Calvo Sánchez, Francisco Javier

Campins, Joan

Díez Muyo, María Victoria

Escribá, Pau

Martín Pérez, Daniel

Morales Martín, Gema

Sánchez Arriola, Jana

Viana Jiménez, Samuel

English

Escribà, Pau

Agencia Estatal de Meteorología

J. Calvo et al.Evaluation of HARMONIE-AROME cycle 43h2.1 at AEMETJavier Calvo, Joan Campins, María Díez, Pau Escribà, Daniel Martín, Gema Morales, JanaSánchez-Arriola y Samuel Viana1 IntroductionAfter a thorough evaluation, AEMET’s HARMONIE-AROME deterministic suite has been upgradedto Cycle 43h2,1. A description of the main characteristics of the version and of the local changescompared to the HARMONIE-AROME reference version is done. Finally, an objective evaluation isperformed compared to cycle 40h1.1 and the main meteorological implications of the new version areoutlined.2 Operational set upThe deterministic operational suite is based on HARMONIE-AROME which is run at 2.5 km 4 timesper day with a forecast length of 72 hours over 2 geographical domains (Fig. 1). 3DVar analysis with3hr  cycle  includes  radar  reflectivities,  ATOVS,  IASI,  GNSS  ZTD,  ASCAT  wind  and  AMDARhumidity  observations.  IFS  humidity  enters  in  the  blending  process  (LSMIX)  with  the  ECMWFforecasts. Upper air analysis includes 2 m temperature and relative humidity.SAPP preprocessing is used for conventional observations. Radar data comes from OPERA usingBALRAD preprocesing  and including Spanish,  Portuguese  and French radars.  The  control  of  theHARMONIE-AROME operational suite is based on ecflow.The operational system has been migrated to a new ATOS computer system composed of two clustereach with 140 computed nodes mounted on Bull Sequana X440 A5 chasis. Each node with   2 AMDEPYC™7742 processors (64 cores). The  peak perfrmance of the system is 1350 TFlops.Figure 1: AEMET’s operational domainsACCORD NL 2. February 2022166/172J. Calvo et al.3 Major changes in cycle 43h2.1The major changes of cycle 43h2.1 compared to cycle 40h1.1 are New physiographic data base: ECOCLIMAP Second Generation New clay and sand database (SOILGRIDS) SURFEX 8.1 version (Le Moigne et al., 2018) 2 patches for Nature tile and disabling Surface Boundary Layer Scheme Modified values of minimum stomatal resistance Rsmin  Increase maximum Richardsson number from 0.0 to 0.2 HARATU turbulence scheme updates mixing at the top of PBL EDMF and microphysics optimizations  Decrease soil moisture  increments in  the OI assimilation scheme New blacklisting procedure based on ECMWF's and redesign of the assimilation scriptingsystem.The major local changes compared with the HARMONIE-AROME reference system are Increase roughness increasing heterogeneity of open land patch (FAKETREES) Orographic roughness parametrization OROTUR enabled (Rontu, 2006)4 Meteorological impactParallel experiments comparing cycle 43h1.2 with cycle 40h1.1 have been conducted for the periods:1aug/17sep2020(AS20),  1oct/30nov2020(ON20),  1dec2020/28feb2021(DEF21)  and1mar/21jun2021(MAM21).  The forecast  length for these tests  is  24 hr.  The overall  impact  of  themodel upgrade can be seen in Table 1. There is a general improvement with some concern for de dewpoint temperature. The impact on the upper level variables is small.Table 1: Summary of the verification results comparing cycle 43h1.2 with cycle 40h1.1. Filledtriangles mean 90% confidence. For the categorical scores (FF10> and Ppt12>) there is nosignificance test but a subjective evaluation of the objective scores2m dew point temperatureConcerning the degradation seen in de dew point temperature, it is due to the first forecast lengths ascan be seen in Fig. 1. This degradation is not seen in relative humidity.ACCORD NL 2. February 2022167/172J. Calvo et al.Figure 2: STDV and Bias of 2 m dew point temperature function of the forecast length for the period16may-3sep202. Cy43h2.1 in green and cy40h1.1 in red.10m wind The  upgrade  to  ECOCLIMAP Second Generation  and  the  discontinuation  of  the  canopy  schemeproduces and increase of the wind bias. The overestimation of 10 m wind  was already significant incycle  40h1.1.   