Search Results

You are looking at 1 - 10 of 19 items for

  • Author or Editor: Guoyu Ren x
  • All content x
Clear All Modify Search
Yuyu Ren and Guoyu Ren

Abstract

In the global lands, the bias of urbanization effects still exits in the surface air temperature series of many city weather stations to a certain extent. Reliable reference climate stations need to be selected for the detection and correction of the local manmade warming bias. The underlying image data of remote sensing retrieval is adopted in this study to obtain the spatial distribution of surface brightness temperature, and the surface air temperature reference stations are determined based on the locations of the weather stations in the remote sensing surface thermal fields. Among the 672 national reference climate stations and national basic weather stations of mainland China, for instance, 113 surface air temperature reference stations are selected for applying this method. Compared with the average surface air temperature series of the reference stations obtained by a more sophisticated method developed in China, this method is proven to be robust and applicable, and can be adopted for the evaluation and adjustment study on the urbanization bias of the currently used air temperature records of surface climate stations in the global lands.

Full access
Baoleerqimuge Bao and Guoyu Ren

Abstract

Sea-effect precipitation (SEP) over the Shandong Peninsula is a unique climatological phenomenon in mainland China, and it exerts a considerable impact on the southern shore of the Bohai Sea. From observed data from 123 stations for the period 1962–2012, the characteristics of cold-season (November–February) SEP in this area were analyzed. Results showed that SEP occurred throughout the late autumn and winter. In all, 1173 SEP days were identified during the 51 years, of which snow days accounted for 73.7% and rain and snow–rain days accounted for 16.1% and 10.1%, respectively. December had the largest number of SEP snow days, followed by January and November. November was the most productive month in terms of SEP rain and snow–rain days. Intense SEP snowfall mainly affected the inland hill area of the peninsula, whereas light SEP snowfall reached farther inland. SEP rainfall shared a similar pattern with snowfall. The SEP frequency showed a significant interannual variability and a nonsignificant upward trend over the period analyzed. SEP was most likely to occur when the temperature difference between sea surface and 850 hPa over the Bohai Sea was above 10°C, indicating a dominant influence of low-level cold-air advection over the sea on the generation and development of the weather phenomenon. A significant negative correlation was also found between the area of sea ice in the Bohai Sea and intense SEP snowfall, indicating that sea ice extent had an important effect on SEP variability over the peninsula. In the case of extremely intense SEP events, a deeper East Asian trough at the 500-hPa level developed over the southwest of the study area and temperature and geopotential height contours were orthogonal to each other, indicating strong geostrophic cold-air advection over the Bohai Sea and the Shandong Peninsula. The extremely intense SEP events were also characterized by anomalous low temperature and high relative humidity in the lower troposphere, which contributed to greater gravitational instability in the study area.

Full access
Guoyu Ren and Yaqing Zhou

Abstract

Understanding the long-term change of extreme temperature events is important to the detection and attribution of climate change. It is unclear, however, how much effect urbanization has had on trends of the extreme temperature indices series constructed based on the commonly used datasets on a subcontinental scale. Applying a homogenized daily temperature dataset of the national reference climate stations and basic meteorological stations, and a rural station network previously developed, urbanization effects on trends of extreme temperature indices in mainland China for the time period 1961–2008 are evaluated. It is found that 1) the country-averaged annual- and seasonal-mean extreme temperature indices series generally experience statistically significant trends; 2) annual-mean urbanization effects in the country as a whole are statistically significant for daily minimum temperature (Tmin), maximum temperature (Tmax), and mean temperature of Tmin and Tmax (Tavg), reaching 0.070°, 0.023°, and 0.047°C (10 yr)−1, respectively, with the largest values for annual-mean Tmin occurring in north China; 3) annual- and seasonal-mean urbanization effects for the declining diurnal temperature range (DTR) are highly significant, and the largest seasonal-mean DTR decline because of urbanization occurs in winter and spring; 4) annual-mean urbanization effects for the lowest Tmin, summer days, tropical nights, and frost days series are significant, but an insignificant urbanization effect is detected for icing days series; 5) urbanization has led to a highly significant decline of annual cold nights at a rate of −1.485 days (10 yr)−1 and a highly significant increase of annual warm nights at a rate of 2.264 days (10 yr)−1. Although urbanization effects are also significant for cold days and warm days, they are relatively smaller, and 6) the smallest absolute values of annual-mean urbanization effects for most of the indices series are found to dominantly appear during 1966–76, a well-known deurbanization period resulting from the Cultural Revolution.

