by R.W. Higgins 1 , V. Silva 2 , W. Shi 1 , and V. E. Kousky

1. Comparison of Daily Precipitation Statistics for the US in Observations and in the NCEP CFS by R.W. Higgins1, V. Silva2 , W. Shi1 , and V. E. Kousky 1Climate Prediction Center, Camp Springs, MD 2RS Information Systems, Mclean, VA

2. Overview Compare statistics of daily precipitation within seasonal climate over the U.S. using gridded station data (1948-2006), NCEP CFS re-forecasts (1981-2005) and CFS CMIP 100-yr simulations: Current Goals: Identify the regional & seasonal dependence of the bias in CFS re-forecasts Examine differences by ENSO phase Examine differences in the frequency of wet and dry spells Future Goal Develop more reliable ensemble-based probabilistic forecasts in real-time at weeks 2-4 (e.g. risks of heavy rain events);

3. Data US Unified Raingauge Database (Higgins et al. 2000) - multi-year (1948-2006) daily analysis (12Z-12Z). - horizontal resolution: (lat, lon)=(0.25°x0.25°) - domain: (140oW-60oW,10oN-60oN) - Cressman (1959) - advanced QC (duplicate, buddy, std dev, radar) NCEP CFS retrospective forecasts (“re-forecasts”) - fully coupled O-A-L prediction system; T62L64 (Saha et al. 2006). - atmosphere (GFS 2003), ocean (GFDL MOM3) - 1981-2005; 15 fcsts per calendar month out to nine months - atmospheric ICs (NCEP/DOE Reanalysis 2; Kanamitsu et al. 2002) - ocean ICs (NCEP GODAS; Behringer 2005). NCEP CFS CMIP Simulations - 100 years; T126L64 - CMIP 1 (init Jan 1, 2002) and CMIP 2 (init Jan 1, 1984)

4. Average Observed Number of Days per Season with p > 1 mm (1981-2005) Average Number of Days per Season with p > 1 mm (CFS Re-forecasts – OBS) • - Observed annual cycle shows highest number of wet days per season in PNW (fall and winter), SE (summer), NE (spring, summer) and SW (summer) • Difference patterns show considerable evolution depending on season and lead: • JFM: positive bias along northern tier at all leads • AMJ: positive bias in west; negative bias GP, GC • JAS: negative bias in SW & GC • OND: positive bias in NP

5. Average Number of Days-per-Season with p > 1 mm (CFS Re-forecasts – CMIP 1) (CFS Re-forecasts – CMIP 2) Differences between the CFS re-forecasts and the CMIP simulations were examined to see if spin-up might be affecting the CFS re-forecast results at shorter leads. There are obvious differences between day 1 and day 10 patterns that appear to be due to the affects of spin-up, while the day 10 and day 100 patterns are similar.

6. Regional Characteristics of the Bias • Bias in the number of days with precipitation in CFS has considerable spatial and temporal variability through the annual cycle. • To examine regional characteristics of the bias, 4 regions were selected based on areas of large bias in the spatial difference (CFS-OBS). Care was taken to choose areas with bias of one sign or the other. • Four regions: • Interior Pacific Northwest (PNW) - (42.5oN-47.5oN, 115oW-120oW) North-Central (NC) - (45oN-47.5oN, 95oW-100oW) • Southwest (SW) - (32.5oN-37.5oN, 107.5oW-112.5oW) Southeast (SE) - (30oN-35oN, 82.5oW-87.5oW)

7. Average Number of Days per Season with Precipitation by Categorical Amount OBS CFS Day 1 CFS Day 10 CFS Day 100 • PNW: Too many precipitation events (P> 4 mm/day) during boreal winter; bias increases with forecast lead suggesting spin-up effects. Orographic influences too far downstream in CFS? Effect of model resolution? • NC: Too many precipitation events for all precipitation intensities during fall and winter. Overactive shallow convection in CFS? • SE and SW compare well during boreal fall and winter

8. Average Number of Days per Season with Precipitation by Categorical Amount OBS CFS Day 1 CFS Day 10 CFS Day 100 • NC: Too few light precipitation events during boreal summer; bias decreases at longer leads. • SW: Too few light precipitation events during boreal summer; bias decreases at longer leads. Weak monsoon? • SE: Negative bias for light events and positive bias for heavy events during JAS. Diurnal cycle too strong?

9. ENSO Composite Analysis: Observations • El Niño & La Niña episodes are identified using the Oceanic Niño Index (ONI) (Kousky and Higgins 2007). • The ONI is computed from 3-mrm values of SSTA in the Niño 3.4 region (5N-5S,120W-170W) using a set of homogeneous historical SST analyses (ERSST.v2 of Smith and Reynolds 2003). • El Niño & La Niña episodes are defined as 5 (or more) consecutive 3-month seasons during the period 1950-2006. El Niño neutral La Niña

10. ENSO Composite Analysis: CMIP Simulations CMIP 1 • A similar procedure is used to identify ENSO episodes in the CFS CMIP simulations (i.e. define an ONI; identify El Niño and La Niña episodes) • The results are similar whether we use 59 years (to match the observations) or 100 years, so we use 100 years to improve the statistics. • The Table shows the number of warm (El Niño), neutral, and cold (La Niña) episodes in the CMIP1 and CMIP 2 simulations. CMIP 2

11. Departures from Average Number of Wet Days (p > 1 mm) by Season and by ENSO Phase (OBS) (CFS CMIP) (Based on ENSO events during 1948-2006) Base period is 1948-2006 (Based on ENSO events from 100 yr simulation) Base period is 100 yr • CFS reproduces many of the classical features of the ENSO precipitation anomaly patterns, but there are some systematic differences.

