A strong teleconnection exists between the sea surface temperature (SST) over the tropical Pacific and the winter precipitation in the southeastern United States (SE US). This feature is adopted to validate the fidelity of Coupled Model Intercomparison Project Phase 5 (CMIP5) in this study. In addition, the authors examine whether the teleconnection pattern persists in the future under a global warming scenario. Generally, most of the eight selected models show a positive correlation between November SST over Niño 3 region and December–February (DJF) mean daily precipitation anomalies over the SE US, consistent with the observation. However, the models with poor realization of skewness of Niño indices fail to simulate the realistic teleconnection pattern in the historical simulation. In the Representative Concentration Pathways 8.5 (RCP8.5) run, all of the models maintain positive and slightly increased correlation patterns. It is noteworthy that the region with strong teleconnection pattern shifts northward in the future. Increased variance of winter precipitation due to the SST teleconnection is shown over Alabama and Georgia rather than over Florida under the RCP8.5 scenario in most of the models, differing from the historical run in which the precipitation in Florida is the most attributable to the eastern Pacific SST.
In 2008, many climate-modeling groups in the world agreed to build a new set of coordinated climate model experiments. The Coupled Model Intercomparison Project Phase 5 (CMIP5) was planned to produce a standard set of simulations from state-of-the-art models to assess the fidelity of the models in simulating the recent past, to provide projections of future climate change, and to promote our understanding of mechanisms responsible for model differences [
Although numerous studies have been conducted to validate the credibility of the newly launched CMIP5 data globally [
It is well known that the SE US has a strong teleconnection to tropical Pacific sea surface temperature (SST). Previous studies demonstrated that warmer (colder) SSTs lead to wetter (drier) winters in the coastal southeastern states and to the opposite signal more inland [
Furthermore, several studies have examined the change of teleconnection with time. For instance, Diaz et al. [
In this study, the fidelity of CMIP5 models in terms of simulation of regional scale climate variability and trend is assessed by comparing modeled teleconnection patterns with the observed pattern. We also investigate whether this current teleconnection will persist in the future under the global warming scenario. This paper is structured as follows. Data and method used for the analysis are described in Section
We analyze historical and Representative Concentration Pathways 8.5 (RCP8.5) simulations produced by 8 CMIP5 models. Eight CMIP5 models are chosen for this study on the basis of their availability of key variables for crop model including precipitation, maximum and minimum surface temperature, and solar radiation so that our results can be applied to forthcoming study focusing on crop yield change under the climate scenario using the crop model. Models with too sparse resolution (both the longitude and latitude are larger than 2.5°) are not selected for this study because our domain of interest is confined to the SE US region. The model resolution, the number of ensemble members, and the total simulated years are given in Table
CMIP5 model names and specifications.
Model | Institution | ID | AM resolution |
Integration period |
Number of | |
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Historical | RCP8.5 | |||||
CCSM4 | National Center for Atmospheric Research | 1 | 0.9°Lat × 1.25°Lon | 156 | 95 | 2 |
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CSIRO-Mk3-6-0 | CSIRO (Commonwealth Scientific and Industrial Research Organisation, Australia) and BOM (Bureau of Meteorology, Australia) | 2 | T63 | 145 | 95 | 10 |
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GFDL-CM3 | Geophysical Fluid Dynamics Laboratory | 3 | 144 × 90: |
145 | 95 | 1 |
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GFDL-ESM2G | Geophysical Fluid Dynamics Laboratory | 4 | 144 × 90: |
145 | 95 | 1 |
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GFDL-ESM2M | Geophysical Fluid Dynamics Laboratory | 5 | 144 × 90: |
156 | 95 | 1 |
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MIROC5 | Atmosphere and Ocean Research Institute (The University of Tokyo), National Institute |
6 | T85 | 156 | 95 | 3 |
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MPI-ESM-LR | Max Planck Institute for Meteorology (MPI-M) | 7 | T63 | 156 | 95 | 3 |
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NorESM1-M | Norwegian Climate Centre | 8 | 0.9°Lat × 1.25°Lon | 156 | 95 | 1 |
The extended reconstruction of historical sea surface temperature (ERSST) version 3 data are used to provide SST observations for the period of 1854–2010. The data are acquired from the web site
Through application of a bilinear interpolation method [
To examine the strength of the teleconnection between the SST over the tropical Pacific and the winter precipitation in the southeastern United States, we compute correlation coefficient (
Although various different methods have been used to specify when El Niño or La Niña events have occurred, Japan Meteorological Agency (JMA) index is utilized to classify ENSO events into El Niño, neutral, and La Niña phases following Hanley et al. [
Burgers and Stephenson [
The SE US has a robust interannual predictability of the precipitation because of the strong teleconnection to the tropical Pacific SST. This distinct feature is applied to the assessment of the CMIP5 models in this study. Figure
Temporal correlation between November Niño 3 index and the observed rainfall (DJF mean) for 1970–2010: a correlation with the absolute value greater than 0.3 is statistically significant at the 95% confidence level.
Comparing this prominent feature in the observation to that in the CMIP5 simulations, we are able to assess the credibility of CMIP5 models implicitly. Figure
Temporal correlations between November Niño 3 index and the DJF mean daily precipitation anomalies for historical (a–h) and RCP8.5 (i–p) experiments from CMIP5 models. Each model is identified by ID number as in Table
On the basis of the results from the historical run, we further examine teleconnection patterns under the future climate scenario, RCP8.5. The right column in Figure
Figure
Stacked explained variances (%) for historical (a) and RCP8.5 (b) experiments from CMIP5 models, respectively. Explained variance is averaged over the States of Florida, Alabama, and Georgia, separately. All ensemble members are presented in the diagram. Observed value is included in (a) at the rightmost column.
