Further Confirmation Of The Misinterpretation Of Miniumum Land Surface Temperature Trends By NCDC, CRU, GISS And BEST As Part Of A Diagnostic Of Global Warming

In post

Guest Post By Richard McNider On The New JGR – Atmosphere Article “Response And Sensitivity Of The Nocturnal Boundary Layer Over Land To Added Longwave Radiative Forcing”

Dick McNider reported in our new paper

McNider, R.T., G.J. Steeneveld, B. Holtslag, R. Pielke Sr, S.   Mackaro, A. Pour Biazar, J.T. Walters, U.S. Nair, and J.R. Christy, 2012: Response and sensitivity of the nocturnal boundary layer over   land to added longwave radiative forcing. J. Geophys. Res., doi:10.1029/2012JD017578, in press.

on a likely warm bias in multi-decadal trends of minimum land temperatures when they are used as part of the diagnosis of global warming.

Anthony Watts had an excellent follow-up in his post

Important New Paper on the Nocturnal Boundary Layer, Mixing, and Radiative Forcing as it applies to GHCN weather stations

In our earlier paper

Klotzbach, P.J., R.A. Pielke Sr., R.A. Pielke Jr.,  J.R. Christy, and R.T. McNider, 2009: An alternative explanation for differential temperature trends at the  surface and in the lower troposphere. J. Geophys. Res., 114, D21102, doi:10.1029/2009JD011841.

we wrote that [highlight added]

“…the minimum temperature occurs in the shallow, cool nocturnal boundary layer (NBL). The NBL is a delicate, nonlinear dynamical system that may be disrupted by increases in surface roughness, surface heat fluxes or radiative forcing. Under strong cooling and light winds, the surface becomes decoupled from the warm air above. A small change in any of these may then trigger coupling, or the downward mixing of warmer air which significantly raises minimum temperature readings. This disruption need occur only a few extra times per year to generate a warmer minimum temperature trend over time. In fact nighttime temperatures are more about the state of turbulence in the atmosphere than the temperature in the deep atmosphere. As an example, the minimum temperature will be quite different based on factors that influence turbulence, such as roughness or wind speed even if the temperature of the deep atmosphere aloft is the same [McNider et al., 1995; Shi et al., 2005]. Candidates for increasing these decoupling events are buildings (roughness), surface heat capacity changes such as irrigated deserts or pavement (heat flux), increased water vapor and increased aerosols (radiative forcing). All of these decoupling events have been observed [Pielke et al., 2007a, 2007b; Christy et al., 2009]. Increases in greenhouse gases can also cause a disruption of the nocturnal boundary layer as enhanced downward radiation destabilizes the NBL allowing more warm air from aloft to be mixed to the surface [Walters et al., 2007]. However, any upward trends in nighttime temperatures [from the above effects] are due to this redistribution of heat and should not be interpreted as an increased accumulation of heat [Walters et al., 2007].

Because the land surface temperature record does in fact combine temperature minimum and maximum temperature measurements, where there has been a reduction in nighttime cooling due to this disruption, the long-term temperature record will have a warm bias. The warm bias will represent an increase in measured temperature because of a local redistribution of heat, however it will not represent an increase in the accumulation of heat in the deep atmosphere. The reduction in nighttime cooling that leads to this bias may indeed be the result of human interference in the climate system (i.e., local effects of increasing greenhouse gases, surface conditions, aerosols or human effects on cloud cover), but through a causal mechanism distinct from the large-scale radiative effects of greenhouse gases. Local land use surface changes in which the local surface roughness and local heat release are altered [see also de Laat, 2008] will also result in a warming bias at night if the local vertical temperature lapse rate is made less stable over time.

The warm bias in the temperature data would most likely be in evidence over land areas where larger vertical temperature stratification occurs near the ground along with a reduction of the atmospheric cooling rate. This effect will be largest in the higher latitudes, especially in minimum temperatures during the winter months, since any reduction in the cooling rate of the atmosphere will result in a particularly large temperature increase near the ground surface in this strongly stably stratified boundary layer.

The new McNider et al 2012 paper, documents in detail why an increase of minimum temperature over time can occur due to changes in vertical turbulent mixing of heat, even without any change in temperatures elsewhere in the troposphere.

In terms of global warming, as reported before on this weblog; see

Significance And Correction Of Misinterpretation By The Media Of The Zhou Et Al 2012 Paper “Impacts Wind Farms On Land Surface Temperature

where we wrote

The global average surface temperature anomalies are computed by the formula

ΔT (global average) = ΔT(ocean average) times fraction of the globe covered by ocean + ΔT (land average) times the fraction of the globe covered by land (including regions with ice sheets).

The value of ΔT (land average) is computed by

ΔT (land average) = ∑ Δ [Tmax + Tmin]/2

where Δ [Tmax + Tmin]/2 is the mean temperature anomaly, such as used in the BEST study, and by NCDC, CRU and GISS;  focused on 2m above the surface ……”

ΔTmin =  ΔTmin (a spatially representative temperature trend from “global warming” or “global cooling”) + ΔTmin (a local change due to changes in vertical mixing in the lowest levels of the atmosphere) + ΔTmin (due to other local effects usch as station siting – Fall et al 2011; see also Pielke st al 2007).

It is important to note that ΔTmin (a local change due to changes in vertical mixing in the lowest levels of the atmosphere) can occur even in pristine locations due to changes in long wave cooling at night (from alterations in cloudiness, water vapor and/or CO2).

In terms of an order of estimate of this bias  (e.g. see Klotzbach et al 2012a), it is on the order of a tenths of a degree Celcius per decade warm bias in the land analyses reported by in the NCDC, GISS, CRU and BEST data.

In other words, the magnitude of multi-decadal land temperature trends, as a diagnostic of global warming, as reported by NCDC, GISS, CRU and BEST for the last several decades is significantly overstatedThis organizations are miscommunicating the complete explanation for observed surface temperature trends over land.

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