Pub Date : 2023-04-05DOI: 10.1175/jamc-d-22-0182.1
F. Ngan, C. Loughner, S. Zinn, M. Cohen, Temple R. Lee, E. Dumas, Travis J. Schuyler, C. Baker, Joseph Maloney, David G. Hotz, George Mathews
A series of meteorological measurements with a small Uncrewed Aircraft System (sUAS) was collected at Oliver Springs Airport, Tennessee. The sUAS provides a unique observing system capable of obtaining vertical profiles of meteorological data within the lowest few hundred meters of the boundary layer. The measurements benefit simulated plume predictions by providing more accurate meteorological data to a dispersion model. The sUAS profiles can be used directly to drive HYSPLIT dispersion simulations. When using sUAS data covering a small domain near a release and meteorological model fields covering a larger domain, simulated pollutants may be artificially increased or decreased near the domain boundary due to inconsistencies in the wind fields between the two meteorological inputs. Numerical experiments using the Weather Research and Forecasting (WRF) model with observational nudging reveal that incorporating sUAS data improves simulated wind fields and can significantly affect mixing characteristics of the boundary layer, especially during the morning transition period of the planetary boundary layer. We conducted HYSPLIT dispersion simulations for hypothetical releases for three case study periods using WRF meteorological fields with and without assimilating sUAS measurements. The comparison of dispersion results on 15 and 16 December 2021 shows that using sUAS observational nudging is more significant under weak synoptic conditions than strong influences from regional weather. Very different dispersion results were introduced by the meteorological fields used. The observational nudging produced not just a sUAS-nudged wind flow but also adjusted meteorological fields that further impacted the mixing calculation in HYSPLIT.
{"title":"The Use of Small Uncrewed Aircraft System Observations in Meteorological and Dispersion Modeling","authors":"F. Ngan, C. Loughner, S. Zinn, M. Cohen, Temple R. Lee, E. Dumas, Travis J. Schuyler, C. Baker, Joseph Maloney, David G. Hotz, George Mathews","doi":"10.1175/jamc-d-22-0182.1","DOIUrl":"https://doi.org/10.1175/jamc-d-22-0182.1","url":null,"abstract":"\u0000A series of meteorological measurements with a small Uncrewed Aircraft System (sUAS) was collected at Oliver Springs Airport, Tennessee. The sUAS provides a unique observing system capable of obtaining vertical profiles of meteorological data within the lowest few hundred meters of the boundary layer. The measurements benefit simulated plume predictions by providing more accurate meteorological data to a dispersion model. The sUAS profiles can be used directly to drive HYSPLIT dispersion simulations. When using sUAS data covering a small domain near a release and meteorological model fields covering a larger domain, simulated pollutants may be artificially increased or decreased near the domain boundary due to inconsistencies in the wind fields between the two meteorological inputs. Numerical experiments using the Weather Research and Forecasting (WRF) model with observational nudging reveal that incorporating sUAS data improves simulated wind fields and can significantly affect mixing characteristics of the boundary layer, especially during the morning transition period of the planetary boundary layer. We conducted HYSPLIT dispersion simulations for hypothetical releases for three case study periods using WRF meteorological fields with and without assimilating sUAS measurements. The comparison of dispersion results on 15 and 16 December 2021 shows that using sUAS observational nudging is more significant under weak synoptic conditions than strong influences from regional weather. Very different dispersion results were introduced by the meteorological fields used. The observational nudging produced not just a sUAS-nudged wind flow but also adjusted meteorological fields that further impacted the mixing calculation in HYSPLIT.","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":"46320615","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 : 2023-03-30DOI: 10.1175/jamc-d-22-0164.1
Alfonso Hernanz, Carlos Correa, M. Domínguez, Esteban Rodríguez-Guisado, E. Rodríguez‐Camino
Statistical downscaling (SD) of climate change projections is a key piece for impact and adaptation studies, due to its low computational expense compared to dynamical downscaling, which allows to explore uncertainties through the generation of large ensembles. SD has been extensively evaluated and applied in the extratropics, but few examples exist in tropical regions. In this study several state-of-the-art methods belonging to different families have been evaluated for maximum/minimum daily temperature and daily accumulated precipitation (both from the ERA5 reanalysis at 0.25°) in two regions with very different climates: Spain (Mid-latitudes) and Central America (Tropics). Some key assumptions of SD have been tested: the strength of the predictors/predictand links, the skill of different approaches and the extrapolation capability of each method. It has been found that relevant predictors are different in both regions, as well as the behavior of statistical methods. For temperature, most methods perform significantly better in Spain than in Central America, where Transfer Function methods present important extrapolation problems, probably due to the low variability