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Copyright of Advances in Atmospheric Sciences is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

We propose a novel machine learning approach to reconstruct meshless surface wind speed fields, i.e., to reconstruct the surface wind speed at any location, based on meteorological background fields and geographical information. The random forest method is selected to develop the machine learning data reconstruction model (MLDRM-RF) for wind speeds over Beijing from 2015–19. We use temporal, geospatial attribute and meteorological background field features as inputs. The wind speed field can be reconstructed at any station in the region not used in the training process to cross-validate model performance. The evaluation considers the spatial distribution of and seasonal variations in the root mean squared error (RMSE) of the reconstructed wind speed field across Beijing. The average RMSE is 1.09 m s−1, considerably smaller than the result (1.29 m s−1) obtained with inverse distance weighting (IDW) interpolation. Finally, we extract the important feature permutations by the method of mean decrease in impurity (MDI) and discuss the reasonableness of the model prediction results. MLDRM-RF is a reasonable approach with excellent potential for the improved reconstruction of historical surface wind speed fields with arbitrary grid resolutions. Such a model is needed in many wind applications, such as wind energy and aviation safety assessments. [ABSTRACT FROM AUTHOR]

Copyright of Advances in Atmospheric Sciences is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Central Asia (CA) is among the most vulnerable regions to climate change due to the fragile ecosystems, frequent natural hazards, strained water resources, and accelerated glacier melting, which underscores the need to achieve robust projection of regional climate change. In this study, we applied three bias-corrected global climate models (GCMs) to conduct 9 km-resolution regional climate simulations in CA for the reference (1986–2005) and future (2031–2050) periods. The regional climate model (RCM) and GCM simulated daily temperature and precipitation are evaluated and the results show that both the bias-correction technique and dynamical downscaling method obtain numerous added values in reproducing the historical climate in CA, respect to the original GCMs. The former contributes more to reducing the biases of the climatology and the latter contributes more to capturing the spatial pattern. The RCM simulations indicate significant warming over CA in the near-term future, with the regional mean increase of annual mean temperature in a range of 1.63–2.01 ℃, relative to the reference period. Pronounced warming is detected north of ~ 45° N in CA from autumn to spring, which can be explained by the snow-albedo feedback. Enhanced warming projected in many mountains in the world is not found in CA, which is consistent with the study based on the reanalysis datasets during the past. Heatwave day frequency, number and maximum duration are expected to become more severe by 2031–2050. Changes in precipitation and Standard Precipitation Index (SPI) shows a wetter condition in CA in the coming decades. However, a fairer assessment of the wet/dry change with Standard Precipitation Evapotranspiration Index (SPEI) which takes into account of both precipitation and potential evapotranspiration reveals a drier condition. The climate change projections presented here serve as a robust scientific basis for assessment of future risk from climate change in CA. [ABSTRACT FROM AUTHOR]

Surface relative humidity (RH) is a key element for weather and climate monitoring and research. However, RH is not as commonly applied in studying climate change, partly because the observation series of RH are prone to inhomogeneous biases due to non-climate changes in the observation system. A homogenized dataset of daily RH series from 746 stations in Chinese mainland for the period 1960–2017, ChinaRHv1.0, has been developed. Most (685 or 91.82% of the total) station time series were inhomogeneous with one or more break points. The major breakpoints occurred in the early 2000s for many stations, especially in the humid and semi-humid zones, due to the implementation of automated observation across the country. The inhomogeneous biases in the early manual records before this change are positive relative to the recent automatic records, for most of the biased station series. There are more break points detected by using the MASH (Multiple Analysis of Series for Homogenization) method, with biases mainly around −0.5% and 0.5%. These inhomogeneous biases are adjusted with reference to the most recent observations for each station. Based on the adjusted observations, the regional mean RH series of China shows little long-term trend during 1960–2017 [0.006% (10 yr)−1], contrasting with a false decreasing trend [−0.414% (10 yr)−1] in the raw data. It is notable that ERA5 reanalysis data match closely with the interannual variations of the raw RH series in China, including the jump in the early 2000s, raising a caveat for its application in studying climate change in the region. [ABSTRACT FROM AUTHOR]

The regional mean surface air temperature (SAT) in China has risen with a rate of 1.3–1.7°C (100 yr)−1 since 1900, based on the recently developed homogenized observations. This estimate is larger than those [0.5–0.8°C (100 yr)−1] adopted in the early National Reports of Climate Change in China. The present paper reviews the studies of the long-term SAT series of China, highlighting the homogenization of station observations as the key progress. The SAT series of China in early studies showed a prominent warm peak in the 1940s, mainly due to inhomogeneous records associated with site-moves of a number of stations from urban to outskirts in the early 1950s, thus leading to underestimates of the centennial warming trend. Parts of China were relatively warm around the 1940s but with different-phase interdecadal variations, while some parts were even relatively cool. This fact is supported by proxy data and could partly be explained by interdecadal changes in large-scale circulation. The effect of urbanization should have a minor contribution to the observed warming in China, although the estimates of such contributions for individual urban stations remain controversial. Further studies relevant to the present topic are discussed. [ABSTRACT FROM AUTHOR]

