Increase In Interannual Variability Research Articles

What Controls the Interdecadal Enhancement in Interannual Variability of Summertime Intraseasonal Precipitation Over South China?

AbstractThis study focuses on the interannual variability of summertime intraseasonal precipitation intensity (SIPI) over South China (SC) in the 30–90‐day range. The results demonstrate a significant increase in the interannual variability of SIPI over SC around the mid‐1990s. By comparing atmospheric and oceanic anomalies between two periods, P1 (1984–1993) and P2 (1994–2003), we identify that both the Silk Road pattern (SRP) and the western Pacific subtropical high (WPSH) play a role in influencing this interdecadal increase in SIPI interannual variability. These system anomalies are modulated by sea surface temperature anomalies (SSTA) in the North Atlantic (NA) and equatorial East Pacific (EP). During years with positive precipitation anomalies in P2, warming EP SSTA induces anomalous Walker cell and local Hadley cell, weakening the WPSH and enhancing convective activity, and increasing moisture transport over SC. The warming NA SSTA near 45°N triggers a more southerly propagation of SRP, thereby providing additional disturbance energy that enhances summer precipitation over SC. Conversely, during years with negative precipitation anomalies in P2, these processes occur in reverse. The enhanced interannual variability of local convective activity from P1 to P2 leads to a corresponding increase in the interannual variability of the WPSH, which, coupled with an amplified interannual variability of SRP, results in heightened interannual variability of SIPI. Additionally, the composite analysis of 30–90‐day ISO events further substantiates the underlying mechanisms driving the interdecadal amplification of SIPI interannual variability. Diagnostic results reveal that the 30–90‐day horizontal wind induces heightened convergence of background moisture over SC.

Management strategies can buffer the effect of mass mortality in early life stages of fish

Abstract Mass mortality (MM) events affecting early life stages of fish can have strong and long‐term consequences for population abundance and demography as well as the economic activity supported by exploited stocks. Adaptive fishery management may help mitigate economic impacts and ensure sustainable resource use following a MM event. Using a state‐space life cycle model, we simulated ‘what‐if’ scenarios of MM on Northeast Arctic cod (Gadus morhua) eggs and larvae. We compared the expected catches, total stock biomass (TSB), and interannual variability in catches over a period of 10 years after the simulated disturbance. We further evaluated a range of management mitigation strategies, namely reductions in fishing mortality of varying duration (1–10 years) and intensity (no fishing reduction to full ban). A large range of reductions in fishing led to an increase in expected catches over 10 years compared to no reductions, especially when applied immediately after the perturbation and when the cod population was characterized by a high mean age and high TSB. Severe fishing reductions can increase catches substantially but are associated with high interannual variability. Fishing reductions of moderate intensity applied between 1 and 4 years would allow to increase catches with only a slight increase in interannual variability. Our findings demonstrate the potential benefits of an adaptive approach to fisheries management and highlight that mitigation actions may ensure the sustainable exploitation of fish stocks in the wake of unexpected disturbances. Synthesis and application. Mass mortality events during early life stages of fish can potentially have substantial and long‐term effects on the population. Mitigation is more efficient when the affected population has a diverse age structure and when the mitigation strategy is applied immediately after the perturbation. Severe reduction in fishing mortality is an efficient measure to increase the expected average catch but is associated with high interannual variability. Fishing reduction of moderate intensity applied during 1–4 years after the event also increases the expected average catch with only slightly higher interannual variability in catches.

Climate service driven adaptation may alleviate the impacts of climate change in agriculture

Building a resilient and sustainable agricultural sector requires the development and implementation of tailored climate change adaptation strategies. By focusing on durum wheat (Triticum turgidum subsp. durum) in the Euro-Mediterranean region, we estimate the benefits of adapting through seasonal cultivar-selection supported by an idealised agro-climate service based on seasonal climate forecasts. The cost of inaction in terms of mean yield losses, in 2021–2040, ranges from −7.8% to −5.8% associated with a 7% to 12% increase in interannual variability. Supporting cultivar choices at local scale may alleviate these impacts and even turn them into gains, from 0.4% to 5.3%, as soon as the performance of the agro-climate service increases. However, adaptation advantages on mean yield may come with doubling the estimated increase in the interannual yield variability.

Spatially overlapping salmon species have varied population response to early life history mortality from increased peak flows

In the Pacific Northwest, USA, climate change is expected to result in a shift in average hydrologic conditions and increase variability. The relative vulnerabilities to peak flow changes among salmonid species within the same basin have not been widely evaluated. We assessed the impacts of predicted increases in peak flows on four salmonid populations in the Chehalis River basin. Coupling observations of peak flows, emissions projections, and multi-stage Beverton–Holt matrix-type life cycle models, we ran 100-year simulations of spawner abundance under baseline, mid-century, and late-century climate change scenarios. Coho (Oncorhynchus kisutch) and spring Chinook salmon (Oncorhynchus tshawytscha) shared the highest projected increase in interannual variability (SD = ±15%). Spring Chinook salmon had the greatest reduction in median spawner abundance (–13% to –15%), followed by coho and fall Chinook salmon (–7% to –9%), then steelhead (Oncorhynchus mykiss) (–4%). Our results show that interspecies and life history variability within a single basin is important to consider. Species with diverse age structures are partially buffered from population variability, which may increase population resilience to climate change.

Sea Ice Variability and Trends in the Western Indian Ocean Sector of Antarctica During the Past Two Centuries and Its Response to Climatic Modes

AbstractAntarctic sea ice is a critical component of the ocean‐climate system. Sea ice concentration (SIC) records of various oceanic sectors of Antarctica available since 1979 reveal dramatic changes in recent years; however, there is no consensus yet on drivers of sea ice variability, changes and their future projections. The lack of long‐term SIC records has impeded the quantification of sea ice variability, trends and various forcing factors and mechanisms. Here, we present a long‐term SIC record (1809−1993 CE) for the Western Indian Ocean Sector (WIOS) of Antarctica derived from a new ice core oxygen isotope (δ18O) record together with three available records from Dronning Maud Land (DML), East Antarctica. This long‐term SIC record at annual resolution reveals a significant decline during 1830–1884 CE with a rate of 0.58% ± 0.12% decade−1 followed by moderate increase during 1927–1993 CE with a rate of 0.24% ± 0.11% decade−1. Current satellite‐derived SIC records reveal an increase of 2.59 ± 0.86% decade−1 during 1994–2014 CE, which is unprecedented over the last two centuries as determined by the ice core‐derived SIC record. The satellite and ice core combined SIC record (1809−2019 CE) also reveals a significant increase in interannual variability at El Niño Southern Oscillation band and decadal variability at 16–32 years band in the last few decades. Our investigation suggests that wind‐driven sea‐ice dynamics associated with switching phases of Southern Annular Mode and remote teleconnections of Pacific oscillations largely control the interannual to decadal sea ice variability in this region.

Faster decline and higher variability in the sea ice thickness of the marginal Arctic seas when accounting for dynamic snow cover

Abstract. Mean sea ice thickness is a sensitive indicator of Arctic climate change and is in long-term decline despite significant interannual variability. Current thickness estimations from satellite radar altimeters employ a snow climatology for converting range measurements to sea ice thickness, but this introduces unrealistically low interannual variability and trends. When the sea ice thickness in the period 2002–2018 is calculated using new snow data with more realistic variability and trends, we find mean sea ice thickness in four of the seven marginal seas to be declining between 60 %–100 % faster than when calculated with the conventional climatology. When analysed as an aggregate area, the mean sea ice thickness in the marginal seas is in statistically significant decline for 6 of 7 winter months. This is observed despite a 76 % increase in interannual variability between the methods in the same time period. On a seasonal timescale we find that snow data exert an increasingly strong control on thickness variability over the growth season, contributing 46 % in October but 70 % by April. Higher variability and faster decline in the sea ice thickness of the marginal seas has wide implications for our understanding of the polar climate system and our predictions for its change.

A new perspective on the spatial, temporal, and vertical distribution of biomass burning: quantifying a significant increase in CO emissions

A variance-maximization approach based on 19 years of weekly measurements of pollution in the troposphere carbon monoxide (CO) measurements quantifies the spatial-temporal distribution of global biomass burning. Seven regions consistent with existing datasets are discovered and shown to burn for longer, over a more widespread area. Each region has a unique and recurring burning season, with three dominated by inter- and intra-annual variation. The CO is primarily lofted to the free troposphere from where it spreads downwind at 800 to 700 mb with three exceptions: The Maritime Continent and South America where there is spread at 300 mb consistent with deep- and pyro-convection; and Southern Africa which reaches to 600 mb. The total mass of CO lofted into the free troposphere ranges from 46% over Central Africa to 92% over Australia. The global, annual emissions made using two different techniques lead to an increase of biomass burning CO emissions of 47TgCO/year and 99TgCO/year respectively. The larger increase is mainly due to two factors: first, a large amount of the emissions is lofted rapidly upwards over the biomass burning region and subsequently transported downwind, therefore not appearing near the biomass source in space and time and second, an increase in inter-annual variability. Consistently, there is an increase in variability year-to-year and during peak events, from which 35% to more than 80% of the total emissions is lofted into the free troposphere. The results demonstrate a significantly higher CO emission from biomass burning, a larger impact on the global atmospheric composition, and likely impacts on atmospheric chemistry and climate change.

