Proactive Quality Control based on Ensemble Forecast Sensitivity to Observations

Despite recent major improvements in numerical weather prediction (NWP) systems, operational NWP forecasts occasionally suffer from an abrupt drop in forecast skill, a phenomenon called "forecast skill dropout." Recent studies have shown that the "dropouts" occur not because of the model's deficiencies but by the use of flawed observations that the operational quality control (QC) system failed to filter out. Thus, to minimize the occurrences of forecast skill dropouts, we need to detect and remove such flawed observations. A diagnostic technique called Ensemble Forecast Sensitivity to Observations (EFSO) enables us to quantify how much each observation has improved or degraded the forecast. A recent study (Ota et al., 2013) has shown that it is possible to detect flawed observations that caused regional forecast skill dropouts by using EFSO with 24-hour lead-time and that the forecast can be improved by not assimilating the detected observations. Inspired by their success, in the first part of this study, we propose a new QC method, which we call Proactive QC (PQC), in which flawed observations are detected 6 hours after the analysis by EFSO and then the analysis and forecast are repeated without using the detected observations. This new QC technique is implemented and tested on a lower-resolution version of NCEP's operational global NWP system. The results we obtained are extremely promising; we have found that we can detect regional forecast skill dropouts and the flawed observations after only 6 hours from the analysis and that the rejection of the identified flawed observations indeed improves 24-hour forecasts. In the second part, we show that the same approximation used in the derivation of EFSO can be used to formulate the forecast sensitivity to observation error covariance matrix R, which we call EFSR. We implement the EFSR diagnostics in both an idealized system and the quasi-operational NWP system and show that it can be used to tune the R matrix so that the utility of observations is improved. We also point out that EFSO and EFSR can be used for the optimal assimilation of new observing systems

Seal Mechanism of Tip Seal in Scroll Compressor

Scroll compressors are widely used in room air conditioning cycles, package air conditioning cycles, refrigeration, water heater and automobile air conditioning cycles as well as air compressors, helium compressors and vacuum pump. There are two main leakage paths in a compression chamber formed by a fixed scroll and an orbiting scroll. One is the leakage path through a radial clearance between the wraps of fixed and orbiting scroll. The leakage through the radial clearance is prevented by pressing the orbiting scroll radially against the fixed scroll by a mechanism such as a compliance mechanism. Oil inside the compression chamber also has the sealing effect and reduces the leakage through the radial clearance. Another leakage path is an axial clearance which is the clearance between a tip of the scroll wrap and a base plate. A tip seal is often used to prevent the leakage through the axial clearance. Although there have been many studies on the tip seal, the seal mechanism of the tip seal is not thoroughly clarified yet, and the influence of design parameters on efficiency of the tip seal is unclear. In addition, the relationship between the sealing effect and a frictional loss of the tip seal is also not validated well. In this study, a test apparatus which can evaluate the sealing effect and the frictional loss of the tip seal simultaneously is developed. The influence of several design parameters on the sealing effect and the frictional loss is examined with the test apparatus. By measuring pressure distribution around the tip seal in a tip seal groove, the sealing mechanism of the tip seal is clarified and a design guideline of the tip seal groove is obtained