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  • Author or Editor: J. P. Evans x
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J. P. Evans

Abstract

This study investigates changes in the types of storm events occurring in the Fertile Crescent as a result of global warming. Regional climate model [fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5)–Noah] simulations are run for the first and last five years of the twenty-first century following the Special Report on Emissions Scenarios (SRES) A2 experiment. Then the precipitation events are classified according to the water vapor fluxes that created them. At present most of the region’s precipitation is from westerly water vapor fluxes. Results indicate that the region will increasingly get its precipitation from large events that are dominated by southerly water vapor fluxes. The increase in these events will occur in the transition seasons, especially autumn.

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J. P. Evans
and
R. B. Smith

Abstract

The study presented here attempts to quantify the significance of southerly water vapor fluxes on precipitation occurring in the eastern Fertile Crescent region. The water vapor fluxes were investigated at high temporal and spatial resolution by using a Regional Climate Model [fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5)–Noah land surface model] to downscale the NCEP–NCAR reanalysis. Using the Iterative Self-Organizing Data Analysis Techniques (ISODATA) clustering algorithm, the 200 largest precipitation events, occurring from 1990 through 1994, were grouped into classes based on the similarity of their water vapor fluxes. Results indicate that, while southerly fluxes were dominant in 24% of tested events, these events produced 43% of the total precipitation produced by the 200 largest events. Thus, while the majority of precipitation events occurring in the Fertile Crescent involve significant water vapor advected from the west, those events that included southerly fluxes produced much larger precipitation totals. This suggests that changes that affect these southerly fluxes more than the westerly fluxes (e.g., changes in the Indian monsoon, movement of the head of the Persian Gulf, etc.) may have a relatively strong affect on the total precipitation falling in the Fertile Crescent even though they affect relatively few precipitation events. To obtain a clearer view of the precipitation mechanisms, the authors used a linear model, along with the estimated water vapor fluxes, to downscale from 25 to 1 km. The result shows a spectrum of mountain scales not seen in the regional model, exerting tight control on the precipitation pattern.

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M. Decker
,
A. J. Pitman
, and
J. P. Evans

Abstract

A land surface scheme with and without groundwater–vegetation interactions is used to explore the impact of rainfall variability on transpiration over drought-vulnerable regions of southeastern Australia. The authors demonstrate that if groundwater is included in the simulations, there is a low correlation between rainfall variability and the response of transpiration to this variability over forested regions. Groundwater reduces near-surface water variability, enabling forests to maintain transpiration through several years of low rainfall, in agreement with independent observations of vegetation greenness. If groundwater is not included, the transpiration variability matches the rainfall variability independent of land cover type. The authors’ results suggest that omitting groundwater in regions where groundwater sustains forests will 1) probably overestimate the likelihood of forest dieback during drought, 2) overestimate a positive feedback linked with declining transpiration and a drying boundary layer, and 3) underestimate the impact of land cover change due to inadequately simulating the different responses to drought for different land cover types.

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X. H. Meng
,
J. P. Evans
, and
M. F. McCabe

Abstract

Moderate Resolution Imaging Spectroradiometer (MODIS)-derived vegetation fraction data were used to update the boundary conditions of the advanced research Weather Research and Forecasting (WRF) Model to assess the influence of realistic vegetation cover on climate simulations in southeast Australia for the period 2000–08. Results show that modeled air temperature was improved when MODIS data were incorporated, while precipitation changes little with only a small decrease in the bias. Air temperature changes in different seasons reflect the variability of vegetation cover well, while precipitation changes have a more complicated relationship to changes in vegetation fraction. Both MODIS and climatology-based simulation experiments capture the overall precipitation changes, indicating that precipitation is dominated by the large-scale circulation, with local vegetation changes contributing variations around these.

Simulated feedbacks between vegetation fraction, soil moisture, and drought over southeast Australia were also investigated. Results indicate that vegetation fraction changes lag precipitation reductions by 6–8 months in nonarid regions. With the onset of the 2002 drought, a potential fast physical mechanism was found to play a positive role in the soil moisture–precipitation feedback, while a slow biological mechanism provides a negative feedback in the soil moisture–precipitation interaction on a longer time scale. That is, in the short term, a reduction in soil moisture leads to a reduction in the convective potential and, hence, precipitation, further reducing the soil moisture. If low levels of soil moisture persist long enough, reductions in vegetation cover and vigor occur, reducing the evapotranspiration and thus reducing the soil moisture decreases and dampening the fast physical feedback. Importantly, it was observed that these feedbacks are both space and time dependent.

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Faye T. Cruz
,
Andrew J. Pitman
,
John L. McGregor
, and
Jason P. Evans

Abstract

Using a coupled atmosphere–land surface model, simulations were conducted to characterize the regional climate changes that result from the response of stomates to increases in leaf-level carbon dioxide (CO2) under differing conditions of moisture availability over Australia. Multiple realizations for multiple Januarys corresponding to dry and wet years were run, where only the leaf-level CO2 was varied at 280, 375, 500, 650, 840, and 1000 ppmv and the atmospheric CO2 was fixed at 375 ppmv. The results show the clear effect of increasing leaf-level CO2 on the transpiration via the stomatal response, particularly when sufficient moisture is available. Statistically significant reductions in transpiration generally lead to a significantly warmer land surface with decreases in rainfall. Increases in CO2 lead to increases in the magnitude and areal extent of the statistically significant mean changes in the surface climate. However, the results also show that the availability of moisture substantially affects the effect of increases in the leaf-level CO2, particularly for a moisture-limited region. The physiological feedback can indirectly lead to more rainfall via changes in the low-level moisture convergence and vertical velocity, which result in a cooling simulated over Western Australia. The significant changes in the surface climate presented in the results suggest that it is still important to incorporate these feedbacks in future climate assessments and projections for Australia. The influence of moisture availability also indicates that the capacity of the physiological feedback to affect the future climate may be affected by uncertainties in rainfall projections, particularly for water-stressed regions such as Australia.

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A. M. Ukkola
,
A. J. Pitman
,
M. G. De Kauwe
,
G. Abramowitz
,
N. Herger
,
J. P. Evans
, and
M. Decker

Abstract

Global climate models play an important role in quantifying past and projecting future changes in drought. Previous studies have pointed to shortcomings in these models for simulating droughts, but systematic evaluation of their level of agreement has been limited. Here, historical simulations (1950–2004) for 20 models from the latest Coupled Model Intercomparison Project (CMIP5) were analyzed for a variety of drought metrics and thresholds using a standardized drought index. Model agreement was investigated for different types of drought (precipitation, runoff, and soil moisture) and how this varied with drought severity and duration. At the global scale, climate models were shown to agree well on most precipitation drought metrics, but systematically underestimated precipitation drought intensity compared to observations. Conversely, simulated runoff and soil moisture droughts varied significantly across models, particularly for intensity. Differences in precipitation simulations were found to explain model differences in runoff and soil moisture drought metrics over some regions, but predominantly with respect to drought intensity. This suggests it is insufficient to evaluate models for precipitation droughts to increase confidence in model performance for other types of drought. This study shows large but metric-dependent discrepancies in CMIP5 for modeling different types of droughts that relate strongly to the component models (i.e., atmospheric or land surface scheme) used in the coupled modeling systems. Our results point to a need to consider multiple models in drought impact studies to account for high model uncertainties.

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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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