Spatial and temporal features of summer extreme temperature over China during 1960–2013

Theoretical and Applied Climatology - Based on daily air temperature data from 772 stations in China, the present study uses absolute index and percentile index to investigate the spatial and...     

An analysis of extreme intraseasonal rainfall events during January–March 2010 over eastern China

The precipitation over eastern China during January–March 2010 exhibited a marked intraseasonal oscillation (ISO) and a dominant period of 10-60 days. There were two active intraseasonal rainfall periods. The physical mechanisms responsible for the onset of the two rainfall events were investigated using ERA-interim data. In the first ISO event, anomalous ascending motion was triggered by vertically integrated (1000–300 hPa) warm temperature advection. In addition to southerly anomalies on the intraseasonal (10–60-day) timescale, synoptic-scale southeasterly winds helped advect warm air from the South China Sea and western Pacific into the rainfall region. In the second ISO event, anomalous convection was triggered by a convectively unstable stratification, which was caused primarily by anomalous moisture advection in the lower troposphere (1000–850 hPa) from the Bay of Bengal and the Indo-China Peninsula. Both the intraseasonal and the synoptic winds contributed to the anomalous moisture advection. Therefore, the winter intraseasonal rainfall events over East Asia in winter could be affected not only by intraseasonal activities but also by higher frequency disturbances.     

Changes in wind speed over China during 1956–2004

Based on two observational data sets in China from 1956 to 2004, wind speed changes are analyzed. The annual mean wind speed (MWS), days of strong wind (SWDs), and maximum wind (MW) all show declining trends over broad areas of China. Only in the southeastern Tibetan Plateau and the regions from the Great Bend of the Yellow River southward to Yunnan and Guangxi Provinces wind speeds are not significantly reduced, but rather, in partial, these regions’ winds speeds are slightly increased. The regions with declining trends match the areas with relatively strong observed winds and the regions without significant declining trends match the areas with light observed winds. In the meantime, the regions with relatively strong winds correspond to areas of reduced days of SWDs. Trends for both increasing intensities and for the number of days of light winds both impact the installation of wind energy facilities. These may be advantageous to the development of wind energy in different regions. Urbanization, the change of anemometers, or relocation of stations are factors that are mildly responsible for the decreasing trend of MWS. The main reason for the decreasing trend is that under the background of global warming, the contrasts of the sea level pressure, and near-surface temperature between the Asian continent and the Pacific Ocean have become significantly smaller, and the east Asian trough has shifted eastward and northward, and has weakened as well. Both East Asian winter and summer monsoons are decreasing, and all of these impacts have resulted in declines of MWS in China.     

Changes in temporal concentration property of summer precipitation in China during 1961–2010 based on a new index

Based on the property of entropy, a new index Q was defined to measure the temporal concentration property of summertime daily rainfall in China, based on daily precipitation data collected at 553 observation stations in China during 1961–2010. Furthermore, changes in the temporal concentration property of summer precipitation in China were investigated. The results indicate that the regions with larger Q values were located in most parts of Northwest China and the north of the Yellow River, where daily precipitation tended to become temporally concentrated during the study period. On the contrary, smaller Q values were found in eastern Tibetan Plateau, southeastern Northwest China, and most parts of Southwest and South China. The most obvious increasing trend of Q index was found in South China and most parts of Southwest China, where precipitation showed a temporal concentration trend. However, a decreasing trend of Q index was found in Northwest China, the Tibetan Plateau, and the north of the Huaihe River. Variations of the Q index and the summer rainfall total during 1961–2010 in China both exhibited an increasing trend, implying larger temporal variability in rainfall attributes. It is illustrated that the summer precipitation in general became more temporally concentrated with more intense rainfall events and wetter days.     

Changes in Regional Heavy Rainfall Events in China during 1961–2012

A new technique for identifying regional climate events, the Objective Identification Technique for Regional Extreme Events(OITREE), was applied to investigate the characteristics of regional heavy rainfall events in China during the period1961–2012. In total, 373 regional heavy rainfall events(RHREs) were identified during the past 52 years. The East Asian summer monsoon(EASM) had an important influence on the annual variations of China's RHRE activities, with a significant relationship between the intensity of the RHREs and the intensity of the Mei-yu. Although the increase in the frequency of those RHREs was not significant, China experienced more severe and extreme regional rainfall events in the 1990 s. The middle and lower reaches of the Yangtze River and the northern part of South China were the regions in the country most susceptible to extreme precipitation events. Some stations showed significant increasing trends in the southern part of the middle and lower reaches of the Yangtze River and the northern part of South China, while parts of North China, regions between Guangxi and Guangdong, and northern Sichuan showed decreasing trends in the accumulated intensity of RHREs.The spatial distribution of the linear trends of events' accumulated intensity displayed a similar so-called "southern flooding and northern drought" pattern over eastern China in recent decades.     

