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The NASA Goddard Earth Observing System (GEOS) employs a hybrid four‐dimensional ensemble‐variational (Hybrid‐4DEnVar) atmospheric data assimilation system to provide global, near‐real time weather analysis and forecast products. This study introduces a land analysis into the GEOS Hybrid‐4DEnVar system to additionally assimilate L‐band (1.4 GHz) brightness temperature observations over land from the NASA Soil Moisture Active Passive (SMAP) satellite mission, which are highly sensitive to surface (∼0–5 cm) soil moisture. This weakly coupled land analysis impacts the simulated and forecast atmosphere through the land–atmosphere exchange processes encoded in the atmospheric model. Retrospective assimilation experiments for boreal summer 2017 were conducted with the system at 50 km horizontal resolution. The SMAP assimilation is shown to mitigate errors in screen‐level (2 m) specific humidity (q2m) and temperature (T2m), with regional reductions in the root‐mean‐square error (RMSE) of q2m and maximum daily T2m by up to 0.4 g·kg−1 and 0.3 K, respectively. These improvements are somewhat smaller than those found in a precursor study that used the atmospheric analysis in the simpler, 3‐dimensional variational (3DVar) atmospheric assimilation configuration of the current GEOS reanalysis; Hybrid‐4DEnVar provides overall better near‐surface background estimates than 3DVar and therefore leaves less room for improvement. Finally, in the Hybrid‐4DEnVar system with SMAP assimilation, forecasts of q2m and T2m have significantly improved anomaly correlation and RMSE (99% confidence) at lead times out to 5 days compared to the Hybrid‐4DEnVar system without SMAP assimilation, with medium‐range lead times extended by ∼3 hr for q2m and ∼2 hr for T2m. Slight but nevertheless significant improvements are also seen for temperature forecasts at the 925 and 850 hPa levels and lead times out to 4 days. Humidity forecasts at 925 and 850 hPa are improved out to 1.5‐day lead time with 90% confidence. [ABSTRACT FROM AUTHOR]

The performance benefits of passive vibration suppression with network configurations consisting of stiffness, damping and inertance elements have been demonstrated for a wide range of mechanical systems. Considering physical implementations of these beneficial network configurations, hydraulic realisations have the advantages of durability and simplicity for integration with existing hydraulic dampers. Such designs are exemplified by fluid inerters and fluid-inerter-damper devices. However, in contrast to the convenience of realising inertance and damping elements, realising 'embedded' stiffness is very challenging. We use 'embedded' to refer to a network element, which is not purely in series or in parallel with the remainder of the network but instead lies within the network layout. In this work, a setup using a rubber membrane to realise such embedded stiffness is proposed, together with a procedure for hydraulic implementations of any stiffness-damping-inertance configurations. The nonlinear properties of the embedded stiffness due to rubber membrane properties are then investigated both theoretically and experimentally. In addition, the effectiveness of both the membrane setup and the design procedure are demonstrated via a case study of suspension design for passenger vehicle ride comfort enhancement. [ABSTRACT FROM AUTHOR]

This paper explores the pathways and barriers to critical consciousness development for Chinese American youth. Thirty‐five interviews conducted in 2020 with high‐school‐aged students in Chicago were analyzed to better understand young people's experiences developing an understanding of anti‐Asian racism and anti‐Blackness. Results indicated that participants overwhelmingly engaged in sustained conversations about Black Lives Matter and/or made efforts to address anti‐Blackness within their families, but engaged in limited conversations about anti‐Asian racism. Furthermore, conversations at home and school often failed to contextualize anti‐Asian racism, specifically in relation to the experiences of other oppressed groups. Findings highlight a need for research on and practice with Chinese American adolescents to recognize the unique racial positioning of Asian Americans under White supremacy. [ABSTRACT FROM AUTHOR]

