Modeling Earth Systems and Environment, Год журнала: 2023, Номер 9(3), С. 3011 - 3028
Опубликована: Янв. 31, 2023
Язык: Английский
npj Climate and Atmospheric Science, Год журнала: 2024, Номер 7(1)
Опубликована: Март 29, 2024
Abstract Drought risk threatens pastoralism in rangelands, which are already under strain from climatic and socioeconomic changes. We examine the future drought (2031–2060 2071–2100) to rangeland productivity across Eurasia (West, Central, East Asia) using a well-tested process-based ecosystem model projections of five climate models three shared pathway (SSP) scenarios low (SSP1−2.6), medium (SSP3−7.0), high (SSP5−8.5) warming relative 1985–2014. employ probabilistic approach, with defined as expected loss induced by probability hazardous droughts (determined precipitation-based index) vulnerability (the response droughts). projected increase magnitude area Eurasian greater increases 2071–2100 than 2031–2060. Increasing West Asia is caused longer more intense vulnerability, whereas higher Central mainly associated increased indicating overall where increases. These findings suggest that may exacerbate livestock feed shortages negatively impact pastoralism. The results have practical implications for management should be adapted ecological contexts different countries region. Existing traditional knowledge can promoted adapt embedded wider set adaptation measures involving improvements, social transformations, capacity building, policy reforms addressing multiple stakeholders.
Язык: Английский
Процитировано
5
Geoscientific model development, Год журнала: 2024, Номер 17(3), С. 1249 - 1269
Опубликована: Фев. 14, 2024
Abstract. Statistical bias adjustment is commonly applied to climate models before using their results in impact studies. However, different methods based on a distributional mapping between observational and model data can change the simulated trends as well spatiotemporal inter-variable consistency of model, are prone misuse if not evaluated thoroughly. Despite importance these fundamental issues, researchers who apply currently do have tools at hand compare or evaluate sufficiently detect possible distortions. Because this, widespread practice statistical aligned with recommendations from academic literature. To address practical issues impeding we introduce ibicus, an open-source Python package for implementation eight peer-reviewed widely used common framework comprehensive evaluation. The evaluation introduced ibicus allows user analyse changes marginal, structure user-defined indices properties any alteration trend model. Applying case study over Mediterranean region seven CMIP6 global circulation models, this finds that most appropriate method depends variable studied, even aim preserve modify it. These findings highlight use-case-specific selection need rigorous when applying adjustment.
Язык: Английский
Процитировано
3
International Journal of Climatology, Год журнала: 2024, Номер 44(6), С. 1994 - 2010
Опубликована: Март 20, 2024
Abstract To evaluate future changes in the climate system, outputs from coarse‐resolution global models (GCMs) need to be downscaled a finer scale, making them more directly applicable for impact assessment. Here we focus on examining projected of three key variables (precipitation, air temperature, and wet bulb temperature) across Arizona (south‐western United States). We use daily GCMs sixth phase Coupled Model Intercomparison Project (CMIP6) bias correct downscale 4‐km resolution. Through leave‐one‐out cross‐validation, compare various correction methods identify that empirical quantile mapping approach performs best regardless variable. Then, analyse bias‐corrected two periods (Mid‐of‐Century: 2015–2048; End‐of‐Century: 2067–2100) with respect 1981–2014 period, under four shared socioeconomic pathway scenarios (SSP1‐2.6, SSP2‐4.5, SSP3‐7.0 SSP5‐8.5). Our results show Arizona's is become overall warmer wetter, so towards end this century higher emission scenarios. Additionally, our findings project an increase temperature cooling degree days, implying ongoing warming climate's potential impacts public health economy. These provide baseline understanding change state highlight response
Язык: Английский
Процитировано
3
Geographica Pannonica, Год журнала: 2024, Номер 28(1), С. 53 - 70
Опубликована: Янв. 1, 2024
This study utilizes satellite-based rainfall CHIRPS to evaluate GCMs-CMIP6 models over Sudan from 1985 2014. Overall, the GCMs of BCC-CSM2-MR, CAMS-CSM1-0, CESM2, ECEarth3-Veg, GFDL-ESM4, MIROC-ES2L, and NorESM2-MM are well reproduced in unimodal pattern June September (JJAS), hence employed calculate Multi-Model Ensemble (MME). Then, we examine capability MME replicating precipitation patterns on annual seasonal scales using numerous ranking metrics, including Pearson Correlation Coefficient (CC), Standard Deviation (SD), Taylor Skill Score (TSS), Mean Absolute Error (MAE), absolute bias (BIAS), and, normalized mean root square error (RMSD). The results show that has lowest slightly overestimates most parts our domain, whilst, others (ACCESS-CM2, CNRM-CM6-1, CNRM-CM6-1-HR, CNRM-ESM2-1, FGOALS-f3-L, FGOALS-g3) consistently overestimate referring data, respectively, but FIO-ESM-2-0 underestimates value. Moreover, MIROC-ES2L demonstrate better performance than other models. Finally, a correction (BC) technique, namely Delta BC, adjust model products through monsoon seasons. applied technique revealed remarkable improvement against observations, with an 0 - 18% original. However, after
Язык: Английский
Процитировано
3
Atmospheric Research, Год журнала: 2024, Номер 307, С. 107481 - 107481
Опубликована: Май 21, 2024
Язык: Английский
Процитировано
3
International Journal of Water Resources Development, Год журнала: 2024, Номер unknown, С. 1 - 21
Опубликована: Сен. 30, 2024
Язык: Английский
Процитировано
3
Theoretical and Applied Climatology, Год журнала: 2025, Номер 156(2)
Опубликована: Янв. 16, 2025
Язык: Английский
Процитировано
0
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
0
Journal of Hydrology Regional Studies, Год журнала: 2025, Номер 59, С. 102399 - 102399
Опубликована: Май 9, 2025
Язык: Английский
Процитировано
0
Journal of Environmental Management, Год журнала: 2025, Номер 388, С. 126025 - 126025
Опубликована: Май 31, 2025
In a rapidly changing world, uncontrolled climate change worsens water scarcity disrupting hydrological cycles and hindering sustainable development. Addressing resources vulnerability requires holistic approaches to better understand complex systems, mitigate risks from weather patterns, develop adaptive management strategies. this study, we modeled impacts on resource using machine learning (ML) SWAT model based CMIP6 Global Climate Model (GCMs) under Shared Socioeconomic Pathway (SSP). Six ML models were evaluated reliably predict hydroclimatic events; Extremely Randomised Trees (ERT) Categorical Boosting (CatBoost) performed best for simulating ensemble interactions. The statistical indicators confirmed reliability reducing input uncertainties with bias-corrected datasets. simulation showed good agreement between simulated observed values (R2 = 93 %, NSE 91 PBIAS -1.08 %) calibration 94 -2.32 validation periods. Furthermore, developed novel Hydrologic Vulnerability Index (HVI) framework balance components quantify watershed dynamics across baseline future scenarios. HVI ranged low extreme, maximum lower (54.03 at baseline, indicating resilience stress, higher severe (43.45 SSP245, extreme drought conditions. integrates projections actionable insights, offering comprehensive approach management, infrastructure, targeted interventions. Hence, innovative policies are critical address HVIs ensuring against ecosystem degradation. This study underscores the importance of coupling data-driven analysis responsiveness effective environmental sustainability. These results demonstrate integrating various perspectives strategies both short- long-term climatic problems, by employing practices ensure sufficient resilience.
Язык: Английский
Процитировано
0