Ben P. Kirtman

El Niño in a changing climate

El Niño events, characterized by anomalous warming in the eastern equatorial Pacific Ocean, have global climatic teleconnections and are the most dominant feature of cyclic climate variability on subdecadal timescales. Understanding changes in the frequency or characteristics of El Niño events in a changing climate is therefore of broad scientific and socioeconomic interest. Recent studies show that the canonical El Niño has become less frequent and that a different kind of El Niño has become more common during the late twentieth century, in which warm sea surface temperatures (SSTs) in the central Pacific are flanked on the east and west by cooler SSTs. This type of El Niño, termed the central Pacific El Niño (CP-El Niño; also termed the dateline El Niño, El Niño Modoki or warm pool El Niño), differs from the canonical eastern Pacific El Niño (EP-El Niño) in both the location of maximum SST anomalies and tropical–midlatitude teleconnections. Here we show changes in the ratio of CP-El Niño to EP-El Niño under projected global warming scenarios from the Coupled Model Intercomparison Project phase 3 multi-model data set. Using calculations based on historical El Niño indices, we find that projections of anthropogenic climate change are associated with an increased frequency of the CP-El Niño compared to the EP-El Niño. When restricted to the six climate models with the best representation of the twentieth-century ratio of CP-El Niño to EP-El Niño, the occurrence ratio of CP-El Niño/EP-El Niño is projected to increase as much as five times under global warming. The change is related to a flattening of the thermocline in the equatorial Pacific.

Evolution of ENSO-Related Rainfall Anomalies in East Asia

Abstract The present study documents seasonal rainfall anomalies in East Asia during different phases of El Nino–Southern Oscillation (ENSO) using station rainfall and the NCEP–NCAR reanalysis for the period of 1951–2000 through lag–lead correlation/regression and extended singular value decomposition analyses. The ENSO-related rainfall anomalies consist of two major evolving centers of action: one positive and the other negative. The positive center of action affects southern China, eastern central China, and southern Japan during the fall of an ENSO developing year through the following spring. The negative center of action is over northern China during the summer and fall of an ENSO developing year. Seasonal rainfall variance explained by ENSO is about 20%–30% in southern China in fall and winter, about 20% in eastern central China in spring after the mature phase of ENSO, and around 15%–20% in western north China in summer and fall of an ENSO developing year. The two main rainfall anomalies are induce...

The North American Multimodel Ensemble: Phase-1 Seasonal-to-Interannual Prediction; Phase-2 toward Developing Intraseasonal Prediction

The recent U.S. National Academies report, Assessment of Intraseasonal to Interannual Climate Prediction and Predictability, was unequivocal in recommending the need for the development of a North American Multimodel Ensemble (NMME) operational predictive capability. Indeed, this effort is required to meet the specific tailored regional prediction and decision support needs of a large community of climate information users. The multimodel ensemble approach has proven extremely effective at quantifying prediction uncertainty due to uncertainty in model formulation and has proven to produce better prediction quality (on average) than any single model ensemble. This multimodel approach is the basis for several international collaborative prediction research efforts and an operational European system, and there are numerous examples of how this multimodel ensemble approach yields superior forecasts compared to any single model. Based on two NOAA Climate Test bed (CTB) NMME workshops (18 February and 8 April 2...

A U.S. Clivar project to assess and compare the responses of global climate models to drought-related SST forcing patterns: Overview and results

Abstract The U.S. Climate Variability and Predictability (CLIVAR) working group on drought recently initiated a series of global climate model simulations forced with idealized SST anomaly patterns, designed to address a number of uncertainties regarding the impact of SST forcing and the role of land–atmosphere feedbacks on regional drought. The runs were carried out with five different atmospheric general circulation models (AGCMs) and one coupled atmosphere–ocean model in which the model was continuously nudged to the imposed SST forcing. This paper provides an overview of the experiments and some initial results focusing on the responses to the leading patterns of annual mean SST variability consisting of a Pacific El Nino–Southern Oscillation (ENSO)-like pattern, a pattern that resembles the Atlantic multidecadal oscillation (AMO), and a global trend pattern. One of the key findings is that all of the AGCMs produce broadly similar (though different in detail) precipitation responses to the Pacific for...

Local Air–Sea Relationship in Observations and Model Simulations

Abstract The present study compares the local simultaneous correlation between rainfall–evaporation and sea surface temperature (SST)–SST tendency among observations, coupled general circulation model (CGCM) simulations, and stand-alone atmospheric general circulation model (AGCM) simulations. The purpose is to demonstrate to what extent the model simulations can reproduce the observed air–sea relationship. While the model-simulated correlation agrees with the observations in the tropical eastern Pacific, large discrepancies are found in the subtropics, midlatitudes, and tropical Indo-western Pacific Ocean regions. In tropical Indo-western Pacific Ocean regions and the midlatitudes where the atmosphere contributes to the observed SST changes, the specified SST simulations produce excessive SST forcing, whereas the CGCM captures the atmospheric feedback on the SST, but with somewhat of an overestimation. In the subtropics, both the AGCM and CGCM produce unrealistic positive rainfall–SST correlations. In th...

