Contributions of Initial Conditions and Meteorological Forecast to Subseasonal-to-Seasonal Hydrological Forecast Skill in Western Tropical South America

被引:0
作者
Recalde-coronel, G. cristina [1 ,2 ]
Zaitchik, Benjamin [1 ]
Pan, William k. [3 ,4 ]
Zhou, Yifan [1 ]
Badr, Hamada [1 ]
机构
[1] Johns Hopkins Univ, Dept Earth & Planetary Sci, Baltimore, MD 21218 USA
[2] Escuela Super Politecn Litoral, Fac Ingn Maritima & Ciencias Mar, Guayaquil, Ecuador
[3] Duke Univ, Duke Global Hlth Inst, Durham, NC USA
[4] Duke Univ, Nicholas Sch Environm, Durham, NC USA
关键词
South America; Forecast veri fi cation/skill; Seasonal forecasting; Climate models; Land surface model; Subseasonal variability; SEA-SURFACE TEMPERATURE; MULTIMODEL ENSEMBLE; DATA ASSIMILATION; INTERANNUAL ACTIVITY; SPATIAL VARIABILITY; CLIMATE VARIABILITY; DROUGHT PREDICTION; CENTRAL ANDES; PRECIPITATION; RAINFALL;
D O I
10.1175/JHM-D-23-0064.1
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
摘要
Hydrological predictions at subseasonal-to-seasonal (S2S) time scales can support improved decisionmaking in climate -dependent sectors like agriculture and hydropower. Here, we present an S2S hydrological forecasting system (S2S-HFS) for western tropical South America (WTSA). The system uses the global NASA Goddard Earth Observing System S2S meteorological forecast system (GEOS-S2S) in combination with the generalized analog regression downscaling algorithm and the NASA Land Information System (LIS). In this implementation study, we evaluate system performance for 3 -month hydrological forecasts for the austral autumn season (March - May) using ensemble hindcasts for 2002 - 17. Results indicate that the S2S-HFS generally offers skill in predictions of monthly precipitation up to 1 -month lead, evapotranspiration up to 2 months lead, and soil moisture content up to 3 months lead. Ecoregions with better hindcast performance are located either in the coastal lowlands or in the Amazon lowland forest. We perform dedicated analysis to understand how two important teleconnections affecting the region are represented in the S2S-HFS: El Ni & ntilde;o - Southern Oscillation (ENSO) and the Antarctic Oscillation (AAO). We fi nd that forecast skill for all variables at 1 -month lead is enhanced during the positive phase of ENSO and the negative phase of AAO. Overall, this study indicates that there is meaningful skill in the S2S-HFS for many ecoregions in WTSA, particularly for long memory variables such as soil moisture. The skill of the precipitation forecast, however, decays rapidly after forecast initialization, a phenomenon that is consistent with S2S meteorological forecasts over much of the world.
引用
收藏
页码:709 / 733
页数:25
相关论文
共 109 条
  • [51] An intercomparison of statistical downscaling methods used for water resource assessments in the United States
    Gutmann, Ethan
    Pruitt, Tom
    Clark, Martyn P.
    Brekke, Levi
    Arnold, Jeffrey R.
    Raff, David A.
    Rasmussen, Roy M.
    [J]. WATER RESOURCES RESEARCH, 2014, 50 (09) : 7167 - 7186
  • [52] En-GARD: A Statistical Downscaling Framework to Produce and Test Large Ensembles of Climate Projections
    Gutmann, Ethan D.
    Hamman, Joseph. J.
    Clark, Martyn P.
    Eidhammer, Trude
    Wood, Andrew W.
    Arnold, Jeffrey R.
    [J]. JOURNAL OF HYDROMETEOROLOGY, 2022, 23 (10) : 1545 - 1561
  • [53] NASA'S NMME-based S2S hydrologic forecast system for food insecurity early warning in southern Africa
    Hazra, Abheera
    McNally, Amy
    Slinski, Kimberly
    Arsenault, Kristi R.
    Shukla, Shraddhanand
    Getirana, Augusto
    Jacob, Jossy P.
    Sarmiento, Daniel P.
    Peters-Lidard, Christa
    Kumar, Sujay, V
    Koster, Randal D.
    [J]. JOURNAL OF HYDROLOGY, 2023, 617
  • [54] Evaluation of remote sensing-based evapotranspiration products at low-latitude eddy covariance sites
    Holwerda, Friso
    Salazar-Martinez, Diego
    Holmes, Thomas R. H.
    Yepez, Enrico A.
    Hain, Christopher R.
    Alvarado-Barrientos, Susana
    Angeles-Perez, Gregorio
    Arredondo-Moreno, Tulio
    Delgado-Balbuena, Josue
    Figueroa-Espinoza, Bernardo
    Garatuza-Payan, Jaime
    del Castillo, Eugenia Gonzalez
    Rodriguez, Julio C.
    Rojas-Robles, Nidia E. Rojas
    Uuh-Sonda, Jorge M.
    Vivoni, Enrique
    [J]. JOURNAL OF HYDROLOGY, 2022, 610
  • [55] Extended Reconstructed Sea Surface Temperature, Version 5 (ERSSTv5): Upgrades, Validations, and Intercomparisons
    Huang, Boyin
    Thorne, Peter W.
    Banzon, Viva F.
    Boyer, Tim
    Chepurin, Gennady
    Lawrimore, Jay H.
    Menne, Matthew J.
    Smith, Thomas M.
    Vose, Russell S.
    Zhang, Huai-Min
    [J]. JOURNAL OF CLIMATE, 2017, 30 (20) : 8179 - 8205
  • [56] THE NORTH AMERICAN MULTIMODEL ENSEMBLE Phase-1 Seasonal-to-Interannual Prediction; Phase-2 toward Developing Intraseasonal Prediction
    Kirtman, Ben P.
    Min, Dughong
    Infanti, Johnna M.
    Kinter, James L., III
    Paolino, Daniel A.
    Zhang, Qin
    van den Dool, Huug
    Saha, Suranjana
    Mendez, Malaquias Pena
    Becker, Emily
    Peng, Peitao
    Tripp, Patrick
    Huang, Jin
    DeWitt, David G.
    Tippett, Michael K.
    Barnston, Anthony G.
    Li, Shuhua
    Rosati, Anthony
    Schubert, Siegfried D.
    Rienecker, Michele
    Suarez, Max
    Li, Zhao E.
    Marshak, Jelena
    Lim, Young-Kwon
    Tribbia, Joseph
    Pegion, Kathleen
    Merryfield, William J.
    Denis, Bertrand
    Wood, Eric F.
    [J]. BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY, 2014, 95 (04) : 585 - 601
  • [57] Koster RD, 2003, J HYDROMETEOROL, V4, P408, DOI 10.1175/1525-7541(2003)4<408:IOLSIO>2.0.CO
  • [58] 2
  • [59] Temperature trends and prediction skill in NMME seasonal forecasts
    Krakauer, Nir Y.
    [J]. CLIMATE DYNAMICS, 2019, 53 (12) : 7201 - 7213
  • [60] Land information system: An interoperable framework for high resolution land surface modeling
    Kumar, S. V.
    Peters-Lidard, C. D.
    Tian, Y.
    Houser, P. R.
    Geiger, J.
    Olden, S.
    Lighty, L.
    Eastman, J. L.
    Doty, B.
    Dirmeyer, P.
    Adams, J.
    Mitchell, K.
    Wood, E. F.
    Sheffield, J.
    [J]. ENVIRONMENTAL MODELLING & SOFTWARE, 2006, 21 (10) : 1402 - 1415