Changes In Spatial Patterns Research Articles

Spatial pattern and cause of centennial-scale hydroclimatic variability over eastern China during the last millennium

Instrumental and historic records have shown that the hydroclimatic variability on interannual- to decadal-timescales over eastern China is spatially different, with a meridional dipole or even tripole pattern. Yet, how this spatial pattern of hydroclimate change on centennial timescales looks like is still unclear due to the lack of well-reconstructed climate records from South China. Here, we present a precisely-dated, high-resolution δ18O record of stalagmite (JL2) from Jiuluo Cave, Guilin, South China, to elucidate the hydroclimatic variability in South China over the last millennium and thus explore the spatial pattern and cause of centennial-scale hydroclimatic variability across eastern China. Based on the previous results of modern cave monitoring carried out in the Guilin region, the δ18O of JL2 is carefully interpreted as a robust proxy for summer monsoonal rainfall change. It clearly shows that a decrease in monsoonal rainfall over South China occurred during the periods of 941–1250 CE (i.e. the Medieval Warm Period (MWP)) and 1550–1850 CE (late Little Ice Age (LIA)), while intensification of monsoonal rainfall occurred during 1250–1550 CE (early LIA) and since 1850 CE (the Current Warm Period). Comparison of the JL2 record with other well-reconstructed proxy records from different zones along the trajectory of the East Asia summer monsoon (EASM) allows us to depict the spatial variation in centennial-scale monsoonal rainfall over eastern China. We confirmed that a “wet northern and dry southern” pattern existed for the rainfall regime of eastern China during the MWP, and a “dry northern and wet southern” pattern during the early LIA. Furthermore, there was a tripole pattern showing dry conditions in both North and South China but wet condition in the Jianghuai area, central China during the late LIA. These spatial patterns of centennial-scale monsoonal rainfall variability were principally linked to changes in summer monsoon intensity and the long-live state of El Niño–Southern Oscillation (ENSO). We also found that solar activity could influence the monsoonal rainfall to some degrees, and reduced monsoonal rainfall often occurred during intervals of solar minimum. Nevertheless, the monsoonal rainfall change during the 14th century was ascribed to great shift in oceanic and atmospheric circulation rather than to variations in solar activity.

The Glacier‐Climate Interaction Over the Tibetan Plateau and Its Surroundings During the Last Glacial Maximum

AbstractGlacier growth affects the local climate, and in turn, can either promote or prohibit its own growth. Such feedback has not been considered in modeling the glaciers of the Tibetan Plateau and its surroundings (TPS) during the Last Glacial Maximum (LGM; ∼28–23 ka). We find that the volume/area of the glaciers simulated by a coupled glacier‐climate model is 20%/10% less than that by a standalone glacier model forced with fixed climate fields; glaciers advance toward their western rims and yet decrease in the interior of TPS. Such changes in spatial patterns improve model‐data comparison. Moreover, the expansion of glaciers warms the winter surface temperature of the eastern TPS and decreases precipitation almost everywhere. These effects are primarily due to the added surface elevation, which blocks the water vapor brought by westerlies and south‐westerlies, reducing precipitation and increasing surface temperatures to the east and northeast of the newly grown glaciers.

Rethinking the spatial transformation of postsocialist cities: Shrinking, sprawling or densifying

This research examines the spatial transformations of postsocialist cities in the context of the polarized national urban system. Focusing on two different periods (1990–2000 and 2000–2014/2015), we study the patterns of spatial changes in 15 selected cities in Serbia in terms of urban sprawl, densification, and urban shrinkage. Using an open-source database, we analyze the relationship between the built-up area, population, and urban density to identify the types and trajectories of spatial transformations. Our results show that urban sprawl characterizes cities with growing/stable populations and those with declining populations but with different scales and dynamics over time. Despite the distinct trend of population decline, no cities were marked by compact shrinkage. Nevertheless, we identify a significant decrease in the annual change rates of the built-up area throughout the latter period in all cities, indicating a possible future decline in inefficient outward expansion. We also observed that this period gave rise to the imbalance between the pace of spatial growth of large cities and medium-sized cities. The obtained spatial patterns fit into the framework of Serbia's asymmetric urban system, with sprawl shrinkage as dominant phenomenon in urban centres ranking lower in the urban system hierarchy and less frequent sprawl growth in major urban centres. Our research results could ignite a process of redefining urban and land policies towards more efficient land use.

Invariant neural dynamics drive commands to control different movements.

