Temperature Trends in the NARCCAP Regional Climate Models

2012 ◽  
Vol 25 (11) ◽  
pp. 3985-3991 ◽  
Author(s):  
Melissa S. Bukovsky

The skill of six regional climate models (RCMs) in reproducing short-term (24-yr), observed, near-surface temperature trends when driven by reanalysis is examined. The RCMs are part of the North American Regional Climate Change Assessment Program (NARCCAP). If RCMs can reproduce observed temperature trends, then they are, in a way, demonstrating their ability to capture a type of climate change, which may be relevant to their ability to credibly simulate anthropogenic climate changes under future emission scenarios. This study finds that the NARCCAP RCMs can simulate some resolved-scale temperature trends, especially those seen recently in spring and, by and large, in winter. However, results in other seasons suggest that RCM performance in this measure may be dependent on the type and strength of the forcing behind the observed trends.

2013 ◽  
Vol 26 (21) ◽  
pp. 8690-8697 ◽  
Author(s):  
Michael A. Alexander ◽  
James D. Scott ◽  
Kelly Mahoney ◽  
Joseph Barsugli

Abstract Precipitation changes between 32-yr periods in the late twentieth and mid-twenty-first centuries are investigated using regional climate model simulations provided by the North American Regional Climate Change Assessment Program (NARCCAP). The simulations generally indicate drier summers in the future over most of Colorado and the border regions of the adjoining states. The decrease in precipitation occurs despite an increase in the surface specific humidity. The domain-averaged decrease in daily summer precipitation occurs in all of the models from the 50th through the 95th percentile, but without a clear agreement on the sign of change for the most extreme (top 1% of) events.


2010 ◽  
Vol 11 (6) ◽  
pp. 1373-1379 ◽  
Author(s):  
William J. Gutowski ◽  
Raymond W. Arritt ◽  
Sho Kawazoe ◽  
David M. Flory ◽  
Eugene S. Takle ◽  
...  

Abstract This paper analyzes the ability of the North American Regional Climate Change Assessment Program (NARCCAP) ensemble of regional climate models to simulate extreme monthly precipitation and its supporting circulation for regions of North America, comparing 18 years of simulations driven by the National Centers for Environmental Prediction (NCEP)–Department of Energy (DOE) reanalysis with observations. The analysis focuses on the wettest 10% of months during the cold half of the year (October–March), when it is assumed that resolved synoptic circulation governs precipitation. For a coastal California region where the precipitation is largely topographic, the models individually and collectively replicate well the monthly frequency of extremes, the amount of extreme precipitation, and the 500-hPa circulation anomaly associated with the extremes. The models also replicate very well the statistics of the interannual variability of occurrences of extremes. For an interior region containing the upper Mississippi River basin, where precipitation is more dependent on internally generated storms, the models agree with observations in both monthly frequency and magnitude, although not as closely as for coastal California. In addition, simulated circulation anomalies for extreme months are similar to those in observations. Each region has important seasonally varying precipitation processes that govern the occurrence of extremes in the observations, and the models appear to replicate well those variations.


Author(s):  
Joshua P. French ◽  
Seth McGinnis ◽  
Armin Schwartzman

Abstract. We assess similarities and differences between model effects for the North American Regional Climate Change Assessment Program (NARCCAP) climate models using varying classes of linear regression models. Specifically, we consider how the average temperature effect differs for the various global and regional climate model combinations, including assessment of possible interaction between the effects of global and regional climate models. We use both pointwise and simultaneous inference procedures to identify regions where global and regional climate model effects differ. We also show conclusively that results from pointwise inference are misleading, and that accounting for multiple comparisons is important for making proper inference.