Compared to individual hot days/nights, compound hot extremes that combine daytime and nighttime heat are more impactful. However, past and future changes in compound hot extremes as well as their underlying drivers and societal impacts remain poorly understood. Here we show that during 1960–2012, significant increases in Northern Hemisphere average frequency (~1.03 days decade−1) and intensity (~0.28 °C decade−1) of summertime compound hot extremes arise primarily from summer-mean warming. The forcing of rising greenhouse gases (GHGs) is robustly detected and largely accounts for observed trends. Observationally-constrained projections suggest an approximate eightfold increase in hemispheric-average frequency and a threefold growth in intensity of summertime compound hot extremes by 2100 (relative to 2012), given uncurbed GHG emissions. Accordingly, end-of-century population exposure to compound hot extremes is projected to be four to eight times the 2010s level, dependent on demographic and climate scenarios. Compound hot extremes that combine day- and nighttime heat have particularly strong impacts. Here, the authors show that anthropogenic emissions of greenhouse gases have made compound hot extremes increasingly frequent and intense, and project that under future emissions four to eight times as many people will be affected by them by 2100. [ABSTRACT FROM AUTHOR]

The warming rates in China determined by daily minimum temperature (Tmin) are considerably large than those based on daily mean temperature (Tmean); therefore, the thermal growing season indices defined from Tmin are expected to show more pronounced changes than those from Tmean. In this study, we investigate changing rates in the local growing season (LGS) defined using the climatological annual mean Tmin and Tmean as temperature thresholds throughout China for the period 1961–2012. Changes in the thermal growing season indices based on fixed-temperature thresholds such as 0 °C, 5 °C, and 10 °C are analyzed for comparison. Results show that the Tmin-based LGS-lengthening rate (3.0 days per decade) is at least 1.2 times that of the Tmean-based result (2.5 days per decade). It is also suggested that the growing season defined via a fixed-temperature threshold should only be applicable when determining the validity of a particular station in relation to its location. For example, the 0 °C-, 5 °C-, and 10 °C-based growing season definitions are applicable in regions to the north of 36° N, 32° N, and 26° N, respectively, based on Tmean in eastern China and to the north of 33° N, 27° N, and 24° N, respectively, based on Tmin. To the north of 35° N in China, the average Tmin-based growing season lengthening rates are about 1.3, 1.4, and 1.7 times of those Tmean-based rates in case of using the fixed-temperature thresholds of 0 °C, 5 °C, and 10 °C, respectively. Therefore, the changes of the growth of some plant species that are more directly correlated with changes in Tmin should be much more pronounced than those of other species. [ABSTRACT FROM AUTHOR]

A set of homogenized monthly mean surface air temperature (SAT) series at 32 stations in China back to the 19th century had previously been developed based on the RHtest method by Cao et al., but some inhomogeneities remained in the dataset. The present study produces a further-adjusted and updated dataset based on the Multiple Analysis of Series for Homogenization (MASH) method. The MASH procedure detects 33 monthly temperature records as erroneous outliers and 152 meaningful break points in the monthly SAT series since 1924 at 28 stations. The inhomogeneous parts are then adjusted relative to the latest homogeneous part of the series. The new data show significant warming trends during 1924-2016 at all the stations, ranging from 0.48 to 3.57°C (100 yr)−1, with a regional mean trend of 1.65°C (100 yr)−1; whereas, the previous results ranged from a slight cooling at two stations to considerable warming, up to 4.5°C (100 yr)−1. It is suggested that the further-adjusted data are a better representation of the large-scale pattern of climate change in the region for the past century. The new data are available online at http://www.dx.doi.org/10.11922/sciencedb.516. [ABSTRACT FROM AUTHOR]

Near-term climate projections are needed by policymakers; however, these projections are difficult because internally generated climate variations need to be considered. In this study, temperature change scenarios in the near-term period 2017-35 are projected at global and regional scales based on a refined multi-model ensemble approach that considers both the secular trend (ST) and multidecadal variability (MDV) in the Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations. The ST and MDV components are adaptively extracted from each model simulation by using the ensemble empirical mode decomposition (EEMD) filter, reconstructed via the Bayesian model averaging (BMA) method for the historical period 1901-2005, and validated for 2006-16. In the simulations of the “medium” representative concentration pathways scenario during 2017-35, the MDV-modulated temperature change projected via the refined approach displays an increase of 0.44°C (90% uncertainty range from 0.30 to 0.58°C) for global land, 0.48°C (90% uncertainty range from 0.29 to 0.67°C) for the Northern Hemispheric land (NL), and 0.29°C (90% uncertainty range from 0.23 to 0.35°C) for the Southern Hemispheric land (SL). These increases are smaller than those projected by the conventional arithmetic mean approach. The MDV enhances the ST in 13 of 21 regions across the world. The largest MDV-modulated warming effect (46%) exists in central America. In contrast, the MDV counteracts the ST in NL, SL, and eight other regions, with the largest cooling effect (220%) in Alaska. [ABSTRACT FROM AUTHOR]

