Detection and attribution of anthropogenic forcing to diurnal temperature range changes from 1950 to 1999: comparing multi-model simulations with observations

Observations show that the surface diurnal temperature range (DTR) has decreased since 1950s over most global land areas due to a smaller warming in maximum temperatures (T _max) than in minimum temperatures (T _min). This paper analyzes the trends and variability in T _max, T _min, and DTR over land in observations and 48 simulations from 12 global coupled atmosphere-ocean general circulation models for the later half of the 20th century. It uses the modeled changes in surface downward solar and longwave radiation to interpret the modeled temperature changes. When anthropogenic and natural forcings are included, the models generally reproduce observed major features of the warming of T _max and T _min and the reduction of DTR. As expected the greenhouse gases enhanced surface downward longwave radiation (DLW) explains most of the warming of T _max and T _min while decreased surface downward shortwave radiation (DSW) due to increasing aerosols and water vapor contributes most to the decreases in DTR in the models. When only natural forcings are used, none of the observed trends are simulated. The simulated DTR decreases are much smaller than the observed (mainly due to the small simulated T _min trend) but still outside the range of natural internal variability estimated from the models. The much larger observed decrease in DTR suggests the possibility of additional regional effects of anthropogenic forcing that the models can not realistically simulate, likely connected to changes in cloud cover, precipitation, and soil moisture. The small magnitude of the simulated DTR trends may be attributed to the lack of an increasing trend in cloud cover and deficiencies in charactering aerosols and important surface and boundary-layer processes in the models.     

Dominant east-west pattern of diurnal temperature range observed across Zambia

Diurnal temperature range (DTR) is an important index for climate because of its statistical relationships to greenhouse gases, urban heat, cloud cover, land use change, and aerosol haze layers. This study examines DTR trends across Zambia for the period 1930–2016 using the latest version of high-resolution monthly data (CRU TS v4.01) from the Climatic Research Unit. Non-parametric trend analyses were extensively employed at different spatial and temporal scales to quantify DTR changes. Taken together, results show a dominant east-west pattern with higher DTR values being observed in the western half of the country. Although there are noticeable differences in the magnitude from one month to the other, this east-west pattern is persistent throughout all the months. It is also found that mean annual DTR is negatively correlated with mean annual cloud cover with a strong and statistically significant coefficient of -0.8 but its correlation with precipitation weakens to -0.5 at the α 0.05. Results from the Mann-Kendall trend test shows marginal increments in DTR during all the seasons and they are all statistically significant at the α 0.05. The observed increments can be attributed to a general decrease in cloud cover over Zambia.     

Watershed-wide trend analysis of temperature characteristics in Karun-Dez watershed, southwestern Iran

Trend estimation of climatic characteristics for a watershed is required to determine developing compatible strategies related to design, development, and management of water resources. In this study, the trends of the annual maximum (T _max), minimum (T _min), and mean (T _mean) air temperature; temperature anomaly (T _anomaly); and diurnal temperature range (DTR) time series at 13 meteorological stations located in the Karun-Dez watershed were analyzed using the Mann–Kendall and linear regression trend tests. The pre-whitening method was used to eliminate the influence of serial correlation on the Mann–Kendall test. The result showed increasing trends in the T _min, T _mean, and T _anomaly series at the majority of stations and decreasing trend in the T _max and DTR series. A geographical analysis of the trends revealed a broad warming trend in most of the watershed, and the cooling trends were observed only in the southern parts. Furthermore, the geographical pattern of the trends in the T _mean and T _anomaly series was similar, and the T _max data did not show any dominant trend for the whole watershed. This study provides temperature change scenarios that may be used for the design of future water resource projects in the watershed.     

