The Relative Impact of Regional Scale Land Cover Change and Increasing CO2 over China

A series of 17-yr equilibrium simulations using the NCAR CCM3 (T42 resolution) were performed to investigate the regional scale impacts of land cover change and increasing CO2 over China. Simulations with natural and current land cover at CO2 levels of 280,355, 430, and 505 ppmv were conducted. Results show statistically significant changes in major climate fields (e.g. temperature and surface wind speed) on a 15-yr average following land cover change. We also found increases in the maximum temperature and in the diurnal temperature range due to land cover change. Increases in CO2 affect both the maximum and minimum temperature so that changes in the diurnal range are small. Both land cover change and CO2 change also impact the frequency distribution of precipitation with increasing CO2 tending to lead to more intense precipitation and land cover change leading to less intense precipitation-indeed, the impact of land cover change typically had the opposite effect versus the impacts of CO2. Our results provide support for the inclusion of future land cover change scenarios in long-term transitory climate inodelling experiments of the 21st Century. Our results also support the inclusion of land surface models that can represent future land cover changes resulting from an ecological response to natural climate variability or increasing CO2. Overall, we show that land cover change can have a significant impact on the regional scale climate of China, and that regionally, this impact is of a similar magnitude to increases in CO2 of up to about 430 ppmv. This means that that the impact of land cover change must be accounted for in detection and attribution studies over China.     

The role of land surface processes in regional climate change: a case study of future land cover change over south western Australia

Summary Using a high resolution regional climate model we perform multiple January simulations of the impact of land cover change over western Australia. We focus on the potential of reforestation to ameliorate the projected warming over western Australia under two emission scenarios (A2, B2) for 2050 and 2100. Our simulations include the structural and physiological responses of the biosphere to changes in climate and changes in carbon dioxide. We find that reforestation has the potential to reduce the warming caused by the enhanced greenhouse effect by as much as 30% under the A2 and B2 scenarios by 2050 but the cooling effect declines to 10% by 2100 as CO₂-induced warming intensifies. The cooling effect of reforestation over western Australia is caused primarily by the increase in leaf area index that leads to a corresponding increase in the latent heat flux. This cooling effect is localized and there were no simulated changes in temperature over regions remote from land cover change. We also show that the more extreme emission scenario (A2) appears to lead to a more intense response in photosynthesis by 2100. Overall, our results are not encouraging in terms of the potential to offset future warming by large scale reforestation. However, at regional scales the impact of land cover change is reasonably large relative to the impact of increasing carbon dioxide (up to 2050) suggesting that future projections of the Australian climate would benefit from the inclusion of projections of future land cover change. We suggest that this would add realism and regional detail to future projections and perhaps aid detection and attribution studies.     

近20年中国土地利用变化影响区域气候的数值模拟

区域尺度土地利用/土地覆盖变化(LUCC)的气候效应以及土地覆盖数据的不确定性, 一直是LUCC研究不可忽视的关键问题。本研究基于最新的遥感资料, 采用新的区域气候模式RegCM4.0, 探讨了1990年至2010年中国LUCC对区域气候的影响。结果表明, 中国区域LUCC使得局地气温和日较差发生了显著改变, 而降水及低层环流场变化不显著;LUCC的影响存在季节性差异, 其中, 夏秋季响应程度较大且主要体现在边界层内。就LUCC对气候影响的机理各地区有所不同, 华北地区LUCC的气候效应主要受蒸散发作用主导, 而长江流域则由反照率与蒸散发共同作用。这些结果均说明, 较短时间尺度的LUCC气候效应主要体现在其局地范围, 且在不同的季节有所差异。     

Probabilistic simulations of the impact of increasing leaf-level atmospheric carbon dioxide on the global land surface

