scholarly journals Spatial downscaling method and application of CMIP5 global climate models based on improved U-Net in Lake Poyang Basin

2022 ◽  
Vol 34 (1) ◽  
pp. 320-333
Author(s):  
Li Kecheng ◽  
◽  
Lu Jianzhong ◽  
Zhang Kerui ◽  
Lu Chengyu ◽  
...  
2020 ◽  
Vol 12 (6) ◽  
pp. 1030 ◽  
Author(s):  
Mengchao Xu ◽  
Qian Liu ◽  
Dexuan Sha ◽  
Manzhu Yu ◽  
Daniel Q. Duffy ◽  
...  

Climate and weather data such as precipitation derived from Global Climate Models (GCMs) and satellite observations are essential for the global and local hydrological assessment. However, most climatic popular precipitation products (with spatial resolutions coarser than 10km) are too coarse for local impact studies and require “downscaling” to obtain higher resolutions. Traditional precipitation downscaling methods such as statistical and dynamic downscaling require an input of additional meteorological variables, and very few are applicable for downscaling hourly precipitation for higher spatial resolution. Based on dynamic dictionary learning, we propose a new downscaling method, PreciPatch, to address this challenge by producing spatially distributed higher resolution precipitation fields with only precipitation input from GCMs at hourly temporal resolution and a large geographical extent. Using aggregated Integrated Multi-satellitE Retrievals for GPM (IMERG) data, an experiment was conducted to evaluate the performance of PreciPatch, in comparison with bicubic interpolation using RainFARM—a stochastic downscaling method, and DeepSD—a Super-Resolution Convolutional Neural Network (SRCNN) based downscaling method. PreciPatch demonstrates better performance than other methods for downscaling short-duration precipitation events (used historical data from 2014 to 2017 as the training set to estimate high-resolution hourly events in 2018).


2021 ◽  

<p>Researches to foresee the possible effects of climate change on the environment and living beings for taking necessary precautions on time have increased in recent years. In the improvement of these studies, especially the reduction of estimation errors by downscaling the outputs of global climate models played an important role. In this study, a model that can predict monthly precipitation amounts in the future by using downscaling methods in different global climate models were applied in Antakya district of Hatay province, and the model results were evaluated. The predictive parameters for global climate models were determined using downscaling methods by applying correlation analysis for the study area. As a result of this analysis, it was seen that the air temperature and specific humidity values at the pressure level of 925 hPa and the geopotential height value at the 300 hPa pressure level had the best correlation for the years 1970-2005. The usability of three different global climate models (CanESM2, GISS-E2H, and CSIRO Mk 3-6-0) for the forecast of future rainfall in the Antakya district of Hatay province was investigated using multiple linear regression analysis, one of the downscaling methods. As a result of the statistical analysis, it was seen that the use of the downscaling method increased the accuracy of all prediction models.</p>


2011 ◽  
Author(s):  
Enrico Scoccimarro ◽  
Silvio Gualdi ◽  
Antonella Sanna ◽  
Edoardo Bucchignani ◽  
Myriam Montesarchio

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Mateusz Taszarek ◽  
John T. Allen ◽  
Mattia Marchio ◽  
Harold E. Brooks

AbstractGlobally, thunderstorms are responsible for a significant fraction of rainfall, and in the mid-latitudes often produce extreme weather, including large hail, tornadoes and damaging winds. Despite this importance, how the global frequency of thunderstorms and their accompanying hazards has changed over the past 4 decades remains unclear. Large-scale diagnostics applied to global climate models have suggested that the frequency of thunderstorms and their intensity is likely to increase in the future. Here, we show that according to ERA5 convective available potential energy (CAPE) and convective precipitation (CP) have decreased over the tropics and subtropics with simultaneous increases in 0–6 km wind shear (BS06). Conversely, rawinsonde observations paint a different picture across the mid-latitudes with increasing CAPE and significant decreases to BS06. Differing trends and disagreement between ERA5 and rawinsondes observed over some regions suggest that results should be interpreted with caution, especially for CAPE and CP across tropics where uncertainty is the highest and reliable long-term rawinsonde observations are missing.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Lennart Quante ◽  
Sven N. Willner ◽  
Robin Middelanis ◽  
Anders Levermann

AbstractDue to climate change the frequency and character of precipitation are changing as the hydrological cycle intensifies. With regards to snowfall, global warming has two opposing influences; increasing humidity enables intense snowfall, whereas higher temperatures decrease the likelihood of snowfall. Here we show an intensification of extreme snowfall across large areas of the Northern Hemisphere under future warming. This is robust across an ensemble of global climate models when they are bias-corrected with observational data. While mean daily snowfall decreases, both the 99th and the 99.9th percentiles of daily snowfall increase in many regions in the next decades, especially for Northern America and Asia. Additionally, the average intensity of snowfall events exceeding these percentiles as experienced historically increases in many regions. This is likely to pose a challenge to municipalities in mid to high latitudes. Overall, extreme snowfall events are likely to become an increasingly important impact of climate change in the next decades, even if they will become rarer, but not necessarily less intense, in the second half of the century.