Comparison of two homogenized datasets of daily maximum/mean/minimum temperature in China during 1960–2013

Two homogenized datasets of daily maximum temperature (Tmax), mean temperature (Tm), and minimum temperature (Tmin) series in China have recently been developed. One is CHTM3.0, based on the Multiple Analysis of Series for Homogenization (MASH) method, and includes 753 stations for the period 1960–2013. The other is CHHTD1.0, based on the Relative Homogenization test (RHtest), and includes 2419 stations over the period 1951–2011. The daily Tmax/Tm/Tmin series at 751 stations, which are in both datasets, are chosen and compared against the raw dataset, with regard to the number of breakpoints, long-term climate trends, and their geographical patterns. The results indicate that some robust break points associated with relocations can be detected, the inhomogeneities are removed by both the MASH and RHtest method, and the data quality is improved in both homogenized datasets. However, the differences between CHTM3.0 and CHHTD1.0 are notable. By and large, in CHHTD1.0, the break points detected are fewer, but the adjustments for inhomogeneities and the resultant changes of linear trend estimates are larger. In contrast, CHTM3.0 provides more reasonable geographical patterns of long-term climate trends over the region. The reasons for the differences between the datasets include: (1) different algorithms for creating reference series for adjusting the candidate series—more neighboring stations used in MASH and hence larger-scale regional signals retained; (2) different algorithms for calculating the adjustments—larger adjustments in RHtest in general, partly due to the individual local reference information used; and (3) different rules for judging inhomogeneity—all detected break points are adjusted in CHTM3.0, based on MASH, while a number of break points detected via RHtest but without supporting metadata are overlooked in CHHTD1.0. The present results suggest that CHTM3.0 is more suitable for analyses of large-scale climate change in China, while CHHTD1.0 contains more original information regarding station temperature records.     

Changes in extreme daily rainfall for São Paulo, Brazil

Significant positive trends are found in the evolution of daily rainfall extremes in the city of São Paulo (Brazil) from 1933 to 2010. Climatic indices including ENSO, PDO, NAO and the sea surface temperature at the coast near São Paulo explain 85 % of the increasing frequency of extremes during the dry season. During the wet season the climatic indices and the local sea surface temperature explain a smaller fraction of the total variance when compared to the dry season indicating that other factors such as the growth of the urban heat island and the role of air pollution in cloud microphysics need to be taken into account to explain the observed trends over the almost eight decades.     

Trend of monthly temperature and daily extreme temperature during 1951–2012 in New Zealand

A new method for calculating evaporation is proposed, using the Penman–Monteith (P-M) model with remote sensing. This paper achieved the effective estimation to daily evapotranspiration in the Ziya river catchment by using the P-M model based on MODIS remote sensing leaf area index and respectively estimated plant transpiration and soil evaporation by using coefficient of soil evaporation. This model divided catchment into seven different sub-regions which are prairie, meadow, grass, shrub, broad-leaved forest, cultivated vegetation, and coniferous forest through thoroughly considering the vegetation diversity. Furthermore, optimizing and calibrating parameters based on each sub-region and analyzing spatio-temporal variation rules of the model main parameters which are coefficient of soil evaporation f and maximum stomatal conductance g _sx . The results indicate that f and g _sx calibrated by model are basically consistent with measured data and have obvious spatio-temporal distribution characteristics. The monthly average evapotranspiration value of simulation is 37.96 mm/mon which is close to the measured value with 33.66 mm/mon and the relative error of simulation results in each subregion are within 11 %, which illustrates that simulated values and measured values fit well and the precision of model is high. In addition, plant transpiration and soil evaporation account for about 84.64 and 15.36 % respectively in total evapotranspiration, which means the difference between values of them is large. What is more, this model can effectively estimate the green water resources in basin and provide effective technological support for water resources estimation.     