Using a climate model with a sophisticated land surface scheme, simulations were conducted to explore the impact of increases in leaf-level carbon dioxide (CO₂) on evaporation, temperature and other land surface quantities. Fifty-one realizations were run, for each of four Januarys and four Julys for CO₂ concentrations at leaf-level of 280, 375, 500, 650, 840 and 1,000 ppmv. Atmospheric CO₂ concentration was held constant at 375 ppmv in all experiments. Statistically significant decreases in evaporation and increases in temperature occur in specific regions as leaf-level CO₂ is increased from 280 to 375 ppmv. These same areas expand geographically, and the magnitude of the changes increase as leaf-level CO₂ is increased further suggesting that changes are caused by the increase in leaf-level CO₂ and are not internal model variability. As leaf-level CO₂ is increased further, larger areas of the continental surface are affected by increasing amounts and a statistically significant change in precipitation is seen. The increase in leaf-level CO₂ from 280 ppmv to 375 ppmv causes statistically significant changes in the evaporation over 12% of continental surfaces in July. This increases to 25% at 500 ppmv, 35% at 650 ppmv, 41% at 840 ppmv and 47% at 1,000 ppmv. This affects temperature and rainfall by similar amounts, generally in coincident regions. An analysis of these results over key regions shows that the probability density functions of the latent heat flux and temperature are affected non-uniformly. There is a shift in the latent heat flux probability density function to lower values, mainly through the reduction in the upper tail of the distribution. The temperature probability density function shifts to higher values, mainly through an increase in the upper tail of the distribution indicating that the impact is focussed on extremes. Given that there are a suite of well evaluated land surface models that include the biogeochemical effects of increasing CO₂ we suggest that the inclusion of such a model should be a recommended component of climate models used in future assessment reports by the Intergovernmental Panel on Climate Change.     

关于气候变化对社会经济系统影响的机理和途径的探讨

本文基于考虑气候变化影响应与经济系统的特征时空尺度相匹配的观点,讨论了气候变化对经济系统影响的途径.认为:气候变化是年代际尺度的气温变化,直接影响的是冰冻圈、海平面、水资源、陆面状况、生态系统、微生物、人体健康等七个领域;觉察不到日变化、季节变化、年际变化而呈现出年代际变化的事物才是受全球变暖影响的事物;由于时间尺度不匹配,经济系统几乎不会受气候变化的直接影响;就间接影响而言,全球变暖导致的极端气候事件加剧和人类为应对与适应气候变化的积极响应,对经济系统的影响要显著得多.     

MM5 Simulations of the China Regional Climate During the LGM.Ⅰ: Influence of CO2 and Earth Orbit Change

Using a regional climate model MM5 nested to an atmospheric global climate model CCM3, a series of simulations and sensitivity experiments have been performed to investigate the relative Last Glacial Maximum (LGM) climate response to different mechanisms over China. Model simulations of the present day (PD) climate and the LGM climate change are in good agreement with the observation data and geological records, especially in the simulation of precipitation change. Under the PD and LGM climate, changes of earth orbital parameters have a small influence on the annual mean temperature over China.However, the magnitude of the effect shows a seasonal pattern, with a significant response in winter. Thus,this influence cannot be neglected. During the LGM, CO2 concentration reached its lowest point to 200 ppmv. This results in a temperature decrease over China. The influences of CO2 concentration on climate show seasonal and regional patterns as well, with a significant influence in winter. On the contrary, CO2concentration has less impact in summer season. In some cases, temperature even increases with decreasing in CO2 concentration. This temperature increase is the outcome of decrease in cloud amount; hence increase the solar radiation that reached the earth's surface. This result suggests that cloud amount plays a very important role in climate change and could direct the response patterns of some climate variables such as temperature during certain periods and over certain regions. In the Tibetan Plateau, the temperature responses to changes of the above two factors are generally weaker than those in other regions because the cloud amount in this area is generally more than in the other areas. Relative to the current climate, changes in orbital parameters have less impact on the LGM climate than changes in CO2 concentration. However,both factors have rather less contributions to the climate change in the LGM. About 3%-10% changes in the annual mean temperature are contributed by CO2.     

