Abstract
This article provides a brief, technical narrative of the WoFS journey to a cloud-based high performance computing (HPC) system, including some of the technological challenges encountered and solutions found. Also discussed are a few new components that are in development for cloud-based WoFS (cb-WoFS), such as the cloud infrastructure project for managing resources, as well as a new web application that manages cb-WoFS runs.
An important initial step in our cloud journey is containerizing all of the compiled applications, such as WRF, GSI, EnKF and their dependencies like NetCDF and MPI. With these applications compiled within a Apptainer container, WoFS can run on any local or cloud-based HPC cluster that supports MPI. Furthermore, an additional software layer was developed that creates and manages cloud vendor resources. This layer, which is referred to as the WoFS Framework, contains the workflow required to run cb-WoFS, as well as management for other aspects of cb-WoFS (including but not limited to creation of HPC pools in the end-to-end workflow, runtime notifications and database management). This additional layer was developed to separate the WoFS business logic from vendor-specific API calls. The WoFS Framework exposes features through its service library, which is then referenced by the newly developed cb-WoFS web application and other cloud applications. This makes WoFS a complete end-to-end cloud-based application, where an administrator can launch a model run, manage resources and view output all within a single web app.
Abstract
This article provides a brief, technical narrative of the WoFS journey to a cloud-based high performance computing (HPC) system, including some of the technological challenges encountered and solutions found. Also discussed are a few new components that are in development for cloud-based WoFS (cb-WoFS), such as the cloud infrastructure project for managing resources, as well as a new web application that manages cb-WoFS runs.
An important initial step in our cloud journey is containerizing all of the compiled applications, such as WRF, GSI, EnKF and their dependencies like NetCDF and MPI. With these applications compiled within a Apptainer container, WoFS can run on any local or cloud-based HPC cluster that supports MPI. Furthermore, an additional software layer was developed that creates and manages cloud vendor resources. This layer, which is referred to as the WoFS Framework, contains the workflow required to run cb-WoFS, as well as management for other aspects of cb-WoFS (including but not limited to creation of HPC pools in the end-to-end workflow, runtime notifications and database management). This additional layer was developed to separate the WoFS business logic from vendor-specific API calls. The WoFS Framework exposes features through its service library, which is then referenced by the newly developed cb-WoFS web application and other cloud applications. This makes WoFS a complete end-to-end cloud-based application, where an administrator can launch a model run, manage resources and view output all within a single web app.
Abstract
Optical turbulence poses a significant challenge for communication, directed energy, and imaging systems, particularly in the atmospheric boundary layer. Effective modeling of optical turbulence is crucial for the development and deployment of these systems, yet the lack of standardized evaluation tools and benchmark data sets hinders the development and adoption of machine learning to address these challenges. We introduce the otbench Python package, a comprehensive framework for rigorous development and evaluation of optical turbulence strength prediction models. This package provides a consistent interface for testing models across diverse data sets and tasks, including a novel, long-term data set collected over two years at the United States Naval Academy. otbench incorporates a range of baseline models (statistical, data-driven, and deep learning), enabling researchers to assess the relative quality of their approaches and identify areas for improvement. Our analysis reveals the applicability of various models across different environments, highlighting the importance of long-term data sets for robust model evaluation. By promoting standardized benchmarking and facilitating model comparison, otbench empowers researchers to accelerate the adoption of machine learning techniques for optical turbulence modeling.
Abstract
Optical turbulence poses a significant challenge for communication, directed energy, and imaging systems, particularly in the atmospheric boundary layer. Effective modeling of optical turbulence is crucial for the development and deployment of these systems, yet the lack of standardized evaluation tools and benchmark data sets hinders the development and adoption of machine learning to address these challenges. We introduce the otbench Python package, a comprehensive framework for rigorous development and evaluation of optical turbulence strength prediction models. This package provides a consistent interface for testing models across diverse data sets and tasks, including a novel, long-term data set collected over two years at the United States Naval Academy. otbench incorporates a range of baseline models (statistical, data-driven, and deep learning), enabling researchers to assess the relative quality of their approaches and identify areas for improvement. Our analysis reveals the applicability of various models across different environments, highlighting the importance of long-term data sets for robust model evaluation. By promoting standardized benchmarking and facilitating model comparison, otbench empowers researchers to accelerate the adoption of machine learning techniques for optical turbulence modeling.
