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The seasonal cycle is the dominant mode of variability in the air-sea CO2 flux in most regions of the global ocean, yet discrepancies between different seasonality estimates are rather large. As part of the Regional Carbon Cycle Assessment and Processes Phase 2 project (RECCAP2), we synthesize surface ocean pCO2 and air-sea CO2 flux seasonality from models and observation-based estimates, focusing on both a present-day climatology and decadal changes between the 1980s and 2010s. Four main findings emerge: First, global ocean biogeochemistry models (GOBMs) and observation-based estimates (pCO2 products) of surface pCO2 seasonality disagree in amplitude and phase, primarily due to discrepancies in the seasonal variability in surface DIC. Second, the seasonal cycle in pCO2 has increased in amplitude over the last three decades in both pCO2 products and GOBMs. Third, decadal increases in pCO2 seasonal cycle amplitudes in subtropical biomes for both pCO2 products and GOBMs are driven by increasing DIC concentrations stemming from the uptake of anthropogenic CO2 (Cant). In subpolar and Southern Ocean biomes, however, the seasonality change for GOBMs is dominated by Cant invasion, whereas for pCO2 products an indeterminate combination of Cant invasion and climate change modulates the changes. Fourth, biome-aggregated decadal changes in the amplitude of pCO2 seasonal variability are largely detectable against both mapping uncertainty (reducible) and natural variability uncertainty (irreducible), but not at the gridpoint scale over much of the northern subpolar oceans and over the Southern Ocean, underscoring the importance of sustained high-quality seasonally resolved measurements over these regions.

As a contribution to the Regional Carbon Cycle Assessment and Processes phase 2 (RECCAP2) project, we present synthesized estimates of Arctic Ocean sea-air CO2 fluxes and their uncertainties from surface ocean pCO2-observation products, ocean biogeochemical hindcast and data assimilation models, and atmospheric inversions. For the period of 1985–2018, the Arctic Ocean was a net sink of CO2 of 116 ± 4 TgC yr−1 in the pCO2 products, 92 ± 30 TgC yr−1 in the models, and 91 ± 21 TgC yr−1 in the atmospheric inversions. The CO2 uptake peaks in late summer and early autumn, and is low in winter when sea ice inhibits sea-air fluxes. The long-term mean CO2 uptake in the Arctic Ocean is primarily caused by steady-state fluxes of natural carbon (70% ± 15%), and enhanced by the atmospheric CO2 increase (19% ± 5%) and climate change (11% ± 18%). The annual mean CO2 uptake increased from 1985 to 2018 at a rate of 31 ± 13 TgC yr−1 dec−1 in the pCO2 products, 10 ± 4 TgC yr−1 dec−1 in the models, and 32 ± 16 TgC yr−1 dec−1 in the atmospheric inversions. Moreover, 77% ± 38% of the trend in the net CO2 uptake over time is caused by climate change, primarily due to rapid sea ice loss in recent years. Furthermore, true uncertainties may be larger than the given ensemble standard deviations due to common structural biases across all individual estimates.

The seasonal cycle is the dominant mode of variability in the air-sea CO2 flux in most regions of the global ocean, yet discrepancies between different seasonality estimates are rather large. As part of the Regional Carbon Cycle Assessment and Processes Phase 2 project (RECCAP2), we synthesize surface ocean pCO2 and air-sea CO2 flux seasonality from models and observation-based estimates, focusing on both a present-day climatology and decadal changes between the 1980s and 2010s. Four main findings emerge: First, global ocean biogeochemistry models (GOBMs) and observation-based estimates (pCO2 products) of surface pCO2 seasonality disagree in amplitude and phase, primarily due to discrepancies in the seasonal variability in surface DIC. Second, the seasonal cycle in pCO2 has increased in amplitude over the last three decades in both pCO2 products and GOBMs. Third, decadal increases in pCO2 seasonal cycle amplitudes in subtropical biomes for both pCO2 products and GOBMs are driven by increasing DIC concentrations stemming from the uptake of anthropogenic CO2 (Cant). In subpolar and Southern Ocean biomes, however, the seasonality change for GOBMs is dominated by Cant invasion, whereas for pCO2 products an indeterminate combination of Cant invasion and climate change modulates the changes. Fourth, biome-aggregated decadal changes in the amplitude of pCO2 seasonal variability are largely detectable against both mapping uncertainty (reducible) and natural variability uncertainty (irreducible), but not at the gridpoint scale over much of the northern subpolar oceans and over the Southern Ocean, underscoring the importance of sustained high-quality seasonally resolved measurements over these regions

Chest radiography is a general method for diagnosing a patient's condition and identifying important information; therefore, radiography is used extensively in routine medical practice in various situations, such as emergency medical care and medical checkup. However, a high level of expertise is required to interpret chest radiographs. Thus, medical specialists spend considerable time in diagnosing such huge numbers of radiographs. In order to solve these problems, methods for generating findings have been proposed. However, the study of generating chest radiograph findings has primarily focused on the English language, and to the best of our knowledge, no studies have studied Japanese data on this subject. There are two challenges involved in generating findings in the Japanese language. The first challenge is that word splitting is difficult because the boundaries of Japanese word are not clear. The second challenge is that there are numerous orthographic variants. For deal with these two challenges, we proposed an end-to-end model that generates Japanese findings at the character-level from chest radiographs. In addition, we introduced the attention mechanism to improve not only the accuracy, but also the interpretation ability of the results. We evaluated the proposed method using a public dataset with Japanese findings. The effectiveness of the proposed method was confirmed using the Bilingual Evaluation Understudy score. And, we were confirmed from the generated findings that the proposed method was able to consider the orthographic variants. Furthermore, we confirmed via visual inspection that the attention mechanism captures the features and positional information of radiographs., Comment: 8 pages, 3 figures, 2 tables

