Pub Date : 2023-05-18DOI: 10.1175/jamc-d-22-0197.1
Franklin T. Lombardo, Zachary B. Wienhoff, Daniel M. Rhee, Justin B. Nevill, Charlotte A. Poole
Tornado characteristics (e.g., frequency, intensity) are challenging to capture. Assessment of tornado characteristics typically requires damage as a proxy. The lack of validation in the Enhanced Fujita (EF) scale and the likelihood of rural tornadoes suggests that tornado characteristics are not accurately captured. This manuscript presents an approach to quantify the potential misclassification of tornado characteristics using Monte Carlo simulation for residential structures in rural areas. An analytical tornado wind field model coupled with fragility curves generates degrees of damage (i.e., DOD) from the EF scale in a wind speed to damage approach. The simulated DODs are then used to derive damage to wind speed relationships built from the National Weather Service Damage Assessment Toolkit (NWS DAT). Comparisons are then made between the simulated tornado characteristics and those derived from damage. Results from the simulations show a substantial proportion of tornadoes were ‘missed’ and path width and path length on average are underestimated. An EF4 rating based on damage is favored for EF3 to EF5 simulated tornadoes. A linear regression was utilized and determined damagebased wind speeds of different percentiles, damage length, damage width and the number of structures rated at a particular DOD were important for prediction. The distribution of DODs was also used to predict wind speed and the associated intensity rating. These methods were tested on actual tornado cases. Tornadoes that have the same damage-based peak wind speed can be objectively assessed to determine differences in overall intensity. The results also raise questions about the level of confidence when assessing wind speed based on damage.
{"title":"An Approach for Assessing Misclassification of Tornado Characteristics using Damage","authors":"Franklin T. Lombardo, Zachary B. Wienhoff, Daniel M. Rhee, Justin B. Nevill, Charlotte A. Poole","doi":"10.1175/jamc-d-22-0197.1","DOIUrl":"https://doi.org/10.1175/jamc-d-22-0197.1","url":null,"abstract":"\u0000Tornado characteristics (e.g., frequency, intensity) are challenging to capture. Assessment of tornado characteristics typically requires damage as a proxy. The lack of validation in the Enhanced Fujita (EF) scale and the likelihood of rural tornadoes suggests that tornado characteristics are not accurately captured. This manuscript presents an approach to quantify the potential misclassification of tornado characteristics using Monte Carlo simulation for residential structures in rural areas. An analytical tornado wind field model coupled with fragility curves generates degrees of damage (i.e., DOD) from the EF scale in a wind speed to damage approach. The simulated DODs are then used to derive damage to wind speed relationships built from the National Weather Service Damage Assessment Toolkit (NWS DAT). Comparisons are then made between the simulated tornado characteristics and those derived from damage.\u0000Results from the simulations show a substantial proportion of tornadoes were ‘missed’ and path width and path length on average are underestimated. An EF4 rating based on damage is favored for EF3 to EF5 simulated tornadoes. A linear regression was utilized and determined damagebased wind speeds of different percentiles, damage length, damage width and the number of structures rated at a particular DOD were important for prediction. The distribution of DODs was also used to predict wind speed and the associated intensity rating. These methods were tested on actual tornado cases. Tornadoes that have the same damage-based peak wind speed can be objectively assessed to determine differences in overall intensity. The results also raise questions about the level of confidence when assessing wind speed based on damage.","PeriodicalId":15027,"journal":{"name":"Journal of Applied Meteorology and Climatology","volume":" ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2023-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49224443","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-18DOI: 10.1175/jamc-d-22-0128.1
Y. Pichugina, R. Banta, W. Brewer, D. Turner, V. Wulfmeyer, E. Strobach, S. Baidar, B. Carroll
Low-level jets (LLJs) are an important nocturnal source of wind energy in the U.S. Great Plains. An August 2017 lidar-based field-measurement campaign (LAFE) studied LLJs over the Central SGP site in Oklahoma, and found nearly equal occurrences of the usual southerly jets, and postfrontal northeasterly jets—typically rare during this season—for an opportunity to compare the two types of LLJs during this month. Southerly winds were stronger than the north-easterlies by more than 4 ms−1 on average, reflecting a significantly higher frequency of winds stronger than 12 ms−1. The analysis of this dataset has been expanded to other SGP Doppler-lidar sites to quantify the variability of winds and LLJ properties between sites of different land use. Geographic variations of winds over the study area were noted: on southerly-wind nights, the winds blew stronger at the highest, westernmost sites by 2 ms−1, whereas on the northeasterlyflow nights, the easternmost sites had the strongest wind speeds. Lidar measurements at 5 sites during August 2017, contrasted to the 2016-2021 summertime data, revealed unusual wind and LLJ conditions. Temporal hodographs using hourly-averaged winds at multiple heights revealed unorganized behavior in the turbulent stable boundary layer (SBL) below the jet nose. Above the nose, some nights showed veering qualitatively similar to inertial-oscillation (IO) behavior, but at amplitudes much smaller than expected for an IO, whereas other nights showed little veering. Vertical hodographs had a linear shape in the SBL, indicating little directional shear there, and veering above, resulting in a hook-shaped hodograph with height.
