scholarly journals Biases and Model Agreement in Projections of Climate Extremes over the Tropical Pacific

2011 ◽  
Vol 15 (24) ◽  
pp. 1-36 ◽  
Author(s):  
Sarah E. Perkins

Abstract Using the Coupled Model Intercomparison Project phase 3 (CMIP3) general circulation models (GCMs), projections of a range of climate extremes are explored for the western Pacific. These projections include the 1-in-20-yr return levels and a selection of climate indices for minimum temperature, maximum temperature, and precipitation, and they are compared to corresponding mean projections for the Special Report on Emission Scenarios (SRES) A2 scenario during 2081–2100. Models are evaluated per variable based on their ability to simulate current extremes, as well as the overall daily distribution. Using the standardized evaluation scores for each variable, models are divided into four subsets where ensemble variability is calculated to measure model uncertainty and biases are calculated in respect to the multimodel ensemble (MME). Results show that higher uncertainty in projections of climate extremes exists when compared to the mean, even in those subsets consisting of higher-skilled models. Higher uncertainty exists for precipitation projections than for temperature, and biases and uncertainties in the 1-in-20-yr precipitation events are an order of magnitude higher than the corresponding mean. Poorer performing models exhibit a cooler bias in the mean and 1-in-20-yr return levels for maximum and minimum temperature, and ensemble variability is low among all subsets of mean minimum temperature, especially the lower-skilled subsets. Higher-skilled models project 1-in-20-yr precipitation return levels that are more intense than in the MME. The frequency of temperature extremes increase dramatically; however, this is explained by the underpinning small temperature range of the region. Although some systematic biases occur in the higher- and lower-skilled models and omitting the poorer performers is recommended, great care should be exercised when interpreting the reduction of uncertainty because the ensemble variability among the remaining models is comparable and in some cases greater than the MME. Such results should be treated on a case-by-case basis.

Water ◽  
2018 ◽  
Vol 10 (12) ◽  
pp. 1793 ◽  
Author(s):  
Najeebullah Khan ◽  
Shamsuddin Shahid ◽  
Kamal Ahmed ◽  
Tarmizi Ismail ◽  
Nadeem Nawaz ◽  
...  

The performance of general circulation models (GCMs) in a region are generally assessed according to their capability to simulate historical temperature and precipitation of the region. The performance of 31 GCMs of the Coupled Model Intercomparison Project Phase 5 (CMIP5) is evaluated in this study to identify a suitable ensemble for daily maximum, minimum temperature and precipitation for Pakistan using multiple sets of gridded data, namely: Asian Precipitation–Highly-Resolved Observational Data Integration Towards Evaluation (APHRODITE), Berkeley Earth Surface Temperature (BEST), Princeton Global Meteorological Forcing (PGF) and Climate Prediction Centre (CPC) data. An entropy-based robust feature selection approach known as symmetrical uncertainty (SU) is used for the ranking of GCM. It is known from the results of this study that the spatial distribution of best-ranked GCMs varies for different sets of gridded data. The performance of GCMs is also found to vary for both temperatures and precipitation. The Commonwealth Scientific and Industrial Research Organization, Australia (CSIRO)-Mk3-6-0 and Max Planck Institute (MPI)-ESM-LR perform well for temperature while EC-Earth and MIROC5 perform well for precipitation. A trade-off is formulated to select the common GCMs for different climatic variables and gridded data sets, which identify six GCMs, namely: ACCESS1-3, CESM1-BGC, CMCC-CM, HadGEM2-CC, HadGEM2-ES and MIROC5 for the reliable projection of temperature and precipitation of Pakistan.


Atmosphere ◽  
2019 ◽  
Vol 10 (11) ◽  
pp. 675 ◽  
Author(s):  
Almazroui

This paper investigates the temperature and precipitation extremes over the Arabian Peninsula using data from the regional climate model RegCM4 forced by three Coupled Model Intercomparison Project Phase 5 (CMIP5) models and ERA–Interim reanalysis data. Indices of extremes are calculated using daily temperature and precipitation data at 27 meteorological stations located across Saudi Arabia in line with the suggested procedure from the Expert Team on Climate Change Detection and Indices (ETCCDI) for the present climate (1986–2005) using 1981–2000 as the reference period. The results show that RegCM4 accurately captures the main features of temperature extremes found in surface observations. The results also show that RegCM4 with the CLM land–surface scheme performs better in the simulation of precipitation and minimum temperature, while the BATS scheme is better than CLM in simulating maximum temperature. Among the three CMIP5 models, the two best performing models are found to accurately reproduce the observations in calculating the extreme indices, while the other is not so successful. The reason for the good performance by these two models is that they successfully capture the circulation patterns and the humidity fields, which in turn influence the temperature and precipitation patterns that determine the extremes over the study region.


2021 ◽  
Vol 9 ◽  
Author(s):  
Chuyin Tian ◽  
Guohe Huang ◽  
Yanli Liu ◽  
Denghua Yan ◽  
Feng Wang ◽  
...  

