Lesley L. Smith – Texas Extreme Precipitation


All plots preliminary.
Right click to see bigger versions.

New Most recent plots first.

re. May 2015 precipitation
How do El Ninos and/or Climate Change affect TX OK precip?

Figures for Cheng et al 2016 paper here

Supplementary Figures

Re. 'model validation'

Re. 'Definition of El Nino'
Re. Step 1:

Re. Step 3: We use each separate 30-year era and normalize by the standard deviation



Standardizing 2050-2080 time series by 1985-2015 standard deviation (notice this case has a mixture of reference periods)

Standardizing 2050-2080 time series by 1985-2015 standard deviation and computing anomalies with respect to 1985-2015

Re. Description of event:
 

Re. 'Definition of El Nino'
For the CESM1 LENS data, we essentially follow the Climate Prediction Center's definitions of Cold & Warm Episodes by Season (www.cpc.ncep.noaa.gov).
Below plots in this section show sample runs 1 - 5:
Step 1: We use each separate 30-year era and compute ONI:



above units degrees C
Step 2: We use each separate 30-year era and detrend:



above units degrees C
Step 3: We use each separate 30-year era and normalize by the standard deviation



values > 1 are considered El Ninos

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Re. 'Model Validation'

Observations El Nino Mays
For observations, following original CPC convention, Nino3.4 region SST anomalies wrt 1971-2000 and with 3 month running mean,
values > 0.5oC are El Ninos

 

Model CESM1 LENS El Nino Mays [mm/day] where El Ninos computed as above in model section

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Observations All Mays

Model CESM1 LENS All Mays



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time series of various CESM1 ensemble means


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CESM1 data sorted by precipitation in TX and OK

Precipitation
Wettest runs:





Wettest quintile

TS
Wettest runs:


Wettest quintile:

Z250
Wettest runs:


Wettest quintile:

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For the TX/OK area Strong May El Ninos


below precip units are mm/day and precipitable water units are kg/m2
digital numbers under titles are the slopes of the best fit lines

All months

Mays only


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Trends in CESM Precipitation:

Ensemble averages:

Individual runs here


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Anomalies for El Ninos for 3 30-year periods:


Everything above detrended over 31-year periods repectively.

Anomalies for the top-El-Nino-related-precipitation for 3 30-year periods:


Everything above detrended over 31-year periods repectively.


Everything above detrended over 31-year periods repectively.

CESM1 Z250 regression with Nino3.4 index for 3 eras:
Mays only
El Ninos only:


All Nino3.4 cases (El Ninos, ENSO Neutral, La Ninas):
detrended and standardized:

Not detrended and standardized:

CESM1 TS regression with Nino3.4 index for 3 eras:
Mays only

detrended and standardized:

Not detrended and standardized:

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CESM1 Precipitable Water


Area average for TX OK: 26.14823, 27.04114, 31.95849 kg/m^2 for 3 eras, respectively.


Standard deviations compare different runs in the ensemble.


Percentages above computed wrt average over 1985-2015 period.
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Observations

SST Observations

Precipitation Observations

GPCP Precip

Climate Division Precip

Z Observations

NCEP Reanalysis:

Precipitable Water Observations

NCEP Reanalysis:


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SST Observations

Various

SST Trend:



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TEXAS PRECIPITATION


old Variability below
old Climatologies below

Comparing temporal periods here

ENSO plots here
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Z500 corresponding to wettest precip

Models:



Individual runs:





Individual runs:

SSTs corresponding to wettest precip

Models:



Individual runs:






Individual runs:

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SSTs

Various

SSTs for 1920-2015:


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Texas and Oklahoma Precipitation:

Climatologies

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Time series

Climate Division Data:

Model Data:

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Texas, Oklahoma & New Mexico Preciptation:

Observations

Precipitation


Time Series of 1800s-2015 May pcpn for NM/TX/OK area average



dashed blue line is mean (excluding 2015)
small-dashed black lines indicate two standard deviations (excluding 2015)


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Re. wettest May precip quintiles

Composite 500Z/SST for top quintile wettest Mays

Observations:



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Model output (ensemble average):


Model output (individual runs):



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Model output (standard deviation):


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Observations:


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Model output (ensemble average):


Model output (individual runs):



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Model output (standard deviation):


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Variability

regarding observational data variability:

Model Output

regarding model variability:

Maps (right click to see bigger images):
Note: the below "CESM1" data is actually CESM1_AMIP, aka, CAM5 data:

Probability Distributions


observations and concatenated model runs (no ensemble means):



Climatologies:

observational and model data:

Long-term model runs:

GFS and GPCC:

CAM4 and GFS-polar:

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Time Series

large model ensembles:

GFS and GPCC:

CAM4 and GPCC:

Comparing anomalies of ensemble means:


Above numbers are correlations of time series.

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Correlations:

GFS Model:

GFS "fix arctic" Model:

CAM4 fully forced AMIP Model:

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Observations:

Regressions:

GFS Model:


The above analyses did not involve detrending.

Observations

Anomaly Maps

GPCC Data

2015 monthly

1901-2014 monthly climatology:



GPCC monthly precip data from Jon Eischeid.

CFSv2 AMIP Data

2015 monthly

1979-2014 monthly climatology:



CFSv2 AMIP monthly precipitation data from Tao Zhang

Observations May 2015

Daily Precipitation









CONUS Daily data from NWS Advanced Hydrologic Prediction Service

Related Fields Reanalysis Data

Daily Precipitable Water









Daily data from NCEP/NCAR Reanalysis

Daily U-Wind









Daily data from NCEP/NCAR Reanalysis

Daily V-Wind









Daily data from NCEP/NCAR Reanalysis

Observations


Mean Precipitation by season:

Mean precipitation: