Division Of Atmospheric Research Limited Area Model Research Articles

Climate change and the genus <i>Rhipicephalus</i> (Acari : Ixodidae) in Africa

The suitability of present and future climates for 30 Rhipicephalus species in Africa are predicted using a simple climate envelope model as well as a Division of Atmospheric Research Limited-Area Model (DARLAM). DARLAM's predictions are compared with the mean outcome from two global circulation models. East Africa and South Africa are considered the most vulnerable regions on the continent to climate-induced changes in tick distributions and tick-borne diseases. More than 50% of the species examined show potential range expansion and more than 70% of this range expansion is found in economically important tick species. More than 20% of the species experienced range shifts of between 50 and 100%. There is also an increase in tick species richness in the south-western regions of the sub-continent. Actual range alterations due to climate change may be even greater since factors like land degradation and human population increase have not been included in this modelling process. However, these predictions are also subject to the effect that climate change may have on the hosts of the ticks, particularly those that favour a restricted range of hosts. Where possible, the anticipated biological implications of the predicted changes are explored.

Simulating tick distributions over sub‐Saharan Africa: the use of observed and simulated climate surfaces

AbstractAim A broad suit of climate data sets is becoming available for use in predictive species modelling. We compare the efficacy of using interpolated climate surfaces [Center for Resource and Environmental Studies (CRES) and Climate Research Unit (CRU)] or high‐resolution model‐derived climate data [Division of Atmospheric Research limited‐area model (DARLAM)] for predictive species modelling, using tick distributions from sub‐Saharan Africa.Location The analysis is restricted to sub‐Saharan Africa. The study area was subdivided into 3000 grids cells with a resolution of 60 × 60 km.Methods Species distributions were predicted using an established multivariate climate envelope modelling approach and three very different climate data sets. The recorded variance in the climate data sets was quantified by employing omnidirectional variograms. To further compare the interpolated tick distributions that flowed from using three climate data sets, we calculated true positive (TP) predictions, false negative (FN) predictions as well as the proportional overlaps between observed and modelled tick distributions. In addition, the effect of tick data set size on the performance of the climate data sets was evaluated by performing random draws of known tick distribution records without replacement.Results The predicted distributions were consistently wider ranging than the known records when using any of the three climate data sets. However, the proportional overlap between predicted and known distributions varied as follows: for Rhipicephalus appendiculatus Neumann (Acari: Ixodidae), these were 60%, 60% and 70%; for Rhipicephalus longus Neumann (Acari: Ixodidae) 60%, 57% and 75%; for Rhipicephalus zambeziensis Walker, Norval & Corwin (Acari: Ixodidae) 57%, 51% and 62%, and for Rhipicephalus capensis Koch (Acari: Ixodidae) 70%, 60% and 60% using the CRES, CRU and DARLAM climate data sets, respectively. All data sets were sensitive to data size but DARLAM performed better when using smaller species data sets. At a 20% data subsample level, DARLAM was able to capture more than 50% of the known records and captured more than 60% of known records at higher subsample levels.Main conclusions The use of data derived from high‐resolution nested climate models (e.g. DARLAM) provided equal or even better species distribution modelling performance. As the model is dynamic and process based, the output data are available at the modelled resolution, and are not hamstrung by the sampling intensity of observed climate data sets (c. one sample per 30,000 km2 for Africa). In addition, when exploring the biodiversity consequences of climate change, these modelled outputs form a more useful basis for comparison with modelled future climate scenarios.

Application of DARLAM to Regional Haze Modeling

— The CSIRO Division of Atmospheric Research limited area model (DARLAM) is applied to atmospheric transport modeling of haze in southeast Asia. The 1998 haze episode is simulated using an emission inventory derived from hotspot information and adopting removal processes based on SO2.¶Results show that the model is able to simulate the transport of haze in the region. The model images closely resemble the plumes of NASA Total Ozone Mapping Spectrometer and Meteorological Service Singapore haze maps. Despite the limitation of input data, particularly for haze emissions, the three-month average pattern correlation obtained for the whole episode is 0.61. The model has also been able to reproduce the general features of transboundary air pollution over a long period of time. Predicted total particulate matter concentration also agrees reasonably well with observation.¶The difference in the model results from the satellite images may be attributed to the large uncertainties of emission, simplification of haze deposition and transformation mechanisms and the relatively coarse horizontal and vertical resolution adopted for this particular simulation.

