scholarly journals Formulation and demonstration of an extended-3DVAR multi-scale data assimilation system for the SWOT altimetry era

2021 ◽  
Author(s):  
Zhijin Li ◽  
Matthew Archer ◽  
Jinbo Wang ◽  
Lee-Lueng Fu
Keyword(s):  
High Resolution ◽  
Data Assimilation ◽  
Small Scale ◽  
Time Interval ◽  
California Current System ◽  
Multi Scale ◽  
Resolution Model ◽  
High Resolution Model ◽  
Data Assimilation System ◽  
Assimilation System

Abstract. A state-of-the-art data assimilation system for a high-resolution model has been developed to address the opportunities and challenges posed by the upcoming Surface Water and Ocean Topography (SWOT) satellite mission. A new ‘extended’ three-dimensional variational data assimilation scheme (extended-3DVAR) is formulated to assimilate observations over a time interval, and integrated using a multi-scale approach (hereafter MSDA). The new MSDA scheme specifically enhances the efficacy of the assimilation of satellite along-track altimetry observations, which are limited by large repeat time intervals. This developed system is computationally highly efficient, and thus can be applied to a very high-resolution model. A crucial consideration of the system is first to assimilate routinely available observations, including satellite altimetry, sea surface temperature (SST) and temperature/salinity vertical profiles, to constrain large scales and large mesoscales. High-resolution (dense) observations and future SWOT measurements can then be effectively and seamlessly assimilated to constrain the smaller scales. Using this system, a reanalysis dataset was produced for the SWOT pre-launch field campaign that took place in the California Current System from September through December, 2019. An evaluation of this system with assimilated and withheld data demonstrates its ability to effectively utilize both routine and campaign observations. These results suggest a promising avenue for data assimilation development in the SWOT altimetry era, which will require the capability to efficiently assimilate large-volume datasets resolving small-scale ocean processes.

scholarly journals Multi-platform model assessment in the Western Mediterranean Sea: impact of downscaling on the surface circulation and mesoscale activity

2019 ◽  
Vol 70 (2) ◽  
pp. 273-288 ◽  
Author(s):  
Eva Aguiar ◽  
Baptiste Mourre ◽  
Mélanie Juza ◽  
Emma Reyes ◽  
Jaime Hernández-Lasheras ◽  
...  
Keyword(s):  
High Resolution ◽  
Data Assimilation ◽  
Western Mediterranean ◽  
Small Scale ◽  
Model Assessment ◽  
Mesoscale Structures ◽  
Western Mediterranean Basin ◽  
Surface Circulation ◽  
Resolution Model ◽  
High Resolution Model

AbstractIn numerical ocean modeling, dynamical downscaling is the approach consisting in generating high-resolution regional simulations exploiting the information from coarser resolution models for initial and boundary conditions. Here we evaluate the impacts of downscaling the 1/16o (~ 6–7 km) CMEMS Mediterranean reanalysis model solution into a high-resolution 2-km free-run simulation over the Western Mediterranean basin, focusing on the surface circulation and mesoscale activity. Multi-platform observations from satellite-borne altimeters, high-frequency radar, fixed moorings, and gliders are used for this evaluation, providing insights into the variability from basin to coastal scales. Results show that the downscaling leads to an improvement of the time-averaged surface circulation, especially in the topographically complex area of the Balearic Sea. In particular, the path of the Balearic current is improved in the high-resolution model, also positively affecting transports through the Ibiza Channel. While the high-resolution model produces a similar number of large eddies as CMEMS Med Rea and altimetry, it generates a much larger number of small-scale eddies. Looking into the variability, in the absence of data assimilation, the high-resolution model is not able to properly reproduce the observed phases of mesoscale structures, especially in the southern part of the domain. This negatively affects the representation of the variability of the surface currents interacting with these eddies, highlighting the importance of data assimilation in the high-resolution ocean model in this region to constrain the evolution of these mesoscale structures.

scholarly journals CTDAS-Lagrange v1.0: A high-resolution data assimilation system for regional carbon dioxide observations

