Evaluation of IPCC Soil Moisture Simulations for the latter half of the 20 th Century Haibin Li 1, Alan Robock 1, Martin Wild 2 1 Department of Environmental.

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Presentation transcript:

Evaluation of IPCC Soil Moisture Simulations for the latter half of the 20 th Century Haibin Li 1, Alan Robock 1, Martin Wild 2 1 Department of Environmental Sciences, Rutgers University, New Brunswick, NJ, USA 2 Institute for Atmospheric and Climate Science ETH, Swiss Federal Institute of Technology, Zurich, Switzerland

Outline Why?? Model intended for projections should provide reliable reproduction of past/current climate Data sets Observations & model outputs Analysis Seasonal cycle, interannual variability, spatial pattern. Long term soil moisture evolution in warm season – trend analysis. Sensitivity experiment – radiation vs. soil moisture Conclusions

Observations RegionDomain Year (0-1 m) Correlation (0-1 m) Year (0-10 cm) Correlation (0-10 cm) No. of stations Ukraine46-52N, 22-40E (0.74) (0.73)26* Russia51-59N, 32-57E (0.77) (0.78)29* Mongolia N, E (0.67) (0.58)5 Northern China 43-48N, E (0.59) (0.54)8 Central China 34-37N, E (0.73) (0.79)5 Illinois N, 88-91W (0.84) (0.81)18

Model outputs: Model NameOrganizationLand SurfaceReference MIROC3.2 (medres) Center for Climate System Research (The University of Tokyo), National Institute for Environmental Studies, and Frontier Research Center for Global Change (JAMSTEC), JAPAN MATSIRO (no tiling), ~2.8º Takata, et a.l 2003 GISS - EH NASA / Goddard Institute for Space Studies, USA Land Surface Model, 4 by 5 Rosenzweig and Abramopoulos, 1997; Friend and Kiang, 2005 GISS - ER MRI-CGCM2.3.2 Meteorological Research Institute, Japan SiB L3 (no vegetation scheme), ~2.8º Sellers et al. 1986; Sato et al FGLOALS-g1.0 LASG / Institute of Atmospheric Physics, China CLM2.0, ~2.8ºDai et al CGCM3.1 (T47) Canadian Centre for Climate Modeling & Analysis, Canada CLASS ~3.75 ºVerseghy et al CCSM3, USA National Center for Atmospheric Research, USA CLM3.0, ~1.4 ºOleson et al UKMO-HADCM3 Hadley Centre for Climate Prediction and Research / Met Office, Met Office, UK MOSES-I (2.5 by 3.75)Cox et al UKMO-HADGEM1 MOSES-II (1.25 by 1.875) Essey et al. 2001

Seasonal cycle Top 10 cm (unit: cm) Total soil column (SWI) Better agreement over FSU regions. Less discrepancy in warm seasons.

Now single model performs superior than others at all regions. Better simulations in Ukraine, Russia and Illinois boxes. Poor results at Mongolia and China. CGCM3.1 (t47) has stronger interannual variations than obs at all regions. Two UK models have interannual variations comparable to obs. Taylor Diagram for top 10 cm soil moisture

Taylor Diagram for precipitation Better simulation of precipitation not necessarily means more realistic soil moisture. Other factors also contribute.

Interannual variability (Coefficient of variance) Generally, the drier the region is, the stronger interannual variation. Large inter- model differences and model-to-obs difference.

Seasonal trends a. Soil moisture b. precipitation c. temperature d. Radiation (SW)

Soil moisture evolution in summer (JJA), Upward trend for both regions. Model ensembles show little change. The observed trend is far above that of model’s range. Evidence from pan evaporation (Peterson et al ) and solar radiation at the earth surface (Wild et al. 2005).

Precipitation Temperature Observed trend for temperature is well constrained in models. Precipitation & temperature all increase slightly but are not statistically significant. What likely contributes to the observed trend in soil moisture?

Radiation: from dimming to brightening. Soil moisture: from upward trend to level-off. Sensitivity experiments from ECHAM5 model (linear trend: units in mm/decade) Coincidence?

Linear trend for top 10 cm ( , mm/decade)

Conclusions 1.Less discrepancy in warm season simulations. 2.Better simulations over Ukraine and Russia and Illinois boxes but not necessarily a result of good precipitation. 3.Large differences between obs and models in terms of interannual variability. Some model systematically exhibits stronger interannual variations. 4.Significant trends in warm season (JJAS) for soil moisture. Prep & temp don’t show much change. Model simulated trend for temperature is generally reliable. 5.Sensitivity analysis from ECHAM5 model did show model with indirect aerosol scheme may have a better change to capture observed soil moisture pattern.

Acknowledgements: