Regional Extreme Monthly Precipitation Simulated by NARCCAP RCMs

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.

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Greenhouse Gas–Induced Changes in Summer Precipitation over Colorado in NARCCAP Regional Climate Models*

Journal of Climate ◽

10.1175/jcli-d-13-00088.1 ◽

2013 ◽

Vol 26 (21) ◽

pp. 8690-8697 ◽

Cited By ~ 12

Author(s):

Michael A. Alexander ◽

James D. Scott ◽

Kelly Mahoney ◽

Joseph Barsugli

Keyword(s):

Climate Models ◽

Climate Model ◽

Regional Climate ◽

Summer Precipitation ◽

Regional Climate Change ◽

Regional Climate Models ◽

Specific Humidity ◽

The North ◽

Climate Model Simulations ◽

Climate Change Assessment

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.

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Temperature Trends in the NARCCAP Regional Climate Models

Journal of Climate ◽

10.1175/jcli-d-11-00588.1 ◽

2012 ◽

Vol 25 (11) ◽

pp. 3985-3991 ◽

Cited By ~ 30

Author(s):

Melissa S. Bukovsky

Keyword(s):

Climate Change ◽

Climate Models ◽

Regional Climate ◽

Regional Climate Change ◽

Regional Climate Models ◽

Near Surface ◽

The North ◽

Temperature Trends ◽

Scale Temperature ◽

Climate Change Assessment

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.

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Assessing NARCCAP climate model effects using spatial confidence regions

Advances in Statistical Climatology Meteorology and Oceanography ◽

10.5194/ascmo-3-67-2017 ◽

2017 ◽

Vol 3 (2) ◽

pp. 67-92

Author(s):

Joshua P. French ◽

Seth McGinnis ◽

Armin Schwartzman

Keyword(s):

Regional Climate Model ◽

Climate Models ◽

Climate Model ◽

Regional Climate ◽

Regional Climate Change ◽

Regional Climate Models ◽

Confidence Regions ◽

Linear Regression Models ◽

The North ◽

Climate Change Assessment

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.

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Extreme Precipitation Spatial Analog: In Search of an Alternative Approach for Future Extreme Precipitation in Urban Hydrological Studies

Water ◽

10.3390/w11051032 ◽

2019 ◽

Vol 11 (5) ◽

pp. 1032 ◽

Cited By ~ 2

Author(s):

Ariel Wang ◽

Francina Dominguez ◽

Arthur Schmidt

Keyword(s):

Extreme Precipitation ◽

General Circulation ◽

Climate Models ◽

Regional Climate ◽

Regional Climate Change ◽

Regional Climate Models ◽

General Circulation Models ◽

Precipitation Frequency ◽

Spatio Temporal ◽

Climate Change Assessment

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.

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Future Decreases in Freezing Days across North America

Journal of Climate ◽

10.1175/jcli-d-15-0802.1 ◽

2016 ◽

Vol 29 (19) ◽

pp. 6923-6935 ◽

Cited By ~ 5

Author(s):

Michael A. Rawlins ◽

Raymond S. Bradley ◽

Henry F. Diaz ◽

John S. Kimball ◽

David A. Robinson

Keyword(s):

North America ◽

Climate Models ◽

Regional Climate ◽

Regional Climate Models ◽

The United States ◽

Rate Of Change ◽

Mean Annual Temperature ◽

The North ◽

Air Temperatures ◽

Climate Change Assessment

Abstract This study used air temperatures from a suite of regional climate models participating in the North American Climate Change Assessment Program (NARCCAP) together with two atmospheric reanalysis datasets to investigate changes in freezing days (defined as days with daily average temperature below freezing) likely to occur between 30-yr baseline (1971–2000) and midcentury (2041–70) periods across most of North America. Changes in NARCCAP ensemble mean winter temperature show a strong gradient with latitude, with warming of over 4°C near Hudson Bay. The decline in freezing days ranges from less than 10 days across north-central Canada to nearly 90 days in the warmest areas of the continent that currently undergo seasonally freezing conditions. The area experiencing freezing days contracts by 0.9–1.0 × 106 km2 (5.7%–6.4% of the total area). Areas with mean annual temperature between 2° and 6°C and a relatively low rate of change in climatological daily temperatures (<0.2°C day−) near the time of spring thaw will encounter the greatest decreases in freezing days. Advances in the timing of spring thaw will exceed the delay in fall freeze across much of the United States, with the reverse pattern likely over most of Canada.