Analysis of the change in temperature trends in Subansiri River basin for RCP scenarios using CMIP5 datasets

This study focuses on changes in the maximum and minimum temperature over the Subansiri River basin for different climate change scenarios. For the study, dataset from Intergovernmental Panel on Climate Change (IPCC) fifth assessment report (AR5) (i.e., coupled model intercomparison project phase five (CMIP5) dataset with representative concentration pathway (RCP) scenarios) were utilized. Long-term (2011–2100) maximum temperature (T _max) and minimum temperature (T_min) time series were generated using the statistical downscaling technique for low emission scenario (RCP2.6), moderate emission scenario (RCP6.0), and extreme emission scenario (RCP8.5). Trends and change of magnitude in T _max, T _min, and diurnal temperature range (DTR) were analyzed for different interdecadal time scales (2011–2100, 2011–2040, 2041–2070, 2070–2100) using Mann-Kendall non-parametric test and Sen’s slope estimator, respectively. The temperature data series for the observed duration (1981–2000) has been found to show increasing trends in T _max and T _min at both annual and monthly scale. Trend analysis of downscaled temperature for the period 2011–2100 shows increase in annual maximum temperature and annual minimum temperature for all the selected RCP scenarios; however, on the monthly scale, T _max and T _min have been seen to have decreasing trends in some months.

     

Impact of vegetation feedback on the temperature and its diurnal range over the Northern Hemisphere during summer in a 2 × CO2 climate

This study examines the potential impact of vegetation feedback on the changes in the diurnal temperature range (DTR) due to the doubling of atmospheric CO₂ concentrations during summer over the Northern Hemisphere using a global climate model equipped with a dynamic vegetation model. Results show that CO₂ doubling induces significant increases in the daily mean temperature and decreases in DTR regardless of the presence of the vegetation feedback effect. In the presence of vegetation feedback, increase in vegetation productivity related to warm and humid climate lead to (1) an increase in vegetation greenness in the mid-latitude and (2) a greening and the expansion of grasslands and boreal forests into the tundra region in the high latitudes. The greening via vegetation feedback induces contrasting effects on the temperature fields between the mid- and high-latitude regions. In the mid-latitudes, the greening further limits the increase in T _max more than T _min, resulting in further decreases in DTR because the greening amplifies evapotranspiration and thus cools daytime temperature. The greening in high-latitudes, however, it reinforces the warming by increasing T _max more than T _min to result in a further increase in DTR from the values obtained without vegetation feedback. This effect on T _max and DTR in the high latitude is mainly attributed to the reduction in surface albedo and the subsequent increase in the absorbed insolation. Present study indicates that vegetation feedback can alter the response of the temperature field to increases in CO₂ mainly by affecting the T _max and that its effect varies with the regional climate characteristics as a function of latitudes.     

阿勒泰地区气温日较差的气候变化特征

利用线性趋势法对1961-2008年阿勒泰地区7个气象站点气温日较差进行趋势研究,并根据各因子趋势值,应用相关统计法分析了影响气温日较差呈减小趋势的因子。结果表明：阿勒泰地区四季日较差呈现显著减小趋势,其中冬季最显著,秋季变化最弱。各季节最低气温上升趋势最明显,而最高气温上升趋势较弱。阿勒泰地区与月平均气温日较差相关性最强的因子是日照时数,呈正相关;其次分别为总云量、降水量和水汽压,都呈负相关。年气温日较差与降水量和水汽压相关性最大。     

Spatial gridding of daily maximum and minimum temperatures in Europe

We developed an operationally applicable land-only daily high-resolution (5?km?×?5?km) gridding method for station observations of minimum and maximum 2?m temperature (T _min/T _max) for Europe (WMO region VI). The method involves two major steps: (1) the generation of climatological T _min/T _max maps for each month of the year using block regression kriging, which considers the spatial variation explained by applied predictors; and (2) interpolation of transformed daily anomalies using block kriging, and combination of the resulting anomaly maps with climatological maps. To account for heterogeneous climatic conditions in the estimation of the statistical parameters, these steps were applied independently in overlapping climatic subregions, followed by an additional spatial merging step. Uncertainties in the gridded maps and the derived error maps were quantified: (a) by cross-validation; and (b) comparison with the T _min/T _max maps estimated in two regions having very dense temperature observation networks. The main advantages of the method are the high quality of the daily maps of T _min/T _max, the calculation of daily error maps and computational efficiency.     

