Climate change and water resources in arid regions : uncertainty of the baseline time period

Recent climate change studies have given a lot of attention to the uncertainty that stems from general circulation models (GCM), greenhouse gas emission scenarios, hydrological models and downscaling approaches. Yet, the uncertainty that stems from the selection of the baseline period has not been studied. Accordingly, the main research question is as follows: What would be the differences and/or the similarities in the evaluation of climate change impacts between the GCM and the delta perturbation scenarios using different baseline periods? This article addresses this issue through comparison of the results of two different baseline periods, investigating the uncertainties in evaluating climate change impact on the hydrological characteristics of arid regions. The Lower Zab River Basin (Northern Iraq) has been selected as a representative case study. The research outcomes show that the considered baseline periods suggest increases and decreases in the temperature and precipitation (P), respectively, over the 2020, 2050 and 2080 periods. The two climatic scenarios are likely to lead to similar reductions in the reservoir mean monthly flows, and subsequently, their maximum discharge is approximately identical. The predicted reduction in the inflow for the 2080–2099 time period fluctuates between 31 and 49% based on SRA1B and SRA2 scenarios, respectively. The delta perturbation scenario permits the sensitivity of the climatic models to be clearly determined compared to the GCM. The former allows for a wide variety of likely climate change scenarios at the regional level and are easier to generate and apply so that they could complement the latter

Radiative forcing by well-mixed greenhouse gases: Estimates from climate models in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4)

The radiative effects from increased concentrations of well-mixed greenhouse gases (WMGHGs) represent the most significant and best understood anthropogenic forcing of the climate system. The most comprehensive tools for simulating past and future climates influenced by WMGHGs are fully coupled atmosphere-ocean general circulation models (AOGCMs). Because of the importance of WMGHGs as forcing agents it is essential that AOGCMs compute the radiative forcing by these gases as accurately as possible. We present the results of a radiative transfer model intercomparison between the forcings computed by the radiative parameterizations of AOGCMs and by benchmark line-by-line (LBL) codes. The comparison is focused on forcing by CO2, CH4, N2O, CFC-11, CFC-12, and the increased H2O expected in warmer climates. The models included in the intercomparison include several LBL codes and most of the global models submitted to the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4). In general, the LBL models are in excellent agreement with each other. However, in many cases, there are substantial discrepancies among the AOGCMs and between the AOGCMs and LBL codes. In some cases this is because the AOGCMs neglect particular absorbers, in particular the near-infrared effects of CH4 and N2O, while in others it is due to the methods for modeling the radiative processes. The biases in the AOGCM forcings are generally largest at the surface level. We quantify these differences and discuss the implications for interpreting variations in forcing and response across the multimodel ensemble of AOGCM simulations assembled for the IPCC AR4

AGCM simulations of intraseasonal variability associated with the Asian summer monsoon

The intraseasonal variability associated with the Asian summer monsoon as simulated by a number of atmospheric general circulation models (AGCMs) are analyzed and assessed against observations. The model data comes from the Monsoon GCM Intercomparison project initiated by the CLIVAR/Asian-Australian Monsoon Panel. Ten GCM groups, i.e., the Center for Ocean-Land-Atmosphere Studies (COLA), Institute of Numerical Mathematics (DNM), Goddard Space Flight Center (GSFC), Geophysical Fluid Dynamics Laboratory (GFDL), Institute of Atmospheric Physics (IAP), Indian Institute of Tropical Meteorology (IITM), Meteorological Research Institute (MRI), National Center for Atmospheric Research (NCAR), Seoul National University (SNU), and the State University of New York (SUNY), participated in the intraseasonal component of the project. Each performed a set of 10 ensemble simulations for 1 September 1996-31 August 1998 using the same observed weekly SST values but with different initial conditions. The focus is on the spatial and seasonal variations associated with intraseasonal variability (ISV) of rainfall, the structure of each model's principal mode of spatial-temporal variation of rainfall [i.e. their depiction of the Intraseasonal Oscillation (ISO)], the teleconnection patterns associated with each model's ISO, and the implications of the models' ISV on seasonal monsoon predictability. The results show that several of the models exhibit ISV levels at or above that found in observations with spatial patterns of ISV that resemble the observed pattern. This includes a number of rather detailed features, including the relative distribution of variability between ocean and land regions. In terms of the area-averaged variance, it is found that the fidelity of a model to represent NH summer versus winter ISV appears to be strongly linked. In addition, most models' ISO patterns do exhibit some form of northeastward propagation. However, the model ISO patterns are typically less coherent, lack sufficient eastward propagation, and have smaller zonal and meridional spatial scales than the observed patterns, and are often limited to one side or the other of the maritime continent. The most pervasive and problematic feature of the models' depiction of ISV and/or their ISO patterns is the overall lack of variability in the equatorial Indian Ocean. In some cases, this characteristic appears to result from some models forming double convergence zones about the equator rather than one region of strong convergence on the equator. This shortcoming results in a poor representation of the local rainfall pattern and also significantly influences the models' representations of the global-scale teleconnection patterns associated with the ISO. Finally, analysis of the model ensemble shows a positive relationship between the strength of a model's ISV of rainfall and its intra-ensemble variability of seasonal monsoon rainfall. The implications of this latter relation are discussed in the context of seasonal monsoon predictability.close12111