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Xiao-yong Zhuge
,
Fan Yu
, and
Ye Wang

Abstract

A new visible (VIS; 0.55–0.9 μm) albedo normalization method, that is, the quasi-Lambertian surface adjustment (QLSA), is developed herein by using the geostationary meteorological satellite data and radiative transfer model. Taking the variation of relative locations between the sun, satellite, and clouds into account, the QLSA effectively reduces the inconsistencies in the VIS image brightness caused by the Lambertian surface approximation to cloud tops (i.e., the reflection characteristic is isotropic). The evaluation, using Chinese and Japanese geostationary satellite data, shows that the QLSA is more effective and accurate than three other albedo normalization methods currently in use. The new algorithm is applicable in regions with solar zenith angle and satellite zenith angle less than 60°, which, in the summertime, approximately corresponds to the time range from 0800 to 1600 local time (LT).

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Xiao-Yong Zhuge
,
Jie Ming
, and
Yuan Wang

Abstract

The hot tower (HT) in the inner core plays an important role in tropical cyclone (TC) rapid intensification (RI). With the help of Tropical Rainfall Measurement Mission (TRMM) data and the Statistical Hurricane Intensity Prediction Scheme dataset, the potential of HTs in operational RI prediction is reassessed in this study. The stand-alone HT-based RI prediction scheme showed little skill in the northern Atlantic (NA) and eastern and central Pacific (ECP), but yielded skill scores of >0.3 in the southern Indian Ocean (SI) and western North Pacific (WNP) basins. The inaccurate predictions are due to four scenarios: 1) RI events may have already begun prior to the TRMM overpass. 2) RI events are driven by non-HT factors. 3) The HT has already dissipated or has not occurred at the TRMM overpass time. 4) Large false alarms result from the unfavorable environment. When the HT was used in conjunction with the TC’s previous 12-h intensity change, the potential intensity, the percentage area from 50 to 200 km of cloud-top brightness temperatures lower than −10°C, and the 850–200-hPa vertical shear magnitude with the vortex removed, the predictive skill score in the SI was 0.56. This score was comparable to that of the RI index scheme, which is considered the most advanced RI prediction method. When the HT information was combined with the aforementioned four environmental factors in the NA, ECP, South Pacific, and WNP, the skill scores were 0.23, 0.32, 0.42, and 0.42, respectively.

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Yong Wang
,
Guang J. Zhang
, and
Yiquan Jiang

abstract

The Plant–Craig (PC) stochastic convective parameterization scheme is modified by linking the stochastic generation of convective clouds to the change of large-scale vertical pressure velocity at 500 hPa with time so as to better account for the relationship between convection and the large-scale environment. Three experiments using the National Center for Atmospheric Research (NCAR) Community Atmosphere Model, version 5 (CAM5), are conducted: one with the default Zhang–McFarlane deterministic convective scheme, another with the original PC stochastic scheme, and a third with the modified PC stochastic scheme. Evaluation is focused on the simulation of the Indian summer monsoon (ISM), which is a long-standing challenge for all current global circulation models. Results show that the modified stochastic scheme better represents the annual cycle of the climatological mean rainfall over central India and the mean onset date of ISM compared to other simulations. Also, for the simulations of ISM intraseasonal variability for quasi-biweekly and 30–60-day modes, the modified stochastic parameterization produces more realistic propagation and magnitude, especially for the observed northeastward movement of the 30–60-day mode, for which the other two simulations show the propagation in the opposite direction. Causes are investigated through a moisture budget analysis. Compared to the other two simulations, the modified stochastic scheme with an appropriate representation of convection better represents the patterns and amplitudes of large-scale dynamical convergence and moisture advection and thus corrects the monsoon cycle associated with their covariation during the peaks and troughs of intraseasonal oscillation.

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Martin Bellus
,
Yong Wang
, and
Florian Meier

Abstract

Two techniques for perturbing surface initial conditions in the regional ensemble system Aire Limitée Adaptation Dynamique Développement International-Limited Area Ensemble Forecasting (ALADIN-LAEF) are presented and investigated in this paper. The first technique is the noncycling surface breeding (NCSB), which combines short-range surface forecasts driven by perturbed atmospheric forcing and the breeding method for generating the perturbations on surface initial conditions. The second technique, which is currently used in the ALADIN-LAEF operational version, applies an ensemble of surface data assimilations (ESDA) in which the observations are randomly perturbed. Both techniques are evaluated over a two-month period from late spring to summer. The results show that the evaluation is more favorable to ESDA. In general, the ensemble forecasts of the observed near-surface meteorological variables (screen-level variables) of ESDA are more skillful than NCSB, in particular for 2-m temperature they are statistically more consistent and reliable. A slightly better statistical reliability for 2-m relative humidity and 10-m wind has been found as well. This could be attributed to the introduction of surface data assimilation in ESDA, which provides more accurate surface initial conditions. Moreover, the observation perturbation in ESDA helps to better estimate the initial condition uncertainties. For the forecast of precipitation and the upper-air variables in the lower troposphere, both ESDA and NCSB perform very similarly, having neutral impact.

