Rain gauge data for the period of 1998–2004 from the Syangboche Automated Weather Station (S-AWS) site in the Nepal Himalayas were compared with multi-satellite precipitation products for the period of 2003–2005, employing several retrieval algorithms: the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA), the Climate Prediction Center (CPC) morphing algorithm (CMORPH), the Precipitation Estimation from Remote Sensing Information using an artificial neural network (PERSIANN), and the Global Satellite Mapping of Precipitation (GSMaP). All the products, except GSMaP, showed an increase in precipitation during the summer monsoon, in agreement with S-AWS. However, PERSIANN showed large differences with the observed values in winter and CMORPH had a tendency to overestimate precipitation in the pre- and post-monsoon seasons relative to S-AWS/TMPA. Summer monsoon precipitation showed an increase in the evening and mid-night in all products except GSMaP, but the local-time peak in PERSIANN lagged compared to that of S-AWS by several hours, and the peak in other products was ahead of that in S-AWS by several hours. All products except for PERSIANN showed an increase in precipitation during the morning. The differences among the products may reflect microwave signatures from convection, the sun-synchronous satellite orbit, and infrared-merging processes. A verification of rain detection by GSMaP revealed good scores over global land areas except for the Tibetan Plateau (including the present study area) due to insufficient resolution for rain/no-rain classification. The peak local-time distribution of precipitation showed a relationship with the topography in the order of precipitation radar (strongest relationship), microwave radiometer, and infrared products.
In this paper, we propose a new approach to four-dimensional variational data assimilation (4DVar) with analysis of the initial condition (IC) at the end of assimilation window. The new approach is referred to as “backward 4DVar (B-4DVar).” The minimization of its cost function is fulfilled through an ensemble of historical prediction samples. B-4DVar is computationally efficient because it does not use tangent linear or adjoint models. To prepare it for numerical weather prediction, a B-4DVar assimilation system is developed based on an operational regional prediction model, the Advanced Regional Eta Model (AREM). Two single observation experiments (SOEs) and an observing system simulation experiment (OSSE) are conducted to evaluate the system. The SOEs reveal a characteristic of flow dependence in B-4DVar, which is consistent with statistical estimation of the background error covariance matrix (simply B-matrix) using a group of IC-reliant historical prediction samples. The OSSE suggests that the B-4DVar approach improves the analytic quality of IC by effectively incorporating conventional observations, thereby outperforming the 3DVar. The time-saving feature, flow dependence in B-matrix, and good performance in assimilating conventional observations indicate the potential and feasibility of B-4DVar in operational use.
The major features of Baiu simulated by the climate model (MIROC_Hires) are examined by analyzing the differences between simulations and the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis data during 1981–2000, focusing on the evaluation of the model performances in reproducing the Baiu precipitation climatology as well as the associated 3-dimensional circulation systems, the relationship with Indian Summer Monsoon (ISM) and the configuration of upper and lower level jets. The results show that the model can reproduce heavy precipitation centers over the Yangtze-Huai River Basin during the Baiu period. The horizontal and vertical structures of the circulation systems during the Baiu period are also well simulated, such as an intensive meridional gradient of moisture and it’s equivalent potential temperature, the strong low-level southwesterly flow in the lower troposphere over East China, the location of the westerly jet in the upper troposphere, the strong ascending motion over heavy rainfall area (HRA) and compensatory descending motion over the northern and southern sides of HRA. However, obvious discrepancies occur in the overestimated precipitation over southeastern China during the Baiu period. In addition, our study suggests that the biases of the ISM and the configuration of upper and lower level jet results in deficiencies in the evolution of Baiu. The simulated onset of ISM is one pentad later than the reanalysis data, while the onset day of simulated Baiu is one pentad later than the reanalysis data, as well. The simulation showed southward shifting of the upper level jet and the stronger, lower level jet. These location and intensity biases essentially favor excess precipitation in southeastern China. Therefore, it is necessary for the coupled model to improve the configuration of upper and lower level jets in simulating the Baiu.
An explosive cyclogenesis over the east coast of South America was simulated during the period from 28 to 30 May 1999, using a limited-area hydrostatic model with 100 km horizontal resolution. The simulations showed that surface heat flux had an important contribution in developing the explosive cyclogenesis, and that the latent heat flux (LHF) has a larger contribution than the sensible heat flux (SHF). In the absence of a total heat flux (THF, ie. LHF plus SHF), the cyclone was 6 hPa shallower than in the control simulation (with THF). Without LHF the cyclone was 4 hPa shallower, while without SHF the cyclone presented the same intensity as the control simulation. The sensitivity experiments show the following effects of surface heat fluxes: i) the magnitudes and extensions of the effects grew with simulation time; ii) the maximum effects appeared in the southeastern part of the cyclone (warm front sector); iii) the LHF effects were 2–3 times larger than the SHF ones; and iv) the LHF effects were observed in the neighborhood of the cyclone, while the SHF effects were more spread out over the domain. In the THF absent experiment, a drier and colder environment was generated, mainly in the lower troposphere over the ocean, decreasing the environmental potential instability, latent heat release and cyclone intensification. Although the THF effects became larger during the most rapid development phase, they must have been present before this period because they preconditioned the environment for explosive development. Thus, to simulate or forecast the explosive cyclogenes on the South American east coast, an adequate representation of the planetary boundary layer is necessary.