Workshop on the Future of Ionospheric Research for Satellite Navigation, Dec 4-15, 2006, ICTP, Trieste, Italy 1 Ionospheric Parameter Estimation Using.

Slides:

Advertisements

Similar presentations

Modelling complexity in the upper atmosphere using GPS data Chris Budd, Cathryn Mitchell, Paul Spencer Bath Institute for Complex Systems, University of.

Advertisements

Near real time assessment of the Space Weather effect on navigation based on the DGPS technique S.Lejeune, R.Warnant, A. Barré, M. Bavier Royal Observatory.

GPS Theory and applications

URSIGA, New Delhi, Oct 2005 Coordinated Observations of Ionospheric Scintillations, Density Profiles and Total Electron Content on a Common Magnetic.

M. Gende 1,2, C. Brunini 1,2, F. Azpilicueta 1,2 Universidad Nacional de La Plata, Argentina 1 CONICET, Argentina 2 La Plata Ionospheric Model as a tool.

CEDAR Workshop, Boulder CO June 20-25, 2010 Statistical Analysis of COSMIC Derived Abel Profiles Jet Propulsion Laboratory California Institute of Technology.

COSMIC and Space Weather Anthony Mannucci, JPL Brian Wilson, JPL Vardan Akopian, JPL, USC George Hajj, JPL, USC Lukas Mandrake, JPL Xiaoqing Pi, JPL, USC.

Global Navigation Satellite Systems

Space Weather Effects on GPS Thomas J. Bogdan, Director Space Weather Prediction Center NCEP/NWS/NOAA 325 Broadway, DSRC Room 2C109 Boulder, CO 80305,

Space Weather influence on satellite based navigation and precise positioning R. Warnant, S. Lejeune, M. Bavier Royal Observatory of Belgium Avenue Circulaire,

Mesoscale ionospheric tomography over Finland Juha-Pekka Luntama Finnish Meteorological Institute Cathryn Mitchell, Paul Spencer University of Bath 4th.

GTECH 201 Session 08 GPS.

Laser Ranging Contributions to Earth Rotation Studies Richard S. Gross Jet Propulsion Laboratory California Institute of Technology Pasadena, CA 91109–8099,

TEC and its Uncertainty Ludger Scherliess Center for Atmospheric and Space Sciences Utah State University GEM Mini-Workshop San Francisco December 2014.

13/06/13 H. Rho Slide 1 Geodetic Research Laboratory Department of Geodesy and Geomatics Engineering University of New Brunswick Evaluation of Precise.

World Renewable Energy Forum May 15-17, 2012 Dr. James Hall.

SVY 207: Lecture 4 GPS Description and Signal Structure

April 29 – May 2, 20081Space Weather Workshop 2008, Boulder, CO JPL/USC GAIM: Assimilating COSMIC occultations & Sample Applications Jet Propulsion Laboratory.

New Satellite Capabilities and Existing Opportunities Bill Kuo 1 and Chris Velden 2 1 National Center for Atmospheric Research 2 University of Wisconsin.

Use of GPS RO in Operations at NCEP

Part VI Precise Point Positioning Supported by Local Ionospheric Modeling GS894G.

GPS derived TEC Measurements for Plasmaspheric Studies: A Tutorial and Recent Results Mark Moldwin LD Zhang, G. Hajj, I. Harris, T. Mannucci, X. PI.

Part Va Centimeter-Level Instantaneous Long-Range RTK: Methodology, Algorithms and Application GS894G.

Lecturer: Jinglin Wang Student name: Hao Li Student ID:

IRI Workshop 2005 TEC Measurements with Dual-Frequency Space Techniques and Comparisons with IRI T. Hobiger, H. Schuh Advanced Geodesy, Institute of Geodesy.

June, 2003EUMETSAT GRAS SAF 2nd User Workshop. 2 The EPS/METOP Satellite.

Sub-ionospheric Point hmhm Ionosphere Earth Surface Ionospheric Piercing Point High Resolution GPS-TEC Gradients in the Northern Hemisphere Ionospheric.

Geodetic Research Laboratory Department of Geodesy and Geomatics Engineering University of New Brunswick 01/06/27 S.Bisnath A NEW TECHNIQUE FOR GPS-BASED.

Claudinei Rodrigues de Aguiar Federal University of Technology - Parana Paulo de Oliveira Camargo São Paulo State University.