of the training sample (present climate). In both regions, Model Output Statistics (MOS) methods have achieved the best results for temperature. In Central America Transfer Function (TF) methods have achieved better results than MOS methods in the evaluation in the present climate, but they do not preserve trends in the future. For precipitation, MOS methods and the machine learning method eXtreme Gradient Boost have achieved the best results in both regions. Additionally, it has been found that although the use of humidity indexes as predictors improve results for the downscaling of precipitation, future trends given by statistical methods are very sensitive to the use of one or another index. Three indexes have been compared: relative humidity, specific humidity and dew point depression. The use of the specific humidity has been found to seriously deviate trends given by the downscaled projections from those given by raw Global Climate Models in both regions.
{"title":"Statistical downscaling in the Tropics and Mid-latitudes: a comparative assessment over two representative regions.","authors":"Alfonso Hernanz, Carlos Correa, M. Domínguez, Esteban Rodríguez-Guisado, E. Rodríguez‐Camino","doi":"10.1175/jamc-d-22-0164.1","DOIUrl":"https://doi.org/10.1175/jamc-d-22-0164.1","url":null,"abstract":"\u0000Statistical downscaling (SD) of climate change projections is a key piece for impact and adaptation studies, due to its low computational expense compared to dynamical downscaling, which allows to explore uncertainties through the generation of large ensembles. SD has been extensively evaluated and applied in the extratropics, but few examples exist in tropical regions. In this study several state-of-the-art methods belonging to different families have been evaluated for maximum/minimum daily temperature and daily accumulated precipitation (both from the ERA5 reanalysis at 0.25°) in two regions with very different climates: Spain (Mid-latitudes) and Central America (Tropics). Some key assumptions of SD have been tested: the strength of the predictors/predictand links, the skill of different approaches and the extrapolation capability of each method. It has been found that relevant predictors are different in both regions, as well as the behavior of statistical methods. For temperature, most methods perform significantly better in Spain than in Central America, where Transfer Function methods present important extrapolation problems, probably due to the low variability of the training sample (present climate). In both regions, Model Output Statistics (MOS) methods have achieved the best results for temperature. In Central America Transfer Function (TF) methods have achieved better results than MOS methods in the evaluation in the present climate, but they do not preserve trends in the future. For precipitation, MOS methods and the machine learning method eXtreme Gradient Boost have achieved the best results in both regions. Additionally, it has been found that although the use of humidity indexes as predictors improve results for the downscaling of precipitation, future trends given by statistical methods are very sensitive to the use of one or another index. Three indexes have been compared: relative humidity, specific humidity and dew point depression. The use of the specific humidity has been found to seriously deviate trends given by the downscaled projections from those given by raw Global Climate Models in both regions.","PeriodicalId":15027,"journal":{"name":"Journal of Applied Meteorology and Climatology","volume":" ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2023-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42191805","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 : 2023-03-29DOI: 10.1175/jamc-d-21-0241.1
Chuancheng Zhao, S. Yao, Yong-jian Ding, Qiudong Zhaoc
Accurate and reliable precipitation product on regular grids is essential for understanding trends and variability within climate studies, for weather forecasting, and in hydrology and agrometeorology applications. However, the construction of high-resolution spatiotemporal precipitation grid product is challenging for complex terrain with sparse rain gauge networks and when only coarse spatial resolutions of satellite data are available. The objective of this study was to consequently provide a practical method to create grid precipitation product by merging accurate quantitative observations from weather stations with continuous spatial information and from satellite-based estimate product. The new gridded precipitation product exhibits a monthly temporal resolution and a spatial resolution of 0.01° for the Tianshan Mountains, while extending back to 1981. To overcome the limitation of low densities and sparse distributions of meteorological stations in the complex terrain of the Tianshan Mountains, a suitable interpolation of ANUSPLIN was used to interpolate grid precipitation based on in situ data. The interpolation grid precipitation was then merged with the satellite precipitation product developed by the U.S. Geological Survey and the Climate Hazards Group. After evaluation and validation using withheld stations and comparison to reference datasets, the result indicated that the merged product exhibit considerable promise for application in complex terrain. The method can be widely applied and is expected to construct precipitation product with high spatial and temporal resolution by merging multiple precipitation data sources.
