Block Hankel Tensor ARIMA for Multiple Short Time Series Forecasting

This work proposes a novel approach for multiple time series forecasting. At first, multi-way delay embedding transform (MDT) is employed to represent time series as low-rank block Hankel tensors (BHT). Then, the higher-order tensors are projected to compressed core tensors by applying Tucker decomposition. At the same time, the generalized tensor Autoregressive Integrated Moving Average (ARIMA) is explicitly used on consecutive core tensors to predict future samples. In this manner, the proposed approach tactically incorporates the unique advantages of MDT tensorization (to exploit mutual correlations) and tensor ARIMA coupled with low-rank Tucker decomposition into a unified framework. This framework exploits the low-rank structure of block Hankel tensors in the embedded space and captures the intrinsic correlations among multiple TS, which thus can improve the forecasting results, especially for multiple short time series. Experiments conducted on three public datasets and two industrial datasets verify that the proposed BHT-ARIMA effectively improves forecasting accuracy and reduces computational cost compared with the state-of-the-art methods.Comment: Accepted by AAAI 202

Simultaneous retrieval of atmospheric CO_2 and light path modification from space-based spectroscopic observations of greenhouse gases: methodology and application to GOSAT measurements over TCCON sites

This paper presents an improved photon path length probability density function method that permits simultaneous retrievals of column-average greenhouse gas mole fractions and light path modifications through the atmosphere when processing high-resolution radiance spectra acquired from space. We primarily describe the methodology and retrieval setup and then apply them to the processing of spectra measured by the Greenhouse gases Observing SATellite (GOSAT). We have demonstrated substantial improvements of the data processing with simultaneous carbon dioxide and light path retrievals and reasonable agreement of the satellite-based retrievals against ground-based Fourier transform spectrometer measurements provided by the Total Carbon Column Observing Network (TCCON)

Controlling factors of large-scale harmful algal blooms with Karenia selliformis after record-breaking marine heatwaves

Unprecedented, large-scale harmful algal blooms (HABs) dominated by Karenia selliformis occurred off the southeastern coast of Hokkaido, Japan, from late September to early November 2021, about a month after intense and extensive marine heatwaves (MHWs) had subsided. The aims of the present study were to understand the mechanism of development, maintenance, and decay of the HABs as well as to investigate the effect of the MHWs on the HABs. We developed a one-dimensional, lower trophic-level ecosystem model (NEMURO+) to simulate the HABs. The model successfully simulated the 2021 HABs and indicated that their development, maintenance, and decay were controlled primarily by changes of water temperature. Nitrate supply from subsurface layers by seasonal vertical diffusion in autumn also helped to maintain the HABs. Vertical diffusion following MHWs in 2021 contributed to the long duration of the preferred temperature for K. selliformis and the occurrence of pre-bloom of K. selliformis, resulting in preconditioning and accelerating the HABs. However, simulations for normal years (i.e., the climatological mean during 2003–2018) showed that HABs could have occurred, even in the absence of MHWs. The simulations indicated that massive blooms of other phytoplankton species (e.g., diatoms) would not have occurred in 2021, even in the absence of a K. selliformis bloom. The implication was that the HABs in 2021 were the species-specific responses of K. selliformis. The proposed mechanism of the HABs was peculiar to our study area and differed from that previously reported for other K. selliformis blooms. Specifically, the preferred temperature for the HABs of K. selliformis was clearly lower than the previously reported preferred temperature of K. selliformis; thus, the physiological characteristics of the K. selliformis that bloomed in our study area differed from those of other K. selliformis strains. These discoveries provide the first evidence to explain how MHWs affect HABs, and to understand how inter-regional dissimilarities of K. selliformis can lead to large-scale, devastating outbreaks under different oceanographic conditions