Validation of Satellite Precipitation Estimates over the Congo Basin

S. E. Nicholson Department of Meteorology, Florida State University, Tallahassee, Florida

Search for other papers by S. E. Nicholson in
Current site
Google Scholar
PubMed
Close
,
D. Klotter Department of Meteorology, Florida State University, Tallahassee, Florida

Search for other papers by D. Klotter in
Current site
Google Scholar
PubMed
Close
,
L. Zhou University at Albany, State University of New York, Albany, New York

Search for other papers by L. Zhou in
Current site
Google Scholar
PubMed
Close
, and
W. Hua University at Albany, State University of New York, Albany, New York

Search for other papers by W. Hua in
Current site
Google Scholar
PubMed
Close
Restricted access

Abstract

This paper evaluates nine satellite rainfall products and the Global Precipitation Centre Climatology (GPCC) gauge dataset over the Congo basin. For the evaluation the reference dataset is a newly created, gridded gauge dataset based on a gauge network that is more complete than that of GPCC in recent years. It is termed NIC131-gridded. Gridding was achieved via a climatic reconstruction method based on principal components, so that reliable estimates of rainfall are available even in the data-sparse central basin. The satellite products were evaluated for two locations, the Congo basin and areas on its eastern and western periphery (termed the “east plus west” sector). The station density was notably higher in the latter region. Two time periods were also considered: 1983–94, when station density was relatively high, and 1998–2010, when station density was much lower than during the earlier period. Several products show excellent agreement with the NIC131-gridded reference dataset. These include CHIRPS2, PERSIANN-CDR, GPCP 2.3, TRMM 3B43, and, to a lesser extent, GPCC V7. RMSE for the period 1983–94 in the east plus west sector is on the order of 20 mm month−1 for GPCC V7 and 20–30 mm month−1 for the other products. The compares with 40–60 mm month−1 for the most poorly performing products, African Rainfall Climatology version 2 (ARCv2) and CMAP. Over the Congo basin, RMSE for those two products is about the same as in the east plus west sector but is on the order of 30–40 mm month−1 for the better-performing products. In all cases, the performance of the 10 products evaluated is notably poorer in recent years (1998–2010), when the station network is sparse, than during the period 1983–94, when the dense station network provides reliable estimates of rainfall. For the more recent period RMSE is on the order of 30–40 mm month−1 for the best-performing products in the east plus west sector but only slightly higher over the Congo basin. All products do reasonably well in reproducing the seasonal cycle and the latitudinal gradients of rainfall. Estimates of interannual variability show more scatter among the various products and are less reliable. Overall, the most important results of the study are to demonstrate the strong impact that actual gauge data have on the various products and the need to have access to such gauge data, in order to produce reliable rainfall estimates from satellites.

Corresponding author: S. E. Nicholson, snicholson@fsu.edu

© 2019 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Abstract

This paper evaluates nine satellite rainfall products and the Global Precipitation Centre Climatology (GPCC) gauge dataset over the Congo basin. For the evaluation the reference dataset is a newly created, gridded gauge dataset based on a gauge network that is more complete than that of GPCC in recent years. It is termed NIC131-gridded. Gridding was achieved via a climatic reconstruction method based on principal components, so that reliable estimates of rainfall are available even in the data-sparse central basin. The satellite products were evaluated for two locations, the Congo basin and areas on its eastern and western periphery (termed the “east plus west” sector). The station density was notably higher in the latter region. Two time periods were also considered: 1983–94, when station density was relatively high, and 1998–2010, when station density was much lower than during the earlier period. Several products show excellent agreement with the NIC131-gridded reference dataset. These include CHIRPS2, PERSIANN-CDR, GPCP 2.3, TRMM 3B43, and, to a lesser extent, GPCC V7. RMSE for the period 1983–94 in the east plus west sector is on the order of 20 mm month−1 for GPCC V7 and 20–30 mm month−1 for the other products. The compares with 40–60 mm month−1 for the most poorly performing products, African Rainfall Climatology version 2 (ARCv2) and CMAP. Over the Congo basin, RMSE for those two products is about the same as in the east plus west sector but is on the order of 30–40 mm month−1 for the better-performing products. In all cases, the performance of the 10 products evaluated is notably poorer in recent years (1998–2010), when the station network is sparse, than during the period 1983–94, when the dense station network provides reliable estimates of rainfall. For the more recent period RMSE is on the order of 30–40 mm month−1 for the best-performing products in the east plus west sector but only slightly higher over the Congo basin. All products do reasonably well in reproducing the seasonal cycle and the latitudinal gradients of rainfall. Estimates of interannual variability show more scatter among the various products and are less reliable. Overall, the most important results of the study are to demonstrate the strong impact that actual gauge data have on the various products and the need to have access to such gauge data, in order to produce reliable rainfall estimates from satellites.