Copyright of Advances in Atmospheric Sciences is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

On 21-22 July 2012, torrential rains hit North China, with the daily precipitation record at Beijing station reaching 160.6 mm; this event is named the Beijing 7-21 case. This paper assesses the likelihood of the occurrence of local torrential rains, such as the Beijing 7-21 case, from the perspective of climate variability. In particular, the influence of the Pacific Decadal Oscillation (PDO) is assessed. There were five extreme events, with daily precipitation records equal to or larger than 160.6 mm, at Beijing station during the period 1951-2012; all of these events happened during negative phases of the PDO. The present analysis indicates that precipitation events more extreme than the Beijing 7-21 case should happen more than once per decade during negative phases of the PDO, but only about once every four decades during positive PDO phases. The negative phase of the PDO is found to be associated with a much greater probability of daily records of southerly winds in North China during summer. Strong southerly summer monsoons are deemed favorable for increasing the occurrence of local extreme rainfall over North China. [ABSTRACT FROM AUTHOR]

The impact of urban warming during the 2013 July-August extreme heat wave event across the Yangtze River Delta (YRD) in China was assessed. Using a newly developed high-resolution, land-use dataset, urban stations were identified from a total of 101 stations in the YRD. The difference between urban and non-urban/rural stations indicates that urban warming reached 1.22 °C in the 2013 summer heat wave. The new land-use dataset was then input to the Weather Research and Forecasting model to further understand the dynamical/physical processes of the urban warming during the heat wave. The model-simulated urban warming is ~1.5 °C. Impacts of urbanization on near-surface temperature had strong diurnal variation, reaching a peak at 19:00 LST, around sunset. In the daytime, urban warming was mainly caused by enhanced sensible heat fluxes and longwave radiation from the surface. Because of reduced latent heat flux and increased heat capacity, urban ground stored much more heat than rural ground during the daytime, which is later released as sensible heat flux from the surface at night, leading to the nocturnal urban warming. The simulation results also suggest a positive feedback between urban warming and heat wave intensity, which makes the heat wave more intense in urban than rural areas and the urban warming during the extreme heat wave stronger than its climatological mean. [ABSTRACT FROM AUTHOR]

The WRF model with chemistry (WRF-Chem) was employed to simulate the impacts of anthropogenic aerosols on summer precipitation over the Beijing-Tianjin-Hebei urban agglomeration in China. With the aid of a high-resolution gridded inventory of anthropogenic emissions of trace gases and aerosols, we conducted relatively long-term regional simulations, considering direct, semi-direct and indirect effects of the aerosols. Comparing the results of sensitivity experiments with and without emissions, it was found that anthropogenic aerosols tended to enhance summer precipitation over the metropolitan areas. Domain-averaged rainfall was increased throughout the day, except for the time around noon. Aerosols shifted the precipitation probability distribution from light or moderate to extreme rain. Further analysis showed that the anthropogenic aerosol radiative forcing had a cooling effect at the land surface, but a warming effect in the atmosphere. However, enhanced convective strength and updrafts accompanied by water vapor increases and cyclone-like wind shear anomalies were found in the urban areas. These responses may originate from cloud microphysical effects of aerosols on convection, which were identified as the primary cause for the summer rainfall enhancement. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Daily precipitation series at 15 stations in the Beijing metropolitan region (BMR) during 1960-2012 were homogenized using the multiple analysis of series for homogenization method, with additional adjustments based on analysis of empirical cumulative density function (ECDF) regarding climate extremes. The cumulative density functions of daily precipitation series, the trends of annual and seasonal precipitation, and summer extreme events during 1960-2012 in the original and final adjusted series at Beijing station were comparatively analyzed to show the necessity and efficiency of the new method. Results indicate that the ECDF adjustments can improve the homogeneity of high-order moments of daily series and the estimation of climate trends in extremes. The linear trends of the regional-mean annual and seasonal (spring, summer, autumn, and winter) precipitation series are −10.16, 4.97, −20.04, 5.02, and −0.11 mm (10 yr), respectively. The trends over the BMR increase consistently for spring/autumn and decrease for the whole year/summer; however, the trends for winter decrease in southern parts and increase in northern parts. Urbanization affects local trends of precipitation amount, frequency, and intensity and their geographical patterns. For the urban-influenced sites, urbanization tends to slow down the magnitude of decrease in the precipitation and extreme amount series by approximately −10.4% and −6.0%, respectively; enhance the magnitude of decrease in precipitation frequency series by approximately 5.7%; reduce that of extremes by approximately −8.9%; and promote the decreasing trends in the summer intensity series of both precipitation and extremes by approximately 6.8% and 51.5%, respectively. [ABSTRACT FROM AUTHOR]