Recent trends of mean maximum and minimum air temperatures in the western half of Iran

In this study, the trends of the annual, seasonal and monthly maximum (T _max) and minimum (T _min) air temperatures time series were investigated for 20 stations in the western half of Iran during 1966?C2005. Three statistical tests including Mann?CKendall, Sen??s slope estimator and linear regression were used for the analysis. The annual T _max and T _min series showed a positive trend in 85% of the stations and a negative trend in 15% of the stations in the study region. The highest increase of T _max and T _min values were obtained over Kermanshah and Ahwaz at the rates of (+)0.597°C/decade and (+)0.911°C/decade, respectively. On the seasonal scale, the strongest increasing trends were identified in T _max and T _min data in summer. The highest numbers of stations with positive significant trends occurred in the monthly T _max and T _min series in August. In contrast, the lowest numbers of stations with significant positive trends were observed between November and March. Overall, the results showed similar increasing trends for the study variables, although T _min generally increased at a higher rate than T _max in the study period.     

1961～2015年中国地区冰雹持续时间的时空分布特征及影响因子研究

本文利用1961～2015年（55年）中国地区577个地面观测站的冰雹资料,应用统计学方法,分析了冰雹持续时间的空间分布、年际变化以及日变化特征,包括站点降雹累积持续时间、平均单次降雹持续时间、区域平均单次降雹持续时间、小时降雹累积持续时间和总降雹累积持续时间。结果表明:（1）1961～2015年中国地区站点降雹累积持续时间与海拔高度呈现较高的正相关关系,相关系数高达0.99。站点降雹累积持续时间的最大值出现在青藏高原地区,累积持续时间高达250分钟,其次为内蒙古中部以及东北部的山区地带,累积持续时间约为150分钟。（2）1961～2015年平均单次降雹持续时间呈现上升趋势,55年冰雹累积持续时间大约增长1分钟,且通过了95%信度水平的显著性检验。（3）西北地区、北部平原地区和东南地区在1961～1980年期间,区域平均单次降雹持续时间都有显著的下降趋势,而在1970～2015年期间西北地区和青藏高原地区呈现显著的上升趋势。1961～1980年期间区域平均单次降雹持续时间在西北地区的长期趋势变化主要受到日最低气温以及温度日较差长期年际变化的影响,在北部平原地区仅与温度日较差相关,而在东南地区与三个对流参数都有较好的相关性;1970～2015年和1961～2015年期间西北地区和青藏高原地区的区域平均单次降雹持续时间的上升趋势分别与这两个区域的区域平均日最高气温、日最低气温呈正相关。（4）单次降雹持续时间的日变化明显,午后至夜间出现的冰雹持续时间长于凌晨和上午的冰雹持续时间,持续时间峰值出现在当地时间17时和18时。本文还利用探空资料分析了对流有效势能和Totals-totals指数与冰雹持续时间的关系,结果表明中国地区20时（北京时）的对流有效势能和Totals-totals指数可能是冰雹持续时间日变化的影响因子之一。     

Current and projected water demand and water availability estimates under climate change scenarios in the Weyib River basin in Bale mountainous area of Southeastern Ethiopia

ENSO has been known to influence the trends of summer warming over Southern Africa. In this work, we used observational and reanalysis data to analyze the relationship between ENSO and maximum surface air temperature (SAT_max) trends during the three epochs created by the ENSO phase shifts around 1977 and 1997 for the period 1960 to 2014. We observed that while ENSO and cloud cover remains the dominant factor controlling SAT_max variability, the first two epochs had the predominant La Niña (El Niño)-like events connected to robust positive (negative) trends in cloud fraction. However, this established relationship reversed in the post-1997 La Niña-like dominated epoch which coincided with a falling cloud cover trend. It is established that this deviation from the previously established link within the previous epochs could be due to the post-1998 era in which SAT_min was suppressed while SAT_max was enhanced. The resulting increase in diurnal temperature range (DTR) could have discouraged the formation of low-level clouds which have relatively more extensive areal coverage and hence allowing more solar energy to reach the surface to boost daytime SAT_max. It is noted that these relationships are more pronounced from December to March.     

