The Impact of the Initial Guess on the Accuracy of Satellite Retrievals

1993 ◽  
pp. 113-130 ◽  
Author(s):  
Larry M. McMillin ◽  
Michael J. Uddstrom
Keyword(s):  
Initial Guess ◽  
Satellite Retrievals ◽  
The Impact

scholarly journals A Hybrid Energy System Workflow for Energy Portfolio Optimization

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4392
Author(s):  
Jia Zhou ◽  
Hany Abdel-Khalik ◽  
Paul Talbot ◽  
Cristian Rabiti
Keyword(s):  
Time Series ◽  
Gaussian Process ◽  
Electricity Market ◽  
Process Model ◽  
Net Present Value ◽  
Historical Data ◽  
Energy System ◽  
Initial Guess ◽  
Reduced Order ◽  
The Impact

This manuscript develops a workflow, driven by data analytics algorithms, to support the optimization of the economic performance of an Integrated Energy System. The goal is to determine the optimum mix of capacities from a set of different energy producers (e.g., nuclear, gas, wind and solar). A stochastic-based optimizer is employed, based on Gaussian Process Modeling, which requires numerous samples for its training. Each sample represents a time series describing the demand, load, or other operational and economic profiles for various types of energy producers. These samples are synthetically generated using a reduced order modeling algorithm that reads a limited set of historical data, such as demand and load data from past years. Numerous data analysis methods are employed to construct the reduced order models, including, for example, the Auto Regressive Moving Average, Fourier series decomposition, and the peak detection algorithm. All these algorithms are designed to detrend the data and extract features that can be employed to generate synthetic time histories that preserve the statistical properties of the original limited historical data. The optimization cost function is based on an economic model that assesses the effective cost of energy based on two figures of merit: the specific cash flow stream for each energy producer and the total Net Present Value. An initial guess for the optimal capacities is obtained using the screening curve method. The results of the Gaussian Process model-based optimization are assessed using an exhaustive Monte Carlo search, with the results indicating reasonable optimization results. The workflow has been implemented inside the Idaho National Laboratory’s Risk Analysis and Virtual Environment (RAVEN) framework. The main contribution of this study addresses several challenges in the current optimization methods of the energy portfolios in IES: First, the feasibility of generating the synthetic time series of the periodic peak data; Second, the computational burden of the conventional stochastic optimization of the energy portfolio, associated with the need for repeated executions of system models; Third, the inadequacies of previous studies in terms of the comparisons of the impact of the economic parameters. The proposed workflow can provide a scientifically defendable strategy to support decision-making in the electricity market and to help energy distributors develop a better understanding of the performance of integrated energy systems.

scholarly journals The impact of improved satellite retrievals on estimates of biospheric carbon balance

2020 ◽  
Vol 20 (1) ◽  
pp. 323-331 ◽  
Author(s):  
Scot M. Miller ◽  
Anna M. Michalak
Keyword(s):  
Carbon Balance ◽  
Near Infrared ◽  
Co2 Flux ◽  
Retrieval Algorithm ◽  
Co2 Uptake ◽  
Near Infrared Radiation ◽  
Sources And Sinks ◽  
Satellite Retrievals ◽  
The Impact ◽  
Insight Into

Abstract. The Orbiting Carbon Observatory 2 (OCO-2) is NASA's first satellite dedicated to monitoring CO2 from space and could provide novel insight into CO2 fluxes across the globe. However, one continuing challenge is the development of a robust retrieval algorithm: an estimate of atmospheric CO2 from satellite observations of near-infrared radiation. The OCO-2 retrievals have undergone multiple updates since the satellite's launch, and the retrieval algorithm is now on its ninth version. Some of these retrieval updates, particularly version 8, led to marked changes in the CO2 observations, changes of 0.5 ppm or more. In this study, we evaluate the extent to which current OCO-2 observations can constrain monthly CO2 sources and sinks from the biosphere, and we particularly focus on how this constraint has evolved with improvements to the OCO-2 retrieval algorithm. We find that improvements in the CO2 retrieval are having a potentially transformative effect on satellite-based estimates of the global biospheric carbon balance. The version 7 OCO-2 retrievals formed the basis of early inverse modeling studies using OCO-2 data; these observations are best equipped to constrain the biospheric carbon balance across only continental or hemispheric regions. By contrast, newer versions of the retrieval algorithm yield a far more detailed constraint, and we are able to constrain CO2 budgets for seven global biome-based regions, particularly during the Northern Hemisphere summer when biospheric CO2 uptake is greatest. Improvements to the OCO-2 observations have had the largest impact on glint-mode observations, and we also find the largest improvements in the terrestrial CO2 flux constraint when we include both nadir and glint data.

