Impact of Land Surface Initialization Approach on Subseasonal Forecast Skill: a Regional Analysis in the Southern Hemisphere

The authors use a sophisticated coupled land-atmosphere modeling system for a Southern Hemisphere subdomain centered over southeastern Australia to evaluate differences in simulation skill from two different land surface initialization approaches. The first approach uses equilibrated land surface states obtained from offline simulations of the land surface model, and the second uses land surface states obtained from reanalyses. The authors find that land surface initialization using prior offline simulations contribute to relative gains in subseasonal forecast skill. In particular, relative gains in forecast skill for temperature of 10%-20% within the first 30 days of the forecast can be attributed to the land surface initialization method using offline states. For precipitation there is no distinct preference for the land surface initialization method, with limited gains in forecast skill irrespective of the lead time. The authors evaluated the asymmetry between maximum and minimum temperatures and found that maximum temperatures had the largest gains in relative forecast skill, exceeding 20% in some regions. These results were statistically significant at the 98% confidence level at up to 60 days into the forecast period. For minimum temperature, using reanalyses to initialize the land surface contributed to relative gains in forecast skill, reaching 40% in parts of the domain that were statistically significant at the 98% confidence level. The contrasting impact of the land surface initialization method between maximum and minimum temperature was associated with different soil moisture coupling mechanisms. Therefore, land surface initialization from prior offline simulations does improve predictability for temperature, particularly maximum temperature, but with less obvious improvements for precipitation and minimum temperature over southeastern Australia

Influence of Leaf Area Index Prescriptions on Simulations of Heat, Moisture, and Carbon Fluxes

Leaf-area index (LAI), the total one-sided surface area of leaf per ground surface area, is a key component of land surface models. We investigate the influence of differing, plausible LAI prescriptions on heat, moisture, and carbon fluxes simulated by the Community Atmosphere Biosphere Land Exchange (CABLEv1.4b) model over the Australian continent. A 15-member ensemble monthly LAI data-set is generated using the MODIS LAI product and gridded observations of temperature and precipitation. Offline simulations lasting 29 years (1980-2008) are carried out at 25 km resolution with the composite monthly means from the MODIS LAI product (control simulation) and compared with simulations using each of the 15-member ensemble monthly-varying LAI data-sets generated. The imposed changes in LAI did not strongly influence the sensible and latent fluxes but the carbon fluxes were more strongly affected. Croplands showed the largest sensitivity in gross primary production with differences ranging from -90 to 60 %. PFTs with high absolute LAI and low inter-annual variability, such as evergreen broadleaf trees, showed the least response to the different LAI prescriptions, whilst those with lower absolute LAI and higher inter-annual variability, such as croplands, were more sensitive. We show that reliance on a single LAI prescription may not accurately reflect the uncertainty in the simulation of the terrestrial carbon fluxes, especially for PFTs with high inter-annual variability. Our study highlights that the accurate representation of LAI in land surface models is key to the simulation of the terrestrial carbon cycle. Hence this will become critical in quantifying the uncertainty in future changes in primary production

Subcontinental heat wave triggers terrestrial and marine, multi-taxa responses

Heat waves have profoundly impacted biota globally over the past decade, especially where their ecological impacts are rapid, diverse, and broad-scale. Although usually considered in isolation for either terrestrial or marine ecosystems, heat waves can straddle ecosystems of both types at subcontinental scales, potentially impacting larger areas and taxonomic breadth than previously envisioned. Using climatic and multi-species demographic data collected in Western Australia, we show that a massive heat wave event straddling terrestrial and maritime ecosystems triggered abrupt, synchronous, and multi-trophic ecological disruptions, including mortality, demographic shifts and altered species distributions. Tree die-off and coral bleaching occurred concurrently in response to the heat wave, and were accompanied by terrestrial plant mortality, seagrass and kelp loss, population crash of an endangered terrestrial bird species, plummeting breeding success in marine penguins, and outbreaks of terrestrial wood-boring insects. These multiple taxa and trophic-level impacts spanned \u3e300,000 km2—comparable to the size of California—encompassing one terrestrial Global Biodiversity Hotspot and two marine World Heritage Areas. The subcontinental multi-taxa context documented here reveals that terrestrial and marine biotic responses to heat waves do not occur in isolation, implying that the extent of ecological vulnerability to projected increases in heat waves is underestimated