Trend analysis of Climatic Research Unit temperature dataset for Gangotri glacier,India

The absence of continuous long term meteorological dataset has led to limited knowledge of glaciers’ response to climate change over Himalayas. This study presents an open source long term temperature dataset Climatic Research Unit (CRU) available since 1901 to study trend analysis of temperature (T_max, T_min and T_mean) for Gangotri basin in Himalayas. The study first establishes close agreement between CRU time series data and observed temperature dataset available from National Institute of Hydrology (NIH), Roorkee for a period of 11 years from 2005 to 2015 using standard anomaly, Wilcoxon Signed-Rank (WSR) and correlation tests. The close agreement of CRU with NIH data validate the use of CRU time series to study variation in meteorological parameter for hilly terrain of Himalayas. The second part includes application of different statistical tests such as Mann-Kendall (MK), Sen’s slope and CUSUM technique on CRU data to detect existence of any possible trends and identification of change points in T_max, T_min and T_mean on long term scale. On annual scale, significant increasing trends for T_mean and T_min were observed with no significant trend for T_max. On seasonal and monthly scale, T_max showed significant decreasing trend for monsoon season and increasing trend for winters while T_min show significant increasing trend for all months (except May) and seasons. CUSUM technique identified 8 change points from 3 annual time series with 2 for T_mean (1974 and 1999), 3 each for T_max (1941, 1975 and 1999) and T_min (1941, 1965 and 1999) respectively. Overall, significant increase in T_min with no significant trend for T_max has been identified over the study area.     

Spatial gridding of daily maximum and minimum 2 m temperatures supported by satellite observations

The usefulness of two remotely sensed variables, land surface temperature (LST) and cloud cover (CC), as predictors for the gridding of daily maximum and minimum 2 m temperature (T _min/T _max) was assessed. Four similar gridding methods were compared, each of which applied regression kriging to capture the spatial variation explained by the predictors used; however, both methods differed in the interpolation steps performed and predictor combinations used. The robustness of the gridding methods was tested for daily observations in January and July in the period 2009–2011 and in two different regions: the Central European region (CER) and the Iberian Peninsula (IP). Moreover, the uncertainty estimate provided by each method was evaluated using cross-validation. The regression analyses for both regions demonstrated the high predictive skills of LST for T _min and T _max on daily and monthly timescales (and lower predictive skills of CC). The application of LST as a predictor considerably improved the gridding performance over the IP region in July; however, there was only a slight improvement over the CER region. CC reduced the loss of spatial variability in the interpolated daily T _min/T _max values over the IP region. The interpolation skill was mainly controlled by the station density, but also depended on the complexity of the terrain. LST was shown to be of particular value for very low station densities (1 station per 50,000 km²). Analyses with artificially decreasing station densities showed that even in the case of very low station densities, LST allows the determination of useful regression functions.     

1951~2010年云贵高原大理和丽江气温、降水的气候特征分析

利用大理和丽江气象站1951~2010年的逐日气象资料,分析了横断山脉东部气温、降水的气候特征。结果表明,1991年以后,大理和丽江地区均存在显著增温的趋势（0.58和0.55℃/10 a）,明显高于同时期中国平均气温的增加幅度;而在1991年之前,大理和丽江的年平均气温呈现下降或微弱上升的趋势（-0.14和0.07℃/10 a）。与夏季平均气温的增温幅度相比,冬季平均气温的增温更显著,且其变化趋势与年均气温的气候特征是一致的。大理和丽江年总降水及各季节降水量在1951~2010年并没有明显增加或减少的趋势。大理和丽江雨季开始的时间分别为第28候和第30候,持续时间分别约为5.5和4.5个月。20世纪80年代以后,丽江年平均风速的减小强度明显大于大理,这是因为丽江站地处城区,城市化剧烈,地表粗糙度增加显著。日照时数与云量呈反相的季节变化,降水量的多年平均的逐候变化与日照时数、总云量、尤其是低云云量相关,随风速增大而减小。     

Analysing temporal trends in the Indian Summer Monsoon and its variability at a fine spatial resolution

