Pub Date : 2023-11-11DOI: 10.3390/meteorology2040027
Vladimir S. Kostsov, Dmitry V. Ionov
Liquid water path (LWP) is one of the most important cloud parameters and is crucial for global and regional climate modelling, weather forecasting, and modelling of the hydrological cycle and interactions between different components of the climate system: the atmosphere, the hydrosphere, and the land surface. Space-borne observations by the SEVIRI instrument have already provided evidence of the systematic difference between the cloud LWP values derived over the land surface in Northern Europe and those derived over the Baltic Sea and major lakes during both cold and warm seasons. In the present study, the analysis of this LWP land-sea contrast for the period 2011–2017 reveals specific temporal and spatial variations, which, in some cases, seem to be artefacts rather than of natural origin. The geographical objects of investigation are water bodies and water areas located in Northern Europe that differ in size and other geophysical characteristics: the Gulf of Finland and the Gulf of Riga in the Baltic Sea and large and small lakes in the neighbouring region. The analysis of intra-seasonal features has detected anomalous conditions in the Gulf of Riga and the Gulf of Finland, which show up as very low values of the LWP land-sea contrast in August with respect to the values in June and July every year within the considered time period. This anomaly is likely an artefact caused by the LWP retrieval algorithm since the transition from large LWP contrast to very low contrast occurs sharply, synchronically, and at a certain date every year at different places in the Baltic Sea.
{"title":"Specific Features of the Land-Sea Contrast of Cloud Liquid Water Path in Northern Europe as Obtained from the Observations by the SEVIRI Instrument: Artefacts or Reality?","authors":"Vladimir S. Kostsov, Dmitry V. Ionov","doi":"10.3390/meteorology2040027","DOIUrl":"https://doi.org/10.3390/meteorology2040027","url":null,"abstract":"Liquid water path (LWP) is one of the most important cloud parameters and is crucial for global and regional climate modelling, weather forecasting, and modelling of the hydrological cycle and interactions between different components of the climate system: the atmosphere, the hydrosphere, and the land surface. Space-borne observations by the SEVIRI instrument have already provided evidence of the systematic difference between the cloud LWP values derived over the land surface in Northern Europe and those derived over the Baltic Sea and major lakes during both cold and warm seasons. In the present study, the analysis of this LWP land-sea contrast for the period 2011–2017 reveals specific temporal and spatial variations, which, in some cases, seem to be artefacts rather than of natural origin. The geographical objects of investigation are water bodies and water areas located in Northern Europe that differ in size and other geophysical characteristics: the Gulf of Finland and the Gulf of Riga in the Baltic Sea and large and small lakes in the neighbouring region. The analysis of intra-seasonal features has detected anomalous conditions in the Gulf of Riga and the Gulf of Finland, which show up as very low values of the LWP land-sea contrast in August with respect to the values in June and July every year within the considered time period. This anomaly is likely an artefact caused by the LWP retrieval algorithm since the transition from large LWP contrast to very low contrast occurs sharply, synchronically, and at a certain date every year at different places in the Baltic Sea.","PeriodicalId":100061,"journal":{"name":"Agricultural Meteorology","volume":"38 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135086730","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-14DOI: 10.3390/meteorology2040026
Adrian F. Tuck
Four observational results: the intermittency of air temperature; its correlation with ozone photodissociation rate; the diurnal variation of ozone in the upper stratosphere; and the cold bias of meteorological analyses compared to observations, are reviewed. The excitation of photofragments and their persistence of velocity after collision is appealed to as a possible explanation. Consequences are discussed, including the interpretation of the Langevin equation and fluctuation–dissipation in the atmosphere, the role of scale invariance and statistical multifractality, and what the results might mean for the distribution of isotopes among atmospheric molecules. An adjunct of the analysis is an exponent characterizing jet streams. Observational tests are suggested.