2017 ◽  
Author(s):  
Wei He ◽  
Ivar R. van der Velde ◽  
Arlyn E. Andrews ◽  
Colm Sweeney ◽  
John Miller ◽  
...  
Keyword(s):  
High Resolution ◽  
Data Assimilation ◽  
Transport Model ◽  
Lateral Boundary ◽  
Lateral Boundary Conditions ◽  
Sensitivity Tests ◽  
Lagrange System ◽  
Data Assimilation System ◽  
Flux Adjustment ◽  
Assimilation System

Abstract. We have implemented a regional carbon dioxide data assimilation system based on the CarbonTracker Data Assimilation Shell (CTDAS) and a high-resolution Lagrangian transport model, the Stochastic Time-Inverted Lagrangian Transport model driven by the Weather Forecast and Research meteorological fields (WRF-STILT). With this system, named as CTDAS‑Lagrange, we simultaneously optimize terrestrial biosphere fluxes and four parameters that adjust the lateral boundary conditions (BCs) against CO2 observations from the NOAA ESRL North America tall tower and aircraft Programmable Flask Packages (PFPs) sampling program. Least-squares optimization is performed with a time-stepping ensemble Kalman smoother, over a time window of 10 days and assimilating sequentially a time series of observations. Because the WRF-STILT footprints are pre-computed, it is computationally efficient to run the CTDAS-Lagrange system. To estimate the uncertainties of the optimized fluxes from the system, we performed sensitivity tests with various a priori biosphere fluxes (SiBCASA, SiB3, CT2013B) and BCs (optimized mole fraction fields from CT2013B and CTE2014, and an empirical data set derived from aircraft observations), as well as with a variety of choices on the ways that fluxes are adjusted (additive or multiplicative), covariance length scales, biosphere flux covariances, BC parameter uncertainties, and model-data mismatches. In pseudo-data experiments, we show that in our implementation the additive flux adjustment method is more flexible in optimizing NEE than the multiplicative flux adjustment method, and that the CTDAS-Lagrange system has the ability to correct for the potential biases in the lateral boundary conditions and to resolve large biases in the prior biosphere fluxes. Using real observations, we have derived a range of estimates for the optimized carbon fluxes from a series of sensitivity tests, which places the North American carbon sink for the year 2010 in a range from −0.92 to −1.26 PgC/yr. This is comparable to the TM5-based estimates of CarbonTracker (version CT2016, −0.91 ± 1.10 PgC/yr) and CarbonTracker Europe (version CTE2016, −0.91 ± 0.31 PgC/yr). We conclude that CTDAS-Lagrange can offer a versatile and computationally attractive alternative to these global systems for regional estimates of carbon fluxes, which can take advantage of high-resolution Lagrangian footprints that are increasingly easy to obtain.

scholarly journals High-Resolution (2.5 km) Ensemble Precipitation Analysis across Canada

2020 ◽  
Vol 21 (9) ◽  
pp. 2023-2039
Author(s):  
Dikra Khedhaouiria ◽  
Stéphane Bélair ◽  
Vincent Fortin ◽  
Guy Roy ◽  
Franck Lespinas
Keyword(s):  
High Resolution ◽  
Data Assimilation ◽  
Background Field ◽  
Spatiotemporal Resolution ◽  
Stochastic Perturbations ◽  
Multiple Observations ◽  
Uncertainty Estimates ◽  
Precipitation Analysis ◽  
Data Assimilation System ◽  
Assimilation System

AbstractConsistent and continuous fields provided by precipitation analyses are valuable for hydrometeorological applications and land data assimilation modeling, among others. Providing uncertainty estimates is a logical step in the analysis development, and a consistent approach to reach this objective is the production of an ensemble analysis. In the present study, a 6-h High-Resolution Ensemble Precipitation Analysis (HREPA) was developed for the domain covering Canada and the northern part of the contiguous United States. The data assimilation system is the same as the Canadian Precipitation Analysis (CaPA) and is based on optimal interpolation (OI). Precipitation from the Canadian national 2.5-km atmospheric prediction system constitutes the background field of the analysis, while at-site records and radar quantitative precipitation estimates (QPE) compose the observation datasets. By using stochastic perturbations, multiple observations and background field random realizations were generated to subsequently feed the data assimilation system and provide 24 HREPA members plus one control run. Based on one summer and one winter experiment, HREPA capabilities in terms of bias and skill were verified against at-site observations for different climatic regions. The results indicated HREPA’s reliability and skill for almost all types of precipitation events in winter, and for precipitation of medium intensity in summer. For both seasons, HREPA displayed resolution and sharpness. The overall good performance of HREPA and the lack of ensemble precipitation analysis (PA) at such spatiotemporal resolution in the literature motivate further investigations on transitional seasons and more advanced perturbation approaches.