January and July regional climate simulation over South America

This work presents results, over the South American region, from the CSIRO Division of Atmospheric Research limited area model (DARLAM) and from the nine‐level general circulation model (GCM) of CSIRO (CSIRO Mk 2), within which it was nested in a one‐way mode. Ten separate 30‐day DARLAM simulations were performed for both January and July with a resolution of 125 km and were averaged to obtain a climatology for those months. This paper presents for the first time simulations of the January South American climate using a limited area model; previous similar studies simulated only the July climate. The goal of this study was to examine the capability of the CSIRO Mk 2 ‐ DARLAM nested modeling system for simulating the climate in the South American region. Further, it was desired to investigate whether the higher resolution of DARLAM improves the simulated climate over various subregions, compared with the GCM and observations. With this purpose, a representative set of variables was analyzed and statistically compared. Overall, the fields simulated by the nesting system provide a better representation of the South American climate than the GCM. In particular, significant improvements are found in the nested model climatology for near‐surface temperature and mean sea level pressure. Comparison of the January and July simulations shows a better wintertime performance. Some significant summertime features, like the Bolivian High, are reasonably well simulated by DARLAM, but not by the GCM.

January and July climate simulations over the SADC region using the limited-area model DARLAM

High-resolution climate simulations of near-surface variables are presented for January and July over the Southern African Developing Countries (SADC) region using the CSIRO Division of Atmospheric Research Limited-Area Model (DARLAM) nested within a General Circulation Model (GCM). The model domain includes tropical (north and south of the equator) and subtropical (Southern Africa) regions. Objective measures of skill are used to assess the quality of model simulations, and the performance of the model is verified over various subregions of the model domain. South of the tropics, DARLAM fields are not only superior to those produced by the GCM, but also compare well with mesoscale observations. This is particularly true for the spatial distribution of rainfall and screen temperature simulations. DARLAM, however, severely over-estimates rainfall totals over regions of steep orography. WaterSA Vol.28(4) 2002: 361-374

Limited-Area Model Sensitivity to the Complexity of Representation of the Land Surface Energy Balance

Abstract By coupling a multimode land surface scheme with a regional climate model, three scientific issues are addressed in this paper: (i) the regional model's sensitivity to the different levels of complexity presented by the land surface parameterization, (ii) relative model sensitivity to the land surface parameterization as compared with that to other model physical representations, and, (iii) following offline calibration, whether different complexity in the land surface representation leads to different model performance in the coupled experiments. In this study, a version of a regional model [Division of Atmospheric Research Limited Area Model (DARLAM)] is coupled with the Chameleon Surface Model (CHASM). Three sets of experiments are analyzed in this paper, employing six different complexity modes of CHASM. Model results from these coupled experiments show that the regional model is sensitive overall to different complexities represented in the CHASM modes. Moreover, these model sensitivities ar...

Interannual, Decadal, and Transient Greenhouse Simulation of Tropical Cyclone–like Vortices in a Regional Climate Model of the South Pacific

Tropical cyclone-like vortices (TCLVs) in the South Pacific Ocean are studied using the CSIRO Division of Atmospheric Research Limited Area Model (DARLAM), nested in a transient carbon dioxide simulation of the CSIRO Mark2 global coupled GCM. This GCM is able to simulate El Nino-Southern Oscillation (ENSO)-like interannual variations, although the amplitude of these is considerably smaller than observed. A comparison is made between observed geographical variations of cyclone formation caused by ENSO and similar variations simulated by DARLAM. An analysis of the simulated interannual variability of TCLV formation suggests that under La Nina conditions TCLVs tend to occur closer to the coast of Australia, whereas under El Nino conditions TCLVs tend to occur farther eastward, in agreement with observations. Under enhanced greenhouse conditions, this geographical variation continues. In addition, the total number of TCLVs in the South Pacific region decreases in a warmer world. As in previous simulations using DARLAM, there is a southward movement in TCLV occurrence under enhanced greenhouse conditions, although this has not been simulated to date by other climate models. The GCM simulation of sea surface temperatures also exhibits coherent decadal variability that has some similarities to the observed ENSO-like decadal variability. This variability forces decadal variations in TCLV formation that, like ENSO-forced variations, have geographically distinct centers of action.

Investigating the haze transport from 1997 biomass burning in Southeast Asia: its impact upon Singapore

The 1997 Indonesia forest fires was an environmental disaster of exceptional proportions. Such a disaster caused massive transboundary air pollution and indiscriminate destruction of biodiversity in the world. The immediate consequence of the fires was the production of large amounts of haze in the region, causing visibility and health problems within Southeast Asia. Furthermore, fires of these magnitudes are potential contributors to global warming and climate change due to the emission of large amounts of greenhouse gases and other pyrogenic products.The long-range transport of fire-related haze in the region is investigated using trajectories from the CSIRO Division of Atmospheric Research Limited Area Model (DARLAM). Emission scenarios were constructed for hotspot areas in Sumatra and Kalimantan for the months of September and October 1997 to determine the period and fire locations most critical to Singapore. This study also examines some transport issues raised from field observations. Results show that fires in the coastal areas of southeast Sumatra and southwest Kalimantan can be potential contributors to transboundary air pollution in Singapore. Singapore was directly affected by haze from these areas whereas Kuala Lumpur was heavily affected by the haze coming from Sumatra. In most cases, Singapore was more affected by fires from Kalimantan than was Kuala Lumpur. This was mainly a result of the shifting of monsoons. The transition of monsoons resulted in weaker low-level winds and shifted convergence zones near to the southeast of Peninsular Malaysia. In addition to severe drought and massive fire activity in 1997, the timing of the monsoon transition has a strong influence on haze transport in the region.