It has been proposed that the nervous system has the capacity to generate a wide variety of movements because it reuses some invariant code. Previous work has identified that dynamics of neural populationactivity are similar during different movements, where dynamics refer to how the instantaneous spatialpattern of population activity changes in time. Here, we test whether invariant dynamics of neural populations are actually used to issue the commands that direct movement. Using a brain-machine interface (BMI) that transforms rhesus macaques' motor-cortex activity into commands for a neuroprosthetic cursor, we discovered that the same command is issued with different neural-activity patterns in different movements. However, these different patterns were predictable, as we found that the transitionsbetween activity patterns are governed by the same dynamics across movements. These invariant dynamics are low dimensional, and critically, they align with the BMI, so that they predict the specific component of neural activity that actually issues the next command. We introduce a model of optimal feedback control (OFC) that shows that invariant dynamics can help transform movement feedback into commands, reducing the input that the neural population needs to control movement. Altogether our results demonstrate that invariant dynamics drive commands to control a variety of movements and show how feedback can be integrated with invariant dynamics to issue generalizable commands.

Spatial patterns of climate change and associated climate hazards in Northwest China

Northwest China (NWC) is experiencing noticeable climate change accompanied with increasing impacts of climate hazards induced by changes in climate extremes. Towards developing climate adaptation strategies to mitigate the negative climatic impacts on both the ecosystem and socioeconomic system of the region, this study investigates systematically the spatial patterns of climate change and the associated climate hazards across NWC based on high resolution reanalysis climate dataset for the period 1979 to 2018. We find that NWC overall is under a warming and wetting transition in climate with change rate of temperature and precipitation around 0.49 °C/10a and 22.8 mm/10a respectively. Characteristics of climate change over the NWC however vary considerably in space. According to significance of long-term trends in both temperature and aridity index for each 0.1° × 0.1° grids, five types of climate change are identified across NWC, including warm-wetting, warm-drying, warm without wetting, wetting without warming and unchanging. The warm-wetting zone accounts for the largest proportion of the region (41%) and mainly locates in the arid or semi-arid northwestern NWC. Our findings show most region of NWC is under impacts of intensifying heatwave and rainstorm due to significant increases in high temperature extremes and precipitation extremes. The warming but without wetting zone is found under a more severe impact of heatwave, particularly for areas near northern Mount. Qinling and northern Loess Plateau. Areas with stronger wetting trend is suffering more from rainstorm.

A climate stress testing method for changes in spatially variable rainfall

With emerging evidence that anthropogenic climate change is affecting the spatial pattern of rainfall, it is important to understand how such changes affect a range of climate-sensitive systems. A method for generating multi-site rainfall sequences is presented that enables the exploration of changes in spatial rainfall patterns separately from various other potential changes (e.g. to the averages, extremes, seasonality), thereby enabling the separation of key drivers of change as part of climate stress tests. The proposed method is based on the ‘inverse approach’ to stochastic weather generation, and is evaluated through a case study with rainfall at 12 sites in the Barossa Valley, South Australia, using a multi-site latent variable stochastic rainfall model. The new method accurately captures (1) observed marginal attributes at each site (i.e. annual totals, seasonality, extreme rainfall, number of dry days, and intermittency), (2) spatial correlation between sites, and (3) observed attributes for areal average rainfall. We then apply the new method to stress test the response of streamflow in the region to changes in spatial rainfall patterns, quantifying how reductions in spatial correlation (while holding all other attributes constant) will lead to reduced mean annual flow and extreme flows, and increased number of low-flow days. The results show that not only can a broad range of rainfall properties (including both marginal and spatial attributes) be simulated using the inverse approach, but also that changes to the spatial properties of rainfall can have large implications on water resources systems, with the potential to amplify or dampen other changes to rainfall attributes.

N equals two (times five). Exploring the effects of horse rewilding on five congeneric adult butterflies