Corresponding author: S. E. Nicholson, snicholson@fsu.edu

© 2019 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Save
  • Adler, R. F., and Coauthors, 2003: The version 2 Global Precipitation Climatology Project (GPCP) monthly precipitation analysis (1979–present). J. Hydrometeor., 4, 11471167, https://doi.org/10.1175/1525-7541(2003)004<1147:TVGPCP>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Asadullah, A., N. McIntyre, and M. Kigobe, 2008: Evaluation of five satellite products for estimation of rainfall over Uganda. Hydrol. Sci. J., 53, 11371150, https://doi.org/10.1623/hysj.53.6.1137.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Ashouri, H., K. L. Hsu, S. Sorooshian, D. K. Braithwaite, K. R. Knapp, L. D. Cecil, B. R. Nelson, and O. P. Prat, 2015: PERSIANN-CDR: Daily precipitation climate data record from multisatellite observations for hydrological and climate studies. Bull. Amer. Meteor. Soc., 96, 6983, https://doi.org/10.1175/BAMS-D-13-00068.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Awange, J. L., V. G. Ferreira, E. Forootan, Khandu, S. A. Andam-Akorful, N. O. Agutu, and X. F. He, 2016: Uncertainties in remotely sensed precipitation data over Africa. Int. J. Climatol., 36, 303323, https://doi.org/10.1002/joc.4346.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Balas, N., S. E. Nicholson, and D. Klotter, 2007: The relationship of rainfall variability in west central Africa to sea-surface temperature fluctuations. Int. J. Climatol., 27, 13351349, https://doi.org/10.1002/joc.1456.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Beighley, R. E., and Coauthors, 2011: Comparing satellite derived precipitation datasets using the Hillslope River Routing (HRR) model in the Congo River Basin. Hydrol. Processes, 25, 32163229, https://doi.org/10.1002/hyp.8045.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Berhane, F., B. Zaitchik, and H. S. Badr, 2015: The Madden–Julian oscillation’s influence on spring rainy season precipitation over equatorial West Africa. J. Climate, 28, 86538672, https://doi.org/10.1175/JCLI-D-14-00510.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cattani, E., A. Merino, and V. Levizzani, 2016: Evaluation of monthly satellite-derived precipitation products over East Africa. J. Hydrometeor., 17, 25552573, https://doi.org/10.1175/JHM-D-15-0042.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Cook, K. H., and E. K. Vizy, 2016: The Congo Basin Walker circulation: Dynamics and connections to precipitation. Climate Dyn., 47, 697717, https://doi.org/10.1007/s00382-015-2864-y.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dezfuli, A. K., 2011: Spatio-temporal variability of seasonal rainfall in western equatorial Africa. Theor. Appl. Climatol., 104, 5769, https://doi.org/10.1007/s00704-010-0321-8.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dezfuli, A. K., and S. E. Nicholson, 2013: The relationship of interannual variability in western equatorial Africa to the tropical oceans and atmospheric circulation. Part II. The boreal autumn. J. Climate, 26, 6684, https://doi.org/10.1175/JCLI-D-11-00686.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dezfuli, A. K., B. F. Zaitchik, and A. Gnadadesikan, 2015: Regional atmospheric circulation and rainfall variability in south equatorial Africa. J. Climate, 28, 809818, https://doi.org/10.1175/JCLI-D-14-00333.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dezfuli, A. K., and Coauthors, 2017: Validation of IMERG precipitation in Africa. J. Hydrometeor., 18, 28172825, https://doi.org/10.1175/JHM-D-17-0139.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Diem, J. E., J. Hartler, and S. J. Ryan, 2014: Validation of satellite rainfall products for western Uganda. J. Hydrometeor., 15, 20302036, https://doi.org/10.1175/JHM-D-13-0193.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dinku, T., P. Ceccato, E. Grover-Kopec, M. Lemma, S. J. Connor, and C. F. Ropelewski, 2007: Validation of satellite rainfall products over East Africa’s complex topography. Int. J. Remote Sens., 28, 15031526, https://doi.org/10.1080/01431160600954688.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dinku, T., P. Ceccato, and S. J. Connor, 2011a: Challenges of satellite rainfall estimation over mountainous and arid parts of east Africa. Int. J. Remote Sens., 32, 59655979, https://doi.org/10.1080/01431161.2010.499381.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dinku, T., S. J. Connor, and P. Ceccato, 2011b: Evaluation of satellite rainfall estimates and gridded gauge products over the Upper Blue Nile region. Nile River Basin: Hydrology, Climate and Water Use, A. M. Melesse, Ed., Springer, 109–127, https://doi.org/10.1007/978-94-007-0689-7_5.

