Krishna AchutaRao

An overview of results from the Coupled Model Intercomparison Project

Abstract The Coupled Model Intercomparison Project (CMIP) collects output from global coupled ocean–atmosphere general circulation models (coupled GCMs). Among other uses, such models are employed both to detect anthropogenic effects in the climate record of the past century and to project future climatic changes due to human production of greenhouse gases and aerosols. CMIP has archived output from both constant forcing (“control run”) and perturbed (1% per year increasing atmospheric carbon dioxide) simulations. This report summarizes results form 18 CMIP models. A third of the models refrain from employing ad hoc flux adjustments at the ocean–atmosphere interface. The new generation of non-flux-adjusted control runs are nearly as stable as—and agree with observations nearly as well as—the flux-adjusted models. Both flux-adjusted and non-flux-adjusted models simulate an overall level of natural internal climate variability that is within the bounds set by observations. These developments represent significant progress in the state of the art of climate modeling since the Second (1995) Scientific Assessment Report of the Intergovernmental Panel on Climate Change (IPCC; see Gates et al. [Gates, W.L., et al., 1996. Climate models—Evaluation. Climate Climate 1995: The Science of Climate Change, Houghton, J.T., et al. (Eds.), Cambridge Univ. Press, pp. 229–284]). In the increasing-CO2 runs, differences between different models, while substantial, are not as great as one might expect from earlier assessments that relied on equilibrium climate sensitivity.

Forced and unforced ocean temperature changes in Atlantic and Pacific tropical cyclogenesis regions

Previous research has identified links between changes in sea surface temperature (SST) and hurricane intensity. We use climate models to study the possible causes of SST changes in Atlantic and Pacific tropical cyclogenesis regions. The observed SST increases in these regions range from 0.32°C to 0.67°C over the 20th century. The 22 climate models examined here suggest that century-timescale SST changes of this magnitude cannot be explained solely by unforced variability of the climate system. We employ model simulations of natural internal variability to make probabilistic estimates of the contribution of external forcing to observed SST changes. For the period 1906–2005, we find an 84% chance that external forcing explains at least 67% of observed SST increases in the two tropical cyclogenesis regions. Model “20th-century” simulations, with external forcing by combined anthropogenic and natural factors, are generally capable of replicating observed SST increases. In experiments in which forcing factors are varied individually rather than jointly, human-caused changes in greenhouse gases are the main driver of the 20th-century SST increases in both tropical cyclogenesis regions.

Anthropogenic Warming of the Oceans: Observations and Model Results

Abstract Observations show the oceans have warmed over the past 40 yr, with appreciable regional variation and more warming at the surface than at depth. Comparing the observations with results from two coupled ocean–atmosphere climate models [the Parallel Climate Model version 1 (PCM) and the Hadley Centre Coupled Climate Model version 3 (HadCM3)] that include anthropogenic forcing shows remarkable agreement between the observed and model-estimated warming. In this comparison the models were sampled at the same locations as gridded yearly observed data. In the top 100 m of the water column the warming is well separated from natural variability, including both variability arising from internal instabilities of the coupled ocean–atmosphere climate system and that arising from volcanism and solar fluctuations. Between 125 and 200 m the agreement is not significant, but then increases again below this level, and remains significant down to 600 m. Analysis of PCM’s heat budget indicates that the warming is dr...

Volcanoes and climate: Krakatoa's signature persists in the ocean

We have analysed a suite of 12 state-of-the-art climate models and show that ocean warming and sea-level rise in the twentieth century were substantially reduced by the colossal eruption in 1883 of the volcano Krakatoa in the Sunda strait, Indonesia. Volcanically induced cooling of the ocean surface penetrated into deeper layers, where it persisted for decades after the event. This remarkable effect on oceanic thermal structure is longer lasting than has previously been suspected and is sufficient to offset a large fraction of ocean warming and sea-level rise caused by anthropogenic influences.

Simulated and observed variability in ocean temperature and heat content

Observations show both a pronounced increase in ocean heat content (OHC) over the second half of the 20th century and substantial OHC variability on interannual-to-decadal time scales. Although climate models are able to simulate overall changes in OHC, they are generally thought to underestimate the amplitude of OHC variability. Using simulations of 20th century climate performed with 13 numerical models, we demonstrate that the apparent discrepancy between modeled and observed variability is largely explained by accounting for changes in observational coverage and instrumentation and by including the effects of volcanic eruptions. Our work does not support the recent claim that the 0- to 700-m layer of the global ocean experienced a substantial OHC decrease over the 2003 to 2005 time period. We show that the 2003–2005 cooling is largely an artifact of a systematic change in the observing system, with the deployment of Argo floats reducing a warm bias in the original observing system.