{"title":"Air Temperature Intermittency and Photofragment Excitation","authors":"Adrian F. Tuck","doi":"10.3390/meteorology2040026","DOIUrl":"https://doi.org/10.3390/meteorology2040026","url":null,"abstract":"Four observational results: the intermittency of air temperature; its correlation with ozone photodissociation rate; the diurnal variation of ozone in the upper stratosphere; and the cold bias of meteorological analyses compared to observations, are reviewed. The excitation of photofragments and their persistence of velocity after collision is appealed to as a possible explanation. Consequences are discussed, including the interpretation of the Langevin equation and fluctuation–dissipation in the atmosphere, the role of scale invariance and statistical multifractality, and what the results might mean for the distribution of isotopes among atmospheric molecules. An adjunct of the analysis is an exponent characterizing jet streams. Observational tests are suggested.","PeriodicalId":100061,"journal":{"name":"Agricultural Meteorology","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135766139","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-26DOI: 10.3390/meteorology2040025
Léa Berthomier, Laurent Perier
Estimating precipitation is of critical importance to climate systems and decision-making processes. This paper presents Espresso, a deep learning model designed for estimating precipitation from satellite observations on a global scale. Conventional methods, like ground-based radars, are limited in terms of spatial coverage. Satellite observations, on the other hand, allow global coverage. Combined with deep learning methods, these observations offer the opportunity to address the challenge of estimating precipitation on a global scale. This research paper presents the development of a deep learning model using geostationary satellite data as input and generating instantaneous rainfall rates, calibrated using data from the Global Precipitation Measurement Core Observatory (GPMCO). The performance impact of various input data configurations on Espresso was investigated. These configurations include a sequence of four images from geostationary satellites and the optimal selection of channels. Additional descriptive features were explored to enhance the model’s robustness for global applications. When evaluated against the GPMCO test set, Espresso demonstrated highly accurate precipitation estimation, especially within equatorial regions. A comparison against six other operational products using multiple metrics indicated its competitive performance. The model’s superior storm localization and intensity estimation were further confirmed through visual comparisons in case studies. Espresso has been incorporated as an operational product at Météo-France, delivering high-quality, real-time global precipitation estimates every 30 min.
{"title":"Espresso: A Global Deep Learning Model to Estimate Precipitation from Satellite Observations","authors":"Léa Berthomier, Laurent Perier","doi":"10.3390/meteorology2040025","DOIUrl":"https://doi.org/10.3390/meteorology2040025","url":null,"abstract":"Estimating precipitation is of critical importance to climate systems and decision-making processes. This paper presents Espresso, a deep learning model designed for estimating precipitation from satellite observations on a global scale. Conventional methods, like ground-based radars, are limited in terms of spatial coverage. Satellite observations, on the other hand, allow global coverage. Combined with deep learning methods, these observations offer the opportunity to address the challenge of estimating precipitation on a global scale. This research paper presents the development of a deep learning model using geostationary satellite data as input and generating instantaneous rainfall rates, calibrated using data from the Global Precipitation Measurement Core Observatory (GPMCO). The performance impact of various input data configurations on Espresso was investigated. These configurations include a sequence of four images from geostationary satellites and the optimal selection of channels. Additional descriptive features were explored to enhance the model’s robustness for global applications. When evaluated against the GPMCO test set, Espresso demonstrated highly accurate precipitation estimation, especially within equatorial regions. A comparison against six other operational products using multiple metrics indicated its competitive performance. The model’s superior storm localization and intensity estimation were further confirmed through visual comparisons in case studies. Espresso has been incorporated as an operational product at Météo-France, delivering high-quality, real-time global precipitation estimates every 30 min.","PeriodicalId":100061,"journal":{"name":"Agricultural Meteorology","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134887070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-09-05DOI: 10.3390/meteorology2030024
Mohamed Hachaichi
Cities are progressively heightening their climate aspirations to curtail urban carbon emissions and establish a future where economies and communities can flourish within the Earth’s ecological limits. Consequently, numerous climate initiatives are being launched to control urban carbon emissions, targeting various sectors, including transport, residential, agricultural, and energy. However, recent scientific literature underscores the disproportionate distribution of climate policies. While cities in the Global North have witnessed several initiatives to combat climate change, cities in the Global South remain uncovered and highly vulnerable to climate hazards. To address this disparity, we employed the Balanced Iterative Reducing and Clustering using the Hierarchies (BRICH) algorithm to cluster cities from diverse geographical areas that exhibit comparable socioeconomic profiles. This clustering strives to foster enhanced cooperation and collaboration among cities globally, with the goal of addressing climate change in a comprehensive manner. In summary, we identified similarities, patterns, and clusters among peer cities, enabling mutual and generalizable learning among worldwide peer-cities regarding urban climate policy exchange. This exchange occurs through three approaches: (i) inner-mutual learning, (ii) cross-mutual learning, and (iii) outer-mutual learning. Our findings mark a pivotal stride towards attaining worldwide climate objectives through a shared responsibility approach. Furthermore, they provide preliminary insights into the implementation of “urban climate policy exchange” among peer cities on a global scale.
