Monthly Archives: December 2009

New Paper On The Need For Improved Cloud Representation In Climate Models By Wang Et Al 2009

Yesterday, I discussed the issue that water vapor feedbacks are more poorly understood than indicated in the papers by Andrew Dessler (see). Today, I have provided a new paper that discusses one aspect of the current inability of the multi-decadal global climate models to skillfully predict cloud-precipitation feedbacks (and thus their difficulty in accurately representing radiative feedbacks in this models).

The new paper is

Wang, Y., C.N. Long, L.R. Leung, J. Dudhia, S.A. McFarlane, J.H. Mather, S.J. Ghan, and X. Liu. 2009. “Evaluating Regional Cloud-Permitting Simulations of the WRF Model for the Tropical Warm Pool International Cloud Experiment (TWP-ICE), Darwin, 2006.” J. Geophys. Res., 114, D21203, doi:10.1029/2009JD012729

The abstract reads

“Data from the Tropical Warm Pool International Cloud Experiment (TWP-ICE) were used to evaluate Weather Research and Forecasting (WRF) model simulations with foci on the performance of three six-class bulk microphysical parameterizations (BMPs). Before the comparison with data from TWP-ICE, a suite of WRF simulations were carried out under an idealized condition, in which the other physical parameterizations were turned off. The idealized simulations were intended to examine the interaction of BMP at a “cloud-resolving” scale (250 m) with the nonhydrostatic dynamic core of the WRF model. The other suite of nested WRF simulations was targeted on the objective analysis of TWP-ICE at a “cloud-permitting” scale (quasi-convective resolving, 4 km). Wide ranges of discrepancies exist among the three BMPs when compared with ground-based and satellite remote sensing retrievals for TWP-ICE. Although many processes and associated parameters may influence clouds, it is strongly believed that atmospheric processes fundamentally govern the cloud feedbacks through the interactions between the atmospheric circulations, cloudiness, and the radiative and latent heating of the atmosphere. Based on the idealized experiments, we suggest that the discrepancy is a result of the different treatment of ice-phase microphysical processes (e.g., cloud ice, snow, and graupel). Because of the turn-off of the radiation and other physical parameterizations, the cloud radiation feedback is not studied in idealized experiments. On the other hand, the “cloud-permitting” experiments engage all physical parameterizations in the WRF model so that the radiative heating processes are considered together with other physical processes. Common features between these two experiment suites indicate that the major discrepancies among the three BMPs are similar. This strongly suggests the importance of ice-phase microphysics. To isolate the influence of cloud radiation feedback, we further carried out an additional suite of simulations, which turns off the interactions between cloud and radiation schemes. It is found that the cloud radiation feedback plays a secondary, but nonnegligible role in contributing to the wide range of discrepancies among the three BMPs.”

There is a news release for this paper that is titled

Computer-simulated Thunderstorms with Ice Clouds Reveal Insights for Next-generation Computer Models

Excerpts from the paper are [highlight added]

“Thunderstorms in the tropics generate widespread cirrus clouds that are important in reflecting and absorbing energy. These mixing ratios for granular snow pellets (also called “soft hail”) (shades) and cloud ice (contours) from comparison testing of thunderstorm clouds in the tropics illustrate the wide discrepancy of the ice-phase cloud microphysics in current models. The melting line is marked as a thicker, red line. These types of discrepancies must be resolved for models to more accurately predict cloud influence on climate change.”

Computer simulations of thunderstorms using data from a field campaign in Australia confirm that the “ice-phase” cloud processes in climate models contribute most to the wide discrepancy between model results and actual cloud measurements. This was a key finding from PNNL scientist Dr. Yi Wang and his colleagues from a recent study.”

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New Paper “Temperature And Equivalent Temperature Over The United States (1979 – 2005) By Fall Et Al 2009

We have a new paper that documents the need to include water vapor trends, in addition to  temperature trends, in the assessment of climate system heat changes (which, of course, includes global warming). 

