Climate Change 2001: The Scientific Basis

4.4.4 Model Simulations of Perturbed and Y2100 Atmospheres

The OxComp workshop also defined a series of perturbations to the Y2000 atmosphere for which the models reported the monthly averaged 3-D distribution of O₃ abundances and the budget for CH₄, specifically the loss due to reaction with tropo-spheric OH. From these diagnostics, the research group at Oslo calculated the change in global mean tropospheric O₃ (DU) and in OH (%) relative to Y2000, as shown in Table 4.11. For each model at every month, the “troposphere” was defined as where O₃ abundances were less than 150 ppb in the Y2000 simulation, a reasonably conservative diagnostic of the tropopause (see Logan, 1999). Because O₃ is more effective as a greenhouse gas when it lies above the surface boundary layer (SAR; Hansen et al., 1997a; Prather and Sausen, 1999; Chapter 6 of this report), the model study diagnosed the O₃ change occurring in the 0 to 2 km layers of the model. This amount is typically 20 to 25% of the total change and is consistent across models and types of perturbations here.

Table 4.11: Changes in tropospheric O₃ (DU) and OH (%) relative to year 2000 for various perturbations to the atmosphere. Individual values calculated with chemistry transport-models (CTMs) plus the average values adopted for this report (TAR).

	Y2000	A2x: Y2100 -Y2000
	+10% CH₄	All A2x	–NO_x	–NO_x–VOC–CH₄

CTM	Case A	Case B	Case C	Case D

Effective^a tropospheric O₃ change (DU):

HGIS		26.5
GISS		25.2
IASB	0.66	18.9	9.2	0.4
KNMI	0.63	18.0	9.0
MOZ1		16.6
MOZ2		22.4
MPIC	0.40
UCI	0.69	23.3	10.2	2.8
UIO	0.51	26.0	6.0	2.1
UKMO		18.9	4.6	3.1
ULAQ	0.85	22.2	14.5	5.9
TAR^b	0.64	22.0	8.9	2.0

Tropospheric OH change (%)

IASB	-2.9%	-7%
KNMI	-3.3%	-25%	-41%
MOZ1		-21%
MOZ2		-18%
MPIC	-2.7%
UCI	-3.2%	-15%	-39%	-16.0%
UIO	-3.1%	-6%	-37%	-12.3%
UKMO	-2.9%	-12%	-37%	-10.8%
ULAQ	-2.7%	-17%	-43%	-22.0%
TAR^b	-3.0%	-16%	-40%	-14%

Model results from OxComp workshop; all changes (DU for O₃ and % for OH) are relative to the year Y2000. Tropospheric mean OH is weighted by CH₄ loss rate. Mean O₃ changes (all positive) are derived from the standard reporting grid on which the CTMs interpolated their results. See Table 4.10 for the model key. The different cases include (A) a 10% increase in CH₄ to 1,920 ppb and (B) a full 2100 simulation following SRES draft marker scenario A2 (based on February 1999 calculations for preliminary work of this report). Case C drops the NO_x missions back to Y2000 values; and case D drops NO_x , VOC, and CH₄ likewise. Adopted CH₄ abundances and pollutant emissions from Y2000 to Y2100 are: Y2000: CH₄ =1,745 ppb, e-NO_x =32.5 TgN/yr, e-CO=1,050 Tg/yr, e-VOC=150 Tg/yr. Y2100: CH₄ =4,300 ppb, e-NO_x =110.0 TgN/yr, e-CO=2,500 Tg/yr, e-VOC=350 Tg/yr. ^aN.B. Unfortunately, after the government review it was discovered that the method of integrating O₃ changes on the reporting grid was not well defined and resulted in some unintentional errors in the values reported above. Thus, the values here include in effect the O₃ increases predicted/expected in the lower stratosphere in addition to the troposphere. In terms of climate change, use of these values may not be unreasonable since O₃ changes in the lower stratosphere do contribute to radiative forcing. Nevertheless, the troposphere-only changes are about 25 to 33% less than the values above. (tropospheric O₃) = +5.0 x ln(CH₄) + 0.125 x (e-NO_x) + 0.0011 x (e-CO) + 0.0033 x (e-VOC) in DU. ^bTAR adopts the weighted average for cases A to D as shown, where the weighting includes factors about model formulation and comparison with observations. A linear interpolation is derived from these results and used in the scenarios: ln(tropospheric OH) = -0.32 x ln(CH₄) + 0.0042 x (e-NO_x) - 1.05e-4 x (e-CO) - 3.15e-4 x (e-VOC). (effective O₃) = +6.7 x ln(CH₄) + 0.17 x (e-NO_x) + 0.0014 x (e-CO) + 0.0042 x (e-VOC) in DU.

Case A, a +10% increase in CH₄ abundance for Y2000, had consistent results across reporting models that differed little from the SAR’s Delta-CH₄ model study. The adopted values for this report are -3% change in OH and +0.64 DU increase in O₃, as listed under the “TAR” row in Table 4.11.
The Y2100 atmosphere in OxComp mimics the increases in pollutant emissions in SRES A2p scenario from year 2000 to year 2100 with the year 2100 abundance of CH₄, 4,300 ppb, calculated with the SAR technology and named here A2x. (See discussion in section 4.4.5; for the SAR, only the CH₄-OH feedback is included.) The long-lived gases CO₂ and N₂O have no impact on these tropospheric chemistry calculations as specified.