Projections of potential submerged area due to sea level rise are helpful for improving understanding of the influence of ongoing global warming on coastal areas. The Ensemble Empirical Mode Decomposition method is used to adaptively decompose the sea level time series in order to extract the secular trend component. Then the linear relationship between the global mean sea level (GMSL) change and the Zhujiang (Pearl) River Delta (PRD) sea level change is calculated: an increase of 1.0 m in the GMSL corresponds to a 1.3 m (uncertainty interval from 1.25 to 1.46 m) increase in the PRD. Based on this relationship and the GMSL rise projected by the Coupled Model Intercomparison Project Phase 5 under three greenhouse gas emission scenarios (representative concentration pathways, or RCPs, from low to high emission scenarios RCP2.6, RCP4.5, and RCP8.5), the PRD sea level is calculated and projected for the period 2006-2100. By around the year 2050, the PRD sea level will rise 0.29 (0.21 to 0.40) m under RCP2.6, 0.31 (0.22 to 0.42) m under RCP4.5, and 0.34 (0.25 to 0.46) m under RCP8.5, respectively. By 2100, it will rise 0.59 (0.36 to 0.88) m, 0.71 (0.47 to 1.02) m, and 1.0 (0.68 to 1.41) m, respectively. In addition, considering the extreme value of relative sea level due to land subsidence (i.e., 0.20 m) and that obtained from intermonthly variability (i.e., 0.33 m), the PRD sea level will rise 1.94 m by the year 2100 under the RCP8.5 scenario with the upper uncertainty level (i.e., 1.41 m). Accordingly, the potential submerged area is 8.57×10 km for the PRD, about 1.3 times its present area. [ABSTRACT FROM AUTHOR]

It is well-known that global warming due to anthropogenic atmospheric greenhouse effects advanced the start of the vegetation growing season (SOS) across the globe during the 20th century. Projections of further changes in the SOS for the 21st century under certain emissions scenarios (Representative Concentration Pathways, RCPs) are useful for improving understanding of the consequences of global warming. In this study, we first evaluate a linear relationship between the SOS (defined using the normalized difference vegetation index) and the April temperature for most land areas of the Northern Hemisphere for 1982-2008. Based on this relationship and the ensemble projection of April temperature under RCPs from the latest state-of-the-art global coupled climate models, we show the possible changes in the SOS for most of the land areas of the Northern Hemisphere during the 21st century. By around 2040-59, the SOS will have advanced by −4.7 days under RCP2.6, −8.4 days under RCP4.5, and −10.1 days under RCP8.5, relative to 1985-2004. By 2080-99, it will have advanced by −4.3 days under RCP2.6, −11.3 days under RCP4.5, and −21.6 days under RCP8.5. The geographic pattern of SOS advance is considerably dependent on that of the temperature sensitivity of the SOS. The larger the temperature sensitivity, the larger the date-shift-rate of the SOS. [ABSTRACT FROM AUTHOR]

Long-term meteorological observation series are fundamental for reflecting climate changes. However, almost all meteorological stations inevitably undergo relocation or changes in observation instruments, rules, and methods, which can result in systematic biases in the observation series for corresponding periods. Homogenization is a technique for adjusting these biases in order to assess the true trends in the time series. In recent years, homogenization has shifted its focus from the adjustments to climate mean status to the adjustments to information about climate extremes or extreme weather. Using case analyses of ideal and actual climate series, here we demonstrate the basic idea of homogenization, introduce new understanding obtained from recent studies of homogenization of climate series in China, and raise issues for further studies in this field, especially with regards to climate extremes, uncertainty of the statistical adjustments, and biased physical relationships among different climate variables due to adjustments in single variable series. [ABSTRACT FROM AUTHOR]

We simulated the impact of anthropogenic heat release (AHR) on the regional climate in three vast city agglomerations in China using the Weather Research and Forecasting model with nested high-resolution modeling. Based on energy consumption and high-quality land use data, we designed two scenarios to represent no-AHR and current-AHR conditions. By comparing the results of the two numerical experiments, changes of surface air temperature and precipitation due to AHR were quantified and analyzed. We concluded that AHR increases the temperature in these urbanized areas by about 0.5°C-1°C, and this increase is more pronounced in winter than in other seasons. The inclusion of AHR enhances the convergence of water vapor over urbanized areas. Together with the warming of the lower troposphere and the enhancement of ascending motions caused by AHR, the average convective available potential energy in urbanized areas is increased. Rainfall amounts in summer over urbanized areas are likely to increase and regional precipitation patterns to be altered to some extent. [ABSTRACT FROM AUTHOR]

