Ron L. Miller

Present-Day Atmospheric Simulations Using GISS ModelE: Comparison to In Situ, Satellite, and Reanalysis Data

Abstract A full description of the ModelE version of the Goddard Institute for Space Studies (GISS) atmospheric general circulation model (GCM) and results are presented for present-day climate simulations (ca. 1979). This version is a complete rewrite of previous models incorporating numerous improvements in basic physics, the stratospheric circulation, and forcing fields. Notable changes include the following: the model top is now above the stratopause, the number of vertical layers has increased, a new cloud microphysical scheme is used, vegetation biophysics now incorporates a sensitivity to humidity, atmospheric turbulence is calculated over the whole column, and new land snow and lake schemes are introduced. The performance of the model using three configurations with different horizontal and vertical resolutions is compared to quality-controlled in situ data, remotely sensed and reanalysis products. Overall, significant improvements over previous models are seen, particularly in upper-atmosphere te...

Simulation of recent northern winter climate trends by greenhouse-gas forcing

The temperature of air at the Earths surface has risen during the past century, but the fraction of the warming that can be attributed to anthropogenic greenhouse gases remains controversial. The strongest warming trends have been over Northern Hemisphere land masses during winter, and are closely related to changes in atmospheric circulation. These circulation changes are manifested by a gradual reduction in high-latitude sea-level pressure, and an increase in mid-latitude sea-level pressure associated with one phase of the Arctic Oscillation (a hemisphere-scale version of the North Atlantic Oscillation). Here we use several different climate-model versions to demonstrate that the observed sea-level-pressure trends, including their magnitude, can be simulated by realistic increases in greenhouse-gas concentrations. Thus, although the warming appears through a naturally occurring mode of atmospheric variability, it may be anthropogenically induced and may continue to rise. The Arctic Oscillation trend is captured only in climate models that include a realistic representation of the stratosphere, while changes in ozone concentrations are not necessary to simulate the observed climate trends. The proper representation of stratospheric dynamics appears to be important to the attribution of climate change, at least on a broad regional scale.

Climate Response to Soil Dust Aerosols

Abstract The effect of radiative forcing by soil dust aerosols upon climate is calculated. Two atmospheric GCM (AGCM) simulations are compared, one containing a prescribed seasonally varying concentration of dust aerosols, and the other omitting dust. Each simulation includes a mixed layer ocean model, which allows SST to change in response to the reduction in surface net radiation by dust. Dust aerosols reduce the surface net radiation both by absorbing and reflecting sunlight. For the optical properties of the dust particles assumed here, the reflection of sunlight is largely offset by the trapping of upwelling longwave radiation, so that the perturbation by dust to the net radiation gain at the top of the atmosphere is small in comparison to the surface reduction. Consequently, the radiative effect of soil dust aerosols is to redistribute heating from the surface to within the dust layer. Beneath the dust layer, surface temperature is reduced on the order of 1 K, typically in regions where deep convect...

Configuration and assessment of the GISS ModelE2 contributions to the CMIP5 archive

We present a description of the ModelE2 version of the Goddard Institute for Space Studies (GISS) General Circulation Model (GCM) and the configurations used in the simulations performed for the Coupled Model Intercomparison Project Phase 5 (CMIP5). We use six variations related to the treatment of the atmospheric composition, the calculation of aerosol indirect effects, and ocean model component. Specifically, we test the difference between atmospheric models that have noninteractive composition, where radiatively important aerosols and ozone are prescribed from precomputed decadal averages, and interactive versions where atmospheric chemistry and aerosols are calculated given decadally varying emissions. The impact of the first aerosol indirect effect on clouds is either specified using a simple tuning, or parameterized using a cloud microphysics scheme. We also use two dynamic ocean components: the Russell and HYbrid Coordinate Ocean Model (HYCOM) which differ significantly in their basic formulations and grid. Results are presented for the climatological means over the satellite era (1980–2004) taken from transient simulations starting from the preindustrial (1850) driven by estimates of appropriate forcings over the 20th Century. Differences in base climate and variability related to the choice of ocean model are large, indicating an important structural uncertainty. The impact of interactive atmospheric composition on the climatology is relatively small except in regions such as the lower stratosphere, where ozone plays an important role, and the tropics, where aerosol changes affect the hydrological cycle and cloud cover. While key improvements over previous versions of the model are evident, these are not uniform across all metrics.

Volcanic and Solar Forcing of Climate Change during the Preindustrial Era

The climate response to variability in volcanic aerosols and solar irradiance, the primary forcings during the preindustrial era, is examined in a stratosphere-resolving general circulation model. The best agreement with historical and proxy data is obtained using both forcings, each of which has a significant effect on global mean temperatures. However, their regional climate impacts in the Northern Hemisphere are quite different. While the short-term continental winter warming response to volcanism is well known, it is shown that due to opposing dynamical and radiative effects, the long-term (decadal mean) regional response is not significant compared to unforced variability for either the winter or the annual average. In contrast, the long-term regional response to solar forcing greatly exceeds unforced variability for both time averages, as the dynamical and radiative effects reinforce one another, and produces climate anomalies similar to those seen during the Little Ice Age. Thus, long-term regional changes during the preindustrial appear to have been dominated by solar forcing.

