Multi-scale I...8) Prediction_Yan GAO.pdf

Multi-scale Incremental Analysis Update Scheme and Its Applicationto Typhoon Mangkhut(2018)PredictionYan GAO1,Jiali FENG1,Xin XIA1,Jian SUN2,Yulong MA1,Dongmei CHEN1,and Qilin WAN*11Guangdong-Hong Kong-Macao Greater Bay Area Weather Research Center forMonitoring Warning and Forecasting,Shenzhen 518038,China2CMA Earth System Modeling and Prediction Centre,China Meteorological Administration,Beijing 100081,China(Received 5 December 2021;revised 5 May 2022;accepted 11 May 2022)ABSTRACTIn the traditional incremental analysis update(IAU)process,all analysis increments are treated as constant forcing in amodels prognostic equations over a certain time window.This approach effectively reduces high-frequency oscillationsintroduced by data assimilation.However,as different scales of increments have unique evolutionary speeds and lifehistories in a numerical model,the traditional IAU scheme cannot fully meet the requirements of short-term forecasting forthe damping of high-frequency noise and may even cause systematic drifts.Therefore,a multi-scale IAU scheme isproposed in this paper.Analysis increments were divided into different scale parts using a spatial filtering technique.Foreach scale increment,the optimal relaxation time in the IAU scheme was determined by the skill of the forecasting results.Finally,different scales of analysis increments were added to the model integration during their optimal relaxation time.The multi-scale IAU scheme can effectively reduce the noise and further improve the balance between large-scale andsmall-scale increments in the model initialization stage.To evaluate its performance,several numerical experiments wereconducted to simulate the path and intensity of Typhoon Mangkhut(2018)and showed that:(1)the multi-scale IAUscheme had an obvious effect on noise control at the initial stage of data assimilation;(2)the optimal relaxation time forlarge-scale and small-scale increments was estimated as 6 h and 3 h,respectively;(3)the forecast performance of the multi-scale IAU scheme in the prediction of Typhoon Mangkhut(2018)was better than that of the traditional IAU scheme.Theresults demonstrate the superiority of the multi-scale IAU scheme.Key words:multi-scale incremental analysis updates,optimal relaxation time,2-D discrete cosine transform,GRAPES_Meso,Typhoon Mangkhut(2018)Citation:Gao,Y.,J.L.Feng,X.Xia,J.Sun,Y.L.Ma,D.M.Chen,and Q.L.Wan,2023:Multi-scale incremental analysisupdate scheme and its application to Typhoon Mangkhut(2018)prediction.Adv.Atmos.Sci.,40(1),95109,https:/doi.org/10.1007/s00376-022-1425-7.Article Highlights:A multi-scale incremental analysis update(IAU)scheme was proposed in this paper for the first time.For the adopted multi-scale IAU scheme,the optimal relaxation time for large-scale and small-scale increments wasestimated at 6 h and 3 h,respectively.The performance of the multi-scale IAU scheme in the prediction of Typhoon Mangkhut(2018)was better than that ofthe traditional IAU scheme.1.IntroductionIn terms of spatial coverage,numerical models can beclassified into two major categories:global models andregional models.Both have unique advantages in describinganalysis information at different scales.Because global analy-sis is not affected by biases at lateral boundaries,the large-scale aspect of global analysis is superior to the aspect ofregional analysis(Peng et al.,2010;Zhuang et al.,2020).However,after assimilating observation data with high spatialdensity,the regional analysis may yield a more accuratesmall-scale analysis(Zhuang et al.,2018).To improve theforecasting performance of a regional model,one possibleapproach is to use a blending technique,which includes anincremental spatial filter to blend large-scale analysis fromthe global model with small-scale fields from the high-resolu-*Corresponding author:Qilin WANEmail:ADVANCES IN ATMOSPHERIC SCIENCES,VOL.40,JANUARY 2023,95109 Original Paper Institute of Atmospheric Physics/Chinese Academy of Sciences,and Science Press and Springer-Verlag GmbH Germany,part of Springer Nature 2023tion regional model(Denis et al.,2002;Yang,2005;Hsiaoet al.,2015).Although the advantages of the blending techniquehave been collectively presented by some previous studies(Keresturi et al.,2019;Feng et al.,2021),this method stillhas some limitations in short-term forecasts,such as short-term precipitation climatology,likely owing to the imbalancebetween large-scale analysis from the global model andsmall-scale analysis from the regional model(Polavarapu etal.,2004;Schwartz et al.,2021).To further improve the per-formance of the blending technique,it is necessary toemploy some strategies to combat this imbalance.One effec-tive method to accomplish this task is to apply an incrementalanalysis update(IAU)technique.Bloom et al.(1996)first pro-posed the IAU technique,which gradually incorporated theanalysis increment.Since this technique emerged,it hasbeen widely used in the atmospheric and oceanic fields andis considered to be su