Trends in extreme temperature indices in Huang-Huai-Hai River Basin of China during 1961–2014

Spatial and temporal characteristics of temperature extremes have been investigated in Huang-Huai-Hai (HHH) region based on the daily series of temperature observations from 162 meteorological stations. A total of 11 indices were used to assess the changes of temperature pattern. Linear trend analyses revealed that the daily maximum temperature (TXx) increased at α = 0.05 level with a magnitude of 0.15 °C per decade on the regional scale during the period of 1961–2014. More pronounced warming trend of the daily minimum temperature (TNn) was detected at a rate of 0.49 °C per decade (α = 0.01 level). Consequently, a decreasing trend of the temperature range of TXx and TNn (extreme temperature range) was observed. The frequency of hot days (TXf90) and annual average of warm events (warm spell duration indicator, WSDI) showed significant increasing trends, while that of cold nights (TNf10) and cold events (cold spell duration indicator, CSDI) showed opposite behaviors. Both warm winter (W-W) and hot summer (H-S) series displayed significant increasing trends at α = 0.01 confidence level. The cold winter (C-W) series showed a decreasing trend at α = 0.01 confidence level, while the cool summer (C-S) series showed a nonsignificant decreasing trend that is not passing the 90% confidence level (α = 0.1). Abrupt increments of warm­related extremes (TXx, TXf90, WSDI) have been detected since 1990s, and a steadily decreasing trend of cold related extremes (TNf10, CSDI) was found since 1970s. Ten hot summers out of 11 and nine warm winters out of 10 occurred after 1990s. Altitude has a large impact on spatial pattern of extreme temperature indices, and the urban heat island effect also has an impact on amplitude of variation in extreme temperature. Trend magnitudes are significantly larger at sites with high altitudes for warm­related indices (TXx, TXf90, WSDI), while those involving cold-related indices (TNn, TNf10) are remarkably larger for stations with low altitudes.     

Changes in Seasonal Cycle and Extremes in China during the Period 1960–2008

Recent trends in seasonal cycles in China are analyzed, based on a homogenized dataset of daily temperatures at 541 stations during the period 1960–2008. Several indices are defined for describing the key features of a seasonal cycle, including local winter/summer (LW/LS) periods and local spring/autumn phase (LSP/LAP). The Ensemble Empirical Mode Decomposition method is applied to determine the indices for each year. The LW period was found to have shortened by 2–6 d (10 yr)-1, mainly due to an earlier end to winter conditions, with the LW mean temperature having increased by 0.2°C–0.4°C (10 yr)?1, over almost all of China. Records of the most severe climate extremes changed less than more typical winter conditions did. The LS period was found to have lengthened by 2–4 d (10 yr)?1, due to progressively earlier onsets and delayed end dates of the locally defined hot period. The LS mean temperature increased by 0.1°C–0.2°C (10 yr)-1 in most of China, except for a region in southern China centered on the mid-lower reaches of the Yangtze River. In contrast to the winter cases, the warming trend in summer was more prominent in the most extreme records than in those of more typical summer conditions. The LSP was found to have advanced significantly by about 2 d (10 yr)-1 in most of China. Changes in the autumn phase were less prominent. Relatively rapid changes happened in the 1980s for most of the regional mean indices dealing with winter and in the 1990s for those dealing with summer.     

Spatiotemporal change in China’s climatic growing season: 1955–2000

The timing, length, and thermal intensity of the climatic growing season in China show statistically significant changes over the period of 1955 to 2000. Nationally, the average start of the growing season has shifted 4.6–5.5 days earlier while the average end has moved 1.8–3.7 days later, increasing the length of the growing season by 6.9–8.7 days depending on the base temperature chosen. The thermal intensity of the growing season has increased by 74.9–196.8 growing degree-days, depending on the base temperature selected. The spatial characteristics of the change in the timing and length of the growing season differ from the geographical pattern of change in temperatures over this period; but the spatial characteristics of change in growing degree-days does resemble the pattern for temperatures, with higher rates in northern regions. Nationally, two distinct regimes are evident over time: an initial period where growing season indicators fluctuate near a base period average, and a second period of rapidly increasing growing season length and thermal intensity. Growing degree-days are highly correlated with March-to-November mean air temperatures in all climatic regions of China; the length of the growing season is likewise highly correlated with March-to-November mean air temperatures except in east, southeast and southwest China at base temperature of 0°C and southeast China at base temperature of 5°C. The growing season start date appears to have the greater influence on the length of the growing season. In China, warmer growing seasons are also likely to be longer growing seasons.     