{"title":"A gridded monthly precipitation merged rain gauge and satellite analysis dataset for the Tianshan Mountains between 1981 and 2019","authors":"Chuancheng Zhao, S. Yao, Yong-jian Ding, Qiudong Zhaoc","doi":"10.1175/jamc-d-21-0241.1","DOIUrl":"https://doi.org/10.1175/jamc-d-21-0241.1","url":null,"abstract":"\u0000Accurate and reliable precipitation product on regular grids is essential for understanding trends and variability within climate studies, for weather forecasting, and in hydrology and agrometeorology applications. However, the construction of high-resolution spatiotemporal precipitation grid product is challenging for complex terrain with sparse rain gauge networks and when only coarse spatial resolutions of satellite data are available. The objective of this study was to consequently provide a practical method to create grid precipitation product by merging accurate quantitative observations from weather stations with continuous spatial information and from satellite-based estimate product. The new gridded precipitation product exhibits a monthly temporal resolution and a spatial resolution of 0.01° for the Tianshan Mountains, while extending back to 1981. To overcome the limitation of low densities and sparse distributions of meteorological stations in the complex terrain of the Tianshan Mountains, a suitable interpolation of ANUSPLIN was used to interpolate grid precipitation based on in situ data. The interpolation grid precipitation was then merged with the satellite precipitation product developed by the U.S. Geological Survey and the Climate Hazards Group. After evaluation and validation using withheld stations and comparison to reference datasets, the result indicated that the merged product exhibit considerable promise for application in complex terrain. The method can be widely applied and is expected to construct precipitation product with high spatial and temporal resolution by merging multiple precipitation data sources.","PeriodicalId":15027,"journal":{"name":"Journal of Applied Meteorology and Climatology","volume":" ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2023-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44752153","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 : 2023-03-15DOI: 10.1175/jamc-d-22-0158.1
A. Hoell, M. Hoerling, X. Quan, R. Robinson
October-September runoff increased 6% and 17% in the Upper (UMRB) and Lower (LMRB) Missouri River Basin, respectively, in a recent (1990-2019) compared to past (1960-1989) climate. The runoff increases were unanticipated, given various projections for semi-permanent drought and/or aridification in the North American Great Plains. Here, five transient coupled climate model ensembles are used to diagnose the effects of natural internal variability and anthropogenic climate change on the observed runoff increases, and to project UMRB and LMRB runoff to the mid-21st century. The runoff increases observed in the recent compared to the past climate were not due to anthropogenic climate change, but resulted mostly from an extreme occurrence of internal multi-decadal variability. High runoff resulted from large, mostly internally-generated, precipitation increases (6% in the UMRB and 5% in the LMRB) that exceeded simulated increases due to climate change forcing alone (0-2% inter-model range). The precipitation elasticity of runoff, which relates runoff sensitivity to precipitation differences in the recent compared to the past climate, led to 1-3-fold and 2-4-fold amplifications of runoff versus precipitation in the UMRB and LMRB, respectively. Without the observed precipitation increases in the recent compared to the past climate, effects of human-induced warming of about 1°C would alone have most likely induced runoff declines of 7% and 13% in the UMRB and LMRB, respectively. Ensemble model simulations overwhelmingly project lower UMRB and LRMB runoff by 2050 compared to 1990-2019, a change found to be insensitive to whether individual realizations experienced high flows in the recent climate.