For modern electrical rail systems, the pantograph-catenary dynamic performance is one of the most critical challenges. Too much fluctuation in contact forces leads to either accelerated wear of the contacting components or losses of contact and, consequently, arcing. In this work, inertance-integrated pantograph damping systems are investigated with the objective of reducing the contact force standard deviation. Firstly, a multibody pantograph model is developed with its accuracy compared with experimental data. The model is improved through the calibration of the pantograph head suspension parameters and the introduction of both non-ideal joint and flexibility effects. Using the calibrated model, beneficial inertance-integrated damping systems are identified for the pantograph suspension. The results show that the configuration with one inerter provides the best performance among other candidate layouts and contends a 40% reduction of the maximum standard deviation of the contact force over the whole operating speed range in the numerical modelling scenario analysed. Considering the identified configuration, time-domain analysis and modal analysis are investigated. It has been shown that the achieved improvement is due to the fact that with the beneficial inertance-integrated damping system, the first resonance frequency of the pantograph system coincides with the natural frequency of the catenary system. [ABSTRACT FROM AUTHOR]

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This paper presents the numerical study on propagative waves in a periodically supported rail below 6000 Hz. A periodic rail model, which considers the effects of both the periodic supports and the rail cross section deformation, has been established based on the periodic structure theory and the finite element method. Two selection approaches are proposed to obtain the concerned dispersion curves from the original calculation results of dispersion relations. The differences between the dispersion curves of different support conditions are studied. The propagative waves corresponding to the dispersion curves are identified by the wave modes. The influences of periodic supports on wave modes in pass bands are revealed. Further, the stop band behaviors are investigated in terms of the bounding frequencies, the standing wave characteristics, and the cross-sectional modes. The results show that eight propagative waves with distinct modes exist in a periodically supported rail below 6000 Hz. The differences between the dispersion curves of periodically and continuously supported rails are not obvious, apart from the stop band behaviors. All the bounding-frequency modes of the stop bands are associated with the standing waves. Two bounding-frequency modes of the same stop band can be regarded as two identical standing waves with the longitudinal translation of the quarter-wavelength, one of which is the so-called pinned-pinned resonance. [ABSTRACT FROM AUTHOR]

An improved representation of 3-D air motion and precipitation structure through forecast models and assimilation of observations is vital for improvements in weather forecasting capabilities. However, there are few independent data to properly validate a model forecast of precipitation structure when the underlying dynamics are evolving on short convective timescales. Using data from the JPL Ku/Ka-band Airborne Precipitation Radar (APR-2) and the 2 µ m Doppler Aerosol Wind (DAWN) lidar collected during the 2017 Convective Processes Experiment (CPEX), the NASA Unified Weather Research and Forecasting (WRF) Ensemble Data Assimilation System (EDAS) modeling system was used to quantify the impact of high-resolution sparsely sampled DAWN measurements on the analyzed variables and on the forecast when the DAWN winds were assimilated. Overall, the assimilation of the DAWN wind profiles had a discernible impact on the wind field as well as the evolution and timing of the 3-D precipitation structure. Analysis of individual variables revealed that the assimilation of the DAWN winds resulted in important and coherent modifications of the environment. It led to an increase in the near-surface convergence, temperature, and water vapor, creating more favorable conditions for the development of convection exactly where it was observed (but not present in the control run). Comparison to APR-2 and observations by the Global Precipitation Measurement (GPM) satellite shows a much-improved forecast after the assimilation of the DAWN winds – development of precipitation where there was none, more organized precipitation where there was some, and a much more intense and organized cold pool, similar to the analysis of the dropsonde data. The onset of the vertical evolution of the precipitation showed similar radar-derived cloud-top heights, but delayed in time. While this investigation was limited to a single CPEX flight date, the investigation design is appropriate for further investigation of the impact of airborne Doppler wind lidar observations upon short-term convective precipitation forecasts. [ABSTRACT FROM AUTHOR]

