Irrigation is becoming increasingly common in agriculture and is essential to meet the growing demand for food. Studies of the impact of irrigated areas on local meteorology reveal a strong influence on near‐surface conditions, although the extent of this influence varies considerably between locations. In addition, though theoretical evidence suggests that irrigation can create breeze‐like atmospheric boundary‐layer circulations, observational evidence is still lacking. This study investigates the effects of irrigation on the surface and atmospheric boundary layer in the Ebro basin, an intensively irrigated area with a semi‐arid climate in northeastern Spain. Observational data from the international field campaign Land Surface Interactions with the Atmosphere over the Iberian Semi‐arid Environment are analysed together with coupled surface–atmosphere model output to better understand and quantify the impact of irrigation on the lower atmosphere. A simple parametrization of irrigation is shown to improve the accuracy of the model. Results demonstrate that irrigation increases the average latent heat flux by over 200 Wm, reduces air temperature by 4.7°C, and increases specific humidity by 50% at 2 m during the day over the irrigated region of the domain. Moreover, irrigation limits convection and strongly stabilizes the atmospheric boundary layer. Notably, the study provides evidence for an irrigation‐induced breeze from the irrigated area to the semi‐arid area. These findings highlight the importance of considering irrigation in numerical models for weather forecasting, climate modelling and sustainable agricultural planning.
{"title":"Irrigation strongly influences near‐surface conditions and induces breeze circulation: Observational and model‐based evidence","authors":"Tanguy Lunel, Aaron A. Boone, Patrick Le Moigne","doi":"10.1002/qj.4736","DOIUrl":"https://doi.org/10.1002/qj.4736","url":null,"abstract":"Irrigation is becoming increasingly common in agriculture and is essential to meet the growing demand for food. Studies of the impact of irrigated areas on local meteorology reveal a strong influence on near‐surface conditions, although the extent of this influence varies considerably between locations. In addition, though theoretical evidence suggests that irrigation can create breeze‐like atmospheric boundary‐layer circulations, observational evidence is still lacking. This study investigates the effects of irrigation on the surface and atmospheric boundary layer in the Ebro basin, an intensively irrigated area with a semi‐arid climate in northeastern Spain. Observational data from the international field campaign Land Surface Interactions with the Atmosphere over the Iberian Semi‐arid Environment are analysed together with coupled surface–atmosphere model output to better understand and quantify the impact of irrigation on the lower atmosphere. A simple parametrization of irrigation is shown to improve the accuracy of the model. Results demonstrate that irrigation increases the average latent heat flux by over 200 Wm, reduces air temperature by 4.7°C, and increases specific humidity by 50% at 2 m during the day over the irrigated region of the domain. Moreover, irrigation limits convection and strongly stabilizes the atmospheric boundary layer. Notably, the study provides evidence for an irrigation‐induced breeze from the irrigated area to the semi‐arid area. These findings highlight the importance of considering irrigation in numerical models for weather forecasting, climate modelling and sustainable agricultural planning.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":"23 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140840085","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}
We propose a forecasting tool for precipitation based on analogues of circulation defined from 5‐day hindcasts and a stochastic weather generator that we call “HC–SWG.” In this study, we aim to improve the forecast of European precipitation for subseasonal lead times (from 2 to 4 weeks) using the HC–SWG. We designed the HC–SWG to generate an ensemble precipitation forecast from the European Centre of Medium‐range Weather Forecasts (ECMWF) and Centre National de la Recherche Météorologique (CNRM) subseasonal‐to‐seasonal ensemble reforecasts. We define analogues from 5‐day ensemble reforecast of Z500 from the ECMWF (11 members) and CNRM (10 members) models. Then, we generate a 100‐member ensemble for precipitation over Europe. We evaluate the skill of the ensemble forecast using probabilistic skill scores such as the continuous ranked probability skill score (CRPSS) and receiver operating characteristic curve. We obtain reasonable forecast skill scores within 35 days for different locations in Europe. The CRPSS shows positive improvement with respect to climatology and persistence at the station level. The HC–SWG shows a capacity to distinguish between events and non‐events of precipitation within 15 days at the different stations. We compare the HC–SWG forecast with other precipitation forecasts to further confirm the benefits of our method. We found that the HC–SWG shows improvement against the ECMWF precipitation forecast until 25 days.
