Search Results

You are looking at 11 - 18 of 18 items for

  • Author or Editor: Hao Wang x
  • Refine by Access: All Content x
Clear All Modify Search
Q.-S. Ge, J.-Y. Zheng, Z.-X. Hao, P.-Y. Zhang, and W.-C. Wang

Chinese historical documents that contain descriptions of weather conditions can be used for studying climate of the past hundreds or even thousands of years. In this study, the progress of reconstructing a 273-station quantitative precipitation dataset for 1736–1911—a period when records of the depth of rain infiltration (into the ground) and snow depth (above the surface) were kept in the Yu–Xue–Fen–Cun (which is part of memos routinely sent to the emperors during the Qing Dynasty) is reported. To facilitate the rainfall reconstruction, a field program of 29 sites covering different climate regimes and soil characteristics was designed for the purpose of establishing the transfer function between the rain infiltration depth and rainfall amount, while the relation between the snow depth and snowfall is obtained using instrumental measurements of recent decades. The results of the first site at Shijiazhuang (near Beijing) are reported here. The reconstruction shows that the summer and winter precipitation during 1736–1911 were generally greater than their respective 1961–90 means. Two years with extreme summer precipitation are identified—112 mm in 1792 and 1167 mm in 1801; the latter is larger than the 998 mm in 1996, which has been the most severe one of recent decades. The long-term high-resolution quantitative data can be used to study climate variability as well as to evaluate historical climate model simulations.

Full access
Lan Cuo, Yongxin Zhang, Qingchun Wang, Leilei Zhang, Bingrong Zhou, Zhenchun Hao, and Fengge Su

Abstract

Gridded daily precipitation, temperature minima and maxima, and wind speed are generated for the northern Tibetan Plateau (NTP) for 1957–2009 using observations from 81 surface stations. Evaluation reveals reasonable quality and suitability of the gridded data for climate and hydrology analysis. The Mann–Kendall trends of various climate elements of the gridded data show that NTP has in general experienced annually increasing temperature and decreasing wind speed but spatially varied precipitation changes. The northwest (northeast) NTP became dryer (wetter), while there were insignificant changes in precipitation in the south. Snowfall has decreased along high mountain ranges during the wet and warm season. Averaged over the entire NTP, snowfall, temperature minima and maxima, and wind speed experienced statistically significant linear trends at rates of −0.52 mm yr−1 (water equivalent), +0.04°C yr−1, +0.03°C yr−1, and −0.01 m s−1 yr−1, respectively. Correlation between precipitation/wind speed and climate indices characterizing large-scale weather systems for four subregions in NTP reveals that changes in precipitation and wind speed in winter can be attributed to changes in the North Atlantic Oscillation (NAO), the Arctic Oscillation (AO), the East Asian westerly jet (WJ), and the El Niño–Southern Oscillation (ENSO) (wind speed only). In summer, the changes in precipitation and wind are only weakly related to these indices. It is speculated that in addition to the NAO, AO, ENSO, WJ, and the East and South Asian summer monsoons, local weather systems also play important roles.

Full access
Jianping Huang, Qiang Fu, Wu Zhang, Xin Wang, Rudong Zhang, Hao Ye, and Stephen G. Warren

Abstract

Snow is the most reflective natural surface on Earth. Its albedo (the fraction of sunlight reflected) can be reduced by small amounts of dark impurities such as dust and black carbon (BC) particles. This effect is significant for climate and the hydrological cycle. BC has previously been measured in Arctic snow, but it now appears that the larger effect may be in the midlatitudes because snow at lower latitudes is exposed to more sunlight and is closer to the sources of BC.

A field campaign was conducted across northern China in January and February 2010. Snow samples were collected at 46 sites in six provinces. The absorbing impurities are principally dust and BC particles in northwestern and northeastern China, respectively. The estimated concentration of BC is only 30–50 ppb in the far north of Heilongjiang Province (51°N), which is not much more than that found along the coast of the Arctic Ocean, 2,000 km farther north, but it increases to several hundred parts per billion in heavily industrialized Liaoning Province, Jilin Province, and the southern part of Heilongjiang. The BC content of snow in northeast China is comparable to values found in Europe (20–800 ppb). The steep drop-off in BC content of snow with latitude may indicate that little BC emitted in China in the winter is exported northward to the Arctic.

Full access
Hao He, Hailong Wang, Zhaoyong Guan, Haishan Chen, Qiang Fu, Muyin Wang, Xiquan Dong, Chunguang Cui, Likun Wang, Bin Wang, Gang Chen, Zhanqing Li, and Da-Lin Zhang
Free access
Hao Huang, Kun Zhao, Guifu Zhang, Qing Lin, Long Wen, Gang Chen, Zhengwei Yang, Mingjun Wang, and Dongming Hu

Abstract

Quantitative precipitation estimation (QPE) with polarimetric radar measurements suffers from different sources of uncertainty. The variational approach appears to be a promising way to optimize the radar QPE statistically. In this study a variational approach is developed to quantitatively estimate the rainfall rate (R) from the differential phase (ΦDP). A spline filter is utilized in the optimization procedures to eliminate the impact of the random errors in ΦDP, which can be a major source of error in the specific differential phase (K DP)-based QPE. In addition, R estimated from the horizontal reflectivity factor (Z H) is used in the a priori with the error covariance matrix statistically determined. The approach is evaluated by an idealized case and multiple real rainfall cases observed by an operational S-band polarimetric radar in southern China. The comparative results demonstrate that with a proper range filter, the proposed variational radar QPE with the a priori included agrees well with the rain gauge measurements and proves to have better performance than the other three approaches, that is, the proposed variational approach without the a priori included, the variational approach proposed by Hogan, and the conventional power-law estimator-based approach.

