Answers t REVIEW2 Interactive cmment n An imprved perspective in the representatin f sil misture: ptential added value f SMOS disaggregated 1km reslutin prduct by Samir Khdayar et al. Answers t Reviewer 2 We thank reviewer 2 fr all his/her suggestins. All f them will be cnsidered in detail fr the crrectin phase f the manuscript. In the fllwing a general descriptin f the main changes t be applied and detail answers t the cmments is presented. Kind regards, Samir Khdayar n behalf f all c-authrs. In the fllwing a descriptin f the main changes suggested is summarized, Prpsed title change: An imprved perspective in the representatin f sil misture: ptential added value f SMOS disaggregated 1 km reslutin all weather prduct Better definitin f the bjective, nvelty and relevance f this study imprving the structure, cntent and length f the publicatin accrdingly: 1. T examine the benefits f the SMOS L4 versin 3.0 r all weather high reslutin sil misture disaggregated prduct (~ 1 km, SMOS_L4 3.0 ). The added value cmpared t SMOS-L3 (~ 25 km) and L2 (~15 km) is investigated. High-tempral (every 10 min ver several years) and spatial (7 statins in an area f abut 10 x 10 km) sil misture bservatins frm the Valencia Anchr Statin (VAS; SMOS Calibratin/Validatin (Cal/Val) site in Eurpe) are used fr cmparisn and assessment f the spati-tempral perfrmance f the satellite derived sil misture prducts. The SURFEX-ISBA mdel is used t simulate pint-scale surface SM (SSM) and, in cmbinatin with high-quality atmspheric infrmatin data, namely ECMWF and the SAFRAN meterlgical analysis system, t btain a representative SSM mapping ver the VAS. 2. First study, t the authrs knwledge, apart frm the quality reprt, that makes use f the newly SMOS L4 3.0 all weather sil misture prduct. Added value cmpared t Level 2 and 3 SMOS prducts Validatin f the SMOS_L4 3.0 prduct in a different climatic regin than REMEDHUS (Quality Reprt, Piles et al 2015) Tempral and spatial assessment f the perfrmance f the SMOS_L4 3.0 prduct including a seasnal analysis First examples f pssible applicatins f this prduct fr initializatin f ff-line Sil-Vegetatin-Atmsphere Transfer mdels (in this case SURFEX-ISBA) in stand-alne r reginal appraches. 1
3. The cmparisn carried ut helps drawing guidelines n best practices fr the sensible use f these prducts. Currently, there is nt a cnsensus abut what is the best SMOS prduct. Different users utilize different prducts depending n their applicatin rather than based n perfrmance arguments. This study and the cnclusins btained n the cmparisn are imprtant t prvide infrmatin n the advantages and drawbacks f these datasets. Furthermre, reginal SM maps with high accuracy are needed fr fld frecasting, crp mnitring and crp develpment strategies, amng thers. Crrect initial cnditins fr mdel simulatins f these SM maps are fundamental t btain a gd accuracy. SMOS-L4 3.0 culd fill the actual infrmatin gap and fulfil this requirement. New references have been included fllwing the reviewers suggestins: Piles, M., Pu, X., Camps, A., Vall-llsera, M. (2015): Quality reprt: Validatin f SMOS-BEC L4 high reslutin sil misture prducts, versin 3.0 r all-weather. Technical reprt. Available at: http://bec.icm.csic.es/dc/bec-smos-l4smv3- QR.pdf SMOS-BEC Team (2016): SMOS-BEC Ocean and Land Prducts Descriptin. Technical reprt. Available at: http://bec.icm.csic.es/dc/bec-smos-0001-pd.pdf Malbéteau, Y., Merlin, O., Balsam, G., Er-Raki, S., Khabba, S.,Walker, J. P., Jarlan, L. (2018). Tward a Surface Sil Misture Prduct at High Spatitempral Reslutin: Temprally Interplated, Spatially Disaggregated SMOS Data. Jurnal f Hydrmeterlgy, 19(1), 183-200. Djamai, N., Magagi, R., Gïta, K., Merlin, O., Kerr, Y., Ry, A. (2016). A cmbinatin f DISPATCH dwnscaling algrithm with CLASS land surface scheme fr sil misture estimatin at fine scale during cludy days. Remte Sensing f Envirnment, 184, 1-14. Luvet, S., Thierry Pellarin, Ahmad al Bitar, Bernard Cappelaere, Sylvie Galle, Manuela Grippa, Claire Gruhier, Yann Kerr, Thierry Lebel, Arnaud Mialn, Eric Mugin, Guillaume Quantin, Philippe Richaume, Patricia de Rsnay (2015). SMOS sil misture prduct evaluatin ver West-Africa frm lcal t reginal scale. Remte Sensing f Envirnment, Vlume 156, Pages 383-394, ISSN 0034-4257, DOI: 10.1016/j.rse.2014.10.005. 2
