scholarly journals Interannual variability of rainfall over the Arabian Peninsula using the IPCC AR4 Global Climate Models

2012 ◽  
Vol 33 (10) ◽  
pp. 2328-2340 ◽  
Author(s):  
Mansour Almazroui ◽  
M. Adnan Abid ◽  
H. Athar ◽  
M. Nazrul Islam ◽  
M. Azhar Ehsan
Keyword(s):  
Interannual Variability ◽  
Climate Models ◽  
Arabian Peninsula ◽  
Global Climate ◽  
Global Climate Models ◽  
Ipcc Ar4

scholarly journals Performance of CMIP3 and CMIP5 GCMs to Simulate Observed Rainfall Characteristics over the Western Himalayan Region

2017 ◽  
Vol 30 (19) ◽  
pp. 7777-7799 ◽  
Author(s):  
Jitendra Kumar Meher ◽  
Lalu Das ◽  
Javed Akhter ◽  
Rasmus E. Benestad ◽  
Abdelkader Mezghani
Keyword(s):  
Interannual Variability ◽  
Annual Cycle ◽  
Climate Models ◽  
Global Climate ◽  
India Meteorological Department ◽  
Rain Gauge ◽  
Global Climate Models ◽  
Himalayan Region ◽  
Western Himalayan Region ◽  
Cmip5 Gcms

Abstract The western Himalayan region (WHR) was subject to a significant negative trend in the annual and monsoon rainfall during 1902–2005. Annual and seasonal rainfall change over the WHR of India was estimated using 22 rain gauge station rainfall data from the India Meteorological Department. The performance of 13 global climate models (GCMs) from phase 3 of the Coupled Model Intercomparison Project (CMIP3) and 42 GCMs from CMIP5 was evaluated through multiple analysis: the evaluation of the mean annual cycle, annual cycles of interannual variability, spatial patterns, trends, and signal-to-noise ratio. In general, CMIP5 GCMs were more skillful in terms of simulating the annual cycle of interannual variability compared to CMIP3 GCMs. The CMIP3 GCMs failed to reproduce the observed trend, whereas approximately 50% of the CMIP5 GCMs reproduced the statistical distribution of short-term (30 yr) trend estimates than for the longer-term (99 yr) trends from CMIP5 GCMs. GCMs from both CMIP3 and CMIP5 were able to simulate the spatial distribution of observed rainfall in premonsoon and winter months. Based on performance, each model of CMIP3 and CMIP5 was given an overall rank, which puts the high-resolution version of the MIROC3.2 model [MIROC3.2 (hires)] and MIROC5 at the top in CMIP3 and CMIP5, respectively. Robustness of the ranking was judged through a sensitivity analysis, which indicated that ranks were independent during the process of adding or removing any individual method. It also revealed that trend analysis was not a robust method of judging performances of the models as compared to other methods.

scholarly journals Assessing the robustness and uncertainties of projected changes in temperature and precipitation in AR5 Global Climate Models over the Arabian Peninsula

2017 ◽  
Vol 194 ◽  
pp. 202-213 ◽  
Author(s):  
Mansour Almazroui ◽  
M. Nazrul Islam ◽  
Fahad Saeed ◽  
Abdulrahman K. Alkhalaf ◽  
Ramzah Dambul
Keyword(s):  
Climate Models ◽  
Arabian Peninsula ◽  
Global Climate ◽  
Global Climate Models ◽  
Temperature And Precipitation ◽  
Projected Changes

Simulations of 20th and 21st century Arctic cloud amount in the global climate models assessed in the IPCC AR4

2008 ◽  
Vol 33 (7-8) ◽  
pp. 1099-1115 ◽  
Author(s):  
Steve Vavrus ◽  
Duane Waliser ◽  
Axel Schweiger ◽  
Jennifer Francis
Keyword(s):  
21St Century ◽  
Climate Models ◽  
Global Climate ◽  
Cloud Amount ◽  
Global Climate Models ◽  
Ipcc Ar4

scholarly journals Improvement of ENSO Simulation Based on Intermodel Diversity

2015 ◽  
Vol 28 (3) ◽  
pp. 998-1015 ◽  
Author(s):  
Yoo-Geun Ham ◽  
Jong-Seong Kug
Keyword(s):  
Interannual Variability ◽  
El Niño ◽  
Climate Models ◽  
El Nino ◽  
Southern Oscillation ◽  
Global Climate ◽  
Coupled Model ◽  
Global Climate Models ◽  
Climate Simulation ◽  
Central Pacific

