DAOS report to WWRP/JSC Feb 2011 Roger Saunders and Pierre Gauthier

Overview of DAOS report to JSC Roger Saunders and Pierre Gauthier WG Activities Update on observations for global NWP Update on developments in DA Results from THORPEX campaigns Paper on targeted observations

Mission statement The DAOS-WG was established to ensure that THORPEX contributes to the international efforts to optimise the use of the current Global Observing System and to the development of well-founded strategies for the evolution of the GOS to support NWP primarily for 1 to 14 day weather forecasting. To achieve its mission the DAOS WG, in collaboration with the CBS OPAG-IOS: Addresses Data Assimilation issues including the development of improved understanding of the sources and growth of errors in analyses and forecasts Promotes research activities that lead to a better use of observations and the understanding of their value Provides input and guidance for THORPEX regional campaigns for the deployment of observations to achieve scientific objectives.

Current membership Pierre Gauthier, Co-chair UQAM, Canada Roger Saunders, Co-chair Met Office, UK Carla Cardinali ECMWF Ron Gelaro, NASA, USA Tom Hamill NOAA, USA Tom Keenan CAWCR, Australia Rolf Langland NRL, USA Bertrand Calpini MeteoSwiss, Switzerland Andrew Lorenc MetOffice, UK Florence Rabier Météo-France Prof. Bin Wang, Chinese Academy of Sciences, China Michael Tsyroulnikov HydroMet Centre, Russia Chris Velden Univ Wisconsin- CIMSS, USA

3 rd THORPEX DAOS Working Group meeting Université du Québec à Montréal 8-9 July 2010 Montréal (Québec) CANADA *

Update on Observations E-AMDAR coverage expanding and now water vapour Use of IASI radiances over cloud shown to be beneficial Chinese FY-3A MW sounder radiances proven for NWP Reduced thinning of AMSU-A radiances at ECMWF Use of Hi-RES AMVs for improved TC forecasts Continuity of scatterometer (Oceansat-2?) and GPS-RO data (COSMIC-2) looks hopeful Polar Communications and Weather Mission in a Molniya orbit for improved coverage of the northern polar latitudes. Raman lidar shows vertical profiles of water vapour at very high time and vertical resolution and can be available 24 hrs a day for high resolution mesoscale models. Common data format for radar backscatter measurements

7 E-AMDAR: Network Performance 1.

8 E-AMDAR: Network Performance 2.

9 E-AMDAR: Network Developments 1. 1st Nov EZY fleets providing data over UK domain and selected European airports. Software installed on BAW A319 (LCY – SNN – JFK).

10 E-AMDAR: WVSS Programme 1.

11 US (NOAA): WVSS Programme 1.

12 PCW

AMVs for Sinlaku in NCEP data file for assimilation (CTL)

CTL: NCEP cloud winds CIMSS-6h: CIMSS 6-hourly wind Enhanced AMVs from CIMSS

Track and Intensity Analyses for Sinlaku (32 members) Enhanced AMVs: Significant improvement in analyzed position, track and intensity in first 3 days

This plot shows the density of AMSU-A channel 9 data for the case of for the different experiments: EXP-HI: global thinning to o EXP: global thinning to 1.25 o (i.e. ope) EXP-SV: EXP but with SV thinning o EXP-CLI:EXP but with SVcli thinning o EXP-RND: EXP but with random thinning o Target areas occupy same fraction (15%) of the Southern hemisphere. The SV-based climatology was derived from the mean 2007 SV-areas Experiments have been run for JAS08 and D08JF09 Forecasts from these experiments have been verified against EXP-HI analyses (~83 cases per season AMSU-A thinning experiments EXP-HI EXP EXP-SV EXP-CLI EXP-RND

Update on Data Assimilation Higher resolution reduced thinning Observability of structure functions Move to hybrid 4D-Var systems EnKF systems also being trialled Improved background error statistics are key to make better use of humidity observations Adjoint sensitivity tools now implemented at most global NWP centres. What about regional/mesoscale?