{"title":"Doppler lidar measurements of wind variability and LLJ Properties in Central Oklahoma during the August 2017 Land-Atmosphere Feedback Experiment.","authors":"Y. Pichugina, R. Banta, W. Brewer, D. Turner, V. Wulfmeyer, E. Strobach, S. Baidar, B. Carroll","doi":"10.1175/jamc-d-22-0128.1","DOIUrl":"https://doi.org/10.1175/jamc-d-22-0128.1","url":null,"abstract":"\u0000Low-level jets (LLJs) are an important nocturnal source of wind energy in the U.S. Great Plains. An August 2017 lidar-based field-measurement campaign (LAFE) studied LLJs over the Central SGP site in Oklahoma, and found nearly equal occurrences of the usual southerly jets, and postfrontal northeasterly jets—typically rare during this season—for an opportunity to compare the two types of LLJs during this month. Southerly winds were stronger than the north-easterlies by more than 4 ms−1 on average, reflecting a significantly higher frequency of winds stronger than 12 ms−1.\u0000The analysis of this dataset has been expanded to other SGP Doppler-lidar sites to quantify the variability of winds and LLJ properties between sites of different land use. Geographic variations of winds over the study area were noted: on southerly-wind nights, the winds blew stronger at the highest, westernmost sites by 2 ms−1, whereas on the northeasterlyflow nights, the easternmost sites had the strongest wind speeds. Lidar measurements at 5 sites during August 2017, contrasted to the 2016-2021 summertime data, revealed unusual wind and LLJ conditions.\u0000Temporal hodographs using hourly-averaged winds at multiple heights revealed unorganized behavior in the turbulent stable boundary layer (SBL) below the jet nose. Above the nose, some nights showed veering qualitatively similar to inertial-oscillation (IO) behavior, but at amplitudes much smaller than expected for an IO, whereas other nights showed little veering. Vertical hodographs had a linear shape in the SBL, indicating little directional shear there, and veering above, resulting in a hook-shaped hodograph with height.","PeriodicalId":15027,"journal":{"name":"Journal of Applied Meteorology and Climatology","volume":" ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2023-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46811483","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-17DOI: 10.1175/jamc-d-23-0016.1
Daniel Choi, Hyo-Jung Lee, L. Chang, Hyun-Young Jo, Yu-Jin Jo, Shin-Young Park, Geum-Hee Yang, Cheol-Hee Kim
In this study, high particulate matter (PM2.5) pollution episodes were examined in Seoul, the capital city of South Korea, which, based on the episode characteristics, were influenced by a distinct meteorological mode, long-range transport (LRT), from two-level meteorological observations: surface and 850-500 hPa level. We performed two-step statistical analysis including principal component (PC) analysis of meteorological variables based on the observation data, followed by multiple linear regression (MLR). The meteorological variables included surface temperature (Tsfc), wind speed (WSsfc), and the east–west (usfc) and north– south (vsfc) components of wind speed, as well as wind components at 850 hPa geopotential height (u850 and v850, respectively) and the vertical temperature gradient between 850 and 500 hPa. Our two-step analysis of data collected during 2018–2019 revealed that the dominant factors influencing high-PM2.5 days in Seoul (129 days) were upper wind characteristics in winter, including positive u850 and negative v850, that were controlled by the presence of continental anticyclones that increased the likelihood of LRT of PM2.5 pollutants. Regional-scale meteorological variables, including surface and upper meteorological variables on normal and high-PM2.5 days, showed distinct covariation over Seoul, a megacity in the eastern part of northeast Asia with large anthropogenic emissions. Although this study examined only two atmospheric layers (surface and 500-850 hPa), our results clearly detected high-PM2.5 episodes with LRT characteristics, suggesting the importance of considering both geographical distinctiveness and seasonal meteorological covariability when scaling down continental-to-local response to emission reduction.
