Spatial variations in sea surface temperature (SST) and rainfall changes over the tropics are investigated based on ensemble simulations for the first half of the twenty-first century under the greenhouse gas (GHG) emission scenario A1B with coupled ocean–atmosphere general circulation models of the Geophysical Fluid Dynamics Laboratory (GFDL) and National Center for Atmospheric Research (NCAR). Despite a GHG increase that is nearly uniform in space, pronounced patterns emerge in both SST and precipitation. Regional differences in SST warming can be as large as the tropical-mean warming. Specifically, the tropical Pacific warming features a conspicuous maximum along the equator and a minimum in the southeast subtropics. The former is associated with westerly wind anomalies whereas the latter is linked to intensified southeast trade winds, suggestive of wind–evaporation–SST feedback. There is a tendency for a greater warming in the northern subtropics than in the southern subtropics in accordance ...

Global Warming Pattern Formation: Sea Surface Temperature and Rainfall

Wind speeds over the world’s oceans have increased over the past two decades, as have wave heights. Studies of climate change typically consider measurements or predictions of temperature over extended periods of time. Climate, however, is much more than temperature. Over the oceans, changes in wind speed and the surface gravity waves generated by such winds play an important role. We used a 23-year database of calibrated and validated satellite altimeter measurements to investigate global changes in oceanic wind speed and wave height over this period. We find a general global trend of increasing values of wind speed and, to a lesser degree, wave height, over this period. The rate of increase is greater for extreme events as compared to the mean condition.

https://researchbank.swinburne.edu.au/file/bca43746-6f16-4ad2-a4b7-27f8d8d60fed/1/PDF (Published version).pdf

Global trends in wind speed and wave height over the past 25 years

. On 11 March 2011, an earthquake occurred about 130 km off the Pacific coast of Japan's main island Honshu, followed by a large tsunami. The resulting loss of electric power at the Fukushima Dai-ichi nuclear power plant developed into a disaster causing massive release of radioactivity into the atmosphere. In this study, we determine the emissions into the atmosphere of two isotopes, the noble gas xenon-133 (133Xe) and the aerosol-bound caesium-137 (137Cs), which have very different release characteristics as well as behavior in the atmosphere. To determine radionuclide emissions as a function of height and time until 20 April, we made a first guess of release rates based on fuel inventories and documented accident events at the site. This first guess was subsequently improved by inverse modeling, which combined it with the results of an atmospheric transport model, FLEXPART, and measurement data from several dozen stations in Japan, North America and other regions. We used both atmospheric activity concentration measurements as well as, for 137Cs, measurements of bulk deposition. Regarding 133Xe, we find a total release of 15.3 (uncertainty range 12.2–18.3) EBq, which is more than twice as high as the total release from Chernobyl and likely the largest radioactive noble gas release in history. The entire noble gas inventory of reactor units 1–3 was set free into the atmosphere between 11 and 15 March 2011. In fact, our release estimate is higher than the entire estimated 133Xe inventory of the Fukushima Dai-ichi nuclear power plant, which we explain with the decay of iodine-133 (half-life of 20.8 h) into 133Xe. There is strong evidence that the 133Xe release started before the first active venting was made, possibly indicating structural damage to reactor components and/or leaks due to overpressure which would have allowed early release of noble gases. For 137Cs, the inversion results give a total emission of 36.6 (20.1–53.1) PBq, or about 43% of the estimated Chernobyl emission. Our results indicate that 137Cs emissions peaked on 14–15 March but were generally high from 12 until 19 March, when they suddenly dropped by orders of magnitude at the time when spraying of water on the spent-fuel pool of unit 4 started. This indicates that emissions may not have originated only from the damaged reactor cores, but also from the spent-fuel pool of unit 4. This would also confirm that the spraying was an effective countermeasure. We explore the main dispersion and deposition patterns of the radioactive cloud, both regionally for Japan as well as for the entire Northern Hemisphere. While at first sight it seemed fortunate that westerly winds prevailed most of the time during the accident, a different picture emerges from our detailed analysis. Exactly during and following the period of the strongest 137Cs emissions on 14 and 15 March as well as after another period with strong emissions on 19 March, the radioactive plume was advected over Eastern Honshu Island, where precipitation deposited a large fraction of 137Cs on land surfaces. Radioactive clouds reached North America on 15 March and Europe on 22 March. By middle of April, 133Xe was fairly uniformly distributed in the middle latitudes of the entire Northern Hemisphere and was for the first time also measured in the Southern Hemisphere (Darwin station, Australia). In general, simulated and observed concentrations of 133Xe and 137Cs both at Japanese as well as at remote sites were in good quantitative agreement. Altogether, we estimate that 6.4 PBq of 137Cs, or 18% of the total fallout until 20 April, were deposited over Japanese land areas, while most of the rest fell over the North Pacific Ocean. Only 0.7 PBq, or 1.9% of the total fallout were deposited on land areas other than Japan.