Our paper is

Fall, S., N. Diffenbaugh, D. Niyogi, R.A. Pielke Sr., and G. Rochon, 2009:  Temperature and equivalent temperature over the United States (1979 – 2005). Int. J. Climatol., in press

has been accepted. The abstract of our paper reads

Temperature (T) and equivalent temperature (TE) trends over the United States from 1979 to 2005 and their correlation to land cover types are investigated using National Centers for Environmental Prediction (NCEP) North American Regional Reanalysis (NARR) data, the Advanced Very High Resolution Radiometer (AVHRR) land use/cover classification, the National Land Cover Database (NLCD) 1992-2001 Retrofit Land Cover Change, and the Normalized Difference Vegetation Index (NDVI) derived from AVHRR.

Even though most of the magnitude of TE is explained by T, the moisture component induces larger trends and variability of TE relative to T. The contrast between pronounced temporal and spatial differences between T and TE at the near-surface level and minor to no differences at 300 mb – 200 mb is a consistent pattern. This study therefore demonstrates that in addition to temperature, atmospheric heat content may help to quantify the differences between surface and tropospheric heating trends, and hence the impact of land cover types on the surface temperature changes.

Correlations of T and TE with NDVI reveal that TE shows a stronger relationship to vegetation cover than T, especially during the growing season, with values that are significantly different and of opposite signs (-0.31 for T vs. NDVI; 0.49 for TE vs. NDVI). Our results suggest that land cover types influence both moisture availability and temperature in the lower atmosphere and that TE is larger in areas with higher physical evaporation and transpiration rates. As a result, TE can be used as an additional metric for analyzing near-surface heating trends with respect to land cover types. Moreover, TE can be tested as a complementary variable for assessing the impact of land surface and boundary layer processes in reanalysis and weather/climate model studies.

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Comment From Josh Willis On The Upper Ocean Heat Content Data Posted On Real Climate

Real Climate has a post titled  Updates to model-data comparisons which includes a plot of the variations in upper ocean content anomalies from the period 1955 through 2009 .  

I asked Josh Willis the following with respect to the plot in the Real Climate post

My question:

Real Climate has posted a plot of ocean heat content, which we have
 discussed before, that shows a sudden jump in the 2002-2003 time frame;

 http://www.realclimate.org/index.php/archives/2009/12/updates-to-model-data-comparisons/

 This jump is not seen it other metrics, including the surface temperatures
 (which they show) or the lower tropospheric temperatures (e.g. see

 see Figure 7 TLT

 http://www.ssmi.com/msu/msu_data_description.html.

 Can you comment on the realism of this jump? Would you be willing to let me
 post your reply, if you do comment?

 Most of their trend agreement with the models is due to this single jump.

Josh Willis’s reply [reproduced with his permission]

There is still a good deal of uncertainty in observational estimates of ocean heat content during the 1990s and into the early part of the 2000s. This is because of known biases in the XBT data set, which are the dominant source of ocean temperature data up until 2003 or 2004. Numerous authors have attempted to correct these biases, but substantial difference remain in the “corrected” data.  As a result, the period from 1993 to 2003 still has uncertainties that are probably larger than the natural or anthropogenic signals in ocean heat content that happen over a period of 1 to 3 years.  However, the decadal trend of 10 to 15 years seems to be large enough to see despite the uncertainties. Because Argo begins to become the dominant source of temperature data in about 2004, the period from 2000 to 2005 is especially worriesome because of the transition from an XBT-dominated estimate of ocean heat content.

You might also comment that there is another easily available estimate besides that of Levitus et al. (the one shown in this blog entry).  The other long-term estimate is from Domingues et al. and can be downloaded from CSIRO:

http://www.cmar.csiro.au/sealevel/sl_data_cmar.html

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Q & A Are Water Vapor Feedbacks From Added CO2 Well Understood?

The issue of the relative roles of the human addition of CO2 and the resulting water vapor feedback remains an incompletely understood issue [and thanks to Tom Fuller for encouraging me to address this question].

As reported on Watts Up With That in a post titled NASA says AIRS satellite data shows positive water vapor feedback

 “AIRS temperature and water vapor observations have corroborated climate model predictions that the warming of our climate produced as carbon dioxide levels rise will be greatly exacerbated — in fact, more than doubled — by water vapor,” said Andrew Dessler, a climate scientist at Texas A&M University, College Station, Texas.