Daily precipitation and temperature records at 13 stations for the period 1960-2008 were analyzed to identify climatic change and possible effects of urbanization on low-temperature precipitation [LTP, precipitation of ⩾ 0.1 mm d occurring under a daily minimum temperature (Tmin) of ⩽ 0°C] in the greater Beijing region (BJR), where a rapid process of urbanization has taken place over the last few decades. The paper provides a climatological overview of LTP in BJR. LTP contributes 61.7% to the total amount of precipitation in BJR in the cold season (November-March). There is a slight increasing trend [1.22 mm (10 yr)] in the amount of total precipitation for the cold season during 1960-2008. In contrast, the amount of LTP decreases by 0.6 mm (10 yr). The warming rate of Tmin in BJR is 0.66°C (10 yr). Correspondingly, the frequency of LTP decreases with increasing Tmin by −0.67 times per °C. The seasonal frequency and amount of LTP in southeast BJR (mostly urban sites) are 17%-20% less than those in the northwestern (rural and montane sites). The intensity of LTP for the urban sites and northeastern BJR exhibited significant enhancing trends [0.18 and 0.15 mm d (10 yr), respectively]. The frequency of slight LTP (<0.2 mm d) significantly decreased throughout BJR [by about 5.74% (10 yr) in the urban area and northeast BJR], while the contribution of the two heaviest LTP events to total LTP amount significantly increased by 3.2% (10 yr). [ABSTRACT FROM AUTHOR]

To quantify the impact of urbanization on changes in observed surface air temperature and extremes, a homogenized dataset of daily mean, maximum and minimum temperature ( T, T and T) observations at 20 stations in Greater Beijing (GBJ) from 1978 to 2008 is analyzed. In contrast with previous studies, a cluster analysis is done to objectively classify observing stations into four categories (urbanized, suburban, rural and mountain), which is checked with remote-sensing night-light images since the 1990s. At urbanized sites, there is an added warming trend in annual mean T representing an average of 10.9% (up to 18.4% or 0.12°C/decade at the most strongly influenced site) of overall warming. Corresponding contributions for T are 12.7% (up to 20.8% or 0.19°C/decade) and 24% for diurnal temperature range DTR (up to 37.4% or 0.149°C/decade) over the last three decades. Although it has not had a significant impact on daytime records ( T), urbanization has enhanced the increasing (decreasing) trend of extremely warm (cold) nights by an average of 12.7% or 2.07 d/decade (29.0% or 5.06 d/decade) at the urbanized sites since the 1970s. [ABSTRACT FROM AUTHOR]

Global warming exerts a lengthening effect on the growing season, with observational evidences emerging from different regions over the world. However, the difficulty for a global overview of this effect for the last century arises from limited availability of the long-term daily observations. In this study, we find a good linear relationship between the start (end) date of local growing season (LGS) and the monthly mean temperature in April (October) using the global gridded daily temperature dataset for 1960-1999. Using homogenized daily temperature records from nine stations where the time series go back to the beginning of the twentieth century, we find that the rate of change in the start (end) date of the LGS for per degree warming in April (October) mean temperature keeps nearly constant throughout the time. This enables us to study LGS changes during the last century using global gridded monthly mean temperature data. The results show that during the period 1901-2009, averaged over the observation areas, the LGS length has increased by a rate of 0.89 days decade, mainly due to an earlier start (−0.58 days decade). This is smaller than those estimates for the late half of the twentieth century, because of multidecadal climate variability (MDV). A MDV component of the LGS index series is extracted by using Ensemble Empirical Mode Decomposition method. The MDV exhibits significant positive correlation with the Atlantic Multi-decadal Oscillation (AMO) over most of the Northern Hemisphere lands, but negative in parts of North America and Western Asia for start date of LGS. These are explained by analyzing differences in atmospheric circulation expressed by sea level pressure departures between the warm and cool phases of AMO. It is suggested that MDV in association with AMO accelerates the lengthening of LGS in Northern Hemisphere by 53 % for the period 1980-2009. [ABSTRACT FROM AUTHOR]

Two approaches of statistical downscaling were applied to indices of temperature extremes based on percentiles of daily maximum and minimum temperature observations at Beijing station in summer during 1960-2008. One was to downscale daily maximum and minimum temperatures by using EOF analysis and stepwise linear regression at first, then to calculate the indices of extremes; the other was to directly downscale the percentile-based indices by using seasonal large-scale temperature and geo-potential height records. The cross-validation results showed that the latter approach has a better performance than the former. Then, the latter approach was applied to 48 meteorological stations in northern China. The cross-validation results for all 48 stations showed close correlation between the percentile-based indices and the seasonal large-scale variables. Finally, future scenarios of indices of temperature extremes in northern China were projected by applying the statistical downscaling to Hadley Centre Coupled Model Version 3 (HadCM3) simulations under the Representative Concentration Pathways 4.5 (RCP 4.5) scenario of the Fifth Coupled Model Inter-comparison Project (CMIP5). The results showed that the 90th percentile of daily maximum temperatures will increase by about 1.5°C, and the 10th of daily minimum temperatures will increase by about 2°C during the period 2011-35 relative to 1980-99. [ABSTRACT FROM AUTHOR]

