Thomas Melvin, Ben Shipway, Nigel Wood, Tommaso Benacchio, Thomas Bendall, Ian Boutle, Alex Brown, Christine Johnson, James Kent, Stephen Pring, Chris Smith, Mohamed Zerroukat, Colin Cotter, John Thuburn
Our previously described reformulation of the Met Office's dynamical core for weather and climate prediction is extended to spherical domains using a cubed‐sphere mesh. We update the semi‐implicit mixed finite‐element formulation to be suitable for spherical domains. In particular, the finite‐volume transport scheme is extended to take account of non‐uniform, non‐orthogonal meshes and uses an advective‐then‐flux formulation so that increment from the transport scheme is linear in the divergence. The resulting model is then applied to a standard set of dry dynamical core tests and compared with the existing semi‐implicit semi‐Lagrangian dynamical core currently used in the Met Office's operational model.
{"title":"A mixed finite‐element, finite‐volume, semi‐implicit discretisation for atmospheric dynamics: Spherical geometry","authors":"Thomas Melvin, Ben Shipway, Nigel Wood, Tommaso Benacchio, Thomas Bendall, Ian Boutle, Alex Brown, Christine Johnson, James Kent, Stephen Pring, Chris Smith, Mohamed Zerroukat, Colin Cotter, John Thuburn","doi":"10.1002/qj.4814","DOIUrl":"https://doi.org/10.1002/qj.4814","url":null,"abstract":"Our previously described reformulation of the Met Office's dynamical core for weather and climate prediction is extended to spherical domains using a cubed‐sphere mesh. We update the semi‐implicit mixed finite‐element formulation to be suitable for spherical domains. In particular, the finite‐volume transport scheme is extended to take account of non‐uniform, non‐orthogonal meshes and uses an advective‐then‐flux formulation so that increment from the transport scheme is linear in the divergence. The resulting model is then applied to a standard set of dry dynamical core tests and compared with the existing semi‐implicit semi‐Lagrangian dynamical core currently used in the Met Office's operational model.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":"63 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141742326","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}
The horizontal grid spacing of numerical weather prediction models keeps decreasing towards the hectometric range. We perform limited‐area simulations with the Icosahedral Nonhydrostatic (ICON) model across horizontal grid spacings (1 km, 500 m, 250 m, 125 m) in the Inn Valley, Austria, and evaluate the model with observations from the Cross‐Valley Flow in the Inn Valley Investigated by Dual‐Doppler LIDAR Measurements (CROSSINN) measurement campaign. This allows us to investigate whether increasing the horizontal resolution automatically improves the representation of the flow structure, surface exchange, and common meteorological variables. Increasing the horizontal resolution results in an improved simulation of the thermally induced circulation. However, the model still faces challenges with scale interactions and the evening transition of the up‐valley flow. Differences between two turbulence schemes (1D turbulence kinetic energy (TKE) and 3D Smagorinsky) emerge due to their different surface transfer formulations, yielding a delayed evening transition in the 3D Smagorinsky scheme. Generally speaking, the correct simulation of the mountain boundary layer depends mostly on the representation of model topography and surface exchange, and the choice of turbulence parameterization is secondary.
