEE documented, for the first time, the total lightning and electrical charge structures of lake-effect storms and the associated storm environment using a lightning mapping array (LMA), a mobile dual-polarization X-band radar, and balloon-based soundings that measured vertical profiles of temperature, humidity, wind, electric field, and hydrometeor types. LEE also observed abundant wind turbine-initiated lightning, which is climatologically more likely during the winter. The frequent occurrence of intense lake-effect storms and the proximity of a wind farm with nearly 300 turbines each more than 100 m tall to the lee of Lake Ontario provided an ideal laboratory for this study. The field project involved many undergraduate (>20) and graduate students.
Some foreseen and unforeseen challenges included: clearing the LMA solar panels of snow and continuous operation in low-sunlight conditions, large sonde balloons prematurely popping due to extremely cold conditions, sonde lines breaking, recovering probes in deep snow in heavily forested areas, vehicles getting stuck in the snowpack, and an abnormally dry season for parts of the LEE domain. In spite of these difficulties a dataset was collected in multiple lake-effect snowstorms (11 observation periods) and one extra-tropical cyclone snowstorm that clarifies the electrical structure of these systems. A key finding was the existence of a near surface substantial positive charge layer (1 nC m-3) near the shoreline during lake-effect thunderstorms.
Abstract
The National Science Foundation-sponsored Lake-Effect Electrification (LEE) field campaign intensive observation periods occurred between November and early February 2022-23 across the eastern Lake Ontario region. Project LEE documented, for the first time, the total lightning and electrical charge structures of lake-effect storms and the associated storm environment using a lightning mapping array (LMA), a mobile dual-polarization X-band radar, and balloon-based soundings that measured vertical profiles of temperature, humidity, wind, electric field, and hydrometeor types. LEE also observed abundant wind turbine-initiated lightning, which is climatologically more likely during the winter. The frequent occurrence of intense lake-effect storms and the proximity of a wind farm with nearly 300 turbines each more than 100 m tall to the lee of Lake Ontario provided an ideal laboratory for this study. The field project involved many undergraduate (>20) and graduate students.
Some foreseen and unforeseen challenges included: clearing the LMA solar panels of snow and continuous operation in low-sunlight conditions, large sonde balloons prematurely popping due to extremely cold conditions, sonde lines breaking, recovering probes in deep snow in heavily forested areas, vehicles getting stuck in the snowpack, and an abnormally dry season for parts of the LEE domain. In spite of these difficulties a dataset was collected in multiple lake-effect snowstorms (11 observation periods) and one extra-tropical cyclone snowstorm that clarifies the electrical structure of these systems. A key finding was the existence of a near surface substantial positive charge layer (1 nC m-3) near the shoreline during lake-effect thunderstorms.
Abstract
In this work, we use 8 years (2014–21) of Operational Programme for the Exchange of Weather Radar Information (OPERA) radar data, ESWD severe weather reports, and arrival time difference (ATD) lightning detection network (ATDnet) data to create a climatology of quasi-linear convective systems (QLCSs) across Europe. In the first step, 15-min radar scans were used to identify 1475 QLCS polygons. Severe weather reports, lightning data, and morphological properties were used to classify QLCSs according to their intensity into 1151 marginal (78.0%), 272 moderate (18.5%), and 52 derecho (3.5%) events. The manual evaluation led to the recognition of QLCS morphological and precipitation archetypes, areal extent, duration, speed, forward motion, width, length, accompanying hazards, injuries, and fatalities. Results indicate that QLCSs are the most frequent during summer in central Europe, while in southern Europe, their occurrence is extended to late autumn. A bow echo feature occurred in around 29% of QLCS cases, while a mesoscale convective vortex occurred in almost 9%. Among precipitation modes, trailing and embedded stratiform types accounted for around 50% of QLCSs. The most frequent hazard accompanying QLCSs was lightning (taking up on average 94.4% of the area impacted by QLCS), followed by severe wind gusts (7.9%), excessive precipitation (6.1%), large hail (2.9%), and tornadoes (0.5%). Derechos had the largest coverage of severe wind reports (49.8%), while back-building QLCSs were the most prone to excessive precipitation events (13.5%). QLCSs caused 104 fatalities and 886 injuries. Severe wind gusts were responsible for 87.6% of fatalities and 73.6% of injuries. Nearly half of all fatalities and injuries were associated with only the 10 most impactful QLCS events, mostly warm-season derechos.