Xenon-133 and caesium-137 releases into the atmosphere from the Fukushima Dai-ichi nuclear power plant: determination of the source term, atmospheric dispersion, and deposition

The new level of precision and global coverage provided by satellite altimetry is rapidly advancing studies of ocean circulation. It allows for new insights into marine geodesy, ice sheet movements, plate tectonics, and for the first time provides high-resolution bathymetry for previously unmapped regions of our watery planet and crucial information on the large-scale ocean features on intra-season to interannual time scales. Satellite Altimetry and Earth Sciences has integrated the expertise of the leading international researchers to demonstrate the techniques, missions, and accuracy of satellite altimetry, including altimeter measurements, orbit determination, and ocean circulation models. Satellite altimetry is helping to advance studies of ocean circulation, tides, sea level, surface waves and allowing new insights into marine geodesy. Satellite Altimetry and Earth Sciences provides high resolution bathymetry for previously unmapped regions of our watery planet. Satellite Altimetry and Earth Sciences is for a very broad spectrum of academics, graduate students, and researchers in geophysics, oceanography, and the space and earth sciences. International agencies that fund satellite-based research will also appreciate the handy reference on the applications of satellite altimetry.

Satellite altimetry and Earth sciences :a handbook of techniques and applications

In this paper a detailed global climatology of wind sea and swell parameters, based on the ERA-40 wave reanalysis, is presented. The spatial pattern of the swell dominance of the Earth’s Oceans, in ...

A Global View on the Wind Sea and Swell Climate and Variability from ERA-40

Numerous case reports and regional studies on swell and wind sea events have been documented during the past century. The global picture of these common oceanic phenomena, however, is still incomplete in many aspects. This paper presents a feasibility study of using collocated wind speed and significant wave height measurements from simultaneous satellite scatterometer and altimeter sources to observe the spatial and seasonal pattern of dominant swell and wind wave zones in the world's oceans. Two energy-related normalized indices are proposed, on the basis of which global statistics of swell/wind sea probabilities and intensities are obtained. It is found that three well-defined tongue-shaped zones of swell dominance, termed “swell pools,” are located in the eastern tropical areas of the Pacific, the Atlantic, and the Indian Oceans, respectively. Regions of intensive wave growth are observed in the northwest Pacific, the northwest Atlantic, the Southern Ocean, and the Mediterranean Sea. Seasonal...

A Global View of Swell and Wind Sea Climate in the Ocean by Satellite Altimeter and Scatterometer

This work presents EddyNet, a deep learning based architecture for automated eddy detection and classification from Sea Surface Height (SSH) maps provided by the Copernicus Marine and Environment Monitoring Service (CMEMS). EddyNet consists of a convolutional encoder-decoder followed by a pixel-wise classification layer. The output is a map with the same size of the input where pixels have the following labels {‘0’: Non eddy, ‘1’: anticyclonic eddy, ‘2’: cyclonic eddy}. Keras Python code, the training datasets and EddyNet weights files are open-source and freely available on https://github.com/redouanelg/EddyNet.

