Abstract
In this study, we evaluate the soil moisture and precipitation products obtained from two reanalysis models: the National Centers for Environment Prediction (NCEP) and the European Center for Medium-Range Weather Forecasts (ECMWF). The study centers on Kuwait’s semi-arid region, during the wet season (November to May) from 2008 to 2018. For the precipitation-related evaluation dataset, rain gauge records from the Kuwait Automatic Weather Observation System (KAWOS) were used, while the ground-truth soil moisture values were taken from the Climate Change Initiative (CCI-SM). Initially, to ensure CCI-SM reliability, we compare it with in-situ soil sensor measurements deployed at a desert site. The analysis revealed a maximum CCI-SM overestimation in winter, decreasing progressively throughout the year with 20% mean bias. The bias-corrected CCI-SM dataset is used for the comprehensive evaluation of the soil moisture reanalysis data. Accuracy metrics, such as mean bias (MB), correlation coefficient (R), and unbiased Root Mean Square Difference (ubRMSD), were used for this purpose. The results indicate that ERA5 consistently underestimates (~ 50% MB) soil moisture, but responds well under high soil moisture conditions. NCEP mostly overestimates soil moisture by a similar magnitude, providing even twice as high values during spring months. Mean monthly precipitation (MP) is also overestimated by NCEP, particularly during extreme episodes, yet found to be reliable enough regarding annual accumulated precipitation. ERA5 has shown strong (R ~ 0.6–0.9) predictive capabilities under both frontal and convective precipitation conditions, with ~ 3% median bias for MP, making it a promising alternative data source, particularly in regions with limited weather station coverage.
Similar content being viewed by others
Availability of data and materials
All reanalyses and observational data sets are freely available on request. We thank the NCEP and Copernicus Climate Data Service for the ERA5 data (precipitation and soil moisture), as well as ESA’s CCI product of soil moisture. Rainfall gauge observations were provided by the Kuwait Automatic Weather Observation System.
References
AlJassar H, Temimi M, Abdelkader M, Petrov P, Kokkalis P, AlSarraf H, Roshni N, Hendi HA (2022) Validation of NASA SMAP satellite soil moisture products over the desert of Kuwait. Remote Sens 14(14):3328. https://doi.org/10.3390/rs14143328
AlMazroui M (2012) Dynamical downscaling of rainfall and temperature over the Arabian Peninsula using RegCM4. Clim Res 52:49–62. https://doi.org/10.3354/cr01073
AlMazroui M, Islam MN, Jones PD, Athar H, Rahman MA (2012) Recent climate change in the Arabian Peninsula: seasonal rainfall and temperature climatology of Saudi Arabia for 1979–2009. Atmos Res. https://doi.org/10.1016/j.atmosres.2012.02.013
AlSarmi S, Washington R (2011) Recent observed climate change over the Arabian Peninsula. J Geophys Res Atmos 116:D11109. https://doi.org/10.1029/2010JD015459
AlSarraf H (2022) Projected climate change over Kuwait simulated using a WRF high resolution regional climate model. Int J Glob Warming 26(2):198–211. https://doi.org/10.1504/IJGW.2022.120844
AlSarraf H, Broeke MVD, Al Jassar H (2019) Effects of the sea breeze circulation on soil temperature over Kuwait using in situ observations and the ECMWF model. Open Atmos Sci J 13:29–42. https://doi.org/10.2174/1874282301913010029
