Ensemble-Guided Tropical Cyclone Track Forecasting for Optimal Satellite Remote Sensing

Within the realm of satellite remote sensing, optimal data acquisition to study natural phenomena under time, resource, and cost constraints is a well-known problem. Furthermore, since the sensors themselves are at remote locations with sparse ground connectivity, the optimal method must use a computationally light forecasting algorithm, which assimilates information from the observations at possibly irregular intervals, in near real time. In this article, we propose and demonstrate the ensemble -guided cyclone track forecasting (EGCTF) method for application in remote tropical cyclone tracking. The algorithm uses ensemble data produced by numerical weather prediction models to guide the forecasting process while assimilating measured cyclone center positions. The algorithm was tested and analyzed with the Global Ensemble Forecasting System (GEFS) data and the National Hurricane Center data for the 2018 year hurricanes within the Atlantic basin. Compared with a baseline method that uses the GEFS-issued mean ensemble track (AEMN) for forecasting and no data assimilation, the proposed algorithm exhibited positive forecast skill for more than 290 test cases over forecast periods spanning 6-48 h. The skill is seen to improve with lengthening forecast periods, with five test cases showing greater than 75% skill for a forecast period of 6 h to 247 test cases for the forecast period of 48 h.

[1]  Jorge Nocedal,et al.  Algorithm 778: L-BFGS-B: Fortran subroutines for large-scale bound-constrained optimization , 1997, TOMS.

[2]  Donghyun You,et al.  Prediction of a typhoon track using a generative adversarial network and satellite images , 2019, Scientific Reports.

[3]  Simone Tanelli,et al.  RainCube, the First Spaceborne Precipitation Radar in a 6U CubeSat , 2019 .

[4]  Marc Sanchez Net,et al.  Autonomous Scheduling of Agile Spacecraft Constellations with Delay Tolerant Networking for Reactive Imaging , 2020, ArXiv.

[5]  Yuejian Zhu,et al.  Performance of the New NCEP Global Ensemble Forecast System in a Parallel Experiment , 2017 .

[6]  Rita Kovordanyi,et al.  Tropical cyclone track forecasting techniques ― A review , 2012 .

[7]  Christopher S. Velden,et al.  Objectively Determining the Rotational Center of Tropical Cyclones in Passive Microwave Satellite Imagery , 2010 .

[8]  Steve Chien,et al.  Flood detection and monitoring with the Autonomous Sciencecraft Experiment onboard EO-1 , 2006 .

[9]  Georgi T. Georgiev,et al.  Multispectral Snapshot Imagers Onboard Small Satellite Formations for Multi-Angular Remote Sensing , 2017, IEEE Sensors Journal.

[10]  Brian Christopher Gunter,et al.  Space-Based Distributed Computing Using a Networked Constellation of Small Satellites , 2013 .

[11]  Christopher S. Velden,et al.  Advancements in Objective Multisatellite Tropical Cyclone Center Fixing , 2016 .

[12]  C. Landsea,et al.  Atlantic Hurricane Database Uncertainty and Presentation of a New Database Format , 2013 .

[13]  Rajeswari Balasubramaniam,et al.  A New Paradigm in Earth Environmental Monitoring with the CYGNSS Small Satellite Constellation , 2018, Scientific Reports.

[14]  Steve A. Chien,et al.  Onboard Product Generation on Earth Observing One: A Pathfinder for the Proposed Hyspiri Mission Intelligent Payload Module , 2013, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[15]  Steve Ankuo Chien,et al.  Monitoring active volcanism with the Autonomous Sciencecraft Experiment on EO-1 , 2006 .

[16]  Robert Atlas,et al.  A Preliminary Impact Study of CYGNSS Ocean Surface Wind Speeds on Numerical Simulations of Hurricanes , 2019, Geophysical research letters.

[17]  K. Brieß,et al.  Autonomous Onboard Classification Experiment for the Satellite BIRD , 2002 .

[18]  T. N. Krishnamurti,et al.  A review of multimodel superensemble forecasting for weather, seasonal climate, and hurricanes , 2016 .

[19]  Joseph M. Pelissier,et al.  An Analysis of Atlantic Tropical Cyclone Forecast Errors, 1970–1979 , 1981 .

[20]  Tim N. Palmer,et al.  Ensemble forecasting , 2008, J. Comput. Phys..

[21]  Colin J. McAdie,et al.  Advances and Challenges at the National Hurricane Center , 2009 .

[22]  Hiroshi Akima,et al.  A New Method of Interpolation and Smooth Curve Fitting Based on Local Procedures , 1970, JACM.

[23]  Xiang Zhou,et al.  On-Board Georeferencing Using FPGA-Based Optimized Second-Order Polynomial Equation , 2019, Remote. Sens..

[24]  F. Marks,et al.  Overview of the NASA TROPICS CubeSat constellation mission , 2018, Optical Engineering + Applications.

[25]  Chandra M. Kishtawal,et al.  Automatic Determination of Center of Tropical Cyclone in Satellite-Generated IR Images , 2011, IEEE Geoscience and Remote Sensing Letters.

[26]  Abdollah Homaifar,et al.  A Sparse Recurrent Neural Network for Trajectory Prediction of Atlantic Hurricanes , 2016, GECCO.

[27]  V. Chandrasekar,et al.  An Earth Venture In-Space Technology Demonstration Mission for Temporal Experiment for Storms and Tropical Systems (Tempest) , 2018, IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium.

[28]  Chandan Roy,et al.  Cyclone track forecasting based on satellite images using artificial neural networks , 2009 .