1 J July, Ionospheric Calibration for the GFO AltimeterXiaoqing JPL Review Ionospheric Calibration for the GFO Altimeter Xiaoqing Pi Byron.

P. Wielgosz and A. Krankowski IGS AC Workshop Miami Beach, June 2-6, 2008 University of Warmia and Mazury in Olsztyn, Poland

SI Traceability Applied to GPS RO October 22, 2008 CLARREO Workshop Oct 2008 AJM/JPL 1 SI Traceability Applied To GPS Radio Occultation A. J. Mannucci,

ROSA – ROSSA Validation results R. Notarpietro, G. Perona, M. Cucca

GPS: Everything you wanted to know, but were afraid to ask Andria Bilich National Geodetic Survey.

VTEC prediction using a recursive artificial neural networks approach in Brazil: initial results Engineer School - University of São Paulo Wagner Carrupt.

Ionospheric Integrity Lessons from the WIPP Todd Walter Stanford University Todd Walter Stanford University

Effects of the Magnetosphere and Lower Atmosphere on the Ionosphere-Thermosphere System R.W. Schunk, L. Gardner, L. Scherliess, D.C. Thompson, J.J. Sojka.

VARIABILITY OF TOTAL ELECTRON CONTENT AT EUROPEAN LATITUDES A. Krankowski(1), L. W. Baran(1), W. Kosek (2), I. I. Shagimuratov(3), M. Kalarus (2) (1) Institute.

The Mesoscale Ionospheric Simulation Testbed (MIST) Regional Data Assimilation Model Joseph Comberiate Michael Kelly Ethan Miller June 24, 2013.

Key RO Advances Observation –Lower tropospheric penetration (open loop / demodulation) –Larger number of profiles (rising & setting) –Detailed precision.

1 SVY 207: Lecture 12 Modes of GPS Positioning Aim of this lecture: –To review and compare methods of static positioning, and introduce methods for kinematic.

Preliminary results from assimilation of GPS radio occultation data in WRF using an ensemble filter H. Liu, J. Anderson, B. Kuo, C. Snyder, A. Caya IMAGe.

(c) 2009 California Institute of Technology. Government sponsorship acknowledged. Improving Predictions of the Earth’s Rotation Using Oceanic Angular Momentum.

Assimilating Data Into Ionospheric Models: The Real-Time Revolution Anthony Mannucci, JPL Brian Wilson, JPL George Hajj, JPL, USC Lukas Mandrake, JPL Xiaoqing.

Daily Operation and Validation of a Global Assimilative Ionosphere Model Brian Wilson, JPL George Hajj, JPL, USC Lukas Mandrake, JPL Xiaoqing Pi, JPL,

Principles of the Global Positioning System Lecture 09 Prof. Thomas Herring Room A;

D. A. Galvan1; A. Komjathy1; M. P. Hickey2; A. Mannucci1

1 Satellite geodesy (ge-2112) Processing of observations E. Schrama.

30 Nov 2009Oceans Program Site Review An Update on GPS-Ionosphere Support for NASA’s Earth Observation Satellites Jet Propulsion Laboratory California.

Improving GPS RO Stratospheric Retrieval for Climate Benchmarking Chi O. Ao 1, Anthony J. Mannucci 1, E. Robert Kursinski 2 1 Jet Propulsion Laboratory,

Formosat3/COSMIC Workshop, Taipei, Oct. 1-3, 2008 The Ionosphere as Signal and Noise in Radio Occultation Christian Rocken, Sergey Sokolovskiy, Bill Schreiner,

0 Earth Observation with COSMIC. 1 COSMIC at a Glance l Constellation Observing System for Meteorology Ionosphere and Climate (ROCSAT-3) l 6 Satellites.

National Aeronautics and Space Administration Jet Propulsion Laboratory California Institute of Technology Pasadena, California CLARREO GPS RO/AJM-JPL.

Electron density profile retrieval from RO data Xin’an Yue, Bill Schreiner  Abel inversion error of Ne  Data Assimilation test.

Data Assimilation Retrieval of Electron Density Profiles from Radio Occultation Measurements Xin’an Yue, W. S. Schreiner, Jason Lin, C. Rocken, Y-H. Kuo.