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Florian Weidle
,
Yong Wang
, and
Geert Smet

Abstract

It is quite common that in a regional ensemble system the large-scale initial condition (IC) perturbations and the lateral boundary condition (LBC) perturbations are taken from a global ensemble prediction system (EPS). The choice of global EPS as a driving model can have a significant impact on the performance of the regional EPS. This study investigates the impact of large-scale IC/LBC perturbations obtained from different global EPSs on the forecast quality of a regional EPS. For this purpose several experiments are conducted where the Aire Limitée Adaption dynamique Développement International–Limited Area Ensemble Forecasting (ALADIN-LAEF) regional ensemble is forced by two of the world’s leading global ensembles, the European Centre for Medium-Range Weather Forecasts’ Ensemble Prediction System (ECMWF-EPS) and the Global Ensemble Forecasting System (GEFS) from the National Centers for Environmental Prediction (NCEP), which provide the IC and LBC perturbations. The investigation is carried out for a 51-day period during summer 2010 over central Europe. The results indicate that forcing of the regional ensemble with GEFS performs better for surface parameters, whereas at upper levels forcing with ECMWF-EPS is superior. Using perturbations from GEFS lead to a considerably higher spread in ALADIN-LAEF, which is beneficial near the surface where regional EPSs are usually underdispersive. At upper levels, forcing with GEFS leads to an overdispersion of ALADIN-LAEF as a result of the large spread of some parameters, where forcing ALADIN-LAEF with ECMWF-EPS provides statistically more reliable forecasts. The results indicate that the best global EPS might not always provide the best ICs and LBCs for a regional ensemble.

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Zhi-Yong Yin
,
Hongli Wang
, and
Xiaodong Liu

Abstract

This study examines precipitation climatology and interannual variability in two regions in the lower midlatitude Asia to the east and west of the Tibetan Plateau, one located in monsoonal East Asia (the M region) and the other in semiarid central Asia (the W region). The focus is on the 5-month summer half year (May–September) for the M region and the winter half year (December–April) for the W region, corresponding to their respective rainy seasons. The main mechanism of moisture transport for the M region is the summer lower-tropospheric southerly winds, whereas the winter midtropospheric westerly circulation between 25° and 45°N is responsible for conducting moisture fluxes to the W region. It is further discovered that the winter precipitation series are positively correlated between the two regions (r = 0.47). There is also a weak cross-seasonal correlation between the winter W region precipitation and summer M region precipitation (r = 0.27). Winter westerly circulation over the W region is influenced by both the east Atlantic–western Russia and the polar–Eurasia extratropical teleconnection patterns, while El Niño–Southern Oscillation influences regional circulation patterns in both regions through teleconnections via the Indo-Pacific warm pool convection in winter and its lagged impact on the western North Pacific anticyclone over the Philippine Sea. In the meantime, responses of the regional winter circulation in the M region to the upstream westerly circulation intensity cause the correlation in winter precipitation between the two regions. Such linkages form the basis of the concurrent and cross-seasonal correlations in precipitation between the two remote regions.

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Jin-Ming Feng
,
Yong-Li Wang
,
Zhu-Guo Ma
, and
Yong-He Liu

Abstract

Together with economic development and accelerated urbanization, the urban population in China has been increasing rapidly, and anthropogenic heat released by large-scale energy consumption in cities is expected to be a vital factor affecting the climate. In this paper, the Weather Research and Forecasting (WRF) model coupled with the Urban Canopy Model (UCM) is employed to simulate the regional impacts on climate under the two scenarios: the underlying surface changes due to urbanization (USCU) and anthropogenic heat release (AHR). Three experiments were performed from December 2006 to December 2008. With respect to the USCU, the surface albedo and the available surface soil water decrease markedly. With the inclusion of AHR, the two scenarios give rise to increased surface temperatures over most areas of China. Especially in the urban agglomeration area of the Yangtze River delta, the combination of USCU and AHR could result in an increase of 2°C in the surface air temperature. The influence of AHR on surface air temperature in winter is greater than the influence of USCU without considering any extra sources of heat, but the opposite is found in summer. The combination of USCU and AHR leads to changes in the surface energy budget. They both increase sensible heat flux, but USCU decreases latent heat flux significantly, and AHR increases latent heat flux slightly. Nevertheless, under the influence of these two scenarios, the precipitation increases in some areas, especially in the Beijing–Tianjin–Hebei region, while it decreases in other areas, most notably the Yangtze River delta.