Andersson JC, Arheimer B, Traoré F, Gustafsson D, Ali A (2017) Process refinements improve a hydrological model concept applied to the Niger River basin. Hydrol Process 31(25):4540–4554. https://doi.org/10.1002/hyp.11376
Barth HJ, Steinkohl F (2004) Origin of winter precipitation in the central coastal lowlands of Saudi Arabia. J Arid Environ 57:101–115. https://doi.org/10.1016/S0140-1963(03)00091-0
Baur M, Jagdhuber T, Link M, Piles M, Akbar R and Entekhabi D (2018) Multi-frequency estimation of canopy penetration depths from SMAP/AMSR2 radiometer and IceSAT lidar data. In IGARSS 2018-2018 IEEE international geoscience and remote sensing symposium: 365–368. DOI: https://doi.org/10.1109/IGARSS.2018.8517438
Bengtsson L, Shukla J (1988) Integration of space and in situ observations to study global climate change. Bull Am Meteorol Soc 69:1130–1143. https://doi.org/10.1175/1520-0477(1988)069%3c1130:IOSAIS%3e2.0.CO;2
Bengtsson L, Hagemann S, Hodges KI (2004) Can climate trends be calculated from reanalysis data? J Geophys Res: Atmos. https://doi.org/10.1029/2004JD004536
Betts AK (2009) Land-surface-atmosphere coupling in observations and models. J Adv Model Earth Syst. https://doi.org/10.3894/JAMES.2009.1.4
Bright RM, Davin E, O’Halloran T, Pongratz J, Zhao K, Cescatti A (2017) Local temperature response to land cover and management change driven by non-radiative processes. Nat Clim Chang 7:296–302. https://doi.org/10.1038/nclimate3250
Brönnimann S (2017) Weather Extremes in an ensemble of historical reanalyses. In: Brönnimann S (ed) Historical weather extremes in reanalyses, vol G92. Geographica Bernensia, pp 7–22. https://doi.org/10.4480/GB2017.G92.01
Cao Q, Liu Y, Georgescu M, Wu J (2020) Impacts of landscape changes on local and regional climate: a systematic review. Landscape Ecol 35:1269–1290. https://doi.org/10.1007/s10980-020-01015-7
Castaneda-Gonzalez M, Poulin A, Romero-Lopez R, Arsenault R, Brissette F, Chaumont D, Paquin D (2018) Impacts of regional climate model spatial resolution on summer flood simulation. EPiC Ser Eng 3:372–380
Colliander A, Jackson TJ, Bindlish R, Chan S, Das N, Kim SB, Cosh MH, Dunbar RS, Dang L, Pashaian L, Asanuma J (2017) Validation of SMAP surface soil moisture products with core validation sites. Remote Sens Environ 191:215–231. https://doi.org/10.1016/j.rse.2017.01.021
Cubasch U, Meehl GA, Boer GJ, Stouffer RJ, Dix M, Noda A, Senior, CA, Raper, S. and Yap KS (2001) Projections of Future Climate Change. In: Houghton JT, Ding Y, Griggs DJ, Noguer M, van der Linden PJ, Dai X, Maskell K, and Johnson CA, Eds., Climate Change 2001. The Scientific Basis, Cambridge University Press, Cambridge, United Kingdom and New York, 525–582. https://www.ipcc.ch/site/assets/uploads/2018/03/TAR-09.pdf
Dasari HP, Viswanadhapalli Y, Langodan S, Abualnaja Y, Desamsetti S, Vankayalapati K, Thang L, Hoteit I (2022) High-resolution climate characteristics of the Arabian Gulf based on a validated regional reanalysis. Meteorol Appl 29(5):e2102. https://doi.org/10.1002/met.2102
Donat MG, Peterson TC, Brunet M, King AD, Almazroui M, Kolli RK, Boucherf D, Al-Mulla AY, Nour AY, Aly AA, Ali Nada TA, Semawi MM, Al Dashti HA, Salhab TG, El Fadli KI, Muftah MK, Eida SD, Badi W, Driouech F, El Rhaz K, Abubaker MJY, Ghulam AS, Erayah AS, Mansoor MB, Alabdouli WO, Al Dhanhani JS, Al Shekaili MN (2014) Changes in extreme temperature and precipitation in the Arab region: long-term trends and variability related to ENSO and NAO. Int J Climatol 34(3):581–592. https://doi.org/10.1002/joc.3707