Evident climate change has been observed and projected in observation records and General Circulation Models (GCMs), respectively. This change is expected to reshape current seasonal variability; the degree varies between regions. High-resolution climate projections are thereby necessary to support further regional impact assessment. In this study, a gated recurrent unit-based recurrent neural network statistical downscaling model is developed to project future temperature change (both daily maximum temperature and minimum temperature) over Metro Vancouver, Canada. Three indexes (i.e., coefficient of determinant, root mean square error, and correlation coefficient) are estimated for model validation, indicating the developed model’s competitive ability to simulate the regional climatology of Metro Vancouver. Monthly comparisons between simulation and observation also highlight the effectiveness of the proposed downscaling method. The projected results (under one model set-up, WRF-MPI-ESM-LR, RCP 8.5) show that both maximum and minimum temperature will consistently increase between 2,035 and 2,100 over the 12 selected meteorological stations. By the end of this century, the daily maximum temperature and minimum temperature are expected to increase by an average of 2.91°C and 2.98°C. Nevertheless, with trivial increases in summer and significant rises in winter and spring, the seasonal variability will be reduced substantially, which indicates less energy requirement over Metro Vancouver. This is quite favorable for Metro Vancouver to switch from fossil fuel-based energy sources to renewable and clean forms of energy. Further, the cold extremes’ frequency of minimum temperature will be reduced as expected; however, despite evident warming trend, the hot extremes of maximum temperature will become less frequent.


2020 ◽  
Vol 20 (14) ◽  
pp. 8381-8404 ◽  
Author(s):  
Prodromos Zanis ◽  
Dimitris Akritidis ◽  
Aristeidis K. Georgoulias ◽  
Robert J. Allen ◽  
Susanne E. Bauer ◽  
...  

Abstract. In this work, we use Coupled Model Intercomparison Project Phase 6 (CMIP6) simulations from 10 Earth system models (ESMs) and general circulation models (GCMs) to study the fast climate responses on pre-industrial climate, due to present-day aerosols. All models carried out two sets of simulations: a control experiment with all forcings set to the year 1850 and a perturbation experiment with all forcings identical to the control, except for aerosols with precursor emissions set to the year 2014. In response to the pattern of all aerosols effective radiative forcing (ERF), the fast temperature responses are characterized by cooling over the continental areas, especially in the Northern Hemisphere, with the largest cooling over East Asia and India, sulfate being the dominant aerosol surface temperature driver for present-day emissions. In the Arctic there is a warming signal for winter in the ensemble mean of fast temperature responses, but the model-to-model variability is large, and it is presumably linked to aerosol-induced circulation changes. The largest fast precipitation responses are seen in the tropical belt regions, generally characterized by a reduction over continental regions and presumably a southward shift of the tropical rain belt. This is a characteristic and robust feature among most models in this study, associated with weakening of the monsoon systems around the globe (Asia, Africa and America) in response to hemispherically asymmetric cooling from a Northern Hemisphere aerosol perturbation, forcing possibly the Intertropical Convergence Zone (ITCZ) and tropical precipitation to shift away from the cooled hemisphere despite that aerosols' effects on temperature and precipitation are only partly realized in these simulations as the sea surface temperatures are kept fixed. An interesting feature in aerosol-induced circulation changes is a characteristic dipole pattern with intensification of the Icelandic Low and an anticyclonic anomaly over southeastern Europe, inducing warm air advection towards the northern polar latitudes in winter.


2018 ◽  
Vol 10 (9) ◽  
pp. 3043 ◽  
Author(s):  
Jang Sung ◽  
Eun-Sung Chung ◽  
Shamsuddin Shahid

This study developed a Reliability–Resiliency–Vulnerability (R–R–V) approach that aggregates the frequency, duration, and severity of droughts estimated using the Standardized Precipitation Evapotranspiration Index (SPEI). This approach was used to analyze the characteristics of droughts for the current (1976–2005) and the future (2010–2099) climates. The future climate data obtained from 28 general circulation models (GCMs) of Coupled Model Intercomparison Project Phase 5 (CMIP5) was divided into three general periods: Future 1: 2010–2039, Future 2: 2040–2069; and Future 3: 2070–2099. As a result, aggregation R–R–V representing water availability would increase during Future 1, and then gradually decrease until the end of the century. The frequencies of future drought events for Future 2 and Future 3 were similar to the current frequency, while the durations will be longer and the severity will be higher at most locations during Future 3. Thus, the mean of R–R–V over South Korea is expected to decrease, except for Future 1, and the spatial variability of R–R–V is expected to increase. In the end, the changes in the mean and variance of rainfall and temperature would lead to a decrease in the mean and increase in the spatial variation of sustainability in South Korea. This approach and its results can be used to establish a long-term drought strategy for regions where the risk of future drought is expected to increase.


