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Abstract
Prediction of weather is a main goal of atmospheric science. Its importance to society is growing continuously due to factors such as vulnerability to natural disasters, the move to renewable energy sources, and the risks of climate change. But prediction is also a major scientific challenge due to the inherently limited predictability of a chaotic atmosphere, and has led to a revolution in forecasting methods as we have moved to probabilistic prediction. These changes provide the motivation for Waves to Weather (W2W), a major national research program in Germany with three main university partners in Munich, Mainz, and Karlsruhe. We are currently in the second 4-yr phase of our planned duration of 12 years and employ 36 doctoral and postdoctoral scientists. In the context of this large program, we address what we have identified to be the most important and challenging scientific questions in predictability of weather, namely, upscale error growth, errors associated with cloud processes, and probabilistic prediction of high-impact weather. This paper presents some key results of the first phase of W2W and discusses how they have influenced our understanding of predictability. The key role of interdisciplinary research linking atmospheric scientists with experts in visualization, statistics, numerical analysis, and inverse methods will be highlighted. To ensure a lasting impact on research in our field in Germany and internationally, we have instituted innovative programs for training and support of early-career scientists, and to support education, equal opportunities, and outreach, which are also described here.
Abstract
Prediction of weather is a main goal of atmospheric science. Its importance to society is growing continuously due to factors such as vulnerability to natural disasters, the move to renewable energy sources, and the risks of climate change. But prediction is also a major scientific challenge due to the inherently limited predictability of a chaotic atmosphere, and has led to a revolution in forecasting methods as we have moved to probabilistic prediction. These changes provide the motivation for Waves to Weather (W2W), a major national research program in Germany with three main university partners in Munich, Mainz, and Karlsruhe. We are currently in the second 4-yr phase of our planned duration of 12 years and employ 36 doctoral and postdoctoral scientists. In the context of this large program, we address what we have identified to be the most important and challenging scientific questions in predictability of weather, namely, upscale error growth, errors associated with cloud processes, and probabilistic prediction of high-impact weather. This paper presents some key results of the first phase of W2W and discusses how they have influenced our understanding of predictability. The key role of interdisciplinary research linking atmospheric scientists with experts in visualization, statistics, numerical analysis, and inverse methods will be highlighted. To ensure a lasting impact on research in our field in Germany and internationally, we have instituted innovative programs for training and support of early-career scientists, and to support education, equal opportunities, and outreach, which are also described here.
Abstract
Sexual harassment in field settings brings unique challenges for prevention and response, as field research occurs outside “typical” workplaces, often in remote locations that create additional safety concerns and new team dynamics. We report on a project that has 1) trained field project participants to recognize, report, and confront sexual harassment, and 2) investigated the perceptions, attitudes, and experiences of field researchers regarding sexual harassment. Precampaign surveys from four major, multi-institutional, domestic, and international field projects indicate that the majority of sexual harassment reported prior to the field campaigns was hostile work environment harassment, and women were more likely to be the recipients, on average reporting two to three incidents each. The majority of those disclosing harassment indicated that they coped with past experiences by avoiding their harasser or downplaying incidents. Of the incidences reported (47) in postcampaign surveys of the four field teams, all fell under the category of hostile work environment and included incidents of verbal, visual, and physical harassment. Women’s harassment experiences were perpetrated by men 100% of the time, and the majority of the perpetrators were in more senior positions than the victims. Men’s harassment experiences were perpetrated by a mix of women and men, and the majority came from those at the same position of seniority. Postproject surveys indicate that the training programs (taking place before the field projects) helped participants come away with more positive than negative emotions and perceptions of the training, the leadership, and their overall experiences on the field campaign.
Abstract
Sexual harassment in field settings brings unique challenges for prevention and response, as field research occurs outside “typical” workplaces, often in remote locations that create additional safety concerns and new team dynamics. We report on a project that has 1) trained field project participants to recognize, report, and confront sexual harassment, and 2) investigated the perceptions, attitudes, and experiences of field researchers regarding sexual harassment. Precampaign surveys from four major, multi-institutional, domestic, and international field projects indicate that the majority of sexual harassment reported prior to the field campaigns was hostile work environment harassment, and women were more likely to be the recipients, on average reporting two to three incidents each. The majority of those disclosing harassment indicated that they coped with past experiences by avoiding their harasser or downplaying incidents. Of the incidences reported (47) in postcampaign surveys of the four field teams, all fell under the category of hostile work environment and included incidents of verbal, visual, and physical harassment. Women’s harassment experiences were perpetrated by men 100% of the time, and the majority of the perpetrators were in more senior positions than the victims. Men’s harassment experiences were perpetrated by a mix of women and men, and the majority came from those at the same position of seniority. Postproject surveys indicate that the training programs (taking place before the field projects) helped participants come away with more positive than negative emotions and perceptions of the training, the leadership, and their overall experiences on the field campaign.