MM5 Simulations of the China Regional Climate During the LGM.I: In uence of CO2 and Earth Orbit Change

Using a regional climate model MM5 nested to an atmospheric global climate model CCM3, a series of simulations and sensitivity experiments have been performed to investigate the relative Last Glacial Maximum (LGM) climate response to different mechanisms over China. Model simulations of the present day (PD) climate and the LGM climate change are in good agreement with the observation data and geological records, especially in the simulation of precipitation change. Under the PD and LGM climate,changes of earth orbital parameters have a small influence on the annual mean temperature over China.However, the magnitude of the effect shows a seasonal pattern, with a significant response in winter. Thus,this influence cannot be neglected. During the LGM, CO2 concentration reached its lowest point to 200 ppmv. This results in a temperature decrease over China. The influences of CO2 concentration on climate show seasonal and regional patterns as well, with a signi cant influence in winter. On the contrary, CO2 concentration has less impact in summer season. In some cases, temperature even increases with decreasing in CO2 concentration. This temperature increase is the outcome of decrease in cloud amount; hence increase the solar radiation that reached the earth's surface. This result suggests that cloud amount plays a very important role in climate change and could direct the response patterns of some climate variables such as temperature during certain periods and over certain regions. In the Tibetan Plateau, the temperature responses to changes of the above two factors are generally weaker than those in other regions because the cloud amount in this area is generally more than in the other areas. Relative to the current climate, changes in orbital parameters have less impact on the LGM climate than changes in CO2 concentration. However,both factors have rather less contributions to the climate change in the LGM. About 3%-10% changes in the annual mean temperature are contributed by CO2.     

A Numerical Simulation Study of Impacts of Historical Land-Use Changes on the Regional Climate in China Since 1700

By using the improved regional climate model (BCC_RegCM1.0), a series of modeling experiments are undertaken to investigate the impacts of historical land-use changes (LUCs) on the regional climate in China. Simulations are conducted for 2 years using estimated land-use for 1700, 1800, 1900, 1950, and 1990. The conversion of land cover in these periods was extensive over China, where large areas were altered from forests to either grass or crops, or from grasslands to crops. Results show that, since 1700, historical LUCs have significant effects on regional climate change, with rainfall increasing in the middle and lower reaches of the Yangtze River Basin, Northwest China, and Northeast China, but decreasing by different degrees in other regions. The air temperature shows significant warming over large areas in recent hundred years, especially from 1950 to 1990, which is consistent with the warming caused by increasing greenhouse gases. On the other hand, historical LUCs have obvious effects on mean circulation, with the East Asian winter and summer monsoonal flows becoming more intensive, which is mainly attributed to the amplifled temperature difference between ocean and land due to vegetation change. Thus, it would be given more attention to the impacts of LUCs on regional climate change.     

中国区域陆面覆盖变化的气候效应模拟研究

基于MODIS和CLCV陆面覆盖资料,利用区域气候模式RegCM4分别进行两组24年（1978-2001年）的数值模拟试验,研究中国区域陆面覆盖变化对区域气候的影响。结果表明,以荒漠化和植被退化为主要特征的陆面覆盖变化通过改变陆面能量、水分平衡与大尺度环流进而对气候要素产生重要影响。夏季,中国南方地区普遍降温,季风边缘区及藏北高原气温升高,降水减少;季风边缘区与西北地区气温年际波动加剧;内蒙古中东部地区西南风增强,进而水汽输送增强,一定程度上增加了该地区降水。冬季,中国东部地区偏北气流增强,更多干燥冷空气南下,使得黄河以南地区降水减少、气温降低。     

A comparison of a GCM response to historical anthropogenic land cover change and model sensitivity to uncertainty in present-day land cover representations

