1. Earth’s Radiative Forcing Given the data: Can you close the energy budget? Alex, Elizabeth, & Tyreke

2. Kevin Trenberth works for NCAR lead author for IPCC reports in 1995, 2001, 2007 father of energy balance figure fun fact: in 2009’s “climategate,” quoted for not being able to account for hiatus and missing energy (Calvin, 2005)

3. Norman G. Loeb works for NASA, principal investigator of CERES focuses on remote sensing plays basketball in free time (NASA, 2011)

4. Data Analysis vs. Modeling -Data analysis: observations-Physical model that has been constructed. Think: Matlab http://www.mathworks.co.uk/

5. Balanced? Energy Budget In steady state, energy follows energy balance model: CHANGE IN STORAGE = IN – OUT These papers discuss an imbalance in this equation, which results in missing energy (Trenberth & Fasullo, 2012)

6. Incoming Shortwave Radiation yellow: total solar irradiance that reaches TOA red: radiation that penetrates through atmosphere to sea level spaces: irradiance absorbed by gases in atmosphere Most of radiation from the sun reaches the Earth’s surface (EPS 22, 2014)

7. Greenhouse Gases and Atmospheric Transmissivity longwave effects: increasing GHG emissions lower the transmissivity of the atmosphere and trap outgoing radiation Graphs show percent of solar radiation absorbed at each wavelength Breaks down atmosphere into constituents Take home: very little longwave radiation escapes

8. Atmospheric Constituents and their Effect on Radiative Forcing Relative forcing for: Greenhouse gases trap longwave radiation (positive Radiative effects) Stratospheric Ozone lowers transmissivity of incoming UV radiation Aerosols reflect solar shortwave radiation back to space (negative radiative effects)

9. Data Sources measuring TOA radiation ERBE (Earth’s Radiant Energy Budget Experiment) o conducted from 1985-1989 -- when TOA values were assumed to be in balance CERES (Clouds and the Earth’s Radiant Energy System) o continuation of ERBE, December 1999- present o Objectives  to continue ERBE, increase accuracy, provide long-term global estimates, bridge gap between clouds and radiative fluxes

10. Data Sources: Through the Atmosphere Moderate Resolution Imaging Spectroradiometer (MODIS) retrievals ❏ captures data in 36 spectral bands (0.4 µm to 14.4 µm) ❏ measures changes in cloud cover, radiation budget, and oceanic/atmospheric processes Photos based on observations from MODIS

11. Data Sources: Precipitation Global Precipitation Climatology Project (GPCP) o Develop a temporal and spatial understanding of global precipitation o Network of ~6,000 stations o contains error (undercatch and sampling), but considered to be most reliable (Trenberth et al. 2007b)

12. Data Sources: CloudSat and GRACE CloudSat o measures altitude and properties of clouds o to add info. on the relationship between clouds and climate Gravity Recovery and Climate Experiment (GRACE) o Shows increase in mass of ocean since 2003 La Ni ñ a

13. Trenberth Paper Motivation: After 2004, the energy balance model is unbalanced and this missing energy is unaccounted for in the climate system Contends the energy is unbalanced and looks to find it by incorporating analysis of subsurface ocean data Used model to suggest what is the main sink: the ocean below 275 meters

14. Ocean Heat Content Has Increased Over Time blue bars: 1961-2003 burgundy bars: 1993-2003 positive energy content change = increase in stored energy (Total) oceans account for most energy uptake (90%) (Trenberth & Fasullo, 2012)

15. “natural climate variability has a cause” o external to the climate system (volcanic eruption) o internal heat once sequestered can resurface at later time ENSO: An Example of Natural Variability NOAA / PMEL / TAO Project Office, Dr. Michael J. McPhaden, Director

16. Increased Heating After 2008 La Niña (Trenberth & Fasullo, 2012) ENSO (°C) drives net increase in energy imbalance Cloud cover decreases Lagged decrease of outgoing longwave radiation (W/m 2 ) to cooler conditions and increase in ASR Extra TOA energy absorbed (W/m 2 ) Net Radiation (R T )=ASR-OLR --Left axis

17. Rate of Increase in Surface Temperature in Relation to Sea Level and CO 2 (Trenberth & Fasullo, 2012) T(sfc): 12-month global mean surface temperature anomalies relative to 1901- 2000 Thick line: data normalized to decadal El Niño (1997-98) La Niña (2007-08) Atmospheric carbon dioxide concentration and sea level are increasing ~ linearly Rate of temperature increase appears to slow after 2003