Hydrological processes exert enormous influences on the land surface water and energy balance, and have a close relationship with human society. We have developed a new hydrological runoff parameterization called XXT to improve the performance of a coupled land surface-atmosphere modeling system. The XXT parameterization, which is based upon the Xinanjiang hydrological model and TOPMODEL, includes an optimized function of runoff calculation with a new soil moisture storage capacity distribution curve (SMSCC). We then couple XXT with the Global/Regional Assimilation Prediction System (GRAPES) and compare it to GRAPES coupled with a simple water balance model (SWB). For the model evaluation and comparison, we perform 72-h online simulations using GRAPES-XXT and GRAPES-SWB during two torrential events in August 2007 and July 2008, respectively. The results show that GRAPES can reproduce the rainfall distribution and intensity fairly well in both cases. Differences in the representation of feedback processes between surface hydrology and the atmosphere result in differences in the distributions and amounts of precipitation simulated by GRAPES-XXT and GRAPES-SWB. The runoff simulations are greatly improved by the use of XXT in place of SWB, particularly with respect to the distribution and amount of runoff. The average runoff depth is nearly doubled in the rainbelt area, and unreasonable runoff distributions simulated by GRAPES-SWB are made more realistic by the introduction of XXT. Differences in surface soil moisture between GRAPES-XXT and GRAPES-SWB show that the XXT model changes infiltration and increases surface runoff. We also evaluate river flood discharge in the Yishu River basin. The peak values of flood discharge calculated from the output of GRAPES-XXT agree more closely with observations than those calculated from the output of GRAPES-SWB. [ABSTRACT FROM AUTHOR]

Climate extremes and changes in eastern China are closely related to variations of the East Asian summer monsoon and corresponding atmospheric circulations. The relationship between frequencies of temperature and precipitation extremes in China during the last half century is investigated using Singular Value Decomposition analysis. During 1980-1996, there was a typical pattern with fewer hot days and more precipitation extremes in the northern part of eastern China, and more hot days and fewer precipitation extremes in the southern part. This geographic pattern tended to reverse after 1997, with fewer hot days and more extreme precipitation days south of the Yangtze River and vice versa to the north. Differences in atmospheric circulation between the former and latter periods are presented. We conclude that a mid-level anomalous high/low, upper-level anomalous easterlies/westerlies over the north/south of eastern China, a weakened East Asian summer monsoon and associated upper-tropospheric center of cooling (30°N, 110°E) are all favorable for the changes in frequencies of temperature and precipitation extremes. [ABSTRACT FROM AUTHOR]

Having provided an overview of the ideas of developing user-oriented interactive forecast system (UIFS) emerging in recent years, the authors proposed an idealized framework of the new-generation meteorological system, which includes the initial user-end module for configuring the forecast target, the physical predictive and downscaling components, and an incessant assessing module in association with decision-making at the user-end. A case study was carried out with a focus on applying the TIGGE (THORPEX Interactive Grand Global Ensemble; THORPEX stands for The Observing System Research and Predictability Experiment) precipitation forecasts for the hydrological users in Linyi, a region richest in rivers and reservoirs in eastern China. The preliminary results exhibited great potential of improvement in applications of weather forecasts by combining the user-end information. Although the TIGGE results provided by existing national/ international operating models were independent from the user-end, the case study enlightened ways of establishing an iteratively self-improving UIFS involving user-orientation throughout the forecast process. [ABSTRACT FROM AUTHOR]

A probabilistic precipitation forecasting model using generalized additive models (GAMs) and Bayesian model averaging (BMA) was proposed in this paper. GAMs were used to fit the spatial-temporal precipitation models to individual ensemble member forecasts. The distributions of the precipitation occurrence and the cumulative precipitation amount were represented simultaneously by a single Tweedie distribution. BMA was then used as a post-processing method to combine the individual models to form a more skillful probabilistic forecasting model. The mixing weights were estimated using the expectation-maximization algorithm. The residual diagnostics was used to examine if the fitted BMA forecasting model had fully captured the spatial and temporal variations of precipitation. The proposed method was applied to daily observations at the Yishusi River basin for July 2007 using the National Centers for Environmental Prediction ensemble forecasts. By applying scoring rules, the BMA forecasts were verified and showed better performances compared with the empirical probabilistic ensemble forecasts, particularly for extreme precipitation. Finally, possible improvements and application of this method to the downscaling of climate change scenarios were discussed. [ABSTRACT FROM AUTHOR]