This study assesses the sensitivity of the fully coupled NCAR-DOE PCM to three different representations of present-day land cover, based on IPCC SRES land cover information. We conclude that there is significant model sensitivity to current land cover characterization, with an observed average global temperature range of 0.21 K between the simulations. Much larger contrasts (up to 5 K) are found on the regional scale; however, these changes are largely offsetting on the global scale. These results show that significant biases can be introduced when outside data sources are used to conduct anthropogenic land cover change experiments in GCMs that have been calibrated to their own representation of present-day land cover. We conclude that hybrid systems that combine the natural vegetation from the native GCM datasets combined with human land cover information from other sources are best for simulating such impacts. We also performed a prehuman simulation, which had a 0.39 K ~higher average global temperature and, perhaps of greater importance, temperature changes regionally of about 2 K. In this study, the larger regional changes coincide with large-scale agricultural areas. The initial cooling from energy balance changes appear to create feedbacks that intensify mid-latitude circulation features and weaken the summer monsoon circulation over Asia, leading to further cooling. From these results, we conclude that land cover change plays a significant role in anthropogenically forced climate change. Because these changes coincide with regions of the highest human population this climate impact could have a disproportionate impact on human systems. Therefore, it is important that land cover change be included in past and future climate change simulations.     

气候检测与归因的格兰杰检验法

为揭示气候变化并探索其可能原因,引入了格兰杰因果检验法。在叙述其基本原理的基础上,对影响中国气温变化的若干因子进行了检验。论证了通过检验的因子与中国气温变化的可能物理联系,着重说明了二氧化碳增加对中国气温变化的影响,解释了我国增温滞后于全球气温变化的原因。由此证实格兰杰因果检验法是气候变化检测与归因的一种有用的新方法。通过计算和分析,证实了格兰杰检验法的可用性。     

Impact of land use changes on surface warming in China

Land use changes such as urbanization, agriculture, pasturing, deforestation, desertification and irrigation can change the land surface heat flux directly, and also change the atmospheric circulation indirectly, and therefore affect the local temperature. But it is difficult to separate their effects from climate trends such as greenhouse-gas effects. Comparing the decadal trends of the observation station data with those of the NCEP/NCAR Reanalysis (NNR) data provides a good method to separate the effects because the NNR is insensitive to land surface changes. The effects of urbanization and other land use changes over China are estimated by using the difference between the station and the NNR surface temperature trends. Our results show that urbanization and other land use changes may contribute to the observed 0.12℃ (10 yr)- 1 increase for daily mean surface temperature, and the 0.20℃ (10 yr)- 1 and 0.03℃ (10 yr)-1 increases for the daily minimum and maximum surface temperatures, respectively. The urban heat island effect and the effects of other land-use changes mayalso play an important role in the diurnal temperature range change. The spatial pattern of the differences in trends shows a marked heterogeneity.The land surface degradation such as deforestation and desertification due to human activities over northern China, and rapidly-developed urbanization over southern China, may have mostly contributed to the increases at stations north of about 38°N and in Southeast China, respectively. Furthermore, the vegetation cover increase due to irrigation and fertilization may have contributed to the decreasing trend of surface temperature over the lower Yellow River Basin. The study illustrates the possible impacts of land use changes on surface temperature over China.     

区域尺度土地利用/土地覆盖变化对气温日较差的影响

利用NCAR CAM4.0模式,针对潜在植被和当代植被两种典型土地覆盖类型,通过平衡态试验探讨土地利用/土地覆盖变化（land use/land cover change, LUCC）对气候的影响。结果表明,LUCC对气温日较差有明显影响。日较差的响应与LUCC变化的区域有紧密的联系。在中纬度,LUCC引起日较差减小,这主要由日最高气温的降低造成。在低纬度东亚地区,日较差的减小主要由日最高气温的降低造成;而在印度半岛,日较差的减小主要由日最低气温的升高决定。这种区域性的差异,主要是由于植被蒸腾和冠层蒸发的作用,LUCC能够显著调节气温日较差的变化。     

