Northern China maximum temperature in the summer of 1743: A historical event of burning summer in a relatively warm climate background

2004 ◽  
Vol 49 (23) ◽  
pp. 2508-2514
Author(s):  
De’er Zhang ◽  
Demaree Gaston
Keyword(s):  
Northern China ◽  
Maximum Temperature ◽  
Historical Event ◽  
Warm Climate ◽  
Climate Background

scholarly journals Effects of Sunshine Hours and Daily Maximum Temperature Declines and Cultivar Replacements on Maize Growth and Yields

Agronomy ◽  
2020 ◽  
Vol 10 (12) ◽  
pp. 1862
Author(s):  
Libing Song ◽  
Jiming Jin
Keyword(s):  
Growth Period ◽  
Northern China ◽  
Shaanxi Province ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Growth Processes ◽  
Maize Production ◽  
Maize Growth ◽  
Sunshine Hours

In this study, the crop environment resource synthesis maize (CERES-Maize) model was used to explore the effects of declining sunshine hours (SSH), decreasing daily maximum temperature (Tmax), and cultivar replacements on growth processes and yields of maize in Northern China, a principal region of maize production. SSH were found to decrease at 189 of 246 meteorological stations in the northern provinces of China over the period of 1994–2012, and a decrease in Tmax was also seen at many of these stations. The most significant decrease in these two climate variables occurred during June to September, a period for summer maize growth. For this study, seven crop field stations in the ShaanXi province, in the Guanzhong Plain, were selected, all of which showed a downward trend in SSH and Tmax over the period of 1994–2012. The CERES-Maize model was first calibrated and validated against yield observations for these stations over the same period, and the yield simulations matched very well with observations. The model was then driven by the detrended SSH and Tmax data, and the simulations were compared with those with a trend in these two input variables. The decline in SSH was found to reduce the maize yield by 8% on average over these stations due mostly to limited root growth, and the decline for shorter SSH reduced the yield more than that for longer SSH. Meanwhile, the decrease in higher Tmax increased the yield by extending the growth period, while the decrease in lower Tmax reduced the yield by lowering the thermal time. In addition, the observed yield showed a significant upward trend, and our modeling results indicate that this increase can be attributed mainly to the frequent cultivar replacements over our study period. The replaced cultivars usually had a longer growth period than the prior ones, which compensated for the yield loss due to fewer SSH. Net maize production decreased with the combined effects of the declines in SSH and Tmax on yields. This study quantifies the contribution of changes in climate and cultivars to maize growth processes and yields and provides strong insights into maize production under a complex dynamic climate system.

scholarly journals Modeling precipitation δ<sup>18</sup>O pariability in East Asia since the Last Glacial Maximum: temperature and amount effects across different time scales

2016 ◽  
Author(s):  
Xinyu Wen ◽  
Zhengyu Liu ◽  
Zhongxiao Chen ◽  
Esther Brady ◽  
David Noone ◽  
...  
Keyword(s):  
East Asia ◽  
Temperature Effect ◽  
Southern China ◽  
Northern China ◽  
Point Of View ◽  
Central China ◽  
Maximum Temperature ◽  
Past Climate ◽  
Amount Effect ◽  
Significant Temperature

Abstract. Water isotope in precipitation has played a key role in the reconstruction of past climate on millennial and longer timescales. However, for mid-latitude regions like East Asia with complex terrain, the reliability behind the basic assumptions of the temperature effect and amount effect are based on modern observational data and still remains unclear for past climate. In the present work, we re-examine the two basic effects on seasonal, interannual, and millennial timescales in a set of time slice experiments for the period 22 ka thru 00 ka using an isotope-enable AGCM. Our study confirms the robustness of the temperature and amount effects on the seasonal cycle over China, with the temperature effect dominating in northern China, and the amount effect dominating in deep southern China, but no one distinct in the transition region of central China. However, our analysis does not show significant temperature and amount effects over China on millennial and interannual timescales, which is a challenge to those classic assumptions in past climate reconstruction. Our work helps shed light on the interpretation of the proxy record of δ18O from modeling point of view.

Effect of Tree Shading on the Thermal Load of a House in a Warm Climate Zone in Mexico

2012 ◽  
Author(s):  
M. A. Chagolla ◽  
G. Alvarez ◽  
E. Simá ◽  
R. Tovar ◽  
G. Huelsz
Keyword(s):  
Temperature Increase ◽  
Energy Savings ◽  
Maximum Temperature ◽  
Warm Climate ◽  
Indoor Temperature ◽  
Maximum Temperature Difference ◽  
Energy Plus ◽  
Test House ◽  
Simulation Results ◽  
North Latitude