{"title":"Recent High Missouri River Basin Runoff Was Unlikely Due to Climate Change","authors":"A. Hoell, M. Hoerling, X. Quan, R. Robinson","doi":"10.1175/jamc-d-22-0158.1","DOIUrl":"https://doi.org/10.1175/jamc-d-22-0158.1","url":null,"abstract":"\u0000October-September runoff increased 6% and 17% in the Upper (UMRB) and Lower (LMRB) Missouri River Basin, respectively, in a recent (1990-2019) compared to past (1960-1989) climate. The runoff increases were unanticipated, given various projections for semi-permanent drought and/or aridification in the North American Great Plains. Here, five transient coupled climate model ensembles are used to diagnose the effects of natural internal variability and anthropogenic climate change on the observed runoff increases, and to project UMRB and LMRB runoff to the mid-21st century.\u0000The runoff increases observed in the recent compared to the past climate were not due to anthropogenic climate change, but resulted mostly from an extreme occurrence of internal multi-decadal variability. High runoff resulted from large, mostly internally-generated, precipitation increases (6% in the UMRB and 5% in the LMRB) that exceeded simulated increases due to climate change forcing alone (0-2% inter-model range). The precipitation elasticity of runoff, which relates runoff sensitivity to precipitation differences in the recent compared to the past climate, led to 1-3-fold and 2-4-fold amplifications of runoff versus precipitation in the UMRB and LMRB, respectively. Without the observed precipitation increases in the recent compared to the past climate, effects of human-induced warming of about 1°C would alone have most likely induced runoff declines of 7% and 13% in the UMRB and LMRB, respectively. Ensemble model simulations overwhelmingly project lower UMRB and LRMB runoff by 2050 compared to 1990-2019, a change found to be insensitive to whether individual realizations experienced high flows in the recent climate.","PeriodicalId":15027,"journal":{"name":"Journal of Applied Meteorology and Climatology","volume":" ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2023-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42189659","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 : 2023-03-07DOI: 10.1175/jamc-d-21-0191.1
Y. Miyamoto, Ayako Matsumoto, Soshi Ito
This study examined the statistics of aviation turbulence that occurred in Japan between 2006 and 2018 by analyzing the Pilot Report (PIREP). In total, 81,639 turbulence events, with moderate or greater intensity, were reported over this period. The monthly number of turbulence cases has an annual periodical variation as observed in different regions by previous studies. The number of turbulence cases is high from March to June and low in July and August. Higher number of turbulence cases are experienced along the major flight routes in Japan, especially around Tokyo, for the active period between 9:00 and 20:00 local time. The number of cases of turbulence peaks when the flight reaches an altitude of 33000 ft (FL330), while it reduces when the flight altitude is above FL380 and below FL280. The statistical features are not largely different among the four seasons; however, there are some exceptions. For instance, the number of turbulence cases is large in high altitudes in summer and small in low altitudes in winter. Considering the number of flights, it is evident that the frequency of turbulence is higher in altitudes between FL200 and FL350, although the number of flights is low in this altitude region. The number of convectively induced turbulence is relatively large during the daytime in summer compared with the other seasons. Large number of mountain wave turbulence is observed around the mountainous region in fall and winter when the jet stream flows over Japan.
{"title":"Statistical analysis of Aviation Turbulence in middle–upper troposphere over Japan","authors":"Y. Miyamoto, Ayako Matsumoto, Soshi Ito","doi":"10.1175/jamc-d-21-0191.1","DOIUrl":"https://doi.org/10.1175/jamc-d-21-0191.1","url":null,"abstract":"\u0000This study examined the statistics of aviation turbulence that occurred in Japan between 2006 and 2018 by analyzing the Pilot Report (PIREP). In total, 81,639 turbulence events, with moderate or greater intensity, were reported over this period. The monthly number of turbulence cases has an annual periodical variation as observed in different regions by previous studies. The number of turbulence cases is high from March to June and low in July and August. Higher number of turbulence cases are experienced along the major flight routes in Japan, especially around Tokyo, for the active period between 9:00 and 20:00 local time. The number of cases of turbulence peaks when the flight reaches an altitude of 33000 ft (FL330), while it reduces when the flight altitude is above FL380 and below FL280. The statistical features are not largely different among the four seasons; however, there are some exceptions. For instance, the number of turbulence cases is large in high altitudes in summer and small in low altitudes in winter. Considering the number of flights, it is evident that the frequency of turbulence is higher in altitudes between FL200 and FL350, although the number of flights is low in this altitude region. The number of convectively induced turbulence is relatively large during the daytime in summer compared with the other seasons. Large number of mountain wave turbulence is observed around the mountainous region in fall and winter when the jet stream flows over Japan.","PeriodicalId":15027,"journal":{"name":"Journal of Applied Meteorology and Climatology","volume":" ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2023-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49432564","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 : 2023-03-02DOI: 10.1175/jamc-d-22-0101.1
Shuren Cao, Chunzheng Cao, Yun Li, Lianhua Zhu
We propose a statistical downscaling model based on multi-way functional principal component analysis (FPCA) for rainfall prediction. The model mainly explains the relationship between the winter mean sea level pressure (MSLP) and rainfall in southern Australia from the perspective of functional data. Compared with the traditional approach of feature extraction based on principal component analysis, the multi-way FPCA needs not only fewer principal components to capture most variance in MSLP, bus also greatly avoid the loss of spatial information. A functional principal component (FPC) regression is further developed to simulate both current and future rainfall. The main results show that the first five leading FPCs are sufficient to capture the spatial characteristics of winter MSLP, achieving the purpose of efficient dimensionality reduction. Specifically, no more than three FPCs are required to develop the functional dowscaling models for the winter rainfall over four studied regions. The functional downscaling model provides a good skill in terms of the correlation higher than 0.7 between the predictions and observations, and the ratio of root mean square error to the climatology of winter rainfall below 20% over four regions. The developed downscaling models are further used to interpret the MSLP patterns from four CMIP5 climate models (ACCESS1.3, BCC-CSM1.1-m, CESM1-CAM5 and MPI-ESM-MR), which have been used to simulate both present-day and future climate. The resulting downscaled values based on ensemble MSLP provides (1) a closer representation of observed present-day rainfall than the raw climate model values; (2) alternative estimates of future changes in rainfall that arises from changes in MSLP.
{"title":"A statistical downscaling model based on multi-way functional principal component analysis for southern Australia winter rainfall","authors":"Shuren Cao, Chunzheng Cao, Yun Li, Lianhua Zhu","doi":"10.1175/jamc-d-22-0101.1","DOIUrl":"https://doi.org/10.1175/jamc-d-22-0101.1","url":null,"abstract":"\u0000We propose a statistical downscaling model based on multi-way functional principal component analysis (FPCA) for rainfall prediction. The model mainly explains the relationship between the winter mean sea level pressure (MSLP) and rainfall in southern Australia from the perspective of functional data. Compared with the traditional approach of feature extraction based on principal component analysis, the multi-way FPCA needs not only fewer principal components to capture most variance in MSLP, bus also greatly avoid the loss of spatial information. A functional principal component (FPC) regression is further developed to simulate both current and future rainfall. The main results show that the first five leading FPCs are sufficient to capture the spatial characteristics of winter MSLP, achieving the purpose of efficient dimensionality reduction. Specifically, no more than three FPCs are required to develop the functional dowscaling models for the winter rainfall over four studied regions. The functional downscaling model provides a good skill in terms of the correlation higher than 0.7 between the predictions and observations, and the ratio of root mean square error to the climatology of winter rainfall below 20% over four regions. The developed downscaling models are further used to interpret the MSLP patterns from four CMIP5 climate models (ACCESS1.3, BCC-CSM1.1-m, CESM1-CAM5 and MPI-ESM-MR), which have been used to simulate both present-day and future climate. The resulting downscaled values based on ensemble MSLP provides (1) a closer representation of observed present-day rainfall than the raw climate model values; (2) alternative estimates of future changes in rainfall that arises from changes in MSLP.","PeriodicalId":15027,"journal":{"name":"Journal of Applied Meteorology and Climatology","volume":" ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2023-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42087814","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 : 2023-03-01DOI: 10.1175/jamc-d-22-0011.1