The temperature thresholds and timings of the 24 climatic Solar Terms in China are determined from a homogenized dataset of the surface air temperature recorded at 549 meteorological stations for the period 1960-2008 employing the ensemble empirical mode decomposition method. Changes in the mean temperature and timing of the climatic solar terms are illustrated. The results show that in terms of the mean situation over China, the number of cold days such as those of Slight Cold and Great Cold has decreased, especially by 56.8% for Great Cold in the last 10 years (1998-2007) compared with in the 1960s. The number of hot days like those of Great Heat has increased by 81.4% in the last 10 years compared with in the 1960s. The timings of the climatic Solar Terms during the warming period (around spring) in the seasonal cycle have advanced significantly by more than 6 d, especially by 15 d for Rain Water, while those during the cooling period (around autumn) have delayed significantly by 5-6 d. These characteristics are mainly due to a warming shift of the whole seasonal cycle under global warming. However, the warming shift affects the different Solar Terms to various extents, more prominently in the spring than in the autumn. The warming tendencies for Rain Water, the Beginning of Spring, and the Waking of Insects are the largest, 2.43°C, 2.37°C, and 2.21°C, respectively, for the period 1961-2007 in China as a whole. Four particular phenology-related climatic Solar Terms, namely the Waking of Insects, Pure Brightness, Grain Full, and Grain in Ear, are found to have advanced almost everywhere. In semi-arid zones in northern China, advances of the timings of these four climatic Solar Terms are significant, 12-16, 4-8, 4-8, and 8-12 d, respectively, for the period 1961-2007. These quantitative results provide a scientific base for climate change adaptation, especially in terms of agricultural planning and energy-saving management throughout a year. [ABSTRACT FROM AUTHOR]

The purpose of improving weather forecast is to enhance the accuracy in weather prediction. An ideal forecasting system would incorporate user-end information. In recent years, the meteorological community has begun to realize that while general improvements to the physical characteristics of weather forecasting systems are becoming asymptotically limited, the improvement from the user end still has potential. The weather forecasting system should include user interaction because user needs may change with different weather. A study was conducted on the conceptual forecasting system that included a dynamic, user-oriented interactive component. This research took advantage of the recently implemented TIGGE (THORPEX interactive grand global ensemble) project in China, a case study that was conducted to test the new forecasting system with reservoir managers in Linyi City, Shandong Province, a region rich in rivers and reservoirs in eastern China. A self-improving forecast system was developed involving user feedback throughout a flood season, changing thresholds for flood-inducing rainfall that were responsive to previous weather and hydrological conditions, and dynamic user-oriented assessments of the skill and uncertainty inherent in weather prediction. This paper discusses ideas for developing interactive, user-oriented forecast systems. [ABSTRACT FROM AUTHOR]

Changes of the frequency of precipitation extremes (the number of days with daily precipitation exceeding the 90th percentile of a daily climatology, referred to as R90N) in summer (June-August) over the mid-lower reaches of the Yangtze River are analyzed based on daily observations during 1961-2007. The first singular value decomposition (SVD) mode of R90N is linked to an ENSO-like mode of the sea surface temperature anomalies (SSTA) in the previous winter. Responses of different grades of precipitation events to the climatic mode are compared. It is notable that the frequency of summer precipitation extremes is significantly related with the SSTA in the Pacific, while those of light and moderate precipitation are not. It is suggested that the previously well-recognized impact of ENSO on summer rainfall along the Yangtze River is essentially due to a response in summer precipitation extremes in the region, in association with the East Asia-Pacific (EAP) teleconnection pattern. A negative relationship is found between the East Asian Summer Monsoon (EASM) and precipitation extremes over the mid-lower reaches of the Yangtze River. In contrast, light rainfall processes are independent from the SST and EASM variations. [ABSTRACT FROM AUTHOR]

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), 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), 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), 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) 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) 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. [ABSTRACT FROM AUTHOR]

Daily observations of wind speed at 12 stations in the Greater Beijing Area during 1960-2008 were homogenized using the Multiple Analysis of Series for Homogenization method. The linear trends in the regional mean annual and seasonal (winter, spring, summer and autumn) wind speed series were −0.26, −0.39, −0.30, −0.12 and −0.22 m s (10 yr), respectively. Winter showed the greatest magnitude in declining wind speed, followed by spring, autumn and summer. The annual and seasonal frequencies of wind speed extremes (days) also decreased, more prominently for winter than for the other seasons. The declining trends in wind speed and extremes were formed mainly by some rapid declines during the 1970s and 1980s. The maximum declining trend in wind speed occurred at Chaoyang (CY), a station within the central business district (CBD) of Beijing with the highest level of urbanization. The declining trends were in general smaller in magnitude away from the city center, except for the winter case in which the maximum declining trend shifted northeastward to rural Miyun (MY). The influence of urbanization on the annual wind speed was estimated to be about −0.05 m s (10 yr) during 1960-2008, accounting for around one fifth of the regional mean declining trend. The annual and seasonal geostrophic wind speeds around Beijing, based on daily mean sea level pressure (MSLP) from the ERA-40 reanalysis dataset, also exhibited decreasing trends, coincident with the results from site observations. A comparative analysis of the MSLP fields between 1966-1975 and 1992-2001 suggested that the influences of both the winter and summer monsoons on Beijing were weaker in the more recent of the two decades. It is suggested that the bulk of wind in Beijing is influenced considerably by urbanization, while changes in strong winds or wind speed extremes are prone to large-scale climate change in the region. [ABSTRACT FROM AUTHOR]