{"title":"Distinct Meteorological Mode associated with High PM2.5 Episodes in Seoul, South Korea","authors":"Daniel Choi, Hyo-Jung Lee, L. Chang, Hyun-Young Jo, Yu-Jin Jo, Shin-Young Park, Geum-Hee Yang, Cheol-Hee Kim","doi":"10.1175/jamc-d-23-0016.1","DOIUrl":"https://doi.org/10.1175/jamc-d-23-0016.1","url":null,"abstract":"\u0000In this study, high particulate matter (PM2.5) pollution episodes were examined in Seoul, the capital city of South Korea, which, based on the episode characteristics, were influenced by a distinct meteorological mode, long-range transport (LRT), from two-level meteorological observations: surface and 850-500 hPa level. We performed two-step statistical analysis including principal component (PC) analysis of meteorological variables based on the observation data, followed by multiple linear regression (MLR). The meteorological variables included surface temperature (Tsfc), wind speed (WSsfc), and the east–west (usfc) and north– south (vsfc) components of wind speed, as well as wind components at 850 hPa geopotential height (u850 and v850, respectively) and the vertical temperature gradient between 850 and 500 hPa. Our two-step analysis of data collected during 2018–2019 revealed that the dominant factors influencing high-PM2.5 days in Seoul (129 days) were upper wind characteristics in winter, including positive u850 and negative v850, that were controlled by the presence of continental anticyclones that increased the likelihood of LRT of PM2.5 pollutants. Regional-scale meteorological variables, including surface and upper meteorological variables on normal and high-PM2.5 days, showed distinct covariation over Seoul, a megacity in the eastern part of northeast Asia with large anthropogenic emissions. Although this study examined only two atmospheric layers (surface and 500-850 hPa), our results clearly detected high-PM2.5 episodes with LRT characteristics, suggesting the importance of considering both geographical distinctiveness and seasonal meteorological covariability when scaling down continental-to-local response to emission reduction.","PeriodicalId":15027,"journal":{"name":"Journal of Applied Meteorology and Climatology","volume":" ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43017848","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-17DOI: 10.1175/jamc-d-23-0002.1
S. Matrosov
Vertically-pointing Ka-band radar measurements are used to derive fall velocity – reflectivity factor (Vt=aZeb) relations for frozen hydrometeor populations of different habits during snowfall events observed at Oliktok Point, Alaska, and at the multidisciplinary drifting observatory for study of Arctic climate (MOSAiC). Case study events range from snowfall with highly rimed particles observed during periods with large amounts of supercooled liquid water path (LWP > 320 g m-2) to unrimed snowflakes including instances when pristine planar crystals were the dominant frozen hydrometeor habit. The prefactor a and the exponent b in the observed Vt –Ze relations scaled to the sea level vary in the approximate ranges 0.5 – 1.4 and 0.03 – 0.13, respectively (reflectivities are in mm6m-3 and velocities are in m s-1). The coefficient a values are the smallest for planar crystals (a~0.5) and the largest (a>1.2) for particles under severe riming conditions with high LWP. There is no clear distinction between b values for high and low LWP conditions. The range of the observed Vt –Ze relation coefficients is in general agreement with results of modeling using fall velocity – size (vt =αDβ) relations for individual particles found in literature for hydrometeors of different habits, though there is significant variability in α and β coefficients from different studies even for a same particle habit. Correspondences among coefficients in the Vt –Ze relations for particle populations and in the individual particle vt–D relations are analyzed. These correspondences and the observed Vt –Ze relations can be used for evaluating different frozen hydrometeor fall velocity parameterizations in models.