An improved representation of the 3-D air motion and precipitation structure through forecast models and assimilation of observations is vital for improvements in weather forecasting capabilities. However, there is little independent data to properly validate a model forecast of precipitation structure when the underlying dynamics are evolving on short convective times scales. Using data from the JPL Ku/Ka-band Airborne Precipitation Radar (APR-2) and the 2- um Doppler Aerosol Wind (DAWN) lidar collected during the 2017 Convective Processes Experiment (CPEX), the NASA Unified Weather Research and Forecasting (WRF) Ensemble Data Assimilation System (EDAS) modeling system was used to quantify the impact of the high resolution, sparsely-sampled DAWN measurements on the analyzed variables and on the forecast when the DAWN winds were assimilated. Overall, the assimilation of the DAWN wind profiles had a discernible impact to the wind field and the evolution and timing of the 3-D precipitation structure. Analysis of individual variables revealed that the assimilation of the DAWN winds resulted in important and coherent modifications of the environment. It led to increase of the near surface convergence, temperature and water vapor, creating more favorable conditions for the development of convection exactly where it was observed (but not present in the control run). Comparison to APR-2 and observations by the Global Precipitation Measurement (GPM) satellite shows a much-improved forecast after the assimilation of the DAWN winds - development of precipitation where there was none, more organized precipitation where there was some, and a much more intense and organized cold pool, similar to the analysis of the dropsonde data. Onset of the vertical evolution of the precipitation showed similar radar-derived cloud top heights, but delayed in time. While this investigation was limited to a single CPEX flight date, the investigation design is appropriate for further investigation of the impact of airborne Doppler wind lidar observations upon short-term convective precipitation forecasts. [ABSTRACT FROM AUTHOR]

The Global Precipitation Measurement (GPM) constellation of spaceborne sensors provides a variety of direct and indirect measurements of precipitation processes. Such observations can be employed to derive spatially and temporally consistent gridded precipitation estimates either via data-driven retrieval algorithms or by assimilation into physically based numerical weather models. We compare the data-driven Integrated Multisatellite Retrievals for GPM (IMERG) and the assimilation-enabled NASA-Unified Weather Research and Forecasting (NU-WRF) model against Stage IV reference precipitation for four major extreme rainfall events in the southeastern United States using an object-based analysis framework that decomposes gridded precipitation fields into storm objects. As an alternative to conventional "grid-by-grid analysis," the object-based approach provides a promising way to diagnose spatial properties of storms, trace them through space and time, and connect their accuracy to storm types and input data sources. The evolution of two tropical cyclones are generally captured by IMERG and NU-WRF, while the less organized spatial patterns of two mesoscale convective systems pose challenges for both. NU-WRF rain rates are generally more accurate, while IMERG better captures storm location and shape. Both show higher skill in detecting large, intense storms compared to smaller, weaker storms. IMERG's accuracy depends on the input microwave and infrared data sources; NU-WRF does not appear to exhibit this dependence. Findings highlight that an object-oriented view can provide deeper insights into satellite precipitation performance and that the satellite precipitation community should further explore the potential for "hybrid" data-driven and physics-driven estimates in order to make optimal usage of satellite observations. [ABSTRACT FROM AUTHOR]

The mechanisms linking convection and cloud dynamical processes are major factors in much of the uncertainty in both weather and climate prediction. Further constraining the uncertainty in convective cloud processes linking 3-D air motion and cloud structure through models and observations is vital for improvements in weather forecasting and understanding limits on atmospheric predictability. To date, there have been relatively few airborne observations specifically targeted for linking the 3-D air motion surrounding developing clouds to the subsequent development (or nondevelopment) of convective precipitation. During the May–June 2017 Convective Processes Experiment (CPEX), NASA DC-8-based airborne observations were collected from the JPL Ku- and Ka-band Airborne Precipitation Radar (APR-2) and the 2 µ m Doppler Aerosol Wind (DAWN) lidar during approximately 100 h of flight. For CPEX, the APR-2 provided the vertical air motion and structure of the cloud systems in nearby precipitating regions where DAWN is unable to sense. Conversely, DAWN sampled vertical wind profiles in aerosol-rich regions surrounding the convection but is unable to sense the wind field structure within most clouds. In this paper, the complementary nature of these data are presented from the 10–11 June flight dates, including the APR-2 precipitation structure and Doppler wind fields as well as adjacent wind profiles from the DAWN data. [ABSTRACT FROM AUTHOR]

