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We evaluated the potential impact of future climate change on spring maize and single-crop rice in northeastern China (NEC) by employing climate and crop models. Based on historical data, diurnal temperature change exhibited a distinct negative relationship with maize yield, whereas minimum temperature correlated positively to rice yield. Corresponding to the evaluated climate change derived from coupled climate models included in the Coupled Model Intercomparison Project Phase 5 (CMIP5) under the Representative Concentration Pathway 4.5 scenario (RCP4.5), the projected maize yield changes for three future periods [2010-39 (period 1), 2040-69 (period 2), and 2070-99 (period 3)] relative to the mean yield in the baseline period (1976-2005) were 2.92%, 3.11% and 2.63%, respectively. By contrast, the evaluated rice yields showed slightly larger increases of 7.19%, 12.39%, and 14.83%, respectively. The uncertainties in the crop response are discussed by considering the uncertainties obtained from both the climate and the crop models. The range of impact of the uncertainty became markedly wider when integrating these two sources of uncertainty. The probabilistic assessments of the evaluated change showed maize yield to be relatively stable from period 1 to period 3, while the rice yield showed an increasing trend over time. The results presented in this paper suggest a tendency of the yields of maize and rice in NEC to increase (but with great uncertainty) against the background of global warming, which may offer some valuable guidance to government policymakers. [ABSTRACT FROM AUTHOR]

Satellite-derived Land Surface Temperature (LST) dynamics have been increasingly used to study various geophysical processes. This review provides an extensive overview of the applications of LST in the context of global change. By filtering a selection of relevant keywords, a total of 164 articles from 14 international journals published during the last two decades were analyzed based on study location, research topic, applied sensor, spatio-temporal resolution and scale and employed analysis methods. It was revealed that China and the USA were the most studied countries and those that had the most first author affiliations. The most prominent research topic was the Surface Urban Heat Island (SUHI), while the research topics related to climate change were underrepresented. MODIS was by far the most used sensor system, followed by Landsat. A relatively small number of studies analyzed LST dynamics on a global or continental scale. The extensive use of MODIS highly determined the study periods: A majority of the studies started around the year 2000 and thus had a study period shorter than 25 years. The following suggestions were made to increase the utilization of LST time series in climate research: The prolongation of the time series by, e.g., using AVHRR LST, the better representation of LST under clouds, the comparison of LST to traditional climate change measures, such as air temperature and reanalysis variables, and the extension of the validation to heterogenous sites. [ABSTRACT FROM AUTHOR]

Observed surface air temperature (SAT) warming at urban stations often contains both the signal of global warming and that of local urban heat island (UHI) effects; these signals are difficult to separate. In this study, an urban impact indicator (Uii) developed by the authors was modified to represent the extent to which the observed temperature from a given station was influenced by UHI effects. The Uii of a city was calculated by simplifying the city's shape to a circle. In addition, a modified Uii (MUii) was calculated by considering the realistic horizontal distribution of the urban land. We selected 45 urban stations in mainland China, along with an adjacent station for each to give a station pair. Background climate changes across each pair were near-homogeneous. Thus, differences in the trends of annual averaged daily mean SAT (Trendmean), maximum SAT (Trendmax), and minimum SAT (Trendmin) between the urban and adjacent stations (ΔTrend) could be mainly attributed to differences in MUii changes between the urban and adjacent stations (ΔMUii). Several linear regressions between ΔTrend and ΔMUii for the 45 station pairs were calculated to estimate UHI effects on Trendmean (UTmean), Trendmax (UTmax), and Trendmin (UTmin). The results showed that the mean MUii of the 45 urban stations increased from 0.06 to 0.35 during 1992 - 2013. Positive correlations between ΔMUii and ΔTrend for the 45 station pairs were significant at the 0.001 significance level (except for Trendmax). The average UTmean and UTmin of the 45 urban stations during 1954 - 2013 were approximately 0.05 and 0.11°C decade-1, respectively, accounting for 18% and 31% of the overall warming trends, respectively. The UTmin estimated in this study is about twice that of previous results based on regression equations between Uii and SAT trends. [ABSTRACT FROM AUTHOR]

