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Held and Soden [2006] clearly show that, forthe computer models used in AR4, atmospheric WVincreases with surface temperature according to theClausius-Clapeyron (CC) equation; precipitationand evaporation increase at a rate significantly lessthan the CC relationship. However, satelliteobservations suggest that actual precipitationincreased twice as fast as models predict [Wentz etal. 2007], indicating the potential of global warmingto cause drought may be less than has been feared.Negative Feedbacks from Water Vapor! Computer models do not simulate apossible negative feedback from watervapor.The models also have problems describing thelatitude and altitude distribution of water vapor. Inparticular, the values of upper-troposphere (UT)water vapor control the heat loss to space andthereby exert an all-important control on the Earth’ssurface temperature. Measurements may give meanvalues of UT water vapor; but since emission variesas the fourth power of temperature, one cannotthereby deduce the average value of outgoinglong-wave radiation (OLR).Since water vapor (WV) is the most importantatmospheric greenhouse gas, it is difficult to explainin simple terms how it can also act to produce anegative feedback, i.e., to reduce the presumedwarming effects of CO 2 . In fact, current GH modelsall incorporate a positive feedback from an increasein WV.However, Richard Lindzen [1990] and others[Ellsaesser 1984] have pointed to ways wherebyWV can produce a negative rather than a positivefeedback. It requires a mechanism for reducing theconcentration of WV in the upper troposphere (UT).Empirical evidence seems to support such adistribution of UTWV [Spencer et al. 2007].The negative feedback mechanism works asfollows [see Figure 15]: With normal values ofUTWV, IR emission into space (called the outgoinglong-wave radiation – OLR) takes place at the lowtemperature of the UT. But if the UT is dry, then theOLR emission from WV bands originates from themuch warmer boundary layer in the lowertroposphere (LT). The emission from the surfacetakes place in the atmospheric window (between 8to 12 microns) and depends on the temperature ofthe surface, which radiates as a black body.Note, however, that the total value of OLR mustFigure 15: The cartoon suggests that drying of the uppertroposphere would lead to a negative feedback reducing theeffects of increasing CO 2 . The (purple) broad band shows theatmospheric infrared emission into space (outgoing long-waveradiation – OLR). The upper boundary corresponds to a dryupper troposphere (UT); the lower boundary corresponds to amoist UT. The peaked red band shows emission from thesurface into space through the atmospheric window (8 to 12microns). To keep total OLR constant, the lower boundary ofthis band would correspond to a dry UT, while the upperboundary would correspond to a moist UT. This change ininfrared emission from the surface suggests a correspondingtemperature change – which ultimately reduces the warmingfrom increased levels of CO 2 .roughly balance the incoming absorbed solarradiation. In the case of a moist UT, more of theOLR radiation will originate from the Earth’ssurface; in the case of a dry UT the opposite is true.Therefore, a dry UT corresponds to a warmersurface; a moist UT corresponds to a cooler surface:Hence the distribution of WV can produce anegative feedback – provided the increasing CO 2causes a particular distribution of WV.! Computer models do not explain manyfeatures of the Earth’s observed climate.Models overestimate the land surface insolation,(the amount of solar radiation striking the surface)when compared to a dataset of 760worldwide-distributed surface stations from theGlobal Energy Balance Archive [Wild 2005a]. Thediscrepancy is 9 watts per square meter (W/m 2 ) onaverage, several times the estimated GH forcing. Itsuggests uncertainties in partitioning of solar energybetween surface and atmospheric absorption.14
Figure 16: A result from the U.S. National Assessment of Climate Change [NACC 2000]: Expected precipitationfor 18 regions of the United States, according to the Hadley model and Canadian model. Note the huge differencesbetween the two model results in magnitude and even in sign. For example, the Dakotas (Souris - Red - Rainy) canturn either into a swamp or into a desert, depending on which climate model is used.Beyond this, the GH models do not explainmany other features of Earth’s observed climate.For instance, the history of polar temperatures, thecooling trend of the Antarctic, the seesaw effect ofNorthern Hemisphere/Southern Hemisphere linkedto ocean circulation, and features such the observedMadden-Julian Oscillation in the tropics, the NorthAtlantic Oscillation, the Atlantic Multi-decadalOscillation [Schlesinger and Ramankutty 1994], thePacific Decadal Oscillation [Mantua 1997], and ElNiño occurrences.In general, climate models do rather poorly inpredicting precipitation, particularly on a regionallevel (see, for example, Figure 16). Nor have theybeen successful in predicting such major climatephenomena as ENSO or the Indian Monsoon.“Climate models are woefully inadequate tosimulate and predict Asian summer Monsoonprecipitation. The Asian summer Monsoon is thelargest single abnormality in the global climatesystem” [Shukla 2007]. Kriplani et al. [2003]conclude that the Indian Monsoon shows decadalvariability with about 30-year cycles of above-andbelow-normalrainfall and is not affected by globalwarming at this time.! Computer models cannot produce reliablepredictions of regional climate change.Computer models are notoriously inadequate insimulating or projecting regional effects,particularly when it comes to precipitation. This factcan be demonstrated most clearly in theU.S.-National Assessment of Climate Change report[NACC 2000] that used both the Hadley model andCanadian model to project future changes for 18regions of the United States. As can be seen fromFigure 16, in about half the regions the two modelsgave opposite results. For example, the Dakotas15
Page 1 and 2: Nature, Not Human Activity,Rules th
Page 3 and 4: ForewordIn his speech at the United
Page 5 and 6: group of activists wrote the all-im
Page 7: that action must be taken to reduce
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Page 15 and 16: Global and U.S. Mean Surface Temper
Page 19 and 20: verification of the IPCC’s analys
Page 21 and 22: ! Global warming prior to 1940 was
Page 23: Lockwood and Fröhlich [2007] have
Page 27 and 28: Sea Level Since Last Glacial Maximu
Page 29 and 30: It is likely that actual SL observa
Page 31 and 32: Figure 21: CO 2 levels versus latit
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Page 35 and 36: ates were linearly related to avera
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Page 39 and 40: About the ContributorsAnderson, War
Page 41 and 42: ReferencesAnonymous 1994. IPCC’s
Page 43 and 44: Keatinge W.R. et al, 2000. Heat rel
Page 45 and 46: Rahmstorf, S., et al. 2007. Recent
Page 47 and 48: AcronymsAGW Anthropogenic Global Wa
Page 49 and 50: Labohm, Hans, Simon Rozendaal, and

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