{"title":"No City Left Behind: Building Climate Policy Bridges between the North and South","authors":"Mohamed Hachaichi","doi":"10.3390/meteorology2030024","DOIUrl":"https://doi.org/10.3390/meteorology2030024","url":null,"abstract":"Cities are progressively heightening their climate aspirations to curtail urban carbon emissions and establish a future where economies and communities can flourish within the Earth’s ecological limits. Consequently, numerous climate initiatives are being launched to control urban carbon emissions, targeting various sectors, including transport, residential, agricultural, and energy. However, recent scientific literature underscores the disproportionate distribution of climate policies. While cities in the Global North have witnessed several initiatives to combat climate change, cities in the Global South remain uncovered and highly vulnerable to climate hazards. To address this disparity, we employed the Balanced Iterative Reducing and Clustering using the Hierarchies (BRICH) algorithm to cluster cities from diverse geographical areas that exhibit comparable socioeconomic profiles. This clustering strives to foster enhanced cooperation and collaboration among cities globally, with the goal of addressing climate change in a comprehensive manner. In summary, we identified similarities, patterns, and clusters among peer cities, enabling mutual and generalizable learning among worldwide peer-cities regarding urban climate policy exchange. This exchange occurs through three approaches: (i) inner-mutual learning, (ii) cross-mutual learning, and (iii) outer-mutual learning. Our findings mark a pivotal stride towards attaining worldwide climate objectives through a shared responsibility approach. Furthermore, they provide preliminary insights into the implementation of “urban climate policy exchange” among peer cities on a global scale.","PeriodicalId":100061,"journal":{"name":"Agricultural Meteorology","volume":"36 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75849746","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-23DOI: 10.3390/meteorology2030023
Vasilică Istrate, Dorin Podiuc, Dragoș Andrei Sîrbu, Eduard Popescu, Emil Sîrbu, Doru Dorian Popescu
Using a database of 378 hail days between 1981 and 2020, the climatic characteristics of 23 convective parameters from sounding data and ERA5 data were statistically analysed. The goal of this work is to evaluate the usefulness and representativeness of convective parameters derived from sounding data and reanalysis data for the operational forecast of the hail phenomenon. As a result, the average values from 12:00 UTC were 433 J/kg for CAPE in the case of data from ERA5 and 505 J/kg from rawinsonde, respectively. The Spearman correlation coefficient matrix between the values of the parameters indicates high correlations among the parameters calculated based on the parcel theory, humidity indices, and the complex indices. The probability for large hail increases with high values of low-level and boundary-layer moisture, high CAPE, and a high lifting condensation level (LCL) height.
{"title":"Characteristics of Convective Parameters Derived from Rawinsonde and ERA5 Data Associated with Hailstorms in Northeastern Romania","authors":"Vasilică Istrate, Dorin Podiuc, Dragoș Andrei Sîrbu, Eduard Popescu, Emil Sîrbu, Doru Dorian Popescu","doi":"10.3390/meteorology2030023","DOIUrl":"https://doi.org/10.3390/meteorology2030023","url":null,"abstract":"Using a database of 378 hail days between 1981 and 2020, the climatic characteristics of 23 convective parameters from sounding data and ERA5 data were statistically analysed. The goal of this work is to evaluate the usefulness and representativeness of convective parameters derived from sounding data and reanalysis data for the operational forecast of the hail phenomenon. As a result, the average values from 12:00 UTC were 433 J/kg for CAPE in the case of data from ERA5 and 505 J/kg from rawinsonde, respectively. The Spearman correlation coefficient matrix between the values of the parameters indicates high correlations among the parameters calculated based on the parcel theory, humidity indices, and the complex indices. The probability for large hail increases with high values of low-level and boundary-layer moisture, high CAPE, and a high lifting condensation level (LCL) height.","PeriodicalId":100061,"journal":{"name":"Agricultural Meteorology","volume":"191 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81068105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-07DOI: 10.3390/meteorology2030022
J. Schiavone
Better understanding of roll vortices that often occur in the tropical cyclone (TC) boundary layer is required to improve forecasts of TC intensification and the granularity of damaging surface winds. It is especially important to characterize rolls over a wide variety of TCs, their environments, and TC development phases. Boundary layer rolls have been observed in TCs since 1998, but only recently in a TC during its extratropical transition phase. The work reported herein is the first to analyze how boundary layer rolls are distributed among the extratropical features of a transitioning TC. To this end, routine and special operational observations recorded during landfalling Post-tropical Cyclone Sandy (2012) were leveraged, including radar, surface, rawinsonde, and aircraft reconnaissance observations. Large rolls occurred in cold airstreams, both in the cold conveyor belt within the northwestern storm quadrant and in the secluding airstream within the northeastern quadrant, but roll presence was much diminished within the intervening warm sector. The large size of the rolls and their confinement to cold airstreams is attributed to an optimum inflow layer depth, which is deep enough below a strong stable layer to accommodate deep and strong positive radial wind shear to promote roll growth, yet not so deep as to limit radial wind shear magnitude, as occurred in the warm sector.
