Subseasonal Prediction of Early-summer Northeast Asian Cut-off Lows by BCC-CSM2-HR and GloSea5

Northeast Asian cut-off lows are crucial cyclonic systems that can bring temperature and precipitation extremes over large areas.Skillful subseasonal forecasting of Northeast Asian cut-off lows is of great importance.Using two dynamical forecasting systems,one from the Beijing Climate Center(BCC-CSM2-HR)and the other from the Met Office(GloSea5),this study assesses simulation ability and subseasonal prediction skill for early-summer Northeast Asian cut-off lows.Both models are shown to have good ability in representing the spatial structure of cut-off lows,but they underestimate the intensity.The skillful prediction time scales for cut-off low intensity are about 10.2 days for BCC-CSM2-HR and 11.4 days for GloSea5 in advance.Further examination shows that both models can essentially capture the initial Rossby wave train,rapid growth and decay processes responsible for the evolution of cut-off lows,but the models show weaker amplitudes for the three-stage processes.The underestimated simulated strength of both the Eurasian midlatitude and East Asian subtropical jets may lead to the weaker local eddy-mean flow interaction responsible for the cut-off low evolution.

Estimation of ground heat flux and its impact on the surface energy budget for a semi-arid grassland

Three approaches, i.e., the harmonic analysis （HA） technique, the thermal diffusion equation and correction （TDEC） method, and the calorimetric method used to estimate ground heat flux, are evaluated by using observations from the Semi-Arid Climate and Environment Observatory of Lanzhou University （SACOL） in July, 2008. The calorimetric method, which involves soil heat flux measurement with an HFP01SC self-calibrating heat flux plate buried at a depth of 5 cm and heat storage in the soil between the plate and the surface, is here called the ITHP approach. The results show good linear relationships between the soil heat fluxes measured with the HFP01SC heat flux plate and those calculated with the HA technique and the TDEC method, respectively, at a depth of 5 cm. The soil heat fluxes calculated with the latter two methods well follow the phase measured with the HFP01SC heat flux plate. The magnitudes of the soil heat flux calculated with the HA technique and the TDEC method are close to each other, and they are about 2 percent and 6 percent larger than the measured soil heat flux, respectively, which mainly occur during the nighttime. Moreover, the ground heat fluxes calculated with the TDEC method and the HA technique are highly correlated with each other （R2= 0.97）, and their difference is only about 1 percent. The TDEC-calculated ground heat flux also has a good linear relationship with the ITttP-calculated ground heat flux （R2 = 0.99）, but their difference is larger （about 9 percent）. Furthermore, compared to the HFP01SC direct measurements at a depth of 5 cm, the ground heat flux calculated with the HA technique, the TDEC method, and the ITHP approach can improve the surface energy budget closure by about 6 percent, 7 percent, and 6 percent at SACOL site, respectively. Therefore, the contribution of ground heat flux to the surface energy budget is very important for the semi-arid grassland over the Loess Plateau in China. Using turbulent heat fluxes with common corrections, soil heat storage between the surface and the heat flux plate can improve the surface energy budget closure by about 6 to 7 percent, resulting in a closure of 82 to 83 percent at the SACOL site.

Prediction of Primary Climate Variability Modes at the Beijing Climate Center

Climate variability modes, usually known as primary climate phenomena, are well recognized as the most impor- tant predictability sources in subseasonal-interarmual climate prediction. This paper begins by reviewing the re- search and development carried out, and the recent progress made, at the Beijing Climate Center （BCC） in predicting some primary climate variability modes. These include the El Nifio-Southern Oscillation （ENSO）, Madden-Julian Oscillation （MJO）, and Arctic Oscillation （AO）, on global scales, as well as the sea surface temperature （SST） modes in the Indian Ocean and North Atlantic, western Pacific subtropical high （WPSH）, and the East Asian winter and summer monsoons （EAWM and EASM, respectively）, on regional scales. Based on its latest climate and statistical models, the BCC has established a climate phenomenon prediction system （CPPS） and completed a hindcast experi- ment for the period 1991-2014. The performance of the CPPS in predicting such climate variability modes is system- atically evaluated. The results show that skillful predictions have been made for ENSO, MJO, the Indian Ocean basin mode, the WPSH, and partly for the EASM, whereas less skillful predictions were made for the Indian Ocean Dipole （IOD） and North Atlantic SST Tripole, and no clear skill at all for the AO, subtropical IOD, and EAWM. Improve- ments in the prediction of these climate variability modes with low skill need to be achieved by improving the BCC＇s climate models, developing physically based statistical models as well as correction methods for model predictions. Some of the monitoring/prediction products of the BCC-CPPS are also introduced in this paper.