Tuning of length-scale and observation-error for radar data assimilation using four dimensional variational (4D-Var) method

The effects of tuning of length-scale and observation-error on heavy rainfall forecasts are investigated. Length scale and observation error are tuned based on observation minus background (O - B) covariances and theoretically expected cost function values, respectively. Tuned length scale and observation error are applied to radar data assimilation using the Four Dimensional Variational (4D-Var) method. Length-scale tuning leads to improved Quantitative Precipitation Forecast (QPF) skill for heavy precipitation, better analyses, and reduced errors of wind, temperature, humidity, and hydrometeor forecasts. The effects of observation-error tuning are not as significant as those of length-scale tuning, and they are limited to improvements in QPF skill. This is because tuned observation errors are close to pre-assumed values. Proper tuning of length-scale and observation-error is essential for radar data assimilation using the 4D-Var method

Does Increasing Model Resolution Improve the Real-Time Forecasts of Western North Pacific Tropical Cyclones?

In this study, the general impact of high-resolution moving nesting domains on tropical cyclone (TC) intensity and track forecasts was verified, for a total of 107 forecast cases of 33 TCs, using the Weather Research and Forecasting (WRF) model. The experiment, with a coarse resolution of 12 km, could not significantly capture the intensification process, especially for maximum intensities (>60 m s(-1)). The intense TCs were better predicted by experiments using a moving nesting domain with a horizontal resolution of 4 km. The forecast errors for maximum wind speed and minimum sea-level pressure decreased in the experiment with higher resolution; the forecast of lifetime maximum intensity was improved. For the track forecast, the experiment with a coarser resolution tended to simulate TC tracks deviating rightward to the TC motions in the best-track data; this erroneous deflection was reduced in the experiment with a higher resolution. In particular, the track forecast in the experiment with a higher resolution improved more frequently for intense TCs that were generally distributed at relatively lower latitudes among the test cases. The sensitivity of the track forecast to the model resolution was relatively significant for lower-latitude TCs. On the other hand, the track forecasts of TCs moving to the mid-latitudes, which were primarily influenced by large-scale features, were not sensitive to the resolution

Added value of high-resolution regional climate model in simulating precipitation based on the changes in kinetic energy

As the resolution of regional climate models has increased with the development of computing resources, Added Values (AVs) have always been a steady research topic. Most previous studies examined AVs qualitatively by comparing model results with different model resolutions qualitatively. This study tried to quantitatively investigate the AV of the high-resolution regional climate model for precipitation by analyzing the distribution of kinetic energy according to the different wavelengths at two different resolutions (36 km vs. 4 km), away from the traditional comparative analysis. In addition, the experiment that the low-resolution topography was forced to the high-resolution model was additionally conducted to separate the AVs associated with the topographic effect. Among the three experiments, two with the same topography and two with the exact horizontal resolution were compared separately. With identical topography, the high-resolution model simulated amplified precipitation intensity more than the low-resolution model in all quantiles, especially for extreme precipitation. The precipitation generated by mesoscale or smaller scale weather/climate events was also simulated with greater intensity in the high-resolution model. With the same grid spacing, the more detailed topography model showed AV for increasing spatial variability of precipitation, especially in mountainous regions. The AVs identified in this study were related to kinetic energy with wavelengths at the meso-beta or smaller scale. On the other hand, the kinetic energy above the meso-alpha or larger scale has no significant correlation with the AV of precipitation

Dynamic ultrasonography of the shoulder

Ultrasonography (US) is a useful diagnostic method that can be easily applied to identify the cause of shoulder pain. Its low cost, excellent diagnostic accuracy, and capability for dynamic evaluation are also advantages. To assess all possible causes of shoulder pain, it is better to follow a standardized protocol and to perform a comprehensive evaluation of the shoulder than to conduct a focused examination. Moreover, a proper dynamic study can enhance the diagnostic quality of US, especially when the pathology is not revealed by a static evaluation. The purpose of this article is to review the common indications for dynamic US of the shoulder, and to present the basic techniques and characteristic US findings

Tropical Cyclone Intensity Estimation Using Multi-Dimensional Convolutional Neural Networks from Geostationary Satellite Data

For a long time, researchers have tried to find a way to analyze tropical cyclone (TC) intensity in real-time. Since there is no standardized method for estimating TC intensity and the most widely used method is a manual algorithm using satellite-based cloud images, there is a bias that varies depending on the TC center and shape. In this study, we adopted convolutional neural networks (CNNs) which are part of a state-of-art approach that analyzes image patterns to estimate TC intensity by mimicking human cloud pattern recognition. Both two dimensional-CNN (2D-CNN) and three-dimensional-CNN (3D-CNN) were used to analyze the relationship between multi-spectral geostationary satellite images and TC intensity. Our best-optimized model produced a root mean squared error (RMSE) of 8.32 kts, resulting in better performance (~35%) than the existing model using the CNN-based approach with a single channel image. Moreover, we analyzed the characteristics of multi-spectral satellite-based TC images according to intensity using a heat map, which is one of the visualization means of CNNs. It shows that the stronger the intensity of the TC, the greater the influence of the TC center in the lower atmosphere. This is consistent with the results from the existing TC initialization method with numerical simulations based on dynamical TC models. Our study suggests the possibility that a deep learning approach can be used to interpret the behavior characteristics of TCs

Screening models using multiple markers for early detection of late-onset preeclampsia in low-risk pregnancy

BACKGROUND: Our primary objective was to establish a cutoff value for the soluble fms-like tyrosine kinase 1(sFlt-1)/placental growth factor (PlGF) ratio measured using the Elecsys assay to predict late-onset preeclampsia in low-risk pregnancies. Our secondary objective was to evaluate the ability of combination models using Elecsys data, second trimester uterine artery (UtA) Doppler ultrasonography measurements, and the serum fetoplacental protein levels used for Down’s syndrome screening, to predict preeclampsia. METHODS: This prospective cohort study included 262 pregnant women with a low risk of preeclampsia. Plasma levels of pregnancy-associated plasma protein-A (PAPP-A) and serum levels of alpha-fetoprotein, unconjugated estriol, human chorionic gonadotropin, and inhibin-A were measured, and sFlt-1/PlGF ratios were calculated. All women underwent UtA Doppler ultrasonography at 20 to 24 weeks of gestation. RESULTS: Eight of the 262 women (3.0%) developed late-onset preeclampsia. Receiver operating characteristic curve analysis showed that the third trimester sFlt-1/PlGF ratio yielded the best detection rate (DR) for preeclampsia at a fixed false-positive rate (FPR) of 10%, followed by the second trimester sFlt-1/PlGF ratio, sFlt-1 level, and PlGF level. Binary logistic regression analysis was used to determine the five best combination models for early detection of late-onset preeclampsia. The combination of the PAPP-A level and the second trimester sFlt-1/PlGF ratio yielded a DR of 87.5% at a fixed FPR of 5%, the combination of second and third trimester sFlt-1/PlGF ratios yielded a DR of 87.5% at a fixed FPR of 10%, the combination of body mass index and the second trimester sFlt-1 level yielded a DR of 87.5% at a fixed FPR of 10%, the combination of the PAPP-A and inhibin-A levels yielded a DR of 50% at a fixed FPR of 10%, and the combination of the PAPP-A level and the third trimester sFlt-1/PlGF ratio yielded a DR of 62.5% at a fixed FPR of 10%. CONCLUSIONS: The combination of the PAPP-A level and the second trimester sFlt-1/PlGF ratio, and the combination of the second trimester sFlt-1 level with body mass index, were better predictors of late-onset preeclampsia than any individual marker

Catalpol Modulates Lifespan via DAF-16/FOXO and SKN-1/Nrf2 Activation in

Catalpol is an effective component of rehmannia root and known to possess various pharmacological properties. The present study was aimed at investigating the potential effects of catalpol on the lifespan and stress tolerance using C. elegans model system. Herein, catalpol showed potent lifespan extension of wild-type nematode under normal culture condition. In addition, survival rate of catalpol-fed nematodes was significantly elevated compared to untreated control under heat and oxidative stress but not under hyperosmolality conditions. We also found that elevated antioxidant enzyme activities and expressions of stress resistance proteins were attributed to catalpol-mediated increased stress tolerance of nematode. We further investigated whether catalpol’s longevity effect is related to aging-related factors including reproduction, food intake, and growth. Interestingly, catalpol exposure could attenuate pharyngeal pumping rate, indicating that catalpol may induce dietary restriction of nematode. Moreover, locomotory ability of aged nematode was significantly improved by catalpol treatment, while lipofuscin levels were attenuated, suggesting that catalpol may affect age-associated changes of nematode. Our mechanistic studies revealed that mek-1, daf-2, age-1, daf-16, and skn-1 are involved in catalpol-mediated longevity. These results indicate that catalpol extends lifespan and increases stress tolerance of C. elegans via DAF-16/FOXO and SKN-1/Nrf activation dependent on insulin/IGF signaling and JNK signaling

Potentiometric detection in ion chromatography using multi-ionophore membrane electrodes

The incorporation of ionophores selective for ammonium, potassium, sodium and calcium ions in an appropriate proportion into a plasticized poly(vinyl chloride) membrane provides a potentiometric membrane sensor with similar sensitivity to ammonium, alkali and alkaline earth metal ions. Such a sensor was employed in single-column ion chromatography using the wall-jet flow-cell arrangement, and was shown to exhibit similar detectability to that observed for conductivity detection.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/30547/1/0000180.pd

Satellite radiance data assimilation for binary tropical cyclone cases over the western North Pacific

A total of three binary tropical cyclone (TC) cases over the Western North Pacific are selected to investigate the effects of satellite radiance data assimilation on analyses and forecasts of binary TCs. Two parallel cycling experiments with a 6 h interval are performed for each binary TC case, and the difference between the two experiments is whether satellite radiance observations are assimilated. Satellite radiance observations are assimilated using the Weather Research and Forecasting Data Assimilation (WRFDA)'s three-dimensional variational (3D-Var) system, which includes the observation operator, quality control procedures, and bias correction algorithm for radiance observations. On average, radiance assimilation results in slight improvements of environmental fields and track forecasts of binary TC cases, but the detailed effects vary with the case. When there is no direct interaction between binary TCs, radiance assimilation leads to better depictions of environmental fields, and finally it results in improved track forecasts. However, positive effects of radiance assimilation on track forecasts can be reduced when there exists a direct interaction between binary TCs and intensities/structures of binary TCs are not represented well. An initialization method (e.g., dynamic initialization) combined with radiance assimilation and/or more advanced DA techniques (e.g., hybrid method) can be considered to overcome these limitations