In this study, the impact of different configurations of the Goddard radiation scheme on convection-permitting simulations (CPSs) of the West African monsoon (WAM) is investigated using the NASA-Unified WRF (NU-WRF). These CPSs had 3 km grid spacing to explicitly simulate the evolution of mesoscale convective systems (MCSs) and their interaction with radiative processes across the WAM domain and were able to reproduce realistic precipitation and energy budget fields when compared with satellite data, although low clouds were overestimated. Sensitivity experiments reveal that (1) lowering the radiation update frequency (i.e., longer radiation update time) increases precipitation and cloudiness over the WAM region by enhancing the monsoon circulation, (2) deactivation of precipitation radiative forcing suppresses cloudiness over the WAM region, and (3) aggregating radiation columns reduces low clouds over ocean and tropical West Africa. The changes in radiation configuration immediately modulate the radiative heating and low clouds over ocean. On the 2nd day of the simulations, patterns of latitudinal air temperature profiles were already similar to the patterns of monthly composites for all radiation sensitivity experiments. Low cloud maintenance within the WAM system is tightly connected with radiation processes; thus, proper coupling between microphysics and radiation processes must be established for each modeling framework. [ABSTRACT FROM AUTHOR]

The mechanisms linking convection and cloud dynamical processes is a major factor in much of the uncertainty in both weather and climate prediction. Further constraining the uncertainty in convective cloud processes linking 3-D air motion and cloud structure through models and observations is vital for improvements in weather forecasting, and understanding limits on atmospheric predictability. To date, there have been relatively few airborne observations specifically targeted for sampling convective cloud processes linking 3-D air motion and transport of water vapor near clouds, and the subsequent development (or non-development) of convective precipitation. During the May–June 2017 Convective Processes Experiment (CPEX), NASA DC-8-based airborne observations were collected from the JPL Ku/Ka-band Airborne Precipitation Radar (APR-2) and the 2-um Doppler Aerosol Wind (DAWN) lidar during approximately 100 flight hours. Frequent dropsonde data accompanied the DAWN observations for validation purposes, and to provide complement wind profiles in and near convection. For CPEX, the APR-2 provided vertical air motion and structure of the cloud systems in nearby precipitating regions where DAWN is unable to sense. Conversely, DAWN sampled vertical wind profiles in aerosol-rich regions surrounding the convection, but is unable to sense the wind field structure within cloud. In this manuscript, the complementary nature of these data are presented from the June 10–11 flight dates, including the APR-2 precipitation structure and Doppler wind fields, and adjacent wind profiles from the DAWN and dropsonde data. [ABSTRACT FROM AUTHOR]

Tuned mass dampers (TMDs), in which a reaction mass is attached to a structural system via a spring-parallel-damper connection, are commonly used in a wide range of applications to suppress deleterious vibrations. Recently, a mass-included absorber layout with an inerter element, termed the tuned mass damper inerter (TMDI), was introduced, showing significant performance benefits on vibration suppression. However, there are countless massincluded absorber layouts with springs, dampers and inerters, which could potentially provide more preferred dynamic properties. Currently, because there is no systematic methodology for accessing them, only an extremely limited number of massincluded absorber layouts have been investigated. This paper proposes an approach to identify optimum vibration absorbers with a reaction mass. Using this approach, a full class of absorber layouts with a reaction mass and a pre-determined number of inerters, dampers and springs connected in series and parallel, can be systematically investigated using generic Immittance-Function-Networks. The advantages of the proposed approach are demonstrated via a 3 d.f. structure example. [ABSTRACT FROM AUTHOR]

This paper provides a complete realisation of a special class of positive-real bicubic impedances. The problem is motivated by the concept of the inerter, which is the mechanical dual of a capacitor. This device allows mechanical network synthesis, by completing the electrical mechanical analogy. With mechanical synthesis, the emphasis is to minimise the number of elements required to allow feasible implementation. The definitions of simple-series-parallel networks and essential-regular positive-real functions are introduced. The simple-series-parallel minimum-reactive networks that can realise all essential-regular bicubics are identified and grouped into six network quartets. One of the advantages of these networks is that they contain the minimal number of reactive elements. The necessary and sufficient realisability conditions for all these networks, as well as corresponding element values, are then derived. Finally, numerical examples are provided to illustrate the validity of the theoretical results. In the course of the argument, interesting conclusions regarding essential-regular bilinear and biquadratic functions have also been presented. Copyright © 2017 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