2021 ◽  
Author(s):  
Antoine Doury ◽  
Samuel Somot ◽  
Sébastien Gadat ◽  
Aurélien Ribes ◽  
Lola Corre

Abstract Providing reliable information on climate change at local scale remains a challenge of first importance for impact studies and policymakers. Here, we propose a novel hybrid downscaling method combining the strengths of both empirical statistical downscaling methods and Regional Climate Models (RCMs). The aim of this tool is to enlarge the size of high-resolution RCM simulation ensembles at low cost.We build a statistical RCM-emulator by estimating the downscaling function included in the RCM. This framework allows us to learn the relationship between large-scale predictors and a local surface variable of interest over the RCM domain in present and future climate. Furthermore, the emulator relies on a neural network architecture, which grants computational efficiency. The RCM-emulator developed in this study is trained to produce daily maps of the near-surface temperature at the RCM resolution (12km). The emulator demonstrates an excellent ability to reproduce the complex spatial structure and daily variability simulated by the RCM and in particular the way the RCM refines locally the low-resolution climate patterns. Training in future climate appears to be a key feature of our emulator. Moreover, there is a huge computational benefit in running the emulator rather than the RCM, since training the emulator takes about 2 hours on GPU, and the prediction is nearly instantaneous. However, further work is needed to improve the way the RCM-emulator reproduces some of the temperature extremes, the intensity of climate change, and to extend the proposed methodology to different regions, GCMs, RCMs, and variables of interest.


Water ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 1032 ◽  
Author(s):  
Ariel Wang ◽  
Francina Dominguez ◽  
Arthur Schmidt

In this paper, extreme precipitation spatial analog is examined as an alternative method to adapt extreme precipitation projections for use in urban hydrological studies. The idea for this method is that real climate records from some cities can serve as “analogs” that behave like potential future precipitation for other locations at small spatio-temporal scales. Extreme precipitation frequency quantiles of a 3.16 km 2 catchment in the Chicago area, computed using simulations from North American Regional Climate Change Assessment Program (NARCCAP) Regional Climate Models (RCMs) with L-moment method, were compared to National Oceanic and Atmospheric Administration (NOAA) Atlas 14 (NA14) quantiles at other cities. Variances in raw NARCCAP historical quantiles from different combinations of RCMs, General Circulation Models (GCMs), and remapping methods are much larger than those in NA14. The performance for NARCCAP quantiles tend to depend more on the RCMs than the GCMs, especially at durations less than 24-h. The uncertainties in bias-corrected future quantiles of NARCCAP are still large compared to those of NA14, and increase with rainfall duration. Results show that future 3-h and 30-day rainfall in Chicago will be similar to historical rainfall from Memphis, TN and Springfield, IL, respectively. This indicates that the spatial analog is potentially useful, but highlights the fact that the analogs may depend on the duration of the rainfall of interest.


2013 ◽  
Vol 120 (4) ◽  
pp. 965-975 ◽  
Author(s):  
L. O. Mearns ◽  
S. Sain ◽  
L. R. Leung ◽  
M. S. Bukovsky ◽  
S. McGinnis ◽  
...  

2013 ◽  
Vol 2013 ◽  
pp. 1-13 ◽  
Author(s):  
Silvina A. Solman

This review summarizes the progress achieved on regional climate modeling activities over South America since the early efforts at the beginning of the 2000s until now. During the last 10 years, simulations with regional climate models (RCMs) have been performed for several purposes over the region. Early efforts were mainly focused on sensitivity studies to both physical mechanisms and technical aspects of RCMs. The last developments were focused mainly on providing high-resolution information on regional climate change. This paper describes the most outstanding contributions from the isolated efforts to the ongoing coordinated RCM activities in the framework of the CORDEX initiative, which represents a major endeavor to produce ensemble climate change projections at regional scales and allows exploring the associated range of uncertainties. The remaining challenges in modeling South American climate features are also discussed.


2013 ◽  
Vol 94 (7) ◽  
pp. 1077-1078 ◽  
Author(s):  
Linda O. Mearns ◽  
Melissa S. Bukovsky ◽  
Ruby Leung ◽  
Yun Qian ◽  
Ray Arritt ◽  
...  

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