Dorigo WA, Gruber A, De Jeu RAM, Wagner W, Stacke T, Loew A, Albergel C, Brocca L, Chung D, Parinussa RM, Kidd R (2015) Evaluation of the ESA CCI soil moisture product using ground-based observations. Remote Sens Environ 162:380–395. https://doi.org/10.1016/j.rse.2014.07.023
Dorigo W, Wagner W, Albergel C, Albrecht F, Balsamo G, Brocca L, Chung D, Ertl M, Forkel M, Gruber A, Haas E (2017) ESA CCI Soil Moisture for improved Earth system understanding: state-of-the art and future directions. Remote Sens Environ 203:185–215. https://doi.org/10.1016/j.rse.2017.07.001
Ek MB, Mitchell KE, Lin Y, Rogers E, Grunmann P, Koren V, Gayno G, Tarpley JD (2003) Implementation of Noah land surface model advances in the National centers for environmental prediction operational mesoscale Eta model. J Geophys Res: Atmos. https://doi.org/10.1029/2002JD003296
Entekhabi D, Njoku EG, O’neill PE, Kellogg KH, Crow WT, Edelstein WN, Entin JK, Goodman SD, Jackson TJ, Johnson J, Kimball J (2010a) The soil moisture active passive (SMAP) mission. Proc IEEE 98(5):704–716. https://doi.org/10.1109/JPROC.2010.2043918
Entekhabi D, Reichle RH, Koster RD, Crow WT (2010b) Performance metrics for soil moisture retrievals and application requirements. J Hydrometeorol 11(3):832–840. https://doi.org/10.1175/2010JHM1223.1
Entekhabi D, Yueh S, and De Lannoy, G (2014) SMAP handbook soil moisture active passive. National Aeronautics and space administration jet propulsion laboratory California institute of technology Pasadena, California
Fan Y, Van den Dool H (2008) A global monthly land surface air temperature analysis for 1948–present. J Geophy Res: Atmos. https://doi.org/10.1029/2007JD008470
Gruber A, Scanlon T, van der Schalie R, Wagner W, Dorigo W (2019) Evolution of the ESA CCI soil moisture climate data records and their underlying merging methodology. Earth Syst Sci Data 11(2):717–739. https://doi.org/10.5194/essd-11-717-2019
Gupta HV, Kling H, Yilmaz KK, Martinez GF (2009) Decomposition of the mean squared error and NSE performance criteria: implications for improving hydrological modelling. J Hydrol 377(1–2):80–91. https://doi.org/10.1016/j.jhydrol.2009.08.003
Hasanean H, Almazroui M (2015) Rainfall: features and variations over Saudi Arabia, a review. Climate 3:578–626. https://doi.org/10.3390/cli3030578
Hersbach H, Bell B, Berrisford P, Biavati G, Horányi A, Muñoz Sabater J, Nicolas J, Peubey C, Radu R, Rozum I, Schepers D (2018) ERA5 hourly data on single levels from 1979 to present. Copernicus Clim Chang Serv (C3S) Clim Data Store (CDS) 10:10243
Hersbach H, Bell B, Berrisford P, Hirahara S, Horányi A, Muñoz-Sabater J, Nicolas J, Peubey C, Radu R, Schepers D, Simmons A, Soci C, Abdalla S, Abellan X, Balsamo G, Bechtold P, Biavati G, Bidlot J, Bonavita M, de Chiara G, Dahlgren P, Dee D, Diamantakis M, Dragani R, Flemming J, Forbes R, Fuentes M, Geer A, Haimberger L, Healy S, Hogan RJ, Hólm E, Janisková M, Keeley S, Laloyaux P, Lopez P, Lupu C, Radnoti G, de Rosnay P, Rozum I, Vamborg F, Villaume S, Thépaut JN (2020) The ERA5 global reanalysis. Q J R Meteorol Soc 146(730):1999–2049. https://doi.org/10.1002/qj.3803
Jing W, Song J, Zhao X (2018) Validation of ECMWF multi-layer reanalysis soil moisture based on the OzNet hydrology network. Water 10(9):1123. https://doi.org/10.3390/w10091123
Kalnay E, Kanamitsu M, Kistler R, Collins W, Deaven D, Gandin L, Iredell M, Saha S, White G, Woollen J, Zhu Y (1996) The NCEP/NCAR 40-year reanalysis project. Bull Amer Meteor Soc 77(3):437–472. https://doi.org/10.1175/1520-0477(1996)077%3c0437:TNYRP%3e2.0.CO;2