    • Crossref
    • Export Citation
  • Dinku, T., K. Hailemariam, R. Maidment, E. Tarnavsky, and S. Connor, 2014: Combined use of satellite estimates and rain gauge observations to generate high-quality historical rainfall time series over Ethiopia. Int. J. Climatol., 34, 24892504, https://doi.org/10.1002/joc.3855.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dyer, E. L. E., D. B. Jonex, J. Nusbaumer, H. Li, O. Colliln, G. Vettoretti, and D. Noone, 2017: Congo Basin precipitation: Assessing seasonality, regional interactions, and sources of moisture. J. Geophys. Res. Atmos., 122, 68826898, https://doi.org/10.1002/2016JD026240.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Funk, C., and Coauthors, 2015: The climate hazards infrared precipitation with stations – A new environmental record for monitoring extremes. Sci. Data, 2, 150066, https://doi.org/10.1038/sdata.2015.66.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gebremichael, J., M. M. Bitew, F. A. Hirpa, and G. N. Tesfay, 2014: Accuracy of satellite rainfall estimates in the Blue Nile Basin: Lowland plain versus highland mountain. Water Resour. Res., 50, 87758790, https://doi.org/10.1002/2013WR014500.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gu, G. J., 2009: Intraseasonal variability in the equatorial Atlantic-West Africa during March–June. Climate Dyn., 32, 457471, https://doi.org/10.1007/s00382-008-0428-0.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Haile, A. T., E. Habib, M. Elsaadani, and T. Rientjes, 2013: Inter-comparison of satellite rainfall products for representing rainfall diurnal cycle over the Nile basin. Int. J. Appl. Earth Obs., 21, 230240, https://doi.org/10.1016/j.jag.2012.08.012.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hirst, A. C., and S. Hastenrath, 1983: Diagnostics of hydrometeorological anomalies in the Zaire (Congo) basin. Quart. J. Roy. Meteor. Soc., 109, 881892, https://doi.org/10.1002/qj.49710946213.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hoell, A., and C. Funk, 2013: The ENSO-related West Pacific Sea surface temperature gradient. J. Climate, 26, 95459562, https://doi.org/10.1175/JCLI-D-12-00344.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hua, W., L. Zhou, H. Chen, S. E. Nicholson, R. Raghavendra, and Y. Jian, 2016: Possible causes of central equatorial long-term drought. Environ. Res. Lett., 11, 124002, https://doi.org/10.1088/1748-9326/11/12/124002.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hua, W., L. Zhou, H. Chen, S. E. Nicholson, Y. Jiang, and R. Raghavendra, 2018: Understanding the central equatorial Africa long-term drought using AMIP-type simulations. Climate Dyn., 50, 11151128, https://doi.org/10.1007/s00382-017-3665-2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Huffman, G. J., and D. T. Bolvin, 2014: TRMM and other data precipitation data set documentation. NASA TRMM Doc., 42 pp., ftp://precip.gsfc.nasa.gov/pub/trmmdocs/3B42_3B43_doc.pdf.