We introduce a novel method and implementation architecture to train neural networks which preserves the confidentiality of both the model and the data. Our method relies on homomorphic capability of lattice based encryption scheme. Our procedure is optimized for operations on packed ciphertexts in order to achieve efficient updates of the model parameters. Our method achieves a significant reduction of computations due to our way to perform multiplications and rotations on packed ciphertexts from a feedforward network to a back-propagation network. To verify the accuracy of the training model as well as the implementation feasibility, we tested our method on the Iris data set by using the CKKS scheme with Microsoft SEAL as a back end. Although our test implementation is for simple neural network training, we believe our basic implementation block can help the further applications for more complex neural network based use cases.

Many studies on future climate projection point out that with progressing of global warming, upper-ocean density stratification will strengthen over this century, and consequently, global-averaged ocean primary productivity will decrease. Observed long-term changes in the stratification to date, however, still show large uncertainties of the change itself and its driver. Focusing on the vertical difference in the emergence of the global warming signals, we used only observational profiles to describe the spatiotemporal characteristic of long-term trend and variability in the upper-ocean stratification (defined as the density difference between the surface and 200-m depth). Statistically significant strengthening of the stratification since the 1960s was detected in similar to 40% of the global ocean area. The global average increase in the stratification corresponds to 3.3-6.1% of the mean stratification. The strengthening trends considerably change depending on the regions and show dominant contribution from the tropical region. In addition to the well-documented explanation of strengthening stratification, namely the surface intensification of global warming signal, we found that changes in subsurface temperature and salinity stratification associated with changes in atmospheric/ocean circulations significantly contribute to the long-term change in the stratification and setting its regional difference. In midlatitude and high-latitude ocean of the Northern Hemisphere, the long-term trend exhibits noteworthy seasonality, which shows faster increase trend in the summer than in the winter. From the detrended time series, interannual variabilities correlated with a particular climate mode are detected in several ocean regions, suggesting that these variabilities are mainly driven by associated sea surface temperature variation. Plain Language Summary In general, upper-ocean stratification (i.e., vertical changes in sea water density) serves as a barrier between relat

Many studies on future climate projection point out that with progressing of global warming, upper-ocean density stratification will strengthen over this century, and consequently, global-averaged ocean primary productivity will decrease. Observed long-term changes in the stratification to date, however, still show large uncertainties of the change itself and its driver. Focusing on the vertical difference in the emergence of the global warming signals, we used only observational profiles to describe the spatiotemporal characteristic of long-term trend and variability in the upper-ocean stratification (defined as the density difference between the surface and 200-m depth). Statistically significant strengthening of the stratification since the 1960s was detected in similar to 40% of the global ocean area. The global average increase in the stratification corresponds to 3.3-6.1% of the mean stratification. The strengthening trends considerably change depending on the regions and show dominant contribution from the tropical region. In addition to the well-documented explanation of strengthening stratification, namely the surface intensification of global warming signal, we found that changes in subsurface temperature and salinity stratification associated with changes in atmospheric/ocean circulations significantly contribute to the long-term change in the stratification and setting its regional difference. In midlatitude and high-latitude ocean of the Northern Hemisphere, the long-term trend exhibits noteworthy seasonality, which shows faster increase trend in the summer than in the winter. From the detrended time series, interannual variabilities correlated with a particular climate mode are detected in several ocean regions, suggesting that these variabilities are mainly driven by associated sea surface temperature variation. Plain Language Summary In general, upper-ocean stratification (i.e., vertical changes in sea water density) serves as a barrier between relat

Many studies on future climate projection point out that with progressing of global warming, upper-ocean density stratification will strengthen over this century, and consequently, global-averaged ocean primary productivity will decrease. Observed long-term changes in the stratification to date, however, still show large uncertainties of the change itself and its driver. Focusing on the vertical difference in the emergence of the global warming signals, we used only observational profiles to describe the spatiotemporal characteristic of long-term trend and variability in the upper-ocean stratification (defined as the density difference between the surface and 200-m depth). Statistically significant strengthening of the stratification since the 1960s was detected in similar to 40% of the global ocean area. The global average increase in the stratification corresponds to 3.3-6.1% of the mean stratification. The strengthening trends considerably change depending on the regions and show dominant contribution from the tropical region. In addition to the well-documented explanation of strengthening stratification, namely the surface intensification of global warming signal, we found that changes in subsurface temperature and salinity stratification associated with changes in atmospheric/ocean circulations significantly contribute to the long-term change in the stratification and setting its regional difference. In midlatitude and high-latitude ocean of the Northern Hemisphere, the long-term trend exhibits noteworthy seasonality, which shows faster increase trend in the summer than in the winter. From the detrended time series, interannual variabilities correlated with a particular climate mode are detected in several ocean regions, suggesting that these variabilities are mainly driven by associated sea surface temperature variation. Plain Language Summary In general, upper-ocean stratification (i.e., vertical changes in sea water density) serves as a barrier between relat