Advances in Atmospheric Sciences

The aim of the present study was to identify multi-decadal variability (MDV) relative to the current centennial global warming trend in available observation data. The centennial global warming trend was first identified in the global mean surface temperature (STgm) data. The MDV was identified based on three sets of climate variables, including sea surface temperature (SST), ocean temperature from the surface to 700 m, and the NCEP and ERA40 reanalysis datasets, respectively. All variables were detrended and low-pass filtered. Through three independent EOF analyses of the filtered variables, all results consistently showed two dominant modes, with their respective temporal variability resembling the Pacific Decadal Oscillation/Inter-decadal Pacific Oscillation (PDO/IPO) and the Atlantic Multi-decadal Oscillation (AMO). The spatial structure of the PDO-like oscillation is characterized by an ENSO-like structure and hemispheric symmetric features. The structure associated with the AMO-like oscillation exhibits hemispheric asymmetric features with anomalous warm air over Eurasia and warm SST in the Atlantic and Pacific basin north of 10°S, and cold SST over the southern oceans. The Pacific and Atlantic MDV in upper-ocean temperature suggest that they are mutually linked. We also found that the PDO-like and AMO-like oscillations are almost equally important in global-scale MDV by EOF analyses. In the period 1975–2005, the evolution of the two oscillations has given rise to strong temperature trends and has contributed almost half of the STgm warming. Hereon, in the next decade, the two oscillations are expected to slow down the global warming trends.

Variation in length of day of the Earth (LOD, equivalent to the Earth’s rotation rate) versus change in atmospheric geopotential height fields and astronomical parameters were analyzed for the years 1962–2006. This revealed that there is a 27.3-day and an average 13.6-day periodic oscillation in LOD and atmospheric pressure fields following lunar revolution around the Earth. Accompanying the alternating change in celestial gravitation forcing on the Earth and its atmosphere, the Earth’s LOD changes from minimum to maximum, then to minimum, and the atmospheric geopotential height fields in the tropics oscillate from low to high, then to low. The 27.3-day and average 13.6-day periodic atmospheric oscillation in the tropics is proposed to be a type of strong atmospheric tide, excited by celestial gravitation forcing. A formula for a Tidal Index was derived to estimate the strength of the celestial gravitation forcing, and a high degree of correlation was found between the Tidal Index determined by astronomical parameters, LOD, and atmospheric geopotential height. The reason for the atmospheric tide is periodic departure of the lunar orbit from the celestial equator during lunar revolution around the Earth. The alternating asymmetric change in celestial gravitation forcing on the Earth and its atmosphere produces a “modulation” to the change in the Earth’s LOD and atmospheric pressure fields.

Continuous periodogram analyses of two 50-years (1871–1920 and 1936–1985) of summer monsoon rainfall over the Indian region and one 84-years set (1893–1976) of winter half-year rainfall over England and Wales show that the power spectra of disparate rainfall regimes follow the universal and unique inverse power law form of the statistical normal distribution with the percentage contribution to total variance representating the eddy probability corresponding to the normalized standard deviation equal to [(log L/logT 50)−1] whereL is the period in years andT 50 the period up to which the cumulative percentage contribution to total variance is equal to 50. The above results are consistent with a recently developed non-deterministic cell dynamical system model for atmospheric flows. The implications of the above results for prediction of interannual variability of rainfall is discussed.

Decadal rainfall data of 228 stations in 1951–1970 and upper-wind records in 1960–1969 published by the Central Meteorological Bureau and relevant provincial organizations are employed in the analysis. It is found that the characteristic features of seasonal variation of the main rain-belts over eastern China to the east of 105°F are quite different from those to the west, over the Qinghai-Xizhang (Tibetan) Plateau. The eastern rain-belts are closely related to the low level flow convergence lines and significantly influenced by the south Asian high and the western Pacific subtropical high.

Large biases exist in real-time ENSO prediction, which can be attributed to uncertainties in initial conditions and model parameters. Previously, a 4D variational (4D-Var) data assimilation system was developed for an intermediate coupled model (ICM) and used to improve ENSO modeling through optimized initial conditions. In this paper, this system is further applied to optimize model parameters. In the ICM used, one important process for ENSO is related to the anomalous temperature of subsurface water entrained into the mixed layer (Te), which is empirically and explicitly related to sea level (SL) variation. The strength of the thermocline effect on SST (referred to simply as “the thermocline effect”) is represented by an introduced parameter, αTe. A numerical procedure is developed to optimize this model parameter through the 4D-Var assimilation of SST data in a twin experiment context with an idealized setting. Experiments having their initial condition optimized only, and having their initial condition plus this additional model parameter optimized, are compared. It is shown that ENSO evolution can be more effectively recovered by including the additional optimization of this parameter in ENSO modeling. The demonstrated feasibility of optimizing model parameters and initial conditions together through the 4D-Var method provides a modeling platform for ENSO studies. Further applications of the 4D-Var data assimilation system implemented in the ICM are also discussed.

Based on the theory of reconstructing state space, a technique for spatiotemporal series prediction is presented. By means of this technique and NCEP/NCAR data of the monthly mean geopotential height anomaly of the 500-hPa isobaric surface in the Northern Hemisphere, a regional prediction experiment is also carried out. If using the correlation coefficientR between the observed field and the prediction field to measure the prediction accuracy, the averagedR given by 48 prediction samples reaches 21%, which corresponds to the current prediction level for the short range climate process.

This study reexamines the propagation mechanism and geostrophic property of the classical two dimensional Rossby waves in a non-divergent barotropic atmosphere. It will be found that propagation of large scale atmospheric waves depends crucially on horizontal divergence. A small Rossby number in Rossby waves is not sufficient for the waves to have a small ageostrophic component, because the two dimensional classical Rossby waves do not manifest the geostrophic balance as good as observed in the atmosphere.

The water and energy cycle in the Tibetan Plateau is an important component of Monsoon Asia and the global energy and water cycle. Using data at a CEOP (Coordinated Enhanced Observing Period)-Tibet site, this study presents a first-order evaluation on the skill of weather forecasting from GCMs and satellites in producing precipitation and radiation estimates. The satellite data, together with the satellite leaf area index, are then integrated into a land data assimilation system (LDAS-UT) to estimate the soil moisture and surface energy budget on the Plateau. The system directly assimilates the satellite microwave brightness temperature, which is strongly affected by soil moisture but not by cloud layers, into a simple biosphere model. A major feature of this system is a dual-pass assimilation technique, which can auto-calibrate model parameters in one pass and estimate the soil moisture and energy budget in the other pass. The system outputs, including soil moisture, surface temperature, surface energy partition, and the Bowen ratio, are compared with observations, land surface models, the Global Land Data Assimilation System, and four general circulation models. The results show that this satellite data-based system has a high potential for a reliable estimation of the regional surface energy budget on the Plateau.