  • Huffman, G. J., and Coauthors, 2007: The TRMM Multi-satellite precipitation analysis: Quasi-global, multi-year, combined-sensor precipitation estimates at finer scale. J. Hydrometeor., 8, 3855, https://doi.org/10.1175/JHM560.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Huffman, G. J., D. T. Bolvin, and E. J. Nelkin, 2010: The TRMM Multi-Satellite Precipitation Analysis (TMPA). Satellite Rainfall Applications for Surface Hydrology, F. Hossain and M. Gebremichael, Eds., Springer-Verlag, 3–22.

    • Crossref
    • Export Citation
  • Jackson, B., S. E. Nicholson, and D. Klotter, 2009: Mesoscale convective systems over western equatorial Africa and their relationship to large-scale circulation. Mon. Wea. Rev., 137, 12721294, https://doi.org/10.1175/2008MWR2525.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jacob, M., A. Frankil, M. Haile, A. Zwertvaegher, and J. Nyssen, 2013: Assessing spatio-temporal rainfall variability in a tropical mountain area (Ethiopia) using NOAA’s rainfall estimates. Int. J. Remote Sens., 34, 83198335, https://doi.org/10.1080/01431161.2013.837230.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Joyce, R. J., J. E. Janowiak, P. A. Arkin, and P. Xie, 2004: CMORPH: A method that produces global precipitation estimates from passive microwave and infrared data at high spatial and temporal resolution. J. Hydrometeor., 5, 487503, https://doi.org/10.1175/1525-7541(2004)005<0487:CAMTPG>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kamsu-Tamo, P. H., S. Janicot, D. Monkam, and A. Lenuou, 2014: Convection activity over the Guinen coast and central Africa during northern spring from synoptic to intra-seasonal timescales. Climate Dyn., 43, 33773401, https://doi.org/10.1007/s00382-014-2111-y.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kizza, M., I. Westerberg, A. Rodhe, and H. K. Ntale, 2012: Estimating areal rainfall over Lake Victoria and its basin using ground-based and satellite data. J. Hydrol., 464–465, 401411, https://doi.org/10.1016/j.jhydrol.2012.07.024.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Koutsouris, A. J., D. L. Chen, and S. W. Lyon, 2016: Comparing global precipitation data sets in eastern Africa: A case study of Kilombero Valley, Tanzania. Int. J. Climatol., 36, 20002014, https://doi.org/10.1002/joc.4476.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Laing, A. G., R. E. Carbone, and V. Levizzani, 2011: Cycles and propagation of deep convection over equatorial Africa. Mon. Wea. Rev., 139, 28322853, https://doi.org/10.1175/2011MWR3500.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Long, Y., Y. Zhang, and Q. Ma, 2016: A merging framework for rainfall estimation at high spatiotemporal resolution for distributed hydrological modeling in a data-scarce area. Remote Sens., 8, 599, https://doi.org/10.3390/rs8070599.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Love, T. B., V. Kumar, P. Xie, and W. Thiaw, 2004: A 20-year daily Africa precipitation climatology using satellite and gauge data. 14th Conf. on Applied Meteorology, Seattle, WA, Amer. Meteor. Soc., P5.4, http://ams.confex.com/ams/pdfpapers/67484.pdf.

