Low-Delay Loop Detection Algorithm for LDPC Codes

Abstract:A low-delay loop detection algorithm for bit-flipping based iteration LDPC decoding is proposed.By introducing the concept of loop characteristic,only the iteration steps with loop characteristics are detected and labeled for the subsequent loop detection.As a result,computation delay is greatly reduced.Furthermore,the position vector for the selected iteration steps is also established to implement loop detection for these iteration steps,which reduces the hardware cost of the loop detection as well.The validity of the proposed algorithm is verified by simulations.

Associations between the Autumn Arctic Sea Ice and North American Winter Precipitation

Associations between the autumn Arctic sea ice concentrations (SICs) and North American winter precipitation were examined using singular value decomposition. The results show that a reduced SIC in the majority of the Arctic is accompanied by dry conditions over the Great Plains, the southern United States, Mexico, eastern Alaska, and southeastern Greenland, and by wet conditions over the majority of Canada, the northeastern United States, and the majority of Greenland. Atmospheric circulation anomalies associated with the SIC variability show a wave train structure that is persistent from autumn to winter and is responsible for the covariability between the autumn Arctic SICs and North American winter precipitation. This relationship suggests a potential long-term outlook for the North American winter precipitation.

Detecting sand-dust storms using a wind-profiling radar

Sand-dust storm is a type of disastrous weather, typically occurring in arid and semi-arid climates. This study selected a region in the hinterlands of the Taklimakan Desert, called the Tazhong region, as the experimental area to quantitatively estimate the particle concentrations of sand-dust storms using the boundary layer wind-profiling radar. We thoroughly studied the radar echo signals and reflectivity factor features during the sand-dust storms. The results indicate that（1） under sand-dust storm conditions, boundary layer wind-profiling radar cannot capture the complete information regarding horizontal wind velocity and direction, but it can obtain the backscattering intensity of sand-dust storms; and（2） during sand-dust storms particle size distributions in the surface layer closely resemble log-normal distributions, with sand-dust particles sizes of 90–100 μm accounting for the maximum particle probability. Retrieved particle size distributions at heights of 600, 800, and 1000 m follow log-normal distributions, and the expected value of particle diameter decreases gradually with increasing height. From the perspective of orders of magnitude, the retrieved results for particle number concentrations and mass concentrations are consistent with previous aircraft-detected results, indicating that it is basically feasible to use boundary layer wind-profiling radar to quantitatively detect the particle concentrations of dust storms.

Low-Level Wind Shear Characteristics and Lidar-Based Alerting at Lanzhou Zhongchuan International Airport,China

Lanzhou Zhongchuan International Airport[International Civil Aviation Organization(ICAO)code ZLLL]is located in a wind shear prone area in China,where most low-level wind shear events occur in dry weather conditions.We analyzed temporal distribution and synoptic circulation background for 18 dry wind shear events reported by pilots at ZLLL by using the NCEP final(FNL)operational global analysis data,and then proposed a lidar-based regional divergence algorithm(RDA)to determine wind shear intensity and location.Low-level wind shear at ZLLL usually occurs in the afternoon and evening in dry conditions.Most wind shear events occur in an unstable atmosphere over ZLLL,with changes in wind speed or direction generally found at 700 hPa and 10-m height.Based on synoptic circulations at 700 hPa,wind shear events could be classified as strong northerly,convergence,southerly,and weak wind types.The proposed RDA successfully identified low-level wind shear except one southerly case,achieving94%alerting rate compared with 82%for the operational system at ZLLL and 88%for the ramp detection algorithm(widely used in some operational alert systems)based on the same dataset.The RDA-unidentified southerly case occurred in a near neutral atmosphere,and wind speed change could not be captured by the Doppler lidar.

Analysis of the Microphysical Properties of a Stratiform Rain Event Using an L-Band Profiler Radar

This paper investigates spatial and temporal distributions of the microphysical properties of precipitating stratiform clouds based on Doppler spectra of rain particles observed by an L-band profiler radar.The retrieval of raindrop size distributions（RSDs） is accomplished through eliminating vertical air motion and isolating the terminal fall velocity of raindrops in the observed Doppler velocity spectrum.The microphysical properties of raindrops in a broad stratiform region with weak convective cells are studied using data collected from a 1320-MHz wind profiler radar in Huayin,Shaanxi Province on 14 May 2009.RSDs and gamma function parameters are retrieved at altitudes between 700 and 3000 m above the surface,below a melting layer.It is found that the altitude of the maximum number of raindrops was closely related to the surface rain rate.The maximum number of large drops was observed at lower altitudes earlier in the precipitation event but at higher altitudes in later periods,suggesting decreases in the numbers of large and medium size raindrops.These decreases may have been caused by the breakup of larger drops and evaporation of smaller drops as they fell.The number of medium size drops decreased with increasing altitude.The relationship between reflectivity and liquid water content during this precipitation event was Z = 1.69×10~4M^（1.5）,and the relationship between reflectivity and rain intensity was Z = 256I^（1.4）.