Comparison of Monthly Mean Station and NNR Surface Temperature Anomalies with Respect to Their Annual Cycles for Selected Stations in Argentina

NUÑEZ, MA. N.; KALNAY, E.; CIAPPESONI, H. H.; ROLLA, A.; MING CAI

Baltimore, Maryland, USA

Conferencia; 1st International CLIVAR Science Conference; 2004

World Climate Research Program

Comparison of Monthly Mean Station and NNR Surface Temperature Anomalies with Respect to Their Annual Cycles for Selected Stations in Argentina Prof. Mario N. Nuñez, CIMA. Pabellon2, Piso 2, Ciudad Universitaria, (1428)Buenos Aires, Argentina, mnunez@cima.fcen.uba.ar Prof. Eugenia Kalnay, University of Maryland at College Park, 3431 CSS, College Park, MD 20742-2425, USA, ekalnay@atmos.umd.edu. Dr. Hector H. Ciappesoni, Servicio Meteorológico Nacional/CONICET, 25 de Mayo 658, Buenos Aires, Argentina, cuqui@meteofa.mil.ar. Alfredo Rolla, CIMA, Pabellon2, Piso 2, Ciudad Universitaria, (1428)Buenos Aires, Argentina, alrolla@cima.fcen.uba.ar. Ming Cai, Florida State University, Tallahassee, FL, USA, cai@huey.met.fsu.edu It is generally accepted that the two most important anthropogenic forcings leading to climate change are the increase of greenhouse gases, commonly referred to as "global warming", and changes in land use, such as urbanization, agriculture, etc. Unfortunately, their impacts on climate change have been very difficult to separate because they both tend to produce surface warming. The impact of urbanization on surface warming has been estimated by comparing observations in cities with those in surrounding rural areas, but these estimations have considerable uncertainty. Here we used the difference between trends in observed temperatures in Argentina and the corresponding trends in the reconstruction of surface temperatures determined from a reanalysis of global weather over the past 50 years, which is insensitive to surface observations, to estimate the impact of land use changes on surface warming. Kalnay and Cai (2003) developed this method, using the property that NCEP-NCAR Reanalysis (NNR) is insensitive to land surface properties, but it is sensitive to atmospheric climate changes. The difference of observation minus reanalysis surface temperature trends is at least partly attributable to changes in land surface use, including both urbanization and agricultural practices. An advantage of the method is that climate changes associated with changes in atmospheric circulation with decadal time scales are filtered out from the trend because they are also present in the reanalysis. For the surface observations, we use the daily surface maximum and minimum surface stations temperatures from the National Weather Service of Argentina over mostly the Argentinean provinces for 1961-2000. For the NNR, we use the global daily surface maximum and minimum temperatures Gaussian distributed, also for the period 1961-2000. Preliminary results for stations situated in four regions of Argentina (Humid Pampas, Litoral, North and Patagonia) agree with the previous results shown in Kalnay and Cai (2003), with good agreement between the reanalysis and the station data. Over the last two decades the differences between the observations and the reanalysis show an increase of 0.5C/decade, at least partly attributable to land-use changes.