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 Contrails, Natural Clouds, and Diurnal Temperature Range

2008 ◽  
Vol 21 (19) ◽  
pp. 5061-5075 ◽  
Author(s):  
Simone Dietmüller ◽  
Michael Ponater ◽  
Robert Sausen ◽  
Klaus-Peter Hoinka ◽  
Susanne Pechtl
Keyword(s):  
United States ◽  
Radiative Forcing ◽  
Diurnal Temperature Range ◽  
Climate Model ◽  
Global Climate Model ◽  
The United States ◽  
Diurnal Temperature ◽  
Temperature Range ◽  
Radiative Impact

Abstract The direct impact of aircraft condensation trails (contrails) on surface temperature in regions of high aircraft density has been a matter of recent debate in climate research. Based on data analysis for the 3-day aviation grounding period over the United States, following the terrorists’ attack of 11 September 2001, a strong effect of contrails reducing the surface diurnal temperature range (DTR) has been suggested. Simulations with the global climate model ECHAM4 (including a contrail parameterization) and long-term time series of observation-based data are used for an independent cross check with longer data records, which allow statistically more reliable conclusions. The climate model underestimates the overall magnitude of the DTR compared to 40-yr ECMWF Re-Analysis (ERA-40) data and station data, but it captures most features of the DTR global distribution and the correlation between DTR and either cloud amount or cloud forcing. The diurnal cycle of contrail radiative impact is also qualitatively consistent with expectations, both at the surface and at the top of the atmosphere. Nevertheless, there is no DTR response to contrails in a simulation that inhibits a global radiative forcing considerably exceeding the upper limit of contrail radiative impact according to current assessments. Long-term trends of DTR, the level of natural DTR variability, and the specific effect of high clouds on DTR are also analyzed. In both ECHAM4 and ERA-40 data, the correlation of cloud coverage or cloud radiative forcing with the DTR is mainly apparent for low clouds. None of the results herein indicates a significant impact of contrails on reducing the DTR. Hence, it is concluded that the respective hypothesis as derived from the 3-day aviation-free period over the United States lacks the required statistical backing.

scholarly journals How aerosols and greenhouse gases influence the diurnal temperature range

2020 ◽  
Author(s):  
Camilla W. Stjern ◽  
Bjørn H. Samset ◽  
Olivier Boucher ◽  
Trond Iversen ◽  
Jean-François Lamarque ◽  
...  
Keyword(s):  
Global Warming ◽  
Greenhouse Gases ◽  
Greenhouse Gas ◽  
Diurnal Temperature Range ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Diurnal Temperature ◽  
Temperature Range ◽  
The Future

Abstract. The diurnal temperature range (DTR), or difference between the maximum and minimum temperature within one day, is one of many climate parameters that affects health, agriculture and society. Understanding how DTR evolves under global warming is therefore crucial. Since physically different drivers of climate change, such as greenhouse gases and aerosols, have distinct influences on global and regional climate, predicting the future evolution of DTR requires knowledge of the effects of individual climate forcers, as well as of the future emissions mix, in particular in high emission regions. Using global climate model simulations from the Precipitation Driver and Response Model Intercomparison Project (PDRMIP), we investigate how idealized changes in the atmospheric levels of a greenhouse gas (CO2) and aerosols (black carbon and sulfate) influence DTR, globally and in selected regions. We find broad geographical patterns of annual mean change that are similar between climate drivers, pointing to a generalized response to global warming which is not defined by the individual forcing agents. Seasonal and regional differences, however, are substantial, which highlights the potential importance of local background conditions and feedbacks. While differences in DTR responses among drivers are minor in Europe and North America, there are distinctly different DTR responses to aerosols and greenhouse gas perturbations over India and China, where present aerosol emissions are particularly high. BC induces substantial reductions in DTR, which we attribute to strong modelled BC-induced cloud responses in these regions.

scholarly journals How aerosols and greenhouse gases influence the diurnal temperature range

2020 ◽  
Vol 20 (21) ◽  
pp. 13467-13480
Author(s):  
Camilla W. Stjern ◽  
Bjørn H. Samset ◽  
Olivier Boucher ◽  
Trond Iversen ◽  
Jean-François Lamarque ◽  
...  
Keyword(s):  
Global Warming ◽  
Greenhouse Gases ◽  
Greenhouse Gas ◽  
Diurnal Temperature Range ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Diurnal Temperature ◽  
Temperature Range ◽  
The Future