垂直指向Ka波段雷达测量用于推导在阿拉斯加Oliktok Point和北极气候研究多学科漂移观测站（MOSAiC）观测到的降雪事件期间不同习惯的冰冻水文气象种群的下降速度-反射率因子（Vt=aZeb）关系。案例研究事件包括在大量过冷液态水路径（LWP>320 g m-2）期间观察到的具有高度聚合颗粒的降雪，以及未成熟的雪花，包括原始平面晶体是主要冷冻水文气象习惯的情况。观测到的与海平面成比例的Vt–Ze关系中的前置因子a和指数b分别在0.5–1.4和0.03–0.13的近似范围内变化（反射率以mm6m-3为单位，速度以m s-1为单位）。在具有高LWP的严重边缘条件下，平面晶体的系数a最小（a~0.5），颗粒的系数a最大（a>1.2）。对于高和低LWP条件，b值之间没有明显的区别。观测到的Vt–Ze关系系数的范围与文献中发现的不同习性的水文气象器的单个颗粒的下落速度-大小（Vt=αDβ）关系的建模结果基本一致，尽管即使对于相同的颗粒习性，不同研究的α和β系数也存在显著差异。分析了粒子群的Vt–Ze关系和单个粒子Vt–D关系中系数之间的对应关系。这些对应关系和观测到的Vt–Ze关系可用于评估模型中不同的冻结水文气象降落速度参数化。
{"title":"Frozen hydrometeor terminal fall velocity dependence on particle habit and riming as observed by vertically-pointing radars","authors":"S. Matrosov","doi":"10.1175/jamc-d-23-0002.1","DOIUrl":"https://doi.org/10.1175/jamc-d-23-0002.1","url":null,"abstract":"\u0000Vertically-pointing Ka-band radar measurements are used to derive fall velocity – reflectivity factor (Vt=aZeb) relations for frozen hydrometeor populations of different habits during snowfall events observed at Oliktok Point, Alaska, and at the multidisciplinary drifting observatory for study of Arctic climate (MOSAiC). Case study events range from snowfall with highly rimed particles observed during periods with large amounts of supercooled liquid water path (LWP > 320 g m-2) to unrimed snowflakes including instances when pristine planar crystals were the dominant frozen hydrometeor habit. The prefactor a and the exponent b in the observed Vt –Ze relations scaled to the sea level vary in the approximate ranges 0.5 – 1.4 and 0.03 – 0.13, respectively (reflectivities are in mm6m-3 and velocities are in m s-1). The coefficient a values are the smallest for planar crystals (a~0.5) and the largest (a>1.2) for particles under severe riming conditions with high LWP. There is no clear distinction between b values for high and low LWP conditions. The range of the observed Vt –Ze relation coefficients is in general agreement with results of modeling using fall velocity – size (vt =αDβ) relations for individual particles found in literature for hydrometeors of different habits, though there is significant variability in α and β coefficients from different studies even for a same particle habit. Correspondences among coefficients in the Vt –Ze relations for particle populations and in the individual particle vt–D relations are analyzed. These correspondences and the observed Vt –Ze relations can be used for evaluating different frozen hydrometeor fall velocity parameterizations in models.","PeriodicalId":15027,"journal":{"name":"Journal of Applied Meteorology and Climatology","volume":" ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2023-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42071908","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-24DOI: 10.1175/jamc-d-22-0124.1
Chenxi Wang, D. Zheng, Yijun Zhang, Wen Yao, Wenjuan Zhang
Using hail records at national meteorological stations for 2014–2018, ERA-interim reanalysis data and Doppler weather radar data, the spatiotemporal distribution of hail events (HEs) in the Beijing-Tianjin-Hebei region is revealed, and the environmental conditions and hailstorm structures corresponding to large hail (diameter ≥ 20 mm) events (LHEs) and small hail (2 mm ≤ diameter < 20 mm) events (SHEs) are compared. It is found that although HEs may be more frequent in mountainous areas, most LHEs occur in the plains and near the foot of the mountains. HE frequency peaks in June and the average hailstone size is larger during May and June. According to daytime records, the HEs predominantly occur in the afternoon and evening, while LHE tends to be more in the evening. Comparison of environmental parameters suggests that relative to SHEs, LHEs tend to correspond to higher 2-m temperature, wetter lower layer, larger difference in RH between 925 and 500 hPa, greater unstable energy and stronger wind shear. Hailstorms associated with LHEs tend to feature greater mesoscale rotation velocity than those associated with SHEs. Hailstorms usually show rapid increase (RI) in vertically integrated liquid (VIL) before hailstones are observed. A significant difference between the hailstorms associated with LHEs and SHEs is that the former has obviously longer time interval between the end of VIL RI and the occurrence of hailfall, indicating that the large hail size benefits from the constant supply of liquid water and the hail can be lifted by updraft for long time.
{"title":"Comparison of Spatiotemporal Distribution and Occurrence Conditions of Large and Small Hail Events in Beijing-Tianjin-Hebei Region","authors":"Chenxi Wang, D. Zheng, Yijun Zhang, Wen Yao, Wenjuan Zhang","doi":"10.1175/jamc-d-22-0124.1","DOIUrl":"https://doi.org/10.1175/jamc-d-22-0124.1","url":null,"abstract":"\u0000Using hail records at national meteorological stations for 2014–2018, ERA-interim reanalysis data and Doppler weather radar data, the spatiotemporal distribution of hail events (HEs) in the Beijing-Tianjin-Hebei region is revealed, and the environmental conditions and hailstorm structures corresponding to large hail (diameter ≥ 20 mm) events (LHEs) and small hail (2 mm ≤ diameter < 20 mm) events (SHEs) are compared. It is found that although HEs may be more frequent in mountainous areas, most LHEs occur in the plains and near the foot of the mountains. HE frequency peaks in June and the average hailstone size is larger during May and June. According to daytime records, the HEs predominantly occur in the afternoon and evening, while LHE tends to be more in the evening. Comparison of environmental parameters suggests that relative to SHEs, LHEs tend to correspond to higher 2-m temperature, wetter lower layer, larger difference in RH between 925 and 500 hPa, greater unstable energy and stronger wind shear. Hailstorms associated with LHEs tend to feature greater mesoscale rotation velocity than those associated with SHEs. Hailstorms usually show rapid increase (RI) in vertically integrated liquid (VIL) before hailstones are observed. A significant difference between the hailstorms associated with LHEs and SHEs is that the former has obviously longer time interval between the end of VIL RI and the occurrence of hailfall, indicating that the large hail size benefits from the constant supply of liquid water and the hail can be lifted by updraft for long time.","PeriodicalId":15027,"journal":{"name":"Journal of Applied Meteorology and Climatology","volume":" ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43980215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-24DOI: 10.1175/jamc-d-22-0186.1
Windmanagda Sawadogo, J. Bliefernicht, B. Fersch, S. Salack, Samuel Guug, K. Ogunjobi, S. Meilinger, H. Kunstmann
The number of solar power plants has increased in West Africa in recent years. Reliable reanalysis data and short-term forecasting of solar irradiance from numerical weather prediction models could provide an economic advantage for the planning and operation of solar power plants, especially in data-poor regions such as West Africa. This study presents a detailed assessment of different shortwave (SW) radiation schemes from the Weather Research and Forecasting option Solar (WRF-Solar) model with appropriate configurations for different atmospheric conditions in Ghana and the southern part of Burkina Faso. We applied a two one-way nested domain (D1=15 km and D2=3 km) to investigate four different SW schemes namely, CAM, Dudhia, RRTMG, Goddard and RRTMG without aerosol and with aerosol inputs (RRTMG_AERO). The simulation results were validated using hourly measurements from different automatic weather stations established in the study region in recent years. The results show that the RRTMG_AERO_D01 generally outperforms the other SW radiation schemes to simulate GHI under all-sky condition (RMSE=235 W/m2 (19%); MAE=172 W/m2 (14%)) and also under cloudy skies. Moreover, RRTMG_AERO_D01 shows the best performance on a seasonal scale. Both the RRTMG_AERO and Dudhia experiments indicate a good performance under clear skies. However, the sensitivity study of different SW radiation schemes in the WRF-Solar model suggests that RRTMG_AERO gives better results. Therefore, it is recommended to use it for solar irradiance forecasts over Ghana and the southern part of Burkina Faso.
{"title":"Global Horizontal Irradiance in West Africa: Evaluation of the WRF-Solar Model in Convective Permitting Mode with Ground Measurements","authors":"Windmanagda Sawadogo, J. Bliefernicht, B. Fersch, S. Salack, Samuel Guug, K. Ogunjobi, S. Meilinger, H. Kunstmann","doi":"10.1175/jamc-d-22-0186.1","DOIUrl":"https://doi.org/10.1175/jamc-d-22-0186.1","url":null,"abstract":"\u0000The number of solar power plants has increased in West Africa in recent years. Reliable reanalysis data and short-term forecasting of solar irradiance from numerical weather prediction models could provide an economic advantage for the planning and operation of solar power plants, especially in data-poor regions such as West Africa. This study presents a detailed assessment of different shortwave (SW) radiation schemes from the Weather Research and Forecasting option Solar (WRF-Solar) model with appropriate configurations for different atmospheric conditions in Ghana and the southern part of Burkina Faso. We applied a two one-way nested domain (D1=15 km and D2=3 km) to investigate four different SW schemes namely, CAM, Dudhia, RRTMG, Goddard and RRTMG without aerosol and with aerosol inputs (RRTMG_AERO). The simulation results were validated using hourly measurements from different automatic weather stations established in the study region in recent years. The results show that the RRTMG_AERO_D01 generally outperforms the other SW radiation schemes to simulate GHI under all-sky condition (RMSE=235 W/m2 (19%); MAE=172 W/m2 (14%)) and also under cloudy skies. Moreover, RRTMG_AERO_D01 shows the best performance on a seasonal scale. Both the RRTMG_AERO and Dudhia experiments indicate a good performance under clear skies. However, the sensitivity study of different SW radiation schemes in the WRF-Solar model suggests that RRTMG_AERO gives better results. Therefore, it is recommended to use it for solar irradiance forecasts over Ghana and the southern part of Burkina Faso.","PeriodicalId":15027,"journal":{"name":"Journal of Applied Meteorology and Climatology","volume":" ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44076813","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-19DOI: 10.1175/jamc-d-21-0231.1
Robert Maisha, T. Ndarana, Francois A. Engelbrecht, M. Thatcher, Mary-Jane M. Bopape, J. van der Merwe, Y. Padayachi, Cecilia Masemola
The study evaluates the performance of the Conformal-Cubic Atmospheric Model (CCAM) when simulating an urban heat island (UHi) over the City of eThekwini, located along the southeast coast of South Africa. The CCAM model is applied at a grid length of 1 km on the panel with eThekwini, in a stretched grid mode. The CCAM is coupled to the urban climate model (UCM) called the Australian Town Energy Budget (ATEB). The ATEB incorporates measured urban parameters including building characteristics, emissions, and albedo. The ATEB incorporates the landcover boundary conditions obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite. The CCAM configuration applied realistically captured the orientation of the city and landcover types. Simulations of meteorological variables such as temperatures and longwave radiation reproduced the spatial distribution and intensity of the UHi. Results shows that the UHi is stronger during summer and weaker in all other seasons. The UHi developed because of natural factors (i.e., distribution of longwave radiation) and human factors (i.e., urban expansion, an increase in anthropogenic emissions, and additional heating). Due to the city location along the coast, the UHi simulation could be weakened by atmospheric circulation resulting from land and sea breezes. Mitigation methods such as applying reflective paints and revegetation of the city may increase albedo and latent heat fluxes but reduce the sensible heat fluxes and weakens the UHi. However, the UHi may not be completely eliminated since natural factors emissions constantly influence its development.
{"title":"Simulation of the eThekwini Heat Island in South Africa","authors":"Robert Maisha, T. Ndarana, Francois A. Engelbrecht, M. Thatcher, Mary-Jane M. Bopape, J. van der Merwe, Y. Padayachi, Cecilia Masemola","doi":"10.1175/jamc-d-21-0231.1","DOIUrl":"https://doi.org/10.1175/jamc-d-21-0231.1","url":null,"abstract":"\u0000The study evaluates the performance of the Conformal-Cubic Atmospheric Model (CCAM) when simulating an urban heat island (UHi) over the City of eThekwini, located along the southeast coast of South Africa. The CCAM model is applied at a grid length of 1 km on the panel with eThekwini, in a stretched grid mode. The CCAM is coupled to the urban climate model (UCM) called the Australian Town Energy Budget (ATEB). The ATEB incorporates measured urban parameters including building characteristics, emissions, and albedo. The ATEB incorporates the landcover boundary conditions obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite. The CCAM configuration applied realistically captured the orientation of the city and landcover types. Simulations of meteorological variables such as temperatures and longwave radiation reproduced the spatial distribution and intensity of the UHi. Results shows that the UHi is stronger during summer and weaker in all other seasons. The UHi developed because of natural factors (i.e., distribution of longwave radiation) and human factors (i.e., urban expansion, an increase in anthropogenic emissions, and additional heating). Due to the city location along the coast, the UHi simulation could be weakened by atmospheric circulation resulting from land and sea breezes. Mitigation methods such as applying reflective paints and revegetation of the city may increase albedo and latent heat fluxes but reduce the sensible heat fluxes and weakens the UHi. However, the UHi may not be completely eliminated since natural factors emissions constantly influence its development.","PeriodicalId":15027,"journal":{"name":"Journal of Applied Meteorology and Climatology","volume":" ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2023-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46743349","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-18DOI: 10.1175/jamc-d-23-0003.1
Siwei He, D. Turner, S. Benjamin, J. Olson, T. Smirnova, T. Meyers
The performance of version 4 of the NOAA High-Resolution Rapid Refresh (HRRR) numerical weather prediction model for near-surface variables, including wind, humidity, temperature, surface latent and sensible fluxes, and longwave and shortwave radiative fluxes, is examined over the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) region. The study evaluated the model’s bias and bias-corrected mean absolute error relative to the observations on different time scales. Forecasts of near-surface geophysical variables at five SGP sites (HRRR at 3-km scale) were found to agree well with observations, but some consistent observation-forecast differences also occurred. Sensible and latent heat fluxes are the most challenging variables to be reproduced. The diurnal cycle is the main temporal scale affecting observation-forecast differences of the near-surface variables, and almost all of the variables showed different biases throughout the diurnal cycle. Results show that the overestimation of downward shortwave and the underestimation of downward longwave radiative flux are the two major biases found in this study. The timing and magnitude of downward longwave flux, wind speed, sensible and latent heat fluxes are also different with contributions from model representations, data assimilation limitations, and differences in scales between HRRR and SGP sites. The positive bias in downward shortwave and negative bias in longwave radiation suggests that the model is underestimating cloud fraction in the study domain. The study concludes by showing a brief comparison against version 3 of the HRRR, and shows that version 4 has better performance in almost all near surface variables.
{"title":"Evaluation of the near-surface variables in the HRRR weather model using observations from the ARM SGP site","authors":"Siwei He, D. Turner, S. Benjamin, J. Olson, T. Smirnova, T. Meyers","doi":"10.1175/jamc-d-23-0003.1","DOIUrl":"https://doi.org/10.1175/jamc-d-23-0003.1","url":null,"abstract":"\u0000The performance of version 4 of the NOAA High-Resolution Rapid Refresh (HRRR) numerical weather prediction model for near-surface variables, including wind, humidity, temperature, surface latent and sensible fluxes, and longwave and shortwave radiative fluxes, is examined over the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) region. The study evaluated the model’s bias and bias-corrected mean absolute error relative to the observations on different time scales. Forecasts of near-surface geophysical variables at five SGP sites (HRRR at 3-km scale) were found to agree well with observations, but some consistent observation-forecast differences also occurred. Sensible and latent heat fluxes are the most challenging variables to be reproduced. The diurnal cycle is the main temporal scale affecting observation-forecast differences of the near-surface variables, and almost all of the variables showed different biases throughout the diurnal cycle. Results show that the overestimation of downward shortwave and the underestimation of downward longwave radiative flux are the two major biases found in this study. The timing and magnitude of downward longwave flux, wind speed, sensible and latent heat fluxes are also different with contributions from model representations, data assimilation limitations, and differences in scales between HRRR and SGP sites. The positive bias in downward shortwave and negative bias in longwave radiation suggests that the model is underestimating cloud fraction in the study domain. The study concludes by showing a brief comparison against version 3 of the HRRR, and shows that version 4 has better performance in almost all near surface variables.","PeriodicalId":15027,"journal":{"name":"Journal of Applied Meteorology and Climatology","volume":" ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2023-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41538046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-12DOI: 10.1175/jamc-d-22-0146.1
M. Mandement, P. Kirstetter, H. Reeves
The accuracy and uncertainty of radar echo top heights estimated by ground-based radars remains largely unknown despite their critical importance for applications ranging from aviation weather forecasting to severe weather diagnosis. As the vantage point of space is more suited for the estimation of echo top heights than ground-based radars, the use of space-borne radar observations is explored as an external reference for cross-comparison. An investigation has been carried out across the conterminous United States by comparing the National Oceanic and Atmospheric Administration (NOAA)/National Severe Storms Laboratory Multi-Radar Multi-Sensor (MRMS) system to the space-based radar onboard the NASA/JAXA Global Precipitation Measurement satellite platform. No major bias was assessed between the two products. An annual cycle of differences is found, driven by an underestimation of the stratiform cloud echo top heights and an overestimation of the convective ones. The investigation of the systematic biases for different radar volume coverage pattern (VCP) shows that scanning strategies with fewer tilts and greater voids as VCP 21/121/221 contribute to overestimations observed for high MRMS tops. For VCP 12/212, the Automated Volume Scan Evaluation and Termination (AVSET) function increases the radar cone of silence, causing overestimations when the echo top lies above the highest elevation scan. However, it seems that for low echo tops, the shorter refresh rates contribute to mitigate underestimations, especially in stratiform cases.
