A common-sense climate index: Is climate changing noticeably?

We propose an index of climate change based on practical climate indicators such as heating degree days and the frequency of intense precipitation. We find that in most regions the index is positive, the sense predicted to accompany global warming. In a few regions, especially in Asia and western North America, the index indicates that climate change should be apparent already, but in most places climate trends are too small to stand out above year-to-year variability. The climate index is strongly correlated with global surface temperature, which has increased as rapidly as projected by climate models in the 1980s. We argue that the global area with obvious climate change will increase notably in the next few years. But we show that the growth rate of greenhouse gas climate forcing has declined in recent years, and thus there is an opportunity to keep climate change in the 21st century less than “business-as-usual” scenarios.

Climate change is affecting altitudinal migrants and hibernating species

Calendar date of the beginning of the growing season at high altitude in the Colorado Rocky Mountains is variable but has not changed significantly over the past 25 years. This result differs from growing evidence from low altitudes that climate change is resulting in a longer growing season, earlier migrations, and earlier reproduction in a variety of taxa. At our study site, the beginning of the growing season is controlled by melting of the previous winter's snowpack. Despite a trend for warmer spring temperatures the average date of snowmelt has not changed, perhaps because of the trend for increased winter precipitation. This disjunction between phenology at low and high altitudes may create problems for species, such as many birds, that migrate over altitudinal gradients. We present data indicating that this already may be true for American robins, which are arriving 14 days earlier than they did in 1981; the interval between arrival date and the first date of bare ground has grown by 18 days. We also report evidence for an effect of climate change on hibernation behavior; yellow-bellied marmots are emerging 38 days earlier than 23 years ago, apparently in response to warmer spring air temperatures. Migrants and hibernators may experience problems as a consequence of these changes in phenology, which may be exacerbated if climate models are correct in their predictions of increased winter snowfall in our study area. The trends we report for earlier formation of permanent snowpack and for a longer period of snow cover also have implications for hibernating species.

Airborne minerals and related aerosol particles: Effects on climate and the environment

Aerosol particles are ubiquitous in the troposphere and exert an important influence on global climate and the environment. They affect climate through scattering, transmission, and absorption of radiation as well as by acting as nuclei for cloud formation. A significant fraction of the aerosol particle burden consists of minerals, and most of the remainder— whether natural or anthropogenic—consists of materials that can be studied by the same methods as are used for fine-grained minerals. Our emphasis is on the study and character of the individual particles. Sulfate particles are the main cooling agents among aerosols; we found that in the remote oceanic atmosphere a significant fraction is aggregated with soot, a material that can diminish the cooling effect of sulfate. Our results suggest oxidization of SO2 may have occurred on soot surfaces, implying that even in the remote marine troposphere soot provided nuclei for heterogeneous sulfate formation. Sea salt is the dominant aerosol species (by mass) above the oceans. In addition to being important light scatterers and contributors to cloud condensation nuclei, sea-salt particles also provide large surface areas for heterogeneous atmospheric reactions. Minerals comprise the dominant mass fraction of the atmospheric aerosol burden. As all geologists know, they are a highly heterogeneous mixture. However, among atmospheric scientists they are commonly treated as a fairly uniform group, and one whose interaction with radiation is widely assumed to be unpredictable. Given their abundances, large total surface areas, and reactivities, their role in influencing climate will require increased attention as climate models are refined.

The observed global warming record: What does it tell us?

Global, near-surface temperature data sets and their derivations are discussed, and differences between the Jones and Intergovernmental Panel on Climate Change data sets are explained. Global-mean temperature changes are then interpreted in terms of anthropogenic forcing influences and natural variability. The inclusion of aerosol forcing improves the fit between modeled and observed changes but does not improve the agreement between the implied climate sensitivity value and the standard model-based range of 1.5–4.5°C equilibrium warming for a CO2 doubling. The implied sensitivity goes from below the model-based range of estimates to substantially above this range. The addition of a solar forcing effect further improves the fit and brings the best-fit sensitivity into the middle of the model-based range. Consistency is further improved when internally generated changes are considered. This consistency, however, hides many uncertainties that surround observed data/model comparisons. These uncertainties make it impossible currently to use observed global-scale temperature changes to narrow the uncertainty range in the climate sensitivity below that estimated directly from climate models.

Models for stochastic climate prediction

There has been a recent burst of activity in the atmosphere/ocean sciences community in utilizing stable linear Langevin stochastic models for the unresolved degree of freedom in stochastic climate prediction. Here several idealized models for stochastic climate modeling are introduced and analyzed through unambiguous mathematical theory. This analysis demonstrates the potential need for more sophisticated models beyond stable linear Langevin equations. The new phenomena include the emergence of both unstable linear Langevin stochastic models for the climate mean and the need to incorporate both suitable nonlinear effects and multiplicative noise in stochastic models under appropriate circumstances. The strategy for stochastic climate modeling that emerges from this analysis is illustrated on an idealized example involving truncated barotropic flow on a beta-plane with topography and a mean flow. In this example, the effect of the original 57 degrees of freedom is well represented by a theoretically predicted stochastic model with only 3 degrees of freedom.

Drought-induced shift of a forest–woodland ecotone: Rapid landscape response to climate variation

In coming decades, global climate changes are expected to produce large shifts in vegetation distributions at unprecedented rates. These shifts are expected to be most rapid and extreme at ecotones, the boundaries between ecosystems, particularly those in semiarid landscapes. However, current models do not adequately provide for such rapid effects—particularly those caused by mortality—largely because of the lack of data from field studies. Here we report the most rapid landscape-scale shift of a woody ecotone ever documented: in northern New Mexico in the 1950s, the ecotone between semiarid ponderosa pine forest and piñon–juniper woodland shifted extensively (2 km or more) and rapidly (<5 years) through mortality of ponderosa pines in response to a severe drought. This shift has persisted for 40 years. Forest patches within the shift zone became much more fragmented, and soil erosion greatly accelerated. The rapidity and the complex dynamics of the persistent shift point to the need to represent more accurately these dynamics, especially the mortality factor, in assessments of the effects of climate change.

El Niño and the related phenomenon Southern Oscillation (ENSO): The largest signal in interannual climate variation

El Niño and the related phenomenon Southern Oscillation (ENSO) is the strongest signal in the interannual variation of ocean-atmosphere system. It is mainly a tropical event but its impact is global. ENSO has been drawing great scientific attention in many international research programs. There has been an observational system for the tropical ocean, and scientists have known the climatologies of the upper ocean, developed some theories about the ENSO cycle, and established coupled ocean-atmosphere models to give encouraging predictions of ENSO for a 1-year lead. However, questions remain about the physical mechanisms for the ENSO cycle and its irregularity, ENSO-monsoon interactions, long-term variation of ENSO, and increasing the predictive skill of ENSO and its related climate variations.

Abrupt climate change in the computer: Is it real?

Models suggest that dramatic changes in the ocean circulation are responsible for abrupt climate changes during the last ice age and may possibly alter the relative climate stability of the last 10,000 years.