{"title":"The impact of mesh size, turbulence parameterization, and land‐surface‐exchange scheme on simulations of the mountain boundary layer in the hectometric range","authors":"Brigitta Goger, Anurag Dipankar","doi":"10.1002/qj.4799","DOIUrl":"https://doi.org/10.1002/qj.4799","url":null,"abstract":"The horizontal grid spacing of numerical weather prediction models keeps decreasing towards the hectometric range. We perform limited‐area simulations with the Icosahedral Nonhydrostatic (ICON) model across horizontal grid spacings (1 km, 500 m, 250 m, 125 m) in the Inn Valley, Austria, and evaluate the model with observations from the Cross‐Valley Flow in the Inn Valley Investigated by Dual‐Doppler LIDAR Measurements (CROSSINN) measurement campaign. This allows us to investigate whether increasing the horizontal resolution automatically improves the representation of the flow structure, surface exchange, and common meteorological variables. Increasing the horizontal resolution results in an improved simulation of the thermally induced circulation. However, the model still faces challenges with scale interactions and the evening transition of the up‐valley flow. Differences between two turbulence schemes (1D turbulence kinetic energy (TKE) and 3D Smagorinsky) emerge due to their different surface transfer formulations, yielding a delayed evening transition in the 3D Smagorinsky scheme. Generally speaking, the correct simulation of the mountain boundary layer depends mostly on the representation of model topography and surface exchange, and the choice of turbulence parameterization is secondary.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":"24 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2024-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141720437","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}
To estimate changes in global mean surface temperature (GMST), one must infer past temperatures for regions of the planet that lacked observations. While current global instrumental temperature datasets (GITDs) estimate different rates of warming for different regions of the planet, this non‐uniform warming is often modelled as residuals relative to underlying trends of spatially uniform warming. To better account for spatial non‐uniform trends in warming, a new GITD was created that used maximum likelihood estimation (MLE) to combine the land surface air temperature (LSAT) anomalies of non‐infilled HadCRUT5 with the sea surface temperature (SST) anomalies of HadSST4. This GITD better accounts for non‐uniform trends in warming in two ways. Firstly, the underlying warming trends in the model are allowed to vary spatially and by the time of year. Secondly, climatological differences between open‐sea and sea ice regions are used to better account for changes in sea ice concentrations (SICs). These improvements increase the estimate of GMST change from the late 19th century (1850–1900) to 2023 by 0.006°C and 0.079°C, respectively. Although, for the latter improvement, tests suggest that there may be an overcorrection by a factor of two and estimates of SICs for the late 19th century are a significant source of unquantified uncertainty. In addition, this new GITD has other improvements compared to the HadCRUT5 Analysis dataset, including correcting for a small underestimation of LSAT warming between 1961 and 1990, taking advantage of temporal correlations of observations, taking advantage of correlations between land and open‐sea observations, and better treatment of the El Niño Southern Oscillation (ENSO). Overall, the median estimate of GMST change from the late 19th century to 2023 is 1.548°C, with a 95% confidence interval of [1.449°C, 1.635°C].
{"title":"Improving global temperature datasets to better account for non‐uniform warming","authors":"Bruce T. T. Calvert","doi":"10.1002/qj.4791","DOIUrl":"https://doi.org/10.1002/qj.4791","url":null,"abstract":"To estimate changes in global mean surface temperature (GMST), one must infer past temperatures for regions of the planet that lacked observations. While current global instrumental temperature datasets (GITDs) estimate different rates of warming for different regions of the planet, this non‐uniform warming is often modelled as residuals relative to underlying trends of spatially uniform warming. To better account for spatial non‐uniform trends in warming, a new GITD was created that used maximum likelihood estimation (MLE) to combine the land surface air temperature (LSAT) anomalies of non‐infilled HadCRUT5 with the sea surface temperature (SST) anomalies of HadSST4. This GITD better accounts for non‐uniform trends in warming in two ways. Firstly, the underlying warming trends in the model are allowed to vary spatially and by the time of year. Secondly, climatological differences between open‐sea and sea ice regions are used to better account for changes in sea ice concentrations (SICs). These improvements increase the estimate of GMST change from the late 19th century (1850–1900) to 2023 by 0.006°C and 0.079°C, respectively. Although, for the latter improvement, tests suggest that there may be an overcorrection by a factor of two and estimates of SICs for the late 19th century are a significant source of unquantified uncertainty. In addition, this new GITD has other improvements compared to the HadCRUT5 Analysis dataset, including correcting for a small underestimation of LSAT warming between 1961 and 1990, taking advantage of temporal correlations of observations, taking advantage of correlations between land and open‐sea observations, and better treatment of the El Niño Southern Oscillation (ENSO). Overall, the median estimate of GMST change from the late 19th century to 2023 is 1.548°C, with a 95% confidence interval of [1.449°C, 1.635°C].","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":"1 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141613311","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}
Reanalysis and observational data are used to identify the precursors of summertime heat waves over the Eastern Mediterranean. After compiling a list of heat waves using objective criteria, we identify robust precursors present 7–10 days before the onset of the heat wave, longer than the typical horizon for trustworthy weather forecasts. If these precursors are present, there is a significant warming over the Eastern Mediterranean over the following 10 days that persists for weeks after. These precursors include a weakened Indian monsoon, a strengthened Sahelian monsoon, warm Western/Central Mediterranean sea‐surface temperatures, and a midlatitude low‐pressure system from the west. Further, horizontal temperature advection is the proximate cause of the heat wave in the days before the extreme; in particular, a weakening of the Etesian winds that would otherwise advect relatively cool maritime air inland accounts for around half of the warming. There has been a clear tendency for more heat extremes in recent years. These results have implications for forecasting anomalous summer temperatures in the Eastern Mediterranean, and the framework developed here can also be applied in other regions.