Abstract
Better understanding and quantification of river floods for very local and “flashy” events calls for modeling capability at fine spatial and temporal scales. However, long-term discharge records with a global coverage suitable for extreme events analysis are still lacking. Here, grounded on recent breakthroughs in global runoff hydrology, river modeling, high-resolution hydrography, and climate reanalysis, we developed a 3-hourly river discharge record globally for 2.94 million river reaches during the 40-yr period of 1980–2019. The underlying modeling chain consists of the VIC land surface model (0.05°, 3-hourly) that is well calibrated and bias corrected and the RAPID routing model (2.94 million river and catchment vectors), with precipitation input from MSWEP and other meteorological fields downscaled from ERA5. Flood events (above 2-yr return) and their characteristics (number, spatial distribution, and seasonality) were extracted and studied. Validations against 3-hourly flow records from 6,000+ gauges in CONUS and daily records from 14,000+ gauges globally show good modeling performance across all flow ranges, good skills in reconstructing flood events (high extremes), and the benefit of (and need for) subdaily modeling. This data record, referred as Global Reach-Level Flood Reanalysis (GRFR), is publicly available at https://www.reachhydro.org/home/records/grfr.
Abstract
Better understanding and quantification of river floods for very local and “flashy” events calls for modeling capability at fine spatial and temporal scales. However, long-term discharge records with a global coverage suitable for extreme events analysis are still lacking. Here, grounded on recent breakthroughs in global runoff hydrology, river modeling, high-resolution hydrography, and climate reanalysis, we developed a 3-hourly river discharge record globally for 2.94 million river reaches during the 40-yr period of 1980–2019. The underlying modeling chain consists of the VIC land surface model (0.05°, 3-hourly) that is well calibrated and bias corrected and the RAPID routing model (2.94 million river and catchment vectors), with precipitation input from MSWEP and other meteorological fields downscaled from ERA5. Flood events (above 2-yr return) and their characteristics (number, spatial distribution, and seasonality) were extracted and studied. Validations against 3-hourly flow records from 6,000+ gauges in CONUS and daily records from 14,000+ gauges globally show good modeling performance across all flow ranges, good skills in reconstructing flood events (high extremes), and the benefit of (and need for) subdaily modeling. This data record, referred as Global Reach-Level Flood Reanalysis (GRFR), is publicly available at https://www.reachhydro.org/home/records/grfr.
Abstract
Inclusion of unmanned aircraft systems (UAS) into the weather surveillance network has the potential to improve short-term (<1 day) weather forecasts through direct integration of UAS-collected data into the forecast process and assimilation into numerical weather prediction models. However, one of the primary means by which the value of any new sensing platform can be assessed is through consultation with principal stakeholders. National Weather Service (NWS) forecasters are principal stakeholders responsible for the issuance of short-term forecasts. The purpose of the work presented here is to use results from a survey of 630 NWS forecasters to assess critical data gaps that impact short-term forecast accuracy and explore the potential role of UAS in filling these gaps. NWS forecasters view winter precipitation, icing, flood, lake-effect/lake-enhanced snow, turbulence, and waves as the phenomena principally impacted by data gaps. Of the 10 high-priority weather-related characteristics that need to be observed to fill critical data gaps, 7 are either measures of precipitation or related to precipitation-producing phenomena. The three most important UAS capabilities/characteristics required for useful data for weather forecasting are real-time or near-real-time data, the ability to integrate UAS data with additional data gathered by other systems, and UASs equipped with cameras to verify forecasts and monitor weather. Of the three operation modes offered for forecasters to consider, targeted surveillance is considered to be the most important compared to fixed site profiling or transects between fixed sites.