This work assimilates multisensor precipitation-sensitive microwave radiance observations into a storm-scale NASA Unified Weather Research and Forecasting (NU-WRF) Model simulation of the West African monsoon. The analysis consists of a full description of the atmospheric states and a realistic cloud and precipitation distribution that is consistent with the observed dynamic and physical features. The analysis shows an improved representation of monsoon precipitation and its interaction with dynamics over West Africa. Most significantly, assimilation of precipitation-affected microwave radiance has a positive impact on the distribution of precipitation intensity and also modulates the propagation of cloud precipitation systems associated with the African easterly jet. Using an ensemble-based assimilation technique that allows state-dependent forecast error covariance among dynamical and microphysical variables, this work shows that the assimilation of precipitation-sensitive microwave radiances over the West African monsoon rainband enables initialization of storms. These storms show the characteristics of continental tropical convection that enhance the connection between tropical waves and organized convection systems. [ABSTRACT FROM AUTHOR]

Linear passive vibration absorbers, such as tuned mass dampers, often contain springs, dampers and masses, although recently there has been a growing trend to employ or supplement the mass elements with inerters. When considering possible configurations with these elements broadly, two approaches are normally used: one structure-based and one immittance-based. Both approaches have their advantages and disadvantages. In this paper, a new approach is proposed: the structure-immittance approach. Using this approach, a full set of possible series-parallel networks with predetermined numbers of each element type can be represented by structural immittances, obtained via a proposed general formulation process. Using the structural immittances, both the ability to investigate a class of absorber possibilities together (advantage of the immittance-based approach), and the ability to control the complexity, topology and element values in resulting absorber configurations (advantages of the structure-based approach) are provided at the same time. The advantages of the proposed approach are demonstrated through two case studies on building vibration suppression and automotive suspension design, respectively. [ABSTRACT FROM AUTHOR]

This paper investigates the use of a two-terminal vibration suppression device in a building. The use of inerter-spring-damper configurations for a multi-storey building structure is considered. The inerter has been used in Formula 1 racing cars and applications to various systems such as road vehicles have been identified. Several devices that incorporate inerter(s), as well as spring(s) and damper(s), have also been identified for vibration suppression of building structures. These include the tuned inerter damper and the tuned viscous mass damper. In this paper, a three-storey building model with a two-terminal absorber located at the bottom subjected to base excitation is studied. The brace stiffness is also taken into consideration. Four optimum absorber layouts, in terms of how spring, damper and inerter components should be arranged, for minimising the maximum relative displacements of the building are obtained with respect to the inerter's size and the brace stiffness. The corresponding parameter values for the optimum absorber layouts are also presented. Furthermore, a real-life earthquake data is used to show the advantage of proposed absorber configurations. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The forthcoming Global Precipitation Measurement ( GPM) Mission will provide next-generation precipitation observations from a constellation of satellites. Since precipitation by nature has large variability and low predictability at cloud-resolving scales, the impact of precipitation data on the skills of mesoscale numerical weather prediction ( NWP) is largely affected by the characterization of background and observation errors and the representation of nonlinear cloud/precipitation physics in an NWP data assimilation system. We present a data impact study on the assimilation of precipitation-affected microwave ( MW) radiances from a pre- GPM satellite constellation using the Goddard WRF Ensemble Data Assimilation System (Goddard WRF- EDAS). A series of assimilation experiments are carried out in a Weather Research Forecast ( WRF) model domain of 9 km resolution in western Europe. Sensitivities to observation error specifications, background error covariance estimated from ensemble forecasts with different ensemble sizes, and MW channel selections are examined through single-observation assimilation experiments. An empirical bias correction for precipitation-affected MW radiances is developed based on the statistics of radiance innovations in rainy areas. The data impact is assessed by full data assimilation cycling experiments for a storm event that occurred in France in September 2010. Results show that the assimilation of MW precipitation observations from a satellite constellation mimicking GPM has a positive impact on the accumulated rain forecasts verified with surface radar rain estimates. The case-study on a convective storm also reveals that the accuracy of ensemble-based background error covariance is limited by sampling errors and model errors such as precipitation displacement and unresolved convective scale instability. [ABSTRACT FROM AUTHOR]

Assimilation of remotely sensed precipitation observations into numerical weather prediction models can improve precipitation forecasts and extend prediction capabilities in hydrological applications. This paper presents a new regional ensemble data assimilation system that assimilates precipitation-affected microwave radiances into the Weather Research and Forecasting Model (WRF). To meet the challenges in satellite data assimilation involving cloud and precipitation processes, hydrometeors produced by the cloud-resolving model are included as control variables and ensemble forecasts are used to estimate flow-dependent background error covariance. Two assimilation experiments have been conducted using precipitation-affected radiances from passive microwave sensors: one for a tropical storm after landfall and the other for a heavy rain event in the southeastern United States. The experiments examined the propagation of information in observed radiances via flow-dependent background error auto- and cross covariance, as well as the error statistics of observational radiance. The results show that ensemble assimilation of precipitation-affected radiances improves the quality of precipitation analyses in terms of spatial distribution and intensity in accumulated surface rainfall, as verified by independent ground-based precipitation observations. [ABSTRACT FROM AUTHOR]

In the near future, the Global Precipitation Measurement (GPM) mission will provide precipitation observations with unprecedented accuracy and spatial/temporal coverage of the globe. For hydrological applications, the satellite observations need to be downscaled to the required finer-resolution precipitation fields. This paper explores a dynamic downscaling method using ensemble data assimilation techniques and cloud-resolving models. A prototype ensemble data assimilation system using the Weather Research and Forecasting Model (WRF) has been developed. A high-resolution regional WRF with multiple nesting grids is used to provide the first-guess and ensemble forecasts. An ensemble assimilation algorithm based on the maximum likelihood ensemble filter (MLEF) is used to perform the analysis. The forward observation operators from NOAA--NCEP''s gridpoint statistical interpolation (GSI) are incorporated for using NOAA--NCEP operational datastream, including conventional data and clear-sky satellite observations. Precipitation observation operators are developed with a combination of the cloud-resolving physics from NASA Goddard cumulus ensemble (GCE) model and the radiance transfer schemes from NASA Satellite Data Simulation Unit (SDSU). The prototype of the system is used as a test bed to optimally combine observations and model information to produce a dynamically downscaled precipitation analysis. A case study on Tropical Storm Erin (2007) is presented to investigate the ability of the prototype of the WRF Ensemble Data Assimilation System (WRF-EDAS) to ingest information from in situ and satellite observations including precipitation-affected radiance. The results show that the analyses and forecasts produced by the WRF-EDAS system are comparable to or better than those obtained with the WRF-GSI analysis scheme using the same set of observations. An experiment was also performed to examine how the analyses and short-term forecasts of microphysical variables and dynamical fields are influenced by the assimilation of precipitation-affected radiances. The results highlight critical issues to be addressed in the next stage of development such as model-predicted hydrometeor control variables and associated background error covariance, bias estimation, and correction in radiance space, as well as the observation error statistics. While further work is needed to optimize the performance of WRF-EDAS, this study establishes the viability of developing a cloud-scale ensemble data assimilation system that has the potential to provide a useful vehicle for downscaling satellite precipitation information to finer scales suitable for hydrological applications. [ABSTRACT FROM AUTHOR]

Currently, operational weather forecasting systems use observations to optimize the initial state of a forecast without considering possible model deficiencies. For precipitation assimilation, this could be an issue since precipitation observations, unlike conventional data, do not directly provide information on the atmospheric state but are related to the state variables through parameterized moist physics with simplifying assumptions. Precipitation observation operators are comparatively less accurate than those for conventional data or observables in clear-sky regions, which can limit data usage not because of issues with observations, but with the model. The challenge lies in exploring new ways to make effective use of precipitation data in the presence of model errors. This study continues the investigation of variational algorithms for precipitation assimilation using column model physics as a weak constraint. The strategy is to develop techniques to make online estimation and correction of model errors to improve the precipitation observation operator during the assimilation cycle. Earlier studies have shown that variational continuous assimilation (VCA) of tropical rainfall using moisture tendency correction can improve Goddard Earth Observing System 3 (GEOS-3) global analyses and forecasts. Here results are presented from a 4-yr GEOS-3 reanalysis assimilating Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and Special Sensor Microwave Imager (SSM/I) tropical rainfall using the VCA scheme. Comparisons with NCEP operational analysis and the 40-yr ECMWF Re-Analysis (ERA-40) show that the GEOS-3 reanalysis is significantly better at replicating the intensity and variability of tropical precipitation systems ranging from a few days to interannual time scales. As a further refinement of rainfall assimilation using the VCA scheme, a variational algorithm for assimilating TMI latent heating retrievals using semiempirical parameters in the model moist physics as control variables is described and initial test results are presented. [ABSTRACT FROM AUTHOR]