Anthropogenic climate change versus internal climate variability: impacts on snow cover in the Swiss Alps

Abstract. Snow is a sensitive component of the climate system. In many parts of the world, water stored as snow is a vital resource for agriculture, tourism and the energy sector. As uncertainties in climate change assessments are still relatively large, it is important to investigate the interdependencies between internal climate variability and anthropogenic climate change and their impacts on snow cover. We use regional climate model data from a new single-model large ensemble with 50 members (ClimEX LE) as a driver for the physically based snow model SNOWPACK at eight locations across the Swiss Alps. We estimate the contribution of internal climate variability to uncertainties in future snow trends by applying a Mann–Kendall test for consecutive future periods of different lengths (between 30 and 100 years) until the end of the 21st century. Under RCP8.5, we find probabilities between 10 % and 60 % that there will be no significant negative trend in future mean snow depths over a period of 50 years. While it is important to understand the contribution of internal climate variability to uncertainties in future snow trends, it is likely that the variability of snow depth itself changes with anthropogenic forcing. We find that relative to the mean, interannual variability of snow increases in the future. A decrease in future mean snow depths, superimposed by increases in interannual variability, will exacerbate the already existing uncertainties that snow-dependent economies will have to face in the future.

Global rangeland production systems and livelihoods at threat under climate change and variability

Rangelands are one of the Earth’s major ice-free land cover types. They provide food and support livelihoods for millions of people in addition to delivering important ecosystems services. However, rangelands are at threat from climate change, although the extent and magnitude of the potential impacts are poorly understood. Any declines in vegetation biomass and fluctuations in grazing availability would be of concern for food production and ecosystem integrity and functionality. In this study, we use a global rangeland model in combination with livestock and socio-economic datasets to identify where and to what extent rangeland systems may be at climatic risk. Overall, mean herbaceous biomass is projected to decrease across global rangelands between 2000 and 2050 under RCP 8.5 (−4.7%), while inter- (year-to-year) and intra- (month-to-month) annual variabilities are projected to increase (+21.3% and +8.2%, respectively). These averaged global estimates mask large spatial heterogeneities, with 74% of global rangeland area projected to experience a decline in mean biomass, 64% an increase in inter-annual variability and 54% an increase in intra-annual variability. Half of global rangeland areas are projected to experience simultaneously a decrease in mean biomass and an increase in inter-annual variability—vegetation trends both potentially harmful for livestock production. These regions include notably the Sahel, Australia, Mongolia, China, Uzbekistan and Turkmenistan and support 376 million people and 174 million ruminant Tropical Livestock Units. Additionally, the rangeland communities currently the most vulnerable (here, with the lowest livestock productivities and economic development levels and with the highest projected increases in human population densities) are projected to also experience the most damaging vegetation trends for livestock production. Although the capacity of rangeland systems to adapt is highly complex, analyses such as these generate some of the information required to inform options to facilitate pastoral system mitigation and adaptation strategies under climate change.

Multimodel ensemble projection of meteorological drought scenarios and connection with climate based on spectral analysis

AbstractPotential change in the hydrological cycles may lead to changes in extreme events such as drought due to the changes in intensity, frequency, and seasonality of precipitation and evaporative demand. In this study, projected drought scenarios and associated uncertainties in the late 21st century over the Continental United States are analysed based on seven regional climate models (RCMs) contributing to the Coordinated Regional Climate Downscaling Experiment. Meteorological drought scenarios are analysed based on standardized precipitation evapotranspiration index (SPEI). Here, we propose a new multimodel ensemble approach based on the similarity of spectral power of different frequency components of the SPEI time series. The approach combines output from different RCMs based on their ability to produce the observed power spectra as well as convergence towards the average spectra from all participating RCMs in the future climate. Furthermore, to understand the SPEI variability associated with climate teleconnection, continuous wavelet transform‐based spectral coherency between the SPEI and two climate indices: the El Niño–Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO) is analysed. Results show that among‐model uncertainty is the dominant source of uncertainties in the projected drought scenarios with contributions as large as 97% to the total uncertainty. Fifteen to 20% more frequent droughts are projected in future climate due to a decrease in mean SPEI as well as an increase in the variability of SPEI. Observed SPEI variability is strongly associated with ENSO variability while PDO modulates the strength of correlation between the SPEI and the ENSO. Spectral analysis of future SPEI shows that the increase in the SPEI variability is due to an increase in interannual variability as well as an enhanced ENSO teleconnection over the study area. The results show the increased role of climatic variability and hence the enhanced predictability of drought scenarios in the future climate.

