Evaluation Of The Sub-seasonal Forecast Skill Of Surface Soil Moisture In China In S2S Database

Sub-seasonal to seasonal(S2S)prediction skills of surface soil moisture(0-20cm)during May-September over China are evaluated against ERA-I reanalysis based on reforecast of five models in the S2 S prediction project.Results show that the effective prediction skill of most of the models are generally before 5-10 days over southern China and northeastern China.Over the Tibetan Plataea and northwestern China,only ECMWF model has good prediction skill before about 20 days.This is probably because very high prediction skill is over western Tibetan Plateau and western Mongolia,where observation is very rare.Generally,good prediction skill tends to appear over wet regions than dry regions.For the seasonal variation of SM prediction skill,some uncertainties can be noticed,but most of the models show good prediction skill during September.Most of the models in the S2 S prediction project have better forecast skill than soil moisture,and good forecast skilly also tends to appear over wet regions than dry regions.For other land surface variables in NCEP model,the forecast skill of skin temperature is the best in all regions of China,and the forecast skill of wind is better than that of radiation,but the forecast skill at initial time of radiation field is higher.For the key factors affecting the forecast skill of S2 S soil moisture,the factors of each model have different performances in different regions,but in most models,the forecast skill of precipitation have greater influence on the forecast skill of soil moisture in wet areas.However,the forecast skill of surface thermal raditation downwards and surface solar radiation downwards in Tibetan Plataea have obvious influence on the forecast skill of soil moisture,which may be due to the strong radiation in plateau area and the greater impact on land surface process.The forecast skill of skin temperature in northeast China have a great influence on the forecast skill of soil moisture,while the main factor affecting the forecast skill of soil moisture in northwest China is the forecast skill of wind field.Prediction skill that shows no consistence during different ENSO years among the five models.There are great differences in the Tibetan Plataea and the arid area of northwest China.This also indicates large uncertainty of the modulation of ENSO on sub-seasonal prediction skill of soil moisture.However,ENSO has little influence on precipitation forecast skills,the influence mainly concentrated in arid areas of northwest China.The positive range of CMA model is the most significant by using ONI index regression for soil moisture forecast skill.Through the evaluation of S2 S prediction skill of soil moisture,it can benoticed that the prediction skill of soil moisture is lower than most of the atmospheric variables in S2 S forecast.Therefore,more attention should be given to the land-processes sub-seasonal forecast.