Effects of land cover change on temperature and rainfall extremes in multi-model ensemble simulations

Abstract

Abstract. The impact of historical land use induced land cover change (LULCC) on regional-scale climate extremes is examined using four climate models within the Land Use and Climate, IDentification of robust impacts project. To assess those impacts, multiple indices based on daily maximum and minimum temperatures and daily precipitation were used. We contrast the impact of LULCC on extremes with the impact of an increase in atmospheric CO 2 from 280 ppmv to 375 ppmv. In general, consistent changes in both high and low temperature extremes are similar to the simulated change in mean temperature caused by LULCC and are restricted to regions of intense modification. The impact of LULCC on both means and on most temperature extremes is statistically significant. While the magnitude of the LULCCinduced change in the extremes can be of similar magnitude to the response to the change in CO 2 , the impacts of LULCC are much more geographically isolated. For most models, the impacts of LULCC oppose the impact of the increase in CO 2 except for one model where the CO 2 -caused changes in the extremes are amplified. While we find some evidence that individual models respond consistently to LULCC in the simulation of changes in rainfall and rainfall extremes, LULCC's role in affecting rainfall is much less clear and less commonly statistically significant, with the exception of a consistent impact over South East Asia. Since the simulated response of mean and extreme temperatures to LULCC is relatively large, we conclude that unless this forcing is included, we risk erroneous conclusions regarding the drivers of temperature changes over regions of intense LULCC.

Inconsistent Responses of Hot Extremes to Historical Land Use and Cover Change Among the Selected CMIP5 Models

“…However, the remaining one third of the cases (i.e., non-GFDL cases) does not reproduce such responses, suggesting that there are evident disagreements among these models. Furthermore, some results from Pitman et al (2012) also imply some asymmetric responses of the T max extremes and inconsistencies of the multimodel results. For example, the percentages of significant grid points of the LUCC signals show clear differences between TX90P and TX10P in Pitman et al (2012, Table 5); the differences can be up to 25% over some regions.…”

Strong dependence of CO2 emissions from anthropogenic land cover change on initial land cover and soil carbon parametrization

“…In MPI-ESM the parameter controlling the fraction of direct emission was chosen arbitrarily as it was argued to be irrelevant for multicentennial emissions, for which the LULCC model was initially designed [Pongratz et al, 2009b]. However, the model was subsequently applied to much shorter timescales [Pitman et al, 2012;Houghton et al, 2012;Brovkin et al, 2013a;Giorgetta et al, 2013;Reick et al, 2013;Wilkenskjeld et al, 2014], and this fraction was recalibrated to minimize biases in the historical land carbon balance [Giorgetta et al, 2013]. Although the parametrization of direct emissions controls legacy emissions, a global quantification of this uncertainty is missing.…”

“…Earth system models (ESMs) and their precursors are a common tool to quantify LULCC emissions and feedbacks between LULCC and climate [Strassmann et al, 2008;Pitman et al, 2009;Arora and Boer, 2010;de Noblet-Ducoudré et al, 2012;Houghton et al, 2012;Lawrence et al, 2012;Pitman et al, 2012;Brovkin et al, 2013a;Shevliakova et al, 2013]. ESMs incorporate process-based land components, land surface models (LSMs), which integrate biological, hydrological, and physical processes within the soil-plant-atmosphere continuum [Prentice et al, 2014].…”

“…A LSM often used in LULCC studies is Jena Scheme for Biosphere-Atmosphere Coupling in Hamburg (JSBACH), the land component of the Max Planck Institute Earth System Model (MPI-ESM) [Giorgetta et al, 2013]. It was used to study the biogeochemical [Pongratz et al, 2009a], the biogeophysical [Pongratz et al, 2009b;Pitman et al, 2009;de Noblet-Ducoudré et al, 2012;Brovkin et al, 2013a], or the combined [Pongratz et al, , 2011Pitman et al, 2012] climate responses, as well as to quantify changes in the terrestrial carbon balance Houghton et al, 2012;Reick et al, 2013;Wilkenskjeld et al, 2014;Schneck et al, 2015].…”

Representation of climate extreme indices in the ACCESS1.3b coupled atmosphere–land surface model

“…It remains uncertain how soil moisture affects rainfall, with no agreement on the sign of the feedback (Findell and Eltahir, 2003;Ek and Holtslag, 2004;Taylor and Ellis, 2006). Pitman et al (2012) analysed several global climate models to examine the impact of land-use changes on temperature and precipitation extremes and found opposing effects to the impact of increasing CO 2 for some extreme indices and additive impacts for others. In short, to understand the changes in extremes linked with natural variability or increasing CO 2 we need to understand how land-surface processes influence climate extremes.…”