Dessler explained that most of the warming caused by carbon dioxide does not come directly from carbon dioxide, but from effects known as feedbacks. Water vapor is a particularly important feedback. As the climate warms, the atmosphere becomes more humid. Since water is a greenhouse gas, it serves as a powerful positive feedback to the climate system, amplifying the initial warming. AIRS measurements of water vapor reveal that water greatly amplifies warming caused by increased levels of carbon dioxide. Comparisons of AIRS data with models and re-analyses are in excellent agreement.

For an observational proof of strong water vapor feedback Dressler recommends

Dessler, A.E., and Sherwood, S.C. A matter of humidity, Science, 323, 1020-1021, DOI: 10.1126/science.1171264, 2009

and

Dessler, A.E., Zhang, Z, and Yang, P. The water-vapor climate feedback inferred from climate fluctuations, 2003-2008, Geophys. Res. Lett., 35, L20704, DOI: 10.1029/2008GL035333, 2008

where the abstract reads

Between 2003 and 2008, the global-average surface temperature of the Earth varied by 0.6°C. We analyze here the response of tropospheric water vapor to these variations. Height-resolved measurements of specific humidity (q) and relative humidity (RH) are obtained from NASA’s satellite-borne Atmospheric Infrared Sounder (AIRS). Over most of the troposphere, q increased with increasing global-average surface temperature, although some regions showed the opposite response. RH increased in some regions and decreased in others, with the global average remaining nearly constant at most altitudes. The water-vapor feedback implied by these observations is strongly positive, with an average magnitude of λ q = 2.04 W/m2/K, similar to that simulated by climate models. The magnitude is similar to that obtained if the atmosphere maintained constant RH everywhere,

while their conclusion is

“The existence of a strong and positive water-vapor feedback means that projected business-as-usual greenhouse gas emissions over the next century are virtually guaranteed to produce warming of several degrees Celsius. The only way that will not happen is if a strong, negative, and currently unknown feedback is discovered somewhere in our climate system.”

The interesting statement that “

Dessler explained that most of the warming caused by carbon dioxide does not come directly from carbon dioxide, but from effects known as feedbacks. Water vapor is a particularly important feedback”

illustrates why skillful climate prediction is such a difficult science issue. Unlike direct radiative forcings, such as a volcanic eruption, in which the diabatic cooling in the troposphere and diabatic heating in the stratospheric can be straightforwardly diagnosed from the amount of ejecta,  the accurate long-term climate change from the human addition of CO2 is a much more complex problem.  The water vapor feedback also involves clouds and precipitation in which phase changes into liquid water and ice occur.

There is a new paper under review that illustrates the inability of the IPCC type models to skillfully predict the water vapor feedback  and thus raises questions on Dressler’s conclusion of model skill (e.g see also Roy Spencer’s research on this topic). This new paper is

Wu, C., T. Zhou, and D.-Z. Sun, 2009: Atmospheric Feedbacks over the Tropical Pacific in Observations and Atmospheric General Circulation Models: An Extended Assessment. J. Climate, Submitted.

The abstract of this paper reads

“The dynamical and radiative feedbacks from the deep convection over the tropical Pacific are quantified using ENSO signal in that region for both the observation and 16 climate models. Different from a previous analysis, we recognize the nonlinear relationship between deep convection and SST over that region, and perform the evaluation using the data from the warm phase and the cold phase separately. We also employ a much longer dataset than the previous analysis. While the results confirm the previous finding that most models underestimate the cloud albedo feedback and overestimate the water vapor feedback, we also show that the discrepancies mainly come from the warm phase, underscoring deep convection as a major source of error. In the cold phase, the models are found to have feedbacks of comparable magnitude and similar spatial pattern to the observations. Examination of the cause of the weaker feedback from cloud albedo in the models suggests that the bias is likely linked to a weaker relationship between the short-wave cloud forcing and the precipitation in the models. In addition, the analysis reveals a systematic feedback bias from the latent heat flux: the models tend to have a too strong positive feedback of latent heat flux over the central Pacific. The results suggest that the deficiency in the atmospheric feedbacks, particularly those from the deep convection, is a possible cause for the excessive cold-tongue in coupled models.”