中国近代土地利用变化对区域气候影响的数值模拟

利用国家气候中心改进的高分辨率区域气候模式(RegCM-NCC)模拟研究了中国近代历史时期土地利用/覆盖变化对中国区域气候的影响,模拟结果显示,1700年以来,以森林砍伐、草地退化及相应耕地面积扩大为主的土地利用变化可能对中国区域降水、温度产生了显著影响。1700—1900年期间,由于土地利用的变化使华北、西南等地区降水呈减少趋势,其他区域变化不明显,但近50年来却使长江中下游地区、西北、东北部分地区降水有所增加。1700—1800年间的土地利用变化使得除东北及长江流域地区外的大部分地区温度呈下降趋势,1900年以后有所升高,特别是近50年来中国大部分区域平均气温升高,与这一时期由于大气中温室气体排放浓度增加造成的温度升高相一致。另外,土地利用变化不仅使大气温度、湿度发生变化,还可引起基本流场的变化,使东亚冬、夏季风气流有所增强,这主要是由于植被变化改变了地面温度,使海、陆温差进一步增大的结果。因此,土地利用变化对区域尺度气候变化的影响是不容忽视的。     

A SPATIAL-TEMPORAL DISTRIBUTION CHARACTERISTICS STUDY ON THE ATMOSPHERIC CARBON DIOXIDE OBSERVED BY GOSAT SATELLITE REMOTE SENSING

The variation of the atmospheric Carbon Dioxide (CO2) concentration plays an important role in global climate and agriculture. We analyzed the spatial-temporal characteristics of CO2 in the China region and around the globe with the CO2 column mixing ratios observed by the Japanese GOSAT satellite (Greenhouse Gases Observing Satellite). In order to make sure that the accuracy of the CO2 data retrieved by the satellite meets the needs of the climate characteristics analyses, we ran a validation on the CO2 column mixing ratios retrieved by the satellite against the ground-based TCCON (Total Carbon Column Observing Network) observation data. The result shows that the two sets of data have a correlation coefficient of higher than 0.7, and a bias of within 2.2 ppmv. Therefore, the GOSAT CO2 data can be used for the climate characteristics analysis of global CO2. Our analysis on the spatial-temporal characteristics of the CO2 column mixing ratios observed during the period of June 2009 through January 2014 proved that, with the impact of the natural emission of near ground CO2 and human activities, the global CO2 concentration has a significant latitudinal characteristics with its highest level averaging 390 ppmv in the 0-40oN latitudinal zone in the Northern Hemisphere, and 387 ppmv in the Southern Hemisphere. China has a relatively higher CO2 concentration with the highest level exceeding 398 ppmv, and the eastern area higher than the western area. The variation of global CO2 concentration shows a seasonal pattern, i.e. the CO2 concentration reaches its highest in spring in the Northern Hemisphere averaging more than 392 ppmv, second highest in winter, and lowest in summer averaging less than 387 ppmv. It fluctuates the most in the Northern Hemisphere with an average concentration of 392.5 ppmv in April, and 385.5 ppmv in July. While in the Southern Hemisphere, the seasonal fluctuation is smaller with the highest concentration occurring in July. Over the recent years, the global CO2 concentration has shown an elevating trend with an average annual increase rate of 1.58 ppmv per year. It is a challenge that the human kind has to face to slow down the increase of the CO2 concentration.     

Recent land cover changes on the Tibetan Plateau: a review

This paper reviews the land cover changes on the Tibetan Plateau during the last 50 years partly caused by natural climate change and, more importantly, influenced by human activities. Recent warming trends on the plateau directly influence the permafrost and snow melting and will impact on the local ecosystem greatly. Human activities increased rapidly on the plateau during the last half century and have significant impacts on land use. Significant land cover changes on the Tibetan Plateau include permafrost and grassland degradation, urbanization, deforestation and desertification. These changes not only impact on local climate and environment, but also have important hydrological implications for the rivers which originate from the plateau. The most noticeable disasters include the flooding at the upper reaches of Yangtze River and droughts along the middle and lower reaches of Yellow River. Future possible land cover changes under future global climate warming are important but hard to assess due to the deficits of global climate model in this topographically complex area. Integrated investigation of climate and ecosystems, including human-beings, are highly recommended for future studies.     