scholarly journals High Resolution Model Intercomparison Project (HighResMIP)

2016 ◽  
Author(s):  
R. J. Haarsma ◽  
M. Roberts ◽  
P. L. Vidale ◽  
C. A. Senior ◽  
A. Bellucci ◽  
...  
Keyword(s):  
High Resolution ◽  
Large Scale ◽  
Computational Cost ◽  
Horizontal Resolution ◽  
Small Scale ◽  
Model Intercomparison ◽  
Resolution Model ◽  
Intercomparison Project ◽  
High Resolution Model ◽  
The Impact

Abstract. Robust projections and predictions of climate variability and change, particularly at regional scales, rely on the driving processes being represented with fidelity in model simulations. The role of enhanced horizontal resolution in improved process representation in all components of the climate system is of growing interest, particularly as some recent simulations suggest the possibility for significant changes in both large-scale aspects of circulation, as well as improvements in small-scale processes and extremes. However, such high resolution global simulations at climate time scales, with resolutions of at least 50 km in the atmosphere and 0.25° in the ocean, have been performed at relatively few research centers and generally without overall coordination, primarily due to their computational cost. Assessing the robustness of the response of simulated climate to model resolution requires a large multi-model ensemble using a coordinated set of experiments. The Coupled Model Intercomparison Project 6 (CMIP6) is the ideal framework within which to conduct such a study, due to the strong link to models being developed for the CMIP DECK experiments and other MIPs. Increases in High Performance Computing (HPC) resources, as well as the revised experimental design for CMIP6, now enables a detailed investigation of the impact of increased resolution up to synoptic weather scales on the simulated mean climate and its variability. The High Resolution Model Intercomparison Project (HighResMIP) presented in this paper applies, for the first time, a multi-model approach to the systematic investigation of the impact of horizontal resolution. A coordinated set of experiments has been designed to assess both a standard and an enhanced horizontal resolution simulation in the atmosphere and ocean. The set of HighResMIP experiments is divided into three tiers consisting of atmosphere-only and coupled runs and spanning the period 1950-2050, with the possibility to extend to 2100, together with some additional targeted experiments. This paper describes the experimental set-up of HighResMIP, the analysis plan, the connection with the other CMIP6 endorsed MIPs, as well as the DECK and CMIP6 historical simulation. HighResMIP thereby focuses on one of the CMIP6 broad questions: “what are the origins and consequences of systematic model biases?”, but we also discuss how it addresses the World Climate Research Program (WCRP) grand challenges.

scholarly journals High Resolution Model Intercomparison Project (HighResMIP v1.0) for CMIP6

2016 ◽  
Vol 9 (11) ◽  
pp. 4185-4208 ◽  
Author(s):  
Reindert J. Haarsma ◽  
Malcolm J. Roberts ◽  
Pier Luigi Vidale ◽  
Catherine A. Senior ◽  
Alessio Bellucci ◽  
...  
Keyword(s):  
High Resolution ◽  
Large Scale ◽  
Computational Cost ◽  
Horizontal Resolution ◽  
Small Scale ◽  
Model Intercomparison ◽  
Resolution Model ◽  
Intercomparison Project ◽  
High Resolution Model ◽  
The Impact