IGARSS 2011, Vancuver, Canada July 28, of 14 Chalmers University of Technology Monitoring Long Term Variability in the Atmospheric Water Vapor Content.

© Copyright QinetiQ limited 2006 On the application of meteorological data assimilation techniques to radio occultation measurements of.

GPS Radio-Occultation data (COSMIC mission) Lidia Cucurull NOAA Joint Center for Satellite Data Assimilation.

AXK/JPL SBAS Training at Stanford University, October 27-30, 2003 Satellite Based Augmentation Systems Brazilian Ionosphere Group Training at Stanford.

Interminimum Changes in Global Total Electron Content and Neutral Mass Density John Emmert, Sarah McDonald Space Science Division, Naval Research Lab Anthony.

Astronomical Institute University of Bern 1 Astronomical Institute, University of Bern, Switzerland * now at PosiTim, Germany 5th International GOCE User.

Global and Regional Total Electron Content Anthony Mannucci, Xing Meng, Panagiotis Vergados, Attila Komjathy JPL/Caltech Collaborators: Sarah E. McDonald,

S. Datta-Barua, Illinois Institute of Technology G. S. Bust, JHUAPL

Center for Atmospheric & Space Sciences

Formosat3 / COSMIC The Ionosphere as Signal and Noise

Formosat3 / COSMIC The Ionosphere as Signal and Noise

GPS Ionospheric Mapping at Natural Resources Canada

Agenda Background and Motivation

Data Assimilation and the GAIM Model at the Air Force Weather Agency

HG contribution to the GRC and more

Presentation transcript:

Workshop on the Future of Ionospheric Research for Satellite Navigation, Dec 4-15, 2006, ICTP, Trieste, Italy 1 Ionospheric Parameter Estimation Using GPS Attila Komjathy, Lawrence Sparks and Anthony J. Mannucci Jet Propulsion Laboratory California Institute of Technology M/S Oak Grove Drive Pasadena CA

Workshop on the Future of Ionospheric Research for Satellite Navigation, Dec 4-15, 2006, ICTP, Trieste, Italy 2 IONOSPHERE ESTIMATION USING GPS Using GPS signals to measure the ionosphere Understand purpose and operation of reference stations Understand how ionospheric corrections are formed Forming ionospheric measurements from GPS observables Data quality and editing Calibration of GPS data This lecture covers: Why?Topics

Workshop on the Future of Ionospheric Research for Satellite Navigation, Dec 4-15, 2006, ICTP, Trieste, Italy 3 Introduction Currently the largest error sources in GPS positioning is that of ionospheric refraction causing signal propagation delays  What can be done? If we have a dual-frequency GPS receiver, then the ionospheric effect can be almost totally accounted for What if we have a single-frequency receiver? –We can ignore the effect and live with the consequences  –We can minimize it using various processing techniques –We can model it using empirical ionospheric models such as the GPS single-frequency Broadcast model, IRI2000 model, PIM, etc. –We can measure it using nearby dual-frequency receiver observations (pseudorange only, carrier-phase only, pseudorange/carrier-phase combined) and apply it as a correction to the single-frequency observations. What is the error in positioning accuracy caused by the ionosphere and how can we reduce it?

Workshop on the Future of Ionospheric Research for Satellite Navigation, Dec 4-15, 2006, ICTP, Trieste, Italy 4 Illustration for GPS and Ionosphere IRI-95 profile

Workshop on the Future of Ionospheric Research for Satellite Navigation, Dec 4-15, 2006, ICTP, Trieste, Italy 5 Broadcast Ionospheric Model

Workshop on the Future of Ionospheric Research for Satellite Navigation, Dec 4-15, 2006, ICTP, Trieste, Italy 6 Broadcast Model: Seasonal Variation

Workshop on the Future of Ionospheric Research for Satellite Navigation, Dec 4-15, 2006, ICTP, Trieste, Italy 7 Broadcast Model: Solar Cycle Dependence

Workshop on the Future of Ionospheric Research for Satellite Navigation, Dec 4-15, 2006, ICTP, Trieste, Italy 8 International Reference Ionosphere

Workshop on the Future of Ionospheric Research for Satellite Navigation, Dec 4-15, 2006, ICTP, Trieste, Italy 9 IRI Model: Seasonal Dependence