{"title":"Improving subseasonal forecast of precipitation in Europe by combining a stochastic weather generator with dynamical models","authors":"Meriem Krouma, Damien Specq, Linus Magnusson, Constantin Ardilouze, Lauriane Batté, Pascal Yiou","doi":"10.1002/qj.4733","DOIUrl":"https://doi.org/10.1002/qj.4733","url":null,"abstract":"We propose a forecasting tool for precipitation based on analogues of circulation defined from 5‐day hindcasts and a stochastic weather generator that we call “HC–SWG.” In this study, we aim to improve the forecast of European precipitation for subseasonal lead times (from 2 to 4 weeks) using the HC–SWG. We designed the HC–SWG to generate an ensemble precipitation forecast from the European Centre of Medium‐range Weather Forecasts (ECMWF) and Centre National de la Recherche Météorologique (CNRM) subseasonal‐to‐seasonal ensemble reforecasts. We define analogues from 5‐day ensemble reforecast of Z500 from the ECMWF (11 members) and CNRM (10 members) models. Then, we generate a 100‐member ensemble for precipitation over Europe. We evaluate the skill of the ensemble forecast using probabilistic skill scores such as the continuous ranked probability skill score (CRPSS) and receiver operating characteristic curve. We obtain reasonable forecast skill scores within 35 days for different locations in Europe. The CRPSS shows positive improvement with respect to climatology and persistence at the station level. The HC–SWG shows a capacity to distinguish between events and non‐events of precipitation within 15 days at the different stations. We compare the HC–SWG forecast with other precipitation forecasts to further confirm the benefits of our method. We found that the HC–SWG shows improvement against the ECMWF precipitation forecast until 25 days.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":"12 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140840083","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}
While there is huge demand for regional forecasts, information needed for selection of the most appropriate temporal and spatial scales is not available. The objective of this study is to demonstrate the basis of forecasting monthly mean rainfall over homogeneous regions by analyzing the forecasting skill and source of predictability. Reforecasts generated at the National Center for Medium Range Weather Forecasting (NCMRWF) for the period 1993–2015 using the coupled Unified Model are used in this study. Analysis of the forecasting skill over increasingly large lead times, averaging periods and spatial scales, is carried out to compare the skill at different time‐scales and to highlight the effect of spatial averaging over regions of coherent rainfall characteristics. Analysis of probabilistic forecasts is carried out to further demonstrate the usefulness of monthly mean forecasts. The influence of forcings on rainfall is studied both in model and in observations to understand the model's skill in representing interannual variability of monthly mean rainfall. Multiple regression analyses carried out for rainfall using climate indices as independent variables shows that the extent of forcings can largely explain the high variability of rainfall during the onset and withdrawal phase compared to the peak phase of monsoons. ENSO‐related subsidence is found to influence mainly the southern peninsular region, while tropical sea surface temperatures (SSTs) in the Indian Ocean are found to influence rainfall over northwest and central India by forcing circulation patterns typically associated with circumglobal teleconnections (CGTs) which are strongest during the month of June. Interestingly, the influence of CGTs on rainfall in the northeast is opposite to its influence on other homogeneous regions, which explains the contrast in influence of the North Indian Ocean SSTs on rainfall over the northeast and over All India. The model representation of influence of forcings and strength of teleconnections is better for specific region–month pairs, which is seen to influence the monthly variations in skill of forecasting rainfall over homogeneous regions.