Land-atmosphere interactions in Southwest Western Australia

The Southwest of Western Australia (SWWA) is a region of extensive land cover change with an estimated 13 million hectares of native vegetation cleared since European settlement. Whilst previous studies have suggested meteorological and climatological implications of this change in land use, no studies have explicitly focussed on the detailed mechanisms behind the impacts of land-cover change on individual meteorological phenomena. This thesis seeks to identify the physical mechanisms inducing changes within the atmosphere by using the Regional Atmospheric Modeling System (RAMS V6.0) to simulate the impact of land use change on meteorological phenomena at different scales and evaluate these model results against high resolution atmospheric soundings, station observations, and gridded rainfall analyses where appropriate. Sensitivity tests show that land-cover change results in an increase in low-level atmospheric moisture advection associated with the southern sea-breeze due to a reduction in surface roughness. It also results in a decrease in convective precipitation associated with cold-fronts and convective clouds associated with the surface heat trough, due to an increase in wind speed, and a decrease in turbulent kinetic energy and vertically integrated moisture convergence within the PBL. Large-eddy simulations further highlight the role of land-cover change and soil moisture, as well as the contributions of surface versus entrainment fluxes on the growth of the PBL and development of convective clouds. These results are discussed within the broader context of the meteorology of the region

Evaluation of ACCESS-S1 seasonal forecasts of growing season precipitation for Western Australia’s wheatbelt region

Seasonal forecasts are increasingly important tools in agricultural crop management. Regions with Mediterranean-type climates typically adopt rain-fed agriculture with minimal irrigation, hence accurate seasonal forecasts of rainfall during the growing season are potentially useful in decision making. In this paper we examined the bias and skill of a seasonal forecast system (ACCESS-S1) in simulating growing season precipitation (GSP) for south-west Western Australian (SWWA), a region with a Mediterranean-type climate and significant cereal crop production. Focusing on July–September (3-month) and May–October (6-month) forecasts, with 0- and 1-month lead times, we showed that overall ACCESS-S1 had a dry bias for SWWA rainfall and a tendency to simulate close to average rainfall during both wetter and drier than average rainfall years. ACCESS-S1 showed particularly poor skill at these timeframes for very wet and very dry years. The limitations in ACCESS-S1 for SWWA GSP were associated with inaccuracies in the timing of heavy rainfall events. In addition, limitations of the ACCESS-S1 model in accurately capturing SST and wind anomaly patterns over the tropical Indian Ocean during extreme rainfall years also contributed to errors in SWWA GSP forecasts. Model improvements in these regions have the potential to improve seasonal rainfall forecasts for SWWA

An investigation of future fuel load and fire weather in Australia

We present an assessment of the impact of future climate change on two key drivers of fire risk in Australia, fire weather and fuel load. Fire weather conditions are represented by the McArthur Forest Fire Danger Index (FFDI), calculated from a 12-member regional climate model ensemble. Fuel load is predicted from net primary production, simulated using a land surface model forced by the same regional climate model ensemble. Mean annual fine litter is projected to increase across all ensemble members, by 1.2 to 1.7 t ha-1 in temperate areas, 0.3 to 0.5 t ha-1 in grassland areas and 0.7 to 1.1 t ha-1 in subtropical areas. Ensemble changes in annual cumulative FFDI vary widely, from 57 to 550 in temperate areas, -186 to 1372 in grassland areas and -231 to 907 in subtropical areas. These results suggest that uncertainty in FFDI projections will be underestimated if only a single driving model is used. The largest increases in fuel load and fire weather are projected to occur in spring. Deriving fuel load from a land surface model may be possible in other regions, when this information is not directly available from climate model outputs

Sensitivity of WRF to driving data and physics options on a seasonal time-scale for the southwest of Western Australia

Regional climate models are sensitive to the forcing data used, as well as different model physics options. Additionally, the behaviour of physics parameterisations may vary depending on the location of the domain due to different climatic regimes. In this study, we carry out a sensitivity analysis of the weather research and forecasting model to different driving data and model physics options over a 10-km resolution domain in the southwest of Western Australia, a region with Mediterranean climate. Simulations are carried out on a seasonal time-scale, in order to better inform future long-term regional climate simulations for this region. We show that the choice of radiation scheme had a strong influence on both temperature and precipitation; the choice of planetary boundary layer scheme has a particularly large influence on minimum temperatures; and, the choice of cumulus scheme or more complex micro-physics did not strongly influence precipitation simulations. More importantly, we show that the same radiation scheme, when used with different driving data, can lead to different results.27 page(s