Workshop on the Future of Ionospheric Research for Satellite Navigation, Dec 4-15, 2006, ICTP, Trieste, Italy 10 The Accuracy of Broadcast Model

Workshop on the Future of Ionospheric Research for Satellite Navigation, Dec 4-15, 2006, ICTP, Trieste, Italy 11 GPS Observation Equations GPS pseudorange observation equation: GPS carrier phase observation equation: Range, clock, ambiguity, ionosphere, troposphere, satellite bias, receiver bias, multipath, noise

Workshop on the Future of Ionospheric Research for Satellite Navigation, Dec 4-15, 2006, ICTP, Trieste, Italy 12 Generating GPS Ionospheric Observables precise but ambiguous less precise but unambiguous phase-leveled ionospheric observable

Workshop on the Future of Ionospheric Research for Satellite Navigation, Dec 4-15, 2006, ICTP, Trieste, Italy 13 GPS Ionospheric Measurements Code measurement Phase measurement

Workshop on the Future of Ionospheric Research for Satellite Navigation, Dec 4-15, 2006, ICTP, Trieste, Italy 14 Leveling the Phase Using Code Measurements The level is computed as: where E is the elevation angle. The uncertainty on the level is computed in a rather rough way using a combination of  th (E) and observed pseudorange scatter : The level is computed by averaging PI-LI using an elevation-dependent weighting. Higher elevation data is weighted more heavily. (The weighting is based on historical Turborogue PI-LI noise/ multipath data giving a historical PI-LI scatter of  th (E) where E is elevation.) The TEC sigma in the JPL Processed Data files are the level uncertainty.

Workshop on the Future of Ionospheric Research for Satellite Navigation, Dec 4-15, 2006, ICTP, Trieste, Italy 15 Supertruth Data for Three Threads

Workshop on the Future of Ionospheric Research for Satellite Navigation, Dec 4-15, 2006, ICTP, Trieste, Italy 16 The Impact of Arc Lengths

Workshop on the Future of Ionospheric Research for Satellite Navigation, Dec 4-15, 2006, ICTP, Trieste, Italy 17 Major Error Source: The Code Multipath

Workshop on the Future of Ionospheric Research for Satellite Navigation, Dec 4-15, 2006, ICTP, Trieste, Italy 18 Global Ionospheric Mapping: GIM is the slant TEC; is the thin shell mapping function for shell 1, etc; is the horizontal basis function (C 2, TRIN, etc); are the basis function coefficients solved for in the filter, indexed by horizontal (i) and vertical (1,2,3 for three shells) indices; are the satellite and receiver instrumental biases. For three shells, our model is where For single shell, our model is

Workshop on the Future of Ionospheric Research for Satellite Navigation, Dec 4-15, 2006, ICTP, Trieste, Italy 19 WAAS Ionospheric Models WAAS planar fit ionospheric model is Pseudo-IGP approach: IPP treated as if it were collocated with IGP are the planar fit parameters, are the distances from the IGP to the IPP in the eastern and northern directions, respectively. are the additional planar fit parameters describing quadratic and cross terms. WAAS-type quadratic fit ionospheric model is where

Workshop on the Future of Ionospheric Research for Satellite Navigation, Dec 4-15, 2006, ICTP, Trieste, Italy 20 All-Site GPS Data Processing Algorithm Bias Fixing Algorithm using all available GPS stations worldwide: is the biased phase-levelled ionospheric observable is the thin shell mapping function for shell 1, etc; is the horizontal basis function (C 2, TRIN, etc); are the satellite and receiver instrumental biases. GIM TEC prediction GIM satellite bias estimate Biased TEC observation are the basis function coefficients solved for in the filter, indexed by horizontal (i) and vertical (1,2,3 for three shells) indices;

Workshop on the Future of Ionospheric Research for Satellite Navigation, Dec 4-15, 2006, ICTP, Trieste, Italy 21 Single Vs. Three-Shell Model Limitations The concept of multi-shell GIM:Single-shell 2-D maps Does not capture small-scale variations in the ionosphere Multi-shell is more realistic and accurate than the single-shell approximation

Workshop on the Future of Ionospheric Research for Satellite Navigation, Dec 4-15, 2006, ICTP, Trieste, Italy 22 Receiver Bias Estimation Precision

