The role of the basic state in the ENSO-monsoon relationship and implications for predictability

The impact of systematic model errors on a coupled simulation of the Asian Summer monsoon and its interannual variability is studied. Although the mean monsoon climate is reasonably well captured, systematic errors in the equatorial Pacific mean that the monsoon-ENSO teleconnection is rather poorly represented in the GCM. A system of ocean-surface heat flux adjustments is implemented in the tropical Pacific and Indian Oceans in order to reduce the systematic biases. In this version of the GCM, the monsoon-ENSO teleconnection is better simulated, particularly the lag-lead relationships in which weak monsoons precede the peak of El Nino. In part this is related to changes in the characteristics of El Nino, which has a more realistic evolution in its developing phase. A stronger ENSO amplitude in the new model version also feeds back to further strengthen the teleconnection. These results have important implications for the use of coupled models for seasonal prediction of systems such as the monsoon, and suggest that some form of flux correction may have significant benefits where model systematic error compromises important teleconnections and modes of interannual variability

Origins of the midlatitude Pacific decadal variability

Analysis of multiple climate simulations shows much of the midlatitude Pacific decadal variability to be composed of two simultaneously occurring elements: One is a stochastically driven, passive ocean response to the atmosphere while the other is oscillatory and represents a coupled mode of the ocean‐atmosphere system. ENSO processes are not required to explain the origins of the decadal variability. The stochastic variability is driven by random variations in wind stress and heat flux associated with internal atmospheric variability but amplified by a factor of 2 by interactions with the ocean. We also found a coupled mode of the ocean‐atmosphere system, characterized by a significant power spectral peak near 1 cycle/20 years in the region of the midlatitude North Pacific and Kuroshio Extension. Ocean dynamics appear to play a critical role in this coupled air/sea mode

Multi-model trends in the Sahara induced by increasing CO2

[1] Five of eighteen climate system models participating the Coupled Model Intercomparison Project (CMIP) are chosen here for analysis based on their ability to simulate a reasonable present-day climatology of the Sahara Desert with similar rainfall distributions and meridional boundaries as in the observational data. When CO 2 concentration is increased at one percent per year for 80 years in these models the Sahara moves north, becomes hotter and dries. Compared to the 40-year control run climatology, the mean average northward shift is around 0.55°latitude and the surface temperature is about 1.8°C warmer at year 70 when the CO 2 doubles. The local enhanced greenhouse effect from increased CO 2 increases the net surface sensible heat flux, which in turn contributes to the warming trend

Sensitivity of MJO to the CAPE lapse time in the NCAR CAM3

Weak and irregular boreal winter MJO in the NCAR CAM3 corresponds to very low CAPE background, which is caused by easy-to-occur and over-dominant deep convection indicating the deep convective scheme uses either too low CAPE threshold as triggering function or too large consumption rate of CAPE to close the scheme. Raising the CAPE threshold from default 70 J/kg to ten times large only enhances the CAPE background while fails to noticeably improve the wind mean state and the MJO. However, lengthening the CAPE lapse time from one to eight hours significantly improved the background in CAPE and winds, and salient features of the MJO. Variances, dominant periods and zonal wave numbers, power spectra and coherent propagating structure in winds and convection associated with MJO are ameliorated and comparable to the observations. Lengthening the CAPE lapse time to eight hours reduces dramatically the cloud base mass flux, which prevents effectively the deep convection from occurring prematurely. In this case, partitioning of deep to shallow convection in MJO active area is about 5:4.5 compared to over 9:0.5 in the control run. Latent heat is significantly enhanced below 600 hPa over the central Indian Ocean and the western Pacific. Such partitioning of deep and shallow convection is argued necessary for simulating realistic MJO features. Although the universal eight hours lies in the upper limit of that required by the quasi-equilibrium theory, a local CAPE lapse time for the parameterized cumulus convection will be more realistic

Statistically derived contributions of diverse human influences to twentieth-century temperature changes