This  bias  is  not  as  clear  for  other  HARMONIE-AROME  domains.  The  wind  isimproved  in  the  new  version  mainly  due  to  the  increase  of  roughness  on  the  open  land  patch(FAKETREES) and activation of an orographic roughness parametrization (OROTUR). The impact on10 m wind can be seen in Figures 3 and 4.Figure 3: STDV and Bias of 10 m wind function of the forecast length for the periods described in thetext. Cy43h2.1 in green and cy40h1.1 in red.Figure 4: Categorical verification of 10 m wind: Equitable Thread Score function of the observedvelocity.  Cy43h2.1 in green and cy40h1.1 in red.It is interesting to note that the impact of the activation of the orographic parameterization is seen notonly in mountain regions (Fig. 5). The improvement on the Canary Islands domain is not so clear withACCORD NL 2. February 2022168/172J. Calvo et al.a reduction of the wind bias but with a deterioration of the winds above 10 m/s (not shown). Probably,a revision of the use of OROTUR for this region is need.Figure 5: Spatial distribution of the 10 m wind bias for the period 1dec2020-28feb2021. Blue colorsindicate underestimation and yellow and red colors overestimation.  Cy43h2.1 (right) and cy40h1.1(left).10m wind gustsThere is an improvement of the 10 m wind gusts with a bias close to zero (Fig. 6). Note that we use arafagosity factor of 2.5 instead of the reference 3.5 in both Cy43h2.1 and cy40h1.1. This reduction inthe rafagosity factor produces an underestimation of the gusts for the strongest large scale wind eventsas can be seen in the categorical verification of the winter period (Fig. 7).Figure 6: STDV and Bias of 10 m wind gusts function of the forecast length for the periods describedin the text. Cy43h2.1 in green and cy40h1.1 in red.Figure 7: Categorical verification of 10 m wind gusts: Equitable Thread Score function of theobserved velocity Cy43h2.1 in green and cy40h1.1 in red.The problem of overestimation of wind gusts in convection events is still present in the new version ascan be seen in the scatterplots of the summer period (Fig. 8)ACCORD NL 2. February 2022169/172J. Calvo et al.Figure 8: Forecast-observation plot  of 10 m wind gusts for the period 1ago-17sep2020. Cy43h2.1(right) and cy40h1.1 (left).Low clouds/Fog over seaThe new version increases low clouds and fog over sea (Fig. 9). This is a serious problem for otherHARMONIE-AROME domains but not so much over Spain because we also have cases with clearunderestimation of low clouds and fog especially over the Mediterranean sea.Figure 9: Simulated satellite images on 12/06/2021 at 09 utc compared with Meteosat Visible Image.Fog over landThe new version decreases the frequency of fog as can be seen from the categorical verification ofvisibility on Fig. 10 for the winter period,  the season when radiation fog usually occurs over theIberian Peninsula. Although from the subjective evaluation of the forecasts it seems that the modelgives a good indication of the spatial distribution of the fogs, from the point verification we can seethat the errors are still big and only for the North Meseta reasonable ETS values are obtained (Fig. 11).Overall conclusion is that the cycle change implies some degradation on the fog forecasts. This seemsmainly due  to  the  change  of  the  maximum Richardson number  because the use of  the  RISHIFTparameterization (Homleid, 2022) produces results close to the cycle 40h1.1 ones.Figure 10: Categorical verification of visibility for the winter period for three climatological regions:North Meseta (CyL), South Meseta and Ebro valley. Frequency bias function of observed visibility.Cy43h2.1 