18. Missing Energy in the Global Net Energy Flux (Trenberth & Fasullo, 2012) Solid black line: original satellite data Dotted black line: EBAF Ed2.5 is revisited satellite data Currently, we are not accounting for all missing energy The ocean is the main energy sink Additional energy sinks (e.g. ice) make 0.6 W/m 2 of total warming Sun changes reduce net heating

19. Storage of Energy Entering Climate System 1993-2003 residual only is 0.7 W/m 2 2004-2008 >50% of energy entering system is residual (Trenberth & Fasullo, 2012)

20. Model: NCAR CCSM version 4 Released May 2010 Modeling temperature for 21 st century Coupled atmospheric and land-surface model Global Mean Surface Temperature (Trenberth & Fasullo, 2012) Black: average of 5 runs Blue: moments of surface warming stasis

21. Modeled Perturbations of 21 st Century Ocean Heat Content (Trenberth & Fasullo, 2012) top left: net radiation at TOA (R T ) increases top right: ocean heat content increases at depth as surface heat content decreases lower panel: ocean heat content modeled Gray: stasis in global mean surface temperature

22. Strengths: Trenberth Effectively discusses history of data analysis and how this information is interpreted in the context of the CCSM model Makes a strong argument for why we should be concerned with missing energy: need to track global energy to understand how hard we are driving the climate system. If we ever want to make predictions it is necessary to better understand and balance the energy budget.

23. Weaknesses: Trenberth Current observations and analyses either: o Provide an incoherent narrative o Have huge error Does not discuss the switch in ocean surveying (to ARGO) in 2004 and its implications on accuracy.

24. Loeb Paper Obtained most of data from CERES then applied adjustment of heat uptake using ARGO and ice melt data Finds imbalance from 2001-2008 to be 0.50±0.42 W/m 2 (confidence of 90%) Motivation: to decrease uncertainty by estimating warming rates over longer periods of time

25. Great Uncertainty in Upper Ocean Warming Rates uncertainty declines in recent years after transition of technology shows ocean warming of 0.64±0.11 W/m 2 between 1993 and 2008 (Loeb et al. 2012) Ocean Heat Rate (W/m 2 )

26. Great Uncertainty in Upper Ocean Warming Rates Loeb et al. finds decline in heating rates after 2004 statistically insignificant (Loeb et al. 2012) Mean and Uncertainty of Ocean Heating Rates at 90% Confidence Level

27. Variations in Radiation Correlated with ENSO Cycle Tropics Global (Loeb et al. 2012) Earth energy anomalies (ASR, NET, OLR) correlate to El Niño and La Niña conditions. Positive anomalies with La Niña. Negative with El Niño years. gray is ENSO index: positive el niño phase negative la niña phase

28. TOA Flux vs Ocean Heating Rates (Loeb et al. 2012) CERES does not show a sharp decline during the XBT to Argo transition (2002-2005) CERES and PMEL/JPL/JIMAR have r ~ 0.46 CERES and ERA-Interim show consistency Interannual variability of net TOA ranges from 0.09-1.5Wm 2 No statistically significant heating rate decline Energy is continuing to accumulate in the oceans

29. Applying Loeb’s Errors to Trenberth’s Image

30. Strengths: Loeb clearly states Trenberth and others hypothesis on missing energy and reruns and reinterprets data argues strength of newer measurements (Argo v XBF) and reevaluates error measurements identifies concrete sources of uncertainty Weaknesses identified in Trenberth’s email regarding Loeb’s paper

31. Trenberth’s Response to Loeb (email) ●Main point of original Trenberth paper: to challenge the OHC and CERES communities to do better ●Trenberth accuses Loeb of having uncertainties too large to confine to “within uncertainty.” ●Large discrepancies between OHC data sets hamper current studies.

32. Summary of Debate: Trenberth ●Missing heat being deposited in ocean: ○Below 700 meters ○in the Pacific ○between 40°S and 30°N ○it is associated with the negative phase of the Pacific Decadal Oscillation and/or La Nina events

33. Summary of Debate: Loeb New satellite and ocean data have improved measurements No statistically significant decline in ocean heating rate There may not be “missing energy” in the climate system, energy is continuing to accumulate in the oceans

34. Given the data: Can you close the energy budget?