The warming of the climate system is unequivocal as evidenced by an increase in global temperatures by 0.8 °C over the past century. However, the attribution of the observed warming to human activities remains less clear, particularly because of the apparent slow-down in warming since the late 1990s. Here we analyse radiative forcing and temperature time series with state-of-the-art statistical methods to address this question without climate model simulations. We show that long-term trends in total radiative forcing and temperatures have largely been determined by atmospheric greenhouse gas concentrations, and modulated by other radiative factors. We identify a pronounced increase in the growth rates of both temperatures and radiative forcing around 1960, which marks the onset of sustained global warming. Our analyses also reveal a contribution of human interventions to two periods when global warming slowed down. Our statistical analysis suggests that the reduction in the emissions of ozone-depleting substances under the Montreal Protocol, as well as a reduction in methane emissions, contributed to the lower rate of warming since the 1990s. Furthermore, we identify a contribution from the two world wars and the Great Depression to the documented cooling in the mid-twentieth century, through lower carbon dioxide emissions. We conclude that reductions in greenhouse gas emissions are effective in slowing the rate of warming in the short term.F.E. acknowledges financial support from the Consejo Nacional de Ciencia y Tecnologia (http://www.conacyt.gob.mx) under grant CONACYT-310026, as well as from PASPA DGAPA of the Universidad Nacional Autonoma de Mexico. (CONACYT-310026 - Consejo Nacional de Ciencia y Tecnologia; PASPA DGAPA of the Universidad Nacional Autonoma de Mexico

How closely do changes in surface and column water vapor follow Clausius-Clapeyron scaling in climate change simulations?

The factors governing the rate of change in the amount of atmospheric water vapor are analyzed in simulations of climate change. The global-mean amount of water vapor is estimated to increase at a differential rate of 7.3% K[superscript − 1] with respect to global-mean surface air temperature in the multi-model mean. Larger rates of change result if the fractional change is evaluated over a finite change in temperature (e.g., 8.2% K [superscript − 1] for a 3 K warming), and rates of change of zonal-mean column water vapor range from 6 to 12% K [superscript − 1] depending on latitude. Clausius–Clapeyron scaling is directly evaluated using an invariant distribution of monthly-mean relative humidity, giving a rate of 7.4% K − 1 for global-mean water vapor. There are deviations from Clausius–Clapeyron scaling of zonal-mean column water vapor in the tropics and mid-latitudes, but they largely cancel in the global mean. A purely thermodynamic scaling based on a saturated troposphere gives a higher global rate of 7.9% K [superscript − 1]. Surface specific humidity increases at a rate of 5.7% K [superscript − 1], considerably lower than the rate for global-mean water vapor. Surface specific humidity closely follows Clausius–Clapeyron scaling over ocean. But there are widespread decreases in surface relative humidity over land (by more than 1% K − 1 in many regions), and it is argued that decreases of this magnitude could result from the land/ocean contrast in surface warming

When will trends in European mean and heavy daily precipitation emerge?

A multi-model ensemble of regional climate projections for Europe is employed to investigate how the time of emergence (TOE) for seasonal sums and maxima of daily precipitation depends on spatial scale. The TOE is redefined for emergence from internal variability only; the spread of the TOE due to imperfect climate model formulation is used as a measure of uncertainty in the TOE itself. Thereby, the TOE becomes a fundamentally limiting timescale and translates into a minimum spatial scale on which robust conclusions can be drawn about precipitation trends. Thus, minimum temporal and spatial scales for adaptation planning are also given. In northern Europe, positive winter trends in mean and heavy precipitation, and in southwestern and southeastern Europe, summer trends in mean precipitation already emerge within the next few decades. However, across wide areas, especially for heavy summer precipitation, the local trend emerges only late in the 21st century or later. For precipitation averaged to larger scales, the trend, in general, emerges earlier

The upper end of climate model temperature projections is inconsistent with past warming

Climate models predict a large range of possible future temperatures for a particular scenario of future emissions of greenhouse gases and other anthropogenic forcings of climate. Given that further warming in coming decades could threaten increasing risks of climatic disruption, it is important to determine whether model projections are consistent with temperature changes already observed. This can be achieved by quantifying the extent to which increases in well mixed greenhouse gases and changes in other anthropogenic and natural forcings have already altered temperature patterns around the globe. Here, for the first time, we combine multiple climate models into a single synthesized estimate of future warming rates consistent with past temperature changes. We show that the observed evolution of near-surface temperatures appears to indicate lower ranges (5–95%) for warming (0.35–0.82 K and 0.45–0.93 K by the 2020s (2020–9) relative to 1986–2005 under the RCP4.5 and 8.5 scenarios respectively) than the equivalent ranges projected by the CMIP5 climate models (0.48–1.00 K and 0.51–1.16 K respectively). Our results indicate that for each RCP the upper end of the range of CMIP5 climate model projections is inconsistent with past warming