Water ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 1819
Author(s):  
Eleni S. Bekri ◽  
Polychronis Economou ◽  
Panayotis C. Yannopoulos ◽  
Alexander C. Demetracopoulos

Freshwater resources are limited and seasonally and spatially unevenly distributed. Thus, in water resources management plans, storage reservoirs play a vital role in safeguarding drinking, irrigation, hydropower and livestock water supply. In the last decades, the dams’ negative effects, such as fragmentation of water flow and sediment transport, are considered in decision-making, for achieving an optimal balance between human needs and healthy riverine and coastal ecosystems. Currently, operation of existing reservoirs is challenged by increasing water demand, climate change effects and active storage reduction due to sediment deposition, jeopardizing their supply capacity. This paper proposes a methodological framework to reassess supply capacity and management resilience for an existing reservoir under these challenges. Future projections are derived by plausible climate scenarios and global climate models and by stochastic simulation of historic data. An alternative basic reservoir management scenario with a very low exceedance probability is derived. Excess water volumes are investigated under a probabilistic prism for enabling multiple-purpose water demands. Finally, this method is showcased to the Ladhon Reservoir (Greece). The probable total benefit from water allocated to the various water uses is estimated to assist decision makers in examining the tradeoffs between the probable additional benefit and risk of exceedance.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Jun Yang ◽  
Maigeng Zhou ◽  
Zhoupeng Ren ◽  
Mengmeng Li ◽  
Boguang Wang ◽  
...  

AbstractRecent studies have reported a variety of health consequences of climate change. However, the vulnerability of individuals and cities to climate change remains to be evaluated. We project the excess cause-, age-, region-, and education-specific mortality attributable to future high temperatures in 161 Chinese districts/counties using 28 global climate models (GCMs) under two representative concentration pathways (RCPs). To assess the influence of population ageing on the projection of future heat-related mortality, we further project the age-specific effect estimates under five shared socioeconomic pathways (SSPs). Heat-related excess mortality is projected to increase from 1.9% (95% eCI: 0.2–3.3%) in the 2010s to 2.4% (0.4–4.1%) in the 2030 s and 5.5% (0.5–9.9%) in the 2090 s under RCP8.5, with corresponding relative changes of 0.5% (0.0–1.2%) and 3.6% (−0.5–7.5%). The projected slopes are steeper in southern, eastern, central and northern China. People with cardiorespiratory diseases, females, the elderly and those with low educational attainment could be more affected. Population ageing amplifies future heat-related excess deaths 2.3- to 5.8-fold under different SSPs, particularly for the northeast region. Our findings can help guide public health responses to ameliorate the risk of climate change.


2021 ◽  
Vol 2 (1) ◽  
Author(s):  
David Docquier ◽  
Torben Koenigk

AbstractArctic sea ice has been retreating at an accelerating pace over the past decades. Model projections show that the Arctic Ocean could be almost ice free in summer by the middle of this century. However, the uncertainties related to these projections are relatively large. Here we use 33 global climate models from the Coupled Model Intercomparison Project 6 (CMIP6) and select models that best capture the observed Arctic sea-ice area and volume and northward ocean heat transport to refine model projections of Arctic sea ice. This model selection leads to lower Arctic sea-ice area and volume relative to the multi-model mean without model selection and summer ice-free conditions could occur as early as around 2035. These results highlight a potential underestimation of future Arctic sea-ice loss when including all CMIP6 models.


2008 ◽  
Vol 80 (2) ◽  
pp. 397-408 ◽  
Author(s):  
David M. Lapola ◽  
Marcos D. Oyama ◽  
Carlos A. Nobre ◽  
Gilvan Sampaio

We developed a new world natural vegetation map at 1 degree horizontal resolution for use in global climate models. We used the Dorman and Sellers vegetation classification with inclusion of a new biome: tropical seasonal forest, which refers to both deciduous and semi-deciduous tropical forests. SSiB biogeophysical parameters values for this new biome type are presented. Under this new vegetation classification we obtained a consensus map between two global natural vegetation maps widely used in climate studies. We found that these two maps assign different biomes in ca. 1/3 of the continental grid points. To obtain a new global natural vegetation map, non-consensus areas were filled according to regional consensus based on more than 100 regional maps available on the internet. To minimize the risk of using poor quality information, the regional maps were obtained from reliable internet sources, and the filling procedure was based on the consensus among several regional maps obtained from independent sources. The new map was designed to reproduce accurately both the large-scale distribution of the main vegetation types (as it builds on two reliable global natural vegetation maps) and the regional details (as it is based on the consensus of regional maps).


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