scholarly journals The impact of MISR-derived injection height initialization on wildfire and volcanic plume dispersion in the HYSPLIT model

2018 ◽  
Vol 11 (11) ◽  
pp. 6289-6307 ◽  
Author(s):  
Charles J. Vernon ◽  
Ryan Bolt ◽  
Timothy Canty ◽  
Ralph A. Kahn
Keyword(s):  
Volcanic Eruptions ◽  
Dust Storms ◽  
Volcanic Plume ◽  
Plume Dispersion ◽  
Hysplit Model ◽  
Particle Injection ◽  
Nominal Model ◽  
Satellite Retrievals ◽  
Aerosol Sources ◽  
The Impact

Abstract. The dispersion of particles from wildfires, volcanic eruptions, dust storms, and other aerosol sources can affect many environmental factors downwind, including air quality. Aerosol injection height is one source attribute that mediates downwind dispersion, as wind speed and direction can vary dramatically with elevation. Using plume heights derived from space-based, multi-angle imaging, we examine the impact of initializing plumes in the NOAA Air Resources Laboratory's Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model with satellite-measured vs. nominal (model-calculated or VAAC-reported) injection height on the simulated dispersion of six large aerosol plumes. When there are significant differences in nominal vs. satellite-derived particle injection heights, especially if both heights are in the free troposphere or if one injection height is within the planetary boundary layer (PBL) and the other is above the PBL, differences in simulation results can arise. In the cases studied with significant nominal vs. satellite-derived injection height differences, the HYSPLIT model can represent plume evolution better, relative to independent satellite observations, if the injection height in the model is constrained by hyper-stereo satellite retrievals.

scholarly journals Gradients of column CO<sub>2</sub> across North America from the NOAA Global Greenhouse Gas Reference Network

2017 ◽  
Vol 17 (24) ◽  
pp. 15151-15165 ◽  
Author(s):  
Xin Lan ◽  
Pieter Tans ◽  
Colm Sweeney ◽  
Arlyn Andrews ◽  
Andrew Jacobson ◽  
...  
Keyword(s):  
North America ◽  
Greenhouse Gas ◽  
Spatial Patterns ◽  
Reference Network ◽  
Spatial Gradients ◽  
Continental Scale ◽  
Satellite Retrievals ◽  
The Impact ◽  
Total Column

Abstract. This study analyzes seasonal and spatial patterns of column carbon dioxide (CO2) over North America, calculated from aircraft and tall tower measurements from the NOAA Global Greenhouse Gas Reference Network from 2004 to 2014. Consistent with expectations, gradients between the eight regions studied are larger below 2 km than above 5 km. The 11-year mean CO2 dry mole fraction (XCO2) in the column below  ∼  330 hPa ( ∼  8 km above sea level) from NOAA's CO2 data assimilation model, CarbonTracker (CT2015), demonstrates good agreement with those calculated from calibrated measurements on aircraft and towers. Total column XCO2 was attained by combining modeled CO2 above 330 hPa from CT2015 with the measurements. We find large spatial gradients of total column XCO2 from June to August, with north and northeast regions having  ∼  3 ppm stronger summer drawdown (peak-to-valley amplitude in seasonal cycle) than the south and southwest regions. The long-term averaged spatial gradients of total column XCO2 across North America show a smooth pattern that mainly reflects the large-scale circulation. We have conducted a CarbonTracker experiment to investigate the impact of Eurasian long-range transport. The result suggests that the large summertime Eurasian boreal flux contributes about half of the north–south column XCO2 gradient across North America. Our results confirm that continental-scale total column XCO2 gradients simulated by CarbonTracker are realistic and can be used to evaluate the credibility of some spatial patterns from satellite retrievals, such as the long-term average of growing-season spatial patterns from satellite retrievals reported for Europe which show a larger spatial difference ( ∼  6 ppm) and scattered hot spots.