Abstract
In this work, we use 8 years (2014–21) of Operational Programme for the Exchange of Weather Radar Information (OPERA) radar data, ESWD severe weather reports, and arrival time difference (ATD) lightning detection network (ATDnet) data to create a climatology of quasi-linear convective systems (QLCSs) across Europe. In the first step, 15-min radar scans were used to identify 1475 QLCS polygons. Severe weather reports, lightning data, and morphological properties were used to classify QLCSs according to their intensity into 1151 marginal (78.0%), 272 moderate (18.5%), and 52 derecho (3.5%) events. The manual evaluation led to the recognition of QLCS morphological and precipitation archetypes, areal extent, duration, speed, forward motion, width, length, accompanying hazards, injuries, and fatalities. Results indicate that QLCSs are the most frequent during summer in central Europe, while in southern Europe, their occurrence is extended to late autumn. A bow echo feature occurred in around 29% of QLCS cases, while a mesoscale convective vortex occurred in almost 9%. Among precipitation modes, trailing and embedded stratiform types accounted for around 50% of QLCSs. The most frequent hazard accompanying QLCSs was lightning (taking up on average 94.4% of the area impacted by QLCS), followed by severe wind gusts (7.9%), excessive precipitation (6.1%), large hail (2.9%), and tornadoes (0.5%). Derechos had the largest coverage of severe wind reports (49.8%), while back-building QLCSs were the most prone to excessive precipitation events (13.5%). QLCSs caused 104 fatalities and 886 injuries. Severe wind gusts were responsible for 87.6% of fatalities and 73.6% of injuries. Nearly half of all fatalities and injuries were associated with only the 10 most impactful QLCS events, mostly warm-season derechos.
Abstract
Aerosols affect the Earth’s climate both directly and indirectly, which is the largest uncertainty in the assessment of radiative forcings affecting anthropogenic climate change. The standard AErosol RObotic NETwork (AERONET) aerosol products have been widely used for more than thirty years. Currently, there is strong community interest in the possibility of determining aerosol composition directly from remote sensing observations. This work presents the results of applying such a recently developed approach by Li et al. (2019) to extended data sets of the directional sky radiances and spectral aerosol optical depth (AOD) measured by AERONET for the retrievals of aerosol components. First, the validation of aerosol optical properties retrieved by this component approach with AERONET standard products shows good agreement. Then, spatio-temporal variations of obtained aerosol component concentration are characterized globally, especially the absorbing aerosol species (black carbon, brown carbon and iron oxides) and scattering aerosol species (organic carbon, quartz, and inorganic salts). Finally, we compared the black carbon (BC) and dust column concentration retrievals to the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) products in several regions of interest (Amazon zone, Indo-China Peninsula, North India, Southern Africa, Sub-Sahel, Gobi Desert, Middle East, Sahara Desert, Taklamakan Desert) for new insights on the quantitative assessment of MERRA-2 aerosol composition products (R = 0.60 ∼ 0.85 for BC; R = 0.75 ∼ 0.90 for dust). The new value-added and long-term aerosol composition product globally is available at https://doi.org/10.6084/m9.figshare.25415239.v1, which provide important measurements for the improvement and optimization of aerosol modelling to enhanced estimate the aerosol radiative forcing.
Abstract
Aerosols affect the Earth’s climate both directly and indirectly, which is the largest uncertainty in the assessment of radiative forcings affecting anthropogenic climate change. The standard AErosol RObotic NETwork (AERONET) aerosol products have been widely used for more than thirty years. Currently, there is strong community interest in the possibility of determining aerosol composition directly from remote sensing observations. This work presents the results of applying such a recently developed approach by Li et al. (2019) to extended data sets of the directional sky radiances and spectral aerosol optical depth (AOD) measured by AERONET for the retrievals of aerosol components. First, the validation of aerosol optical properties retrieved by this component approach with AERONET standard products shows good agreement. Then, spatio-temporal variations of obtained aerosol component concentration are characterized globally, especially the absorbing aerosol species (black carbon, brown carbon and iron oxides) and scattering aerosol species (organic carbon, quartz, and inorganic salts). Finally, we compared the black carbon (BC) and dust column concentration retrievals to the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) products in several regions of interest (Amazon zone, Indo-China Peninsula, North India, Southern Africa, Sub-Sahel, Gobi Desert, Middle East, Sahara Desert, Taklamakan Desert) for new insights on the quantitative assessment of MERRA-2 aerosol composition products (R = 0.60 ∼ 0.85 for BC; R = 0.75 ∼ 0.90 for dust). The new value-added and long-term aerosol composition product globally is available at https://doi.org/10.6084/m9.figshare.25415239.v1, which provide important measurements for the improvement and optimization of aerosol modelling to enhanced estimate the aerosol radiative forcing.
