1. 1 Impact of the NAME04 Soundings on the NCEP data assimilation systems Wesley Ebisuzaki Kingtse Mo, Eric Rogers, Wesley Ebisuzaki, R. Wayne Higgins, Jack Wollen and Marco Carrera Climate Prediction Center NOAA/NWS/NCEP

2. 2 NAME04 Special Upper Air Soundings During the EOP Altair, Yuma did not get onto the GTS; 25% Loreto data did not get in. All other stations had less than 10 reports missing.

3. 3 Data Impact Experiments NAME04 EOP (1 July – 15 August,2004) Experiments accomplished: CDASw, CDASwt, CDASwtmex GDASw; RCDASw, RCDASwt, RCDASwtmex EDASw, EDASwt. EDASwtmex DASw is the operational product

4. 4 Global and regional data assimilation systems GLOBAL: CDAS2 (Climate Data Assimilation System): T62L28 The CMAP precipitation is used to adjust soil moisture, but no direct assimilation of P GDAS (Global Data Assimilation System) :T254T64 model. No P assimilation Regional : EDAS: ( Eta model 3D-Var Data Assimilation system) 12KM 60 layers. It assimilates radar precipitation data over the continental US. RCDAS ( Regional Climate Data Assimilation System) 32Km, 45 layers, It assimilates P.

5. 5 INPUT data Input data In all assimilation systems All systems use rawinsondes, dropsondes, cloud drift winds from Geostationary satellite and aircraft data getting into the buffer. They all use the TOVS-1B radiance data Major differences Both the GDAS and EDAS use more satellite observations than the CDAS2 and RCDAS: SSM/I wind speeds, TRMM TMI precipitation estimates, NOAA-15, NOAA-16 AMSU-A 1b radiances and NOAA-15 –16 and –17 AMSU-B 1b radiances

6. 6 Ratio=  diff**2/var Z500V850CDASw-CDASwt CDASw-CDASwtmex

7. 7 P over the EOP obs CDASw CDAS wt CDAS wtmex Improvement over the SMO, but not over the AZNM area

8. 8 Vertically integrated moisture flux (vector) (qv,contoured) GDAS CDAS w CDAS wt Diff

9. 9 Puerto Penasco 31.18N, 113-33W The CDASw really tries, But the coarse resolution Model is not able to take advantage of the soundings

10. 10 Conclusions 1. The impact of the NAME 04 soundings is largely local and is concentrated over the NAME core region; 2. Over the monsoon region, rainfall improves with soundings, but the coarse resolution model Is not able to take advantage of the soundings to improve the moisture fluxes

11. 11 2. 1. Differences of the NAME Soundings are local and concentrated over the Tier I area for both RCDAS and EDAS. 2. At upper level, the impact on winds and Circulations are similar for the RCDAS and the EDAS RCDASEDAS

12. 12 [qv] (contoured) and [qu,qv] flux(vector) with soundings 1.GPLLJ: The GPLLJ from RCDASw and RCDASwt, GDAS are similar,while the EDASDwt shows a stronger jet. 2. The GCLLJ from the GDAS, and EDASw and EDASwt are similar, while the RCDAS depicts a very strong jet with a center over the Gulf of California Units:kg m -1 s -1 EDASw EDASwt RCDASw RCDASwt

13. 13 a)Obs soundings [qv] at Puerto Penasco (31.3N, 113.5W) at northern Gulf of California. unit is (g/kg)(m/s) When the soundings are assimilated, the differences between the observations, EDAS and RCDAS are close. When the soundings are taken out, the differences are greater than 60 (k/kg)(m/s)

14. 14 [qu,qv] anomalies for 3 surge events

15. 15 Impact of soundings on the EDAS fcsts CMORPH EDAS day 2-3 EDASw-EDASwt day 2-3 fcsts EDASw-EDASwt 3hr fcsts

16. 16 Conclusions The impact of the NAME04 special soundings on global and regional analyses and short range forecasts is largely local and is concentrated over the Tier 1 area. The impact on analyses differs from system to system. Overall, the soundings will correct some uncertainties in the assimilation system and improve the analyses

17. 17 Conclusions EDAS:The NAME soundings improve the magnitude and location of the GPLLJ and improve rainfall over northeastern Mexico. RCDAS: Soundings improve the GCLLJ Soundings will improve analyses somewhat, but they will not correct all errors in the system.