S. Farina, Mattia Marchio, F. Barbano, S. Di Sabatino, D. Zardi
This paper investigates the surface layer processes associated with the morning transition from nighttime downslope winds to daytime upslope winds over a semi-isolated massif. It provides an insight into the characteristics of the transition and its connection with the processes controlling the erosion of the temperature inversion at the foot of the slope. First, a criterion for the identification of days prone to the development of purely thermally driven slope winds is proposed and adopted to select five representative case studies. Then, the mechanisms leading to different patterns of erosion of the nocturnal temperature inversion at the foot of the slope are analyzed. Three main patterns of erosion are identified: the first is connected to the growth of the convective boundary layer at the surface, the second to the descent of the inversion top, and the third to a combination of the previous two. The first pattern is linked to the initiation of the morning transition through surface heating, while the second pattern is connected to the top-down dilution mechanism and so to mixing with the above air. The discriminating factor in the determination of the erosion pattern is identified in the partitioning of turbulent sensible heat flux at the surface.
{"title":"Characterization Of The Morning Transition Over The Gentle Slope Of A Semi-Isolated Massif","authors":"S. Farina, Mattia Marchio, F. Barbano, S. Di Sabatino, D. Zardi","doi":"10.1175/jamc-d-22-0011.1","DOIUrl":"https://doi.org/10.1175/jamc-d-22-0011.1","url":null,"abstract":"\u0000This paper investigates the surface layer processes associated with the morning transition from nighttime downslope winds to daytime upslope winds over a semi-isolated massif. It provides an insight into the characteristics of the transition and its connection with the processes controlling the erosion of the temperature inversion at the foot of the slope. First, a criterion for the identification of days prone to the development of purely thermally driven slope winds is proposed and adopted to select five representative case studies. Then, the mechanisms leading to different patterns of erosion of the nocturnal temperature inversion at the foot of the slope are analyzed. Three main patterns of erosion are identified: the first is connected to the growth of the convective boundary layer at the surface, the second to the descent of the inversion top, and the third to a combination of the previous two. The first pattern is linked to the initiation of the morning transition through surface heating, while the second pattern is connected to the top-down dilution mechanism and so to mixing with the above air. The discriminating factor in the determination of the erosion pattern is identified in the partitioning of turbulent sensible heat flux at the surface.","PeriodicalId":15027,"journal":{"name":"Journal of Applied Meteorology and Climatology","volume":" ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45009739","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 : 2023-02-28DOI: 10.1175/jamc-d-21-0266.1
A. Tokay, L. Liao, R. Meneghini, C. N. Helms, S. Munchak, D. Wolff, P. Gatlin
Parameters of the normalized gamma particle size distribution (PSD) have been retrieved from the Precipitation Image Package (PIP) snowfall observations collected during the International Collaborative Experiment - PyeongChang Olympics and Paralympic (ICE-POP 2018). Two of the gamma PSD parameters, the mass weighted particle diameter (Dmass) and the normalized intercept parameter NW, have median values of 1.15-1.31 mm and 2.84-3.04 log(mm−1 m−3), respectively. This range arises from the choice of the relationship between the maximum versus equivalent diameter, Dmx−Deq, and the relationship between the Reynolds and Best numbers, Re-X. Normalization of snow water equivalent rate (SWER) and ice water content (W) by NW reduces the range in NW resulting in well fitted power law relationship, between SWER/NW and Dmass and between W/NW and Dmass. The bulk descriptors of snowfall are calculated from PIP observations and from the gamma PSD with values of the shape parameter (μ) ranging from −2 to 10. NASA's Global Precipitation Measurement (GPM) mission, which adopted the normalized gamma PSD, assumes μ = 2 and μ = 3 in its two separate algorithms. The mean fractional bias (MFB) of the snowfall parameters changes with μ, where the functional dependence on μ depends on the specific snowfall parameter of interest. The MFB of the total concentration was underestimated by 0.23−0.34 when μ = 2 and by 0.29−0.40 when μ = 3, while the MFB of SWER had a much narrower range (−0.03 to 0.04) for the same μ values.
