Assessing Land Surface Albedo Bias in Models of Tropical Climate

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DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Assessing Land Surface Albedo Bias in Models of Tropical Climate William R. Boos (PI) Yale University PO Box 208109 New Haven, CT 06520 phone: (203) 432-2627 fax: (203) 432-3134 email: william.boos@yale.edu Award Number: N00014-15-1-2531 Carolyn A. Reynolds (co-pi) Naval Research Laboratory Monterey, CA 93940 phone: (831) 656 4728 fax: (831) 656 4769 email: carolyn.reynolds@nrlmry.navy.mil LONG-TERM GOALS Variability in tropical atmospheric circulations has great importance for international socio-economic stability and worldwide military operations. Although tropical circulations are known to respond to changes in both land and ocean boundary conditions, research and operational forecasting in recent years have strongly focused on sea surface temperature (SST) as a cause of atmospheric variability. Here we shift attention back to the land surface boundary condition and present a plan to quantify errors in land surface energy fluxes and their contribution to bias in numerical models of weather and climate. This project is expected to improve the fidelity of numerical simulations of weather and climate, and to deepen understanding of the fundamental role played by the land surface in tropical climate. The project directly addresses the ONR Marine Meteorology program goal of improving atmospheric prediction in marine and coastal zones. OBJECTIVES Land surface albedo is of particular importance because it controls the net flux of energy from land into the atmosphere, and is typically more persistent than land surface temperature or soil moisture. This proposed work will quantify bias in land surface albedo in an ensemble of climate models and in the Navy Global Environmental Model (NAVGEM), and relate this bias to errors in simulated tropical circulations. Multiple observational estimates of land surface albedo will be compared to model output from phase 5 of the Coupled Model Intercomparison Project (CMIP5) and to NAVGEM analyses and short-term and extended forecasts. This project will focus on two particular applications: the Somali jet and African easterly waves. The Somali jet constitutes a large part of the global cross-equatorial atmospheric mass flux during boreal summer, and is a good dynamical index of the South Asian monsoon; it is closely associated with the vertical wind shear that suppresses tropical cyclone formation in the Indian Ocean during boreal summer. African easterly waves, which are precursors of many Atlantic tropical cyclones, are thought to originate from instability of the African easterly jet, which in 1

turn is generated by surface heat fluxes over the Sahel and the Sahara Desert. Both the Somali jet and African easterly waves will thus be sensitive to the albedo of the proximal monsoon continent. This project will quantify simulated activity of the Somali jet and African easterly waves and relate this activity to model albedo bias. Simple modifications of NAVGEM surface albedo will be performed to estimate the degree to which correcting albedo bias can remediate circulation bias. APPROACH This project divides naturally into two parts. The first consists of analysis of albedo and circulation bias in the CMIP5 models, and is being performed by personnel at Yale University. The second part involves assessing and modifying NAVGEM surface albedo and is led by staff at NRL with assistance from Yale. Design of model experiments, development of analysis methods, and interpretation of results will all be done collaboratively by both Yale and NRL. Key tasks and the project time line are summarized below. Key individuals are: William Boos (PI), Yale University Carolyn Reynolds (co-pi), Naval Research Laboratory Naftali Cohen, postdoctoral associate at Yale Xavier Levine, postdoctoral associate at Yale James Ridout, Naval Research Laboratory 2