Abstract
This study explores the potential impacts of the Madden-Julian Oscillation (MJO) on flash drought occurrence over the Lancang-Mekong River Basin (LMRB). The flash drought events are identified across individual grid cells from gridded datasets, based on rapid decline rate in soil moisture and dry persistency of flash droughts. The onset of flash drought is typically accompanied by precipitation deficit and abnormally increase of surface air temperature (SAT). Both the onset and persistency risks of flash drought vary significantly depending on the MJO phase. Generally, the onset and persistency risks of flash droughts over the LMRB increase when the MJO convection is active over the Indian Ocean (phases 2–3), while decrease when the MJO is active over the Pacific Ocean (phases 6–7). The MJO primarily influences flash droughts over the lower reaches of the LMRB by modulating SAT and precipitation. During MJO phases 2–3, there exists significant increased SAT and preceding precipitation deficit over the lower reaches, leading to decline in soil moisture. During MJO phases 6–7, there are decreased SAT and preceding increased precipitation. Diagnosis results revealed that the impact of the MJO on SAT over the lower reaches is dominated by large-scale temperature advection associated with the MJO-induced vertical and meridional circulation anomalies, while its impact on precipitation is mainly modulated by the MJO-induced zonal wind gradients. This study emphasizes the importance of considering the effects of the MJO on precipitation and SAT for predicting flash droughts over the LMRB.
Abstract
This study explores the potential impacts of the Madden-Julian Oscillation (MJO) on flash drought occurrence over the Lancang-Mekong River Basin (LMRB). The flash drought events are identified across individual grid cells from gridded datasets, based on rapid decline rate in soil moisture and dry persistency of flash droughts. The onset of flash drought is typically accompanied by precipitation deficit and abnormally increase of surface air temperature (SAT). Both the onset and persistency risks of flash drought vary significantly depending on the MJO phase. Generally, the onset and persistency risks of flash droughts over the LMRB increase when the MJO convection is active over the Indian Ocean (phases 2–3), while decrease when the MJO is active over the Pacific Ocean (phases 6–7). The MJO primarily influences flash droughts over the lower reaches of the LMRB by modulating SAT and precipitation. During MJO phases 2–3, there exists significant increased SAT and preceding precipitation deficit over the lower reaches, leading to decline in soil moisture. During MJO phases 6–7, there are decreased SAT and preceding increased precipitation. Diagnosis results revealed that the impact of the MJO on SAT over the lower reaches is dominated by large-scale temperature advection associated with the MJO-induced vertical and meridional circulation anomalies, while its impact on precipitation is mainly modulated by the MJO-induced zonal wind gradients. This study emphasizes the importance of considering the effects of the MJO on precipitation and SAT for predicting flash droughts over the LMRB.
Abstract
The L-band passive microwave radiometer onboard the NASA Soil Moisture Active Passive (SMAP) satellite can measure brightness temperature to retrieve sea surface wind speed under tropical cyclone (TC) conditions without being affected by rainfall or signal saturation caused by high wind speeds. Based on this advantage, this paper used the SMAP wind products for parameterizing the key decay exponent (α) of the Rankine vortex model (a traditional parametric model of the TC wind field) and finally developed new Rankine models. The SMAP dataset included 67 TC cases. Through data statistics, we examined the relationship between α and the maximum wind speed (U m), the relationship between α and the radius of maximum wind speed (R m), and the relationship between R m and the averaged radius of 17 m/s (R 17). Results showed that the three relationships were both positive correlations, indicating that α can be parameterized in three empirical ways. The first way is to calculate solely with U m. The second way is to calculate solely with R m. The third way is to calculate with U m and R m together. The three ways correspond to three new models: the SMAP Rankine Model-1 (SRM-1), the SMAP Rankine Model-2 (SRM-2) and the SMAP Rankine Model-3 (SRM-3). Finally, comparisons were made between the new models and three existing Rankine models, according to the model simulations and the Advanced Microwave Scanning Radiometer 2 measurements of 49 TC cases. Results showed that the SRM-3 performed best overall.
Abstract
The L-band passive microwave radiometer onboard the NASA Soil Moisture Active Passive (SMAP) satellite can measure brightness temperature to retrieve sea surface wind speed under tropical cyclone (TC) conditions without being affected by rainfall or signal saturation caused by high wind speeds. Based on this advantage, this paper used the SMAP wind products for parameterizing the key decay exponent (α) of the Rankine vortex model (a traditional parametric model of the TC wind field) and finally developed new Rankine models. The SMAP dataset included 67 TC cases. Through data statistics, we examined the relationship between α and the maximum wind speed (U m), the relationship between α and the radius of maximum wind speed (R m), and the relationship between R m and the averaged radius of 17 m/s (R 17). Results showed that the three relationships were both positive correlations, indicating that α can be parameterized in three empirical ways. The first way is to calculate solely with U m. The second way is to calculate solely with R m. The third way is to calculate with U m and R m together. The three ways correspond to three new models: the SMAP Rankine Model-1 (SRM-1), the SMAP Rankine Model-2 (SRM-2) and the SMAP Rankine Model-3 (SRM-3). Finally, comparisons were made between the new models and three existing Rankine models, according to the model simulations and the Advanced Microwave Scanning Radiometer 2 measurements of 49 TC cases. Results showed that the SRM-3 performed best overall.