Abstract
Inclusion of unmanned aircraft systems (UAS) into the weather surveillance network has the potential to improve short-term (<1 day) weather forecasts through direct integration of UAS-collected data into the forecast process and assimilation into numerical weather prediction models. However, one of the primary means by which the value of any new sensing platform can be assessed is through consultation with principal stakeholders. National Weather Service (NWS) forecasters are principal stakeholders responsible for the issuance of short-term forecasts. The purpose of the work presented here is to use results from a survey of 630 NWS forecasters to assess critical data gaps that impact short-term forecast accuracy and explore the potential role of UAS in filling these gaps. NWS forecasters view winter precipitation, icing, flood, lake-effect/lake-enhanced snow, turbulence, and waves as the phenomena principally impacted by data gaps. Of the 10 high-priority weather-related characteristics that need to be observed to fill critical data gaps, 7 are either measures of precipitation or related to precipitation-producing phenomena. The three most important UAS capabilities/characteristics required for useful data for weather forecasting are real-time or near-real-time data, the ability to integrate UAS data with additional data gathered by other systems, and UASs equipped with cameras to verify forecasts and monitor weather. Of the three operation modes offered for forecasters to consider, targeted surveillance is considered to be the most important compared to fixed site profiling or transects between fixed sites.
Abstract
The boundary layer plays a critical role in regulating energy and moisture exchange between the surface and the free atmosphere. However, the boundary layer and lower atmosphere (including shallow flow features and horizontal gradients that influence local weather) are not sampled at time and space scales needed to improve mesoscale analyses that are used to drive short-term model predictions of impactful weather. These data gaps are exasperated in remote and less developed parts of the world where relatively cheap observational capabilities could help immensely. The continued development of small, weather-sensing uncrewed aircraft systems (UAS), coupled with the emergence of an entirely new commercial sector focused on UAS applications, has created novel opportunities for partially filling this observational gap. This article provides an overview of the current level of readiness of small UAS for routinely sensing the lower atmosphere in support of national meteorological and hydrological services (NMHS) around the world. The potential benefits of UAS observations in operational weather forecasting and numerical weather prediction are discussed, as are key considerations that will need to be addressed before their widespread adoption. Finally, potential pathways for implementation of weather-sensing UAS into operations, which hinge on their successful demonstration within collaborative, multi-agency-sponsored testbeds, are suggested.
Abstract
The boundary layer plays a critical role in regulating energy and moisture exchange between the surface and the free atmosphere. However, the boundary layer and lower atmosphere (including shallow flow features and horizontal gradients that influence local weather) are not sampled at time and space scales needed to improve mesoscale analyses that are used to drive short-term model predictions of impactful weather. These data gaps are exasperated in remote and less developed parts of the world where relatively cheap observational capabilities could help immensely. The continued development of small, weather-sensing uncrewed aircraft systems (UAS), coupled with the emergence of an entirely new commercial sector focused on UAS applications, has created novel opportunities for partially filling this observational gap. This article provides an overview of the current level of readiness of small UAS for routinely sensing the lower atmosphere in support of national meteorological and hydrological services (NMHS) around the world. The potential benefits of UAS observations in operational weather forecasting and numerical weather prediction are discussed, as are key considerations that will need to be addressed before their widespread adoption. Finally, potential pathways for implementation of weather-sensing UAS into operations, which hinge on their successful demonstration within collaborative, multi-agency-sponsored testbeds, are suggested.
Abstract
The Tibetan Plateau, known as the world’s “Third Pole” due to its high altitude, is experiencing rapid, intense climate change, similar to and even far more than that occurring in the Arctic and Antarctic. Scientific data sharing is very important to address the challenges of better understanding the unprecedented changes in the Third Pole and their impacts on the global environment and humans. The National Tibetan Plateau Data Center (TPDC, http://data.tpdc.ac.cn) is one of the first 20 national data centers endorsed by the Ministry of Science and Technology of China in 2019 and features the most complete scientific data for the Tibetan Plateau and surrounding regions, hosting more than 3,500 datasets in diverse disciplines. Fifty datasets featuring high-mountain observations, land surface parameters, near-surface atmospheric forcing, cryospheric variables, and high-profile article-associated data over the Tibetan Plateau, frequently being used to quantify the hydrological cycle and water security, early warning assessments of glacier avalanche disasters, and other geoscience studies on the Tibetan Plateau, are highlighted in this manuscript. The TPDC provides a cloud-based platform with integrated online data acquisition, quality control, analysis, and visualization capability to maximize the efficiency of data sharing. The TPDC shifts from the traditional centralized architecture to a decentralized deployment to effectively connect Third Pole–related data from other domestic and international data sources. As an embryo of data sharing and management over extreme environment in the upcoming “big data” era, the TPDC is dedicated to filling the gaps in data collection, discovery, and consumption in the Third Pole, facilitating scientific activities, particularly those featuring extensive interdisciplinary data use.