Towards high-towards high-resolution dust reanalysis for Northern Africa, the Middle East and Europe

2020 ◽  
Author(s):  
Enza Di Tomaso ◽  
Sara Basart ◽  
Jeronimo Escribano ◽  
Paul Ginoux ◽  
Oriol Jorba ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Middle East ◽  
Data Assimilation ◽  
Dust Storms ◽  
Northern Africa ◽  
Combine Model ◽  
Climate Services ◽  
Deep Blue ◽  
Satellite Retrievals ◽  
The Impact

&lt;p&gt;DustClim (Dust Storms Assessment for the development of user-oriented Climate Services in Northern Africa, Middle East and Europe) is a project of the European Research Area For Climate Services (ERA4CS). DustClim is aiming to provide reliable information on sand and dust storms for developing dust-related services for selected socio-economic sectors: air quality, aviation and solar energy.&lt;/p&gt;&lt;p&gt;This contribution will describe the work done within the DustClim project towards the production of a dust reanalysis over the domain of Northern Africa, the Middle East and Europe at an unprecedented high spatial resolution (at 10km x 10km) using the state-of-art Multiscale Online Nonhydrostatic Atmosphere Chemistry model (MONARCH) and its data assimilation capability (Di Tomaso et al., 2017). An ensemble-based Kalman filter (namely the local ensemble transform Kalman filter &amp;#8211; LETKF) has been utilized to optimally combine model simulations and satellite retrievals.&lt;/p&gt;&lt;p&gt;Dust ensemble forecasts are used to estimate flow-dependent forecast uncertainty, which is used by the data assimilation scheme to optimally combine model prior information with satellite retrievals. Satellite observations from MODIS Deep Blue with specific observational constraint for dust (Ginoux et al., 2012; Pu and Ginoux, 2016; Sayer et al., 2014) are considered for assimilation over land surfaces, including source regions. MONARCH ensemble has been generated by applying multi-parameters, multi-physics, multi-meteorological initial and boundary conditions perturbations. Sensitive parameters of the assimilation configuration like the balance between observational and background uncertainty, or the spatial location of errors have been carefully calibrated.&lt;/p&gt;&lt;p&gt;The dust reanalysis for the period 2011-2016 is being compared against independent dust-filtered observations from AERONET (AErosol RObotic NETwork) show the benefit of the assimilation of dust-related MODIS Deep Blue products over areas not easily covered by other observational datasets. Particularly relevant is the improvement of the model skills over the Sahara.&lt;/p&gt;&lt;p&gt;References:&lt;br&gt;Di Tomaso, E., Schutgens, N. A. J., Jorba, O., and P&amp;#233;rez Garc&amp;#237;a-Pando, C. (2017): Assimilation of MODIS Dark Target and Deep Blue observations in the dust aerosol component of NMMB-MONARCH version 1.0, Geosci. Model Dev., 10, 1107-1129, doi:10.5194/gmd-10-1107-2017.&lt;br&gt;Ginoux, P., Prospero, J. M., Gill, T. E., Hsu, N. C. and Zhao, M. Global-Scale Attribution of Anthropogenic and Natural Dust Sources and Their Emission Rates Based on Modis Deep Blue Aerosol Products. Rev Geophys 50, doi:10.1029/2012rg000388 (2012).&lt;br&gt;Pu, B., and Ginoux, P. (2016). The impact of the Pacific Decadal Oscillation on springtime dust activity in Syria. Atmospheric Chemistry and Physics, 16(21), 13431-13448.&lt;br&gt;Sayer, A. M., Munchak, L. A., Hsu, N. C., Levy, R. C., Bettenhausen, C., and Jeong, M.-J.: MODIS Collection 6 aerosol products: Comparison between Aqua&amp;#8217;s e-Deep Blue, Dark Target, and &amp;#8220;merged&amp;#8221; data sets, and usage recommendations, J. Geophys. Res.-Atmos., 119, 13965&amp;#8211;13989, doi:10.1002/2014JD022453, 2014.&lt;/p&gt;&lt;p&gt;Acknowledgement&lt;br&gt;DustClim project is part of ERA4CS, an ERA-NET initiated by JPI Climate, and funded by FORMAS (SE), DLR (DE), BMWFW (AT), IFD (DK), MINECO (ES), ANR (FR) with co-funding by the European Union (Grant 690462). We acknowledge PRACE for awarding access to HPC resources through the eDUST and eFRAGMENT1 projects.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;

scholarly journals The Impact of New Water Vapor Spectroscopy on Satellite Retrievals