Increasing interannual variability of global vegetation greenness

Despite the long-term greening trend in global vegetation identified in previous investigations, changes in the interannual variability (IAV) of vegetation greenness over time is still poorly understood. Using Global Inventory Modeling and Mapping Studies normalized difference vegetation index (NDVI) third generation data and corresponding meteorological data from 1982 to 2015, we studied the changes and drivers of the IAV of vegetation greenness as indicated by the coefficient of variation of vegetation greenness at a global scale. Dry and high-latitude areas exhibited high NDVI variability whereas humid areas exhibited relatively low NDVI variability. We detected an increase in the global IAV of vegetation greenness over time using a 15 year moving window. Spatially, we observed significant increases in the IAV of vegetation greenness in greater than 45% of vegetated areas globally and decreases in 21%. Our comparison of ecological models suggests good performance in terms of simulating spatial differences in vegetation variability, but relatively poor performance in terms of capturing changes in the IAV of vegetation greenness. Furthermore, the dominant climate variables controlling changes in the IAV of vegetation greenness were determined spatially using principal component regression and partial least squares regression. The two methods yielded similar patterns, revealing that temperature exerted the biggest influence on changes in the IAV of vegetation greenness, followed by solar radiation and precipitation. This study provides insights into global vegetation variability which should contribute to an understanding of vegetation dynamics in the context of climate change.

Future Climate and Land Use Change Impacts on River Flows in the Tapajós Basin in the Brazilian Amazon

AbstractLand conversion and changing climate are expected to significantly alter tropical forest hydrology. We used a land surface model integrated with a river routing scheme to analyze the hydrological alterations expected in the Tapajós River basin, a large portion of the Brazilian Amazon, caused by two environmental drivers: climate and land use. The model was forced with two future climate scenarios (years 2026–2045) from the Earth System Model HadGem2‐ES with moderate (+4.5 W/m2 radiative forcing value in the year 2100 with respect to preindustrial levels) and severe (+8.5 W/m2) representative atmospheric carbon dioxide pathways (Representative Concentration Pathways). We tested the sensitivity of our results to the uncertainty in future climate projections by running simulations with IPSL‐CM5 (wettest scenarios) and GISS‐E2 (driest scenarios). Human land use effects on vegetation were evaluated using a limited and an extreme deforestation scenario. Our analysis indicates that climate change is predicted to reduce river flows across seasons (up to 20%) and bring a considerable shift in flow seasonality toward a later onset (nearly 1.5 months) and increase in interannual variability. While land use change partially counteracts the climate‐driven diminishing trend in river flows, it is expected to contribute to a further increase in interannual and intraannual variability. From a water management perspective, the overall reduction of river flows and their increased variability, combined with the shift and the shortening of the wet season, could potentially affect the productivity of the large hydropower systems planned for the region and the growing demand for agricultural and transport expansion.

Atlantic Zonal Mode: An Emerging Source of Indian Summer Monsoon Variability in a Warming World

AbstractAtlantic Zonal Mode (AZM) and Indian summer monsoon rainfall (ISMR) are known to have an inverse relationship, which means that the cold (warm) phases of AZM result in strong (weak) ISMR. Here, we report that the inverse relationship between AZM and ISMR has significantly strengthened in recent decades. The cause of this strengthening relationship has been investigated. We find a robust increase in interannual variability of sea surface temperature over the eastern tropical Atlantic Ocean in recent decades, which implies an increase in the number of strong AZM events toward the end of the twentieth century. The increase in strong AZM events alters the large‐scale monsoon circulation over the Indian subcontinent by enhancing the Kelvin wave response into the Indian Ocean, leading to an enhanced AZM‐ISMR teleconnection. This demands a better representation of the AZM‐ISMR teleconnection in climate models for improving seasonal monsoon prediction in a warming world.