{"title":"Precursors of summer heat waves in the Eastern Mediterranean","authors":"Chaim I. Garfinkel, Dorita Rostkier‐Edelstein, Efrat Morin, Assaf Hochman, Chen Schwartz, Ronit Nirel","doi":"10.1002/qj.4795","DOIUrl":"https://doi.org/10.1002/qj.4795","url":null,"abstract":"Reanalysis and observational data are used to identify the precursors of summertime heat waves over the Eastern Mediterranean. After compiling a list of heat waves using objective criteria, we identify robust precursors present 7–10 days before the onset of the heat wave, longer than the typical horizon for trustworthy weather forecasts. If these precursors are present, there is a significant warming over the Eastern Mediterranean over the following 10 days that persists for weeks after. These precursors include a weakened Indian monsoon, a strengthened Sahelian monsoon, warm Western/Central Mediterranean sea‐surface temperatures, and a midlatitude low‐pressure system from the west. Further, horizontal temperature advection is the proximate cause of the heat wave in the days before the extreme; in particular, a weakening of the Etesian winds that would otherwise advect relatively cool maritime air inland accounts for around half of the warming. There has been a clear tendency for more heat extremes in recent years. These results have implications for forecasting anomalous summer temperatures in the Eastern Mediterranean, and the framework developed here can also be applied in other regions.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":"20 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141613252","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}
The main goal of this article is to test the long‐term performance of the three‐dimensional non‐local turbulence (NLT) parameterization scheme at different grid sizes in the so‐called gray zone between classical mesoscale modeling ( several km) and large eddy simulations (LES: several 100 m). For this, NLT has been implemented in the numerical weather prediction Icosahedral Nonhydrostatic model (ICON) of Deutscher Wetterdienst (DWD). Results are compared with a one‐dimensional version of NLT (NLT) and with two operational turbulence schemes available in ICON. Comparisons with observations from radiosondes, the operational surface synoptic (SYNOP) station network, and RAdar‐OnLine‐ANeichung (RADOLAN) radar data of DWD indicate that all turbulence schemes investigated perform reasonably well. Nonetheless, a more detailed study of the model results reveals several interesting differences between the turbulence parameterizations to be discussed in detail. Median absolute errors (MAE) from point‐to‐point comparisons between numerical results and SYNOP observations tend to be smaller than those from comparisons with averaging simulated fields over an environment around each station location. This behavior indicates an information loss caused by the averaging process. For the 2‐m temperature () and the hourly precipitation sums (), MAEs decrease with decreasing grid sizes, thus suggesting an information gain for finer grids. The nighttime MAEs of and obtained with NLT and NLT are similar to or lower than those of the operational turbulence schemes of ICON. Moreover, during a shallow warm‐air intrusion, NLT and especially NLT yield a more realistic representation of the horizontal structures of and, during nighttime stable boundary‐layer situations, also . Radiosonde profiles of the potential temperature confirm a reasonable vertical mixing as obtained with NLT and NLT.
{"title":"Implementation and tests of the NLT3D scheme in the ICON model","authors":"V. Kuell, A. Bott","doi":"10.1002/qj.4789","DOIUrl":"https://doi.org/10.1002/qj.4789","url":null,"abstract":"The main goal of this article is to test the long‐term performance of the three‐dimensional non‐local turbulence (NLT) parameterization scheme at different grid sizes in the so‐called gray zone between classical mesoscale modeling ( several km) and large eddy simulations (LES: several 100 m). For this, NLT has been implemented in the numerical weather prediction Icosahedral Nonhydrostatic model (ICON) of Deutscher Wetterdienst (DWD). Results are compared with a one‐dimensional version of NLT (NLT) and with two operational turbulence schemes available in ICON. Comparisons with observations from radiosondes, the operational surface synoptic (SYNOP) station network, and RAdar‐OnLine‐ANeichung (RADOLAN) radar data of DWD indicate that all turbulence schemes investigated perform reasonably well. Nonetheless, a more detailed study of the model results reveals several interesting differences between the turbulence parameterizations to be discussed in detail. Median absolute errors (MAE) from point‐to‐point comparisons between numerical results and SYNOP observations tend to be smaller than those from comparisons with averaging simulated fields over an environment around each station location. This behavior indicates an information loss caused by the averaging process. For the 2‐m temperature () and the hourly precipitation sums (), MAEs decrease with decreasing grid sizes, thus suggesting an information gain for finer grids. The nighttime MAEs of and obtained with NLT and NLT are similar to or lower than those of the operational turbulence schemes of ICON. Moreover, during a shallow warm‐air intrusion, NLT and especially NLT yield a more realistic representation of the horizontal structures of and, during nighttime stable boundary‐layer situations, also . Radiosonde profiles of the potential temperature confirm a reasonable vertical mixing as obtained with NLT and NLT.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":"7 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141588133","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}
In this study, the medium‐range predictability of heatwave (HW) onsets in four midlatitude European regions is investigated statistically with the help of ensemble reforecasts for the period 2001–2018. The concept of Euro‐Atlantic weather regimes is adopted to characterise HWs (about 50 in each region) and to study whether forecast skill may depend on the large‐scale dynamical setup. HW onsets over the British Isles and Scandinavia are mainly associated with Scandinavian and European blocking regimes, whereas the “no regime” case is observed more frequently for Central Europe. Stratified by weather regime, the predictability of heatwave onsets is then studied by means of a multiple metric‐based analysis of European Centre for Medium‐Range Weather Forecasts (ECMWF) and Global Ensemble Forecast System Version 12 (GEFSv12) ensemble reforecasts. For two of the regions considered, Central Europe and the British Isles, a conclusive picture is obtained: medium‐range predictive skill is significantly higher for HW onsets associated with Scandinavian or European blocking compared with cases with no pronounced regime. This skill advantage mostly concerns the large‐scale flow and, to some extent, 850‐hPa temperatures, but is generally not reflected in the correct prediction of near‐surface temperatures. Finally, we investigate for two regions how exceptionally good or poor forecasts are related to the atmospheric state during or shortly after forecast initialisation. At 10 days lead time, poor large‐scale flow predictive skill for Central European HW onsets is linked to anomalously high baroclinicity further upstream and an intensified North Atlantic jet stream, whereas good forecasts on average feature an initial state close to climatology. Forecast skill for near‐surface temperatures is not affected by such dynamical precursors, but rather by pre‐existing soil‐moisture anomalies. For the British region, exceptionally good forecasts of both large‐scale flow and near‐surface temperatures are associated with an already established continental blocking. In contrast to Central Europe, pre‐existing soil‐moisture anomalies play less of a role there.
