Evaluating observed and future spatiotemporal changes in precipitation and temperature across China based on <scp>CMIP6‐GCMs</scp>

Lu, Kaidong; Arshad, Muhammad; Ma, Xieyao; Ullah, Irfan; Wang, Jianjian; Shao, Wei

doi:10.1002/joc.7673

Cited by 47 publications

(26 citation statements)

References 84 publications

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“…Interestingly, the present study also witnessed increasing trends of warm temperature events in the southwestern and northeastern parts of the regions, which agreed with the findings of previous studies in the same regions [51,52]. The upsurge of frequency, intensity, and extent of daily warm extreme temperature and decline of extreme cold temperature may occur in parts of the world, resulting in the escalation of length and intensity of warm period or a heatwave in most land areas [3,5,53,54].…”

Section: Observed Annual and Seasonal Trends Of Precipitation And Tem...supporting

confidence: 92%

Recent Changes in Drought Events over South Asia and Their Possible Linkages with Climatic and Dynamic Factors

Ullah

Ren

et al. 2022

Remote Sensing

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South Asia is home to one of the fastest-growing populations in Asia, and human activities are leaving indelible marks on the land surface. Yet the likelihood of successive observed droughts in South Asia (SA) and its four subregions (R-1: semi-arid, R-2: arid, R-3: subtropical wet, and R-4: tropical wet and dry) remains poorly understood. Using the state-of-the-art self-calibrated Palmer Drought Severity Index (scPDSI), we examined the impact of different natural ocean variability modes on the evolution, severity, and magnitude of observed droughts across the four subregions that have distinct precipitation seasonality and cover key breadbaskets and highly vulnerable populations. The study revealed that dryness had significantly increased in R-1, R-2, and R-4 during 1981–2020. Temporal analysis revealed an increase in drought intensity for R-1 and R-4 since the 2000s, while a mixed behavior was observed in R-2 and R-3. Moreover, most of the sub-regions witnessed a substantial upsurge in annual precipitation, but a significant decrease in vapor pressure deficit (VPD) during 1981–2020. The increase in precipitation and the decline in VPD partially contributed to a significant rise in Normalized Difference Vegetation Index (NDVI) and a decrease in dryness. In contrast, a strong positive correlation was found between drought index and precipitation, and NDVI across R-1, R-2, and R-4, whereas temperature and VPD exhibited a negative correlation over these regions. No obvious link was detected with El-Niño Southern Oscillation (ENSO) events, or Indian Ocean Dipole (IOD) and drought evolution, as explored for certain regions of SA. The findings showed the possibility that the precipitation changes over these regions had an insignificant relationship with ENSO, IOD, and drought onset. Thus, the study results highlight the need for considering interactions within the longer climate system in describing observed drought risks rather than aiming at drivers from an individual perspective.

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Section: Observed Annual and Seasonal Trends Of Precipitation And Tem...supporting

confidence: 92%

Recent Changes in Drought Events over South Asia and Their Possible Linkages with Climatic and Dynamic Factors

Ullah

Ren

et al. 2022

Remote Sensing

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“…However, rainfall responses to climate change are highly uncertain over most parts of SA (Almazroui et al., 2020). Although rainfall extremes are expected to increase under the warmer climate in SA (Ali et al., 2019; Almazroui et al., 2020; Lu et al., 2022), extreme rainfall and initial hydroclimate events may play a vital role (Mie Sein et al., 2021; Ullah, Ma, et al., 2022). Similarly, SA has witnessed notable drought events that have had a remarkable imprint on groundwater resources and agricultural production (Aadhar & Mishra, 2020b; Saleem et al., 2021).…”

Section: Introductionmentioning

confidence: 99%

Projected Changes in Increased Drought Risks Over South Asia Under a Warmer Climate