2003 ◽  
pp. 259-272 ◽  
Author(s):  
A. N. Maurellis ◽  
R. Lang ◽  
J. E. Williams ◽  
Wim J. Zande ◽  
Kevin Smith ◽  
...  
Keyword(s):  
Water Vapor ◽  
Satellite Retrievals ◽  
Water Vapor Spectroscopy ◽  
The Impact

Application of the Harmonic Balance Method to Ground Moling Machines Operating in Periodic Regimes

2001 ◽  
Author(s):  
Ko-Choong Woo ◽  
Albert A. Rodger ◽  
Richard D. Neilson ◽  
Marian Wiercigroch
Keyword(s):  
Harmonic Balance ◽  
Harmonic Balance Method ◽  
Structural Complexity ◽  
Initial Guess ◽  
Balance Method ◽  
Operational Parameters ◽  
Impact Oscillator ◽  
Time Harmonic ◽  
Wide Range ◽  
The Impact

Abstract The paper describes current research into mathematical modelling of a novel vibro-impact ground moling system. Experimental and theoretical studies suggest periodic responses are required to achieve the optimal penetrating conditions for the ground moling process, as this results in reduced soil penetration resistance. Therefore, there is a practical need for a robust and efficient methodology to calculate periodic responses for a wide range of operational parameters. Due to the structural complexity of a real vibro-impact moling system, the dynamic response of an idealised impact oscillator has been investigated in the first instance. This paper presents a detailed study of periodic responses of the impact oscillator under harmonic forcing using alternating frequency-time harmonic balance method. Recommendations of how to effectively adapt the alternating frequency-time harmonic balance method for a stiff impacting system are given. The periodic motion is represented algebraically by a truncated Fourier series and the systematic methodology employed allows for convergence. The idea central to this procedure is that the linear oscillator is explicitly solvable analytically, and this allows for the initial set of Fourier coefficients. The clearance value is then adjusted so that contact with the secondary stiffness is slight and the nonlinearity is weak. The solution to this subsequent system is obtainable as the initial guess is close to the required solution.

scholarly journals Quantifying the Impact of Solar Spectra on the Inter-Calibration of Satellite Instruments

2021 ◽  
Vol 13 (8) ◽  
pp. 1438
Author(s):  
Rajendra Bhatt ◽  
David R. Doelling ◽  
Odele Coddington ◽  
Benjamin Scarino ◽  
Arun Gopalan ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Reference Spectrum ◽  
Absolute Accuracy ◽  
Common Reference ◽  
The Past ◽  
Sensing Applications ◽  
Satellite Retrievals ◽  
Remote Sensing Applications ◽  
Spectral Solar Irradiance ◽  
The Impact

In satellite-based remote sensing applications, the conversion of the sensor recorded top-of-atmosphere reflectance to radiance, or vice-versa, is carried out using a reference spectral solar irradiance (SSI) dataset. The choice of reference SSI spectrum has consistently changed over the past four decades with the increasing availability of more accurate SSI measurements with greater spectral coverage. Considerable differences (up to 15% at certain wavelengths) exist between the numerous SSI spectra that are currently being used in satellite ground processing systems. The aim of this study is to quantify the absolute differences between the most commonly used SSI datasets and investigate their impact in satellite inter-calibration and environmental retrievals. It was noted that if analogous SNPP and NOAA-20 VIIRS channel reflectances were perfectly inter-calibrated, the derived channel radiances can still differ by up to 3% due to the utilization of differing SSI datasets by the two VIIRS instruments. This paper also highlights a TSIS-1 SIM-based Hybrid Solar Reference Spectrum (HSRS) with an unprecedented absolute accuracy of 0.3% between 460 and 2365 nm, and recommends that the remote sensing community use it as a common reference SSI in satellite retrievals.

scholarly journals Some implications of sampling choices on comparisons between satellite and model aerosol optical depth fields

2010 ◽  
Vol 10 (7) ◽  
pp. 17789-17814
Author(s):  
A. M. Sayer ◽  
G. E. Thomas ◽  
P. I. Palmer ◽  
R. G. Grainger
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Transport Model ◽  
Grid Cell ◽  
Point Sources ◽  
Clear Sky ◽  
Model Aerosol ◽  
Satellite Retrievals ◽  
Along Track ◽  
The Impact