Global microwave rainfall retrievals from a five-satellite constellation, including the Tropical Rainfall Measuring Mission Microwave Imager, Special Sensor Microwave Imager from the Defense Meteorological Satellite Program F13, F14, and F15, and the Advanced Microwave Scanning Radiometer from the Earth Observing System Aqua, are assimilated into the NASA Goddard Earth Observing System (GEOS) Data Assimilation System using a 1D variational continuous assimilation (VCA) algorithm. The physical and dynamical impact of rainfall assimilation on GEOS analyses is examined at various temporal and spatial scales. This study demonstrates that the 1D VCA algorithm, which was originally developed and evaluated for rainfall assimilations over tropical oceans, can effectively assimilate satellite microwave rainfall retrievals and improve GEOS analyses over both the Tropics and the extratropics where the atmospheric processes are dominated by different large-scale dynamics and moist physics, and also over land, where rainfall estimates from passive microwave radiometers are believed to be less accurate. Results show that rainfall assimilation renders the GEOS analysis physically and dynamically more consistent with the observed precipitation at the monthly mean and 6-h time scales. Over regions where the model precipitation tends to misbehave in distinctly different rainy regimes, the 1D VCA algorithm, by compensating for errors in the model’s moist time tendency in a 6-h analysis window, is able to bring the rainfall analysis closer to the observed. The radiation and cloud fields also tend to be in better agreement with independent satellite observations in the rainfall–assimilation run especially over regions where rainfall analyses indicate large improvements. Assimilation experiments with and without rainfall data for a midlatitude frontal system clearly indicate that the GEOS analysis is improved through changes in the thermodynamic and dynamic fields that respond to the rainfall assimilation. The synoptic structures of temperature, moisture, winds, divergence, and vertical motion, as well as vorticity, are more realistically captured across the front. [ABSTRACT FROM AUTHOR]

This study describes a 1D variational continuous assimilation (VCA) algorithm for assimilating tropical rainfall data using moisture/temperature time-tendency corrections as the control variable to offset model deficiencies. For rainfall assimilation, model errors are of special concern since model-predicted precipitation is based on parameterized moist physics, which can have substantial systematic errors. The authors examine whether a VCA scheme using the forecast model as a weak constraint offers an effective pathway to precipitation assimilation. The particular scheme investigated employs a precipitation observation operator based on a 6-h integration of a column model of moist physics from the Goddard Earth Observing System (GEOS) global data assimilation system (DAS). In earlier studies, a simplified version of this scheme was tested, and improved monthly mean analyses and better short-range forecast skills were obtained. This paper describes the full implementation of the 1DVCA scheme using background and observation error statistics and examines its impact on GEOS analyses and forecasts of prominent tropical weather systems such as hurricanes. Assimilation experiments with and without rainfall data for Hurricanes Bonnie and Floyd show that assimilating 6-h Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and Special Sensor Microwave Imager (SSM/I) surface rain accumulations leads to more realistic analyzed storm features and better 5-day storm track prediction and precipitation forecasts. These results demonstrate the importance of addressing model deficiencies in moisture time tendency in order to make effective use of precipitation information in data assimilation. [ABSTRACT FROM AUTHOR]

Describes the benefits of using rainfall and total precipitable water (TPW) information derived from instruments in global data assimilation with observations from the Tropical Rainfall Measuring Mission Microwave Imager and two Special Sensor Microwave/Imager instruments. Importance of addressing deficiencies in model physics in assimilating data types such as precipitation; Potential of using rainfall and TPW information.

ABSTRACT A global analysis that optimally combines observations from diverse sources with physical models of atmospheric and land processes can provide a comprehensive description of the climate systems. Currently, such data products contain significant errors in primary hydrological fields such as precipitation and evaporation, especially in the Tropics. In this study it is demonstrated that assimilating precipitation and total precipitable water (TPW) derived from the Tropical Rainfall Measuring Mission Microwave Imager (TMI) can significantly improve the quality of global analysis. It is shown that assimilating the 6-h averaged TMI rainfall and TPW retrievals improves not only the hydrological cycle, but also key climate parameters such as clouds, radiation, and the large-scale circulation produced by the Goddard Earth Observing System (GEOS) data assimilation system (DAS). Notably, assimilating TMI rain rates improves clouds and radiation in areas of active convection, as well as the latent heating distribution and the large-scale motion field in the Tropics, while assimilating TMI TPW retrievals leads to reduced moisture biases and improved radiative fluxes in clear-sky regions. Assimilating these data also improves the instantaneous wind and temperature fields in the analysis, leading to better short-range forecasts in the Tropics. Ensemble forecasts initialized with analyses incorporating TMI rain rates and TPW yield... [ABSTRACT FROM AUTHOR]