{"title":"Retrieval of Normalized Gamma Size Distribution Parameters using Precipitation Imaging Package (PIP) Snowfall Observations during ICE-POP 2018","authors":"A. Tokay, L. Liao, R. Meneghini, C. N. Helms, S. Munchak, D. Wolff, P. Gatlin","doi":"10.1175/jamc-d-21-0266.1","DOIUrl":"https://doi.org/10.1175/jamc-d-21-0266.1","url":null,"abstract":"\u0000Parameters of the normalized gamma particle size distribution (PSD) have been retrieved from the Precipitation Image Package (PIP) snowfall observations collected during the International Collaborative Experiment - PyeongChang Olympics and Paralympic (ICE-POP 2018). Two of the gamma PSD parameters, the mass weighted particle diameter (Dmass) and the normalized intercept parameter NW, have median values of 1.15-1.31 mm and 2.84-3.04 log(mm−1 m−3), respectively. This range arises from the choice of the relationship between the maximum versus equivalent diameter, Dmx−Deq, and the relationship between the Reynolds and Best numbers, Re-X. Normalization of snow water equivalent rate (SWER) and ice water content (W) by NW reduces the range in NW resulting in well fitted power law relationship, between SWER/NW and Dmass and between W/NW and Dmass. The bulk descriptors of snowfall are calculated from PIP observations and from the gamma PSD with values of the shape parameter (μ) ranging from −2 to 10. NASA's Global Precipitation Measurement (GPM) mission, which adopted the normalized gamma PSD, assumes μ = 2 and μ = 3 in its two separate algorithms. The mean fractional bias (MFB) of the snowfall parameters changes with μ, where the functional dependence on μ depends on the specific snowfall parameter of interest. The MFB of the total concentration was underestimated by 0.23−0.34 when μ = 2 and by 0.29−0.40 when μ = 3, while the MFB of SWER had a much narrower range (−0.03 to 0.04) for the same μ values.","PeriodicalId":15027,"journal":{"name":"Journal of Applied Meteorology and Climatology","volume":" ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46335959","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 : 2023-02-24DOI: 10.1175/jamc-d-22-0161.1
S. Lagmiri, S. Dahech
Daily atmospheric concentrations of the pollutants PM10 and O3 vary according to weather types. This study aims to identify the weather patterns associated with PM10 and O3 pollution episodes from 2009 to 2020. Episodes characterized by exceedance of WHO standards were identified, and their duration and persistence were studied. The results show that air pollution days are associated with three atmospheric patterns for PM10 and four for O3. The dominant weather pattern corresponds to an anticyclonic situation in central and eastern Europe with a ridge of high pressure over France at the surface and a 500 hPa geopotential height. For PM10, the persistent high-concentration sequences were found to be associated with a thermal inversion constraining the vertical dispersion of pollutants. For O3, the four weather types responsible for ozone pollution all have a higher occurrence in summer. The highest percentage (46% of days) is associated with the presence of a ground-level barometric swamp and a ridge at 500 hPa (weather type T1). Similarly, thermal inversions and thermal winds cause pollution to persist beyond 8 consecutive days.