Climate simulations for 1880–2003 with GISS modelE

We carry out climate simulations for 1880–2003 with GISS modelE driven by ten measured or estimated climate forcings. An ensemble of climate model runs is carried out for each forcing acting individually and for all forcing mechanisms acting together. We compare side-by-side simulated climate change for each forcing, all forcings, observations, unforced variability among model ensemble members, and, if available, observed variability. Discrepancies between observations and simulations with all forcings are due to model deficiencies, inaccurate or incomplete forcings, and imperfect observations. Although there are notable discrepancies between model and observations, the fidelity is sufficient to encourage use of the model for simulations of future climate change. By using a fixed well-documented model and accurately defining the 1880–2003 forcings, we aim to provide a benchmark against which the effect of improvements in the model, climate forcings, and observations can be tested. Principal model deficiencies include unrealistically weak tropical El Nino-like variability and a poor distribution of sea ice, with too much sea ice in the Northern Hemisphere and too little in the Southern Hemisphere. Greatest uncertainties in the forcings are the temporal and spatial variations of anthropogenic aerosols and their indirect effects on clouds.

Forcings and chaos in interannual to decadal climate change

We investigate the roles of climate forcings and chaos (unforced variability) in climate change via ensembles of climate simulations in which we add forcings one by one. The experiments suggest that most interannual climate variability in the period 1979–1996 at middle and high latitudes is chaotic. But observed SST anomalies, which themselves are partly forced and partly chaotic, account for much of the climate variability at low latitudes and a small portion of the variability at high latitudes. Both a natural radiative forcing (volcanic aerosols) and an anthropogenic forcing (ozone depletion) leave clear signatures in the simulated climate change that are identified in observations. Pinatubo aerosols warm the stratosphere and cool the surface globally, causing a tendency for regional surface cooling. Ozone depletion cools the lower stratosphere, troposphere and surface, steepening the temperature lapse rate in the troposphere. Solar irradiance effects are small, but our model is inadequate to fully explore this forcing. Well-mixed anthropogenic greenhouse gases cause a large surface wanning that, over the 17 years, approximately offsets cooling by the other three mechanisms. Thus the net calculated effect of all measured radiative forcings is approximately zero surface temperature trend and zero heat storage in the ocean for the period 1979–1996. Finally, in addition to the four measured radiative forcings, we add an initial (1979) disequilibrium forcing of +0.65 W/m2. This forcing yields a global surface warming of about 0.2°C over 1979–1996, close to observations, and measurable heat storage in the ocean. We argue that the results represent evidence of a planetary radiative imbalance of at least 0.5° W/m2; this disequilibrium presumably represents unrealized wanning due to changes of atmospheric composition prior to 1979. One implication of the disequilibrium forcing is an expectation of new record global temperatures in the next few years. The best opportunity for observational confirmation of the disequilibrium is measurement of ocean temperatures adequate to define heat storage.

Amplification of the North American “Dust Bowl” drought through human-induced land degradation

The “Dust Bowl” drought of the 1930s was highly unusual for North America, deviating from the typical pattern forced by “La Nina” with the maximum drying in the central and northern Plains, warm temperature anomalies across almost the entire continent, and widespread dust storms. General circulation models (GCMs), forced by sea surface temperatures (SSTs) from the 1930s, produce a drought, but one that is centered in southwestern North America and without the warming centered in the middle of the continent. Here, we show that the inclusion of forcing from human land degradation during the period, in addition to the anomalous SSTs, is necessary to reproduce the anomalous features of the Dust Bowl drought. The degradation over the Great Plains is represented in the GCM as a reduction in vegetation cover and the addition of a soil dust aerosol source, both consequences of crop failure. As a result of land surface feedbacks, the simulation of the drought is much improved when the new dust aerosol and vegetation boundary conditions are included. Vegetation reductions explain the high temperature anomaly over the northern U.S., and the dust aerosols intensify the drought and move it northward of the purely ocean-forced drought pattern. When both factors are included in the model simulations, the precipitation and temperature anomalies are of similar magnitude and in a similar location compared with the observations. Human-induced land degradation is likely to have not only contributed to the dust storms of the 1930s but also amplified the drought, and these together turned a modest SST-forced drought into one of the worst environmental disasters the U.S. has experienced.

Constraining the magnitude of the global dust cycle by minimizing the difference between a model and observations

Current estimates of global dust emission vary by over a factor of two. Here, we use multiple data types and a worldwide array of stations combined with a dust model to constrain the magnitude of the global dust cycle for particles with radii between 0.1 and 8 μm. An optimal value of global emission is calculated by minimizing the difference between the model dust distribution and observations. The optimal global emission is most sensitive to the prescription of the dust source region. Depending upon the assumed source, the agreement with observations is greatest for global, annual emission ranging from 1500 to 2600 Tg. However, global annual emission between 1000 and 3000 Tg remains in agreement with the observations, given small changes in the method of optimization. Both ranges include values that are substantially larger than calculated by current dust models. In contrast, the optimal fraction of clay particles (whose radii are less than 1 μm) is lower than current model estimates. The optimal solution identified by a combination of data sets is different from that identified by any single data set and is more robust. Uncertainty is introduced into the optimal emission by model biases and the uncertain contribution of other aerosol species to the observations.

A general circulation model study on the interannual variability of soil dust aerosol

To assess interannual soil dust aerosol variability, we computed dust as a tracer in the Goddard Institute for Space Studies general circulation model. Comparisons of dust model results with results from an off-line tracer model, satellite retrievals, and ground observations show mostly good agreement, but also reveal problems with the model results and difficulties with such comparisons. Two 15–year runs with prescribed sea surface temperatures were carried out, one with identical dust sources for each year and one with varying dust sources in order to investigate the contribution of dust sources and transport to the variability of dust concentrations in different regions. Specifically for the North Atlantic and the Mediterranean region, 70–90% of the dust variability is attributable to transport variability. Correlation coefficients between dust concentrations with precipitation and surface winds were calculated to find controlling factors for dust concentration for different regions of the world.