Excerpts from the conclusion read

“…..our extended analysis further substantiates the suggestion that the excessive cold-tongue problem may have something to do with the weak regulating effect from the model atmosphere—the deep convection in particular. The analysis based on the data from the ENSO warm phase shows that all models — with no exception — have a net atmospheric feedback that is far weaker than that in the observation. While in the cold phase, some models replicate the observed ∂Fs/∂T feedback. Further more, this result underscores the relationship between the underestimate of feedbacks and deep convection.”

“……The results underscore the potentially critical role of deep convection in the large-scale tropical ocean-atmosphere interaction, and the continuing difficulty in capturing this role in the current state-of-the-art climate models.”

Other papers on this topic led by Dr. Sun include

Sun, D.-Z., Y. Yu, and T. Zhang, 2009: Tropical Water Vapor and Cloud Feedbacks in Climate Models: A Further Assessment Using Coupled Simulations. J. Climate, 22, 1287-1304.

Thus, while Andrew Dressler is correct that water vapor feedback is required to significantly amplify the warming effect of added CO2, the water vapor feedback itself is not as well understood as he has indicated. Moreover,  their conclusions indicate that any warming of the atmosphere, such as from black carbon (soot) would also have such a strong positive water vapor feedback.  The Dressler analysis should be generalized to include all positive and negative radiative forcings.

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Q & A On the Adequacy of the Upper Ocean Heat Content to Diagnosis Global Warming

In response to my posts 

Information on the Argo Ocean Monitoring Network 

Comment On EPA Response To Reviewer Comments On Ocean Heat Content 

Further Comments on The Inadequate EPA Response To Reviewer Comments On Ocean Heat Content 

I am providing further information as to why the upper ocean heat content has been adequately sampled particularly since 2005 [and thanks to Leonard Ornstein for encouraging me to do this!]. 

The direct sampling of vertical profiles in the ocean is completed by the Argo network

Spatial plot of Argo network

 The ocean data is less uncertain also because it does not have the larger spatial variations that the land part of the surface temperature. It also does not have much larger diurnal range that occurs on land; e.g. see the spatial distribution of the surface temperature portion of the upper ocean temperature anomalies for December 24 2009; 

Sea Surface Temperature Anomalies

and for the land for November 2009  from the NOAA Terra satellite (see; this website also animates the anomalies for each month back to 2005);  

Land surface temperature anomalies November 2009

 

The MODIS- TERRA sample, of course, is a snapshot of land at a particular time in the diurnal cycle, while the Argo network samples a climate component (the ocean) in which a large daily cycle of temperature does not occur.  

In addition, the upper ocean data is mass weighted with heat content expressed in Joules, while the surface temperatures are not. There is no lags or “heat in the pipeline” when Joules are used as the currency to diagnose the Earth’s radiative imbalance; e.g. see 

Is There Climate Heating In “The Pipeline”? 

Further Comments Regarding The Concept “Heating In The Pipeline” 

Thus the Argo network, along with other observational platforms including GRACE and satellite altimetry; e.g. see provides a much more robust methodology to monitor global warming than the NCDC, GISS and CRU surface temperature data analyses.

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A New Paper On The Role Of Biomass Burning On The Climate System – Tosca Et Al 2009

Papers which document human climate forcings other than CO2 continue to be published.

Today I was alerted to a paper that demonstrates the major role of biomass burning on regional climate. The paper is

M. G. Tosca, J. T. Randerson, C. S. Zender, M. G. Flanner, and P. J. Rasch, 2009: Do biomass burning aerosols intensify drought in equatorial Asia during El Nino? Manuscript prepared for Atmos. Chem. Phys. with version 3.0 of the LATEX class copernicus.cls. Date: 6 August 2009