{"title":"Prospects and status of forecasting monthly mean subregional rainfall during the Indian summer monsoon using the coupled Unified Model","authors":"Ankur Gupta, Ashis K. Mitra, Avinash C. Pandey","doi":"10.1002/qj.4741","DOIUrl":"https://doi.org/10.1002/qj.4741","url":null,"abstract":"While there is huge demand for regional forecasts, information needed for selection of the most appropriate temporal and spatial scales is not available. The objective of this study is to demonstrate the basis of forecasting monthly mean rainfall over homogeneous regions by analyzing the forecasting skill and source of predictability. Reforecasts generated at the National Center for Medium Range Weather Forecasting (NCMRWF) for the period 1993–2015 using the coupled Unified Model are used in this study. Analysis of the forecasting skill over increasingly large lead times, averaging periods and spatial scales, is carried out to compare the skill at different time‐scales and to highlight the effect of spatial averaging over regions of coherent rainfall characteristics. Analysis of probabilistic forecasts is carried out to further demonstrate the usefulness of monthly mean forecasts. The influence of forcings on rainfall is studied both in model and in observations to understand the model's skill in representing interannual variability of monthly mean rainfall. Multiple regression analyses carried out for rainfall using climate indices as independent variables shows that the extent of forcings can largely explain the high variability of rainfall during the onset and withdrawal phase compared to the peak phase of monsoons. ENSO‐related subsidence is found to influence mainly the southern peninsular region, while tropical sea surface temperatures (SSTs) in the Indian Ocean are found to influence rainfall over northwest and central India by forcing circulation patterns typically associated with circumglobal teleconnections (CGTs) which are strongest during the month of June. Interestingly, the influence of CGTs on rainfall in the northeast is opposite to its influence on other homogeneous regions, which explains the contrast in influence of the North Indian Ocean SSTs on rainfall over the northeast and over All India. The model representation of influence of forcings and strength of teleconnections is better for specific region–month pairs, which is seen to influence the monthly variations in skill of forecasting rainfall over homogeneous regions.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":"27 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140840027","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}
Ekaterina Vorobeva, Mari Dahl Eggen, Alise Danielle Midtfjord, Fred Espen Benth, Patrick Hupe, Quentin Brissaud, Yvan Orsolini, Sven Peter Näsholm
There are sparse opportunities for direct measurement of upper stratospheric winds, yet improving their representation in subseasonal‐to‐seasonal prediction models can have significant benefits. There is solid evidence from previous research that global atmospheric infrasound waves are sensitive to stratospheric dynamics. However, there is a lack of results providing a direct mapping between infrasound recordings and polar‐cap upper stratospheric winds. The global International Monitoring System (IMS), which monitors compliance with the Comprehensive Nuclear‐Test‐Ban Treaty, includes ground‐based stations that can be used to characterize the infrasound soundscape continuously. In this study, multi‐station IMS infrasound data were utilized along with a machine‐learning supported stochastic model, Delay‐SDE‐net, to demonstrate how a near‐real‐time estimate of the polar‐cap averaged zonal wind at 1‐hPa pressure level can be found from infrasound data. The infrasound was filtered to a temporal low‐frequency regime dominated by microbaroms, which are ambient‐noise infrasonic waves continuously radiated into the atmosphere from nonlinear interaction between counter‐propagating ocean surface waves. Delay‐SDE‐net was trained on 5 years (2014–2018) of infrasound data from three stations and the ERA5 reanalysis 1‐hPa polar‐cap averaged zonal wind. Using infrasound in 2019–2020 for validation, we demonstrate a prediction of the polar‐cap averaged zonal wind, with an error standard deviation of around 12 m·s compared with ERA5. These findings highlight the potential of using infrasound data for near‐real‐time measurements of upper stratospheric dynamics. A long‐term goal is to improve high‐top atmospheric model accuracy, which can have significant implications for weather and climate prediction.
