Vertical structure and physical processes of the Madden-Julian oscillation: Biases and uncertainties at short range

An analysis of diabatic heating and moistening processes from 12-36 hour lead time forecasts from 12 Global Circulation Models are presented as part of the "Vertical structure and physical processes of the Madden-Julian Oscillation (MJO)" project. A lead time of 12-36 hours is chosen to constrain the large scale dynamics and thermodynamics to be close to observations while avoiding being too close to the initial spin-up for the models as they adjust to being driven from the YOTC analysis. A comparison of the vertical velocity and rainfall with the observations and YOTC analysis suggests that the phases of convection associated with the MJO are constrained in most models at this lead time although the rainfall in the suppressed phase is typically overestimated. Although the large scale dynamics is reasonably constrained, moistening and heating profiles have large inter-model spread. In particular, there are large spreads in convective heating and moistening at mid-levels during the transition to active convection. Radiative heating and cloud parameters have the largest relative spread across models at upper levels during the active phase. A detailed analysis of time step behaviour shows that some models show strong intermittency in rainfall and differences in the precipitation and dynamics relationship between models. The wealth of model outputs archived during this project is a very valuable resource for model developers beyond the study of the MJO. In addition, the findings of this study can inform the design of process model experiments, and inform the priorities for field experiments and future observing systems

Importance of recent shifts in soil thermal dynamics on growing season length, productivity, and carbon sequestration in terrestrial high-latitude ecosystems

Author Posting. © The Authors, 2005. This is the author's version of the work. It is posted here by permission of Blackwell for personal use, not for redistribution. The definitive version was published in Global Change Biology 12 (2006): 731-750, doi:10.1111/j.1365-2486.2006.01113.x.In terrestrial high-latitude regions, observations indicate recent changes in snow cover, permafrost, and soil freeze-thaw transitions due to climate change. These modifications may result in temporal shifts in the growing season and the associated rates of terrestrial productivity. Changes in productivity will influence the ability of these ecosystems to sequester atmospheric CO2. We use the Terrestrial Ecosystem Model (TEM), which simulates the soil thermal regime, in addition to terrestrial carbon, nitrogen and water dynamics, to explore these issues over the years 1960-2100 in extratropical regions (30°-90°N). Our model simulations show decreases in snow cover and permafrost stability from 1960 to 2100. Decreases in snow cover agree well with NOAA satellite observations collected between the years 1972-2000, with Pearson rank correlation coefficients between 0.58-0.65. Model analyses also indicate a trend towards an earlier thaw date of frozen soils and the onset of the growing season in the spring by approximately 2-4 days from 1988-2000. Between 1988 and 2000, satellite records yield a slightly stronger trend in thaw and the onset of the growing season, averaging between 5-8 days earlier. In both the TEM simulations and satellite records, trends in day of freeze in the autumn are weaker, such that overall increases in growing season length are due primarily to earlier thaw. Although regions with the longest snow cover duration displayed the greatest increase in growing season length, these regions maintained smaller increases in productivity and heterotrophic respiration than those regions with shorter duration of snow cover and less of an increase in growing season length. Concurrent with increases in growing season length, we found a reduction in soil carbon and increases in vegetation carbon, with greatest losses of soil carbon occurring in those areas with more vegetation, but simulations also suggest that this trend could reverse in the future. Our results reveal noteworthy changes in snow, permafrost, growing season length, productivity, and net carbon uptake, indicating that prediction of terrestrial carbon dynamics from one decade to the next will require that large-scale models adequately take into account the corresponding changes in soil thermal regimes.Funds were provided by the NSF for the Arctic Biota/Vegetation portion of the ‘Climate of the Arctic: Modeling and Processes’ project (OPP- 0327664), and by the USGS ‘Fate of Carbon in Alaska Landscapes’ project

A modeling study of the seasonal oxygen budget of the global ocean

Author Posting. © American Geophysical Union, 2007. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 112 (2007): C05017, doi:10.1029/2006JC003731.An ecosystem model embedded in a global ocean general circulation model is used to quantify roles of biological and physical processes on seasonal oxygen variations. We find that the thermally induced seasonal net outgassing (SNO) of oxygen is overestimated by about 30% if gas phase equilibrium is assumed, and we find that seasonal variations in thermocline oxygen due to biology are approximated well using the oxygen anomaly. Outside the tropics and the north Indian Ocean, biological SNO is, on average, 56% of net community production (defined as net oxygen production above 76 m) during the outgassing period and 35% of annual net community production. In the same region the seasonal drawdown of the oxygen anomaly within the upper thermocline (76–500 m) is 76% of the remineralization during the drawdown and 48% of annual remineralization. Applying model-derived relationships to observed O2 climatologies and using independent estimates for tropical and monsoonal systems, we estimate global net community production to be 14.9 ± 2.5 Pg C yr−1.R.N., X.J., and F.L. were supported from the following grants: NOAA NA16GP2987, NASA NAG5-6451, and NSF OCE-9711937

Mapping the stray domestic cat (Felis catus) population in New Zealand: Species distribution modelling with a climate change scenario and implications for protected areas

Species distribution models of stray cats were developed using two types of occurrence data: (i) a combined dataset of stray cats and cat colonies in Auckland and projected to the wider New Zealand area; and (ii) population density as an analogue for country-wide stray cat occurrence. These occurrence data, together with sets of environmental variables were used as input to the Maxent modelling tool to produce maps of suitability for the species. Environmental variables used in the models consist of current bioclimatic conditions, and a future climate scenario (RCP8.5 for year 2070 CCSM model). Commonly occurring bias in the modelling process due to latitude, the area for selecting background points in model evaluation, inherent spatial autocorrelation of occurrence points, and correlated bioclimatic variables were explicitly addressed. Results show that the North Island consistently provide more suitable areas for stray cats with increased suitability in a high emission climate change condition. Key protected areas at risk from the increased suitability to stray cats are also presented

Impact of large-scale climatic oscillations on snowfall-related climate parameters in the world's major downhill ski areas: a review

Skiers are passionate about finding the best snow conditions. Snow conditions in thousands of ski resorts around the world depend mainly on natural snowfall, particularly in the case of backcountry skiing. In various mountain ranges popular among skiers, snowfall is strongly linked to large-scale climatic oscillations. This paper reviews existing information on the impacts of several of these phenomena, such as the El Niño-Southern Oscillation, North Atlantic Oscillation, and North Pacific Index, on snowfall-related climate parameters in the world's major ski areas. We found that in each of the studied areas, one or more large-scale climatic oscillations affected snowfall-related climate parameters. Understanding the predictability of such oscillations is high on the climate research agenda. If this research leads to improved predictability in the coming years, this could be combined with the knowledge summarized in our paper on the relationships between climatic oscillations and snow-related parameters to provide useful information for winter sports and other snow-related fields. © 2012 International Mountain Society

GlobusWORLD 2005 Grid-BGC: A Grid-Enabled Terrestrial Carbon Cycle Modeling System

❑ This is a collaborative project between the National Center for Atmospheric Research (NCAR