  • Maidment, R. I., D. I. F. Grimes, R. P. Allan, H. Greatrex, O. Rojas, and O. Leo, 2013: Evaluation of satellite-based and model re-analysis rainfall estimates for Uganda. Meteor. Appl., 20, 308317, https://doi.org/10.1002/met.1283.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Maidment, R. I., and Coauthors, 2017: A new, long-term daily satellite-based rainfall dataset for operational monitoring in Africa. Sci. Data, 4, 170063, https://doi.org/10.1038/sdata.2017.63.

    • Search Google Scholar
    • Export Citation
  • Mashingia, F., F. Mtalo, and M. Bruen, 2014: Validation of remotely sensed rainfall over major climatic regions in northeast Tanzania. Phys. Chem. Earth, 67-69, 5563, https://doi.org/10.1016/j.pce.2013.09.013.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • McCollum, J. R., A. Gruber, and M. B. Ba, 2000: Discrepancy between gauges and satellite estimates of rainfall in equatorial Africa. J. Appl. Meteor., 39, 666679, https://doi.org/10.1175/1520-0450-39.5.666.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Munzimi, Y. A., M. C. Hansen, B. Adusei, and G. B. Senay, 2015: Characterizing Congo Basin rainfall and climate using Tropical Rainfall Measuring Mission (TRMM) satellite data and limited rain gauge ground observations. J. Appl. Meteor. Climatol., 54, 541555, https://doi.org/10.1175/JAMC-D-14-0052.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Negron Juarez, R. I. N., W. H. Li, R. Fu, K. Fernandes, and A. D. Cardoso, 2009: Comparison of precipitation datasets over the tropical South American and African continents. J. Hydrometeor., 10, 289299, https://doi.org/10.1175/2008JHM1023.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Neupane, N., 2016: The Congo basin zonal overturning circulation. Adv. Atmos. Sci., 33, 767782, https://doi.org/10.1007/s00376-015-5190-8.

