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Verification of NAEFS Land-Surface Forecasts in Warm Season JAS 2006

Wanru Wu, Kingtse Mo and Muthuvel Chelliah

Climate Prediction Center/NCEP/NOAA

CDPW 2007, Tallahassee Florida

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Provide experimental objective drought monitoring and outlook over the United States and Mexico in support of the National Integrated Drought Information System (NIDIS)

Explore the possibility to apply the North American Ensemble Forecast System (NAEFS) for short-range drought outlook operationally

Motivation & Objective

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NAEFS: an ensemble forecast system that combines state-of-the-art weather forecast tools developed at the U.S. National Weather Service and at the Meteorological Service of Canada to provide numerical weather prediction products in both countries for a forecast period of 1-14 days (see details at http://www.emc.noaa.gov/gmb/ens/NAEFS.html).

Data: archived since 23 May 2006. Means and spreads for week1 (1-7 days) and week2 (8-14 days) forecasts were calculated from 60 ensemble members, with 1x1 degree spatial resolutions and 6-hour temporal intervals.

Forecast Verification: focused on the warm season JAS 2006. Data from the North American Regional Reanalysis (NARR) were used for the verification. Note that the NAEFS DO NOT initialize the land-surface conditions.

Data

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Errors are consistent:Positive P error positive SM error positive E errorCooler Ts is also consistent with more P

Mean Errors Averaged over JAS 2006

Errors are large ( > 1 std), especially for SM

Error patterns are similar for Week1 & week2 forecasts

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RMSE vs. Training Period

Fcst (corrected) = Fcst - X1(Fcst) + X2(RR)

where

X1(Fcst) = ave(Fcst, t=t-T-t0, t=t-t0)

X2(RR) = ave(RR, t=t-T-t0, t=t-t0)

T = the training period t0 = 7 & 14 days for week1 & week2 forecast correction, respectively

RMSE averaged over 70o-125oW 20o-50oN

RMSE is not sensitive to T > ~ 2 weeks

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Black – no correction

Red – after correction

Anomaly Correlation over 70o-125oW 20o-50oN

P 0.38 0.45 0.14 0.22

SM 0.20 0.79 0.12 0.66

E 0.34 0.61 0.26 0.47

T2m 0.57 0.81 0.36 0.55

Week1 Week2

SM and E errors are mostly systematic

T2m and P are less so

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Errors Averaged over 31o-35oN for Week1 Forecasts

SM & E: mostly corrected

T2m: largely corrected

P: complicated

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Errors Averaged over 31o-35oN for Week2 Forecasts

Similar as week1

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Anomalies Averaged in JAS with Respect to RR Climatology

Verification

Forecasts

Error-Corrected Forecasts

Patterns improved after the correction

P T2m

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Errors in the Initial Conditions Averaged for July 2006

The NAEFS do not initialize the land-surface conditions.

Errors are mostly inherited from the initial conditions.

Forecast Error IC Error

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Errors in IC of May 23, 2006

(a) SM IC - RR (b) T2m IC - RR

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The Verification Reliability

RR, Noah, Mosaic & VIC 4-Model Ensemble Anomaly & Spread JAS 2006

NAEFS Forecast Mean Errors JAS 2006

Errors >> Model Spreads

(a) Ensemble Anomaly

(b) Spread

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Experimental Operational Forecasts – Precip (mm)

CPC real time precipitation analysis

7-day accumulation 12Z10Oct2007–12Z17Oct2007

Made on 09Oct2007 Made on 02Oct2007

NAEFS Forecasts

00Z10Oct2007– 00Z17Oct2007

http://www.cpc.ncep.noaa.gov/products/Drought

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Experimental Operational Forecasts – Temp (oC)Made on 09Oct2007 Made on 02Oct2007

NAEFS Forecasts

10 Oct 2007–16 Oct 2007

CPC 7-day temperature analyses

7-day mean anomaly ending 16 Oct 2007

http://www.cpc.ncep.noaa.gov/products/Drought

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Experimental Operational Forecasts – SM (mm)Made on 09Oct2007 Made on 02Oct2007

NAEFS Forecasts 10 Oct 2007–16 Oct 2007

CPC Leaky Bucket Model 7-day mean anomaly 10 Oct 2007–16 Oct 2007

RR 7-day mean anomaly

http://www.cpc.ncep.noaa.gov/products/Drought

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Summary Large systematic errors exist in the verified land-surface quantities, especially for soil moisture and evaporation.

The NAEFS do not initialize the land-surface conditions for forecasting, a large portion of the mean errors is inherited from the initial conditions.

Forecasts are significantly improved after the error correction.

The systematic error correction is not sensitive to the training period.

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Future Plans

1. Add more hydro-meteorological variables: Snow depth, Snow water equivalent, & Runoff.

2. Use ensemble NLDAS to correct systematic errors.

3. Leave no county behind - downscale

NAEF forecasts forcing NLDAS models to produce ensemble forecast products at 1/8 degree.

4. Use CFS to extend forecasts beyond 2 weeks.