Verification of an operational ocean circulation-surface wave coupled forecasting system for the China＇s seas

An operational ocean circulation-surface wave coupled forecasting system for the seas off China and adjacent areas（OCFS-C） is developed based on parallelized circulation and wave models. It has been in operation since November 1, 2007. In this paper we comprehensively present the simulation and verification of the system, whose distinguishing feature is that the wave-induced mixing is coupled in the circulation model. In particular, with nested technique the resolution in the China＇s seas has been updated to（1/24）° from the global model with（1/2）°resolution. Besides, daily remote sensing sea surface temperature（SST） data have been assimilated into the model to generate a hot restart field for OCFS-C. Moreover, inter-comparisons between forecasting and independent observational data are performed to evaluate the effectiveness of OCFS-C in upper-ocean quantities predictions, including SST, mixed layer depth（MLD） and subsurface temperature. Except in conventional statistical metrics, non-dimensional skill scores（SS） is also used to evaluate forecast skill. Observations from buoys and Argo profiles are used for lead time and real time validations, which give a large SS value（more than 0.90）. Besides, prediction skill for the seasonal variation of SST is confirmed. Comparisons of subsurface temperatures with Argo profiles data indicate that OCFS-C has low skill in predicting subsurface temperatures between 100 m and 150 m. Nevertheless, inter-comparisons of MLD reveal that the MLD from model is shallower than that from Argo profiles by about 12 m, i.e., OCFS-C is successful and steady in MLD predictions. Validation of 1-d, 2-d and 3-d forecasting SST shows that our operational ocean circulation-surface wave coupled forecasting model has reasonable accuracy in the upper ocean.

Prediction of Seasonal Tropical Cyclone Activity in the NUIST-CFS1.0 Forecast System

Prediction skill for the seasonal tropical cyclone(TC)activity in the Northern Hemisphere is investigated using the coupled climate forecast system(version 1.0)of Nanjing University of Information Science and Technology(NUISTCFS1.0).This assessment is based on the seven-month(May to November)hindcasts consisting of nine ensemble members during 1982–2019.The predictions are compared with the Japanese 55-year Reanalysis and observed tropical storms in the Northern Hemisphere.The results show that the overall distributions of the TC genesis and track densities in model hindcasts agree well with the observations,although the seasonal mean TC frequency and accumulated cyclone energy(ACE)are underestimated in all basins due to the low resolution(T106)of the atmospheric component in the model.NUIST-CFS1.0 closely predicts the interannual variations of TC frequency and ACE in the North Atlantic(NA)and eastern North Pacific(ENP),which have a good relationship with indexes based on the sea surface temperature.In the western North Pacific(WNP),NUIST-CFS1.0 can closely capture ACE,which is significantly correlated with the El Ni?o–Southern Oscillation(ENSO),while it has difficulty forecasting the interannual variation of TC frequency in this area.When the WNP is further divided into eastern and western subregions,the model displays improved TC activity forecasting ability.Additionally,it is found that biases in predicted TC genesis locations lead to inaccurately represented TC–environment relationships,which may affect the capability of the model in reproducing the interannual variations of TC activity.

A New Statistical Downscaling Scheme for Predicting Winter Precipitation in China

An effective statistical downscaling scheme was developed on the basis of singular value decomposition to predict boreal winter(December-January-February)precipitation over China.The variable geopotential height at 500 hPa(GH5)over East Asia,which was obtained from National Centers for Environmental Prediction’s Coupled Forecast System(NCEP CFS),was used as one predictor for the scheme.The preceding sea ice concentration(SIC)signal obtained from observed data over high latitudes of the Northern Hemisphere was chosen as an additional predictor.This downscaling scheme showed significantly improvement in predictability over the original CFS general circulation model(GCM)output in cross validation.The multi-year average spatial anomaly correlation coefficient increased from–0.03 to 0.31,and the downscaling temporal root-mean-square-error(RMSE)decreased significantly over that of the original CFS GCM for most China stations.Furthermore,large precipitation anomaly centers were reproduced with greater accuracy in the downscaling scheme than those in the original CFS GCM,and the anomaly correlation coefficient between the observation and downscaling results reached～0.6 in the winter of 2008.

Quantify Urbanization-Induced Precipitation and Runoff Anomalies over the Qinhuai River Basin of China: Sensitivity Experiments with WRF-Hydro

Urbanization-related precipitation and surface runoff changes have been widely investigated,but few studies have directly quantified these changes and their link to urbanization in the hydrological cycle.A two-way dynamically coupled atmospheric–hydrological modeling system,Weather Research and Forecasting(WRF)-Hydro,has been applied in this study to perform the quantification.The offline WRF-Hydro was first calibrated and validated for several flooding events against gauge observed streamflow data,with the Nash–Sutcliffe efficiency reaching 0.9.Compared to the WRF model,WRF-Hydro resolves more detailed rainfall pattern features and reproduces the gauge rainfall with a correlation coefficient of 0.8.Then,the impact of urbanization on hydrometeorological processes was investigated with coupled WRF-Hydro sensitivity simulations over the Qinhuai River basin of China during 2 June–31 July 2015.The results indicate that urbanization enhances regional precipitation,resulting in an indirect increase in surface runoff,overland flow,and streamflow by 16.7,93.5,and 111.2 mm,respectively;however,the impervious area results in higher surface runoff,overland flow,and streamflow.Moreover,changes in main hydrometeorological processes further impact the atmospheric–terrestrial water budget,resulting in a decrease in terrestrial water storage and an increase(a decrease)in precipitable water storage in the middle(lower)parts of the lower troposphere.These changes are likely associated with the warmer urban environment than rural areas.Increased water vapor and strengthened convective conditions in the middle part of the lower troposphere due to urban warming are advantageous to the formation of precipitation in urban areas,which in turn increases surface runoff,thereby facilitating the water cycle and altering the atmospheric–terrestrial water budget.