Full access
Yi Jin, Shouping Wang, Jason Nachamkin, James D. Doyle, Gregory Thompson, Lewis Grasso, Teddy Holt, Jon Moskaitis, Hao Jin, Richard M. Hodur, Qingyun Zhao, Ming Liu, and Mark DeMaria

Abstract

The impact of ice phase cloud microphysical processes on prediction of tropical cyclone environment is examined for two microphysical parameterizations using the Coupled Ocean–Atmosphere Mesoscale Prediction System–Tropical Cyclone (COAMPS-TC) model. An older version of microphysical parameterization is a relatively typical single-moment scheme with five hydrometeor species: cloud water and ice, rain, snow, and graupel. An alternative newer method uses a hybrid approach of double moment in cloud ice and rain and single moment in the other three species. Basin-scale synoptic flow simulations point to important differences between these two schemes. The upper-level cloud ice concentrations produced by the older scheme are up to two orders of magnitude greater than the newer scheme, primarily due to differing assumptions concerning the ice nucleation parameterization. Significant (1°–2°C) warm biases near the 300-hPa level in the control experiments are not present using the newer scheme. The warm bias in the control simulations is associated with the longwave radiative heating near the base of the cloud ice layer. The two schemes produced different track and intensity forecasts for 15 Atlantic storms. Rightward cross-track bias and positive intensity bias in the control forecasts are significantly reduced using the newer scheme. Synthetic satellite imagery of Hurricane Igor (2010) shows more realistic brightness temperatures from the simulations using the newer scheme, in which the inner core structure is clearly discernible. Applying the synthetic satellite imagery in both quantitative and qualitative analyses helped to pinpoint the issue of excessive upper-level cloud ice in the older scheme.

Full access
Dan Wu, Kun Zhao, Matthew R. Kumjian, Xiaomin Chen, Hao Huang, Mingjun Wang, Anthony C. Didlake Jr., Yihong Duan, and Fuqing Zhang

Abstract

This study analyzes the microphysics of convective cells in an outer rainband of Typhoon Nida (2016) using data collected by a newly upgraded operational polarimetric radar in China. The life cycle of these convective cells is divided into three stages: developing, mature, and decaying according to the intensity of the corresponding updraft. Composite analysis shows that deep columns of Z DR and K DP collocate well with the enhanced updraft as the cells develop to their mature stage. A layered microphysical structure is observed in the ice region with riming near the −5°C level within the updraft, aggregation around the −15°C level, and deposition anywhere above the 0°C level. These ice-phase microphysical processes are important pathways of particle growth in the outer rainbands. In particular, riming contributes significantly to surface heavy rainfall. These contrast to previously documented inner rainbands, where warm-rain processes are the predominant pathway of particle growth.

Full access
Longhui Li, Yingping Wang, Vivek K. Arora, Derek Eamus, Hao Shi, Jing Li, Lei Cheng, James Cleverly, T. Hajima, Duoying Ji, C. Jones, M. Kawamiya, Weiping Li, J. Tjiputra, A. Wiltshire, Lu Zhang, and Qiang Yu

Abstract

Water and carbon fluxes simulated by 12 Earth system models (ESMs) that participated in phase 5 of the Coupled Model Intercomparison Project (CMIP5) over several recent decades were evaluated using three functional constraints that are derived from both model simulations, or four global datasets, and 736 site-year measurements. Three functional constraints are ecosystem water-use efficiency (WUE), light-use efficiency (LUE), and the partitioning of precipitation P into evapotranspiration (ET) and runoff based on the Budyko framework. Although values of these three constraints varied significantly with time scale and should be quite conservative if being averaged over multiple decades, the results showed that both WUE and LUE simulated by the ensemble mean of 12 ESMs were generally lower than the site measurements. Simulations by the ESMs were generally consistent with the broad pattern of energy-controlled ET under wet conditions and soil water-controlled ET under dry conditions, as described by the Budyko framework. However, the value of the parameter in the Budyko framework ω, obtained from fitting the Budyko curve to the ensemble model simulation (1.74), was larger than the best-fit value of ω to the observed data (1.28). Globally, the ensemble mean of multiple models, although performing better than any individual model simulations, still underestimated the observed WUE and LUE, and overestimated the ratio of ET to P, as a result of overestimation in ET and underestimation in gross primary production (GPP). The results suggest that future model development should focus on improving the algorithms of the partitioning of precipitation into ecosystem ET and runoff, and the coupling of water and carbon cycles for different land-use types.

Open access