in green and cy40h1.1 in red.ACCORD NL 2. February 2022170/172J. Calvo et al.Figure 11: As Fig 10, Equitable Thread Score function of observed visibilityPrecipitationThe model upgrade implies an improvement of the precipitation forecasts as can be seen in Fig.12 butwithout big changes in model climatology (Figs. 13 and 14).Figure 12: Categorical verification of precipitation accumulated in 12 hr. Equitable Thread Scorefunction of the observed rain gauges precipitation. Cy43h2.1 in green and cy40h1.1 in red.Figure 13: Precipitation accumulated in one month (august 2020). Analysis of precipitation (left),cy40h1.1 (center) and Cy43h2.1 (right). Note that the analysis is based only in rain gauges with muchlower resolution, very few data over Portugal and no data over France.Figure 14: As Fig. 13 for December 2020ACCORD NL 2. February 2022171/172J. Calvo et al.Lightning intensityThe  density  of  electrical  discharges  is  estimated  from  the  vertically  integrated  graupel.  TheHARMONIE-AROME reference computation is not used but a particular tuning to try to simulate thecloud-earth discharges observed from the AEMET observation network. Due to the changes in themicrophysics that imply a reduction of the proportion of graupel, a reduction of the discharge densityis seen in the new version (Fig. 15). We think that the modifications on the hydrometeors partitioncome from updates  on  cycle  40h1.2 (Ivarsson,  2017).  Besides,  there  has  been an  update  of   theAEMET observational network, so a new tuning in the algorithm for the discharges estimation seemsto be needed.Figure 15: Comparison of discharge density in 24 hr on 17/06/2021. Observation (left), cy40h1.1(center) and Cy43h2.1 (right). Thanks to José A. Sosa5 ConclusionsThe  deterministic  operational  suite  was  upgraded  to  cycle  43h2.1  on  7th  September  2021.  Theoperations have been moved to a new computer system that increases AEMET’s computing power atleast 6 times.The  upgrade  from cycle  40h1.1  to  cycle  43h2.1 implies  a  general  improvement  in  most  forecastvariables. Bigger improvement is found in 10 m wind that comes mainly from the activation of theorographic roughness parameterization OROTUR and enhancement of roughness on open land byFAKETREES. Wind gusts also improved but there is some concern about the underestimation of thegusts for the more intense events associated with large scale lows. There is some increase in the cloudcover  amount,  especially  for  low  clouds  over  sea.  Nevertheless,  there  is  some  decrease  on  thefrequency of radiative fogs over land which implies a slight degradation of its prediction. Finally,there is an improvement on precipitation forecasts and there is a decrease on the maxima of the densityof electrical discharges.6 ReferencesHomleid, M. (2022). Improving model performance in stable situations by using a pragmatic shift inthe drag calculations - XRISHIFT . ACCORD Newsletter, 2.Ivarsson, K.-I. (2017), Recent development of cloud microphysics (ICE3) within MetCoOp. ALADIN-HIRLAM Newesletter, 9.Le  Moigne  and  coauthors  (2018):  SURFEX  V8.1  main  scientific  documentation.  Available  athttps://www.umr-cnrm.fr/surfex/IMG/pdf/surfex_scidoc_v8.1.pdfRontu, L. (2006) A study on parametrization of orography-related momentum fluxes in a synoptic-scale  NWP model.  Tellus  A:  Dynamic Meteorology  and Oceanography,  58:1,  69-81,  doi:10.1111/j.1600-0870.2006.00162.xRooy, Wim de, et al. (2020). Improved parametrization of the boundary layer in Harmonie-Arome(focusing on low clouds). ALADIN-HIRLAM Newsletter, 15.ACCORD NL 2. February 2022172/172

Evaluation of HARMONIE-AROME cycle 43h2.1 at AEMET

https://repositorio.aemet.es/bitstream/20.500.11765/13549/1/ACCORD-NL2_Calvo.pdf

Evaluation of HARMONIE-AROME cycle 43h2.1 at AEMET

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