{"title":"Estimating stratospheric polar vortex strength using ambient ocean‐generated infrasound and stochastics‐based machine learning","authors":"Ekaterina Vorobeva, Mari Dahl Eggen, Alise Danielle Midtfjord, Fred Espen Benth, Patrick Hupe, Quentin Brissaud, Yvan Orsolini, Sven Peter Näsholm","doi":"10.1002/qj.4731","DOIUrl":"https://doi.org/10.1002/qj.4731","url":null,"abstract":"There are sparse opportunities for direct measurement of upper stratospheric winds, yet improving their representation in subseasonal‐to‐seasonal prediction models can have significant benefits. There is solid evidence from previous research that global atmospheric infrasound waves are sensitive to stratospheric dynamics. However, there is a lack of results providing a direct mapping between infrasound recordings and polar‐cap upper stratospheric winds. The global International Monitoring System (IMS), which monitors compliance with the Comprehensive Nuclear‐Test‐Ban Treaty, includes ground‐based stations that can be used to characterize the infrasound soundscape continuously. In this study, multi‐station IMS infrasound data were utilized along with a machine‐learning supported stochastic model, Delay‐SDE‐net, to demonstrate how a near‐real‐time estimate of the polar‐cap averaged zonal wind at 1‐hPa pressure level can be found from infrasound data. The infrasound was filtered to a temporal low‐frequency regime dominated by microbaroms, which are ambient‐noise infrasonic waves continuously radiated into the atmosphere from nonlinear interaction between counter‐propagating ocean surface waves. Delay‐SDE‐net was trained on 5 years (2014–2018) of infrasound data from three stations and the ERA5 reanalysis 1‐hPa polar‐cap averaged zonal wind. Using infrasound in 2019–2020 for validation, we demonstrate a prediction of the polar‐cap averaged zonal wind, with an error standard deviation of around 12 m·s compared with ERA5. These findings highlight the potential of using infrasound data for near‐real‐time measurements of upper stratospheric dynamics. A long‐term goal is to improve high‐top atmospheric model accuracy, which can have significant implications for weather and climate prediction.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":"19 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2024-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140842390","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}
J. Camp, P. Gregory, A. G. Marshall, M. C. Wheeler
The skill of subseasonal (multiweek) forecasts of tropical‐cyclone (TC) occurrence over the Northern Hemisphere is examined in the Australian Bureau of Meteorology's (BoM) multiweek to seasonal prediction system, ACCESS‐S2. ACCESS‐S2 shows a good representation of the spatial distribution of TCs in the Northern Hemisphere; however, TC track frequency is generally underpredicted in the western North Pacific to the east of the Philippines and in the eastern North Pacific. The reduced activity relative to observations could be due to a significant positive bias in 850–200‐hPa wind shear in both of these regions, as well as a significant negative sea‐surface temperature (SST) bias in the eastern North Pacific. Despite biases in climatological TC frequency, the observed change in TC track frequency across the Northern Hemisphere with the phase of the Madden–Julian Oscillation (MJO) is well captured by ACCESS‐S2. Changes in the large‐scale environment (e.g., precipitation, 600‐hPa relative humidity, 850‐hPa absolute vorticity and 850–200‐hPa wind shear) are also well represented, with the location and size of the anomalies comparable to ERA‐Interim, apart from SST which shows a different response during some phases. ACCESS‐S2 shows skill relative to climatology for multiweek predictions of TC occurrence out to week 5 in the western North Pacific, eastern North Pacific and North Atlantic; and out to week 2 for the North Indian Ocean. Assessment of real‐time forecasts for Typhoon Rai (December 2021) showed that ACCESS‐S2 provided good guidance of the development and potential landfall of a TC in the Philippines at four weeks lead time.
{"title":"Skilful multiweek predictions of tropical‐cyclone frequency in the Northern Hemisphere using ACCESS‐S2","authors":"J. Camp, P. Gregory, A. G. Marshall, M. C. Wheeler","doi":"10.1002/qj.4738","DOIUrl":"https://doi.org/10.1002/qj.4738","url":null,"abstract":"The skill of subseasonal (multiweek) forecasts of tropical‐cyclone (TC) occurrence over the Northern Hemisphere is examined in the Australian Bureau of Meteorology's (BoM) multiweek to seasonal prediction system, ACCESS‐S2. ACCESS‐S2 shows a good representation of the spatial distribution of TCs in the Northern Hemisphere; however, TC track frequency is generally underpredicted in the western North Pacific to the east of the Philippines and in the eastern North Pacific. The reduced activity relative to observations could be due to a significant positive bias in 850–200‐hPa wind shear in both of these regions, as well as a significant negative sea‐surface temperature (SST) bias in the eastern North Pacific. Despite biases in climatological TC frequency, the observed change in TC track frequency across the Northern Hemisphere with the phase of the Madden–Julian Oscillation (MJO) is well captured by ACCESS‐S2. Changes in the large‐scale environment (e.g., precipitation, 600‐hPa relative humidity, 850‐hPa absolute vorticity and 850–200‐hPa wind shear) are also well represented, with the location and size of the anomalies comparable to ERA‐Interim, apart from SST which shows a different response during some phases. ACCESS‐S2 shows skill relative to climatology for multiweek predictions of TC occurrence out to week 5 in the western North Pacific, eastern North Pacific and North Atlantic; and out to week 2 for the North Indian Ocean. Assessment of real‐time forecasts for Typhoon <jats:italic>Rai</jats:italic> (December 2021) showed that ACCESS‐S2 provided good guidance of the development and potential landfall of a TC in the Philippines at four weeks lead time.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":"23 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2024-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140840172","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}
Graham P. Weedon, Simon R. Osborne, Martin J. Best
