By Roger Pielke Sr., Climate Science Blog

We have a new paper accepted. It is

Fall, S., D. Niyogi, A. Gluhovsky, R. A. Pielke Sr., E. Kalnay, and G. Rochon, 2009: Impacts of land us land cover on temperature trends over the continental United States: Assessment using the North American Regional Reanalysis. Int. J. Climatol., accepted.

This paper (and other such publications) avoids systematic biases in using reanalyses with respect to the the 2m temperatures that were identified by the Pitman and Perkins (2009) paper (see). As explained by Eugenia Kalnay in an e-mail to me last week, working with anomalies eliminates those types of bias in the 2m temperatures.

The abstract of the new Fall et al paper is

“We investigate the sensitivity of surface temperature trends to land use land cover change (LULC) over the conterminous United States (CONUS) using the observation minus reanalysis (OMR) approach. We estimated the OMR trends for the 1979-2003 period from the US Historical Climate Network (USHCN), and the NCEP-NCAR North American Regional Reanalysis (NARR). We used a new mean square differences (MSDs) based assessment for the comparisons between temperature anomalies from observations and interpolated reanalysis data. Trends of monthly mean temperature anomalies show a strong agreement, especially between adjusted USHCN and NARR (r = 0.9 on average) and demonstrate that NARR captures the climate variability at different time scales. OMR trend results suggest that unlike findings from studies based on the global reanalysis (NCEP/NCAR reanalysis), NARR often has a larger warming trend than adjusted observations (on average, 0.28 and 0.27C/decade respectively). OMR trends were found to be sensitive to land cover types. We analyzed decadal OMR trends as a function of land types using the Advanced Very High Resolution Radiometer (AVHRR) and new National Land Cover Database (NLCD) 1992-2001 Retrofit Land Cover Change.

Results indicate that when the dynamic nature of LULC is taken into account, the magnitude of OMR trends is larger than the ones derived from a “static” LULC dataset and land use conversion often results in more warming than cooling. Overall, our results confirm the robustness of the OMR method for detecting nonclimatic changes at the station level, evaluating the impacts of adjustments performed on raw observations, and demonstrating sensitivity to LULC changes at local and regional scales. Since the majority of warming trends that we identify can be explained on the basis of LULC changes, we suggest that in addition to considering the greenhouse gases driven radiative forcings, multi-decadal and longer climate models simulations must further include LULC changes.”

Text in the conclusion includes

“The need to separate the local from the regional land use change effect on the temperature record does merit further study, as the later is a regional climate forcing effect, while the local microclimate and non-climatic station effects are a contamination of the temperature data in terms of constructing regional scale temperature trends.

Since the majority of warming trends that we identify can be explained on the basis of land use/land cover changes, we suggest that in addition to considering the well-mixed greenhouse gases and aerosol driven radiative forcings, multi-decadal and longer climate models simulations must further include land cover/land use changes. In terms of using long term surface temperature records as a metric to monitor climate change, there also needs to be further work to separate the local microclimate and non-climate station effects from the regional land use/land cover change effects on surface temperatures.” See post here.