Abstract. The comparison of satellite and model aerosol optical depth (AOD) fields provides useful information on the strengths and weaknesses of both. However, the sampling of satellite and models is very different and some subjective decisions about data selection and aggregation must be made in order to perform such comparisons. This work examines some implications of these decisions, using GlobAerosol AOD retrievals at 550 nm from Advanced Along-Track Scanning Radiometer (AATSR) measurements, and aerosol fields from the GEOS-Chem chemistry transport model. It is recommended to sample the model only where the satellite flies over on a particular day; neglecting this can cause regional differences in model AOD of up to 0.1 on monthly and annual timescales. The comparison is observed to depend strongly upon thresholds for sparsity of satellite retrievals in the model grid cells. Requiring at least 25% coverage of the model grid cell by satellite data decreases the observed difference between the two by approximately half over land. The impact over ocean is smaller. In both model and satellite datasets, there is an anticorrelation between the proportion p of a model grid cell covered by satellite retrievals and the AOD. This is attributed to small p typically occuring due to high cloud cover and lower AODs being found in large clear-sky regions. Daily median AATSR AODs were found to be closer to GEOS-Chem AODs than daily means (with the root mean squared difference being approximately 0.05 smaller). This is due to the decreased sensitivity of medians to outliers such as cloud-contaminated retrievals, or aerosol point sources not included in the model.

scholarly journals Representativeness errors in comparing chemistry transport and chemistry climate models with satellite UV/Vis tropospheric column retrievals

2015 ◽  
Vol 8 (9) ◽  
pp. 7821-7877 ◽  
Author(s):  
K. F. Boersma ◽  
G. C. M. Vinken ◽  
H. J. Eskes
Keyword(s):  
Measurement Errors ◽  
Cloud Cover ◽  
Climate Models ◽  
Transport Model ◽  
Atmospheric Composition ◽  
Satellite Measurements ◽  
Temporal Sampling ◽  
Satellite Retrievals ◽  
Tropospheric No2 ◽  
The Impact

Abstract. UV/Vis satellite retrievals of trace gas columns of nitrogen dioxide (NO2), sulphur dioxide (SO2), and formaldehyde (HCHO) are useful to test and improve models of atmospheric composition, for data assimilation, air quality hindcasting and forecasting, and to provide top-down constraints on emissions. However, because models and satellite measurements do not represent the exact same geophysical quantities, the process of confronting model fields with satellite measurements is complicated by representativeness errors, which degrade the quality of the comparison beyond contributions from modelling and measurement errors alone. Here we discuss three types of representativeness errors that arise from the act of carrying out a model-satellite comparison: (1) horizontal representativeness errors due to imperfect collocation of the model grid cell and an ensemble of satellite pixels called superobservation, (2) temporal representativeness errors originating mostly from differences in cloud cover between the modelled and observed state, and (3) vertical representativeness errors because of reduced satellite sensitivity towards the surface accompanied with necessary retrieval assumptions on the state of the atmosphere. To minimize the impact of these representativeness errors, we recommend that models and satellite measurements be sampled as consistently as possible, and our paper provides a number of recipes to do so. A practical confrontation of tropospheric NO2 columns simulated by the TM5 chemistry transport model (CTM) with Ozone Monitoring Instrument (OMI) tropospheric NO2 retrievals suggests that horizontal representativeness errors, while unavoidable, are limited to within 5–10 % in most cases and of random nature. These errors should be included along with the individual retrieval errors in the overall superobservation error. Temporal sampling errors from mismatches in cloud cover, and, consequently, in photolysis rates, are on the order of 10 % for NO2 and HCHO, and systematic, but partly avoidable. In the case of air pollution applications where sensitivity down to the ground is required, we recommend that models should be sampled on the same mostly cloud-free days as the satellite retrievals. The most relevant representativeness error is associated with the vertical sensitivity of Ultraviolet-visible (UV/Vis) satellite retrievals. Simple vertical integration of modelled profiles leads to systematically different model columns compared to application of the appropriate averaging kernel. In comparing OMI NO2 to GEOS-Chem NO2 simulations, these systematic differences are as large as 15–20 % in summer, but, again, avoidable.

Sign in / Sign up

Export Citation Format

Share Document