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An intercomparison of ozone profiling instruments, two differential absorption lidars, a microwave radiometer, electrochemical concentration sondes, and the SAGE II satellite instrument is presented.
The OMPS Limb Profiler (LP) instrument is de-signed to provide high-vertical-resolution ozone and aerosol profiles from measurements of the scattered solar radiation in the 290–1000 nm spectral range. It collected its first Earth limb measurement on 10 January 2012 and continues to provide daily global measurements of ozone and aerosol profiles from the cloud top up to 60 and 40 km, respectively. The relatively high vertical and spatial sampling allow detection and tracking of sporadic events when aerosol particles are injected into the stratosphere, such as volcanic eruptions or pyro cumulonimbus (PyroCb) events. In this paper we discuss the newly released Version 2.0 OMPS multi-wavelength aerosol extinction coefficient retrieval algorithm. The algorithm now produces aerosol extinction profiles at 510, 600, 674, 745, 869 and 997 nm wavelengths. The OMPS LP Version 2.0 data products are compared to the SAGE III/ISS, OSIRIS and CALIPSO missions and shown to be of good quality and suitable for scientific studies. The comparison shows significant improvements in the OMPS LP retrieval performance in the Southern Hemisphere (SH) and at lower altitudes. These improvements arise from use of the longer wavelengths, in contrast with the V1.0 and V1.5 OMPS aerosol retrieval algorithms, which used radiances only at 675 nm and therefore had limited sensitivity in those regions. In particular, the extinction coefficients at 745, 869 and 997 nm are shown to be the most accurate, with relative accuracies and precisions close to 10% and 15%, respectively, while the 675 nm relative accuracy and precision are on the order of 20%. The 510 nm extinction coefficient is shown to have limited accuracy in the SH and is only recommended for use between 20–24 km and only in the Northern Hemisphere. The V2.0 retrieval algorithm has been applied to the complete set of OMPS LP measurements, and the new dataset is publicly available.
In this study, we evaluate a decadal ozone profile record derived from Suomi NPP Ozone Mapping and Profiler Suite (OMPS) Limb Profiler (LP). The data from OMPS LP were re-processed with the new retrieval algorithm from 2012 to present. The new reprocessing includes adjustments in both Level 1 and Level 2 algorithms. The sensor’s altitude registration, updates in radiometric calibrations, under-sampling and stray light corrections were addressed in Level 1 processing. The new retrieval algorithm (version 2.7) combines measurements from UV and VIS parts of the spectra to retrieve a single vertical ozone profile between 12.5 km (or cloud tops) and 57.5 km, unlike to previous version 2.5 where ozone profiles were retrieved independently from UV and VIS. To improve ozone retrievals in the Upper Troposphere Lower Stratosphere (UTLS) region, we implemented a new aerosol correction that assumes a gamma-function particle size distribution. In addition, ozone and nitrogen dioxide cross sections and climatologies were updated. We discuss sensitivity of the ozone retrievals to implemented changes in Level 1 and Level 2 algorithms. We focus our analysis on evaluation of the stability of the 10-year record from OMPS LP. We show results from the internal methods for characterizing the stability of the LP altitude registration and compare the LP reflectivity and ozone with the similar quantities measured by OMPS nadir sensors. Finally, we will show results from comparisons with independent satellite (MLS and SAGE III) and ozone sonde measurements.
In this presentation we evaluate ozone profile retrievals from Ozone Mapping and Profiling Suite Limb Profiler (OMPS-LP) launched in October 2011 on Suomi NPP satellite. The data from OMPS-LP were re-processed with the new retrieval algorithm that combines measurements from UV and VIS parts of the spectra to retrieve a single ozone profile between 12.5 km (or cloud tops) and 57.5 km. To improve ozone retrievals in the Upper Troposphere Lower Stratosphere (UTLS) region, a new aerosol correction with a gamma-function particle size distribution was implemented. The OMPS-LP altitude registration was also adjusted in the new version to ensure the stability of the ozone record. The continuous ozone profile observations with Suomi NPP OMPS LP exceeds 10 years. We will compare OMPS-LP ozone profiles with coincident stratospheric ozone measurements from NASA Aura MLS, ISS SAGE III, and OMPS NP and with the observations in UTLS and middle stratosphere from a ground-based network of ozone sonde stations to evaluate accuracy and precision of OMPS-LP retrievals and overall stability of the record. We will also investigate the quality of stratospheric ozone columns obtained from OMPS-LP and estimate the contribution of various errors to integrated stratospheric columns from OMPS-LP.