GENERAL COMMENTS 1) The manuscript investigates a relevant tpic. The recent availability f 1-km sil misture prducts frm the disaggregatin f carse reslutin retrievals, and frm high reslutin micrwave sensrs (e.g., Sentinel-1), still need t be thrughly assessed and, particularly, tested the ptential added value in hydrlgical r climatic applicatins. By reading the title, I was really interested t the paper and I thught its cntent was different with respect t the current text. I expected a mre general view in which the added value f the high reslutin prduct in real-wrld applicatin(s) was determined. Therefre, I firstly suggest changing the title that is misleading. The main gal f this study is t investigate the added value f the 1 km all weather prduct with respect t carser reslutins, the SMOS-L3 (~ 25 km) and L2 (~15 km) prducts, underging an evaluatin against in situ bservatins. Additinally, in a first simple apprach examples f pssible applicatins f this prduct fr initializatin f ff-line Sil-Vegetatin-Atmsphere Transfer mdels (in this case SURFEX-ISBA) in stand-alne r reginal appraches are presented. As described fr the reviewer 1, in a new study f the first authr, which is abut t be submitted t HESS, the suggestin f the reviewers is explred, in which we assess the benefit f using the SMOS- L4 prduct fr the initializatin f high-reslutin cnvective-permitting simulatins t imprve the predictability f extreme weather phenmena such as heavy precipitatin. We suggest t slightly mdify the title: An imprved perspective in the representatin f sil misture: ptential added value f SMOS disaggregated 1 km reslutin all weather prduct, t better reflect which prduct we refer t, as suggested by the reviewer. Majr cmments: The paper is t lng, nt well rganized (e.g., several repetitins), and nt fcused t a clear message. We will fllw the reviewer s suggestin and try t remve all repetitins and better describe the main gals/fcus f this study. The new SMOS L4 (v3.0) all weather prduct is intrduced. Hwever, a little descriptin f the prduct is carried ut, with a reference t a Quality Reprt nt present in the reference list. As highlighted by reviewer 1, many details are missing (e.g., spatial reslutin f ERA- Interim LST, its merging with MODIS-derived LST,...). These pints need t be clarified. The title shuld be changed t underline the presentatin f the new prduct. The whle paper shuld be fcused n this new prduct. The references t the quality reprt as well as ther publicatins f relevance t the tpic have been included in the reference list. Additinal infrmatin regarding details f the SMOS L4 3.0 prduct which culd be helpful fr the reader will be included in the text. The title has been slightly mdified t better identify the prduct we are discussing. We d nt intend t intrduce the new SMOS L4 (v3.0) all weather prduct, which is nt urs (it was develped at BEC as described in the manuscript), but just t shw the added value f the prduct with respect t ther SMOS-derived SM prducts and give a simple example f the ptential benefit f the new prduct. 3
2) Mre imprtant than pint 1, the paper shuld be fcused clearly n the mre relevant aspects the authrs want t cnvey t the readers. The disaggregated prduct as a spatial reslutin f 1-km, the assessment shuld be carried ut with bservatins and/r mdelling at 1-km reslutin. It is nt dne in the paper. As in mst sil misture dwnscaling papers the assessment f the disaggregated prduct is carried ut in the TEMPORAL DOMAIN, usually cncluding that as the disaggregated prduct shws similar perfrmance than the carse reslutin prduct. Being at higher reslutin, it is a better prduct. Unfrtunately, fr me it is wrng and misleading. I expected that the new disaggregated prduct was cmpared with high reslutin mdelled data (cnstrained by in situ bservatins) in the SPATIAL DOMAIN. This cmparisn is needed t understand if the disaggregated prduct is able t reprduce the high reslutin sil misture variability (at 1-km scale). Of curse, the mdel shuld be frced with high reslutin meterlgical frcing (e.g., radar rainfall), and it is hard t be dne. The spati-tempral crrelatins are analysed thrugh cmparisn with pint-scale bservatins ver the VAS regin. A netwrk f six statins is lcated in an area f abut 10x 10 km 2. Sectin 4.2, lines 438 t 477, is devted t the cmparisn f SMOS L4 and L2 prducts t the in situ measurements frm the VAS netwrk. Statistics fr individual cmparisns at all statins are summarized in Table 3. Figures 7, 8 and even 9 are devted t these cmparisns, althugh it is nt pssible t always shw all statins due t space issues. In the descriptin, details are given abut the better accuracy f L4 prduct. An assessment f the quality f the SMOS L4 prduct using high reslutin mdelled data, even when cnstrained by in situ bservatins, is nt a crrect apprach since mdelled data present relevant biases. In general, the bservatins, as used in this study are cnsidered the truth ; hence, they are used fr validatin f satellite prducts. Indeed, when fr example sil misture prducts are used fr initializatin and/r assimilatin in ur mdels the crrect apprach is t apply CDF (Cumulative Distributin Functin) matching methdlgy t similarly rescale bth prducts. In my pinin, the cmparisn with SMOS L2 and L3 prducts shuld be strngly reduced and the authrs shuld fcus n the SPATIAL assessment f the SMOS L4 all weather prduct (likely cmpared with SMOS L4 v2 prduct nt including ERA-Interim LST). If the new prduct is able t reprduce the spatial variability f high reslutin mdelled data, then the authrs can say that the SMOS L4 v3 prduct captures the 1-km sil misture spatial variability. Otherwise, all the sentences similar t this ne shuld be remved by the paper. We agree with reviewer 1 that an analysis f the SMOS level 4 data and its added value cmpared t Level 2 r Level 3 data is interesting since n reference is given elsewhere. The cmparisn carried ut helps drawing guidelines n best practices fr the sensible use f these prducts. Different users utilize different prducts depending n their applicatin rather than based n perfrmance arguments. This study and the cnclusins btained n the cmparisn are imprtant t prvide infrmatin n the advantages and drawbacks f these datasets. Nevertheless, fllwing the reviewer s suggestin we will reduce this part and nly fcus n the mst relevant infrmatin, always reinfrcing the rle f the SMOS L4 3.0 prduct. Cncerning the cmparisn with the SMOS L4 2.0 prduct, the cmparisn was made during ur analysis but results were nt included in this manuscript, but fllwing the reviewer s suggestin we will describe in the text the mst relevant cnclusins btained frm this cmparisn. 3) The analysis fr the initializatin f mdelled data is, at least fr me, nt clear and likely nt apprpriate. T assess the added value f the sil misture prduct, the authrs shuld 4
intrduce the prduct int the mdelling (e.g., thrugh data assimilatin) and assess the mdel perfrmance withut and with the use f the prduct. Specifically, the authrs shuld assimilate different SMOS prducts int the mdelling and then assess the best prduct based n the simulatin results after the assimilatin. The authrs nly shwed that if different initial sil misture cnditins are cnsidered, different results are btained. Hwever, this is highly expected and largely shwn in the scientific literature. An assimilatin analysis I guess ges beynd the scpe f the paper. Therefre, I am suggesting remving, r strngly reducing, this part. As the reviewer crrectly pints ut a data assimilatin exercise was nt the gal f this study and it was ut f the scpe f this paper. The prblematic assciated with the initializatin f sil misture in mdel simulatins acrss scales is als a well-knwn and still a ht tpic that deserves further cnsideratin. As the reviewer pinted ut if different initial sil misture cnditins are cnsidered, different results are btained, in ur first initializatin exercise we wanted t stress this pint ut and assess the ptential change that culd be expected when different nrmally used initializatin values are used. In the secnd part f the analysis, an initializatin exercise using SMOS L4 3.0 infrmatin is presented. Fllwing the reviewer s suggestin we will reduce this part and better clarify ur purpse and results. Sme specific cmments and crrectins shuld be als addressed. Fr instance, the intrductin intrduces ONLY SMOS amng the satellite sil misture prducts currently available. We have SMAP, ASCAT, AMSR2, ESA CCI and Sentinel-1 as peratinal prducts freely available. They shuld be at least mentined. We agree with the reviewer and we will include in the intrductin additinal infrmatin regarding ther peratinal prducts freely available. 5