scholarly journals Exploring the Sensitivity of the Australian Climate to Regional Land-Cover-Change Scenarios under Increasing CO2 Concentrations and Warmer Temperatures

2006 ◽  
Vol 10 (7) ◽  
pp. 1-27 ◽  
Author(s):  
G. T. Narisma ◽  
A. J. Pitman

Abstract The potential role of the impacts of land-cover changes (LCCs) in the Australian climate is investigated within the context of increasing CO2 concentrations and temperature. Specifically, it is explored if possible scenarios for LCC can moderate or amplify CO2-induced changes in climate over Australia. The January climate of Australia is simulated under three different land-cover-change scenarios using a high-resolution regional climate model. The land-cover-change scenarios include a steady-state land cover that is equivalent to current land cover, a low-reforestation scenario that recovers approximately 25% of the trees replaced by grasslands within the last 200 yr, and a high-reforestation scenario that recovers at least 75% of the deforested regions. The model was driven by boundary conditions taken from transitory climate simulations from a general circulation model that included two climate scenarios based on two projected scenarios of CO2 concentration increase. The results show that reforestation has the potential to reduce the projected increase in Australian temperatures in 2050 and 2100 by as much as 40% and 20%, respectively. This cooling effect, however, is highly localized and occurs only in regions of reforestation. The results therefore hint that the potential of reforestation to moderate the impact of global warming may be significantly limited by the spatial scale of reforestation. In terms of deforestation, results show that any future land clearing can exacerbate the projected warming in certain regions of Australia. Carbon-related variables are also analyzed and results show that changes in net CO2 flux may be influenced more by soil respiration than by photosynthesis. The results herein encourage studies on the inclusion of land-cover-change scenarios in future climate change projection simulations of the Australian climate.

2008 ◽  
Vol 21 (12) ◽  
pp. 2835-2851 ◽  
Author(s):  
Andréa S. Taschetto ◽  
Ilana Wainer

Abstract This work investigates the reproducibility of precipitation simulated with an atmospheric general circulation model (AGCM) forced by subtropical South Atlantic sea surface temperature (SST) anomalies. This represents an important test of the model prior to investigating the impact of SSTs on regional climate. A five-member ensemble run was performed using the National Center for Atmospheric Research (NCAR) Community Climate Model, version 3 (CCM3). The CCM3 was forced by observed monthly SST over the South Atlantic from 20° to 60°S. The SST dataset used is from the Hadley Centre covering the period of September 1949–October 2001; this covers more than 50 yr of simulation. A statistical technique is used to determine the reproducibility in the CCM3 runs and to assess potential predictability in precipitation. Empirical orthogonal function analysis is used to reconstruct the ensemble using the most reproducible forced modes in order to separate the atmospheric response to local SST forcing from its internal variability. Results for reproducibility show a seasonal dependence, with higher values during austral autumn and spring. The spatial distribution of reproducibility shows that the tropical atmosphere is dominated by the underlying SSTs while variations in the subtropical–extratropical regions are primarily driven by internal variability. As such, changes in the South Atlantic convergence zone (SACZ) region are mainly dominated by internal atmospheric variability while the ITCZ has greater external dependence, making it more predictable. The reproducibility distribution reveals increased values after the reconstruction of the ensemble.


10.29007/hd8l ◽  
2018 ◽  
Author(s):  
Mariana Castaneda-Gonzalez ◽  
Annie Poulin ◽  
Rabindranarth Romero-Lopez ◽  
Richard Arsenault ◽  
François Brissette ◽  
...  

This study aims to evaluate the impact of the Canadian Regional Climate Model’s (CRCM) spatial resolution on summer floods simulation. Four different climate simulations issued from the fourth version of the CRCM (two driven by the Canadian General Circulation Model (CGCM) and two driven by the ERA40c reanalysis) are employed. One simulation at 45 km resolution and another one at 15km resolution for each driver were compared on a daily time-step for the 1960-1990 period. These four simulations are used as inputs for two hydrological models of varying complexity (HSAMI and MOHYSE). Each model is calibrated using three different objective functions based on the Kling-Gupta Efficiency criterion (KGE) to target floods. Two seasonal indices are used to evaluate the CRCM outputs: bias (temperature) and relative bias (precipitation). For the streamflow simulations analysis, the seasonal values of KGE and relative bias are used. The results show an impact of spatial resolution on climate model outputs, on streamflow simulation and flood indicators in the hydrological models. However, other elements such as climate model driver and domain size can influence the results, highlighting the need for further research to assess the impact of spatial resolution on summer floods.