Rewilding incomplete ecosystems by using ungulate megaherbivores represents a significant potential for sustainable management of habitats of declining species. Two xeric grasslands patches in the Podyjí National Park, Czech Republic, were rewilded by a feral horse breed, the Exmoor pony, in 2018. Before this in 2017, demography, mobility, and adult habitat use of five congeneric Melitaea butterflies co-occurring at the grasslands were investigated (Vodickova et al., J. Nature Conserv. 2019). In 2021, four seasons after the rewilding, we replicated the survey to assess the effects of the horse on the butterflies. Here, we compare the results of the two surveys and investigate changes in spatial patterns of adult distribution using Ripley’s K-functions.Total numbers of captures, and estimated population sizes, were consistently lower in 2021, with the largest drop for spring-flying M. cinxia. We cannot discern whether this was due to the cold 2021 spring, or due to reduction of grasses by the horse, possibly contributing to desiccation of M. cinxia host plants. Demographic parameters such as residency/longevity and capture probability changed only little. Mobility ranking among species remained identical, but within species, some mobility characteristics changed among years. Among early summer species, M. britomartis, second most abundant in 2017, switched to the first position with M. aurelia, and these two species displayed the most notable shift in adult habitat use between the two seasons. Short thorny shrubs avoided by the horse protect M. britomartis host plants; this threatened butterfly thus did not suffer from horse presence. M. athalia, a species of woodland edges, profited from decay of conifers caused by a series of dry years; and M. didyma, forming multiple generations, from increase of its host plant. Contrary to expectations, spatial distribution of most butterflies became more aggregated within rewilded pastures, probably due to regularities in home ranges use by the horses, which restructured the vegetation in a zonal, rather than patchy, way. A considerably larger areas should be rewilded by the herbivores to fully achieve the desired beneficial effects.

Soil-Water Comprehensive Treatment Theory of Urban Fringe

Urban fringe is an active expanding belt, the environment of the urban fringe is complex and frangible. Previous studies have focused on the landscape spatial pattern changes, the spatial-temporal variability of soil pollutants and the land management and policy issues, etc., but it is lack of the theory and practice study of land & water comprehensive remediation in urban fringe areas. This article is taking the Shichuan River as an example. And establish a new concept of comprehensive remediation with soil purification as the key, and with water treatment as the link, meanwhile it will keep clear water with pure land. Form land organic rearrangement theory for different types of land utilization.

Exploring Relationships between Spatial Pattern Change in Steel Plants and Land Cover Change in Tangshan City

It is of great significance for the sustainable development of steel cities to explore the relationship between the spatial pattern change in steel plants and land cover change during the transformation of steel cities. To address the issue of unsatisfactory results for segmenting steel plants based on high-resolution remote sensing images, due to insufficient sample datasets and task complexity, we proposed a steel plant segmentation strategy that combines high-resolution remote sensing images, POI data, and OSM data. Additionally, we discussed the effect of POI data and OSM data on steel plant segmentation, analyzing the spatial pattern change in steel plants in Tangshan City during 2017–2022 and its relationship with land cover change. The results demonstrate that: (1) The proposed strategy can significantly improve the accuracy of steel plant segmentation. The introduction of POI data can significantly improve the precision of steel plant segmentation, however, it will to some extent reduce the recall of steel plant segmentation, and this phenomenon weakens as the distance threshold increases. The introduction of OSM data can effectively improve the effectiveness of steel plant segmentation, however, it has significant limitations. (2) During 2017–2022, the spatial distribution center of steel plants in Tangshan City moved obviously to the southeast, and the positive change in steel plants was mainly concentrated in the coastal regions of southern Tangshan City, while the negative change in steel plants was mainly concentrated in central Tangshan City. (3) There is a relatively strong spatial correlation between the positive change in steel plants and the transition from vegetation to built area, as well as the transition from cropland to built area.

The knee connectome: A novel tool for studying spatiotemporal change in cartilage thickness.

Cartilage thickness change is a well-documented biomarker of osteoarthritis pathogenesis. However, there is still much to learn about the spatial and temporal patterns of cartilage thickness change in health and disease. In this study, we develop a novel analysis method for elucidating such patterns using a functional connectivity approach. Descriptive statistics are reported for 1186 knees that did not develop osteoarthritis during the 8 years of observation, which we present as a model of cartilage thickness change related to healthy aging. Within the control population, patterns vary greatly between male and female subjects, while body mass index (BMI) has a more moderate impact. Finally, several differences are shown between knees that did and did not develop osteoarthritis. Some but not all significance appears to be accounted for by differences in sex, BMI, and knee alignment. With this work, we present the connectome as a novel tool for studying spatiotemporal dynamics of tissue change.