This paper presents the effect of the shade of a tree on the indoor temperature and thermal loads of a house (test house) located in the State of Morelos, Mexico, 18° 50′ 43″ north latitude and 99° 10′ 44″ west longitude. Energy Plus was used to simulate different geometries of the shadow of a tree and the simulation results were compared with experimental measurements of the house without air-conditioning, for one warm and one cold week of the year 2011. The results showed that the maximum temperature difference between the measured and simulated temperatures with both geometry models of tree-shading was 1.7°C. When the effect of tree shading is not considered, it was found that there is a maximum temperature increase of 4°C in the warm week compared with the measured results. In the cold week, the temperature increase was 1.3°C compared with the measured results. Simulation results for an air-conditioned tree-shaded test house show that total annual energy consumption for cooling and heating to achieve thermal comfort represents a substantial energy savings of 76.6% when compared with an unshaded house.

scholarly journals Maximum temperature accounts for annual soil CO2 efflux in temperate forests of Northern China

2015 ◽  
Vol 5 (1) ◽  
Author(s):  
Zhiyong Zhou ◽  
Meili Xu ◽  
Fengfeng Kang ◽  
Osbert Jianxin Sun
Keyword(s):  
Temperate Forests ◽  
Northern China ◽  
Soil Co2 Efflux ◽  
Maximum Temperature ◽  
Co2 Efflux ◽  
Soil Co2

scholarly journals A Comprehensive Study of Spatiotemporal Variations in Temperature Extremes across China during 1960–2018

2021 ◽  
Vol 13 (7) ◽  
pp. 3807
Author(s):  
Na Zhao ◽  
Mingxing Chen
Keyword(s):  
Spatial Heterogeneity ◽  
Mainland China ◽  
Kendall Test ◽  
Northern China ◽  
Central China ◽  
Maximum Temperature ◽  
Temperature Extremes ◽  
Northwestern Part ◽  
Spatiotemporal Variations ◽  
Increasing Trends

Understanding the changing patterns of extreme temperatures is important for taking measures to reduce their associated negative impacts. Based on daily temperature data derived from 2272 meteorological stations in China, the spatiotemporal variations in temperature extremes were examined with respect to covariates by means of the Mann–Kendall test and a spatiotemporal model during 1960–2018. The results indicated that the temporal changes in cold extremes showed decreasing trends and warm extremes experienced increasing trends across almost all of China, with mean change rates of −3.9 days, −1.8 days, 3.7 days and 2.3 days per decade for TN10p, TX10p, TN90p and TX90p, respectively. Nighttime warming/cooling was higher than daytime warming/cooling, which indicated that trends in minimum temperature extremes are more rapid than trends in maximum temperature extremes. In addition, the temporal effect on the temperature extremes varied throughout the year, with significant increasing trends in the temporal heterogeneity of warm extremes occurring during 1992–2018. The areas with strong spatial heterogeneity of cool nights mainly included northeastern and central China, and the spatial variation on cool days was more prominent in northern China. For warm nights, the areas showing high spatial heterogeneity were mainly located in the northwestern part of China, while areas for warm days were distributed in northern China. Our results provide meaningful information for a deeper understanding of the spatiotemporal variations in temperature extremes across mainland China.

scholarly journals Observational Evidences of Double Cropping Impacts on the Climate in the Northern China Plains

2012 ◽  
Vol 25 (13) ◽  
pp. 4721-4728 ◽  
Author(s):  
C.-H. Ho ◽  
S.-J. Park ◽  
S.-J. Jeong ◽  
J. Kim ◽  
J.-G. Jhun
Keyword(s):  
Land Surface ◽  
Vegetation Index ◽  
Meteorological Data ◽  
Regional Climate ◽  
Northern China ◽  
Specific Humidity ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Double Cropping

Abstract The impacts of harvested cropland in the double cropping region (DCR) of the northern China plains (NCP) on the regional climate are examined using surface meteorological data and the satellite-derived normalized difference vegetation index (NDVI) and land surface temperature (LST). The NDVI data are used to distinguish the DCR from the single cropping region (SCR) in the NCP. Notable increases in LST in the period May–June are found in the area identified as the DCR on the basis of the NDVI data. The difference between the mean daily maximum temperature averaged over the DCR and SCR stations peaks at 1.27°C in June. The specific humidity in the DCR is significantly smaller than in the SCR. These results suggest that the enhanced agricultural production by multiple cropping may amplify regional warming and aridity to further modify the regional climate in addition to the global climate change. Results in this study may also be used as a quantitative observed reference state of the crop/vegetation effects for future climate modeling studies.

scholarly journals Estimation of Urbanization Impacts on Local Weather: A Case Study in Northern China (Jing-Jin-Ji District)

Water ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 797 ◽  
Author(s):  
Hui-Dong Su ◽  
Xuejian Cao ◽  
Da-Cheng Wang ◽  
Yang-Wen Jia ◽  
Guangheng Ni ◽  
...  
Keyword(s):  
Large Population ◽  
Management Strategies ◽  
Wrf Model ◽  
Single Layer ◽  
Northern China ◽  
Maximum Temperature ◽  
Rapid Urbanization ◽  
Temperature And Precipitation ◽  
The Mean ◽  
Local Weather