Ullah

Asfaw

et al. 2022

Earth's Future

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Every year, millions of people are at risk due to droughts in South Asia (SA). The likely impacts of droughts are projected to increase with global warming. This study uses the new ensemble mean of 23 global climate models from the Coupled Model Intercomparison Project phase 6 (CMIP6), population and gross domestic product (GDP) projections to quantify future changes in increasing drought risks and associated socioeconomic exposure across SA and its subregions under 1.5°C and 2°C of warming. We used two shared socioeconomic pathways (SSPs), SSP2‐4.5 and SSP5‐8.5. The most likely realization copula functions are used to model the joint distribution of drought severity and duration. Simultaneously, changes in the bivariate return period are calculated under a warming climate. The frequency of 50‐year historical droughts (under a bivariate framework) might double across 80% of the SA land area under 1.5°C of warming. Conversely, 12% of SA landmasses may suffer extreme droughts under 2°C of warming. The severe drought episode frequency is expected to increase under 1.5°C (40%–75%) and 2°C (60%–90%) of warming relative to the recent climate. The largest exposure increase is projected in R2 and R4, then R1. Additionally, 75% (65%) of the SA population (GDP) could suffer from increased drought risks under the 1.5°C warmer climate, whereas the additional 0.5°C warming will lead to an unbearable regional situation. Limiting global warming to 1.5°C compared with 2°C can significantly reduce the drought risk influence in SA. These findings can help disaster‐risk managers to adopt climate‐smart management strategies.

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“…The DL merged data have showed a relatively small rise than the EM data globally. From the regional scale, researchers found that EM mean temperature data underestimates temperature in three main river basins (Yellow River basin, Yangtze River basin and Southwest River basin) of China (Lu et al ., 2022).…”

Section: Resultsmentioning

confidence: 99%

Deep‐learning‐based harmonization and super‐resolution of near‐surface air temperature from CMIP6 models (1850–2100)

Wei

Wang

Feng

et al. 2022

Intl Journal of Climatology

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Future global temperature change will have significant effects on society and ecosystems. Earth system models (ESM) are the primary tools to explore future climate change. However, ESMs have great uncertainty and often run at a coarse spatial resolution (usually about 2°). Accurate high‐spatial‐resolution temperature dataset are needed to improve our understanding of temperature variations and for many other applications. We apply Super resolution (SR) in computer vision using deep learning (DL) to merge 31 ESMs data. The proposed method performs data merging, bias‐correction, and spatial downscaling simultaneously. The CRU TS (Climate Research Unit gridded Time Series) data is used as reference data in the model training process. To find a suitable DL method, we select five SR methodologies with different structures. We compare the performances of the methods based on mean square error (MSE), mean absolute error (MAE) and Pearson correlation coefficient (R). The best method is used to merge the projected monthly data (1850–1900), and monthly future scenarios data (2015–2100), at the high spatial resolution of 0.5°. Results show that the merged data have considerably improved performance compared with individual ESM data and their ensemble mean (EM), both spatially and temporally. The MAE shows significant improvement; the spatial distribution of the MAE widens along the latitudes in the Northern Hemisphere. The MAE of merged data is ranging from 0.60 to 1.50, the South American (SA) has the lowest error and the Europe has the highest error. The merged product has excellent performance when the observation data is smooth with few fluctuations in the time series. This work demonstrates the applicability and effectiveness of the DL methods in data merging, bias‐correction and spatial downscaling when enough training data are available. Data can be accessed at https://doi.org/10.5281/zenodo.5746632.

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Evaluating observed and future spatiotemporal changes in precipitation and temperature across China based on CMIP6‐GCMs

Cited by 47 publications

References 84 publications

Recent Changes in Drought Events over South Asia and Their Possible Linkages with Climatic and Dynamic Factors

Recent Changes in Drought Events over South Asia and Their Possible Linkages with Climatic and Dynamic Factors

Projected Changes in Increased Drought Risks Over South Asia Under a Warmer Climate

Deep‐learning‐based harmonization and super‐resolution of near‐surface air temperature from CMIP6 models (1850–2100)

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