Background: To study the impact of climate warming on crops, it is crucial to have a warming equipment suitable for their field environment. A facility is needed that can provide suitable combinations of different temperatures at reasonable cost for large plots. Results: Here, an additional field warming facility option named the hot-blast warming facility (HBWF), which comprised heaters, blowers, wind breaks, and a control board was developed. An application case based on HBWF was carried out to assess elevated temperature effects on rice in Central China during 2015 and 2016. We tested four elevated temperature treatments on four rice cultivars under paddy field conditions and measured yield and its components. Heating convection air directly, the facility could increase the temperature of the rice canopy up to 1–2 °C, which could properly simulate global warming. Considering the costs, the HBWF reduced the operating costs because of its relatively lower power consumption (0.164 kW/m2), which was 80% lower than that of Free Air Temperature Increase. Our results demonstrate that the HBWF could build a 25 m2 homogeneous heating area and had little effect on the relative humidity under a paddy field environment. Warming treatments significantly reduced the grain yield by 4.4–22.7% in 2015, and 30.8–61.9% in 2016, compared to the control. The main contribution to the significant decrease of the grain yields was the decrease in seed setting rate. Moreover, a reduction of 1000-grain weight led to the decline in grain yield. The increasing ranges of the temperature simulated by HBWF were stable in different years, however, whether the elevated treatments demonstrated significant difference on rice growth mainly decided by the basic atmospheric temperature (as the control) during the growth period. Conclusions: The new warming facility is suitable for field trials to assess elevated temperature combinations and provides an extra equipment option for use in elevated temperature research in the future. [ABSTRACT FROM AUTHOR]

This study examines the sampling error uncertainties in the monthly surface air temperature (SAT) change in China over recent decades, focusing on the uncertainties of gridded data, national averages, and linear trends. Results indicate that large sampling error variances appear at the station-sparse area of northern and western China with the maximum value exceeding 2.0 K while small sampling error variances are found at the station-dense area of southern and eastern China with most grid values being less than 0.05 K. In general, the negative temperature existed in each month prior to the 1980s, and a warming in temperature began thereafter, which accelerated in the early and mid-1990s. The increasing trend in the SAT series was observed for each month of the year with the largest temperature increase and highest uncertainty of 0.51 ± 0.29 K (10 year) occurring in February and the weakest trend and smallest uncertainty of 0.13 ± 0.07 K (10 year) in August. The sampling error uncertainties in the national average annual mean SAT series are not sufficiently large to alter the conclusion of the persistent warming in China. In addition, the sampling error uncertainties in the SAT series show a clear variation compared with other uncertainty estimation methods, which is a plausible reason for the inconsistent variations between our estimate and other studies during this period. [ABSTRACT FROM AUTHOR]

Positive degree-day (PDD) indicates the accumulated positive temperature in a given time period; it directly relates to the melting of snow and ice, and it is a key parameter between global warming and cryosphere changes. In this study, we calculated the PDD based on the daily mean temperatures from 1960 to 2018 at meteorological stations, and we used measured and interpolated data to determine spatial and temporal distribution and changes in PDD in western China (WC). Results show that the mean annual, warm season, and cold season PDD values at 209 meteorological stations were 3652.2, 2832.9, and 819.3 °C, respectively. PDD spatial distribution in WC is similar to that of air temperature. In WC, PDD mainly ranged from 0 to 5000, 1000 to 4000, and 0 to 1000 °C year−1, respectively for annual, warm season, and cold season. From 1960 to 2018, the observed mean initial day of PDD moved forward by 8.3 days, and the final day was delayed by 8.2 days, with the duration expanding to 16.6 days; the trend in PDD reversed in the 1980s and the change rate in PDD for annual, warm season and cold season was 6.6, 3.8, and 2.7 °C year−1, respectively. Regionally, PDD increased in almost all areas; the high PDD advanced from south to north, east to west, desert to mountain, and low to high altitudes. The results also showed that the warming rate of PDD was lower in the cold season and in high-altitude areas, which was opposite to the observed temperature patterns, however, the non-linear relationship between PDD and mean temperature over a period of time is the main reason for this phenomenon. This study adds more details for the understanding of climate change in WC, and suggests that more attention should be paid to PDD in the study of cryosphere changes. [ABSTRACT FROM AUTHOR]

Characterized by increasing surface air temperature, global warming has altered the hydrological cycle at global and regional scales. In order to adapt water resources management under the context of global warming, attribution analysis on regional differentiation of water resources in the Yangtze River basin (YRB) was conducted in this study. Meteoro-hydrological variations across the basin were examined for the period 1960–2013, and then a statistic-based method was applied in quantifying the contributions of climate variability and human activities on annual runoff variations in different tributary sub-basins in the YRB. Our observation indicates that both the annual increasing rate and the inter-annual fluctuations of temperature in China and in the YRB were higher than that of the global average since the turn of the century. Climate change analysis indicates that the YRB experienced a hot-wet period during 1994–2002 and a hot-dry period during 2003–2013, since the step change of temperature in 1993. Contributions of climate change and human activities on runoff variations varied spatially in the basin. With reference to the baseline period of 1960–1993, the contribution of climate change played a dominant role in most regions of the basin, especially in those upstream sub-basins. The effect of human activities in the basin was quite complicated, not only its regional differentiation, but also its contribution were opposite during the hot-wet period and the hot-dry period in some sub-basins. The result of this study is helpful in understanding the impacts of climate change and human activities on water resources variation in both temporal and spatial scales. [ABSTRACT FROM AUTHOR]