Given difficulties with modelling radiation fog and the similarity of meteorological conditions linked to dewfall and frost we investigated the formation of dew, frost and fog. For a site in the UK seven years of data were analysed representing high‐resolution atmospheric profiles and dew meter measurements for radiation nights with stable conditions. Classical dewfall occurs by condensation when the surface is below the dew point and cooler than the air above. However, the profiles show that, in the absence of fog, typically dew and frost form with the surface warmer than the immediately overlying air due to lifted temperature minima (LTMs) at about 0.15 m. Observations of aerosol number density and average hydrated radii show that aerosol optical extinction (and hence their radiative effect) is weakly but significantly correlated with the intensity of LTMs. Low wind speed on stable nights allows settling of aerosols which radiatively cool the air near the ground more quickly than the surface cools – thus creating LTMs. In the presence of LTMs typically dew and frost form not by condensation, but by occult deposition of water droplets onto the canopy and ground. Among radiation fog observations, 91% are associated with light near‐surface winds and LTMs. When the rate of removal of suspended water droplets by occult deposition generating dew or frost is too slow, then build‐up of droplets in the air just above the surface leads to the formation of radiation fog. Future modelling should allow for the accumulation of near‐surface aerosols and their radiative effects during stable nights to represent the formation of LTMs. Modelling of typical dew and frost will require representation of occult deposition. Assessing rates of occult deposition compared to rates of generation of suspended water droplets is needed to forecast the onset of radiation fog formed near the ground.
{"title":"Dew, frost, fog and lifted temperature minima: Observations in southern England and implications for modelling","authors":"Graham P. Weedon, Simon R. Osborne, Martin J. Best","doi":"10.1002/qj.4702","DOIUrl":"https://doi.org/10.1002/qj.4702","url":null,"abstract":"Given difficulties with modelling radiation fog and the similarity of meteorological conditions linked to dewfall and frost we investigated the formation of dew, frost and fog. For a site in the UK seven years of data were analysed representing high‐resolution atmospheric profiles and dew meter measurements for radiation nights with stable conditions. Classical dewfall occurs by condensation when the surface is below the dew point and cooler than the air above. However, the profiles show that, in the absence of fog, typically dew and frost form with the surface warmer than the immediately overlying air due to lifted temperature minima (LTMs) at about 0.15 m. Observations of aerosol number density and average hydrated radii show that aerosol optical extinction (and hence their radiative effect) is weakly but significantly correlated with the intensity of LTMs. Low wind speed on stable nights allows settling of aerosols which radiatively cool the air near the ground more quickly than the surface cools – thus creating LTMs. In the presence of LTMs typically dew and frost form not by condensation, but by occult deposition of water droplets onto the canopy and ground. Among radiation fog observations, 91% are associated with light near‐surface winds and LTMs. When the rate of removal of suspended water droplets by occult deposition generating dew or frost is too slow, then build‐up of droplets in the air just above the surface leads to the formation of radiation fog. Future modelling should allow for the accumulation of near‐surface aerosols and their radiative effects during stable nights to represent the formation of LTMs. Modelling of typical dew and frost will require representation of occult deposition. Assessing rates of occult deposition compared to rates of generation of suspended water droplets is needed to forecast the onset of radiation fog formed near the ground.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":"66 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2024-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140808852","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}
Jack M. Mustafa, Adrian J. Matthews, Rob A. Hall, Karen J. Heywood, Marina V. C. Azaneu
This study investigates the temporal and spatial complexities of the mean diurnal cycle (DC) of precipitation over the Maritime Continent during the wet season using the Integrated Multi‐satellite Retrievals for GPM (IMERG) data product and highlights systematic inaccuracies of amplitude and phase representation using the first diurnal harmonic (FDH). The first‐order nature of the DC of precipitation is already well documented, typically featuring heavy precipitation over near‐coastal land areas in the late afternoon and evening followed by maximum precipitation overnight over the surrounding seas, with offshore propagation evident in places. The DC is often described concisely in terms of an amplitude and phase based on the FDH parameters, however the omission of higher‐order components of variability results in the FDH parameters being poor indicators of the magnitude and peak time of diurnal variability in many locations. This study improves the accuracy of the amplitude and phase parameters by characterising the DC using two novel waveforms—a skew‐permitting waveform and a spike‐permitting waveform—which are constructed to characterise single‐peak cycles with rapid transitions more accurately. Key characterisation improvements include correction of a phase lag (averaging approximately 1 h) over near‐coastal land areas and capture of the short‐lasting but extreme peak in precipitation rate over Java which increases the amplitude by the order of 20%. The new skew parameter shows that locations close to coastlines experience rapid intensification and gradual weakening of diurnal precipitation, while there is a tendency toward gradual intensification and rapid weakening far inland and offshore. The new spike parameter shows that near‐coastal land experiences a brief and precisely timed peak in precipitation, whereas diurnal activity over inland locations is longer‐lasting and less precisely timed, and waters surrounding Java experience a precisely timed suppression of precipitation. Other potential applications of the novel waveforms used in this study are discussed.