Cases B-C-D are a sequence of three Y2100 atmospheres based on A2x: Case B is the full Y2100-A2x scenario; Case C is the same Y2100-A2x scenario but with unchanged (Y2000) NO_x emissions; and Case D is the same but with NO_x, VOC and CH₄ unchanged since Y2000 (i.e., only CO emissions change). Case B (Y2100-A2x) results are available from most OxComp participants. All models predict a decrease in OH, but with a wide range from -6 to -25%, and here we adopt a decrease of -16%. Given the different distributions of the O₃ increase from the OxComp models (Figures 4.12-13), the increases in globally integrated O₃ were remarkably consistent, ranging from +16.6 to +26.5 DU, and we adopt +22 DU. Without the increase in NO_x emissions (Case C) the O₃ increase drops substantially, ranging from +4.6 to +14.5 DU; and the OH decrease is large, -37 to -43%. With only CO emissions (Case D) the O₃ increase is smallest in all models, +0.4 to +5.9 DU.

This report adopts a weighted, rounded average of the changes in OH and O₃ for cases A-D as shown in the bold rows in Table 4.11. The weighting includes factors about model formulation and comparison with observations. This sequence of calculations (Y2000 plus Cases A-B-C-D) allows us to define a simple linear relationship for the absolute change in tropospheric O₃ and the relative change in OH as a function of the CH₄ abundance and the emission rates for NO_x, for CO, and for VOC. These two relationships are given in Table 4.11. Since the change in CH₄ abundance and other pollutant emissions for Y2100-A2x are among the largest in the SRES scenarios, we believe that interpolation of the O₃ and OH changes for different emission scenarios and years introduces little additional uncertainty.

The possibility that future emissions of CH₄ and CO overwhelm the oxidative capacity of the troposphere is tested (Case E, see Table 4.3 footnote c) with a +10% increase in CH₄ on top of Y2100-A2x (Case B). Even at 4,300 ppb CH₄, the decrease in OH calculated by two CTMs is only slightly larger than in Case A, and thus, at least for SRES A2p, the CH₄-feedback factor does not become as large as in the runaway case (Prather, 1996). This report assumes that the CH₄ feedback remains constant over the next century; however, equivalent studies for the low-NO_x future scenarios are not assessed.

The apparent agreement on predicting the single global, annual mean tropospheric O₃ increase, e.g., Case B in Table 4.11, belies the large differences as to where this increase occurs and what is its peak magnitude. The spatial distributions of the tropospheric O₃ increases in July for Case B are shown in Figure 4.12 (latitude by altitude zonal average abundance, ppb) and Figure 4.13 (latitude by longitude column density, DU) for nine CTMs. The largest increase in abundance occurs near the tropopause at 40°N latitude; yet some models concentrate this increase in the tropics and others push it to high latitudes. In terms of column density, models generally predict large increases along the southern edge of Asia from Arabia to eastern China; although the increases in tropical, biomass-burning regions varies widely from model to model.

Figure 4.12: July zonal mean increase in tropospheric O₃ (ppb) as a function of latitude and altitude from Y2000 to Y2100 adopting SRES A2p projections for CH₄, CO, VOC, and NO_x. Results are shown for a sample of the chemistry-transport models (CTM) participating in IPCC OxComp workshop. Increases range from 0 to more than 80 ppb. Changes in the stratosphere (defined as O₃ > 150 ppb in that model’s Y2000 simulation) are masked off, as are also regions in the upper troposphere for some CTMs (UKMO, HGIS) where O₃ is not explicitly calculated. See Table 4.10 for participating models.

Figure 4.13: July column increase in tropospheric O₃ (DU) as a function of latitude and longitude from Y2000 to Y2100 adopting SRES A2p projections for CH₄ , CO, VOC, and NO_x is shown for some OxComp simulations. See Figure 4.12.

This similarity in the total, but difference in the location, of the predicted O₃ increases is noted in Isaksen and Jackman (1999) and is probably due to the different transport formulations of the models as documented in previous CTM intercomparisons (Jacob et al., 1997). Possibly, the agreement on the average O₃ increase may reflect a more uniform production of O₃ molecules as a function of NO_x emissions and CH₄ abundance across all models. Nevertheless, the large model range in the predicted patterns of O₃ perturbations leads to a larger uncertainty in climate impact than is indicated by Table 4.11.

The projected increases in tropospheric O₃ under SRES A2 and A1FI will have serious consequences on the air quality of most of the Northern Hemisphere by year 2100. Taking only the global numbers from Figure 4.14, the mean abundance of tropospheric O₃ will increase from about 52 ppb (typical mid-tropospheric abundances) to about 84 ppb in year 2100. Similar increases of about +30 ppb are seen near the surface at 40°N on a zonal average in Figure 4.12. Such increases will raise the “background” levels of O₃ in the northern mid-latitudes to close to the current clean-air standard.

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