Abstract
The Eurasian teleconnection pattern (EU) is an important atmospheric intrinsic mode over the extratropical Northern Hemisphere, and it has strong influence on the weather and climate over Eurasia and remote regions. Investigating factors for the EU variability is crucial and has important implications for regional climate prediction. This study reveals a remarkable influence of El Niño-Southern Oscillation (ENSO) on the EU in early-winter, and particularly a notable enhancement of this influence since the late-1980s. The results indicate that ENSO can lead to the vertical motion and atmospheric heating anomalies over the tropical Indian Ocean, triggering an atmospheric wave train propagating along the subtropical westerly jet and inducing an EU-like pattern over Eurasia in early winter. The interdecadal enhancement of the ENSO impact on the EU after the late-1980s may be attributable to the warming of the background mean sea surface temperature (SST) in the tropical Indian Ocean. In particular, ENSO can lead to stronger atmospheric heating and circulation anomalies over the tropical Indian Ocean via a strong air-sea interaction due to a warmer background mean SST after the late-1980s. A warmer background mean SST in the tropical Indian Ocean accelerates the subtropical westerly jet due to the thermal-wind balance, which is more favorable for the propagation of the atmospheric wave train forced by the atmospheric heating anomalies in the tropical Indian Ocean. The observed mechanisms for the enhanced impact of ENSO on the EU are also validated by numerical experiments.
Abstract
The Eurasian teleconnection pattern (EU) is an important atmospheric intrinsic mode over the extratropical Northern Hemisphere, and it has strong influence on the weather and climate over Eurasia and remote regions. Investigating factors for the EU variability is crucial and has important implications for regional climate prediction. This study reveals a remarkable influence of El Niño-Southern Oscillation (ENSO) on the EU in early-winter, and particularly a notable enhancement of this influence since the late-1980s. The results indicate that ENSO can lead to the vertical motion and atmospheric heating anomalies over the tropical Indian Ocean, triggering an atmospheric wave train propagating along the subtropical westerly jet and inducing an EU-like pattern over Eurasia in early winter. The interdecadal enhancement of the ENSO impact on the EU after the late-1980s may be attributable to the warming of the background mean sea surface temperature (SST) in the tropical Indian Ocean. In particular, ENSO can lead to stronger atmospheric heating and circulation anomalies over the tropical Indian Ocean via a strong air-sea interaction due to a warmer background mean SST after the late-1980s. A warmer background mean SST in the tropical Indian Ocean accelerates the subtropical westerly jet due to the thermal-wind balance, which is more favorable for the propagation of the atmospheric wave train forced by the atmospheric heating anomalies in the tropical Indian Ocean. The observed mechanisms for the enhanced impact of ENSO on the EU are also validated by numerical experiments.
Abstract
A zonally symmetric perspective has proven to be very useful in studying the key role of the Southern Ocean for global ocean heat uptake. Despite this, reconstructions of changes in Southern Ocean heat content (ΔOHC) over the past few decades have revealed substantial deviations from symmetry. Here, we investigate the zonal asymmetry of ΔOHC and the processes driving it for the period 1979-2019 using an eddy-permitting ocean model forced by atmospheric reanalysis (ERA5). We find that the model successfully reproduces the observed zonal asymmetry in ΔOHC, and that it is primarily due to zonal asymmetries in changing surface fluxes. Zonal asymmetries in mean ocean circulation play an important secondary role. Factorial simulations are used to attribute the asymmetry in ΔOHC to the different surface flux components (wind stress, heat, and freshwater fluxes), revealing strong regional differences. North of the Antarctic Circumpolar Current (ACC), we find roughly equal contributions from changes in wind stress and surface heat flux. Within the ACC, all three forcings play an important role, while south of it only wind stress and freshwater flux changes are important. Our findings argue for full consideration of the three-dimensional circulation to understand heat uptake and storage in the Southern Ocean, especially when considering multidecadal timescales where natural variations are as important as the long-term warming trend.
Abstract
A zonally symmetric perspective has proven to be very useful in studying the key role of the Southern Ocean for global ocean heat uptake. Despite this, reconstructions of changes in Southern Ocean heat content (ΔOHC) over the past few decades have revealed substantial deviations from symmetry. Here, we investigate the zonal asymmetry of ΔOHC and the processes driving it for the period 1979-2019 using an eddy-permitting ocean model forced by atmospheric reanalysis (ERA5). We find that the model successfully reproduces the observed zonal asymmetry in ΔOHC, and that it is primarily due to zonal asymmetries in changing surface fluxes. Zonal asymmetries in mean ocean circulation play an important secondary role. Factorial simulations are used to attribute the asymmetry in ΔOHC to the different surface flux components (wind stress, heat, and freshwater fluxes), revealing strong regional differences. North of the Antarctic Circumpolar Current (ACC), we find roughly equal contributions from changes in wind stress and surface heat flux. Within the ACC, all three forcings play an important role, while south of it only wind stress and freshwater flux changes are important. Our findings argue for full consideration of the three-dimensional circulation to understand heat uptake and storage in the Southern Ocean, especially when considering multidecadal timescales where natural variations are as important as the long-term warming trend.