Full access
Ping Yang, Guoyu Ren, and Wei Hou

Abstract

Hourly datasets obtained by automatic weather stations in Beijing, China, are developed and employed to analyze the spatial and temporal characteristics of relative humidity (RH) and urban dryness island intensity (UDII) over built-up areas. A total of 36 stations inside the sixth ring road are considered as urban sites, while six stations in suburban belts surrounding the built-up areas are taken as reference sites. Results show that the RH is obviously smaller in urban areas than in suburban areas, indicating the effect of urbanization on near-surface atmospheric moisture and RH. A further analysis of relations between RH and temperature on varied time scales shows that the variations in RH in the urban areas are not due solely to changes in temperature. The annual and seasonal mean UDII are high in central urban areas, with the strongest UDII values occurring in autumn and the weakest values occurring in spring. The diurnal UDII variations are characterized by a steadily strong UDII stage from 2000 to 0800 LT and a minimum at 1500 or 1600 LT. The rapid shifts of UDII from high (low) to low (high) occur during the periods 0800–1600 LT (1600–2000 LT). The occurrence time of the peaks varies among different seasons: the peaks appear at 0700, 2100, 2000, and 0800 LT for spring, summer, autumn, and winter, respectively. Further analysis shows that large UDII values appear in the evenings and early nights in late summer and early to midautumn and that low UDII values mainly occur in the afternoon hours of spring, winter, and late autumn.

Full access
Ping Yang, Guoyu Ren, and Weidong Liu

Abstract

An hourly dataset of automatic weather stations over Beijing Municipality in China is developed and is employed to analyze the spatial and temporal characteristics of urban heat island intensity (UHII) over the built-up areas. A total of 56 stations that are located in the built-up areas [inside the 6th Ring Road (RR)] are considered to be urban sites, and 8 stations in the suburban belts surrounding the built-up areas are taken as reference sites. The reference stations are selected by using a remote sensing method. The urban sites are further divided into three areas on the basis of the city RRs. It is found that the largest UHII generally takes place inside the 4th RR and that the smallest ones occur in the outer belts of the built-up areas, between the 5th RR and the 6th RR, with the areas near the northern and southern 6th RR experiencing the weakest UHI phenomena. On a seasonal basis, the strongest UHII generally occurs in winter and weak UHII is dominantly observed in summer and spring. The UHII diurnal variations for each of the urban areas are characterized by a steadily strong UHII stage from 2100 local solar time (LST) to 0600 LST and a steadily weak UHII stage from 1100 to 1600 LST, with the periods 0600–1100 LST and 1600–2100 LST experiencing a swift decline and rise, respectively. UHII diurnal variation is seen throughout the year, but the steadily strong UHII stage at night is longer (shorter) and the steadily weak UHII stage during the day is shorter (longer) during winter and autumn (summer and spring).

Full access
Ping Yang, Guoyu Ren, and Pengcheng Yan

Abstract

Correlations of the urban heat island intensity (UHII) and key surface variables with the short-duration intense rainfall (SDIR) events are examined for the Beijing urban areas by applying hourly data of a high-density automatic weather station (AWS) network. Higher frequencies (amounts) of the SDIR events are found in or near the central urban area, and most of the SDIR events begin to appear in late evening and nighttime, but tend to end in late night and early morning. Correlations of the UHII with the SDIR frequency (amount) are all highly significant for more than 3 h ahead of the beginning of the SDIR events. Although the UHII at immediate hours (<3 h) before the SDIR occurrence is more indicative of SDIR events, their occurrence more depends on the magnitude of the UHII at earlier hours. The UHII before the beginning of the SDIR events also shows high-value centers in the central urban area, which is generally consistent with the distribution of the SDIR events. The spatial and temporal patterns of regional SDIR events exhibit similar characteristics to the site-based SDIR events and also show a good relationship with the UHII in the urban areas. In addition to the UHII over the urban areas, surface air temperature, surface air pressure, relative humidity, and near-surface wind directions at the Beijing station experience large changes before and after the beginning time of regional SDIR events, and have the potential to indicate the occurrence of SDIR events in the studied area.

Full access
Yingxian Zhang, Yuyu Ren, Guoyu Ren, and Guofu Wang

Abstract

Typical rain gauge measurements have long been recognized to underestimate actual precipitation. Long-term daily precipitation records during 1961–2013 from a dense national network of 2379 gauges were corrected to remove systematic errors caused by trace precipitation, wetting losses, and wind-induced undercatch. The corrected percentage was higher in cold seasons and lower in warm seasons. Both trace precipitation and wetting loss corrections were more important in arid regions than in wet regions. A greater correction percentage for wind-induced error could be found in cold and arid regions, as well as high wind speed areas. Generally, the annual precipitation amounts as well as the annual precipitation intensity increased to varying degrees after bias correction with the maximum percentage being about 35%. More importantly, the bias-corrected snowfall amount as well as the rainstorm amount increased remarkably by percentages of more than 50% and 18%, respectively. Remarkably, the total number of actual rainstorm events during the past 53 years could be 90 days more than the observed rainstorm events in some coastal areas of China. Therefore, the actual amounts of precipitation, snowfall, and intense rainfall were much higher than previously measured over China. Bias correction is thus needed to obtain accurate estimates of precipitation amounts and precipitation intensity.

