Attribution of Climate Variability During the Last 100 Years III Posters
Presiding: M P Hoerling, NOAA Climate Diagnostics Center; A Kumar, NOAA Climate Prediction Center
A41E-01 0830h
Seasonal and inter-annual trends in earth's albedo
Recently measurements of earthshine have been used to determine that there are large decadal scale variability in the earth's short-wave reflectance. Here we will discuss the qualitative and quantitative agreement of these decadal trends with those from other independent studies of the SW forcing of climate. Further, special attention will be given to the continuous earthshine measurements from 1998 to present. The internal consistency of the earthshine dataset over this period of time and its seasonal and inter-annual trends will be analyzed in detail.
A41E-02 0830h
Anthropogenic Influence on Lower Atmospheric Temperature Trends
Surface temperature trends during the last two decades show a significant increase which appears to be anthropogenic in origin. By this it is meant that global temperature changes using surface as well as satellite measurements show that lower tropospheric temperature trends for the last three decades are spatially correlated to surface CO2 emissions, which can be used as a measure of direct anthropogenic influence on global warming. Furthermore, temperature trends for the regions not spatially correlated with CO2 emissions are considerably smaller or even negligible for some of the satellite data. Very similar results are arrived at after analysing many other data sets, including NCEP and ECMWF. It is also possible to show, using the same measure, that two important climate models do not reproduce the geographical climate response to all known forcings as found in the observed temperature trends. Thus it becomes interesting to consider whether a component of the observed surface temperature changes might be a result of local warming processes in addition to global greenhouse forcing.
A41E-03 0830h
Global Land Precipitation and its Uncertainties in the Long-term Trend in Gauge-based Analyses
In recent years, several sets of analyzed fields of global land precipitation have been constructed by interpolating historical gauge observations (e.g. Dai et al. 1997, New et al. 2000, and Chen et al. 2002). Covering extended time periods of multiple decades, these data sets have been utilized to detect long-term trends in precipitation over various portions of the global land, in addition to their wide applications in analysis of climate variations of seasonal to inter-annual time scales. Uncertainties, however, exist, in these gauge-based analyses due to changes in the density and configuration of gauge networks. In particular, over regions where natural long-term variability of precipitation is relatively small compared to the spatial gradients of precipitation fields, shifts of gauge locations over the recording periods will yield temporally changing bias in the gauge-based analyses, producing an artificial trend of long term precipitation. In this study, we examine and quantify the uncertainties of the published data sets of gauge precipitation in detecting long-term trend of global land precipitation. Quantitative comparisons are performed between gauge-based analyses derived from fixed and changing gauge networks to examine the magnitude of the uncertainties on each grid box of 0.5 deg lat/lon over the global land areas. The results are then compared against the long-term trend derived from the gauge-based analyses on various spatial scales to quantify their relatively importance. Detailed results of this study will be reported at the workshop.
A41E-04 0830h
Ocean Heat Content: Reconciling observations and Climate Models.
Since Levitus [Science, 2000] reported increases in observed Ocean Heat Content between the 1950s-1990s, numerous studies (e.g., Barnett et al.[Science 2001], Levitus et al. [Science, 2001], and Reichert et al. [GRL,2002]) have carried out climate change detection studies comparing model simulated changes in ocean heat content to observations. While these studies confirm that the increasing trend in ocean heat content is due to anthropogenic sources, they have not shown variability in the interannual to decadal time-scales that the observations indicate. This has naturally led to questions about the fidelity of models in being able to simulate natural variability. Recent work by Gregory et al [GRL, 2004] suggests that sparse, time-varying data coverage in several ocean basins is a possible source of apparent disagreement between one coupled climate model and observations. Recently, a new and updated version of the World Ocean Heat Content which extends the time series to more recent years has been released by Levitus et al. [GRL, 2005]. In this study, we analyze the shortcomings of the observations and show the effects of data coverage on variability using a suite of coupled ocean-atmosphere climate models from the Coupled Model Intercomparison Project (CMIP2+). We will address possible implications for climate model diagnosis and for climate change detection studies with simulations of 20th Century warming using state-of-the-art IPCC class models.