{"title":"Airstream Association of Large Boundary Layer Rolls during Extratropical Transition of Post-Tropical Cyclone Sandy (2012)","authors":"J. Schiavone","doi":"10.3390/meteorology2030022","DOIUrl":"https://doi.org/10.3390/meteorology2030022","url":null,"abstract":"Better understanding of roll vortices that often occur in the tropical cyclone (TC) boundary layer is required to improve forecasts of TC intensification and the granularity of damaging surface winds. It is especially important to characterize rolls over a wide variety of TCs, their environments, and TC development phases. Boundary layer rolls have been observed in TCs since 1998, but only recently in a TC during its extratropical transition phase. The work reported herein is the first to analyze how boundary layer rolls are distributed among the extratropical features of a transitioning TC. To this end, routine and special operational observations recorded during landfalling Post-tropical Cyclone Sandy (2012) were leveraged, including radar, surface, rawinsonde, and aircraft reconnaissance observations. Large rolls occurred in cold airstreams, both in the cold conveyor belt within the northwestern storm quadrant and in the secluding airstream within the northeastern quadrant, but roll presence was much diminished within the intervening warm sector. The large size of the rolls and their confinement to cold airstreams is attributed to an optimum inflow layer depth, which is deep enough below a strong stable layer to accommodate deep and strong positive radial wind shear to promote roll growth, yet not so deep as to limit radial wind shear magnitude, as occurred in the warm sector.","PeriodicalId":100061,"journal":{"name":"Agricultural Meteorology","volume":"52 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75039448","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-31DOI: 10.3390/meteorology2030020
J. Phadtare
During the post-monsoon cyclone season, the landfalls of westward-moving cyclonic systems often lead to extreme rainfall over the east coast of the Indian peninsula. A stationary cyclonic system over the coast can produce heavy rainfall for several days and cause catastrophic flooding. This study analyzes the dynamics of a propagating and stationary cyclonic system over the east coast, highlighting the possible cause behind the stagnation. The vorticity budgets of these two systems are presented using a reanalysis dataset. Vortex stretching and horizontal vorticity advection were the dominant terms in the budget. Vertical advection and tilting terms were significant over the orography. The horizontal advection of vorticity was positive (negative) on the western (eastern) side of the systems and, thus, favored westward propagation. Vortex stretching was confined to the upstream of orography in the stationary vortex. In the propagating vortex, the vortex stretching occurred over the orography during its passage. Data from the radiosonde soundings over a coastal station showed orographic blocking of the low-level winds in the stationary case. Conversely, the flow crossed the orographic barrier in the propagating case. Thus, the predominance of the upstream orographic convergence over the vortex circulation can be the reason for system stagnation over the coast.