Atmosphere ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1543
Author(s):  
Reinhardt Pinzón ◽  
Noriko N. Ishizaki ◽  
Hidetaka Sasaki ◽  
Tosiyuki Nakaegawa

To simulate the current climate, a 20-year integration of a non-hydrostatic regional climate model (NHRCM) with grid spacing of 5 and 2 km (NHRCM05 and NHRCM02, respectively) was nested within the AGCM. The three models did a similarly good job of simulating surface air temperature, and the spatial horizontal resolution did not affect these statistics. NHRCM02 did a good job of reproducing seasonal variations in surface air temperature. NHRCM05 overestimated annual mean precipitation in the western part of Panama and eastern part of the Pacific Ocean. NHRCM05 is responsible for this overestimation because it is not seen in MRI-AGCM. NHRCM02 simulated annual mean precipitation better than NHRCM05, probably due to a convection-permitting model without a convection scheme, such as the Kain and Fritsch scheme. Therefore, the finer horizontal resolution of NHRCM02 did a better job of replicating the current climatological mean geographical distributions and seasonal changes of surface air temperature and precipitation.


2012 ◽  
Vol 25 (20) ◽  
pp. 7083-7099 ◽  
Author(s):  
S. C. Hardiman ◽  
N. Butchart ◽  
T. J. Hinton ◽  
S. M. Osprey ◽  
L. J. Gray

Abstract The importance of using a general circulation model that includes a well-resolved stratosphere for climate simulations, and particularly the influence this has on surface climate, is investigated. High top model simulations are run with the Met Office Unified Model for the Coupled Model Intercomparison Project Phase 5 (CMIP5). These simulations are compared to equivalent simulations run using a low top model differing only in vertical extent and vertical resolution above 15 km. The period 1960–2002 is analyzed and compared to observations and the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis dataset. Long-term climatology, variability, and trends in surface temperature and sea ice, along with the variability of the annular mode index, are found to be insensitive to the addition of a well-resolved stratosphere. The inclusion of a well-resolved stratosphere, however, does improve the impact of atmospheric teleconnections on surface climate, in particular the response to El Niño–Southern Oscillation, the quasi-biennial oscillation, and midwinter stratospheric sudden warmings (i.e., zonal mean wind reversals in the middle stratosphere). Thus, including a well-represented stratosphere could improve climate simulation on intraseasonal to interannual time scales.


2016 ◽  
Vol 7 (3) ◽  
pp. 627-647 ◽  
Author(s):  
Minchao Wu ◽  
Guy Schurgers ◽  
Markku Rummukainen ◽  
Benjamin Smith ◽  
Patrick Samuelsson ◽  
...  

Abstract. Africa has been undergoing significant changes in climate and vegetation in recent decades, and continued changes may be expected over this century. Vegetation cover and composition impose important influences on the regional climate in Africa. Climate-driven changes in vegetation structure and the distribution of forests versus savannah and grassland may feed back to climate via shifts in the surface energy balance, hydrological cycle and resultant effects on surface pressure and larger-scale atmospheric circulation. We used a regional Earth system model incorporating interactive vegetation–atmosphere coupling to investigate the potential role of vegetation-mediated biophysical feedbacks on climate dynamics in Africa in an RCP8.5-based future climate scenario. The model was applied at high resolution (0.44 × 0.44°) for the CORDEX-Africa domain with boundary conditions from the CanESM2 general circulation model. We found that increased tree cover and leaf-area index (LAI) associated with a CO2 and climate-driven increase in net primary productivity, particularly over subtropical savannah areas, not only imposed important local effect on the regional climate by altering surface energy fluxes but also resulted in remote effects over central Africa by modulating the land–ocean temperature contrast, Atlantic Walker circulation and moisture inflow feeding the central African tropical rainforest region with precipitation. The vegetation-mediated feedbacks were in general negative with respect to temperature, dampening the warming trend simulated in the absence of feedbacks, and positive with respect to precipitation, enhancing rainfall reduction over the rainforest areas. Our results highlight the importance of accounting for vegetation–atmosphere interactions in climate projections for tropical and subtropical Africa.


2017 ◽  
Vol 49 (3) ◽  
pp. 893-907 ◽  
Author(s):  
Gonghuan Fang ◽  
Jing Yang ◽  
Yaning Chen ◽  
Zhi Li ◽  
Philippe De Maeyer

Abstract Quantifying the uncertainty sources in assessment of climate change impacts on hydrological processes is helpful for local water management decision-making. This paper investigated the impact of the general circulation model (GCM) structural uncertainty on hydrological processes in the Kaidu River Basin. Outputs of 21 GCMs from the Coupled Model Intercomparison Project Phase 5 (CMIP5) under two representative concentration pathway (RCP) scenarios (i.e., RCP4.5 and RCP8.5), representing future climate change under uncertainty, were first bias-corrected using four precipitation and three temperature methods and then used to force a well-calibrated hydrological model (the Soil and Water Assessment Tool, SWAT) in the study area. Results show that the precipitation will increase by 3.1%–18% and 7.0%–22.5%, the temperature will increase by 2.0 °C–3.3 °C and 4.2 °C–5.5 °C and the streamflow will change by −26% to 3.4% and −38% to −7% under RCP4.5 and RCP8.5, respectively. Timing of snowmelt will shift forward by approximately 1–2 months for both scenarios. Compared to RCPs and bias correction methods, GCM structural uncertainty contributes most to streamflow uncertainty based on the standard deviation method (55.3%) while it is dominant based on the analysis of variance approach (94.1%).