{"title":"Characterisation of the observed diurnal cycle of precipitation over the Maritime Continent","authors":"Jack M. Mustafa, Adrian J. Matthews, Rob A. Hall, Karen J. Heywood, Marina V. C. Azaneu","doi":"10.1002/qj.4725","DOIUrl":"https://doi.org/10.1002/qj.4725","url":null,"abstract":"This study investigates the temporal and spatial complexities of the mean diurnal cycle (DC) of precipitation over the Maritime Continent during the wet season using the Integrated Multi‐satellite Retrievals for <jats:italic>GPM</jats:italic> (IMERG) data product and highlights systematic inaccuracies of amplitude and phase representation using the first diurnal harmonic (FDH). The first‐order nature of the DC of precipitation is already well documented, typically featuring heavy precipitation over near‐coastal land areas in the late afternoon and evening followed by maximum precipitation overnight over the surrounding seas, with offshore propagation evident in places. The DC is often described concisely in terms of an amplitude and phase based on the FDH parameters, however the omission of higher‐order components of variability results in the FDH parameters being poor indicators of the magnitude and peak time of diurnal variability in many locations. This study improves the accuracy of the amplitude and phase parameters by characterising the DC using two novel waveforms—a skew‐permitting waveform and a spike‐permitting waveform—which are constructed to characterise single‐peak cycles with rapid transitions more accurately. Key characterisation improvements include correction of a phase lag (averaging approximately 1 h) over near‐coastal land areas and capture of the short‐lasting but extreme peak in precipitation rate over Java which increases the amplitude by the order of 20%. The new skew parameter shows that locations close to coastlines experience rapid intensification and gradual weakening of diurnal precipitation, while there is a tendency toward gradual intensification and rapid weakening far inland and offshore. The new spike parameter shows that near‐coastal land experiences a brief and precisely timed peak in precipitation, whereas diurnal activity over inland locations is longer‐lasting and less precisely timed, and waters surrounding Java experience a precisely timed suppression of precipitation. Other potential applications of the novel waveforms used in this study are discussed.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":"11 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2024-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140798931","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}
Data assimilation of atmospheric observations traditionally relies on variational and Kalman filter methods. Here, an alternative neural network data assimilation (NNDA) with variational autoencoder (VAE) is proposed. The three‐dimensional variational (3D‐Var) data assimilation cost function is utilised to determine the analysis that optimally fuses simulated observations and the encoded short‐range persistence forecast (background), accounting for their errors. The minimisation is performed in the reduced‐order latent space discovered by the VAE. The variational problem is autodifferentiable, simplifying the computation of the cost‐function gradient necessary for efficient minimisation. We demonstrate that the background‐error covariance (B) matrix measured and represented in the latent space is quasidiagonal. The background‐error covariances in the grid‐point space are flow‐dependent, evolving seasonally and depending on the current state of the atmosphere. Data assimilation experiments with a single temperature observation in the lower troposphere indicate that the B matrix describes both tropical and extratropical background‐error covariances simultaneously.