{"title":"Influence of Underlying Topography on Post-Monsoon Cyclonic Systems over the Indian Peninsula","authors":"J. Phadtare","doi":"10.3390/meteorology2030020","DOIUrl":"https://doi.org/10.3390/meteorology2030020","url":null,"abstract":"During the post-monsoon cyclone season, the landfalls of westward-moving cyclonic systems often lead to extreme rainfall over the east coast of the Indian peninsula. A stationary cyclonic system over the coast can produce heavy rainfall for several days and cause catastrophic flooding. This study analyzes the dynamics of a propagating and stationary cyclonic system over the east coast, highlighting the possible cause behind the stagnation. The vorticity budgets of these two systems are presented using a reanalysis dataset. Vortex stretching and horizontal vorticity advection were the dominant terms in the budget. Vertical advection and tilting terms were significant over the orography. The horizontal advection of vorticity was positive (negative) on the western (eastern) side of the systems and, thus, favored westward propagation. Vortex stretching was confined to the upstream of orography in the stationary vortex. In the propagating vortex, the vortex stretching occurred over the orography during its passage. Data from the radiosonde soundings over a coastal station showed orographic blocking of the low-level winds in the stationary case. Conversely, the flow crossed the orographic barrier in the propagating case. Thus, the predominance of the upstream orographic convergence over the vortex circulation can be the reason for system stagnation over the coast.","PeriodicalId":100061,"journal":{"name":"Agricultural Meteorology","volume":"16 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78372633","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-31DOI: 10.3390/meteorology2030021
N. Cook
The reliability of extreme wind speed predictions at large mean recurrence intervals (MRI) is assessed by bootstrapping samples from representative known distributions. The classical asymptotic generalized extreme value distribution (GEV) and the generalized Pareto (GPD) distribution are compared with a contemporary sub-asymptotic Gumbel distribution that accounts for incomplete convergence to the correct asymptote. The sub-asymptotic model is implemented through a modified Gringorten method for epoch maxima and through the XIMIS method for peak-over-threshold values. The mean bias error is shown to be minimal in all cases, so that the variability expressed by the standard error becomes the principal reliability metric. Peak-over-threshold (POT) methods are shown to always be more reliable than epoch methods due to the additional sub-epoch data. The generalized asymptotic methods are shown to always be less reliable than the sub-asymptotic methods by a factor that increases with MRI. This study reinforces the previously published theory-based arguments that GEV and GPD are unsuitable models for extreme wind speeds by showing that they also provide the least reliable predictions in practice. A new two-step Weibull-XIMIS hybrid method is shown to have superior reliability.
{"title":"Reliability of Extreme Wind Speeds Predicted by Extreme-Value Analysis","authors":"N. Cook","doi":"10.3390/meteorology2030021","DOIUrl":"https://doi.org/10.3390/meteorology2030021","url":null,"abstract":"The reliability of extreme wind speed predictions at large mean recurrence intervals (MRI) is assessed by bootstrapping samples from representative known distributions. The classical asymptotic generalized extreme value distribution (GEV) and the generalized Pareto (GPD) distribution are compared with a contemporary sub-asymptotic Gumbel distribution that accounts for incomplete convergence to the correct asymptote. The sub-asymptotic model is implemented through a modified Gringorten method for epoch maxima and through the XIMIS method for peak-over-threshold values. The mean bias error is shown to be minimal in all cases, so that the variability expressed by the standard error becomes the principal reliability metric. Peak-over-threshold (POT) methods are shown to always be more reliable than epoch methods due to the additional sub-epoch data. The generalized asymptotic methods are shown to always be less reliable than the sub-asymptotic methods by a factor that increases with MRI. This study reinforces the previously published theory-based arguments that GEV and GPD are unsuitable models for extreme wind speeds by showing that they also provide the least reliable predictions in practice. A new two-step Weibull-XIMIS hybrid method is shown to have superior reliability.","PeriodicalId":100061,"journal":{"name":"Agricultural Meteorology","volume":"16 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88840194","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-12DOI: 10.3390/meteorology2030019
Felipe M. de Andrade, V. A. Godoi, J. Aravéquia
El Niño is generally associated with negative rainfall anomalies (below-average rainfall) in northern Northeast Brazil (NNEB). In 2019, however, the opposite rainfall pattern was observed during an El Niño episode. Here, we explore the mechanisms that overwhelmed typical El Niño-related conditions and resulted in positive rainfall anomalies (above-average rainfall) in NNEB. We focus on the austral autumn when El Niño is most prone to rainfall anomalies in the region. The analysis of several datasets, including weather station data, satellite data, reanalysis data, and modelled data derived from a dry linear baroclinic model, allowed us to identify that the austral autumn 2019 above-average rainfall in NNEB was likely associated with four combined factors; these are (1) the weak intensity of the 2019 El Niño; (2) the negative phase of the Atlantic Meridional Mode; (3) local and remote diabatic heating anomalies, especially over the western South Pacific and tropical South Atlantic, which resulted in anticyclonic and cyclonic circulations in the upper and lower troposphere, respectively, over the tropical South Atlantic; and (4) sub-seasonal atmospheric convection anomalies over the western South Pacific, which reinforced the low-frequency convection signal over that region. This latter factor suggests the influence of the Madden–Julian Oscillation on rainfall in NNEB during the first ten days of March 2019. We discuss these mechanisms in detail and provide evidence that, even during an El Niño event, above-average rainfall in NNEB in the austral autumn may occur, and its modulation is not limited to the influence of a single climate phenomenon. Our results may assist in the planning of several crucial activities, such as water resources management and agriculture.