EddyNet: A Deep Neural Network For Pixel-Wise Classification of Oceanic Eddies

Accurate mapping of benthic habitats in the Florida Keys is essential in developing effective management strategies for this unique coastal ecosystem. In this study, we evaluated the applicability of hyperspectral imagery collected from Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) for benthic habitat mapping in the Florida Keys. An overall accuracy of 84.3% and 86.7% was achieved respectively for a group-level (3-class) and code-level (12-class) classification by integrating object-based image analysis (OBIA), hyperspectral image processing methods, and machine learning algorithms. Accurate and informative object-based benthic habitat maps were produced. Three commonly used image correction procedures (atmospheric, sun-glint, and water-column corrections) were proved unnecessary for small area mapping in the Florida Keys. Inclusion of bathymetry data in the mapping procedure did not increase the classification accuracy. This study indicates that hyperspectral systems are promising in accurate benthic habitat mapping at a fine detail level.

/pdf/object-based-benthic-habitat-mapping-in-the-florida-keys-18jb3wcocq.pdf

Object-based benthic habitat mapping in the Florida Keys from hyperspectral imagery

Predicting the passenger flow of metro networks is of great importance for traffic management and public safety. However, such predictions are very challenging, as passenger flow is affected by complex spatial dependencies (nearby and distant) and temporal dependencies (recent and periodic). In this paper, we propose a novel deep-learning-based approach, named STGCNNmetro (spatiotemporal graph convolutional neural networks for metro), to collectively predict two types of passenger flow volumes—inflow and outflow—in each metro station of a city. Specifically, instead of representing metro stations by grids and employing conventional convolutional neural networks (CNNs) to capture spatiotemporal dependencies, STGCNNmetro transforms the city metro network to a graph and makes predictions using graph convolutional neural networks (GCNNs). First, we apply stereogram graph convolution operations to seamlessly capture the irregular spatiotemporal dependencies along the metro network. Second, a deep structure composed of GCNNs is constructed to capture the distant spatiotemporal dependencies at the citywide level. Finally, we integrate three temporal patterns (recent, daily, and weekly) and fuse the spatiotemporal dependencies captured from these patterns to form the final prediction values. The STGCNNmetro model is an end-to-end framework which can accept raw passenger flow-volume data, automatically capture the effective features of the citywide metro network, and output predictions. We test this model by predicting the short-term passenger flow volume in the citywide metro network of Shanghai, China. Experiments show that the STGCNNmetro model outperforms seven well-known baseline models (LSVR, PCA-kNN, NMF-kNN, Bayesian, MLR, M-CNN, and LSTM). We additionally explore the sensitivity of the model to its parameters and discuss the distribution of prediction errors.

/pdf/predicting-station-level-short-term-passenger-flow-in-a-1ttvpzzgeg.pdf

Predicting Station-Level Short-Term Passenger Flow in a Citywide Metro Network Using Spatiotemporal Graph Convolutional Neural Networks

This paper proposes a new algorithm for parallel identification of mesoscale eddies from global satellite altimetry data. By simplifying the recognition process and the sea level anomaly (SLA) contours’ search range, the method improves identification efficiency compared with the previous SSH-based method even in the single-threaded process. The global SLA map is divided into several regions. These regions are identified simultaneously with a new SSH-based method. All the eddy identification results of these regions are merged seamlessly into a global eddy map. A β-plane approximation is used to calculate the geostrophic speed in the equatorial band. Compared with the computation complexity of the previous SSH-based method, which is , the computation complexity of the new method is , where K is the number of threads and L is the number of regional SLA maps. When applying the new method to the global SLA map, the computation is ~100 times faster than the previous SSH-based method on an average comp...

Ge Chen

Papers

A Global View of Swell and Wind Sea Climate in the Ocean by Satellite Altimeter and Scatterometer

EddyNet: A Deep Neural Network For Pixel-Wise Classification of Oceanic Eddies

Object-based benthic habitat mapping in the Florida Keys from hyperspectral imagery

Predicting Station-Level Short-Term Passenger Flow in a Citywide Metro Network Using Spatiotemporal Graph Convolutional Neural Networks

A Parallel SLA-Based Algorithm for Global Mesoscale Eddy Identification