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

Cloud radiative effect on tropical troposphere to stratosphere transport represented in a large‐scale model

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95019/1/grl25189.pd

A moist benchmark calculation for atmospheric general circulation models

A benchmark calculation is designed to compare the climate and climate sensitivity of atmospheric general circulation models (AGCMs). The experimental setup basically follows that of the aquaplanet experiment (APE) proposed by Neale and Hoskins, but a simple mixed layer ocean is embedded to enable air-sea coupling and the prediction of surface temperature. In calculations with several AGCMs, this idealization produces very strong zonal-mean flow and exaggerated ITCZ strength, but the model simulations remain sufficiently realistic to justify the use of this framework in isolating key differences between models. Because surface temperatures are free to respond to model differences, the simulation of the cloud distribution, especially in the subtropics, affects many other aspects of the simulations. The analysis of the simulated tropical transients highlights the importance of convection inhibition and air-sea coupling as affected by the depth of the mixed layer. These preliminary comparisons demonstrate that this idealized benchmark provides a discriminating framework for understanding the implications of differing physics parameterization in AGCMs.open101

The spectral dimension of longwave feedback in the CMIP3 and CMIP5 experiments

Radiative feedback is normally discussed in terms of the change of broadband flux. Yet it has an intrinsic dimension of spectrum. A set of longwave (LW) spectral radiative kernels (SRKs) is constructed and validated in a similar way as the broadband radiative kernel. The LW broadband feedback derived using this SRK are consistent with those from the broadband radiative kernels. As an application, the SRK is applied to 12 general circulation models (GCMs) from the Coupled Model Intercomparison Project Phase 3 and 12 GCMs from the Coupled Model Intercomparison Project Phase 5 simulations to derive the spectrally resolved Planck, lapse rate, and LW water vapor feedback. The spectral details of the Planck feedback from different GCMs are essentially the same, but the lapse rate and LW water vapor feedback do reveal spectrally dependent difference among GCMs. Spatial distributions of the feedback at different spectral regions are also discussed. The spectral feedback analysis provides us another dimension to understand and evaluate the modeled radiative feedback. Key Points Spectral radiative kernel is developed and validated to get spectral feedback Lapse rate and water vapor feedback have different spectral dependence Spectral kernel provides new information not available from broadband studiesPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/110043/1/grl52334.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/110043/2/grl52334-sup-0001-readme.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/110043/3/grl52334-sup-0002-Auxiliary_material.pd

Comparison of regime‐sorted tropical cloud profiles observed by CloudSat with GEOS5 analyses and two general circulation model simulations

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/94863/1/jgrd16832.pd

Impact of ENSO longitudinal position on teleconnections to the NAO

While significant improvements have been made in understanding how the El Niño–Southern Oscillation (ENSO) impacts both North American and Asian climate, its relationship with the North Atlantic Oscillation (NAO) remains less clear. Observations indicate that ENSO exhibits a highly complex relationship with the NAO-associated atmospheric circulation. One critical contribution to this ambiguous ENSO/NAO relationship originates from ENSO’s diversity in its spatial structure. In general, both eastern (EP) and central Pacific (CP) El Niño events tend to be accompanied by a negative NAO-like atmospheric response. However, for two different types of La Niña the NAO response is almost opposite. Thus, the NAO responses for the CP ENSO are mostly linear, while nonlinear NAO responses dominate for the EP ENSO. These contrasting extra-tropical atmospheric responses are mainly attributed to nonlinear air-sea interactions in the tropical eastern Pacific. The local atmospheric response to the CP ENSO sea surface temperature (SST) anomalies is highly linear since the air-sea action center is located within the Pacific warm pool, characterized by relatively high climatological SSTs. In contrast, the EP ENSO SST anomalies are located in an area of relatively low climatological SSTs in the eastern equatorial Pacific. Here only sufficiently high positive SST anomalies during EP El Niño events are able to overcome the SST threshold for deep convection, while hardly any anomalous convection is associated with EP La Niña SSTs that are below this threshold. This ENSO/NAO relationship has important implications for NAO seasonal prediction and places a higher requirement on models in reproducing the full diversity of ENSO

Characterizing the tropospheric ozone response to methane emission controls and the benefits to climate and air quality