18. 18 Qfluxes IMPACT on qfluxes for EDAS IMPACT for RCDAS Differences between EDASw and RCDAS w qv qu

19. 19 Experiments w/wt P assimilation Four experiments: RCDASw(P): with P assimilation, with soundings; RCDASwt(P): with P assimilation, without soundings; RCDASw(no P): without P assimilation, with soundings; RCDASwt(no P): without P assimilation and without soundings

20. 20 Precip from RCDAS EOP mean obs RCDASw(P) RCDASw(no P) RCDASwt(no P)

21. 21 Vertical cross section of qv at 30N Impact of sndings w PImpact of sndings wt P Impact of P w sndings Impact of P wt sndings

22. 22 T2m diff RCDASw(P)-RCDASw (no P) Impact due to P assimilation with soundings RCDASwt(P)- RCDASwt(no P) Impact due to P assimilation Without soundings RCDASw(P)-RCDASwt(P); Impact due to soundings

23. 23 Temperature profile between soundings and molts Black (with P with sndings); Green (with P wt sndings) blue (no P w sndings) Red (no P wt sndings) Over N Mexico, The impact of P assimilation Is larger than the NAME04 soundings No P With P Torreon Chihuahua

24. 24 Conclusions The differences between analyses with and without soundings are smaller than the differences between two regional systems. The P assimilation has large impact on analyses, but the impact differs from the soundings

25. 25 Goal: Prediction of summer precipitation over the United States and Mexico Challenges: 1.Truth: Analyses depend on the model, assimilation system and data inputs. The differences can be very large. We have more than one version of the “Truth”, what are we going to do about?

26. 26 Analyses Analyses can only be as good as the model, assimilation system and the input data including precipitation; Impact of soundings on short range forecasts is small. Why? 1. No changes on long waves; 2. Model’s convection has problems; 3. Targeting?

27. 27 P assimilation (Lin et al. 2004) Compare the model P and observed P; Change the latent heating profile, water vapor mixing ratio and cloud water fields  P (assimilation) is close to P obs;  Changes in E and soil moisture and changes in temperature profile.

28. 28 Difference in moisture transport Impact of Soundings w PImpact of Sndings no P P impact w sndingsP impact wt sndings

29. 29 Input data differences among the NCEP data assimilation systems Not usedUsed NOAA-15 –16 and –17 AMSU-B 1b radiance s Not usedUsed NOAA-15, NOAA-16 AMSU-A 1b radiances Not used Used over land GOES precipitable water Precipitation included through variational scheme and model physics Not usedUsedNot used TRMM TMI precipitation estimates Precipitation included through variational scheme and model physics Not usedUsedNot used SSM/I precipitation estimates Not used Used SSM/I precipitable water Not usedUsedNot used Quickscat wind speed and direction Not used Assigns direction from guess Used directly SSM/I wind speeds u,v T, s and q From the COADS u, v, T, Ps, q Surface ship and buoy observations Ps 10m winds,2m q Psu, v, T, Ps, q Surface land observations not usedu, v GOES water vapor cloud top winds u, vu, v, Tu, v GMS, METEOSAT,GOES cloud drift IR and visible winds CommentsRegional CDAS Eta operationalGFSInput Data

30. 30 Vertically Integrated Meridional Moisture Flux (kg/ms) (1995-2000) GCLLJ RROperational EDAS

31. 31 RROperational EDAS Vertical cross section of qv at 30N 1998-2000

32. 32 For the EOP period, 96- hr fcst was performed each day at 0Z, The RSM errors for Z500 AND v850 over the PNA region (150W- 60W,20-50N) is very small, but at 96 hr, the regional differences over the Gulf and the SMO regions are visible RMS errors ICs CDAS wICs CDAS wt 12h 24h 96 h