Variability of Ocean Heat Uptake: Reconciling Observations and Models

This study examines the temporal variability of ocean heat uptake in observations and in climate models. Previous work suggests that coupled Atmosphere-Ocean General Circulation Models (A-OGCMs) may have underestimated the observed natural variability of ocean heat content, particularly on decadal and longer timescales. To address this issue, we rely on observed estimates of heat content from the 2004 World Ocean Atlas (WOA-2004) compiled by Levitus et al. (2005). Given information about the distribution of observations in WOA-2004, we evaluate the effects of sparse observational coverage and the infilling that Levitus et al. use to produce the spatially-complete temperature fields required to compute heat content variations. We first show that in ocean basins with limited observational coverage, there are important differences between ocean temperature variability estimated from observed and infilled portions of the basin. We then employ data from control simulations performed with eight different A-OGCMs as a test-bed for studying the effects of sparse, space- and time-varying observational coverage. Subsampling model data with actual observational coverage has a large impact on the inferred temperature variability in the top 300 and 3000 meters of the ocean. This arises from changes in both sampling depth and in the geographical areas sampled. Our results illustrate that subsampling model data at the locations of available observations increases the variability, reducing the discrepancy between models and observations.

Evaluation of a CCSM3 Simulation with a Finite Volume Dynamical Core for the Atmosphere at 1° Latitude 1.25° Longitude Resolution

Abstract A simulation of the present-day climate by the Community Climate System Model version 3 (CCSM3) that uses a Finite Volume (FV) numerical method for solving the equations governing the atmospheric dynamics is presented. The simulation is compared to observations and to the well-documented simulation by the standard CCSM3, which uses the Eulerian spectral method for the atmospheric dynamics. The atmospheric component in the simulation herein uses a 1° latitude × 1.25° longitude grid, which is a slightly finer resolution than the T85-grid used in the spectral transform. As in the T85 simulation, the ocean and ice models use a nominal 1-degree grid. Although the physical parameterizations are the same and the resolution is comparable to the standard model, substantial testing and slight retuning were required to obtain an acceptable control simulation. There are significant improvements in the simulation of the surface wind stress and sea surface temperature. Improvements are also seen in the simulat...

Coupled Climate Model appraisal: A benchmark for future studies

Studies of future climate scenarios, such as those conducted in support of the Intergovernmental Panel on Climate Change (IPCC, http://www.ipcc.ch/), rely heavily on numerical experiments performed with coupled ocean-atmosphere general circulation models (OAGCMs). In order to assess the results of such climate change experiments, a benchmark for evaluating model performance is required.To provide this benchmark, Lawrence Livermore National Laboratorys Program for Climate Model Diagnosis and Intercomparison (PCMDI) conducted an extensive appraisal of multidecadal climate simulations by 11 coupled OAGCMs that were developed during the period of 1995–2002 [Bader etal., 2004]. While diverse representations of atmosphere, ocean, sea ice, land, and of their respective couplings were employed (see Table 1), all of these climate models were run with current values of solar and greenhouse gas radiative forcings. Thus, by comparing details of the OAGCM simulations with analogous facets of climate observations, the needed model-performance benchmark can be obtained. If, for instance, a model simulation closely replicates the salient features of the present climate, a necessary (though not sufficient) condition is met for placing some confidence in the models projections of the climate of the next several decades.

The Deadly Combination of Heat and Humidity in India and Pakistan in Summer 2015

Author(s): Wehner, M; Stone, D; Krishnan, H; Achutarao, K; Castillo, F | Abstract:

The Heavy Precipitation Event of December 2015 in Chennai, India

Introduction. At the beginning of December 2015, the Indian state of Tamil Nadu experienced extensive f looding. November had been the second wettest month in Chennai (1049 mm) in more than 100 years, but the main floods were caused by one day of extreme precipitation on 1 December. The commercial center, Chennai (formerly known as Madras), reported 24-hr precipitation from 0830 LT ranging from 77 to 494 mm at 18 stations, with a citywide-average of 286 mm (Fig. 17.1a). The city was declared a disaster area on 2 December after many areas, including the airport, were flooded. Although in the satellite-based CMORPH analysis the largest precipitation amounts were recorded south of Chennai (Fig. 17.1b), we concentrate our analysis on this city because the impact was largest here. Damages were estimated to be as high as