Reducing methane (CH4) emissions is an attractive option for jointly addressing climate and ozone (O3) air quality goals. With multidecadal full-chemistry transient simulations in the MOZART-2 tropospheric chemistry model, we show that tropospheric O3 responds approximately linearly to changes in CH4 emissions over a range of anthropogenic emissions from 0–430 Tg CH4 a−1 (0.11–0.16 Tg tropospheric O3 or ∼11–15 ppt global mean surface O3 decrease per Tg a−1 CH4 reduced). We find that neither the air quality nor climate benefits depend strongly on the location of the CH4 emission reductions, implying that the lowest cost emission controls can be targeted. With a series of future (2005–2030) transient simulations, we demonstrate that cost-effective CH4 controls would offset the positive climate forcing from CH4 and O3 that would otherwise occur (from increases in NOx and CH4 emissions in the baseline scenario) and improve O3 air quality. We estimate that anthropogenic CH4 contributes 0.7 Wm−2 to climate forcing and ∼4 ppb to surface O3 in 2030 under the baseline scenario. Although the response of surface O3 to CH4 is relatively uniform spatially compared to that from other O3 precursors, it is strongest in regions where surface air mixes frequently with the free troposphere and where the local O3 formation regime is NOx-saturated. In the model, CH4 oxidation within the boundary layer (below ∼2.5 km) contributes more to surface O3 than CH4 oxidation in the free troposphere. In NOx-saturated regions, the surface O3 sensitivity to CH4 can be twice that of the global mean, with >70% of this sensitivity resulting from boundary layer oxidation of CH4. Accurately representing the NOx distribution is thus crucial for quantifying the O3 sensitivity to CH4

Interannual variations in precipitation: the effect of the North Atlantic and Southern oscillations as seen in a satellite precipitation data set and in models

Precipitation is a parameter that varies on many different spatial and temporal scales. Here we look at interannual variations associated with the North Atlantic Oscillation (NAO) and the Southern Oscillation (SO), comparing the spatial and temporal changes as shown by three data sets. The Global Precipitation Climatology Project (GPCP) product is based upon satellite data, whereas both the National Centers for Environmental Prediction (NCEP) and European Centre for Medium-Range Weather Forecasts (ECMWF) climatologies are produced through reanalysis of atmospheric circulation models. All three products show a consistent response to the NAO in the North Atlantic region, with negative states of the NAO corresponding to increases in precipitation over Greenland and southern Europe, but to a decrease over northern Europe. None of the climatologies display any net change in total rainfall as a result of the NAO, but rather a redistribution of precipitation patterns. However, this redistribution of rain is important because of its potential effect on oceanic overturning circulation. Similarly, all three data sets concur that the SO has a major effect on precipitation in certain tropical regions; however, there is some disagreement amongst the data sets as to the regional sensitivity, with NCEP showing a much weaker response than GPCP and ECMWF over Indonesia. The GPCP and NCEP climatologies show that the various phases of El Niño and La Niña act to redistribute, rather than enhance, the freshwater cycle. Given that the models incorporate no actual observations of rain, and are known to be imperfect, it is surprising how well they represent these interannual phenomena

On the contribution of local feedback mechanisms to the range of climate sensitivity in two GCM ensembles

Global and local feedback analysis techniques have been applied to two ensembles of mixed layer equilibrium CO 2 doubling climate change experiments, from the CFMIP (Cloud Feedback Model Intercomparison Project) and QUMP (Quantifying Uncertainty in Model Predictions) projects. Neither of these new ensembles shows evidence of a statistically significant change in the ensemble mean or variance in global mean climate sensitivity when compared with the results from the mixed layer models quoted in the Third Assessment Report of the IPCC. Global mean feedback analysis of these two ensembles confirms the large contribution made by inter-model differences in cloud feedbacks to those in climate sensitivity in earlier studies; net cloud feedbacks are responsible for 66% of the inter-model variance in the total feedback in the CFMIP ensemble and 85% in the QUMP ensemble. The ensemble mean global feedback components are all statistically indistinguishable between the two ensembles, except for the clear-sky shortwave feedback which is stronger in the CFMIP ensemble. While ensemble variances of the shortwave cloud feedback and both clear-sky feedback terms are larger in CFMIP, there is considerable overlap in the cloud feedback ranges; QUMP spans 80% or more of the CFMIP ranges in longwave and shortwave cloud feedback. We introduce a local cloud feedback classification system which distinguishes different types of cloud feedbacks on the basis of the relative strengths of their longwave and shortwave components, and interpret these in terms of responses of different cloud types diagnosed by the International Satellite Cloud Climatology Project simulator. In the CFMIP ensemble, areas where low-top cloud changes constitute the largest cloud response are responsible for 59% of the contribution from cloud feedback to the variance in the total feedback. A similar figure is found for the QUMP ensemble. Areas of positive low cloud feedback (associated with reductions in low level cloud amount) contribute most to this figure in the CFMIP ensemble, while areas of negative cloud feedback (associated with increases in low level cloud amount and optical thickness) contribute most in QUMP. Classes associated with high-top cloud feedbacks are responsible for 33 and 20% of the cloud feedback contribution in CFMIP and QUMP, respectively, while classes where no particular cloud type stands out are responsible for 8 and 21%.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45863/1/382_2006_Article_111.pd