The 2011 Survey on Hypertensive Disorders of Pregnancy (HDP) in China:Prevalence, Risk Factors, Complications, Pregnancy and Perinatal Outcomes

Hypertensive disorders of pregnancy (HDP) are a group of medical complications in pregnancy and also a risk factor for severe pregnancy outcomes, but it lacks a large-scale epidemiological investigation in recent years. This survey represents a multicenter cross-sectional retrospective study to estimate the prevalence and analyze the risk factors for HDP among the pregnant women who had referred for delivery between January 1st 2011 and December 31st 2011 in China Mainland. A total of 112,386 pregnant women were investigated from 38 secondary and tertiary specialized or general hospitals randomly selected across the country, of which 5,869 had HDP, accounting for 5.22% of all pregnancies. There were significant differences in the prevalence of HDP between geographical regions, in which the North China showed the highest (7.44%) and Central China showed the lowest (1.23%). Of six subtypes of HDP, severe preeclampsia accounted for 39.96%, gestational hypertension for 31.40%, mild preeclampsia for 15.13%, chronic hypertension in pregnancy for 6.00%, preeclampsia superimposed on chronic hypertension for 3.68% and eclampsia for 0.89%. A number of risk factors for HDP were identified, including twin pregnancy, age of >35 years, overweight and obesity, primipara, history of hypertension as well as family history of hypertension and diabetes. The prevalence of pre-term birth, placental abruption and postpartum hemorrhage were significantly higher in women with HDP than those without HDP. The possible risk factors confirmed in this study may be useful for the development of early diagnosis and appropriate treatment of HDP

Impacts of model resolution on responses of western North Pacific tropical cyclones to ENSO in the HighResMIP-PRIMAVERA ensemble

The El Niño/Southern Oscillation (ENSO) is the major driver of interannual variations of the western North Pacific (WNP) tropical cyclones (TCs). Realistic reproduction of ENSO-WNPTC teleconnection in coupled models (CGCMs) is thus crucial for improved seasonal-to-interannual prediction of WNPTC activity. Here, basing on the outputs of six pairs of high-resolution (HR) and low-resolution (LR) CGCMs participating the HighResMIP-PRIMAVERA project, we showed that the HR models outperform the LR ones in reproducing the observed increase of TC genesis in the southeastern WNP but the decrease in the northwestern WNP in the developing years of El Niño. The better performance of HR than LR models is on one hand due to the generally increased frequency and variability of TCs in the HR models. On the other hand, the teleconnection of El Niño to the WNP shows a dipole circulation difference between the HR and LR models with an anomalous cyclone in the southeastern WNP and anticyclone in the northwestern WNP, which enhances the dipole TC genesis anomalies in the HR compared to the LR models. The teleconnection difference stems from the westward shift of the ENSO-related SST and convection anomalies in the tropical Pacific in the HR compared to the LR models, which may be ultimately linked to the reduced cold tongue biases in the HR models

Forecasts of MJO during DYNAMO in a Coupled Tropical Channel Model: Impact of Planetary Boundary Layer Schemes

It is challenging to predict the eastward-propagating Madden–Julian Oscillation (MJO) events across the Maritime Continent (MC) in models. We constructed an air–sea coupled numerical weather prediction model—a tropical channel model—to investigate the role of the planetary boundary layer (PBL) scheme on eastward-propagating and non-propagating MJO precipitation events during the Dynamics of the MJO (DYNAMO) campaign period. Analysis of three hindcast experiments with different PBL schemes illustrates that the PBL scheme is crucial to simulating the eastward-propagating MJO events. The experiment with the University of Washington (UW) PBL scheme can predict the convection activity over the MC due to a good representation of moist static energy (MSE) tendency relatively well. The horizontal advection and the upward transport of moisture from the PBL to the free atmosphere play a major role in the MSE tendency ahead of MJO convection. The difference in the meridional component of MSE advection accounts for the different MSE budgets in the three hindcast experiments. A well-simulated meridional advection can transport the meridional water vapor to moisten the MC. Our results suggest that a proper PBL scheme with better simulated meridional water vapor distribution is crucial to predicting the eastward propagation of MJO events across the MC in the tropical channel model

