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Variations in both the total flux, and in just the 13 flux that extends into the heliosphere (the “open” flux) are estimated, arising from the deposition of bipolar 14 magnetic regions (active regions) and smaller-scale ephemeral regions on the Sun’s surface, in strengths and 15 numbers proportional to the sunspot number. The open flux compares reasonably well with the geomagnetic 16 and cosmogenic isotopes whose variations arise, in part, from heliospheric modulation.

Although the instruments are designed 34 to the same specifications for each satellite, MSU instruments have had relative biases of the order 1-2°C. 35 As the orbits have tended to drift, MSU instruments measure at systematically later local times over a 36 satellite’s lifetime requiring adjustments to be made for the diurnal cycle, a procedure accommodated 37 automatically in ERA-40 by inserting the observation at the appropriate time.

The Kwajalein data also suggest increased variability in sea level after the mid-1970s, 14 consistent with the trend to more frequent, persistence and intense ENSO events since the mid 1970’s -1 15 (Folland et al., 2001). For the Kwajalein record, the rate of relative sea level rise is 1.3 ± 0.4 mm yr (all 16 error estimates are one standard deviation) and after correction for GIA land motions and isostatic response -1 17 to atmospheric pressure changes is 1.9 ± 0.4 mm yr.

Romanou et al. (2005) compare 22 the regional surface irradiance changes in a multi-model mean from a subset of the AR4 models shown here. 23 They demonstrate that some of the regional trends present in the data are indeed present in the models, 24 though the regional trends in the model-mean data set are smaller than those in the satellite-derived data set. 25 26 Figures 9.2.1 and 9.2.2 also show that the spatial signature of a climate model’s response is seldom like that 27 of the forcing. This comes about because climate system feedbacks vary spatially. For example, sea ice 28 albedo feedbacks tend to enhance the high latitude response of both a positive forcing, such as that by CO2, 29 and a negative forcing such as that by sulphate aerosol (e.g., Rotstayn and Penner, 2001; Mitchell et al., 30 2001).

Walsh et al 50 2004 obtained for 3 × CO2 condition, a 56% increase in storms of maximum windspeed of greater than 30 m -1 51 s . However, in general Walsh (2004) concluded that there is no clear picture with respect to regional 52 changes in frequency and movement, but increases in intensity are indicated.

By 1990, it was clear that tropospheric ozone had increased over the 20th 23 century and stratospheric ozone had decreased since 1980, but these radiative forcings were not evaluated. 24 Neither was the effect of anthropogenic sulfate aerosols, except to note in the FAR that "it is conceivable 25 that this radiative forcing has been of a comparable magnitude, but of opposite sign, to the greenhouse 26 forcing earlier in the century." Reflecting in general the community’s concerns about this relatively new 27 measure of climate forcing, RF bar charts appear only in the underlying FAR chapters, but not in the FAR 28 Summary.

At this time and in parallel with the growth rate anomaly in the methane concentration an anomaly 1312 36 was observed in methane’s C/C ratio at surface sites in the Southern Hemisphere. This was attributed to a 37 decrease in emissions from an isotopically heavy source such as biomass burning (Lowe et al., 1997; Mak et 38 al., 2000).

IPCC/TEAP (2005) concluded that the 37 combined CO2-equivalent emissions of CFCs, HCFCs, and HFCs decreased from a peak of about 7.5 -1-1 38 GtCO2-eq yr in the late 1980s to about 2.5 GtCO2-eq yr by the year 2000, corresponding to about 10% of 39 that year’s CO2 emission due to global fossil fuel burning. 40 41 Measurements of the CFCs and HCFCs, summarized in Figure 2.7, are available from the AGAGE network 42 (Prinn et al., 2000; Prinn et al., 2005b) and the GMD network (Montzka et al., 1999 updated; Thompson et 43 al., 2004).

Second-Order Draft Chapter 2 IPCC WG1 Fourth Assessment Report 1 obtained is consistent with Twomey’s hypothesis and formula; however, when plotted on a log-log graph, 2 the slope obtained is smaller than previous estimates (0.5 versus 0.7-0.8; Kaufman et al, 1991), but larger 3 than the 0.26 value obtained by Martin et al (1994).

This treatment includes the main 38 influences on bT, but still excludes the time-dependent effects of glacier dynamics. 39 40 The geometrical and dynamical approaches of Raper et al. (2000) and Oerlemans et al. (1998) cannot be 41 applied to all the world’s glaciers individually as the required data are unknown for the vast majority of 42 them. Instead, it might be applied to a representative ensemble derived from statistics of size distributions of 43 G&IC.