{"title":"Weather types and their influence on PM10 and O3 urban concentrations in the Cergy-Pontoise conurbation","authors":"S. Lagmiri, S. Dahech","doi":"10.1175/jamc-d-22-0161.1","DOIUrl":"https://doi.org/10.1175/jamc-d-22-0161.1","url":null,"abstract":"\u0000Daily atmospheric concentrations of the pollutants PM10 and O3 vary according to weather types. This study aims to identify the weather patterns associated with PM10 and O3 pollution episodes from 2009 to 2020. Episodes characterized by exceedance of WHO standards were identified, and their duration and persistence were studied. The results show that air pollution days are associated with three atmospheric patterns for PM10 and four for O3. The dominant weather pattern corresponds to an anticyclonic situation in central and eastern Europe with a ridge of high pressure over France at the surface and a 500 hPa geopotential height. For PM10, the persistent high-concentration sequences were found to be associated with a thermal inversion constraining the vertical dispersion of pollutants. For O3, the four weather types responsible for ozone pollution all have a higher occurrence in summer. The highest percentage (46% of days) is associated with the presence of a ground-level barometric swamp and a ridge at 500 hPa (weather type T1). Similarly, thermal inversions and thermal winds cause pollution to persist beyond 8 consecutive days.","PeriodicalId":15027,"journal":{"name":"Journal of Applied Meteorology and Climatology","volume":" ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2023-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45995265","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 : 2023-02-22DOI: 10.1175/jamc-d-22-0145.1
Dilchand Nauth, C. Loughner, M. Tzortziou
The continually changing atmospheric conditions over densely populated coastal urban regions make it challenging to produce models that accurately capture the complex interactions of anthropogenic and environmental emissions, chemical reactions, and unique meteorological processes, such as sea- and land-breeze circulations. The purpose of this study is to determine and identify the influence of synoptic scale wind patterns on the development of local scale sea breeze circulations and air quality over the New York City (NYC) metropolitan area. This study utilizes column integrated nitrogen dioxide observations made during the Long Island Sound Tropospheric Ozone Study (LISTOS) field campaign, ground level ozone observations, the HRRR numerical weather prediction model, and trajectory model simulations using the NOAA HYSPLIT model. A cluster analysis within the HYSPLIT modeling system was performed to determine that there were six unique synoptic scale transport pathways for NYC. Stagnant conditions or weak transport out of the northwest resulted in the worst air quality for NYC. Weak synoptic scale forcings associated with these conditions allowed for local scale sea breeze circulations to develop resulting in air pollution to recirculate and mix with freshly emitted pollutants.
{"title":"The influence of synoptic scale wind patterns on column integrated nitrogen dioxide, ground level ozone, and the development of sea breeze circulations in the New York City metropolitan area","authors":"Dilchand Nauth, C. Loughner, M. Tzortziou","doi":"10.1175/jamc-d-22-0145.1","DOIUrl":"https://doi.org/10.1175/jamc-d-22-0145.1","url":null,"abstract":"\u0000The continually changing atmospheric conditions over densely populated coastal urban regions make it challenging to produce models that accurately capture the complex interactions of anthropogenic and environmental emissions, chemical reactions, and unique meteorological processes, such as sea- and land-breeze circulations. The purpose of this study is to determine and identify the influence of synoptic scale wind patterns on the development of local scale sea breeze circulations and air quality over the New York City (NYC) metropolitan area. This study utilizes column integrated nitrogen dioxide observations made during the Long Island Sound Tropospheric Ozone Study (LISTOS) field campaign, ground level ozone observations, the HRRR numerical weather prediction model, and trajectory model simulations using the NOAA HYSPLIT model. A cluster analysis within the HYSPLIT modeling system was performed to determine that there were six unique synoptic scale transport pathways for NYC. Stagnant conditions or weak transport out of the northwest resulted in the worst air quality for NYC. Weak synoptic scale forcings associated with these conditions allowed for local scale sea breeze circulations to develop resulting in air pollution to recirculate and mix with freshly emitted pollutants.","PeriodicalId":15027,"journal":{"name":"Journal of Applied Meteorology and Climatology","volume":" ","pages":""},"PeriodicalIF":3.0,"publicationDate":"2023-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43958793","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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