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Projecting Changes in Extreme Precipitation in the Midwestern United States Using North American Regional Climate Change Assessment Program (NARCCAP) Regional Climate Models

Greenhouse Gases - Emission, Measurement and Management ◽

10.5772/32667 ◽

2012 ◽

Cited By ~ 1

Author(s):

Shuang-Ye Wu

Keyword(s):

Climate Change ◽

United States ◽

North American ◽

Extreme Precipitation ◽

Climate Models ◽

Regional Climate ◽

Regional Climate Change ◽

Regional Climate Models ◽

Assessment Program ◽

Climate Change Assessment

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A Multiresolution Approach to Estimating the Value Added by Regional Climate Models

Journal of Climate ◽

10.1175/jcli-d-14-00557.1 ◽

2015 ◽

Vol 28 (22) ◽

pp. 8873-8887 ◽

Cited By ~ 5

Author(s):

Ryan J. Parker ◽

Brian J. Reich ◽

Stephan R. Sain

Keyword(s):

Climate Models ◽

Spatial Scales ◽

Regional Climate ◽

Value Added ◽

Regional Climate Change ◽

Regional Climate Models ◽

Local Analysis ◽

Discrete Cosine Transformation ◽

Local Climate ◽

The North

Abstract Climate models have emerged as an essential tool for studying the earth’s climate. Global models are computationally expensive, and so a relatively coarse spatial resolution must be used within the model. This hinders direct application for many impacts studies that require regional and local climate information. A regional model with boundary conditions taken from the global model achieves a finer spatial scale for local analysis. In this paper the authors propose a new method for assessing the value added by these higher-resolution models, and they demonstrate the method within the context of regional climate models (RCMs) from the North American Regional Climate Change Assessment Program (NARCCAP) project. This spectral approach using the discrete cosine transformation (DCT) is based on characterizing the joint relationship between observations, coarser-scale models, and higher-resolution models to identify how the finer scales add value over the coarser output. The joint relationship is computed by estimating the covariance of the data sources at different spatial scales with a Bayesian hierarchical model. Using this model the authors can then estimate the value added by each data source over the others. For the NARCCAP data, they find that the higher-resolution models add value starting with low wavenumbers corresponding to features 550 km apart (or 11 total 50-km grid boxes per cycle) all the way down to higher wavenumbers at 150 km apart (3 grid boxes per cycle).

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Cool season precipitation projections for California and the Western United States in NA-CORDEX models

Climate Dynamics ◽

10.1007/s00382-021-05632-z ◽

2021 ◽

Author(s):

Kelly Mahoney ◽

James D. Scott ◽

Michael Alexander ◽

Rachel McCrary ◽

Mimi Hughes ◽

...

Keyword(s):

United States ◽

Climate Models ◽

Snow Water Equivalent ◽

Regional Climate ◽

Regional Climate Models ◽

Western United States ◽

Monthly Precipitation ◽

Wet Season ◽

Cool Season ◽

Projected Change

AbstractUnderstanding future precipitation changes is critical for water supply and flood risk applications in the western United States. The North American COordinated Regional Downscaling EXperiment (NA-CORDEX) matrix of global and regional climate models at multiple resolutions (~ 50-km and 25-km grid spacings) is used to evaluate mean monthly precipitation, extreme daily precipitation, and snow water equivalent (SWE) over the western United States, with a sub-regional focus on California. Results indicate significant model spread in mean monthly precipitation in several key water-sensitive areas in both historical and future projections, but suggest model agreement on increasing daily extreme precipitation magnitudes, decreasing seasonal snowpack, and a shortening of the wet season in California in particular. While the beginning and end of the California cool season are projected to dry according to most models, the core of the cool season (December, January, February) shows an overall wetter projected change pattern. Daily cool-season precipitation extremes generally increase for most models, particularly in California in the mid-winter months. Finally, a marked projected decrease in future seasonal SWE is found across all models, accompanied by earlier dates of maximum seasonal SWE, and thus a shortening of the period of snow cover as well. Results are discussed in the context of how the diverse model membership and variable resolutions offered by the NA-CORDEX ensemble can be best leveraged by stakeholders faced with future water planning challenges.

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Spatial and temporal characteristics in streamflow-related hydroclimatic variables over western Canada. Part 2: future projections

Hydrology Research ◽

10.2166/nh.2016.045 ◽

2016 ◽

Vol 48 (4) ◽

pp. 932-944 ◽

Cited By ~ 4

Author(s):

H. C. L. O'Neil ◽

T. D. Prowse ◽

B. R. Bonsal ◽

Y. B. Dibike

Keyword(s):

Snow Depth ◽

Climate Models ◽

Regional Climate ◽

Regional Climate Models ◽

Cold Season ◽

Maximum Temperature ◽

Western Canada ◽

The North ◽

Spring Freshet ◽

Hydroclimatic Variables

Much of the freshwater in western Canada originates in the Rocky Mountains as snowpack. Temperature and precipitation patterns throughout the region control the amount of snow accumulated and stored throughout the winter, and the intensity and timing of melt during the spring freshet. Therefore, changes in temperature, precipitation, snow depth, and snowmelt over western Canada are examined through comparison of output from the current and future periods of a series of regional climate models for the time periods 1971–2000 and 2041–2070. Temporal and spatial analyses of these hydroclimatic variables indicate that minimum temperature is likely to increase more than maximum temperature, particularly during the cold season, possibly contributing to earlier spring melt. Precipitation is projected to increase, particularly in the north. In the coldest months of the year snow depth is expected to increase in northern areas and decrease across the rest of study area. Snowmelt results indicate increases in mid-winter melt events and an earlier onset of the spring freshet. This study provides a summary of potential future climate using key hydroclimatic variables across western Canada with regard to the effects these changes may have on streamflow and the spring freshet, and thus water resources, throughout the study area.

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