Developing scenarios of climate change for Southeastern Australia: an example using regional climate model output

Regional climate models nested in global climate models are now being used in Aus- tralia to produce high resolution climate change scenarios for use in impact assessments. This paper describes the development of such scenarios for the State of Victoria in Southeastern Australia using the CSIRO Division of Atmospheric Research Limited Area Model (DARLAM) at a horizontal resolu- tion of 60 km nested in the slab ocean version of the CSIRO global climate model (GCM). Rainfall and temperature over Victoria are substantially better simulated in DARLAM than they are in the host GCM, although some poor features of the simulation of the seasonal cycle of rainfall have not been improved with the increase in resolution. There is evidence to suggest that some of these errors are due to errors in the simulation of atmospheric circulation provided by the host GCM. Under 2 × CO2 conditions, DARLAM simulates patterns of rainfall and temperature change which differ significantly from those provided by the host GCM and which appear more physically plausible. In particular, winter rainfall in southern Victoria increases in the DARLAM simulation, but decreases in the host GCM. Although the DARLAM scenario could be considered the best single scenario available for Victoria at the time of its production, it is noted that different, but equally plausible, scenarios could be obtained by nesting DARLAM in other GCMs, or by increasing the simulation sample size. Our assessment is that the rainfall changes simulated by DARLAM in summer may be most sensitive to such changes. In general, it is concluded that there is great potential to increase the realism of climate change scenarios in the Victorian region through careful use of nested regional modelling.

Modeling trace gas concentrations at Cape Grim using the CSIRO Division of Atmospheric Research Limited Area Model (DARLAM)

The CSIRO Division of Atmospheric Research Limited Area Model (DARLAM) is used to study the emission and transport of trace gases in the atmosphere. Two simulations are performed, one for radon, which has relatively simple surface emissions, and another for CO2, which has more complex spatial and temporal distributions of surface fluxes. For this study, DARLAM was initialized from observed atmospheric conditions. Diurnally varying surface fluxes from photosynthesis and respiration were included as functions of temperature, incoming solar radiation, and vegetation type. Industrial sources of CO2 and an Australian inventory of radon fluxes were also included. This study provides an evaluation of the model's trace gas transport capability by comparing Cape Grim measurements with the modeled concentrations of radon and CO2. Correlations calculated using 3‐hour averaging are generally high for radon (0.6–0.8), and lower for CO2 (0.2–0.6). An objective verification technique of categorical forecasting is used to show that the model can satisfactorily forecast the occurrence of radon events. The quality of the model CO2 simulation is less satisfactory. Extra simulations suppressing either island or mainland sources are used to identify whether the air is of island, oceanic, or mainland origin. Further simulations suppressing industrial or biospheric sources are then used to show that the model can handle isolated industrial sources, but biospheric sources and sinks are not handled well at present. We conclude that insufficient accuracy in the spatial and temporal representation of the biospheric CO2 sources and sinks is the main reason for the model's less satisfactory CO2 simulation.

Simulating midsummer climate over southern Africa using a nested regional climate model

The Commonwealth Scientific and Industrial Research Organisation (CSIRO) Division of Atmospheric Research limited area model (DARLAM) is used to simulate midsummer (January) climate over southern Africa. Using a one‐way nesting procedure, lateral boundary and initial conditions are supplied by the CSIRO nine‐level Mark 2 general circulation model (GCM), CSIRO9. In general, the DARLAM results are improved in comparison with those from CSIRO9, although certain deficiencies in the GCM climatology over southern Africa are also present in the nested model results. DARLAM captures the spatial pattern of observed rainfall and interannual rainfall variability over the region as a whole more accurately than CSIRO9. Over most parts of the subcontinent, interannual rainfall variability simulated by DARLAM is not significantly different from observations. Over the steep escarpment region of south‐east South Africa, DARLAM simulates more rainfall than CSIRO9 and significantly more rainfall than observed. Over Madagascar, DARLAM simulates more rainfall than CSIRO9, but less than observed, and interannual variability is also significantly less than the observed variability.