A verification framework for interannual-to-decadal predictions experiments

Decadal predictions have a high profile in the climate science community and beyond, yet very little is known about their skill. Nor is there any agreed protocol for estimating their skill. This paper proposes a sound and coordinated framework for verification of decadal hindcast experiments. The framework is illustrated for decadal hindcasts tailored to meet the requirements and specifications of CMIP5 (Coupled Model Intercomparison Project phase 5). The chosen metrics address key questions about the information content in initialized decadal hindcasts. These questions are: (1) Do the initial conditions in the hindcasts lead to more accurate predictions of the climate, compared to un-initialized climate change projections? and (2) Is the prediction model’s ensemble spread an appropriate representation of forecast uncertainty on average? The first question is addressed through deterministic metrics that compare the initialized and uninitialized hindcasts. The second question is addressed through a probabilistic metric applied to the initialized hindcasts and comparing different ways to ascribe forecast uncertainty. Verification is advocated at smoothed regional scales that can illuminate broad areas of predictability, as well as at the grid scale, since many users of the decadal prediction experiments who feed the climate data into applications or decision models will use the data at grid scale, or downscale it to even higher resolution. An overall statement on skill of CMIP5 decadal hindcasts is not the aim of this paper. The results presented are only illustrative of the framework, which would enable such studies. However, broad conclusions that are beginning to emerge from the CMIP5 results include (1) Most predictability at the interannual-to-decadal scale, relative to climatological averages, comes from external forcing, particularly for temperature; (2) though moderate, additional skill is added by the initial conditions over what is imparted by external forcing alone; however, the impact of initialization may result in overall worse predictions in some regions than provided by uninitialized climate change projections; (3) limited hindcast records and the dearth of climate-quality observational data impede our ability to quantify expected skill as well as model biases; and (4) as is common to seasonal-to-interannual model predictions, the spread of the ensemble members is not necessarily a good representation of forecast uncertainty. The authors recommend that this framework be adopted to serve as a starting point to compare prediction quality across prediction systems. The framework can provide a baseline against which future improvements can be quantified. The framework also provides guidance on the use of these model predictions, which differ in fundamental ways from the climate change projections that much of the community has become familiar with, including adjustment of mean and conditional biases, and consideration of how to best approach forecast uncertainty.

Distinguishing the Roles of Natural and Anthropogenically Forced Decadal Climate Variability: Implications for Prediction

Abstract Given that over the course of the next 10–30 years the magnitude of natural decadal variations may rival that of anthropogenically forced climate change on regional scales, it is envisioned that initialized decadal predictions will provide important information for climate-related management and adaptation decisions. Such predictions are presently one of the grand challenges for the climate community. This requires identifying those physical phenomena—and their model equivalents—that may provide additional predictability on decadal time scales, including an assessment of the physical processes through which anthropogenic forcing may interact with or project upon natural variability. Such a physical framework is necessary to provide a consistent assessment (and insight into potential improvement) of the decadal prediction experiments planned to be assessed as part of the IPCCs Fifth Assessment Report.

A Unified Modeling Approach to Climate System Prediction

There is a new perspective of a continuum of prediction problems, with a blurring of the distinction between short-term predictions and long-term climate projections. At the heart of this new persp...

Observed Relationship of Spring and Summer East Asian Rainfall with Winter and Spring Eurasian Snow

Abstract This study investigates the relationship between spring and summer rainfall in East Asia and the preceding winter and spring snow cover/depth over Eurasia, using station rainfall observations, satellite-observed snow cover, satellite-derived snow water equivalent, and station observations of the number of days of snow cover and snow depth. Correlation analysis shows that snow-depth anomalies can persist from winter to spring whereas snow cover anomalies cannot in most regions of Eurasia. Locally, snow cover and snow-depth anomalies in February are not related in most regions to the north of 50°N, but those anomalies in April display consistent year-to-year variations. The results suggest that the winter snow cover cannot properly represent all the effects of snow and it is necessary to separate the winter and spring snow cover in addressing the snow–monsoon relationship. Spring snow cover in western Siberia is positively correlated with spring rainfall in southern China. The circulation anomalies...

Discrepancy of Interdecadal Changes in the Asian Region among the NCEP–NCAR Reanalysis, Objective Analyses, and Observations

Abstract This study compares decadal means and interdecadal changes of surface and sea level pressures, tropospheric heights, and winds in the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis with objective analyses and observations. It is found that over Asia the NCEP–NCAR reanalysis pressures and heights are systematically lower than objective analyses and observations before the late 1970s. The magnitude of the differences changes from one decade to another and shows obvious seasonal dependence. The nonuniform spatial distribution of pressure and height differences is consistent with the discrepancy in lower-level meridional winds along the east Asian coast. The seasonal dependence of pressure differences affects the strength of the seasonal cycle over Asia. More importantly, large changes in the discrepancies from one decade to another lead to inconsistent interdecadal changes between the reanalysis and objective analyses or observations in ...