Temporal trends between 1951 and 2007 in annual Indian Summer Monsoon (ISM) precipitation, frequency of severe drought years and onset date of ISM were analysed on a 0.25°?×?0.25° grid cell basis across India using APHRODITE daily gridded precipitation data. Locations which experienced temporal trends of increasing or decreasing inter-annual variation in annual ISM precipitation and onset date of ISM were detected using the non-parametric Mann-Kendall test. A new method of defining local onset of ISM from daily precipitation data was developed to enable countrywide temporal trend analysis of onset date. India was characterised by a heterogeneous spatial distribution in the magnitude of inter-annual variation and location of significant temporal trends in the examined facets of ISM precipitation. A greater extent of the country experienced significant trends (p?<?0.05) of increasing inter-annual variation rather than simple increasing or decreasing trends in annual ISM precipitation and onset date of ISM. Field significance tests showed grid cells reporting significant trends were significant (p?<?0.05) at the global or field level (except trends of increasing, i.e. later, ISM onset date). This research provides finer spatial detail regarding trends and variation in annual ISM precipitation, severe drought years and onset date of ISM complementing recent studies on trends in extreme precipitation events over India to produce a comprehensive overview of recent behaviour of ISM precipitation. These findings will benefit water managers charged with managing water resources sustainably at a fine spatial scale (the watershed or basin level).     

Empirical estimation of the monthly-mean daily temperature range

Summary ?This is a sequel to a study of the empirical estimation of the annual mean temperature and its range, at any location on land, based on the historical surface climate record. Here the spatial patterns of the daily temperature range (DTR) and its seasonal variation are examined. The DTR is highest in the subtropical deserts and is less at high latitudes, as well as within 30–150 km from an ocean. It is generally higher in winter (summer) at low (high) latitudes. The coastal DTR reduction is explained by sea breezes, onshore advection, and low-level cloud cover. Even large bodies of water, such as Lake Michigan, affect the near-shore DTR. Elevation does not directly affect the DTR, but valleys tend to have a DTR that is 2–6 K larger than adjacent hills or ridges. The main factor affecting the DTR is the afternoon relative humidity, which is dynamically linked to low-level cloud cover. An empirical relationship between DTR and afternoon relative humidity has an uncertainty of about 1.4 K for monthly-mean values. Received March 6, 2002; revised September 20, 2002; accepted November 3, 2002     

Multivariate drought frequency estimation using copula method in Southwest China

This study reveals the impacts of climatic variable trends on drought severity in Xinjiang, China. Four drought indices, including the self-calibrating Palmer drought severity index (sc-PDSI), Erinç’s index (I _m), Sahin’s index (I _sh), and UNEP aridity index (AI), were used to compare drought severity. The ensemble empirical mode decomposition and the modified Mann-Kendall trend test were applied to analyze the nonlinear components and trends of the climatic variable and drought indices. Four and six climatic scenarios were generated in sc-PDSI, I _m, I _sh, and AI with different combinations of the observed and detrended climatic variables, respectively. In Xinjiang, generally increasing trends in minimal, average, and maximal air temperature (T _min, T _ave, T _max) and precipitation (P) were found, whereas a decreasing trend in wind speed at 2 m height (U ₂) was observed. There were significantly increasing trends in all of the four studied drought indices. Drought relief was more obvious in northern Xinjiang than in southern Xinjiang. The strong influences of increased P on drought relief and the weak influences of increased T _min, T _ave, and T _max on drought aggravation were shown by comparing four drought indices under different climate scenarios. Decreased U ₂ had a weak influence on drought, as shown by the AI in different climate scenarios. The weak influences of T and U ₂ were considered to be masked by the strong influences of P on droughts. Droughts were expected to be more severe if P did not increase, but were likely milder without an increase in air temperature and with a decrease in U ₂.     

