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Shaoxiu Ma
,
Andy Pitman
,
Jiachuan Yang
,
Claire Carouge
,
Jason P. Evans
,
Melissa Hart
, and
Donna Green

Abstract

Global warming, in combination with the urban heat island effect, is increasing the temperature in cities. These changes increase the risk of heat stress for millions of city dwellers. Given the large populations at risk, a variety of mitigation strategies have been proposed to cool cities—including strategies that aim to reduce the ambient air temperature. This paper uses common heat stress metrics to evaluate the performance of several urban heat island mitigation strategies. The authors found that cooling via reducing net radiation or increasing irrigated vegetation in parks or on green roofs did reduce ambient air temperature. However, a lower air temperature did not necessarily lead to less heat stress because both temperature and humidity are important factors in determining human thermal comfort. Specifically, cooling the surface via evaporation through the use of irrigation increased humidity—consequently, the net impact on human comfort of any cooling was negligible. This result suggests that urban cooling strategies must aim to reduce ambient air temperatures without increasing humidity, for example via the deployment of solar panels over roofs or via cool roofs utilizing high albedos, in order to combat human heat stress in the urban environment.

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Annette L. Hirsch
,
Jatin Kala
,
Andy J. Pitman
,
Claire Carouge
,
Jason P. Evans
,
Vanessa Haverd
, and
David Mocko

Abstract

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.

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Jatin Kala
,
Mark Decker
,
Jean-François Exbrayat
,
Andy J. Pitman
,
Claire Carouge
,
Jason P. Evans
,
Gab Abramowitz
, and
David Mocko

Abstract

Leaf area index (LAI), the total one-sided surface area of leaf per ground surface area, is a key component of land surface models. The authors investigate the influence of differing, plausible LAI prescriptions on heat, moisture, and carbon fluxes simulated by the Community Atmosphere Biosphere Land Exchange version 1.4b (CABLEv1.4b) model over the Australian continent. A 15-member ensemble monthly LAI dataset is generated using the Moderate Resolution Imaging Spectroradiometer (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 datasets 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%. Plant function types (PFTs) with high absolute LAI and low interannual variability, such as evergreen broadleaf trees, showed the least response to the different LAI prescriptions, while those with lower absolute LAI and higher interannual variability, such as croplands, were more sensitive. The authors show that reliance on a single LAI prescription may not accurately reflect the uncertainty in the simulation of terrestrial carbon fluxes, especially for PFTs with high interannual variability. The study highlights that 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.

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Jean-Daniel Paris
,
Philippe Ciais
,
Philippe Nédélec
,
Andreas Stohl
,
Boris D. Belan
,
Mikhail Yu. Arshinov
,
Claire Carouge
,
Georgii S. Golitsyn
, and
Igor G. Granberg

There are very few large-scale observations of the chemical composition of the Siberian airshed. The Airborne Extensive Regional Observations in Siberia (YAKAEROSIB) French–Russian research program aims to fill this gap by collecting repeated aircraft high-precision measurements of the vertical distribution of CO2, CO, O3, and aerosol size distribution in the Siberian troposphere on a transect of 4,000 km during campaigns lasting approximately one week. This manuscript gives an overview of the results from five campaigns executed in April 2006, September 2006, August 2007, and early and late July 2008. The dense set of CO2 vertical profiles, consisting of some 50 profiles in each campaign, is shown to constrain large-scale models of CO2 synoptic transport, in particular frontal transport processes. The observed seasonal cycle of CO2 in altitude reduces uncertainty on the seasonal covariance between vegetation fluxes and vertical mixing, known as the “seasonal rectifier effect.” Regarding carbon dioxide, we illustrate the potential of the YAKAEROSIB data to cross-validate a global CO2 transport model. When compared to the CO2 data, the model is likely to be biased toward too-weak mixing in winter, as it overestimates the CO2 vertical gradient compared to the observation. Regarding pollutants, we illustrate through case studies the occurence of CO enhancements of 30–50 ppb above background values, coincident with high O3. These high CO values correspond to large-scale transport of anthropogenic emissions from Europe, and to wildfires in the Caspian Sea area, over much cleaner Arctic air (September 2006). An occurence of extremely high CO values above 5,000 km in eastern Siberia is found to be related to the very fast transport and uplift of Chinese anthropogenic emissions caused by a cold front (April 2006).

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