Characteristics of extreme daily minimum and maximum temperature over Northeast China, 1961–2009

In this study, the multifractal detrended fluctuation analysis method is employed to determine the thresholds of extreme events. Subsequently, the characteristics of extreme temperatures have been analyzed over Northeast China during 1961–2009. Approximately 58 % of stations have negative interdecadal trends of ?2.2 days/10 years to 0 days/10 years in extreme low minimum temperature (ELMT) frequency. Notable positive trend of 0–2.5 days/10 years in extreme high maximum temperature (EHMT) frequency of about 94 % stations are found. Approximately 58 % of stations have decreasing trend in ELMT intensity, whereas 69 % of stations have increasing trend of EHMT intensity. The trends are the range of ?0.72 °C/10 years to 0 °C/10 years and 0–0.7 °C/10 years, respectively. We propose the extreme temperatures indices, ELMT index (ELMTI) and EHMT index (EHMTI), which combined the frequency and intensity of extreme temperatures to represent the order of severity of extreme temperatures. According to this approach, serious ELMT mainly occur in the Songliao Plain and the Sanjiang Plain, especially in the Songliao Plain. Serious EHMT distinctly occur in the Sanjing Plain, and the southwestern and northwestern regions of Northeast China in recent five decades.     

Reconstructing medieval April-July mean temperatures in East Anglia, 1256–1431

This paper presents the first annually resolved temperature reconstruction for England in the Middle Ages. To effect this reconstruction the starting date of the grain harvest in Norfolk has been employed as a temperature proxy. Using c. 1,000 manorial accounts from Norfolk, 616 dates indicating the onset of the grain harvest were extracted for the period 1256 to 1431 and a composite Norfolk series was constructed. These data were then converted into a temperature series by calibrating a newly constructed comparison series of grain harvest dates in Norfolk from 1768 to 1816 with the Central England Temperature series. These results were verified over the period 1818?C1867. For the British Isles no other annually resolved proxy data are available and the onset of the grain harvest remains the only proxy for assessing April-July mean temperatures. In addition, this is the first time-series regarding the onset of grain harvests in medieval Europe known so far. The long-term trend in the reconstructed medieval temperature series suggests that there was a cooling in the mean April-July temperatures over the period 1256 to 1431. Average temperatures dropped from 13°C to 12.4°C, which possibly indicates the onset of the Little Ice Age. The decline in values was not steady, however, and the reconstruction period contains decades of warmer spring-early summer temperatures (for example the 1320s to the early 1330s and the 1360s) as well as colder conditions (for example the late 1330s, 1340s and the 1380s). The decline in grain-growing-season average temperatures would not have been a major problem for medieval agriculture, rather the phases of very high interannual variability partly found in the medieval time-series, such as 1315?C1335 and 1360?C1375, would have proved disruptive.     

Droughts near the northern fringe of the East Asian summer monsoon in China during 1470–2003

Historical annual dry–wet index for 1470–2003 combined with instrumental precipitation since 1951 were used to identify extremely dry years and events near the northern fringe of the East Asian summer monsoon in China—the Great Bend of the Yellow River (GBYR) region. In total, 49 drought years, of which 26 were severe, were identified. Composites of the dry–wet index under the drought years show an opposite wet pattern over the Southeast China. The longest drought event lasted for 6?years (1528–1533), the second longest one 4?years (1637–1640). The most severe 2-year-long drought occurred in 1928–1929, and the two driest single years were 1900 and 1965. These persistent and extreme drought events caused severe famines and huge losses of human lives. Wavelet transform applied to the dry–wet index indicates that the severe drought years are nested in several significant dry–wet variations across multiple timescales, i.e., the 65–85?year timescale during 1600– 1800, 40–55?year timescale before 1640 and 20–35?year timescale mainly from 1550 to 1640. These timescales of dry–wet variations are discussed in relation to those forcing such as cycles of solar radiation, oscillation in the thermohaline circulation and the Pacific Decadal Oscillation (PDO). Comparing 850?hPa winds in Asia in extremely dry and wet years, it was concluded that dry–wet variability in the GBYR region strongly depends upon whether the southerly monsoon flow can reach northern China.     

Changes of precipitation pattern in China: 1961–2010

Theoretical and Applied Climatology - Based on the precipitation records of 2474 meteorological stations, this study investigated precipitation characteristics and trends in China from 1961 to...