{"title":"Investigating the medium‐range predictability of European heatwave onsets in relation to weather regimes using ensemble reforecasts","authors":"Alexander Lemburg, Andreas H. Fink","doi":"10.1002/qj.4801","DOIUrl":"https://doi.org/10.1002/qj.4801","url":null,"abstract":"In this study, the medium‐range predictability of heatwave (HW) onsets in four midlatitude European regions is investigated statistically with the help of ensemble reforecasts for the period 2001–2018. The concept of Euro‐Atlantic weather regimes is adopted to characterise HWs (about 50 in each region) and to study whether forecast skill may depend on the large‐scale dynamical setup. HW onsets over the British Isles and Scandinavia are mainly associated with Scandinavian and European blocking regimes, whereas the “no regime” case is observed more frequently for Central Europe. Stratified by weather regime, the predictability of heatwave onsets is then studied by means of a multiple metric‐based analysis of European Centre for Medium‐Range Weather Forecasts (ECMWF) and Global Ensemble Forecast System Version 12 (GEFSv12) ensemble reforecasts. For two of the regions considered, Central Europe and the British Isles, a conclusive picture is obtained: medium‐range predictive skill is significantly higher for HW onsets associated with Scandinavian or European blocking compared with cases with no pronounced regime. This skill advantage mostly concerns the large‐scale flow and, to some extent, 850‐hPa temperatures, but is generally not reflected in the correct prediction of near‐surface temperatures. Finally, we investigate for two regions how exceptionally good or poor forecasts are related to the atmospheric state during or shortly after forecast initialisation. At 10 days lead time, poor large‐scale flow predictive skill for Central European HW onsets is linked to anomalously high baroclinicity further upstream and an intensified North Atlantic jet stream, whereas good forecasts on average feature an initial state close to climatology. Forecast skill for near‐surface temperatures is not affected by such dynamical precursors, but rather by pre‐existing soil‐moisture anomalies. For the British region, exceptionally good forecasts of both large‐scale flow and near‐surface temperatures are associated with an already established continental blocking. In contrast to Central Europe, pre‐existing soil‐moisture anomalies play less of a role there.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":"37 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141588135","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}
The detection and quantification of strong sea surface winds, reaching up to 25 m·s−1, whether associated with deep convection aloft or not, have been extensively discussed in previous studies. This method involves the combined observation of the same event from both low‐orbit altitude and geostationary (GEO) satellites. Strong surface winds observed by the Sentinel‐1 C‐band synthetic aperture radar (SAR) are robustly associated with deep convective clouds detected by GEO infrared sensors. The current paper aims to generalize the previous assessment of several convective wind events by collecting a larger dataset and comparing these data to in‐situ wind observations. To achieve this, we evaluated wind speeds retrieved from Sentinel‐1 SAR images against corresponding in‐situ wind measurements from all active buoys/stations in the Gulf of Mexico. Significant agreement between satellite‐based winds and in‐situ data was achieved, particularly for wind speeds exceeding 3 m·s−1, with even better agreement for wind speeds over 10 m·s−1. From this dataset, three specific convective cases were extracted to illustrate various stages of convective squall events: before, during, and after the occurrence of a squall peak. In each case, comparison with in‐situ measurements showed that SAR‐estimated wind speeds closely matched observed speeds, including the peak convective winds, which were estimated at 18.90 m·s−1 and measured at 20.69 m·s−1. Furthermore, combining these findings with GOES‐16 sequential images illustrates the temporal and spatial similarity between deep convection areas, estimated strong sea surface wind patterns, and measured wind speeds.
