Lidia Cucurull (1) and Richard A. Anthes (2)

1. Impact of Infrared, Microwave and Radio Occultation Satellite Observations on Operational Numerical Weather Prediction Lidia Cucurull (1) and Richard A. Anthes(2) (1 )Earth System Research Laboratory (ESRL) GSD / CIRES NOAA Office of Oceanic and Atmospheric Research (2) University Corporation for Atmospheric Research 12th JCDSA Workshop, 21-23 May 2014, College Park, MD..

2. Motivation • RO limb soundings and passive MW & IR nadir-viewing observations are together the most effective observational systems in reducing forecast error • The limb-viewing and nadir-viewing systems are highly complementary • The assimilation of satellite radiances in operational weather forecasting benefits from the assimilation of unbiased observations that reduce the drift of a weather model towards its own climatology • The goal of the study is to investigate the differences and similarities between the assimilation of RO, MW, and IR observations in the NCEP’s global data assimilation system • Results of the study are under current review (Cucurull and Anthes 2014a, MWR) • A follow-up study to analyze the impact of loss of MW and RO observations in operational NWP has been conducted in support of the US Data Gap Mitigation Activities (Cucurull and Anthes2014b, WAF, in preparation) – a couple of main results will be shown here

3. Radio Occultation ranks very high Cardinally et al. 2011

4. C Radio Occultation Concept Raw measurement is traceable to atomic clock time standard Courtesy of UCAR

5. Experiment Design • Six experiments • CTL, operational configuration with all the observations • BASE, CTL without IR, MW and RO • IR, BASE with IR added • MW, BASE with MW added • RO, BASE with RO added • All experimental forecasts begin 00 GMT and ran for 8 days • Time period: 21 February – 31 March 2013 (first seven days used for model spin-up) • NCEP’s global configuration (hybrid GSI, T574, 64 levels in the vertical) • We looked at fit to radiosondes; horizontal maps of the analysis differences & RMS differences; vertical profiles of global and temporal averages of mean differences, RMS differences and correlations; and anomaly correlation score.

6. Fit to Radiosondes Moisture Temperature • IR, MW, CTL are cold in stratosphere • Warm bias in the upper troposphere • MW produces the largest coldest bias in stratosphere and the warmest bias in the troposphere Dry stratosphere Moist troposphere

7. 850 mb horizontal maps (mean diff) • Impacts within 0.5K in the monthly mean • Greatest differences are in the Southern Hemisphere • MW produces a much warmer analysis over Arctic region, northern Africa, North Atlantic, the Southern Ocean and the western Antarctica. • IR and RO show cooler patterns over the Southern Ocean • All three analyses show a cooler region off the western coast of South America Temperature Moisture • IR and MW show similar patterns – wetter over Africa, off the west coasts of North and South America, and over the tropical Atlantic; and drier over Australia and off the eastern coast of South America • RO shows less impacts

8. 850 mb horizontal maps (RMS diff) Temperature • Maximum impacts generally in SH, with maxima over Antarctica, Southern Ocean and the South Pacific • Region of very large impact off the coast of South America • Large RMS differences over the tropical North Pacific • Similar patterns in IR, MW and RO • Large impact across the globe north and south of the Equator to about 40N and 40S • Strong maxima over Equatorial Africa, the Indian Ocean, tropical North Pacific, and Caribbean and off both the east and wests coasts of South America Moisture

9. Global mean impacts of IR and RO are similar, MW quite different Temperature Largest variability in LT, and between MW and RO In general, high correlation except in LT

10. Overall, drier analyses Moisture High correlations except in LT Overall, small rms differences; smallest between IR and MW

11. 500 mb AC geopotential heights

12. Impact of loss of MW and RO • High vertical resolution (~100 m) • Time period: March-April 2013 • NCEP’s operational configuration • Verification done against consensus analysis (average of NCEP, ECMWF and UK Met Office analyses) • Experiments: • prctl: control, operational configuration with all the observations • prnogps: prctl without RO observations • prnoatms: prctl without ATMS observations • A potential gap in RO is a serious problem (see next slides)

13. Cucurulland Anthes2014b, in preparation

14. Fit to radiosondes RO reduces the bias of the NCEP’s model Evolution of bias at 300 mb F-O (K) Cucurulland Anthes2014b, in preparation

15. Conclusions • Without RO observations, satellite radiances are over or under bias corrected, producing less accurate analysis and forecasts • The largest biases are found for the experiment that only assimilates MW observations • Overall, the patterns of the impact of the different satellite systems are similar, with the MW observations producing the largest impact on the analyses and RO the smallest – due to the lower number of RO observations being assimilated • Positive correlation coefficients of temperature impacts are generally found between the different satellite observation analysis, indicating that the three satellite systems are affecting the global temperatures in a similar way • Correlation for temperature and moisture in the lower troposphere among all three systems is surprisingly small • A potential gap in RO is a serious problem