  • Nguyen, H., and J. P. Duvel, 2008: Synoptic wave perturbations and convective systems over equatorial Africa. J. Climate, 21, 63726388, https://doi.org/10.1175/2008JCLI2409.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Nicholson, S. E., 2018: The ITCZ and the seasonal cycle over equatorial Africa. Bull. Amer. Meteor. Soc., 99, 337348, https://doi.org/10.1175/BAMS-D-16-0287.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Nicholson, S. E., and J. P. Grist, 2003: The seasonal evolution of the atmospheric circulation over West Africa and equatorial Africa. J. Climate, 16, 10131030, https://doi.org/10.1175/1520-0442(2003)016<1013:TSEOTA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Nicholson, S. E., and A. K. Dezfuli, 2013: The relationship of interannual variability in western equatorial Africa to the tropical oceans and atmospheric circulation. Part I. The boreal spring. J. Climate, 26, 4565, https://doi.org/10.1175/JCLI-D-11-00653.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Nicholson, S. E., C. Funk, and A. Fink, 2018a: One and a half centuries of rainfall variability over the African continent. Global Planet. Change, 165, 114127, https://doi.org/10.1016/j.gloplacha.2017.12.014.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Nicholson, S. E., D. Klotter, A. K. Dezfuli, and L. Zhou, 2018b: New rainfall data sets for the Congo Basin and surrounding regions. J. Hydrometeor., 19, 13791396, https://doi.org/10.1175/JHM-D-18-0015.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Novella, N. S., and W. M. Thiaw, 2013: African Rainfall Climatology version 2 for famine early warning systems. J. Appl. Meteor. Climatol., 52, 588606, https://doi.org/10.1175/JAMC-D-11-0238.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pokam, W. M., L. A. T. Djiotang, and F. K. Mkankam, 2012: Atmospheric water vapor transport and recycling in equatorial Central Africa through NCEP/NCAR reanalysis data. Climate Dyn., 38, 17151729, https://doi.org/10.1007/s00382-011-1242-7.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pokam, W. M., C. L. Bain, R. S. Chadwick, R. Graham, D. J. Sonwa, and F. M. Kamga, 2014: Identification of processes driving low-level westerlies in west equatorial Africa. J. Climate, 27, 42454262, https://doi.org/10.1175/JCLI-D-13-00490.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pombo, S., and R. Proença de Oliveira, 2015: Evaluation of extreme precipitation estimates from TRMM in Angola. J. Hydrol., 523, 663679, https://doi.org/10.1016/j.jhydrol.2015.02.014.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pombo, S., R. Proença de Oliveira, and A. Mendes, 2015: Validation of remote-sensing precipitation products for Angola. Meteor. Appl., 22, 395409, https://doi.org/10.1002/met.1467.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Samba, G., and D. Nganga, 2012: Rainfall variability in Congo-Brazzaville: 1932–2007. Int. J. Climatol., 32, 854873, https://doi.org/10.1002/joc.2311.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Samba, G., D. Nganga, and M. Mpounza, 2008: Rainfall and temperature variations over Congo-Brazzaville between 1950 ad 1998. Theor. Appl. Climatol., 91, 8597, https://doi.org/10.1007/s00704-007-0298-0.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sandjon, A. T., A. Nzeukou, and C. Tchawoua, 2012: Intraseasonal atmospheric variability and its interannual modulation in central Africa. Meteor. Atmos. Phys., 117, 167179, https://doi.org/10.1007/s00703-012-0196-6.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sandjon, A. T., A. Nzeukou, C. Tchawoua, F. M. Kamga, and D. Vondou, 2014a: A comparative analysis of intraseasonal atmospheric variability in OLR and 1DD GPCP rainfall data over central Africa. Theor. Appl. Climatol., 116, 3749, https://doi.org/10.1007/s00704-013-0911-3.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sandjon, A. T., A. Nzeukou, C. Tchawoua, B. Sonfack, and T. Siddi, 2014b: Comparing the patterns of 20–70 days intraseasonal oscillations over central Africa during the last three decades. Theor. Appl. Climatol., 118, 319329, https://doi.org/10.1007/s00704-013-1063-1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Schneider, U., A. Becker, P. Finger, A. Meyer-Christoffer, B. Rudolf, and M. Ziese, 2015: GPCC Full Data Monthly Product version 7 at 2.5°: Monthly land-surface gauges built on GTS-based and historic data. DWD, accessed December 2017, https://doi.org/10.5676/DWD_GPCC/FD_M_V7_250.

    • Crossref
    • Export Citation
  • Serrat-Capdevila, A., M. Merino, J. B. Valdes, and M. Durcik, 2016: Evaluation of the performance of three satellite precipitation products over Africa. Remote Sens., 8, 836, https://doi.org/10.3390/rs8100836.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sinclaire, Z., A. Lenouo, C. Tchawoua, and S. Janicot, 2015: Synoptic Kelvin type perturbation waves over Congo basin over the period 1979–2010. J. Atmos. Terr. Phys., 130–131, 4356, https://doi.org/10.1016/j.jastp.2015.04.015.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sorooshian, S., K. Hsu, D. Braithwaite, H. Ashouri, and the NOAA CDR Program, 2014: NOAA Climate Data Record (CDR) of Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN-CDR), version 1 revision 1. Subset used: Monthly rainfall over Africa, NOAA National Centers for Environmental Information. accessed December 2017, https://doi.org/10.7289/V51V5BWQ.