Spatial pattern and hot spots of vegetation change in Uttar Pradesh during 2001 to 2021

Spatial pattern and hot spots of vegetation change in Uttar Pradesh during 2001 to 2021

Analysis of the spatial and temporal patterns in land use land cover in Belize city from 1991 to 2021

Urban theorists and planning researchers ignore small cities with ports. Rectifying this neglect, we focus on Belize City. We assess the spatial and temporal patterns of land use and cover changes, utilizing remote sensing analysis and multiyear Landsat satellite images. Focusing on the contemporary period (1991-present), we analyze the impacts of the rapid development of the Port of Belize and its consequent effect on the expansion of the urban built environment of Belize City. In addition to analyzing land use land cover changes, we calculated key indices such as NDVI, NDBI, and LST in Belize City. Importantly, local-level clustering of differences in NDBI and NDVI values is analyzed using LISA analysis. Our results show that the urbanized area has increased in the past 30 years, with corresponding reductions in the area under forest and water. Our analyses reveal three distinctive periods of urban changes: 1991–2001, 2001–2011, and 2011–2021. From 1991 to 2001 most of the urban expansion occurred along the Belize River. Significant urban expansion from 2001 to 2011 is related to a private company managing and developing the port, accelerating construction around the port. Finally, from 2011 to 2021, the process of urban sprawl slowed, with only sporadic new construction in the suburbs, due to the master planning at the port. Nevertheless, masterplan implementation delays, numerous appeals, and weak enforcement of regulations have not curbed unplanned urbanization.

Spatiotemporal changes in Universal Thermal Climate Index over South Asia

The rising global temperatures have posed challenges to human survival and well-being in various regions worldwide. However, little is known about human thermal stress exposure changes among populations living in extreme poverty and struggling to meet their basic needs. This study aimed to investigate the spatial patterns of changes in human thermal stress levels in South Asia using the Universal Thermal Climate Index (UTCI). ERA5 HEAT data from 1979 to 2021 were analyzed using Sen's slope method and the Modified Mann-Kendall test to determine the changes in annual and seasonal thermal stress levels. The findings revealed that Bangladesh, located in the eastern part of South Asia, experiences the highest mean UTCI range (26 to 32 °C), while Afghanistan has the lowest among the South Asian nations. In contrast, the western part of South Asia, particularly the region bordering India and Pakistan, exhibits the highest daily maximum UTCI range (38 to 46 °C). Trend analysis indicated an increase in mean and maximum UTCI levels across the western part of South Asia, including Pakistan, Afghanistan, and northwest India, at 0.25 to 0.75 °C/decade. This increase was more widespread during the June–September (JAS) period than in other seasons. In many regions of the study area, moderate and high thermal stress days increased by 4 to 8 days per decade. As a result, 27.6% of the area shifted from an average comfortable temperature to moderate thermal stress and 18.7% from moderate to strong thermal stress during JAS.

Climate change projections of soil erosion in South America in the XXI century

Global climate projections indicate that continental South America (SA) can experience significant changes in soil erosion caused by water in the coming years due to changes in the precipitation spatial and temporal patterns, threatening food security and biodiversity and impairing agroecosystems to provide services. This study aims to quantify future impacts on soil erosion in the SA provoked by changes in precipitation from climate change scenarios using the Revised Universal Soil Loss Equation (RUSLE). A 20 km spatial resolution of annual precipitation projected from the ensemble of four global climate models (BESM, CanESM2, HadGEM2-ES, and MIROC5 models) was used to assess impacts between 2010 and 2099, sliced every 30 years. The Eta/CPTEC model dynamically regionalized the datasets, and the RCPs 4.5 and 8.5 scenarios were selected to quantify rainfall erosivity and soil erosion rates. The projected average soil erosion over the continent was 37% above the present estimation (3.8 Mg ha−1 year−1), reaching 5.2 Mg ha−1 year−1 at the end of the 21st century. The projections indicate an increase in soil losses across the Andes Cordillera with less severe impacts on lowlands commonly used for crops and livestock. Contrastingly, soil erosion rates tended to decrease by the end of the century in northern SA due to the reduced precipitation projected by most climate models. Overall, the most significant impacts on soil erosion caused by climate change were found for the last time slice (2071–2099) in the RCP 8.5 scenario, with mixed results, i.e., an increase in some regions and a decrease in others.