With the past rapid economic development and large population growth, Jing-Jin-Ji District has been undergoing rapid urbanization, which has caused considerable regional weather changes in local regions. In this paper, we used the Weather Research and Forecasting (WRF) model to quantitatively analyze the effects of past urbanization and potential future urbanization on the regional weather in the center of Jing-Jin-Ji District. The hydrometeorological data from two weeks in July 2019 were used to simulate the influence of urbanization on local weather in the Jing-Jin-Ji District at regional scales using a single-layer canopy parameterization scheme. To better quantify the differences in temperature and precipitation induced by urbanization, three simulation scenarios were designed, which were no urban cover (NU), current urbanization cover (CU), and full urban land cover (FU), respectively. The results showed that: (1) Urbanization progress (from NU to CU and from CU to FU) in Jing-Jin-Ji District increased the daytime temperature, night temperature, and temperature difference between day and night, while decreasing the total rainfall and peak rainfall. (2) Compared with NU, the mean temperature of the CU and FU increased 0.3 K and 0.6 K, respectively, and the mean precipitation of CU and FU decreased by approximately 6% and 8.4%, respectively. (3) The main influence of urbanization on weather was reflected by the maximum temperature and peak rainfall, while the other impacts were relatively insignificant. (4) Compared with NU, the maximum temperature of CU and FU increased 0.82 K and 1.35 K, respectively, and the peak rainfall of NU and FU decreased by approximately 9.5% and 19.0%, respectively; The results of this study bring to light the urban management strategies for policy makers.

scholarly journals Monitoring landcover change and desertification processes in northern China and Mongolia using historical written sources and vegetation indices

2021 ◽  
Author(s):  
Michael Kempf
Keyword(s):  
Climate Change ◽  
Land Degradation ◽  
Vegetation Index ◽  
Northern China ◽  
Ice Age ◽  
Maximum Temperature ◽  
Political Agenda ◽  
The Past ◽  
Landcover Change ◽  
Written Sources

Abstract. Fighting land degradation of semi-arid and climate-sensitive grasslands are among the most urgent tasks of current eco-political agenda. Northern China and Mongolia are particularly prone to surface transformations caused by heavily increased livestock numbers during the 20th century. Extensive overgrazing and resource exploitation amplify regional climate change effects and trigger intensified surface transformation, which forces policy-driven interventions to prevent desertification. In the past, the region has been subject to major shifts in environmental and socio-cultural parameters, what makes it difficult to measure the extent of the regional anthropogenic impact and global climate change. This article analyses historical written sources, palaeoenvironmental data, and Normalized Difference Vegetation Index (NDVI) temporal series from the Moderate Resolution Imaging Spectroradiometer (MODIS) to compare landcover change during the Little Ice Age (LIA) and the reference period 2000–2018. Results show that decreasing precipitation and temperature records led to increased land degradation during the late 17th century. However, modern landcover data shows enhanced expansion of bare lands contrasting an increase in precipitation (Ptotal) and maximum temperature (Tmax). Vegetation response during the early growing season (March–May) and the late grazing season (September) does not relate to Ptotal and Tmax and generally low NDVI values indicate no major grassland recovery over the past 20 years.

scholarly journals Predicting the influence of climate on grassland area burned in Xilingol, China with dynamic simulations of autoregressive distributed lag models

PLoS ONE ◽  
2020 ◽  
Vol 15 (4) ◽  
pp. e0229894 ◽  
Author(s):  
Ali Hassan Shabbir ◽  
Jiquan Zhang ◽  
James D. Johnston ◽  
Samuel Asumadu Sarkodie ◽  
James A. Lutz ◽  
...  
Keyword(s):  
Climate Change ◽  
Wind Speed ◽  
Inner Mongolia ◽  
Northern China ◽  
Maximum Temperature ◽  
Science Literature ◽  
Dynamic Simulations ◽  
Area Burned ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag

The influence of climate change on wildland fire has received considerable attention, but few studies have examined the potential effects of climate variability on grassland area burned within the extensive steppe land of Eurasia. We used a novel statistical approach borrowed from the social science literature—dynamic simulations of autoregressive distributed lag (ARDL) models—to explore the relationship between temperature, relative humidity, precipitation, wind speed, sunlight, and carbon emissions on grassland area burned in Xilingol, a large grassland-dominated landscape of Inner Mongolia in northern China. We used an ARDL model to describe the influence of these variables on observed area burned between 2001 and 2018 and used dynamic simulations of the model to project the influence of climate on area burned over the next twenty years. Our analysis demonstrates that area burned was most sensitive to wind speed and temperature. A 1% increase in wind speed was associated with a 20.8% and 22.8% increase in observed and predicted area burned respectively, while a 1% increase in maximum temperature was associated with an 8.7% and 9.7% increase in observed and predicted future area burned. Dynamic simulations of ARDL models provide insights into the variability of area burned across Inner Mongolia grasslands in the context of anthropogenic climate change.

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