This article describes a variational framework for assimilating the SSM/I-derived surface rain rate and total precipitable water (TPW) and examines their impact on the analysis produced by the Goddard Earth Observing System (GEOS) Data Assimilation System (DAS). The SSM/I observations consist of tropical rain rates retrieved using the Goddard Profiling Algorithm and tropical TPW estimates produced by Wentz. In a series of assimilation experiments for December 1992, results show that the SSM/I-derived rain rate, despite current uncertainty in its intensity, is better than the model-generated precipitation. Assimilating rainfall data improves cloud distributions and the cloudy-sky radiation, while assimilating TPW data reduces a moisture bias in the lower troposphere to improve the clear-sky radiation. Together, the two data types reduce the monthly mean spatial bias by 46% and the error standard deviation by 26% in the outgoing longwave radiation (OLR) averaged over the Tropics, as compared with the NOAA OLR observation product. The improved cloud distribution, in turn, improves the solar radiation at the surface. There is also evidence that the latent heating change associated with the improved precipitation improves the large-scale circulation in the Tropics. This is inferred from a comparison of the clear-sky brightness temperatures for TIROS Operational Vertical Sounder channel 12 computed from the GEOS analyses with the observed values, suggesting that rainfall assimilation reduces a prevailing moist bias in the upper-tropospheric humidity in the GEOS system through enhanced subsidence between the major convective centers. This work shows that assimilation of satellite-derived precipitation and TPW can reduce state-dependent systematic errors in the OLR, clouds, surface radiation, and the large-scale circulation in the assimilated dataset. The improved analysis also leads to better short-range forecasts, but the impact is modest compared with improvements... [ABSTRACT FROM AUTHOR]

Describes three-dimensional numerical simulations of flow through a channel with spatially periodical temperature boundary conditions in the streamwise direction. Occurrence of a supercritical bifurcation to three-dimensional flow before the onset of unsteadiness; Introduction of an incommensurate frequency causing quasiperiodic flow.

Two-dimensional numerical simulations of flow through a channel with spatially periodic temperature boundary conditions at the lower wall have been carried out. A spectral method with a Fourier series expansion in the streamwise direction and a Chebyshev expansion in the vertical direction is employed. A bifurcation to a limit cycle occurs at Reynolds numbers as low as Re=4 and Rayleigh numbers as low as Ra= 14 500. The frequency of oscillation decreases with Re and is essentially independent of Ra. Maps of flow regimes for varying periodicities have been created. Regimes with periodicities longer than the imposed temperature boundary condition have been found. [ABSTRACT FROM AUTHOR]

Summary: This paper investigates the use of two two‐terminal vibration suppression devices in a building and assesses the performance benefits over those achieved using a single device. The inerter‐combined configurations for a multi‐storey building structure are considered. The inerter is a two‐terminal device, with the property that the applied force is proportional to the relative acceleration across its terminals. In this paper, a five‐storey building model with two absorbers of the same kind subjected to base excitation is studied, where one is located between ground and the first floor and the other is between the first and second floors of the building. Three passive suppression layouts, two dampers, two tuned inerter dampers, and two tuned viscous mass dampers are considered. The optimal configurations for minimising the maximum interstorey drifts of the building are obtained with respect to the inerter's size and the damping boundary. The corresponding parameter values are also presented. For the sake of comparison, the single device mounted between the ground and first floor is also considered. Finally, with specific inertance and damping values, the frequency response is provided to show the potential advantage of the proposed optimal configurations. It is demonstrated that the optimal configurations with a pair of devices are more effective than the optimal single device with equal total inertance and the same total damping boundary. The approach demonstrated in this paper is applicable to the investigation of using more than two devices for multistorey buildings. [ABSTRACT FROM AUTHOR]