环杭州湾地区自然植被净初级生产力的变化特征及其成因

利用1971—2006年环杭州湾地区25个气象站的降水、温度和云量资料及全球CO2年平均体积分数资料,采用LPJ全球动态植被模式（Lund-Potsdam-Jena Dynamic Global Vegetation Model）,通过模拟环杭州湾地区的植被年净初级生产力（Annual Net Primary Productivity,ANPP）,分析了该地区ANPP的变化特征,并探讨了植被ANPP变化的可能原因。结果表明：1）就环杭州湾地区,36a间植被ANPP均表现出不同程度的增加,尤其以嘉兴市北部、绍兴市东部较明显;全区平均增加速率为1.5243g·m-2·a-2;2）通过多元线性回归分析发现,环杭州湾地区平均云量与植被ANPP的关系最为密切,偏相关系数为-0.5175,而温度、降水与植被ANPP的关系不明显;同时,植被ANPP对气候变化的响应存在一定的地域性差异;3）在全区平均情况下,36a间由温度下降、降水增加、云量减小、CO2体积分数升高引起的植被ANPP变化趋势分别为-0.0813、-0.0171、0.7601、0.8673g·m-2·a-2,其对应的贡献率分别为-5.18%、-1.09%、48.38%、55.21%。由此可见,该地区植被ANPP变化的主要强迫因子是CO2体积分数和云量,而降水变化对植被ANNP的变化作用不大。     

Analysis of climatic variability and snow cover in the Kaligandaki River Basin,Himalaya, Nepal

Various remote sensing products and observed data sets were used to determine spatial and temporal trends in climatic variables and their relationship with snow cover area in the higher Himalayas, Nepal. The remote sensing techniques can detect spatial as well as temporal patterns in temperature and snow cover across the inaccessible terrain. Non-parametric methods (i.e. the Mann–Kendall method and Sen's slope) were used to identify trends in climatic variables. Increasing trends in temperature, approximately by 0.03 to 0.08 °C year^?1 based on the station data in different season, and mixed trends in seasonal precipitation were found for the studied basin. The accuracy of MOD10A1 snow cover and fractional snow cover in the Kaligandaki Basin was assessed with respect to the Advanced Spaceborne Thermal Emission and Reflection Radiometer-based snow cover area. With increasing trends in winter and spring temperature and decreasing trends in precipitation, a significant negative trend in snow cover area during these seasons was also identified. Results indicate the possible impact of global warming on precipitation and snow cover area in the higher mountainous area. Similar investigations in other regions of Himalayas are warranted to further strengthen the understanding of impact of climate change on hydrology and water resources and extreme hydrologic events.     

营口和鞍山城市气候变化对比分析及原因探讨

利用1951—2005年辽宁省沿海轻工业城市营口和重工业城市鞍山的气温、降水、云量、相对湿度及平均风速等气候资料,采用对比分析方法,分析了近55 a来2城市的各类气候变化特征及产生的原因。结果表明:近55 a来营口和鞍山平均气温呈递增趋势,降水、总云量、平均风速和相对湿度均呈递减趋势,只有低云量变化趋势不同,其中营口呈递增趋势,鞍山呈递减趋势,鞍山平均气温递增趋势及总云量、平均风速和相对湿度递减趋势均强于营口同类气候要素变化;营口和鞍山城市平均气温、相对湿度、低云量和风力气候要素特征趋势变率较大,降水和总云量趋势变率相对较小。     

Projecting the future vegetation–climate system over East Asia and its RCP-dependence

The future vegetation–climate system over East Asia, as well as its dependence on Representative Concentration Pathways (RCPs), is investigated using a regional climate–vegetation model driven with boundary conditions from Flexible Global Ocean–Atmosphere–Land System Model: Grid-point Version 2. Over most of the region, due to the rising CO₂ concentration and climate changes, the model projects greater vegetation density (leaf area index) and gradual shifts of vegetation type from bare ground to grass or from grass to trees; the projected spatial extent of the vegetation shift increases from RCP2.6 to RCP8.5. Abrupt shifts are projected under RCP8.5 over northeast China (with grass replacing boreal needleleaf evergreen trees due to heat stress) and India (with tropical deciduous trees replacing grass due to increased water availability). The impact of vegetation feedback on future precipitation is relatively weak, while its impact on temperature is more evident, especially during DJF over northeast China and India with differing mechanisms. In northeast China, the projected forest loss induces a cooling through increased albedo, and daytime high temperature (T_max) is influenced more than nighttime low temperature (T_min); in India, increased vegetation cover induces an evaporative cooling that outweighs the warming effect of an albedo decrease in DJF, leading to a weaker impact on T_max than on T_min. Based on a single model, the qualitative aspects of these results may hold while quantitative assessment will benefit from a follow-up regional model ensemble study driven by multiple general circulation models.