Markov Chain Monte Carlo simulation and regression approach guided by El Niño–Southern Oscillation to model the tropical cyclone occurrence over the Bay of Bengal

Tropical cyclone (TC) is one of the most devastating weather systems that causes enormous loss of life and property in the coastal regions of Bay of Bengal (BoB). Statistical forecasting of TC occurrence can help decision-makers and inhabitants in shoreline zones to take necessary planning and actions in advance. In this study, we have investigated the impact of El Niño–Southern Oscillation (ENSO) on the frequency of TC over the BoB by using 100 years TC and Southern Oscillation Index data. The frequency of TC is approximated through observation and Markov Chain Monte Carlo (MCMC) simulation. Two-sample Student’s t test has been applied for examining the statistical significance where the results are significant at 5% level for all cyclonic disturbances. The monthly and seasonal distribution show this feature more distinctly. The total annual frequency of depressions and cyclonic storms in El Niño and La Niña conditions does not differ much, but the monthly/seasonal distribution shows high differences for certain months and seasons. The simulated frequency of TC landfall using MCMC matches well with the observation. The proposed methodology is illustrated through a case study in BoB rim countries-Bangladesh, India, Sri Lanka and Myanmar. Poisson and Bayesian regression have also been used to predict the probabilities of TC frequency over the BoB. Both the regression approaches show 10 and 32% improvement than climatology for the forecast and cross-validation skill respectively. We have also analyzed TC impact over Bangladesh as a case study. Possible links of the variation of TC activities with the largescale geographical distribution of sea surface temperature, vertical wind shear, vorticity, moisture and relative humidity are also explored.</p

Current status of intraseasonal-seasonal-to-interannual prediction of the Indo-Pacific climate

International audiencePrediction skill regarding the Indo-Pacific climate has been rapidly enhanced in the past decade. While early prediction efforts were made based on statistical methods and/or simple climate models, recent climate predictions have been performed using comprehensive ocean–atmosphere general circulation models (OAGCMs). Both model performance of climate simulation and the data assimilation scheme have been improved to produce better prediction skill. Multimodel prediction results have been collected to gain higher skill, which is usually superior to that of the individual model. Most of the OAGCMs can now skillfully predict the Indian Ocean Dipole (IOD) at lead times of up to 1–2 seasons, and ENSO up to 6–9 months. Distinct SST patterns associated with different El Ni˜no flavors can also be well predicted at short-to-medium lead times. Furthermore, global climate anomalies induced by ENSO and IOD are realistically predicted. The subtropical dipole modes in the South Atlantic Ocean and the Indian Ocean (IO), the southern African climate, Asian monsoon precipitation, and Northern Hemisphere atmospheric circulation anomalies are predictable at short-to-medium lead times. Encouragingly, the JAMSTEC SINTEX-F model produces a useful skill of ENSO prediction at lead times of up to two years. And some strong IOD events can be well predicted up to one year ahead even if El Ni˜no's influence is suppressed. The results also suggest the importance of the IO–Pacific interbasin coupling and the recent global warming trend to climate predictability. For MJO prediction, the multimodel ensemble based on 12 OAGCMs achieves a useful skill (>0.5) of up to 26–28 days in advance

Univariate regression analysis of possible risk factors for HDP.

<p>Univariate regression analysis of possible risk factors for HDP.</p

Demographic characteristics of the 112,386 pregnant women in the study.

<p>Demographic characteristics of the 112,386 pregnant women in the study.</p

Differences in pregnancy outcomes between women with and without HDP.

<p>Differences in pregnancy outcomes between women with and without HDP.</p