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Atmospheric energy budgets in the Japanese Reanalysis: Evaluation and variability

Abstract: The vertically-integrated atmospheric energy and moisture budgets have been computed for all available months for the Japanese reanalysis (1979 to 2004), and results are described in detail for the month of January 1989 and compared with those of other reanalyses. Time series are also presented. The moistening, diabatic heating and total energy forcing of the atmosphere are computed as a residual from the analyses using the moisture, dry energy (dry static energy plus kinetic energy) and total atmospheric (moist static plus kinetic) energy budget equations. These fields are also computed from the model output based on the assimilating model parameterizations. Moreover, some component fields can also be computed from observations to evaluate the results. In particular, when the vertically-integrated forcings computed from the model parameterizations are compared with available observations and the budget-derived values, significant JRA model biases are revealed in radiation and precipitation. The energy and moisture budget-derived quantities are more realistic than the model output and better depict the real atmosphere. However, low frequency decadal variability is spurious and is mainly associated with changes in the observing system. Results also depend on the quality of the analyses which are not constructed to conserve mass, moisture or energy, owing to analysis increments. By emphasizing the differences and the errors, there is a tendency to overlook the considerable progress in depicting diabatic components of the atmosphere, while also pointing to where research can make further improvements.

Figure. Q₁, -Q₂ and Q₁ - Q₂ estimated directly from the model accumulated values and their differences with the vertically-integrated budget derived quantities in Fig. 1. The plots are smoothed to T42 resolution and the units are W m^-2. For the plots at left, the contour interval is 80 W m^-2, and stipple and hatching begin at ± 120 W m^-2 and more densely at ±200 W m^-2. For the difference plots at right, the contour interval is 40 W m^-2, and stipple and hatching begin at ±60 W m^-2 and more densely at ±100 W m^-2.

Submitted to J. Meteor. Soc. Japan, 3 March 2008.

Authored by: Kevin E. Trenberth (corresponding author) and Lesley Smith
NCAR/Climate and Global Dynamics Division, Boulder, CO 80307, USA
Email: trenbert@ucar.edu

 

Lessons learned from IPCC AR4: Future scientific developments needed to understand, predict and respond to climate change

Abstract: The recently-released Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC) concluded that it is very likely that human activities are leading to an increase in global average temperature and that anthropogenic warming has likely to very likely lead to other changes such as in wind patterns and storm tracks, temperature patterns, and temperature extremes, sea level rise and many other physical and biological indicators, with implications for both socioeconomic and ecological systems. It is now clear that we are committed to some level of climate change, and this must be considered when planning future climate research and observational strategies. As such, the Global Climate Observing System Programme (GCOS), the World Climate Research Programme (WCRP), and the International Geosphere-Biosphere Programme (IGBP) initiated a process whereby key scientists involved in AR4 Working Groups 1 and 2 decided on a set of high-priority research and observational needs. Two fundamental classes of recommendations emerged from this process. First is the body of work needed to improve process-level understanding, climate models, and observational and climate monitoring systems. Second, the framework for climate research and observations must be re-designed with the specific goal of producing the information needed for decisions around impacts, adaptation and mitigation. At the intersection of these two are research and observational strategies specifically aimed at improving the predictability and understanding of impacts, adaptive capacity, and societal and ecosystem vulnerabilities. In this paper we discuss specific recommendations pertaining to each of these areas.

Submitted to BAMS, 7 March 2008.

Authored by: Doherty, S.J., S. Bojinski, A. Henderson-Sellers, K. Noone, D. Goodrich, N.L. Bindoff, J.A. Church, K. Hibbard, T.R. Karl, L. Kajfez-Bogataj, A.A. Lynch, D.E. Parker, I.C. Prentice, V. Ramaswamy, R.W. Saunders, A.J. Simmons, M.S. Smith, K. Steffen, T.F. Stocker, P.W. Thorne, K.E. Trenberth, M.M. Verstraete, and F.W. Zwiers