Kanamitsu M, Ebisuzaki W, Woollen J, Yang SK, Hnilo JJ, Fiorino M, Potter GL (2002) Ncep–doe amip-ii reanalysis (r-2). Bull Am Meteor Soc 83(11):1631–1644. https://doi.org/10.1175/BAMS-83-11-1631
Kerr YH, Al-Yaari A, Rodriguez-Fernandez N, Parrens M, Molero B, Leroux D, Bircher S, Mahmoodi A, Mialon A, Richaume P, Delwart S (2016) Overview of SMOS performance in terms of global soil moisture monitoring after six years in operation. Remote Sens Environ 180:40–63. https://doi.org/10.1016/j.rse.2016.02.042
Khanal S, Tiwari S, Lutz AF, Hurk BVD, Immerzeel WW (2023) Historical climate trends over high mountain Asia derived from ERA5 reanalysis data. J Appl Meteor Climatol 62:263–288. https://doi.org/10.1175/JAMC-D-21-0045.1
Knoben WJ, Freer JE, Woods RA (2019) Inherent benchmark or not? Comparing Nash-Sutcliffe and Kling-Gupta efficiency scores. Hydrol Earth Syst Sci 23(10):4323–4331. https://doi.org/10.5194/hess-23-4323-2019
Kokkalis P, Al Jassar H, Solomos S, Raptis P-I, Al Hendi H, Amiridis V, Papayannis A, Al Sarraf H, Al DM (2018) Long-term ground-based measurements of aerosol optical depth over Kuwait City. Remote Sens 10(11):1807. https://doi.org/10.3390/rs10111807
Lavers DA, Simmons A, Vamborg F, Rodwell MJ (2022) An evaluation of ERA5 precipitation for climate monitoring. Q J R Meteorol Soc 148(748):3152–3165. https://doi.org/10.1002/qj.4351
Li XR, Ma FY, Xiao HL, Wang XP, Kim KC (2004) Long-term effects of revegetation on soil water content of sand dunes in arid region of Northern China. J Arid Environ 57(1):1–16. https://doi.org/10.1016/S0140-1963(03)00089-2
Liu Z, Xu Z, Yao Z, Huang H (2012) Comparison of surface variables from ERA and NCEP reanalysis with station data over eastern China. Theoret Appl Climatol 107:611–621. https://doi.org/10.1007/s00704-011-0501-1
Ma L, Zhang T, Frauenfeld OW, Ye B, Yang D, Qin D (2009) Evaluation of precipitation from the ERA-40, NCEP-1, and NCEP-2 reanalyses and CMAP-1, CMAP-2, and GPCP-2 with ground-based measurements in China. J Geophys Res: Atmos. https://doi.org/10.1029/2008JD011178
Mao J, Shi X, Ma L, Kaiser DP, Li Q, Thornton PE (2010) Assessment of reanalysis daily extreme temperatures with China’s homogenized historical dataset during 1979–2001 using probability density functions. J Clim 23(24):6605–6623. https://doi.org/10.1175/2010JCLI3581.1
Marcella MP, Eltahir EAB (2008) The hydroclimatology of Kuwait: explaining the variability of rainfall at seasonal and interannual time scales. J Hydrometeor 9:1095–1105. https://doi.org/10.1175/2008JHM952.1
Massad RS, Lathière J, Strada S, Perrin M, Personne E, Stefanon M, Stella P, Szopa S, De Noblet-Ducoudre N (2019) Reviews and syntheses: influences of landscape structure and land uses on local to regional climate and air quality. Biogeosci Eur Geosci Union 16(11):2369–2408. https://doi.org/10.5194/bg-16-2369-2019
McNally A, Shukla S, Arsenault KR, Wang S, Peters-Lidard CD, Verdin JP (2016) Evaluating ESA CCI soil moisture in East Africa. Int J Appl Earth Obs Geoinf 48:96–109. https://doi.org/10.1016/j.jag.2016.01.001
Patlakas P, Stathopoulos C, Flocas H, Bartsotas NS, Kallos G (2021) Precipitation climatology for the Arid region of the Arabian Peninsula—variability, trends and extremes. Climate 9(7):103. https://doi.org/10.3390/cli9070103