{"title":"3D‐Var data assimilation using a variational autoencoder","authors":"Boštjan Melinc, Žiga Zaplotnik","doi":"10.1002/qj.4708","DOIUrl":"https://doi.org/10.1002/qj.4708","url":null,"abstract":"Data assimilation of atmospheric observations traditionally relies on variational and Kalman filter methods. Here, an alternative neural network data assimilation (NNDA) with variational autoencoder (VAE) is proposed. The three‐dimensional variational (3D‐Var) data assimilation cost function is utilised to determine the analysis that optimally fuses simulated observations and the encoded short‐range persistence forecast (background), accounting for their errors. The minimisation is performed in the reduced‐order latent space discovered by the VAE. The variational problem is autodifferentiable, simplifying the computation of the cost‐function gradient necessary for efficient minimisation. We demonstrate that the background‐error covariance (B) matrix measured and represented in the latent space is quasidiagonal. The background‐error covariances in the grid‐point space are flow‐dependent, evolving seasonally and depending on the current state of the atmosphere. Data assimilation experiments with a single temperature observation in the lower troposphere indicate that the B matrix describes both tropical and extratropical background‐error covariances simultaneously.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":"89 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140798912","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}
Andrew K. Mirza, Helen F. Dacre, Chun Hay Brian Lo
Most Lagrangian dispersion models represent free tropospheric turbulence as a homogeneous steady‐state process. However, intermittent turbulent mixing in the free troposphere may be a significant source of mixing. We test a new parametrization scheme that represents spatial‐ and temporal‐varying turbulence in the free troposphere in the Met Office's Numerical Atmospheric‐dispersion Modelling Environment. We use semi‐idealized emissions of radon‐222 (Rn) from rocks and soil in the United Kingdom to evaluate the impact of using a variable free tropospheric turbulence parameterization on the dispersion of Rn. We performed two experiments, the first using the existing steady‐state scheme and the second using the newly implemented spatio‐temporal‐varying scheme, for two case periods July 2018 and April 2021. We find that the turbulence in the varying scheme (represented by the vertical velocity variance) can range by two to three orders of magnitude (10 to 10 m s) when compared with the steady‐state scheme (10 m s). In particular, low‐altitude turbulence is enhanced when synoptic conditions are conducive to forming low‐level jets. This leads to a greater dispersion in the free troposphere, reducing the mean monthly Rn concentration above the boundary layer by 20–40% relative to the steady‐state scheme. We conclude that without a space–time‐varying free tropospheric turbulence scheme atmospheric dispersion may be significantly underestimated under synoptic conditions that are favourable for low‐level jet formation. This underestimation of dispersion may potentially result in inaccurate estimations of local emissions in top‐down greenhouse gas inventory studies.
{"title":"A case study analysis of the impact of a new free tropospheric turbulence scheme on the dispersion of an atmospheric tracer","authors":"Andrew K. Mirza, Helen F. Dacre, Chun Hay Brian Lo","doi":"10.1002/qj.4681","DOIUrl":"https://doi.org/10.1002/qj.4681","url":null,"abstract":"Most Lagrangian dispersion models represent free tropospheric turbulence as a homogeneous steady‐state process. However, intermittent turbulent mixing in the free troposphere may be a significant source of mixing. We test a new parametrization scheme that represents spatial‐ and temporal‐varying turbulence in the free troposphere in the Met Office's Numerical Atmospheric‐dispersion Modelling Environment. We use semi‐idealized emissions of radon‐222 (Rn) from rocks and soil in the United Kingdom to evaluate the impact of using a variable free tropospheric turbulence parameterization on the dispersion of Rn. We performed two experiments, the first using the existing steady‐state scheme and the second using the newly implemented spatio‐temporal‐varying scheme, for two case periods July 2018 and April 2021. We find that the turbulence in the varying scheme (represented by the vertical velocity variance) can range by two to three orders of magnitude (10 to 10 m s) when compared with the steady‐state scheme (10 m s). In particular, low‐altitude turbulence is enhanced when synoptic conditions are conducive to forming low‐level jets. This leads to a greater dispersion in the free troposphere, reducing the mean monthly Rn concentration above the boundary layer by 20–40% relative to the steady‐state scheme. We conclude that without a space–time‐varying free tropospheric turbulence scheme atmospheric dispersion may be significantly underestimated under synoptic conditions that are favourable for low‐level jet formation. This underestimation of dispersion may potentially result in inaccurate estimations of local emissions in top‐down greenhouse gas inventory studies.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":"19 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140615404","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}