Trends in the frequencies of four temperature extremes (the occurrence of warm days, cold days, warm nights and cold nights) with respect to a modulated annual cycle (MAC), and those associated exclusively with weather-intraseasonal fluctuations (WIF) in eastern China were investigated based on an updated homogenized daily maximum and minimum temperature dataset for 1960-2008. The Ensemble Empirical Mode Decomposition (EEMD) method was used to isolate the WIF, MAC, and longer-term components from the temperature series. The annual, winter and summer occurrences of warm (cold) nights were found to have increased (decreased) significantly almost everywhere, while those of warm (cold) days have increased (decreased) in northern China (north of 40°N). However, the four temperature extremes associated exclusively with WIF for winter have decreased almost everywhere, while those for summer have decreased in the north but increased in the south. These characteristics agree with changes in the amplitude of WIF. In particular, winter WIF of maximum temperature tended to weaken almost everywhere, especially in eastern coastal areas (by 10%-20%); summer WIF tended to intensify in southern China by 10%-20%. It is notable that in northern China, the occurrence of warm days has increased, even where that associated with WIF has decreased significantly. This suggests that the recent increasing frequency of warm extremes is due to a considerable rise in the mean temperature level, which surpasses the effect of the weakening weather fluctuations in northern China. [ABSTRACT FROM AUTHOR]

Climatic changes in the onset of spring in northern China associated with changes in the annual cycle and with a recent warming trend were quantified using a recently developed adaptive data analysis tool, the Ensemble Empirical Mode Decomposition. The study was based on a homogenized daily surface air temperature (SAT) dataset for the period 1955-2003. The annual cycle here is referred to as a refined modulated annual cycle (MAC). The results show that spring at Beijing has arrived significantly earlier by about 2.98 d (10 yr), of which about 1.85 d (10 yr) is due to changes in the annual cycle and 1.13 d (10 yr) due to the long-term warming trend. Variations in the MAC component explain about 92.5% of the total variance in the Beijing daily SAT series and could cause as much as a 20-day shift in the onset of spring from one year to another. The onset of spring has been advancing all over northern China, but more significant in the east than in the west part of the region. These differences are somehow unexplainable by the zonal pattern of the warming trend over the whole region, but can be explained by opposite changes in the spring phase of the MAC, i.e. advancing in the east while delaying in the west. In the east of northern China, the change in the spring phase of MAC explains 40%-60% of the spring onset trend and is attributable to a weakening Asian winter monsoon. The average sea level pressure in Siberia (55°-80°N, 50°-110°E), an index of the strength of the winter monsoon, could serve as a potential short-term predictor for the onset of spring in the east of northern China. [ABSTRACT FROM AUTHOR]

Homogenization of climate observations remains a challenge to climate change researchers, especially in cases where metadata (e.g., probable dates of break points) are not always available. To examine the influence of metadata on homogenizing climate data, the authors applied the recently developed Multiple Analysis of Series for Homogenization (MASH) method to the Beijing (BJ) daily temperature series for 1960–2006 in three cases with different references: (1) 13M—considering metadata at BJ and 12 nearby stations; (2) 13NOM—considering the same 13 stations without metadata; and (3) 21NOM—considering 20 further stations and BJ without metadata. The estimated mean annual, seasonal, and monthly inhomogeneities are similar between the 13M and 13NOM cases, while those in the 21NOM case are slightly different. The detected biases in the BJ series corresponding to the documented relocation dates are as low as −0.71°C, −0.79°C, and −0.5°C for the annual mean in the 3 cases, respectively. Other biases, including those undocumented in metadata, are minor. The results suggest that any major inhomogeneity could be detected via MASH, albeit with minor differences in estimating inhomogeneities based on the different references. The adjusted annual series showed a warming trend of 0.337, 0.316, and 0.365°C (10 yr)−1 for the three cases, respectively, smaller than the estimate of 0.453°C (10 yr)−1 in the original series, mainly due to the relocation-induced biases. The impact of the MASH-type homogenization on estimates of climate extremes in the daily temperature series is also discussed. [ABSTRACT FROM AUTHOR]

A wavelet method was applied to detect inhomogeneities in daily meteorological series, data which are being increasingly applied in studies of climate extremes. The wavelet method has been applied to a few well-established long-term daily temperature series back to the 18th century, which have been “homogenized” with conventional approaches. Various types of problems remaining in the series were revealed with the wavelet method. Their influences on analyses of change in climate extremes are discussed. The results have importance for understanding issues in conventional climate data processing and for development of improved methods of homogenization in order to improve analysis of climate extremes based on daily data. [ABSTRACT FROM AUTHOR]

An extended narrative dataset of the Medieval time AD 708-1426 in continental western Europe was set up. Some 30-year-moving mean seasonal temperature deviation series were reconstructed. A- warming trend occurred around AD 1200. During the warm stage, seasonal cycle might be weak due to frequent cool summers. Significant warm summer conditions did not occur until the late 14th century, when the annual temperature level began decreasing. The mean warm season temperature level during the late 14th to the early 15th century might be about 0.3°C higher than the present. It was suggested to cautiously comment on historical climates for different seasons. [ABSTRACT FROM AUTHOR]