Pielke RA, Avissar R (1990) Influence of landscape structure on local and regional climate. Landscape Ecol 4:133–155. https://doi.org/10.1007/BF00132857
Pielke RA, Dalu GA, Snook JS, Lee TJ, Kittel TGF (1991) Nonlinear influence of mesoscale land use on weather and climate. J Clim 4(11):1053–1069. https://doi.org/10.1175/1520-0442(1991)004%3c1053:NIOMLU%3e2.0.CO;2
Portal G, Jagdhuber T, Vall-llossera M, Camps A, Pablos M, Entekhabi D, Piles M (2020) Assessment of multi-scale SMOS and SMAP soil moisture products across the Iberian Peninsula. Remote Sens 12(3):570. https://doi.org/10.3390/rs12030570
Preimesberger W, Scanlon T, Su CH, Gruber A, Dorigo W (2020) Homogenization of structural breaks in the global ESA CCI soil moisture multisatellite climate data record. IEEE Trans Geosci Remote Sens 59(4):2845–2862. https://doi.org/10.1109/TGRS.2020.3012896
Rowntree PR, Murphy JM, Mitchell BJF (1993) Climatic change and future rainfall predictions. Water Environ J 7(5):464–470. https://doi.org/10.1111/j.1747-6593.1993.tb00874.x
Schneider DP, Deser C, Fasullo J, Trenberth KE (2013) Climate data guide spurs discovery and understanding. EOS Trans Am Geophys Union 94(13):121–122. https://doi.org/10.1002/2013EO130001
Southgate RI, Masters P, Seely MK (1996) Precipitation and biomass changes in the Namib Desert dune ecosystem. J Arid Environ 33(3):267–280. https://doi.org/10.1006/jare.1996.0064
Taylor KE (2001) Summarizing multiple aspects of model performance in a single diagram. J Geophys Res: Atmos 106(D7):7183–7192. https://doi.org/10.1029/2000JD900719
Wang A, Zeng X (2012) Evaluation of multireanalysis products with in situ observations over the Tibetan Plateau. J Geophys Res: Atmos. https://doi.org/10.1029/2011JD016553
Zhao T, Fu C (2006) Comparison of products from ERA-40, NCEP-2, and CRU with station data for summer precipitation over China. Adv Atmos Sci 23:593–604. https://doi.org/10.1007/s00376-006-0593-1
Zhu L, Wang H, Tong C, Liu W, Du B (2019) Evaluation of ESA active, passive and combined soil moisture products using upscaled ground measurements. Sensors 19(12):2718. https://doi.org/10.3390/s19122718
Acknowledgements
We are thankful to Kuwait Foundation for the Advancement of Sciences (KFAS) for fully supporting and sponsoring this Project no. CN1742SP01. We are also grateful to Kuwait University (KU) for the administration support.
Funding
Kuwait Foundation for the Advancement of Sciences, CN1742SP01, Hala K. Al Jassar.
Author information
Authors and Affiliations
Contributions
All authors: Conceptualization; All authors: methodology; Panagiotis Kokkalis, Hala K. Al Jassar, and Hussain Al Sarraf; Panagiotis Kokkalis, Hamad Al Hendi, and Roshni Nair: prepared all figures; All authors reviewed the manuscript.
Corresponding author
Ethics declarations
Conflict of interest
Always applicable and includes interests of a financial or personal nature: None.
Ethical approval
Applicable for both human and/or animal studies. Ethical committees, Internal Review Boards, and guidelines followed must be named. When applicable, additional headings with statements on consent to participate and consent to publish are also required: not applicable.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Kokkalis, P., Al Jassar, H.K., Al Sarraf, H. et al. Evaluation of ERA5 and NCEP reanalysis climate models for precipitation and soil moisture over a semi-arid area in Kuwait. Clim Dyn (2024). https://doi.org/10.1007/s00382-024-07141-1
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s00382-024-07141-1