Jakob Boyd Pernov, Jules Gros‐Daillon, Julia Schmale
In this study, data from 17 ground‐based, continental Arctic observatories are used to evaluate the performance of the European Centre for Medium‐Range Weather Forecasts Reanalysis version 5 (ERA5) reanalysis model. Three aspects are evaluated: (i) the overall reproducibility of variables at all stations for all seasons at one‐hour time resolution; (ii) the seasonal performance; and (iii) performance between different temporal resolutions (one hour to one month). Performance is evaluated based on the slope, R2 value, and root‐mean‐squared error (RMSE). We focus on surface meteorological variables including 2‐m air temperature (temperature), relative humidity (RH), surface pressure, wind speed, zonal and meridional wind speed components, and short‐wave downward (SWD) radiation flux. The overall comparison revealed the best results for surface pressure (0.98 ± 0.02, R2mean ± standard deviation [σR2]), followed by temperature (0.94 ± 0.02), and SWD radiation flux (0.87 ± 0.03) while wind speed (0.49 ± 0.12), RH (0.42 ± 0.20), zonal (0.163 ± 0.15) and meridional wind speed (0.129 ± 0.17) displayed poor results. We also found that certain variables (surface pressure, wind speed, meridional, and zonal wind speed) showed no seasonal dependency while others (temperature, RH, and SWD radiation flux) performed better during certain seasons. Improved results were observed when decreasing the temporal resolution from one hour to one month for temperature, meridional and zonal wind speed, and SWD radiation flux. However, certain variables (RH and surface pressure) showed comparatively worse results for monthly resolution. Overall, ERA5 performs well in the Arctic, but caution needs to be taken with wind speed and RH, which has implications for the use of ERA5 in global climate models. Our results are useful to the scientific community as it assesses the confidence to be placed in each of the surface variables produced by ERA5.
{"title":"Comparison of selected surface level ERA5 variables against in‐situ observations in the continental Arctic","authors":"Jakob Boyd Pernov, Jules Gros‐Daillon, Julia Schmale","doi":"10.1002/qj.4700","DOIUrl":"https://doi.org/10.1002/qj.4700","url":null,"abstract":"In this study, data from 17 ground‐based, continental Arctic observatories are used to evaluate the performance of the European Centre for Medium‐Range Weather Forecasts Reanalysis version 5 (ERA5) reanalysis model. Three aspects are evaluated: (i) the overall reproducibility of variables at all stations for all seasons at one‐hour time resolution; (ii) the seasonal performance; and (iii) performance between different temporal resolutions (one hour to one month). Performance is evaluated based on the slope, <jats:italic>R</jats:italic><jats:sup>2</jats:sup> value, and root‐mean‐squared error (RMSE). We focus on surface meteorological variables including 2‐m air temperature (temperature), relative humidity (RH), surface pressure, wind speed, zonal and meridional wind speed components, and short‐wave downward (SWD) radiation flux. The overall comparison revealed the best results for surface pressure (0.98 ± 0.02, <jats:italic>R</jats:italic><jats:sup>2</jats:sup><jats:sub>mean</jats:sub> ± standard deviation [<jats:italic>σ</jats:italic><jats:sub><jats:italic>R</jats:italic>2</jats:sub>]), followed by temperature (0.94 ± 0.02), and SWD radiation flux (0.87 ± 0.03) while wind speed (0.49 ± 0.12), RH (0.42 ± 0.20), zonal (0.163 ± 0.15) and meridional wind speed (0.129 ± 0.17) displayed poor results. We also found that certain variables (surface pressure, wind speed, meridional, and zonal wind speed) showed no seasonal dependency while others (temperature, RH, and SWD radiation flux) performed better during certain seasons. Improved results were observed when decreasing the temporal resolution from one hour to one month for temperature, meridional and zonal wind speed, and SWD radiation flux. However, certain variables (RH and surface pressure) showed comparatively worse results for monthly resolution. Overall, ERA5 performs well in the Arctic, but caution needs to be taken with wind speed and RH, which has implications for the use of ERA5 in global climate models. Our results are useful to the scientific community as it assesses the confidence to be placed in each of the surface variables produced by ERA5.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":"7 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140615405","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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