{"title":"Evaluating synthetic aperture radar surface winds for convective squalls in the Gulf of Mexico","authors":"Tran Vu La, Christophe Messager","doi":"10.1002/qj.4810","DOIUrl":"https://doi.org/10.1002/qj.4810","url":null,"abstract":"The detection and quantification of strong sea surface winds, reaching up to 25 m·s<jats:sup>−1</jats:sup>, whether associated with deep convection aloft or not, have been extensively discussed in previous studies. This method involves the combined observation of the same event from both low‐orbit altitude and geostationary (GEO) satellites. Strong surface winds observed by the Sentinel‐1 C‐band synthetic aperture radar (SAR) are robustly associated with deep convective clouds detected by GEO infrared sensors. The current paper aims to generalize the previous assessment of several convective wind events by collecting a larger dataset and comparing these data to in‐situ wind observations. To achieve this, we evaluated wind speeds retrieved from Sentinel‐1 SAR images against corresponding in‐situ wind measurements from all active buoys/stations in the Gulf of Mexico. Significant agreement between satellite‐based winds and in‐situ data was achieved, particularly for wind speeds exceeding 3 m·s<jats:sup>−1</jats:sup>, with even better agreement for wind speeds over 10 m·s<jats:sup>−1</jats:sup>. From this dataset, three specific convective cases were extracted to illustrate various stages of convective squall events: before, during, and after the occurrence of a squall peak. In each case, comparison with in‐situ measurements showed that SAR‐estimated wind speeds closely matched observed speeds, including the peak convective winds, which were estimated at 18.90 m·s<jats:sup>−1</jats:sup> and measured at 20.69 m·s<jats:sup>−1</jats:sup>. Furthermore, combining these findings with GOES‐16 sequential images illustrates the temporal and spatial similarity between deep convection areas, estimated strong sea surface wind patterns, and measured wind speeds.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":"18 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141569351","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}
Sergey Skachko, Mark Buehner, Alain Caya, Yves Franklin Ngueto, Dorina Surcel‐Colan
A new global daily sea‐surface temperature (SST) analysis system has been developed at Environment and Climate Change Canada (ECCC). All components of the new SST analysis system are implemented within the Modular and Integrated Data Assimilation System (MIDAS) software. MIDAS is already used for the data assimilation component of the main operational numerical weather prediction (NWP) systems at ECCC. The new SST analysis system, integrated together with the global sea‐ice analysis, will be part of the combined ocean surface analysis used for all operational prediction systems at ECCC. The data assimilation method used to compute the new SST analyses is two‐dimensional variational method with a diffusion operator for representing the horizontal background‐error correlations. A new algorithm for satellite data bias estimation has also been developed employing gridded bias estimates computed from a spatial averaging of the differences between collocated satellite and in‐situ data. New algorithms for quality control and thinning of satellite data have also been implemented, making each type of observational dataset more evenly distributed over the globe. The performance of the new SST system is examined relative to the current operational SST system by using independent data. The impact of using the new SST analysis within NWP and ocean prediction systems is also evaluated. When compared with the operational system currently in use, the experiments employing the new SST analysis system produce a nearly neutral impact on the NWP and ocean prediction systems. This validation of the new system is an important first step towards the ability to use MIDAS to perform ensemble‐based three‐dimensional ocean and coupled ocean‐ice–atmosphere data assimilation.
{"title":"A new global daily sea‐surface temperature analysis system at Environment and Climate Change Canada","authors":"Sergey Skachko, Mark Buehner, Alain Caya, Yves Franklin Ngueto, Dorina Surcel‐Colan","doi":"10.1002/qj.4796","DOIUrl":"https://doi.org/10.1002/qj.4796","url":null,"abstract":"A new global daily sea‐surface temperature (SST) analysis system has been developed at Environment and Climate Change Canada (ECCC). All components of the new SST analysis system are implemented within the Modular and Integrated Data Assimilation System (MIDAS) software. MIDAS is already used for the data assimilation component of the main operational numerical weather prediction (NWP) systems at ECCC. The new SST analysis system, integrated together with the global sea‐ice analysis, will be part of the combined ocean surface analysis used for all operational prediction systems at ECCC. The data assimilation method used to compute the new SST analyses is two‐dimensional variational method with a diffusion operator for representing the horizontal background‐error correlations. A new algorithm for satellite data bias estimation has also been developed employing gridded