El Niño通常与巴西东北北部(NNEB)的负降雨异常(低于平均降雨量)有关。然而，在2019年的厄尔尼诺Niño事件期间观察到相反的降雨模式。在这里，我们探讨了克服典型El Niño-related条件并导致NNEB正降雨异常(高于平均降雨量)的机制。我们将重点放在厄尔尼诺Niño最容易出现降雨异常的南方秋季。对几个数据集的分析，包括气象站数据、卫星数据、再分析数据和来自干线性斜压模型的建模数据，使我们能够确定NNEB 2019年秋季南部高于平均水平的降雨量可能与四个综合因素有关;这些是(1)2019年厄尔尼诺Niño弱强度;(2)大西洋经向模态负相;(3)局地和远地非绝热加热异常，特别是南太平洋西部和热带南大西洋，导致热带南大西洋对流层上层和下层分别出现反气旋和气旋环流;(4)南太平洋西部的次季节大气对流异常，强化了该地区的低频对流信号。后一个因素表明了2019年3月上旬麦登-朱利安涛动对NNEB降水的影响。我们详细讨论了这些机制，并提供证据表明，即使在El Niño事件期间，NNEB南部秋季也可能出现高于平均水平的降雨，其调节并不局限于单一气候现象的影响。我们的结果可能有助于规划若干关键活动，例如水资源管理和农业。
{"title":"Why Above-Average Rainfall Occurred in Northern Northeast Brazil during the 2019 El Niño?","authors":"Felipe M. de Andrade, V. A. Godoi, J. Aravéquia","doi":"10.3390/meteorology2030019","DOIUrl":"https://doi.org/10.3390/meteorology2030019","url":null,"abstract":"El Niño is generally associated with negative rainfall anomalies (below-average rainfall) in northern Northeast Brazil (NNEB). In 2019, however, the opposite rainfall pattern was observed during an El Niño episode. Here, we explore the mechanisms that overwhelmed typical El Niño-related conditions and resulted in positive rainfall anomalies (above-average rainfall) in NNEB. We focus on the austral autumn when El Niño is most prone to rainfall anomalies in the region. The analysis of several datasets, including weather station data, satellite data, reanalysis data, and modelled data derived from a dry linear baroclinic model, allowed us to identify that the austral autumn 2019 above-average rainfall in NNEB was likely associated with four combined factors; these are (1) the weak intensity of the 2019 El Niño; (2) the negative phase of the Atlantic Meridional Mode; (3) local and remote diabatic heating anomalies, especially over the western South Pacific and tropical South Atlantic, which resulted in anticyclonic and cyclonic circulations in the upper and lower troposphere, respectively, over the tropical South Atlantic; and (4) sub-seasonal atmospheric convection anomalies over the western South Pacific, which reinforced the low-frequency convection signal over that region. This latter factor suggests the influence of the Madden–Julian Oscillation on rainfall in NNEB during the first ten days of March 2019. We discuss these mechanisms in detail and provide evidence that, even during an El Niño event, above-average rainfall in NNEB in the austral autumn may occur, and its modulation is not limited to the influence of a single climate phenomenon. Our results may assist in the planning of several crucial activities, such as water resources management and agriculture.","PeriodicalId":100061,"journal":{"name":"Agricultural Meteorology","volume":"96 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89620570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-22DOI: 10.3390/meteorology2030018
R. Park, Song‐You Hong
In atmospheric models, the representation of cloudiness is a direct linkage between the moisture amount and associated radiative forcing. This paper begins by providing a review of the parameterization of cloudiness that has been used for numerical weather predictions and climate studies. The inherent uncertainties in representing a partial fraction of clouds for radiation feedback and in evaluating it against the corresponding observations are focused. It is also stated that the major hydrometeor categories of water substances such as cloud ice and water that are responsible for cloud cover are readily available in modern weather and climate models. Inconsistencies in cloud cover and hydrometeors, even in the case of the prognostic method, are discussed. The compensating effect of cloudiness for radiative feedback is found to imply that the condensed water amount itself is more influential on the radiative forcing, rather than the accuracy of the cloudiness. Based on the above perspectives, an alternative diagnostic parameterization method is proposed, utilizing a monotonic relation between the cloud water amounts and cloudiness that are obtained from aircraft and satellite observations. The basic premise of this approach lies in the accuracy of the water substance in the models, indicating that future efforts need to be given to improvements in physical processes concerning hydrometeor properties for the accurate representation of cloud radiative feedback.
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