12. Average Number of Wet Days (p > 1 mm) by Season and by ENSO Phase (CFS CMIP – OBS) OBS: Based on ENSO events during 1948-2006 CMIP: Based on ENSO events from 100 yr simulation Composite differences are based on the full fields • CFS has a positive bias in the average number of wet days per season independent of ENSO phase, except in the Southwest during the warm season. • The CFS has as a positive bias of up to 30-40 additional wet days per season, which implies that it rains nearly every day at some locations.

13. Total Number of Wet Spells for Conterminous US OND OBS (1948-2006) and last 59 yrs of CMIP 1 JFM OND and JFM: - CFS has a positive bias in the number of wet spells in the PNW and along the northern tier-of-states and a negative bias in the SE. - Results suggest a systematic northward shift of the jetstream and stormtrack in CFS, and a tendency for the flow to be too zonal in CFS relative to OBS.

14. Total Number of Wet Spells for Conterminous US AMJ OBS (1948-2006) and last 59 yrs of CMIP 1 JAS AMJ and JAS: - CFS has positive bias in PNW and SE & negative bias in SW (JAS only), Great Lakes and Gulf Coast. - Summer monsoon induced precipitation is too weak in CFS relative to OBS. - Land-sea breeze induced precipitation is too weak along the Gulf Coast in CFS (especially JAS) - These analyses motivate additional synoptic studies aimed at improving the linkage between daily precipitation and related circulation features in CFS

15. Circulation Differences CMIP1-CDAS • Average 200-hPa wind was examined for JFM and JJA over the last 50 years of the CMIP1 free run. • The differences between those fields and the 1971-2000 CDAS1 mean fields were used to evaluate the performance of the CFS (CMIP1 run). • Differences are considered to be biases in the model climatology.

16. CMIP1 –vs- CDAS1: NH flow is more zonally symmetric. NH westerlies are shifted poleward. Eastern Pacific low-latitude troughs are too weak.Consistent with positive bias in number of wet spells in CFS along northern tier-of-states

17. CMIP1 –vs- CDAS1: SH flow is more zonally symmetric. NH westerlies are too strong over NH subtropics. Eastern Pacific low-latitude troughs are too weak.

18. CMIP1 –vs- CDAS1: Upper-level ridge too weak in the SW (weak monsoon) - Anomalous convergence (divergence) in SW (PNW) - Consistent with negative (positive) bias in the number of wet spells in SW (PNW) Westerlies are too strong over the hurricane development regions in the Gulf of Mexico, off the Southeast US coast and over the western Caribbean.

19. Total Number of Dry Spells for Conterminous US OBS (1948-2006) and last 59 yrs of CMIP 1 OND JFM OND and JFM: - CFS has a negative bias in the number of dry spells at most locations during boreal fall & winter. - There are very few dry spells longer than about 20 days in the CMIP runs (difference patterns are similar to observed patterns and of opposite sign).

20. Total Number of Dry Spells for Conterminous US OBS (1948-2006) and last 59 yrs of CMIP 1 AMJ JAS • AMJ and JAS: • During boreal spring the CFS has a negative bias in the number of dry spells of all durations at most locations except in the southwestern states. • During boreal summer the CFS has a positive bias in the Southwest (weak monsoon induced precipitation) and along the Gulf Coast (weak land-sea breeze induced precipitation).

21. Statistical Adjustment of CFS Operational Forecasts • The re-forecasts and their corresponding verifications can be used to calibrate ensemble-based probabilistic forecasts. • The value of this approach has been demonstrated for both weather & (short term) climate predictions (e.g. Hamill et al. 2004; 2006). • Day-to-day weather cannot be predicted at leads of 2-6 weeks, but shifts in time averages (e.g. average weather over the period) may still be predicted skillfully. (Signal-vs-noise). • -e.g. likelihood of extreme events (e.g. risk of heavy rain event s, flash floods, flash droughts) • Bias corrected forecasts would be immediately useful in CPC forecast operations for preparation of the day 6-10, day 8-14 forecasts and Hazards Assessments (US, Africa, global tropics).

22. Summary The statistics of daily precipitation within seasonal climate over the U.S. from gridded station data (1948-2006) & from NCEP CFS re-forecasts (1981-2005) and 100-yr CMIP simulations were intercompared. Current Results: Quantified the regional & seasonal dependence of the bias in CFS re-forecasts; Examined differences by ENSO phase; Examined differences in the frequency of wet and dry spells. Future Goal Develop reliable ensemble-based probabilistic forecasts in real-time at weeks 2-4 (e.g. risks of heavy rain events, flash floods or flash drought); Compare current results to those from next generation CFS.