bias estimates computed from a spatial averaging of the differences between collocated satellite and in‐situ data. New algorithms for quality control and thinning of satellite data have also been implemented, making each type of observational dataset more evenly distributed over the globe. The performance of the new SST system is examined relative to the current operational SST system by using independent data. The impact of using the new SST analysis within NWP and ocean prediction systems is also evaluated. When compared with the operational system currently in use, the experiments employing the new SST analysis system produce a nearly neutral impact on the NWP and ocean prediction systems. This validation of the new system is an important first step towards the ability to use MIDAS to perform ensemble‐based three‐dimensional ocean and coupled ocean‐ice–atmosphere data assimilation.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":"35 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141569253","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}
When using sub‐km models to forecast convection, it is important to have a large enough domain to allow convection to fully spin‐up from the lateral boundaries. However, running large domains is computationally expensive and while it may be feasible for research purposes it is not yet feasible for routinely run models, such as the Met Office 300‐m London model. To try and mitigate the spin‐up issues in the London model, a variable‐resolution 300‐m London Model (the ‘LMV’) has been developed, which allows the boundaries of the London model to be further away from areas of interest (e.g., London Heathrow) at lower computational cost. Results from several cases of summertime convection show that the convective storms in the variable‐resolution model are more like those in a large fixed‐resolution 300‐m model than those in the much smaller London model. This implies variable resolution is a viable option for increasing the size of the London model domain without increasing the computational costs too much. Extended evaluation of the LMV was conducted during summer 2022, running as an ensemble nested inside the Met Office's operational UK ensemble (MOGREPS‐UK). Overall, the LMV looks promising for high‐impact convective events as it is better able to represent the organisation of convection into lines or larger storms whereas MOGREPS‐UK tends to simulate isolated, circular storms. This often leads to more reliable probabilities of heavy rainfall in the LMV ensemble compared to MOGREPS‐UK. However, there is an issue with the LMV producing too many small precipitating showers in situations where there should only be shallow clouds. This is thought to be a result of shallow clouds getting too deep in the model and precipitating erroneously.
{"title":"The performance of a variable‐resolution 300‐m ensemble for forecasting convection over London","authors":"Kirsty Hanley, Humphrey Lean","doi":"10.1002/qj.4794","DOIUrl":"https://doi.org/10.1002/qj.4794","url":null,"abstract":"When using sub‐km models to forecast convection, it is important to have a large enough domain to allow convection to fully spin‐up from the lateral boundaries. However, running large domains is computationally expensive and while it may be feasible for research purposes it is not yet feasible for routinely run models, such as the Met Office 300‐m London model. To try and mitigate the spin‐up issues in the London model, a variable‐resolution 300‐m London Model (the ‘LMV’) has been developed, which allows the boundaries of the London model to be further away from areas of interest (e.g., London Heathrow) at lower computational cost. Results from several cases of summertime convection show that the convective storms in the variable‐resolution model are more like those in a large fixed‐resolution 300‐m model than those in the much smaller London model. This implies variable resolution is a viable option for increasing the size of the London model domain without increasing the computational costs too much. Extended evaluation of the LMV was conducted during summer 2022, running as an ensemble nested inside the Met Office's operational UK ensemble (MOGREPS‐UK). Overall, the LMV looks promising for high‐impact convective events as it is better able to represent the organisation of convection into lines or larger storms whereas MOGREPS‐UK tends to simulate isolated, circular storms. This often leads to more reliable probabilities of heavy rainfall in the LMV ensemble compared to MOGREPS‐UK. However, there is an issue with the LMV producing too many small precipitating showers in situations where there should only be shallow clouds. This is thought to be a result of shallow clouds getting too deep in the model and precipitating erroneously.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":"8 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141569354","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}
F. Lott, R. Rani, C. McLandress, A. Podglajen, A. Bushell, M. Bramberger, H.‐K. Lee, J. Alexander, J. Anstey, H.‐Y. Chun, A. Hertzog, N. Butchart, Y.‐H. Kim, Y. Kawatani, B. Legras, E. Manzini, H. Naoe, S. Osprey, R. Plougonven, H. Pohlmann, J. H. Richter, J. Scinocca, J. García‐Serrano, F. Serva, T. Stockdale, S. Versick, S. Watanabe, K. Yoshida