Abstract. Robust projections and predictions of climate variability and change, particularly at regional scales, rely on the driving processes being represented with fidelity in model simulations. The role of enhanced horizontal resolution in improved process representation in all components of the climate system is of growing interest, particularly as some recent simulations suggest both the possibility of significant changes in large-scale aspects of circulation as well as improvements in small-scale processes and extremes. However, such high-resolution global simulations at climate timescales, with resolutions of at least 50 km in the atmosphere and 0.25° in the ocean, have been performed at relatively few research centres and generally without overall coordination, primarily due to their computational cost. Assessing the robustness of the response of simulated climate to model resolution requires a large multi-model ensemble using a coordinated set of experiments. The Coupled Model Intercomparison Project 6 (CMIP6) is the ideal framework within which to conduct such a study, due to the strong link to models being developed for the CMIP DECK experiments and other model intercomparison projects (MIPs). Increases in high-performance computing (HPC) resources, as well as the revised experimental design for CMIP6, now enable a detailed investigation of the impact of increased resolution up to synoptic weather scales on the simulated mean climate and its variability. The High Resolution Model Intercomparison Project (HighResMIP) presented in this paper applies, for the first time, a multi-model approach to the systematic investigation of the impact of horizontal resolution. A coordinated set of experiments has been designed to assess both a standard and an enhanced horizontal-resolution simulation in the atmosphere and ocean. The set of HighResMIP experiments is divided into three tiers consisting of atmosphere-only and coupled runs and spanning the period 1950–2050, with the possibility of extending to 2100, together with some additional targeted experiments. This paper describes the experimental set-up of HighResMIP, the analysis plan, the connection with the other CMIP6 endorsed MIPs, as well as the DECK and CMIP6 historical simulations. HighResMIP thereby focuses on one of the CMIP6 broad questions, “what are the origins and consequences of systematic model biases?”, but we also discuss how it addresses the World Climate Research Program (WCRP) grand challenges.

scholarly journals An update on the 4D-LETKF data assimilation system for the whole neutral atmosphere

2021 ◽  
Author(s):  
Dai Koshin ◽  
Kaoru Sato ◽  
Masashi Kohma ◽  
Shingo Watanabe
Keyword(s):  
Data Assimilation ◽  
Lower Thermosphere ◽  
Mean Field ◽  
Forecast Model ◽  
Small Scale ◽  
Neutral Atmosphere ◽  
Broadband Emission ◽  
Short Period ◽  
Data Assimilation System ◽  
Assimilation System

Abstract. The four-dimensional local ensemble transform Kalman filter (4D-LETKF) data assimilation system for the whole neutral atmosphere is updated to better represent disturbances with wave periods shorter than 1 day in the mesosphere and lower thermosphere (MLT) region. First, incremental analysis update (IAU) filtering is introduced to reduce the generation of spurious waves arising from the insertion of the analysis updates. The IAU is better than other filtering methods, and also is commonly used for the middle atmospheric data assimilation. Second, the horizontal diffusion in the forecast model is modified to reproduce the more realistic tidal amplitudes that were observed by satellites. Third, the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) and Special Sensor Microwave Imager/Sounder (SSMIS) observations in the stratosphere and mesosphere also are assimilated. The performance of the resultant analyses is evaluated by comparing them with the mesospheric winds from meteor radars, which are not assimilated. The representation of assimilation products is greatly improved not only for the zonal mean field but also for short-period and/or horizontally small-scale disturbances.

scholarly journals Objective Center-Finding Algorithm for Tropical Cyclones in Numerical Models

Atmosphere ◽  
2019 ◽  
Vol 10 (7) ◽  
pp. 376 ◽  
Author(s):  
Chengwu Zhao ◽  
Junqiang Song ◽  
Hongze Leng ◽  
Juan Zhao
Keyword(s):  
High Resolution ◽  
Tropical Cyclones ◽  
Numerical Models ◽  
Small Scale ◽  
Two Dimensional ◽  
Model Data ◽  
Centroid Algorithm ◽  
Resolution Model ◽  
High Resolution Model ◽  
Resolution Simulation

Precise center-detection of tropical cyclones (TCs) is critical for dynamic analysis in high resolution model data. The existence of both smaller scale perturbations and larger scale circulations could reduce the accuracy of center positioning. In this study, an objective center-finding algorithm is developed based on a two-dimensional Fourier filter and a vorticity centroid algorithm. This proposed algorithm is able to automatically adjust its parameters according to the scale of the target vortex instead of using artificially prescribed parameters in previous research. What’s more, this new algorithm has been optimized and validated by a hundred idealized vortexes with different sizes and small-scale perturbations. A high-resolution simulation of Typhoon Soudelor (2015) was used to evaluate the performance of the new algorithm, and the proposed objective center-finding algorithm was found able to detect a precise and reliable center.

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