Abstract. The diurnal temperature range (DTR) (or difference between the maximum and minimum temperature within a day) is one of many climate parameters that affects health, agriculture and society. Understanding how DTR evolves under global warming is therefore crucial. Physically different drivers of climate change, such as greenhouse gases and aerosols, have distinct influences on global and regional climate. Therefore, predicting the future evolution of DTR requires knowledge of the effects of individual climate forcers, as well as of the future emissions mix, in particular in high-emission regions. Using global climate model simulations from the Precipitation Driver and Response Model Intercomparison Project (PDRMIP), we investigate how idealized changes in the atmospheric levels of a greenhouse gas (CO2) and aerosols (black carbon and sulfate) influence DTR (globally and in selected regions). We find broad geographical patterns of annual mean change that are similar between climate drivers, pointing to a generalized response to global warming which is not defined by the individual forcing agents. Seasonal and regional differences, however, are substantial, which highlights the potential importance of local background conditions and feedbacks. While differences in DTR responses among drivers are minor in Europe and North America, there are distinctly different DTR responses to aerosols and greenhouse gas perturbations over India and China, where present aerosol emissions are particularly high. BC induces substantial reductions in DTR, which we attribute to strong modeled BC-induced cloud responses in these regions.

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 Comparison of Early Twentieth Century Arctic Warming and Contemporary Arctic Warming in the light of daily and sub-daily data

2022 ◽  
pp. 1-59
Keyword(s):  
Twentieth Century ◽  
Air Temperature ◽  
Diurnal Temperature Range ◽  
Surface Air Temperature ◽  
The Arctic ◽  
Arctic Warming ◽  
Diurnal Temperature ◽  
Temperature Range ◽  
Early Twentieth Century ◽  
Daily Data

Abstract A review of many studies published since the late 1920s reveals that the main driving mechanisms responsible for the Early Twentieth Century Arctic Warming (ETCAW) are not fully recognized. The main obstacle seems to be our limited knowledge about the climate of this period and some forcings. A deeper knowledge based on greater spatial and temporal resolution data is needed. The article provides new (or improved) knowledge about surface air temperature (SAT) conditions (including their extreme states) in the Arctic during the ETCAW. Daily and sub-daily data have been used (mean daily air temperature, maximum and minimum daily temperature, and diurnal temperature range). These were taken from ten individual years (selected from the period 1934–50) for six meteorological stations representing parts of five Arctic climatic regions. Standard SAT characteristics were analyzed (monthly, seasonal, and yearly means), as were rarely investigated aspects of SAT characteristics (e.g., number of characteristic days; day-to-day temperature variability; and onset, end, and duration of thermal seasons). The results were compared with analogical calculations done for data taken from the Contemporary Arctic Warming (CAW) period (2007–16). The Arctic experienced warming between the ETCAW and the CAW. The magnitude of warming was greatest in the Pacific (2.7 °C) and Canadian Arctic (1.9 °C) regions. A shortening of winter and lengthening of summer were registered. Furthermore, the climate was also a little more continental (except the Russian Arctic) and less stable (greater day-to-day variability and diurnal temperature range) during the ETCAW than during the CAW.

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 mean maximum temperature, mean minimum temperature and mean relative humidity for Lautoka, Fiji during 2003–2013

2017 ◽  
Vol 26 (4) ◽  
pp. 415-422 ◽  
Author(s):  
Syed Ghani ◽  
Aman Deo ◽  
Md Iqubal ◽  
Ramendra Prasad
Keyword(s):  
Relative Humidity ◽  
Minimum Temperature ◽  
Diurnal Temperature Range ◽  
Maximum Temperature ◽  
Small Island ◽  
Climate Conditions ◽  
Temperature Changes ◽  
Diurnal Temperature ◽  
Temperature Range ◽  
Recent Climate

The current work observes the trends in Lautoka’s temperature and relative humidity during the period 2003–2013, which were analyzed using the recently updated data obtained from Fiji Meteorological Services (FMS). Four elements, mean maximum temperature, mean minimum temperature along with diurnal temperature range (DTR) and mean relative humidity are investigated. From 2003–2013, the annual mean temperature has been enhanced between 0.02 and 0.080C. The heating is more in minimum temperature than in maximum temperature, resulting in a decrease of diurnal temperature range. The statistically significant increase was mostly seen during the summer months of December and January. Mean Relative Humidity has also increased from 3% to 8%. The bases of abnormal climate conditions are also studied. These bases were defined with temperature or humidity anomalies in their appropriate time sequences. These established the observed findings and exhibited that climate has been becoming gradually damper and heater throughout Lautoka during this period. While we are only at an initial phase in the probable inclinations of temperature changes, ecological reactions to recent climate change are already evidently noticeable. So it is proposed that it would be easier to identify climate alteration in a small island nation like Fiji.

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