Campaigns sponsored by THORPEX

Concordiasi: an international project Participating Institutes: CNES, CNRS/INSU (LMD, LGGE, LA), Météo-France, NSF, Alfred Wegener Institute, Met Office, Purdue University, UCAR, University of Colorado, University of Wyoming, BSRN Polar institutes: IPEV, PNRA, USAP, BAS, ECMWF Collaborating institutes: NWP centres (Australia…), NASA/GMAO, UCLA, …. Part of the THORPEX-cluster Overview of Concordiasi : “The Concordiasi project in Antarctica” Rabier et al, Bulletin of the American Meteorological Society, January Website:

CONCORDIASI In September and October 2010, 19 balloons were deployed from McMurdo, 6 with a scientific payload sounding the stratosphere, and 13 of the driftsonde type. From the 13 driftsondes, around 640 dropsondes were dropped over Antarctica and the surrounding seas. Most of these were transmitted in real-time on the Global Telecommunication System, for use by the Numerical Weather Prediction centres.

Balloon tracks

Dropsonde coverage

Concordiasi: Sep 2010 Dropsonde Data 39 reports up to 21Z 30/9/ assimilated. Wind: Similar bias/rms to Antarctic sondes. Temp: ~+0.5 K bias above 600hPa. ~-1.0K bias near surface (few reports rejected). Humidity: 11/37 reports rejected. Not RS92 so data <-40C not used.

Assimilation of surface sensitive observations from AMSU over land: Impact on humidity analyses Impact studies with 2 versions of ARPEGE: CY32 and CY33 during summer CY33 introduces important changes in the physics. Data assimilation is identical between the two versions and takes advantage of better description of the land surface emissivity to assimilate the observations near the surface (Karbou et al ab). TCWV (EXP-CTL), CY32, August 2006 TCWV (EXP-CTL), CY33, August 2006 Similar humidity bias features were noticed with the assimilation of MERIS observations over land (Bauer, 2009) and AMSU observations in IFS More moisture in EXP F. Karbou

HyMeX: 2 types of balloons will be used in BAMED project (CNES) Alex Doerenbecher, Clement Fesquet, Claude Basdevant

The intercomparison experiment on the impact of observations  A goal of THORPEX is to improve our understanding of the ‘value’ of observations provided by the current global network  In 2007, DAOS-WG proposed a comparison of observation impacts in several forecast systems, facilitated by the emergence of new (adjoint-based) techniques  Experiments for a baseline observation set were designed by DAOS members from NRL, GMAO, EC, ECMWF, Météo-France …so far, results obtained for 3 systems: NRL, EC, GMAO optimize the use of current observations inform the design/deployment of new obs systems

 AMSU-A,  Raob,  Satwind and  Aircraft have largest impact in all systems GMAO GEOS-5NRL NOGAPS EC GDPS         27 Global domain: UTC assimilations Jan 2007 Daily average observation impacts

24h Observation Impacts in GEOS-5 Average values at 00z for the period 01 Sep – 31 Dec 2010 Global Northern Hemisphere TropicsSouthern Hemisphere

Total # of targeted radiosonde data = 27,508 (06UTC and 18UTC) Number of targeted radiosonde profiles = 247 (33 stations provided at least one profile) Total targeted radiosonde impact = J kg -1 For comparison: 00UTC and 12UTC observations from these same stations: J kg -1 and 2,154 profiles during all of January x10 -3 J kg -1 (Moist Total Energy Norm) Error Reduction Error Increase Circled stations provided ten or more profiles JANUARY 2009 Petropavlosk

FEBRUARY 2009 TARGETED DROPSONDE IMPACT ON 24H FORECAST ERROR IN NOGAPS/NAVDAS 1x10 -3 J kg -1 (Moist Total Energy Norm) Error Reduction Error Increase Total # of assimilated dropsonde data = 32,172 (T, q, u, v at all levels) Number of dropsonde profiles = 355 Total dropsonde impact = J kg -1 Average impact per dropsonde observation = -2.23x10 -5 J kg -1 Impact summed in 2x2 lat/lon boxes

1x10 -3 J kg -1 (Moist Total Energy Norm) Error Reduction Error Increase Impact summed in 2x2 lat/lon boxes January 2009 – all analysis times EAMDAR Summary Impact #of observations Level Flight J kg , % from Dec 2008 Ascent Profiles J kg -1 79, % from Dec 2008 Descent Profiles J kg -1 33, % from Dec 2008 ALL Lufthansa AMDAR