WORK COMPLETED Yale staff obtained one observational dataset of land surface albedo (GEWEX) and the entire ensemble of CMIP5 surface radiative fluxes needed to calculate albedo. Albedo bias relative to GEWEX has been computed, together with several measures of intermodel variability in albedo. Intermodel covariations in time-mean circulation and albedo have been assessed. NRL and Yale staff have determined the NAVGEM output needed to diagnose surface albedo bias. RESULTS Funding for the Yale component of this project has been active for only one month, so only preliminary results have been obtained. We found that CMIP5 models exhibit large model-to-model variability in tropical land surface albedo with intermodel variability being larger than the typical seasonal cycle (Fig. 1). For example, the surface albedoes of the Sahara and India vary by at least 0.1 across the model ensemble; this is a large variation that would correspond to surface flux variations on the order of 30 W m -2. Idealized models have shown that surface albedo anomalies of this magnitude can produce large changes in the strength of the African and Asian monsoons and in the amplitude of synoptic activity such as African easterly waves. The ensemble mean CMIP5 albedo is also biased, with errors over tropical Africa, South Asia, and Australia easily reaching 0.05. A notable result is that land surface albedo in the CMIP5 models correlates strongly with the simulated strength of the South Asian monsoon (Fig. 2). The multi-model mean albedo is too high while the multi-model mean monsoon is too weak, consistent with the response expected from theory. There is no statistical association between interannual variations in model albedo and rainfall, which supports the hypothesis that the albedo changes cause the rainfall changes (as opposed to the converse). Fig. 1: Horizontal mean land surface broadband shortwave albedo over India in the CMIP5 model ensemble. Each line shows the climatological mean seasonal cycle for one model. Note that the model-to-model differences are relatively constant throughout the seasonal cycle; this suggests that model bias does not simply result from differences in precipitation during the local summer rainy season. 3

Fig. 2: Relationship between South Asian rainfall and land surface albedo of India in the CMIP5 models. Each circle represents June-August climatological means for a single model simulation of the 20 th century. The black star shows the multi-model mean and the magenta star shows observations. The line shows the best linear fit. IMPACT/APPLICATIONS This project directly addresses the goal of ONR s Marine Meteorology program to improve atmospheric prediction in marine and coastal zones. Numerical weather prediction on time scales longer than a day or two requires a global domain and correct representation of large-scale tropical circulations such as the Hadley circulation and monsoons. This project will diagnose and attempt to correct bias in land surface albedo that contributes to errors in these large-scale circulations. Furthermore, this project gives particular focus to the effect of albedo on African easterly waves and the Somali jet. The former serve as precursors for Atlantic tropical cyclones, and the latter influences Indian Ocean cyclogenesis (via its effects on vertical wind shear) and navigability of the Arabian Sea for small watercraft (such as those involved in piracy). This work, focusing on land surface characteristics, will directly complement research under the Earth System Prediction Capability, which is focused on the coupling of the atmospheric model to ocean and ice models. Deficiencies in the NAVGEM land surface albedo identified in this project will be addressed in other projects focused on NAVGEM operational improvements. RELATED PROJECTS This project is related to the PI s previous ONR award, Understanding the Global Distribution of Monsoon Depressions (N00014-11-1-0617). That award focused on synoptic (5-7 day) variability in the Indian Ocean and West Pacific, while this award focuses on the boundary conditions that drive the larger-scale monsoon circulations in which that weather is embedded. By reducing model bias in the mean state, simulations and forecasts of weather should be improved. This project will both leverage and provide feedback for the development of NAVGEM under the ONR and PMW-120 NAVGEM 4

Rapid Transition project, and the Navy ESPC global coupled system under PMW-120 Earth System Prediction Capability project. PUBLICATIONS (The below publications resulted from the PI s previous ONR award, N00014-11-1-0617, but are included here because they were not previously listed in an annual or final report.) Ditchek, S. D., W. R. Boos, S. J. Camargo, and M. K. Tippett: A genesis index for monsoon disturbances. Journal of Climate [submitted, refereed] Haertel, P., and W. R. Boos: Global impacts of the Madden Julian Oscillation on monsoon lows and depressions. Journal of Climate [submitted, refereed] Cohen, N. Y., and W. R. Boos: Perspectives on moist baroclinic instability: implications for the growth of monsoon depressions. Journal of the Atmospheric Sciences [submitted, refereed] Boos, W. R., A. V. Fedorov, and L. Muir: Convective self-aggregation and tropical cyclogenesis under the hypohydrostatic rescaling. Journal of the Atmospheric Sciences [in press, refereed] 5