Workshop on the Future of Ionospheric Research for Satellite Navigation, Dec 4-15, 2006, ICTP, Trieste, Italy 23 Slant TEC Bias-Fixing Method Estimated bias time series: errors caused by GIM, multipath, noise, sub-daily bias drift Bias-removed slant TEC Location of station

Workshop on the Future of Ionospheric Research for Satellite Navigation, Dec 4-15, 2006, ICTP, Trieste, Italy 24 Coverage of Daily IGS Network and Regional Networks (10 degree elevation mask; 450 km shell height)

Workshop on the Future of Ionospheric Research for Satellite Navigation, Dec 4-15, 2006, ICTP, Trieste, Italy 25 An Example of the Diurnal Variation of TEC for a Geomagnetically Quiet Day Components in TECU, TECU/hour, TECU/km Example for Single Shell Model Results

Workshop on the Future of Ionospheric Research for Satellite Navigation, Dec 4-15, 2006, ICTP, Trieste, Italy 26 JPL’s GIM Multi-Shell Model

Workshop on the Future of Ionospheric Research for Satellite Navigation, Dec 4-15, 2006, ICTP, Trieste, Italy 27 TOPEX Validation for 12 Oct 2001, Track 10

Workshop on the Future of Ionospheric Research for Satellite Navigation, Dec 4-15, 2006, ICTP, Trieste, Italy 28 Recent GIM Validation Using Jason-1

Workshop on the Future of Ionospheric Research for Satellite Navigation, Dec 4-15, 2006, ICTP, Trieste, Italy 29 Global Point Plots

Workshop on the Future of Ionospheric Research for Satellite Navigation, Dec 4-15, 2006, ICTP, Trieste, Italy 30 Point Plot Differences

Workshop on the Future of Ionospheric Research for Satellite Navigation, Dec 4-15, 2006, ICTP, Trieste, Italy 31 October 30, 2003 DST -390 nT at 2315 UT on October 30 2nd Interplanetary Coronal Mass Ejection

Workshop on the Future of Ionospheric Research for Satellite Navigation, Dec 4-15, 2006, ICTP, Trieste, Italy 32 November 20, 2003 Storm Details are difficult to interpret Quiet ionosphere following the storm 5-day average of quiet ionosphere removed: structures are easier to detect

Workshop on the Future of Ionospheric Research for Satellite Navigation, Dec 4-15, 2006, ICTP, Trieste, Italy 33 An Example for Repeatibility of Estimated Satellite Biases: Multi-Shell versus Single-Shell Multi-shell significantly improves repeatibility in daily bias estimates –We compare bias averages over 7–10 days –Scatter (std. dev.) over a week improved by factor of 2 to 4 Satellite biases –7-day scatter improved from 2–6 cm to 8–24 mm This may indicate reduction of systematic errors in bias estimation 6 cm 0 cm

Workshop on the Future of Ionospheric Research for Satellite Navigation, Dec 4-15, 2006, ICTP, Trieste, Italy 34 An Example for Repeatibility in Estimated Receiver Biases:Multi-Shell versus Single-Shell 0.6 m 0 m Receiver biases 7-day scatter improved from 8–64 cm to 0.5–19 cm Larger scatter due to stations in low latitude sector Systematic error? Examine long time-series of biases Look for shifts in ionospheric delay level for all biases simultaneously

Workshop on the Future of Ionospheric Research for Satellite Navigation, Dec 4-15, 2006, ICTP, Trieste, Italy 35 Comparison of Single and Multi-Shell Results for ENG1 Postfit Residuals Prediction Residuals ENG1 = English Turn, LA Improvement at low elevation angles

Workshop on the Future of Ionospheric Research for Satellite Navigation, Dec 4-15, 2006, ICTP, Trieste, Italy 36 Comparison of Single and Multi-Shell Results for MBWW Postfit Residuals Prediction Residuals MBWW = Medicine Bow, WY Improvement at low elevation angles

Workshop on the Future of Ionospheric Research for Satellite Navigation, Dec 4-15, 2006, ICTP, Trieste, Italy 37

Workshop on the Future of Ionospheric Research for Satellite Navigation, Dec 4-15, 2006, ICTP, Trieste, Italy 38 Six-satellite COSMIC constellation Launched April 14, 2006 Low-Earth Orbiter GPS Electron Density Profile COSMIC coverage: 2500 profiles/day COSMIC Ionospheric Weather Constellation

Workshop on the Future of Ionospheric Research for Satellite Navigation, Dec 4-15, 2006, ICTP, Trieste, Italy 39

Workshop on the Future of Ionospheric Research for Satellite Navigation, Dec 4-15, 2006, ICTP, Trieste, Italy 40 Global Assimilative Ionospheric Model Data Assimilation Process Driving Forces Driving Forces Mapping State To Measurements Mapping State To Measurements Physics Model Physics Model Kalman Filter State and covariance Forecast State and covariance Analysis Adjustment Of Parameters 4DVAR Innovation Vector Kalman Filter –Recursive Filtering –Covariance estimation and state correction Optimal interpolation Band-Limited Kalman filter 4-Dimensional Variational Approach –Minimization of cost function by estimating driving parameters –Non-linear least-square minimization –Adjoint method to efficiently compute the gradient of cost function –Parameterization of model “drivers”

Workshop on the Future of Ionospheric Research for Satellite Navigation, Dec 4-15, 2006, ICTP, Trieste, Italy 41 Input Data Types Ground GPS Data (Absolute TEC) >200 5-min. to Hourly Global GPS Ground Stations Assimilate >300,000 TEC points per day 5 min rate) per day Space GPS Data (Absolute or Relative TEC) CHAMP 440 km) SAC-C 700 km) IOX 800 km) GRACE 350 km) Topex/Poseidon km) (Upward looking only) Jason 1 km) (Upward looking only) C/NOFS & COSMIC constellation UV airglow data (135.6 nm radiance) LORAAS on ARGOS, GUVI on TIMED SSUSI/SSULI on DMSP TIP on COSMIC Other Data Types TEC from TOPEX/JASON Altimeters Ionosonde bottomside profiles DMSP in situ CHAMP in situ GRACE cross-links

Workshop on the Future of Ionospheric Research for Satellite Navigation, Dec 4-15, 2006, ICTP, Trieste, Italy 42 Kalman Assimilation Runs for June 26, 2006 Three runs: GAIM Climate (no data) Ground GPS TEC (200 sites) Ground + COSMIC links (upward & occultation) Resolution:2.5 deg. Lat. 10 deg. Lon. 40 km Alt. No. of grid cells: 100,000 Sparse Kalman filter: Update & propagate covariance Truncate off-diagonal covariance that is beyond physical correlation lengths

Workshop on the Future of Ionospheric Research for Satellite Navigation, Dec 4-15, 2006, ICTP, Trieste, Italy 43 GAIM Assimilation Using Ground and COSMIC Data

Workshop on the Future of Ionospheric Research for Satellite Navigation, Dec 4-15, 2006, ICTP, Trieste, Italy 44 GAIM Validation Using Jason-2 Vertical TEC Ground-data only Ground and space data

Workshop on the Future of Ionospheric Research for Satellite Navigation, Dec 4-15, 2006, ICTP, Trieste, Italy 45 GAIM vs. Abel HmF2 Comparison

Workshop on the Future of Ionospheric Research for Satellite Navigation, Dec 4-15, 2006, ICTP, Trieste, Italy 46 GAIM Driven By Ground GPS Only versus JASON VTEC June – Nov. 2004: 137 days

Workshop on the Future of Ionospheric Research for Satellite Navigation, Dec 4-15, 2006, ICTP, Trieste, Italy 47 COSMIC Demo 2007 COSMIC data: 120+ minutes latency CDAAC: COSMIC Data Analysis and Archiving Center at UCAR Start of orbit End of orbit; data downloaded Data received at CDAAC Limb TEC available Profiles (Abel) available GAIM 3-D global electron density grids 15-minute cadence Global ground network data: 5-minute and 1-hour latency

Workshop on the Future of Ionospheric Research for Satellite Navigation, Dec 4-15, 2006, ICTP, Trieste, Italy 48 What You Have Learned 1.Ionosphere is the largest error source in GPS positioning 2.Empirical models can be used to mitigate effects 3.Dual-frequency GPS data can be used to solve for the ionospheric effect 4.Error sources affecting GPS-based ionospheric estimation: arc length,leveling, biases, multipath, noise, etc. 5.Global Ionospheric Mapping techniques: single vs multi- shell approaches: ionospheric delay and biases estimation 6.Validation of maps, point plots, movies, etc.