The most extreme manifestation of a fire–weather interaction is the formation of pyrocumulonimbus (pyroCb) thunderstorms, triggered by super-heated updrafts, which can eject smoke at altitudes exceeding 20 Km. In this study, we investigated climate-related impacts from the most intensive pyroCb-triggered injection of smoke in the stratosphere: the Australian New Year wildfires in 2019/2020. We first provide a general overview of the vision and objectives of the StratoFIRE project. With the aid of the global chemistry-climate model EMAC, we then simulate radiative and chemical perturbations in the stratosphere in relation to 0.9 Tg smoke in the stratosphere assuming different injection heights, from 13 to 16 Km. The simulation of stratospheric optical depth perturbations were found to be sensitive to the assumed injection height, with a maximum height at 16 Km showing the best agreement with the GLOSSAC and SAGE-ISS aerosol extinction observations.
Using the NASA GEOS Chemistry Climate Model (CCM) coupled to a detailed sectional aerosol microphysical model, we have simulated the January 2022 Hunga Tonga-Hunga Ha’apai (HTHH) plume. We have developed a version of the Global Modeling Initiative (GMI) chemistry mechanism to include the requisite sulfur chemistry and coupled it to the Community Aerosol and Radiation Model for Atmospheres (CARMA) sectional aerosol microphysics within the GEOS CCM. Our simulations focus on the lifecycle of stratospheric sulfur injected by the eruption–from the oxidation of the injected sulfur dioxide to the nucleation, growth, coagulation, hydration, and eventual settling of the volcanic sulfate aerosol particles. In order to constrain the simulated microphysics, we focus on comparing our model to observations with aerosol size information, namely in-situ particle counter observations and multi-wavelength satellite observations from OMPS-LP and SAGE-III. This eruption provides an interesting test case for our model; both the modeled gas-phase chemistry as well as the modeled aerosol microphysics are perturbed by the massive injection of water that accompanied the primary sulfur emissions from the eruption.
The conference clearly demonstrated the increasing interest and growth of the scientific community working on the development and application of sub-seasonal to seasonal prediction since the start of the World Weather Research Programme (WWRP)/World Climate Research Programme (WCRP) sub-seasonal to seasonal (S2S) prediction project in 2013. The conference, which was held at the University of Reading (United Kingdom), was organized into three main themes as briefly summarized below, with eleven invited talks, 74 oral contributed talks, and 101 posters. The conference also included a two-hour breakout session, wherein eight groups discussed the current state and prospect for S2S prediction, and an early career researcher event. A summary of these discussions and recommendations is presented below. The conference web page (https://research.reading.ac.uk/s2s-summit2023/) is archived at the University of Reading. Introductory comments by representatives of the World Meteorological Organization (WMO) WWRP and WCRP emphasized the importance of the weather–climate linkage, targeted by S2S forecasts (from 2 weeks to a season ahead), addressing the challenges of creating “end-to-end” forecasts that encompass the entire climate-services chain from the prediction science and forecast, to the development and issuing of forecast products tailored to informing user-decisions. They also emphasized the efficacy of multi-model ensemble efforts and databases to foster collaborations internationally and between operational centres and academia. Although the WWRP/WCRP S2S project comes to an end in 2023, S2S prediction will remain an important focus for WWRP and WCRP. In WWRP, a new project called SAGE (Sub-seasonal to seasonal predictions for Agriculture and Environment) will start in 2024. Another important legacy of the S2S project will be the maintenance of the S2S database (Vitart et al. 2017) and the establishment of a WMO Lead Center for sub-seasonal prediction multi-model ensemble (LC-SSPMME) which will provide real-time multi-model S2S climate information. In two keynote presentations, Prof. Brian Hoskins (University of Reading) and Dr. Gilbert Brunet (Australian Bureau of Meteorology) discussed the potential of S2S predictability and the ongoing journey for understanding and improving these predictions. This conference was a sequel to the International Conference on Sub-seasonal to Seasonal Prediction (Robertson et al., 2014) which took place in College Park (Maryland, USA) in February 2014 to celebrate the start of the WWRP/WCRP S2S project, and to WCRP and WWRP conferences in Boulder, USA, in 2018 (Merryfield et al., 2020). A significant development compared to the previous S2S conferences was the large number of presentations on research to operation (R2O) and S2S applications and on the use of artificial intelligence and machine learning (AI/ML) methods for S2S prediction. Some of these methods provide empirical S2S forecasts which are competitive with state-of-the-art dynamical models. Other presentations demonstrated that AI/ML can provide alternative calibration of dynamical model outputs to traditional methods. Several talks and posters highlighted the increasing use of AI/ML, including deep learning, in S2S forecast post-processing and using AI to identify higher flow-dependent skill. Finally, some presentations demonstrated the value of AI/ML methods for a better understanding of S2S sources of predictability and attribution of extreme events.