    • Crossref
    • Export Citation
  • Soula, S., J. K. Kasereka, J. F. Georgis, and C. Barthe, 2016: Lightning climatology in the Congo basin. Atmos. Res., 178–179, 304319, https://doi.org/10.1016/j.atmosres.2016.04.006.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sun, Q., C. Miao, Q. Duan, H. Ashouri, S. Sorooshian, and K.-L. Hsu, 2018: A review of global precipitation data sets: Data sources, estimation, and intercomparisons. Rev. Geophys., 56, 79–107, https://doi.org/10.1002/2017RG000574.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tarnavsky, E., D. Grimes, R. Maidment, E. Black, R. P. Allan, and M. Stringer, 2014: Extension of the TAMSAT satellite-based rainfall monitoring over Africa and from 1983 to present. J. Appl. Meteor. Climatol., 53, 28052822, https://doi.org/10.1175/JAMC-D-14-0016.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Taylor, K. E., 2001: Summarizing multiple aspects of model performance in a single diagram. J. Geophys. Res., 106, 71837192, https://doi.org/10.1029/2000JD900719.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Todd, M. C., and R. Washington, 2004: Climate variability in central equatorial Africa: Influence from the Atlantic sector. Geophys. Res. Lett., 31, L23202, https://doi.org/10.1029/2004GL020975.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • van de Giesen, N., R. Hut, and J. Selker, 2014: The Trans-African Hydro-Meteorological Observatory (TAHMO). Wiley Interdiscip. Rev.: Water, 1, 341348, https://doi.org/10.1002/wat2.1034.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Vondou, D. A., A. Nzeukou, A. Lenouo, and F. M. Kamga, 2010a: Seasonal variations in the diurnal patterns of convection in Cameroon–Nigeria and the neighboring areas. Atmos. Sci. Lett., 11, 290300, https://doi.org/10.1002/asl.297.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Vondou, D. A., A. Nzeukou, and F. M. Kamga, 2010b: Diurnal cycle of convective activity over the West of Central Africa based on Meteosat images. Int. J. Appl. Earth Obs. Geoinf., 12 (Suppl. 1), S58S62, https://doi.org/10.1016/j.jag.2009.09.011.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xie, P., and P. A. Arkin, 1996: Analyses of global monthly precipitation using gauge observations, satellite estimates, and numerical model predictions. J. Climate, 9, 840858, https://doi.org/10.1175/1520-0442(1996)009<0840:AOGMPU>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xie, P., and P. A. Arkin, 1997: Global precipitation: A 17-year monthly analysis based on gauge observations, satellite estimates, and numerical model outputs. Bull. Amer. Meteor. Soc., 78, 25392558, https://doi.org/10.1175/1520-0477(1997)078<2539:GPAYMA>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Xie, P., R. J. Joyce, S. Wu, S.-H. Yoo, Y. Yarosh, F. Sun, and R. Lin, 2017: Reprocessed, bias-corrected CMORPH CRT global high resolution estimates form 1998. J. Hydrometeor., 18, 16171641, https://doi.org/10.1175/JHM-D-16-0168.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yin, X., and A. Gruber, 2010: Validation of the abrupt change in GPCP precipitation in the Congo River basin. Int. J. Climatol., 30, 110119, https://doi.org/10.1002/joc.1875.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yin, X., A. Gruber, and P. Arkin, 2004: Comparison of the GPCP and CMAP merged gauge-satellite monthly precipitation products for the period 1979–2001. J. Hydrometeor., 5, 12071222, https://doi.org/10.1175/JHM-392.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zebaze, S., A. Lenuou, and C. Tchawoua, 2017: Interaction between moisture transport and Kelvin waves over Equatorial Africa through ERA-Interim. Atmos. Sci. Lett., 18, 300306, https://doi.org/10.1002/asl.756.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zhou, L., and Coauthors, 2014: Widespread decline of Congo rainforest greenness in the past decade. Nature, 509, 8690, https://doi.org/10.1038/nature13265.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zipser, E. J., D. J. Cecil, C. T. Liu, S. W. Nesbitt, and D. P. Yorty, 2006: Where are the most intense thunderstorms on Earth? Bull. Amer. Meteor. Soc., 87, 10571071, https://doi.org/10.1175/BAMS-87-8-1057.

    • Crossref
    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 1151 475 18
PDF Downloads 1489 484 29