北方土地利用变化对中国夏季气候可能影响的敏感性试验

为考察中国北方地区当代土地利用变化对中国夏季气候的可能影响,以区域气候模式RegCM3为模拟工具,利用1992年和1999年的土地利用资料,进行了中国地区植被覆盖变化的敏感性试验。结果表明,中国北方地区土地利用/植被覆盖的改变,将通过影响大气环流和改变陆地—大气或植被—大气之间的能量平衡状态等,对降水和气温等产生较大影响。     

Impacts of Future NOx and CO Emissions on Regional Chemistry and Climate over Eastern China

A coupled chemical/dynamical model (SOCOL-SOlar Climate Ozone Links) is applied to study the impacts of future enhanced CO and NOx emissions over eastern China on regional chemistry and climate. The result shows that the increase of CO and NOx emissions has significant effects on regional chemistry, including NOx, CO, O₃, and OH concentrations. During winter, the CO concentration is uniformly increased in the northern hemisphere by about 10 ppbv. During summer, the increase of CO has a regional distribution. The change in O₃, concentrations near eastern China has both strong seasonal and spatial variations. During winter, the surface O₃, concentrations decrease by about 2 ppbv, while during summer they increase by about 2 ppbv in eastern China. The changes of CO, NOx, and O₃, induce important impacts on OH concentrations. The changes in chemistry, especially O₃, induce important effects on regional climate. The analysis suggests that during winter, the surface temperature decreases and air pressure increases in central-eastern China. The changes of temperature and pressure produce decreases in vertical velocity. We should mention that the model resolution is coarse, and the calculated concentrations are generally underestimated when they are compared to measured results. However, because this model is a coupled dynamical/chemical model, it can provide some useful insights regarding the climate impacts due to changes in air pollutant emissions.     

气候检测与归因的格兰杰检验法

 为揭示气候变化并探索其可能原因,引入了格兰杰因果检验法。在叙述其基本原理的基础上,对影响中国气温变化的若干因子进行了检验。论证了通过检验的因子与中国气温变化的可能物理联系,着重说明了二氧化碳增加对中国气温变化的影响,解释了我国增温滞后于全球气温变化的原因。由此证实格兰杰因果检验法是气候变化检测与归因的一种有用的新方法。通过计算和分析,证实了格兰杰检验法的可用性。     

Modeling the impact of urbanization on the local and regional climate in Yangtze River Delta, China

The Yangtze River Delta Economic Belt is one of the most active and developed areas in China and has experienced quick urbanization with fast economic development. The weather research and forecasting model (WRF), with a single-layer urban canopy parameterization scheme, is used to simulate the influence of urbanization on climate at local and regional scales in this area. The months January and July, over a 5-year period (2003–2007), were selected to represent the winter and summer climate. Two simulation scenarios were designed to investigate the impacts of urbanization: (1) no urban areas and (2) urban land cover determined by MODIS satellite observations in 2005. Simulated near-surface temperature, wind speed and specific humidity agree well with the corresponding measurements. By comparing the simulations of the two scenarios, differences in near-surface temperature, wind speed and precipitation were quantified. The conversion of rural land (mostly irrigation cropland) to urban land cover results in significant changes to near-surface temperature, humidity, wind speed and precipitation. The mean near-surface temperature in urbanized areas increases on average by 0.45?±?0.43°C in winter and 1.9?±?0.55°C in summer; the diurnal temperature range in urbanized areas decreases on average by 0.13?±?0.73°C in winter and 0.55?±?0.84°C in summer. Precipitation increases about 15% over urban or leeward areas in summer and changes slightly in winter. The urbanization impact in summer is stronger and covers a larger area than that in winter due to the regional east-Asian monsoon climate characterized by warm, wet summers and cool, dry winters.