The way volcanic clouds evolve is very sensitive to the initial spatial 3D distributions of volcanic materials, which are often unknown. In this study, we conducted inverse modeling of the Mt. Pinatubo cloud using TOMS 2D mapping of Aerosol Index and SO 2 loading during the first three post-eruption days to estimate the time-dependent emissions profiles and initial 3D spatial distributions of volcanic ash and SO 2 . We account for aerosol radiative feedback and dynamic lofting of volcanic ash in the inversion calculations for the first time. This resulted in a lower ash injection height (by 1.5 km for ash) than without ash radiative feedback. The Pinatubo eruption ejected ≈77% of fine ash at 12 to 23 km, ≈65% of SO 2 at 18–25 km. In contrast with previous studies, which suggested that all volcanic materials were emitted above the tropopause, a significant fraction of SO 2 (5.1 of 15.5 Mt) and fine ash (37.2 of 66.5 Mt) were ejected in the troposphere, where SO 2 quickly oxidized into sulfate aerosol that is short-lived in the troposphere. This explains the early presence of sulfate aerosols in the plume and why the models can reproduce the observed volcanic aerosols' optical depth (AOD), assuming lower-than-observed SO 2 emission in the stratosphere. Despite the quicker than in observations build-up of sulfate AOD, in a month after the eruption, the evolution of the Pinatubo AOD simulated using the obtained ash and SO 2 initial distributions converges with the available stratospheric aerosol and gas experiment (SAGE) observations.
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Parameter adjustment model reference adaptive control of nuclear rocket engine, noting design parameters, system performance, propellant savings estimates and dynamic stability
Nonlinear and nonstationary finite differential system identification by quasi-linearization and differential approximation
Nuclear magnetic resonance measurement of impurities in magnetic garnets - ferromagnetic relaxation in metals and in magnetic oxides - ultrasonic attenuation in magnetic oxides
Real time digital simulation of linear and nonlinear control systems with large sampling intervals, determining optimization criterion by nonlinear multipoint boundary value problem
Sequential suboptimal adaptive control of nonlinear systems, considering generation of optimum closed-loop control for startup dynamics of nuclear reactor
Real time approximation of continuous system performance on digital computer using difference equations obtained from digitized transfer function
Suboptimal feedback solution to guidance and control in minimum time and fuel for low thrust orbital transfer
Previous attempts to identify aircraft stability and control derivatives from flight test data, using three-degrees-of-freedom (3-DOF) longitudinal or lateral-directional perturbation-equations-of-motion models, suffer from the disadvantage that the coupling between the longitudinal and lateral-directional dynamics has been ignored. In this paper the identification of aircraft stability parameters is accomplished using a more accurate 6-DOF model which includes this coupling. Hierarchical system identification theory is used to reduce the computational effort involved. The 6-DOF system of equations is decomposed into two 3-DOF subsystems, one for the longitudinal dynamics and the other for the lateral-directional dynamics. The two subsystem parameter identification processes are then coordinated in such a way that the overall system parameter identification problem is solved.
This guidebook describes the characteristics and interrelationships of Archean greenstone-granite and high-grade gneiss terrains of the Superior Province. A 300-km long west to east transect between Wawa and Timmins, Ontario will be used to illustrate regional-scale relationships. The major geological features of the Superior Province are described.