In the RCP8.5 run (Figure
Percentage of the explained variance of Florida, Alabama, and Georgia contributes to a total explained variance of southeastern US spanning 3 states for historical (a) and RCP8.5 (b) experiments from CMIP5 models.
To analyze the impact of ENSO on the high percentile of rainfall over the SE US during winter, we focus on the 75th percentile from the right tail of DJF daily rainfall anomalies distribution in terms of ENSO phases (i.e., El Niño, neutral, and La Niña phases) classified by the JMA index. Model-generated DJF daily precipitation is displayed on the rightmost column of Figures
The 75th percentile of DJF mean daily precipitation anomalies (mm/day) distribution of El Niño ((a)–(d)), neutral ((e)–(h)), and La Niña ((i)–(l)) years in historical run of CMIP5 models 1–4. DJF mean daily precipitation is shown in the right column.
Same as Figure
Figure
Difference of 75th percentile of DJF mean daily precipitation anomalies (mm/day) between RCP8.5 and historical run for El Niño ((a)–(d) and (i)–(l)) and La Niña ((e)–(h) and (m)–(p)).
We have examined the teleconnection between the SST over the eastern Pacific in November and the following wintertime precipitation over the SE US. Figures
Ensemble member averaged correlation between the November SST and the DJF mean daily rainfall anomaly averaged over the SE US for CMIP5 models 1–4 (historical run: (a)–(d), RCP8.5 run: (e)–(h)). Locations of the Niño 3, 3.4, and 4 regions are marked with rectangular box from left, middle, and right, respectively. The 0.4 contour is thickened for better comparison.
Same as Figure
The possible reason that many coupled climate models have exhibited unrealistic teleconnections between ENSO and extratropical circulation patterns is attributed to having poorly represented physical processes in the ENSO region in the models [
Therefore, the CMIP5 models’ performance of simulating the SST over the equatorial Pacific Ocean can also result in different climate impacts on the remote regions, especially the SE US. There have been numerous studies that examined the ability of CMIP5 models to simulate ENSO by comparing equatorial SST mean, standard deviation of Nino indices, ENSO spectral characteristics, and occurrence of ENSO events [
In this section, the SST over the equatorial Pacific Ocean in the CMIP5 models is further examined by comparing skewness of the SST from the historical run of CMIP5 models to that of the observed SST to reveal the reason for the models simulating different teleconnection patterns.
Figure
Skewness of November ENSO indices of ERSST observation for the period from 1854 to 2010.
By comparing the skewness of Niño indices obtained from the CMIP5 models to the observation shown in Figure
Ensemble member averaged skewness of November ENSO indices for historical (a) and RCP8.5 (b) experiments, respectively.
Although the SST from the historical run of CMIP5 models in this study shows different characteristics of skewness from those observed in Figure
In this study, we inquire whether the current teleconnection characteristics between winter precipitation over the SE US and the tropical Pacific SST will persist in the future under the global warming scenario simulated by current state-of-the-art climate models. The credibility of CMIP5 models regarding the simulation of the regional scale climate variability is validated by applying the robust teleconnection feature to the assessment in order to obtain confidence in future climate prediction. We find out that most of the 8 models selected in this study show a positive correlation between the November Niño 3 SST and the DJF mean daily precipitation anomalies over the SE US, consistent with the observation. Although the global models in the CMIP5 are capable of simulating the regional response of the teleconnection, it is of interest to note that one partial change in the model could contribute to different teleconnection patterns.
In the RCP8.5 run, all of the models maintain the positive and slightly increased correlation patterns. However, the degree of change in the relationship differs from domains under the climate change scenario, RCP8.5. Whereas the SST over Niño 3 region accounts for the largest portion of variance of rainfall in Florida in the observation as well as in the historical run of the models (NorESM1-M, MIROC5, GFDL-ESM2M, GFDL-CM3, and CCSM4), the models have an increased portion of variance in Alabama and Georgia in the RCP8.5 regarding the winter precipitation that is attributed to the SST over Niño 3 region.
To analyze the impact of ENSO on the wintertime extreme rainfall over the SE US, we focus on the 75th percentile from the right tail of DJF daily rainfall anomaly distribution in terms of ENSO phases. The greater value of the 75th percentile of rainfall for El Niño is mostly found over Florida, differing from the DJF mean daily precipitation pattern in which maximum DJF mean daily rainfall area is mostly located over the northern SE US, spanning Alabama and Georgia. In the same way, the smaller value of the 75th percentile of rainfall for La Niña is mostly located over Florida. The models that show a greater correlation coefficient in the RCP8.5 than in the historical run have heavier rainfall during El Niño events in the future run. It is noteworthy that the increase in extreme rainfall amount during El Niño events tends to be dominant over the northern regions of the SE US, including Alabama and Georgia under the climate change.
We have found that the CMIP5 models’ performance of simulating the SST over the equatorial Pacific Ocean affects the climate impact on the SE US. By comparing the skewness of Niño indices obtained from the historical run of CMIP5 models to that of the observation, we assessed which model has the highest credibility. It turns out that the models with poor realization of skewness, such as CSIRO-Mk3-6-0, GFDL-ESM2G, and MPI-ESM-LR, fail to simulate the realistic teleconnection pattern and have lower confidence in future climate prediction.
We also have shown the northward shift of the ENSO teleconnection pattern over the SE US. This finding refines the results of previous studies on the change of the teleconnections over the North Pacific and North America associated with El Niño events in a future warmer climate [
The authors declare that there is no conflict of interests regarding the publication of this paper.
This work was supported by a grant from the Agriculture and Food Research Initiative of the USDA National Institute of Food and Agriculture (NIFA), Grant no. FLAW-2011-00828 (EaSM Project).