Gravity‐wave (GW) parameterizations from 12 general circulation models (GCMs) participating in the Quasi‐Biennial Oscillation initiative (QBOi) are compared with Strateole 2 balloon observations made in the tropical lower stratosphere from November 2019–February 2020 (phase 1) and from October 2021–January 2022 (phase 2). The parameterizations employ the three standard techniques used in GCMs to represent subgrid‐scale non‐orographic GWs, namely the two globally spectral techniques developed by Warner and McIntyre (1999) and Hines (1997), as well as the “multiwaves” approaches following the work of Lindzen (1981). The input meteorological fields necessary to run the parameterizations offline are extracted from the ERA5 reanalysis and correspond to the meteorological conditions found underneath the balloons. In general, there is fair agreement between amplitudes derived from measurements for waves with periods less than h and parameterizations. The correlation between the daily observations and the corresponding results of the parameterization can be around 0.4, which is significant, since 1200 days of observations are used. Given that the parameterizations have only been tuned to produce a quasi‐biennial oscillation (QBO) in the models, the 0.4 correlation coefficient of the GW momentum fluxes is surprisingly good. These correlations nevertheless vary between schemes and depend little on their formulation (globally spectral versus multiwaves for instance). We therefore attribute these correlations to dynamical filtering, which all schemes take into account, whereas only a few relate the gravity waves to their sources. Statistically significant correlations are mostly found for eastward‐propagating waves, which may be due to the fact that during both Strateole 2 phases the QBO is easterly at the altitude of the balloon flights. We also found that the probability density functions (pdfs) of the momentum fluxes are represented better in spectral schemes with constant sources than in schemes (“spectral” or “multiwaves”) that relate GWs only to their convective sources.
{"title":"Comparison between non‐orographic gravity‐wave parameterizations used in QBOi models and Strateole 2 constant‐level balloons","authors":"F. Lott, R. Rani, C. McLandress, A. Podglajen, A. Bushell, M. Bramberger, H.‐K. Lee, J. Alexander, J. Anstey, H.‐Y. Chun, A. Hertzog, N. Butchart, Y.‐H. Kim, Y. Kawatani, B. Legras, E. Manzini, H. Naoe, S. Osprey, R. Plougonven, H. Pohlmann, J. H. Richter, J. Scinocca, J. García‐Serrano, F. Serva, T. Stockdale, S. Versick, S. Watanabe, K. Yoshida","doi":"10.1002/qj.4793","DOIUrl":"https://doi.org/10.1002/qj.4793","url":null,"abstract":"Gravity‐wave (GW) parameterizations from 12 general circulation models (GCMs) participating in the Quasi‐Biennial Oscillation initiative (QBOi) are compared with Strateole 2 balloon observations made in the tropical lower stratosphere from November 2019–February 2020 (phase 1) and from October 2021–January 2022 (phase 2). The parameterizations employ the three standard techniques used in GCMs to represent subgrid‐scale non‐orographic GWs, namely the two globally spectral techniques developed by Warner and McIntyre (1999) and Hines (1997), as well as the “multiwaves” approaches following the work of Lindzen (1981). The input meteorological fields necessary to run the parameterizations offline are extracted from the ERA5 reanalysis and correspond to the meteorological conditions found underneath the balloons. In general, there is fair agreement between amplitudes derived from measurements for waves with periods less than h and parameterizations. The correlation between the daily observations and the corresponding results of the parameterization can be around 0.4, which is significant, since 1200 days of observations are used. Given that the parameterizations have only been tuned to produce a quasi‐biennial oscillation (QBO) in the models, the 0.4 correlation coefficient of the GW momentum fluxes is surprisingly good. These correlations nevertheless vary between schemes and depend little on their formulation (globally spectral versus multiwaves for instance). We therefore attribute these correlations to dynamical filtering, which all schemes take into account, whereas only a few relate the gravity waves to their sources. Statistically significant correlations are mostly found for eastward‐propagating waves, which may be due to the fact that during both Strateole 2 phases the QBO is easterly at the altitude of the balloon flights. We also found that the probability density functions (pdfs) of the momentum fluxes are represented better in spectral schemes with constant sources than in schemes (“spectral” or “multiwaves”) that relate GWs only to their convective sources.","PeriodicalId":49646,"journal":{"name":"Quarterly Journal of the Royal Meteorological Society","volume":"87 1","pages":""},"PeriodicalIF":8.9,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141569254","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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