{"title":"Intercomparison between ground-based and space-borne radars echo top heights: Application to the Multi-Radar Multi-Sensor and the Global Precipitation Measurement.","authors":"M. Mandement, P. Kirstetter, H. Reeves","doi":"10.1175/jamc-d-22-0146.1","DOIUrl":"https://doi.org/10.1175/jamc-d-22-0146.1","url":null,"abstract":"\u0000The accuracy and uncertainty of radar echo top heights estimated by ground-based radars remains largely unknown despite their critical importance for applications ranging from aviation weather forecasting to severe weather diagnosis. As the vantage point of space is more suited for the estimation of echo top heights than ground-based radars, the use of space-borne radar observations is explored as an external reference for cross-comparison. An investigation has been carried out across the conterminous United States by comparing the National Oceanic and Atmospheric Administration (NOAA)/National Severe Storms Laboratory Multi-Radar Multi-Sensor (MRMS) system to the space-based radar onboard the NASA/JAXA Global Precipitation Measurement satellite platform. No major bias was assessed between the two products. An annual cycle of differences is found, driven by an underestimation of the stratiform cloud echo top heights and an overestimation of the convective ones. The investigation of the systematic biases for different radar volume coverage pattern (VCP) shows that scanning strategies with fewer tilts and greater voids as VCP 21/121/221 contribute to overestimations observed for high MRMS tops. For VCP 12/212, the Automated Volume Scan Evaluation and Termination (AVSET) function increases the radar cone of silence, causing overestimations when the echo top lies above the highest elevation scan. However, it seems that for low echo tops, the shorter refresh rates contribute to mitigate underestimations, especially in stratiform cases.","PeriodicalId":15027,"journal":{"name":"Journal of Applied Meteorology and Climatology","volume":"44 1","pages":""},"PeriodicalIF":3.0,"publicationDate":"2023-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41249494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-04-05DOI: 10.1175/jamc-d-23-0005.1
A major challenge encountered in the development of systems exposed to weather stressors, such as autonomous vehicles (AVs) and unmanned aerial vehicles (UAVs), is to ensure their proper functioning under adverse rain or snow conditions. Since the sensing of the surroundings by these vehicles relies on optical sensors such as lidars and cameras, it is essential to ensure the robustness of these systems from the early stages of the project. In this respect, experiments in climatic wind tunnels provide a solution for simulating the operating conditions in which the autonomous vehicles will be confronted. This work proposes a method based on field measurements and unsupervised machine learning to faithfully reproduce in controlled environments real weather conditions captured during wintertime in Ontario, Canada. The purpose of this paper is not to investigate correlations between observed weather conditions and the characteristics of the precipitation encountered, but rather to establish a consistent method based on outdoor disdrometer data to identify critical parameters to be simulated in climatic wind tunnels. To achieve this goal, weather data such as temperature, relative humidity, and droplet size distribution (DSD) were recorded at GM's McLaughlin Advanced Technology Track (MATT) using an FD70 disdrometer and WXT530 weather transmitter, both manufactured by Vaisala, installed on a car provided by the Automotive Center of Excellent (ACE) team of Ontario Tech University. The implementation of the proposed method allowed the identification of precipitation clusters characterized by parameters of a theoretical model for particle size distributions fitted to the collected data.
{"title":"Machine Learning Method for Road Vehicle Collected Data Analysis","authors":"","doi":"10.1175/jamc-d-23-0005.1","DOIUrl":"https://doi.org/10.1175/jamc-d-23-0005.1","url":null,"abstract":"\u0000A major challenge encountered in the development of systems exposed to weather stressors, such as autonomous vehicles (AVs) and unmanned aerial vehicles (UAVs), is to ensure their proper functioning under adverse rain or snow conditions. Since the sensing of the surroundings by these vehicles relies on optical sensors such as lidars and cameras, it is essential to ensure the robustness of these systems from the early stages of the project. In this respect, experiments in climatic wind tunnels provide a solution for simulating the operating conditions in which the autonomous vehicles will be confronted. This work proposes a method based on field measurements and unsupervised machine learning to faithfully reproduce in controlled environments real weather conditions captured during wintertime in Ontario, Canada. The purpose of this paper is not to investigate correlations between observed weather conditions and the characteristics of the precipitation encountered, but rather to establish a consistent method based on outdoor disdrometer data to identify critical parameters to be simulated in climatic wind tunnels. To achieve this goal, weather data such as temperature, relative humidity, and droplet size distribution (DSD) were recorded at GM's McLaughlin Advanced Technology Track (MATT) using an FD70 disdrometer and WXT530 weather transmitter, both manufactured by Vaisala, installed on a car provided by the Automotive Center of Excellent (ACE) team of Ontario Tech University. The implementation of the proposed method allowed the identification of precipitation clusters characterized by parameters of a theoretical model for particle size distributions fitted to the collected data.","PeriodicalId":15027,"journal":{"name":"Journal of Applied Meteorology and Climatology","volume":" ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2023-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48314170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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