Abstract
The Tibetan Plateau, known as the world’s “Third Pole” due to its high altitude, is experiencing rapid, intense climate change, similar to and even far more than that occurring in the Arctic and Antarctic. Scientific data sharing is very important to address the challenges of better understanding the unprecedented changes in the Third Pole and their impacts on the global environment and humans. The National Tibetan Plateau Data Center (TPDC, http://data.tpdc.ac.cn) is one of the first 20 national data centers endorsed by the Ministry of Science and Technology of China in 2019 and features the most complete scientific data for the Tibetan Plateau and surrounding regions, hosting more than 3,500 datasets in diverse disciplines. Fifty datasets featuring high-mountain observations, land surface parameters, near-surface atmospheric forcing, cryospheric variables, and high-profile article-associated data over the Tibetan Plateau, frequently being used to quantify the hydrological cycle and water security, early warning assessments of glacier avalanche disasters, and other geoscience studies on the Tibetan Plateau, are highlighted in this manuscript. The TPDC provides a cloud-based platform with integrated online data acquisition, quality control, analysis, and visualization capability to maximize the efficiency of data sharing. The TPDC shifts from the traditional centralized architecture to a decentralized deployment to effectively connect Third Pole–related data from other domestic and international data sources. As an embryo of data sharing and management over extreme environment in the upcoming “big data” era, the TPDC is dedicated to filling the gaps in data collection, discovery, and consumption in the Third Pole, facilitating scientific activities, particularly those featuring extensive interdisciplinary data use.
ABSTRACT
Two reports of Antarctic region potential new record high temperature observations (18.3°C, 6 February 2020 at Esperanza station and 20.8°C, 9 February 2020 at a Brazilian automated permafrost monitoring station on Seymour Island) were evaluated by a World Meteorological Organization (WMO) panel of atmospheric scientists. The latter figure was reported as 20.75°C in the media. The panel considered the synoptic situation and instrumental setups. It determined that a large high pressure system over the area created föhn conditions and resulted in local warming for both situations. Examination of the data and metadata of the Esperanza station observation revealed no major concerns. However, analysis of data and metadata of the Seymour Island permafrost monitoring station indicated that an improvised radiation shield led to a demonstrable thermal bias error for the temperature sensor. Consequently, the WMO has accepted the 18.3°C value for 1200 LST 6 February 2020 (1500 UTC 6 February 2020) at the Argentine Esperanza station as the new “Antarctic region (continental, including mainland and surrounding islands) highest temperature recorded observation” but rejected the 20.8°C observation at the Brazilian automated Seymour Island permafrost monitoring station as biased. The committee strongly emphasizes the permafrost monitoring station was not badly designed for its purpose, but the project investigators were forced to improvise a nonoptimal radiation shield after losing the original covering. Second, with regard to media dissemination of this type of information, the committee urges increased caution in early announcements as many media outlets often tend to sensationalize and mischaracterize potential records.
ABSTRACT
Two reports of Antarctic region potential new record high temperature observations (18.3°C, 6 February 2020 at Esperanza station and 20.8°C, 9 February 2020 at a Brazilian automated permafrost monitoring station on Seymour Island) were evaluated by a World Meteorological Organization (WMO) panel of atmospheric scientists. The latter figure was reported as 20.75°C in the media. The panel considered the synoptic situation and instrumental setups. It determined that a large high pressure system over the area created föhn conditions and resulted in local warming for both situations. Examination of the data and metadata of the Esperanza station observation revealed no major concerns. However, analysis of data and metadata of the Seymour Island permafrost monitoring station indicated that an improvised radiation shield led to a demonstrable thermal bias error for the temperature sensor. Consequently, the WMO has accepted the 18.3°C value for 1200 LST 6 February 2020 (1500 UTC 6 February 2020) at the Argentine Esperanza station as the new “Antarctic region (continental, including mainland and surrounding islands) highest temperature recorded observation” but rejected the 20.8°C observation at the Brazilian automated Seymour Island permafrost monitoring station as biased. The committee strongly emphasizes the permafrost monitoring station was not badly designed for its purpose, but the project investigators were forced to improvise a nonoptimal radiation shield after losing the original covering. Second, with regard to media dissemination of this type of information, the committee urges increased caution in early announcements as many media outlets often tend to sensationalize and mischaracterize potential records.