2008 ◽  
Vol 21 (1) ◽  
pp. 3-21 ◽  
Author(s):  
Soon-Il An ◽  
Jong-Seong Kug ◽  
Yoo-Geun Ham ◽  
In-Sik Kang

Abstract The multidecadal modulation of the El Niño–Southern Oscillation (ENSO) due to greenhouse warming has been analyzed herein by means of diagnostics of Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) coupled general circulation models (CGCMs) and the eigenanalysis of a simplified version of an intermediate ENSO model. The response of the global-mean troposphere temperature to increasing greenhouse gases is more likely linear, while the amplitude and period of ENSO fluctuates in a multidecadal time scale. The climate system model outputs suggest that the multidecadal modulation of ENSO is related to the delayed response of the subsurface temperature in the tropical Pacific compared to the response time of the sea surface temperature (SST), which would lead a modulation of the vertical temperature gradient. Furthermore, an eigenanalysis considering only two parameters, the changes in the zonal contrast of the mean background SST and the changes in the vertical contrast between the mean surface and subsurface temperatures in the tropical Pacific, exhibits a good agreement with the CGCM outputs in terms of the multidecadal modulations of the ENSO amplitude and period. In particular, the change in the vertical contrast, that is, change in difference between the subsurface temperature and SST, turns out to be more influential on the ENSO modulation than changes in the mean SST itself.


The thunder-storms referred to in this communication are recorded in a tabular form., arranged according to their dates. In this table are given the date; the hour of the commencement of the storm; the mean height of the barometer to tenths of an inch; whether it is rising, stationary, or falling; the direction of the wind before the storm, during its continuance, and after its cessation; the maximum temperature on the day of the storm and on the day after; the minimum temperature on the night before and on the night after; and general remarks on the storms. This table is followed by remarks on particular storms recorded in it. In conclusion the author gives the results of his observations with reference to the number of storms in each year; the number in each month, with the hours at which they mostly occur in particular months; the number that have occurred with a rising, stationary, or falling barometer; the number in respect to the direction of the wind and of the current in which the storms moved; the number of storms that have occurred at the various heights of the maximum, and also of the minimum thermometer; the number in which the peculiar breeze that suddenly springs up on the commencement of thunder-storms has been well marked; the change in the direction of some of these storms, and indications of rotatory motion; and finally, the different atmospheric phenomena which have accompanied these storms.


2017 ◽  
Vol 56 (9) ◽  
pp. 2393-2409 ◽  
Author(s):  
Rick Lader ◽  
John E. Walsh ◽  
Uma S. Bhatt ◽  
Peter A. Bieniek

AbstractClimate change is expected to alter the frequencies and intensities of at least some types of extreme events. Although Alaska is already experiencing an amplified response to climate change, studies of extreme event occurrences have lagged those for other regions. Forced migration due to coastal erosion, failing infrastructure on thawing permafrost, more severe wildfire seasons, altered ocean chemistry, and an ever-shrinking season for snow and ice are among the most devastating effects, many of which are related to extreme climate events. This study uses regional dynamical downscaling with the Weather Research and Forecasting (WRF) Model to investigate projected twenty-first-century changes of daily maximum temperature, minimum temperature, and precipitation over Alaska. The forcing data used for the downscaling simulations include the European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-Interim; 1981–2010), Geophysical Fluid Dynamics Laboratory Climate Model, version 3 (GFDL CM3), historical (1976–2005), and GFDL CM3 representative concentration pathway 8.5 (RCP8.5; 2006–2100). Observed trends of temperature and sea ice coverage in the Arctic are large, and the present trajectory of global emissions makes a continuation of these trends plausible. The future scenario is bias adjusted using a quantile-mapping procedure. Results indicate an asymmetric warming of climate extremes; namely, cold extremes rise fastest, and the greatest changes occur in winter. Maximum 1- and 5-day precipitation amounts are projected to increase by 53% and 50%, which is larger than the corresponding increases for the contiguous United States. When compared with the historical period, the shifts in temperature and precipitation indicate unprecedented heat and rainfall across Alaska during this century.


2014 ◽  
Vol 6 (2) ◽  
pp. 124 ◽  
Author(s):  
Chongyi E ◽  
Hongchang Hu ◽  
Hong Xie ◽  
Yongjuan Sun

The study of temperature change and its elevation dependency in the source region of the Yangtze River and Yellow River have been insufficient owing to the lack of adequate observation stations and long-term climatic data. In this study five temperature indices of 32 stations from 1961 to 2007 in and near the source region are used. The 32 stations all have experienced significant warming; the warming amplitudes are higher than the mean warming amplitude of the Qinghai-Tibetan plateau. The warming amplitudes and the numbers of stations showing significant warming trends in mean minimum temperature and extreme minimum temperature are higher than that of the mean maximum temperature and extreme maximum temperature. The elevation dependency of climatic warming and the amount of significant warming stations are not obvious; the influence of human activity and urbanization may be higher. The warming amplitudes of 26 stations above 3000 m tend to be uniform, and there is no significant law at 6 stations below 3000 m. On the contrary, the ratio of stations showing significant warming in minimum temperature above 4000 m is far less than that of the stations below 4000 m.


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