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Jinfeng Ding
,
Xiao-Yong Zhuge
,
Yuan Wang
, and
Anyuan Xiong

Abstract

Aircraft Meteorological Data Relay (AMDAR) weather reports are a type of high spatiotemporal data currently widely used in weather monitoring and prediction. A recent Chinese AMDAR project began in 2003 has made rapid progress. However, the assessment and accuracy of these Chinese AMDAR reports have yet to be thoroughly discussed. A comparison of temperature and wind observations between Chinese AMDAR reports and rawinsonde data between 2004 and 2010 is conducted in this paper. Results demonstrate that the root-mean-square error (RMSE) between these two sets of data is 1.40°C for temperature, 3.56 m s−1 for wind speed, and 28° for wind direction. Because of the particularity of observation and inversion method, comparison results are not only affected by AMDAR measurement and reporting error but also by spatial and temporal representativeness, flight phases, and the environment. This evaluation helps create a complete estimation of the accuracy of Chinese AMDAR in order to assist with data assimilation.

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Zhang Chen
,
Renguang Wu
,
Yong Zhao
, and
Zhibiao Wang

Abstract

The present study investigated impacts of strong and weak El Niño events on central Asian precipitation variability from El Niño developing years to decaying years. It is found that strong El Niño events persistently enhance central Asian precipitation from the mature winter to decaying summer. Large warm sea surface temperature (SST) anomalies in the tropical central-eastern Pacific induce anomalous upper-level divergence and updraft over central Asia through large-scale convergence and divergence in the mature winter and decaying spring. Meanwhile, the associated wind anomalies induce anomalous eastward and northeastward moisture flux from the North Atlantic and the Arabian Sea to central Asia. Both anomalous ascent and moisture flux convergence favor above-normal precipitation over central Asia in the mature winter and decaying spring. The El Niño events induced central Asian precipitation anomalies that are extended to the decaying summer due to the role of soil moisture. Increased rainfall in winter and spring enhances soil moisture in the following summer, which in turn contributes to more precipitation in summer through modulating regional evaporation. During weak El Niño events, significant wet anomalies are only seen in the developing autumn, which result from anomalous southeastward moisture flux from the Arctic Ocean, and the abnormal signals are weak in the other seasons. The different responses of central Asian precipitation to strong and weak El Niño events may be attributed to the difference in intensity of tropical SST anomalies between the two types of events.

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Lin Wang
,
Peiqiang Xu
,
Wen Chen
, and
Yong Liu

Abstract

Based on several reanalysis and observational datasets, this study suggests that the Silk Road pattern (SRP), a major teleconnection pattern stretching across Eurasia in the boreal summer, shows clear interdecadal variations that explain approximately 50% of its total variance. The interdecadal SRP features a strong barotropic wave train along the Asian subtropical jet, resembling its interannual counterpart. Additionally, it features a second weak wave train over the northern part of Eurasia, leading to larger meridional scale than its interannual counterpart. The interdecadal SRP contributes approximately 40% of the summer surface air temperature’s variance with little uncertainty and 10%–20% of the summer precipitation’s variance with greater uncertainty over large domains of Eurasia. The interdecadal SRP shows two regime shifts in 1972 and 1997. The latter shift explains over 40% of the observed rainfall reduction over northeastern Asia and over 40% of the observed warming over eastern Europe, western Asia, and northeastern Asia, highlighting its importance to the recent decadal climate variations over Eurasia. The Atlantic multidecadal oscillation (AMO) does not show a significant linear relationship with the interdecadal SRP. However, the Monte Carlo bootstrapping resampling analysis suggests that the positive (negative) phases of the spring and summer AMO significantly facilitate the occurrence of negative (positive) phases of the interdecadal SRP, implying plausible prediction potentials for the interdecadal variations of the SRP. The reported results are insensitive to the long-term trends in datasets and thereby have little relevance to externally forced climate change.

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