Summary of intercomparison  Comparison experiments for GMAO, NRL and EC systems completed for baseline set of observations and now UKMO added  Despite differences in assimilation methodologies, overall quantitative results similar for all systems; but details of impact differ (e.g., impact-per- ob, channels)  Largest impacts provided by AMSU-A and raobs (GMAO, UKMO), AMSU-A and satwinds (NRL, EC); aircraft also has large impact in all systems  Common problem areas with AMSU-A noted; handling of surface properties a likely cause  First paper of adjoint impact intercomparison facilitated by DAOS WG has been published (Gelaro et al. 2010)

DAOS-WG draft statement on need for additional in-situ observations There is increasing evidence based upon results from A- TREC, TPARC, AMMA (in the form of OSEs, adjoint- based observation impact studies, and analysis uncertainty estimates) to recommend, if feasible, increases in observations from: Commercial aircraft over the N. Pacific, N. Atlantic, and the S. Hemisphere in general. Additional soundings from certain coastal radiosondes, including those in eastern Siberia, and perhaps selected stations in polar regions, Africa, and South America. to improve NWP forecasts in the 2-5 day timeframe.

Review of the impact of targeted data Community paper being written * Lead author is Sharan Majumdar with contributions from the DAOS-WG and scientists involved in targeting campaigns (including Y. Song and Z. Toth) Reconcile seemingly opposing views on the impact of targeted data * Summary of results obtained so far * Identify issues that need to be addressed to improve the use of observations that impact weather forecasts (e.g., metrics, assimilation methods, sampling of precursors to dynamic instability)

A. Doerenbecher, Météo France The targeting procedure

Field Campaigns: pre-THORPEX / independent campaigns 1997: FASTEX 1998: NORPEX 1999-present: NOAA Winter Storm Reconnaissance (WSR) : NOAA Hurricane Synoptic Flow 1997-present: NOAA Hurricane Synoptic Surveillance 2003-present: DOTSTAR Typhoon Surveillance

Field Campaigns: THORPEX era 2003: A-TReC. Atlantic, minimal impact. (Forecasts very good without targeted obs) : European Experiments with a small targeting component: AMMA-THORPEX, COPS/E- TReC, GFDex, DTS-MEDEX, THORPEX-IPY 2008: Summer T-PARC 2009: Winter T-PARC 2010 and future: Concordiasi, HYMEX, T- NAWDEX (THORPEX PDP) EURORISK PREVIEW helped facilitate coordination

Winter T-PARC case Y. Song, NOAA/NCEP

NCEP GFS KMA WRF no mean improvement? JMA GSM ECMWF improvement after 72 h Period: and track error reduced by up to 200km! Summer T-PARC: effectiveness of targeted obs depends on model/DA M. Weissmann, DLR

Conclusions 1 Extratropical: average value of targeted data (mostly from aircraft) is positive but small. –Still a lack of strong consensus, limited evaluations –Results may depend on choice of verification metric Tropical cyclones: significant benefits sampling around the storm; results depend on model. Most evaluations for short-range (1-3 day) forecasts. Smaller sample for medium-range; results promising in some cases, neutral in others.

Conclusions 2 Targeting techniques that identify ‘sensitive’ areas sometimes agree, sometimes disagree, but are not thought to be the first-order problem. –Targeting in sensitive areas is better than at random –Target areas are often in cloudy areas and/or baroclinic zones Results from the adjoint-based observation impact calculations can be used to explain why we cannot consistently get large impacts from a few targeted observations. –Benefit of aircraft data per observation is large, but cumulative benefit is small.

Recommendations Seek to further optimize existing resources: commercial aircraft, rawinsonde network, satellite radiances, atmospheric motion vectors Account for data assimilation scheme in targeting strategy; quantitatively predict effects of obs Further evaluations with common cases and multiple models/DA would strengthen conclusions Targeting for longer-range f/casts is interesting topic, but results are not mature enough to make an authoritative statement. Broader-scale regime-based targeting seems the most promising approach.

Targeted Observations for Improving Numerical Weather Prediction: An Overview S. J. Majumdar (RSMAS/U. Miami) R. Saunders, P. Gauthier (DAOS WG Co-Chairs) S. Aberson, C. Bishop, C. Cardinali, J. Caughey, A. Doerenbecher, R. Gelaro, T. Hamill, R. Langland, A. Lorenc, T. Nakazawa, F. Rabier, C. Reynolds, Y. Song, Z. Toth, C. Velden, M. Weissmann, C.-C. Wu plus contributions from past and present DAOS WG members Manuscript in preparation for WMO Report and BAMS