Full access
Yulian Liu, Guoyu Ren, Hengyuan Kang, and Xiubao Sun

Abstract

The systematic bias of the estimated average temperature using daily T max and T min records relative to the standard average temperature of four time-equidistant observations and its effect on the estimated trend of long-term temperature change have not been well understood. This paper attempts to evaluate the systematic bias across mainland China using the daily data of national observational stations. The results revealed that the positive bias of annual mean temperature was large, reaching 0.58°C nationally on average; regional average bias was lowest in the northwest arid region and highest in the Qinghai–Tibetan Plateau; the bias was low in spring and summer and high in autumn and winter, reaching its lowest point in mid- and late May and highest point in early November. Furthermore, the bias showed a significant upward trend in the past 50 years, with a rising rate of 0.021°C (10 yr)−1, accounting for about 12% of the overall warming as estimated from the data of the observational network; the largest positive trend bias was found in the northwest arid region, while the east monsoon region experienced the smallest change; the most remarkable increase of the bias occurred after early 1990s. These results indicate that the customarily applied method to calculate daily and monthly mean temperature using T max and T min significantly overestimates the climatological mean and the long-term trend of surface air temperature in mainland China.

Full access
Panfeng Zhang, Guoyu Ren, Yan Xu, Xiaolan L. Wang, Yun Qin, Xiubao Sun, and Yuyu Ren

Abstract

This paper presents an analysis of changes in global land extreme temperature indices (1951–2015) based on the new global land surface daily air temperature dataset recently developed by the China Meteorological Administration (CMA). The linear trends of the gridpoint time series and global land mean time series were calculated by using a Mann–Kendall method that accounts for the lag-1 autocorrelation in the time series of annual extreme temperature indices. The results, which are generally consistent with previous studies, showed that the global land average annual and seasonal mean extreme temperature indices series all experienced significant long-term changes associated with warming, with cold threshold indices (frost days, icing days, cold nights, and cold days) decreasing, warm threshold indices (summer days, tropical nights, and warm days) increasing, and all absolute indices (TXx, TXn, TNx, and TNn) also increasing, over the last 65 years. The extreme temperature indices series based on daily minimum temperatures generally had a stronger and more significant trend than those based on daily maximum temperatures. The strongest warming occurred after the mid-1970s, and a few extreme temperature indices showed no significant trend over the period from 1951 to the mid-1970s. Most parts of the global land experienced significant warming trends over the period 1951–2015 as a whole, and the largest trends appeared in mid- to high latitudes of the Eurasian continent.

Full access
Kangmin Wen, Guoyu Ren, Jiao Li, Aiying Zhang, Yuyu Ren, Xiubao Sun, and Yaqing Zhou

Abstract

A dataset from 763 national Reference Climate and Basic Meteorological Stations (RCBMS) was used to analyze surface air temperature (SAT) change in mainland China. The monthly historical observational records had been adjusted for urbanization bias existing in the data series of size-varied urban stations, after they were corrected for data inhomogeneities mainly caused by relocation and instrumentation. The standard procedures for creating area-averaged temperature time series and for calculating linear trend were used. Analyses were made for annual and seasonal mean temperature. Annual mean SAT in mainland China as a whole rose by 1.24°C for the last 55 years, with a warming rate of 0.23°C decade−1. This was close to the warming of 1.09°C observed in global mean land SAT over the period 1951–2010. Compared to the SAT before correction, after-corrected data showed that the urbanization bias had caused an overestimate of the annual warming rate of more than 19.6% during 1961–2015. The winter, autumn, spring, and summer mean warming rates were 0.28°, 0.23°, 0.23°, and 0.15°C decade−1, respectively. The spatial patterns of the annual and seasonal mean SAT trends also exhibited an obvious difference from those of the previous analyses. The largest contrast was a weak warming area appearing in central parts of mainland China, which included a small part of southwestern North China, the northwestern Yangtze River, and the eastern part of Southwest China. The annual mean warming trends in Northeast and North China obviously decreased compared to the previous analyses, which caused a relatively more significant cooling in Northeast China after 1998 under the background of global warming slowdown.

Full access