2009 ◽  
Vol 9 (1) ◽  
pp. 1977-2020
Author(s):  
F. Khosrawi ◽  
R. Müller ◽  
M. H. Proffitt ◽  
R. Ruhnke ◽  
O. Kirner ◽  
...  

Abstract. 1-year data sets of monthly averaged nitrous oxide (N2O) and ozone (O3) derived from satellite measurements were used as a tool for the evaluation of atmospheric photochemical models. Two 1-year data sets, one derived from the Improved Limb Atmospheric Spectrometer (ILAS and ILAS-II) and one from the Odin Sub-Millimetre Radiometer (Odin/SMR) were employed. Here, these data sets are used for the evaluation of two Chemical Transport Models (CTMs), the Karlsruhe Simulation Model of the Middle Atmosphere (KASIMA) and the Chemical Lagrangian Model of the Stratosphere (CLaMS) as well as for one Chemistry-Climate Model (CCM), the atmospheric chemistry general circulation model ECHAM5/MESSy1 (E5M1) in the lower stratosphere with focus on the Northern Hemisphere. Since the Odin/SMR measurements cover the entire hemisphere, the evaluation is performed for the entire hemisphere as well as for the low latitudes, midlatitudes and high latitudes using the Odin/SMR 1-year data set as reference. To assess the impact of using different data sets for such an evaluation study we repeat the evaluation for the polar lower stratosphere using the ILAS/ILAS-II data set. Only small differences were found using ILAS/ILAS-II instead of Odin/SMR as a reference, thus, showing that the results are not influenced by the particular satellite data set used for the evaluation. The evaluation of CLaMS, KASIMA and E5M1 shows that all models are in good agreement with Odin/SMR and ILAS/ILAS-II. Differences are generally in the range of ±20%. Larger differences (up to −40%) are found in all models at 500±25 K for N2O mixing ratios greater than 200 ppb. Generally, the largest differences were found for the tropics and the lowest for the polar regions. However, an underestimation of polar winter ozone loss was found both in KASIMA and E5M1 both in the Northern and Southern Hemisphere.


2021 ◽  
Vol 17 (4) ◽  
pp. 1685-1699
Author(s):  
Marcus Breil ◽  
Emanuel Christner ◽  
Alexandre Cauquoin ◽  
Martin Werner ◽  
Melanie Karremann ◽  
...  

Abstract. In order to investigate the impact of spatial resolution on the discrepancy between simulated δ18O and observed δ18O in Greenland ice cores, regional climate simulations are performed with the isotope-enabled regional climate model (RCM) COSMO_iso. For this purpose, isotope-enabled general circulation model (GCM) simulations with the ECHAM5-wiso general circulation model (GCM) under present-day conditions and the MPI-ESM-wiso GCM under mid-Holocene conditions are dynamically downscaled with COSMO_iso for the Arctic region. The capability of COSMO_iso to reproduce observed isotopic ratios in Greenland ice cores for these two periods is investigated by comparing the simulation results to measured δ18O ratios from snow pit samples, Global Network of Isotopes in Precipitation (GNIP) stations and ice cores. To our knowledge, this is the first time that a mid-Holocene isotope-enabled RCM simulation is performed for the Arctic region. Under present-day conditions, a dynamical downscaling of ECHAM5-wiso (1.1∘×1.1∘) with COSMO_iso to a spatial resolution of 50 km improves the agreement with the measured δ18O ratios for 14 of 19 observational data sets. A further increase in the spatial resolution to 7 km does not yield substantial improvements except for the coastal areas with its complex terrain. For the mid-Holocene, a fully coupled MPI-ESM-wiso time slice simulation is downscaled with COSMO_iso to a spatial resolution of 50 km. In the mid-Holocene, MPI-ESM-wiso already agrees well with observations in Greenland and a downscaling with COSMO_iso does not further improve the model–data agreement. Despite this lack of improvement in model biases, the study shows that in both periods, observed δ18O values at measurement sites constitute isotope ratios which are mainly within the subgrid-scale variability of the global ECHAM5-wiso and MPI-ESM-wiso simulation results. The correct δ18O ratios are consequently not resolved in the GCM simulation results and need to be extracted by a refinement with an RCM. In this context, the RCM simulations provide a spatial δ18O distribution by which the effects of local uncertainties can be taken into account in the comparison between point measurements and model outputs. Thus, an isotope-enabled GCM–RCM model chain with realistically implemented fractionating processes constitutes a useful supplement to reconstruct regional paleo-climate conditions during the mid-Holocene in Greenland. Such model chains might also be applied to reveal the full potential of GCMs in other regions and climate periods, in which large deviations relative to observed isotope ratios are simulated.


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