Abstract In this study, a new methodology is developed to improve the climate simulation of state-of-the-art coupled global climate models (GCMs), by a postprocessing based on the intermodel diversity. Based on the close connection between the interannual variability and climatological states, the distinctive relation between the intermodel diversity of the interannual variability and that of the basic state is found. Based on this relation, the simulated interannual variabilities can be improved, by correcting their climatological bias. To test this methodology, the dominant intermodel difference in precipitation responses during El Niño–Southern Oscillation (ENSO) is investigated, and its relationship with climatological state. It is found that the dominant intermodel diversity of the ENSO precipitation in phase 5 of the Coupled Model Intercomparison Project (CMIP5) is associated with the zonal shift of the positive precipitation center during El Niño. This dominant intermodel difference is significantly correlated with the basic states. The models with wetter (dryer) climatology than the climatology of the multimodel ensemble (MME) over the central Pacific tend to shift positive ENSO precipitation anomalies to the east (west). Based on the model’s systematic errors in atmospheric ENSO response and bias, the models with better climatological state tend to simulate more realistic atmospheric ENSO responses. Therefore, the statistical method to correct the ENSO response mostly improves the ENSO response. After the statistical correction, simulating quality of the MME ENSO precipitation is distinctively improved. These results provide a possibility that the present methodology can be also applied to improving climate projection and seasonal climate prediction.

scholarly journals Characteristics and Scenarios Projection of Climate Change on the Tibetan Plateau

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Zhenchun Hao ◽  
Qin Ju ◽  
Weijuan Jiang ◽  
Changjun Zhu
Keyword(s):  
Climate Change ◽  
Tibetan Plateau ◽  
Climate Models ◽  
Global Climate ◽  
Surface Air Temperature ◽  
Global Climate Models ◽  
The Tibetan Plateau ◽  
Intergovernmental Panel ◽  
Temperature And Precipitation ◽  
Ipcc Ar4

The Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR4) presents twenty-two global climate models (GCMs). In this paper, we evaluate the ability of 22 GCMs to reproduce temperature and precipitation over the Tibetan Plateau by comparing with ground observations for 1961~1900. The results suggest that all the GCMs underestimate surface air temperature and most models overestimate precipitation in most regions on the Tibetan Plateau. Only a few models (each 5 models for precipitation and temperature) appear roughly consistent with the observations in annual temperature and precipitation variations. Comparatively, GFCM21 and CGMR are able to better reproduce the observed annual temperature and precipitation variability over the Tibetan Plateau. Although the scenarios predicted by the GCMs vary greatly, all the models predict consistently increasing trends in temperature and precipitation in most regions in the Tibetan Plateau in the next 90 years. The results suggest that the temperature and precipitation will both increase in all three periods under different scenarios, with scenario A1 increasing the most and scenario A1B increasing the least.

scholarly journals Net irrigation requirement under different climate scenarios using AquaCrop over Europe

2022 ◽  
Author(s):  
Louise Busschaert ◽  
Shannon de Roos ◽  
Wim Thiery ◽  
Dirk Raes ◽  
Gabriëlle J. M. De Lannoy
Keyword(s):  
Climate Change ◽  
Soil Moisture ◽  
Interannual Variability ◽  
Climate Models ◽  
Global Climate ◽  
Crop Productivity ◽  
Global Climate Models ◽  
Irrigation Requirement ◽  
Aquacrop Model ◽  
Far Future