Quantifying the Spatio-Temporal Pattern Differences in Climate Change before and after the Turning Year in Southwest China over the Past 120 Years

In conjunction with Earth’s ongoing global warming, the Southwest China (SWC) region has become a fascinating case study on the control of local climate change. Moreover, an entire period of climate change may partially mask the patterns in some stages. Therefore, in this research, we investigated the spatial patterns of the significant turning years of climatic factor change, and determined the heterogeneity of the spatial patterns of climate change before and after the significant turning years. We used the long time-series of the CRU datasets (CRU_TS4.02) from 1901 to 2017 with a piecewise linear regression model to explore the significant turning-year distribution characteristics of inter-annual and inter-seasonal climate factor changes, and further describe and quantize the differences in the spatio-temporal patterns of climate factors before and after the significant turning years on the grid scale in SWC. Overall, the trends in temperature and precipitation factors in SWC were segmented over the last 120 years, with significant turning years with different regional and stepwise characteristics. In terms of timing, temperature and precipitation factors changed significantly in 1954 and 1928, respectively, and overall temporal variability (0.04 °C/(10 a) (p < 0.05), −0.48 mm/(10 a)) masked the magnitude or direction of variability (0.13 °C/(10 a) and 0.16 °C/(10 a) both at the level of p < 0.05 before the turning year, 19.56 mm/(10 a) (p < 0.05) and 1.19 mm/(10 a) after the turning year) around the watershed years. Spatially, the significant turning years were concentrated in the periods 1940–1993 (temperature) and 1910–2008 (precipitation), and the distribution pattern of the turning years was patchy and concentrated. The turning years of temperature factors were gradually delayed from east to west, and the variability of climate factors before and after the turning years exhibited significant shifts in location (e.g., temperature decreased from southeast to northwest before the turning year and increased after the turning year). After the turning year, the warming variability of the temperature factor increased, while the increasing variability of the precipitation factor decreased. Further integrated analysis revealed that the increase in variability of the climate factor after the turning year was mainly due to the increase in winter and autumn variability (0.05 °C/(10 a), 7.30 mm/(10 a) in autumn; and 0.12 °C/(10 a), 1.97 mm/(10 a) in winter). To the extent that this study provides a necessary academic foundation for efficiently unveiling the spatio-temporal variability properties of climate factors against the background of modern global climate change, more attention should be paid to the location and phase of the study.

Spatial and temporal variability of 21st century sea level changes

SUMMARY Mass loss from polar ice sheets is becoming the dominant contributor to current sea level changes, as well as one of the largest sources of uncertainty in sea level projections. The spatial pattern of sea level change is sensitive to the geometry of ice sheet mass changes, and local sea level changes can deviate from the global mean sea level change due to gravitational, Earth rotational and deformational (GRD) effects. The pattern of GRD sea level change associated with the melting of an ice sheet is often considered to remain relatively constant in time outside the vicinity of the ice sheet. For example, in the sea level projections from the most recent IPCC sixth assessment report (AR6), the geometry of ice sheet mass loss was treated as constant during the 21st century. However, ice sheet simulations predict that the geometry of ice mass changes across a given ice sheet and the relative mass loss from each ice sheet will vary during the coming century, producing patters of global sea level changes that are spatiotemporally variable. We adopt a sea level model that includes GRD effects and shoreline migration to calculate time-varying sea level patterns associated with projections of the Greenland and Antarctic Ice Sheets during the coming century. We find that in some cases, sea level changes can be substantially amplified above the global mean early in the century, with this amplification diminishing by 2100. We explain these differences by calculating the contributions of Earth rotation as well as gravitational and deformational effects to the projected sea level changes separately. We find in one case, for example, that ice gain on the Antarctic Peninsula can cause an amplification of up to 2.9 times the global mean sea level equivalent along South American coastlines due to positive interference of GRD effects. To explore the uncertainty introduced by differences in predicted ice mass geometry, we predict the sea level changes following end-member mass loss scenarios for various regions of the Antarctic Ice Sheet from the ISMIP6 model ensemblely, and find that sea level amplification above the global mean sea level equivalent differ by up to 1.9 times between different ice mass projections along global coastlines outside of Greenland and Antarctica. This work suggests that assessments of future sea level hazard should consider not only the integrated mass changes of ice sheets, but also temporal variations in the geometry of the ice mass changes across the ice sheets. As well, this study highlights the importance of constraining the relative timing of ice mass changes between the Greenland and Antarctic Ice Sheets.

Spatial and temporal changes and development predictions of urban green spaces in Jinan City, Shandong, China

The study of long-term changes to urban green space reveals the reasons for changes in the spatial pattern of urban green space and predicts the future development trends, which is of great importance for urban green space protection and integrated urban development. This study used Markov Chain and PLUS models to explore the spatial and temporal patterns of changes to green space in urban and rural areas in Jinan City during recent rapid urbanization and the driving forces behind them. The results show that from 2000 to 2020, the decrease in urban green space in Jinan City slowed down gradually, and that elevation and population density were the primary factors influencing changes in urban green space. In the simulation projections, the ecologically protected development scenario had a relatively low rate of site change and was more protective of arable land and green space. Ecological conservation development was predicted to result in a decrease in unused urban land and to reflect the advantages of intensive land use. The findings will provide decision-makers with ideas related to the sustainable development of urban green space.

