scholarly journals The Diurnal Temperature Range in CMIP6 Models: Climatology, Variability, and Evolution

2020 ◽  
Vol 33 (19) ◽  
pp. 8261-8279
Author(s):  
Kang Wang ◽  
Gary D. Clow
Keyword(s):  
Northern Hemisphere ◽  
Diurnal Temperature Range ◽  
Climate Models ◽  
Coupled Model ◽  
Spatiotemporal Evolution ◽  
Diurnal Temperature ◽  
Temperature Range ◽  
Intercomparison Project ◽  
Land Surfaces ◽  
Better Than

AbstractThe diurnal temperature range (DTR) is an identifiable and sensitive indicator of the synchronicity of changes in diurnal temperature extrema, but capturing DTR dynamics is challenging for climate models. This study investigates the climatology, variability, and changes of DTR in recent models participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6). The results show that the CMIP6 models underestimate DTR climatology relative to observations. Most individual models overestimate December–February variability, particularly at high latitudes of the Northern Hemisphere. The models show substantially different changes over land surfaces and do not fully capture the observed spatiotemporal evolution of DTR. Large intermodel differences seem to be controlled by daily minimum air temperature. In the Northern Hemisphere, precipitation and cloud longwave and shortwave radiative effects appear to make important contributions to the intermodel discrepancies. Evaporative fraction is an important factor contributing to the intermodel differences in DTR during the summer in the Northern Hemisphere. In general, CMIP6 models have not improved their ability to simulate temporal DTR changes in a consistent way over the entire analysis period (1901–2005) relative to their CMIP5 counterparts. For periods of rapid DTR decline (e.g., 1951–80) CMIP6 models are typically better than the CMIP5 versions at simulating DTR, whereas for other periods CMIP6 models underperform their CMIP5 counterparts.

scholarly journals Northern Hemisphere Snow-Cover Trends (1967–2018): A Comparison between Climate Models and Observations

Geosciences ◽  
2019 ◽  
Vol 9 (3) ◽  
pp. 135 ◽  
Author(s):  
◽  
◽  
◽  
◽  
◽  
...  
Keyword(s):  
Snow Cover ◽  
Northern Hemisphere ◽  
Climate Models ◽  
Climate Model ◽  
Coupled Model ◽  
Poor Performance ◽  
Four Seasons ◽  
Intercomparison Project ◽  
Autumn And Winter

Observed changes in Northern Hemisphere snow cover from satellite records were compared to those predicted by all available Coupled Model Intercomparison Project Phase 5 (“CMIP5”) climate models over the duration of the satellite’s records, i.e., 1967–2018. A total of 196 climate model runs were analyzed (taken from 24 climate models). Separate analyses were conducted for the annual averages and for each of the seasons (winter, spring, summer, and autumn/fall). A longer record (1922–2018) for the spring season which combines ground-based measurements with satellite measurements was also compared to the model outputs. The climate models were found to poorly explain the observed trends. While the models suggest snow cover should have steadily decreased for all four seasons, only spring and summer exhibited a long-term decrease, and the pattern of the observed decreases for these seasons was quite different from the modelled predictions. Moreover, the observed trends for autumn and winter suggest a long-term increase, although these trends were not statistically significant. Possible explanations for the poor performance of the climate models are discussed.

scholarly journals Attribution of Recent Temperature Changes in the Australian Region

2005 ◽  
Vol 18 (3) ◽  
pp. 457-464 ◽  
Author(s):  
David J. Karoly ◽  
Karl Braganza
Keyword(s):  
Twentieth Century ◽  
Diurnal Temperature Range ◽  
Significant Contribution ◽  
Climate Models ◽  
Climate Model ◽  
Temperature Changes ◽  
Diurnal Temperature ◽  
Temperature Range ◽  
Climate Model Simulations ◽  
Natural Climate

Abstract Variations of Australian-average mean temperature and diurnal temperature range over the twentieth century are investigated. The observed interannual variability of both is simulated reasonably well by a number of climate models, but they do not simulate the observed relationship between the two. Comparison of the observed warming and reduction in diurnal temperature range with climate model simulations shows that Australian temperature changes over the twentieth century were very unlikely to be due to natural climate variations alone. It is likely that there has been a significant contribution to the observed warming during the second half of the century from increasing atmospheric greenhouse gases and sulfate aerosols.