The abstract reads

“During El Nino years, fires in tropical forests and peatlands in equatorial Asia create large regional smoke clouds. We characterized the sensitivity of these clouds to regional drought, and we investigated their effects on climate by using an atmospheric general circulation model. Satellite observations during 2000-2006 indicated that El Ni˜no-induced regional drought led to increases in fire emissions and, consequently, increases in aerosol optical depths over Sumatra, Borneo and the surrounding ocean. Next, we used the Community Atmosphere Model (CAM) to investigate how climate responded to this forcing. We conducted two 30 year simulations in which monthly fire emissions were prescribed for either a high (El Ni˜no; 1997) or low (La Ni˜na; 2000) fire year using a satellite derived time series of fire emissions. Our simulations included the direct and semi-direct effects of aerosols on the radiation budget within the model. Fire aerosols reduced net shortwave radiation at the surface during August–October by 19.1 ± 12.9 Wm−2 (10%) in a region that encompassed most of Sumatra and Borneo (90E–120E, 5S–5N). The reductions in net radiation cooled sea surface temperatures (SSTs) and land surface temperatures by 0.5 ± 0.3 and 0.4 ± 0.2C during these months. Tropospheric heating from black carbon (BC) absorption averaged 20.5 ± 9.3 Wm−2 and was balanced by a reduction in latent heating. The combination of decreased SSTs and increased atmospheric heating reduced regional precipitation by 0.9 ± 0.6 mmd−1 (10%). The vulnerability of ecosystems to fire was enhanced because the decreases in precipitation exceeded those for evapotranspiration. Together, the satellite and modeling results imply a possible positive feedback loop in which anthropogenic burning in the region intensifies drought stress during El Nino.”

The finding that the tropospheric heating from black carbon absorption averaged 20.5 ± 9.3 Wm−2  is on the same order of the heating rates that we found in our paper

Matsui, T., and R.A. Pielke Sr., 2006: Measurement-based estimation of the spatial gradient of aerosol radiative forcing. Geophys. Res. Letts., 33, L11813, doi:10.1029/2006GL025974.

As we wrote in our paper

“….. the spatial mean and the spatial gradient of the aerosol radiative forcing in comparison with
those of well-mixed green-house gases (GHG). Unlike GHG, aerosols have much greater spatial heterogeneity in their radiative forcing. The heterogeneous diabatic heating can modulate the gradient in horizontal pressure field and atmospheric circulations, thus altering the regional climate.”

The new Tosca et al 2009 further confirms our conclusion on the major role of human aerosols in altering regional climate.

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Yet Another Human Climate Warming Effect In The Arctic – Aircraft Contrails

We have reported on the role of black carbon (soot) as a major non-greenhouse gas human climate forcing in the Arctic; e.g. see

New Study On The Role Of Soot Within the Climate In The Higher Latitudes And On “Global Warming

where an article in Scientific American by David Biello based on a study by Charlie Zender, a climate physicist at the University of California, Irvine stated

“…. on snow—even at concentrations below five parts per billion—such dark carbon triggers melting, and may be responsible for as much as 94 percent of Arctic warming”.

Now we have yet another human climate forcing that was reported by Rex Dalton  of Nature News in the article

How aircraft emissions contribute to warming – Aviation contributes up to one-fifth of warming in some areas of the Arctic.

The article includes the text

“The first analysis of emissions from commercial airline flights shows that they are responsible for 4–8% of surface global warming since surface air temperature records began in 1850 — equivalent to a temperature increase of 0.03–0.06 °C overall.

The analysis, by atmospheric scientists at Stanford University in Palo Alto, California, also shows that in the Arctic, aircraft vapour trails produced 15–20% of warming.”

The photo in the news release has the caption

“Aircraft emissions could be having a dramatic effect on the warming of the Arctic”.

Clearly, as we summarized in our EOS article

Pielke Sr., R., K. Beven, G. Brasseur, J. Calvert, M. Chahine, R. Dickerson, D. Entekhabi, E. Foufoula-Georgiou, H. Gupta, V. Gupta, W. Krajewski, E. Philip Krider, W. K.M. Lau, J. McDonnell,  W. Rossow,  J. Schaake, J. Smith, S. Sorooshian,  and E. Wood, 2009: Climate change: The need to consider human forcings besides greenhouse gases. Eos, Vol. 90, No. 45, 10 November 2009, 413. Copyright (2009) American Geophysical Union

the human role in the climate system is much more than the human emissions of  CO2 and a few other greenhouse gases.

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