A practice study of land and water comprehensive remediation in urban-rural fringe-with Sichuan River Shaanxi Province, Northwest China, as an example.

Urban-rural fringe area (URFa) is an active and expansive region, and its environment is complex and frangible. Previous studies have focused on the landscape spatial pattern changes, the spatial-temporal variability of soil pollutants and the land management and policy issues, etc., but it is lack of the practice study of land and water comprehensive remediation in URFa. This article is taking the Sichuan River, a typical URFa, as an example. Based on field investigation and lab tests, the main characteristic form of the URFa and land and water comprehensive remediation measures are summarized in this paper. The results show that it is feasible to turn wasteland, low-efficiency land, and old deserted beach into farm land, residential land, and ecological land by comprehensive land improvement. For the farm land reconstruction, the texture is an important indicator. The content of soil organic matter (SOM), carbon, nitrogen, and phosphorus has increased after remediation. For the SOM, 58.3% are more than 10.0g·kg-1, and 79.2% are more than 8.0g·kg-1. For the frequent dry-off and polluted low flow river channels in URFa, the river bottom consolidation and water purification is the important measures. The water quality meets IV standard of the "Environmental Quality Standards for Surface Water" (GB3838-2002) (State EPA of China, 2002) by pollution treatment after remediation, and water volume keeps balance. The findings of this study are expected to provide support for better construction practices in arid and semiarid area in China and for the improvement of the ecological environment in URFa.

3D imaging reveals apical stem cell responses to ambient temperature

Plant growth is driven by apical meristems at the shoot and root growth points, which comprise continuously active stem cell populations. While many of the key factors involved in homeostasis of the shoot apical meristem (SAM) have been extensively studied under artificial constant growth conditions, only little is known how variations in the environment affect the underlying regulatory network. To shed light on the responses of the SAM to ambient temperature, we combined 3D live imaging of fluorescent reporter lines that allowed us to monitor the activity of two key regulators of stem cell homeostasis in the SAM namely CLAVATA3 (CLV3) and WUSCHEL (WUS), with computational image analysis to derive morphological and cellular parameters of the SAM. Whereas CLV3 expression marks the stem cell population, WUS promoter activity is confined to the organizing center (OC), the niche cells adjacent to the stem cells, hence allowing us to record on the two central cell populations of the SAM. Applying an integrated computational analysis of our data we found that variations in ambient temperature not only led to specific changes in spatial expression patterns of key regulators of SAM homeostasis, but also correlated with modifications in overall cellular organization and shoot meristem morphology.

Changes in convective and stratiform precipitation over the Tibetan Plateau projected by global and regional climate models

AbstractPrecipitation is a crucial influencing factor in the global hydrological cycle and terrestrial ecosystems. Previous studies have mostly focused on the historical precipitation variations over the Tibetan Plateau (TP). However, little attention has been given to the differences between convective and stratiform precipitation under future climate change scenarios. In order to acquire the high‐resolution precipitation information over the TP, the dynamical downscaling simulation was conducted utilizing a regional climate model (Weather Research and Forecasting [WRF] model) forced with a global climate model (Community Climate System Model [CCSM]). In this study, we focus on projections of future changes in convective and stratiform precipitation over the TP. The downscaling results during a 26‐year period 1980–2005 are compared for dry season, wet season and annual mean precipitation against the gridded observation dataset. Then, the changes in the wet season convective and stratiform precipitation with warming between CCSM and WRF‐CCSM were compared in the future period 2070–2099 under two scenarios (RCP4.5 and RCP8.5). Compared with the coarse‐resolution forcing, the historical precipitation of dry season, wet season and annual mean over the TP were found to better reproduce in WRF‐CCSM simulation. WRF‐CCSM projects an opposite spatial pattern of total precipitation change between the northern and southern TP in the future under different scenarios, which were attributed to the decreased stratiform precipitation in the southern TP and the increased convective precipitation in the northern TP, contrasting with the uniform increase of total precipitation in its forcing. The surface air temperature projected in WRF‐CCSM is larger increase than in the CCSM forcing. Compared to the CCSM forcing, WRF‐CCSM projects more pronounced increase in convective precipitation in response to rapid warming, and increasingly dominates changes of total precipitation with temperature exceeds the Clausius–Clapeyron rate over the northern TP.