Evaluation of Historical Diurnal Temperature Range Trends in CMIP5 Models

2013 ◽  
Vol 26 (22) ◽  
pp. 9077-9089 ◽  
Author(s):  
Sophie C. Lewis ◽  
David J. Karoly
Keyword(s):  
Land Surface ◽  
Diurnal Temperature Range ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate Models ◽  
Cmip5 Models ◽  
Model Simulations ◽  
Diurnal Temperature ◽  
Temperature Range ◽  
Maximum Temperatures

Abstract Diurnal temperature range (DTR) is a useful index of climatic change in addition to mean temperature changes. Observational records indicate that DTR has decreased over the last 50 yr because of differential changes in minimum and maximum temperatures. However, modeled changes in DTR in previous climate model simulations of this period are smaller than those observed, primarily because of an overestimate of changes in maximum temperatures. This present study examines DTR trends using the latest generation of global climate models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5) and utilizes the novel CMIP5 detection and attribution experimental design of variously forced historical simulations (natural-only, greenhouse gas–only, and all anthropogenic and natural forcings). Comparison of observed and modeled changes in DTR over the period of 1951–2005 again reveals that global DTR trends are lower in model simulations than observed across the 27-member multimodel ensemble analyzed here. Modeled DTR trends are similar for both experiments incorporating all forcings and for the historical experiment with greenhouse gases only, while no DTR trend is discernible in the naturally forced historical experiment. The persistent underestimate of DTR changes in this latest multimodel evaluation appears to be related to ubiquitous model deficiencies in cloud cover and land surface processes that impact the accurate simulation of regional minimum or maximum temperatures changes observed during this period. Different model processes are likely responsible for subdued simulated DTR trends over the various analyzed regions.

scholarly journals Diurnal Temperature Range in Winter Wheat Growing Regions of China: CMIP6 Model Evaluation and Comparison

2021 ◽  
Author(s):  
Wenqiang Xie ◽  
Shuangshuang Wang ◽  
Xiaodong Yan
Keyword(s):  
Winter Wheat ◽  
Diurnal Temperature Range ◽  
Climate Model ◽  
Wheat Yield ◽  
Coupled Model ◽  
Growing Season ◽  
Skill Score ◽  
Diurnal Temperature ◽  
Temperature Range ◽  
Winter Wheat Yield

Abstract Diurnal temperature range (DTR) is an important meteorological component affecting the yield and protein content of winter wheat. The accuracy of climate model simulations of DTR will directly affect the prediction of winter wheat yield and quality. Previous model evaluations for worldwide or nationwide cannot answer which model is suitable for the estimation of winter wheat yield. We evaluated the ability of the coupled model intercomparison project phase 6 (CMIP6) models to simulate DTR in the winter wheat growing regions of China using CN05 observations. The root mean square error (RMSE) and the interannual varibility skill score (IVS) were used to quantitatively evaluate the ability of models in simulating DTR spatial and temporal characteristics, and the comprehensive rating index (CRI) was used to determine the most suitable climate model for winter wheat. The results showed that the CMIP6 model can reproduce DTR in winter wheat growing regions. BCC-CSM2-MR simulations of DTR in the winter wheat growing season were more consistent with observations. EC-Earth3-Veg simulated the climatological DTR best in the wheat growing regions (RMSE=0.848). Meanwhile, the evaluation for climatological DTR in China is not applicable to the evaluation of DTR in winter wheat growing regions, and the evaluation for annual DTR is not a substitute for the evaluation for winter wheat growing season DTR. Our study highlights the importance of evaluating winter wheat growing regions' DTR, which can further improve the ability of CMIP6 models simulating DTR to serve the research of climate change impact on winter wheat yield.

scholarly journals Trends in the Diurnal Temperature Range Over the Southern Slope of Central Himalaya: Retrospective and Prospective Evaluation

Atmosphere ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1683
Author(s):  
Kalpana Hamal ◽  
Shankar Sharma ◽  
Rocky Talchabhadel ◽  
Munawar Ali ◽  
Yam Prasad Dhital ◽  
...  
Keyword(s):  
Diurnal Temperature Range ◽  
Coupled Model ◽  
Significant Negative Correlation ◽  
Research Unit ◽  
Central Himalaya ◽  
Prospective Evaluation ◽  
Southern Slope ◽  
Diurnal Temperature ◽  
Temperature Range ◽  
Four Seasons

The Diurnal Temperature Range (DTR) profoundly affects human health, agriculture, eco-system, and socioeconomic systems. In this study, we analyzed past and future changes in DTR using gridded Climate Research Unit (CRU) datasets for the years 1950–2020 and an ensemble means of thirteen bias-corrected Coupled Model Intercomparison Project Phase 6 (CMIP6) models under different Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, and SSP5-8.5) scenarios for the rest of the 21st century over the southern slope of Central Himalaya, Nepal. Furthermore, the potential drivers (precipitation and cloud cover) of seasonal and annual DTR were studied using correlation analysis. This study found that the DTR trends generally declined; the highest decrease was observed in the pre-monsoon and winter at a rate of 0.09 °C/decade (p ≤ 0.01). As expected, DTR demonstrated a significant negative correlation with cloudiness and precipitation in all four seasons. Further, the decreased DTR was weakly related to the Sea Surface Temperature variation (SST) in the tropical Pacific and Indian Oceans. We found that the projected DTR changes in the future varied from a marginal increase under the SSP1-2.6 (only pre-monsoon) scenario to continued significant decreases under SSP2-4.5 and SSP5-8.5. Insights based on retrospective and prospective evaluation help to understand the long-term evolution of diurnal temperature variations.

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