Subfossil trees suggest enhanced Mediterranean hydroclimate variability at the onset of the Younger Dryas

Nearly 13,000 years ago, the warming trend into the Holocene was sharply interrupted by a reversal to near glacial conditions. Climatic causes and ecological consequences of the Younger Dryas (YD) have been extensively studied, however proxy archives from the Mediterranean basin capturing this period are scarce and do not provide annual resolution. Here, we report a hydroclimatic reconstruction from stable isotopes (δ18O, δ13C) in subfossil pines from southern France. Growing before and during the transition period into the YD (12 900–12 600 cal BP), the trees provide an annually resolved, continuous sequence of atmospheric change. Isotopic signature of tree sourcewater (δ18Osw) and estimates of relative air humidity were reconstructed as a proxy for variations in air mass origin and precipitation regime. We find a distinct increase in inter-annual variability of sourcewater isotopes (δ18Osw), with three major downturn phases of increasing magnitude beginning at 12 740 cal BP. The observed variation most likely results from an amplified intensity of North Atlantic (low δ18Osw) versus Mediterranean (high δ18Osw) precipitation. This marked pattern of climate variability is not seen in records from higher latitudes and is likely a consequence of atmospheric circulation oscillations at the margin of the southward moving polar front.

Increased Winter‐Mean Wave Height, Variability, and Periodicity in the Northeast Atlantic Over 1949–2017

AbstractA 69‐year (1948–2017) numerical weather and wave hindcast is used to investigate the interannual variability and trend of winter wave height along the west coast of Europe. Results show that the winter‐mean wave height, variability, and periodicity all increased significantly in the northeast Atlantic over the last seven decades which primarily correlate with changes in the climate indices North Atlantic Oscillation (NAO) and West Europe Pressure Anomaly (WEPA) affecting atmospheric circulation in the North Atlantic. NAO and WEPA primarily explain the increase in winter‐mean wave height and periodicity, respectively, while both WEPA and NAO explain the increase in interannual variability. This increase in trend, variability, and periodicity resulted in more frequent high‐energy winters with high NAO and/or WEPA over the last decades. The ability of climate models to predict the winter NAO and WEPA indices a few months ahead will be crucial to anticipate coastal hazards in this region.

Response of diatom and dinoflagellate lifeforms to reduced phosphorus loading: A case study in the Thau lagoon, France

The basin of Thau in southern France is a shallow, weakly flushed lagoon which is an important location for oyster cultivation. Phytoplankton analyses were carried out in 1975–1976 and then (almost) continuously since 1987. We report an investigation of ‘the balance of organisms’ in phytoplankton in relation to reductions in phosphorus loading, using two new tools based on phytoplankton lifeforms: the Plankton Index for Phytoplankton (PIp); Euclidean distance in state-space. Our results show the utility of the tools for analysing changes in the ‘balance of organisms’ at the level of functional groups (in our study diatoms and dinoflagellates), but also illustrate the difficulties in demonstrating the reversal of human impacts resulting from eutrophication.The comparison between 1987–89 and 1976 showed the expected ‘de-eutrophication’ due to the reduction in dissolved inorganic phosphate (DIP), with a decrease in dinoflagellate abundance. Since 1989, year-to-year variation in annual mean concentrations of DIP may have contributed to inter-annual variability in the balance of the two lifeforms, but the data suggest that the system has remained in a dynamically stable regime because: (1) there was no long-term trend in Euclidean distance from the reference; and (2) there was no increase in inter-annual variability about the time-series mean Euclidean distance suggesting there has been no decrease in resilience which might signal a regime change.Integrated management of human activities will be required to manage (and reduce) total P in the system. Monitoring phytoplankton and nutrients concentrations to determine how primary production and the balance of species respond to further changes in the nutrient status of the lagoon should be an integral part of any management programme.

Background albedo dynamics improve simulated precipitation variability in the Sahel region

Abstract. Using the general circulation model ECHAM5–JSBACH forced by observed sea surface temperatures (SSTs) for the 20th century, we investigate the role of vegetation and land surface albedo dynamics in shaping rainfall variability in the Sahel. We use two different land surface albedo schemes, one in which the albedo of the canopy is varying and one in which the albedo changes of the surface below the canopy are also taken into account. The SST forcing provides the background for simulating the observed decadal signal in Sahelian rainfall, though the response to SST forcing only is not strong enough to fully capture the observed signal. The introduction of dynamic vegetation leads to an increase in interannual variability of the rainfall, and gives rise to an increased number of high-amplitude rainfall anomaly events. The dynamic background albedo leads to an increased persistence of the rainfall anomalies. The increase in persistence means that the difference between the dry and the wet decades is increased compared to the other simulations, and thus more closely matching the observed absolute change between these two periods. These results highlight the need for a consistent representation of land surface albedo dynamics for capturing the full extent of rainfall anomalies in the Sahel.

Consistent increase in Indian monsoon rainfall and its variability across CMIP-5 models

Abstract. The possibility of an impact of global warming on the Indian monsoon is of critical importance for the large population of this region. Future projections within the Coupled Model Intercomparison Project Phase 3 (CMIP-3) showed a wide range of trends with varying magnitude and sign across models. Here the Indian summer monsoon rainfall is evaluated in 20 CMIP-5 models for the period 1850 to 2100. In the new generation of climate models, a consistent increase in seasonal mean rainfall during the summer monsoon periods arises. All models simulate stronger seasonal mean rainfall in the future compared to the historic period under the strongest warming scenario RCP-8.5. Increase in seasonal mean rainfall is the largest for the RCP-8.5 scenario compared to other RCPs. Most of the models show a northward shift in monsoon circulation by the end of the 21st century compared to the historic period under the RCP-8.5 scenario. The interannual variability of the Indian monsoon rainfall also shows a consistent positive trend under unabated global warming. Since both the long-term increase in monsoon rainfall as well as the increase in interannual variability in the future is robust across a wide range of models, some confidence can be attributed to these projected trends.

Atmospheric Carbon Dioxide Variability in the Community Earth System Model: Evaluation and Transient Dynamics during the Twentieth and Twenty-First Centuries

Abstract Changes in atmospheric CO2 variability during the twenty-first century may provide insight about ecosystem responses to climate change and have implications for the design of carbon monitoring programs. This paper describes changes in the three-dimensional structure of atmospheric CO2 for several representative concentration pathways (RCPs 4.5 and 8.5) using the Community Earth System Model–Biogeochemistry (CESM1-BGC). CO2 simulated for the historical period was first compared to surface, aircraft, and column observations. In a second step, the evolution of spatial and temporal gradients during the twenty-first century was examined. The mean annual cycle in atmospheric CO2 was underestimated for the historical period throughout the Northern Hemisphere, suggesting that the growing season net flux in the Community Land Model (the land component of CESM) was too weak. Consistent with weak summer drawdown in Northern Hemisphere high latitudes, simulated CO2 showed correspondingly weak north–south and vertical gradients during the summer. In the simulations of the twenty-first century, CESM predicted increases in the mean annual cycle of atmospheric CO2 and larger horizontal gradients. Not only did the mean north–south gradient increase due to fossil fuel emissions, but east–west contrasts in CO2 also strengthened because of changing patterns in fossil fuel emissions and terrestrial carbon exchange. In the RCP8.5 simulation, where CO2 increased to 1150 ppm by 2100, the CESM predicted increases in interannual variability in the Northern Hemisphere midlatitudes of up to 60% relative to present variability for time series filtered with a 2–10-yr bandpass. Such an increase in variability may impact detection of changing surface fluxes from atmospheric observations.

A Simulation Study on Climatic Effects of Land Cover Change in China

The regional climate model RegCM4 was used to investigate the regional climate effects of land cover change over China. Two 24-year simulations (1978–2001), one with the land cover derived from the MODIS data and the other with the CLCV (Chinese land cover derived from vegetation map) data, were conducted for a region encompassing China. The differences between the MODIS and CLCV data reflect characteristics of desertification and degradation of vegetation in China. Results indicate that the land cover change has important impacts on local climate through mechanisms related to changes in surface energy, water budgets and macro-scale circulation. In summer, the land cover change leads to a decrease in surface air temperature over southern China, a reduction in precipitation and an increase in surface air temperature in the transitional climate zone and the northern Tibetan Plateau, and an increase in inter-annual variability of surface air temperature in the marginal monsoon zone and northwestern China. Strengthened southwesterly winds increase precipitation to some extent in central and eastern Inner Mongolia by enhancing water vapor transport. In winter, enhanced northerly winds, bringing more dry and cold air, lead to a reduction in precipitation and temperature over areas south of the Yellow River. CitationYu, Y., and Z.-H. Xie, 2013: A simulation study on climatic effects of land cover change in China. Adv. Clim. Change Res.,4(2), doi: 10.3724/SP.J.1248.2013.117.