Abstract. Global soil water availability is challenged by the effects of climate change and a growing population. On average 70 % of freshwater extraction is attributed to agriculture, and the demand is increasing. In this study, the effects of climate change on the evolution of the irrigation water requirement to sustain current crop productivity are assessed by using the FAO crop growth model AquaCrop version 6.1. The model is run at 0.5° lat × 0.5° lon resolution over the European mainland, assuming a general C3-type of crop, and forced by climate input data from the Inter-Sectoral Impact Model Intercomparison Project phase three (ISIMIP3). First, the performance of AquaCrop surface soil moisture (SSM) simulations using historical meteorological input from two ISIMIP3 forcing datasets is evaluated with satellite-based SSM estimates. When driven by ISIMIP3a reanalysis meteorology for the years 2011–2016, daily simulated SSM values have an unbiased root-mean-square difference of 0.08 and 0.06 m3m−3 with SSM retrievals from the Soil Moisture Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) missions, respectively. When forced with ISIMIP3b meteorology from five Global Climate Models (GCM) for the years 2011–2020, the historical simulated SSM climatology closely agrees with the climatology of the reanalysis-driven AquaCrop SSM climatology as well as the satellite-based SSM climatologies. Second, the evaluated AquaCrop model is run to quantify the future irrigation requirement, for an ensemble of five GCMs and three different emission scenarios. The simulated net irrigation requirement (Inet) of the three summer months for a near and far future climate period (2031–2060 and 2071–2100) is compared to the baseline period of 1985–2014, to assess changes in the mean and interannual variability of the irrigation demand. Averaged over the continent and the model ensemble, the far future Inet is expected to increase by 67 mm year–1 (+30 %) under a high emission scenario Shared Socioeconomic Pathway (SSP) 3-7.0. Central and southern Europe are the most impacted with larger Inet increases. The interannual variability of Inet is likely to increase in northern and central Europe, whereas the variability is expected to decrease in southern regions. Under a high mitigation scenario (SSP1-2.6), the increase in Inet will stabilize around 40 mm year–1 towards the end of the century and interannual variability will still increase but to a smaller extent. The results emphasize a large uncertainty in the Inet projected by various GCMs.

scholarly journals Increased Interannual Precipitation Extremes over California under Climate Change

2015 ◽  
Vol 28 (16) ◽  
pp. 6324-6334 ◽  
Author(s):  
Neil Berg ◽  
Alex Hall
Keyword(s):  
Interannual Variability ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
First Century ◽  
Precipitation Extremes ◽  
Wet Season ◽  
Precipitation Total ◽  
The Mean ◽  
Projected Changes

Abstract Changes to mean and extreme wet season precipitation over California on interannual time scales are analyzed using twenty-first-century precipitation data from 34 global climate models. Models disagree on the sign of projected changes in mean precipitation, although in most models the change is very small compared to historical and simulated levels of interannual variability. For the 2020/21–2059/60 period, there is no projected increase in the frequency of extremely dry wet seasons in the ensemble mean. Wet extremes are found to increase to around 2 times the historical frequency, which is statistically significant at the 95% level. Stronger signals emerge in the 2060/61–2099/2100 period. Across all models, extremely dry wet seasons are roughly 1.5 to 2 times more common, and wet extremes generally triple in their historical frequency (statistically significant). Large increases in precipitation variability in most models account for the modest increases to dry extremes. Increases in the frequency of wet extremes can be ascribed to equal contributions from increased variability and increases to the mean. These increases in the frequency of interannual precipitation extremes will create severe water management problems in a region where coping with large interannual variability in precipitation is already a challenge. Evidence from models and observations is examined to understand the causes of the low precipitation associated with the 2013/14 drought in California. These lines of evidence all strongly indicate that the low 2013/14 wet season precipitation total can be very likely attributed to natural variability, in spite of the projected future changes in extremes.

scholarly journals Performance Evaluation of Global Climate Models (MCGs) from the IPCC-AR4, in climatic data simulation of air temperature and pluviometric precipitation for South America

2020 ◽  
Vol 6 (5) ◽  
pp. 31241-31260
Author(s):  
Fábio da Silveira Castro ◽  
Alexandre Cândido Xavier ◽  
Roberto Avelino Cecílio ◽  
Luciano Roncetti Pimenta ◽  
Valéria Hollunder Klippel ◽  
...  
Keyword(s):  
Performance Evaluation ◽  
South America ◽  
Air Temperature ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Climatic Data ◽  
Data Simulation ◽  
Ipcc Ar4
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