Bibliography

BPS06

N. E. Bowler, C. E. Pierce, and A. W. Seed. STEPS: a probabilistic precipitation forecasting scheme which merges an extrapolation nowcast with downscaled NWP. Quarterly Journal of the Royal Meteorological Society, 132(620):2127–2155, 2006. doi:10.1256/qj.04.100.

BrockerS07

J. Bröcker and L. A. Smith. Increasing the reliability of reliability diagrams. Weather and Forecasting, 22(3):651–661, 2007. doi:10.1175/WAF993.1.

CRS04

B. Casati, G. Ross, and D. B. Stephenson. A new intensity-scale approach for the verification of spatial precipitation forecasts. Meteorological Applications, 11(2):141––154, 2004. doi:10.1017/S1350482704001239.

CP02

A. Clothier and G. Pegram. Space-time modelling of rainfall using the string of beads model: integration of radar and raingauge data. WRC Report No. 1010/1/02. Water Research Commission, Durban, South Africa, 2002.

EWW+13

E. Ebert, L. Wilson, A. Weigel, M. Mittermaier, P. Nurmi, P. Gill, M. Göber, S. Joslyn, B. Brown, T. Fowler, and A. Watkins. Progress and challenges in forecast verification. Meteorological Applications, 20(2):130–139, 2013. doi:10.1002/met.1392.

FSN+19

L. Foresti, I.V. Sideris, D. Nerini, L. Beusch, and U. Germann. Using a 10-year radar archive for nowcasting precipitation growth and decay: a probabilistic machine learning approach. Weather and Forecasting, 34:1547–1569, 2019. doi:10.1175/WAF-D-18-0206.1.

FNP+20

G. Franch, D. Nerini, M. Pendesini, L. Coviello, G. Jurman, and C. Furlanello. Precipitation nowcasting with orographic enhanced stacked generalization: improving deep learning predictions on extreme events. Atmosphere, 11(3):267, 2020. doi:10.3390/atmos11030267.

GZ02

U. Germann and I. Zawadzki. Scale-dependence of the predictability of precipitation from continental radar images. Part I: description of the methodology. Monthly Weather Review, 130(12):2859–2873, 2002. doi:10.1175/1520-0493(2002)130<2859:SDOTPO>2.0.CO;2.

HMG+04

A. M. Hering, C. Morel, G. Galli, P. Ambrosetti, and M. Boscacci. Nowcasting thunderstorms in the alpine region using a radar based adaptive thresholding scheme. Proceedings of ERAD Conference 2004, pages 206–211, 2004. URL: http://www.meteoschweiz.admin.ch/web/en/research/completed_projects/trt.Related.0002.DownloadFile.tmp/erad04p00039trt.pdf.

Her00

H. Hersbach. Decomposition of the continuous ranked probability score for ensemble prediction systems. Weather and Forecasting, 15(5):559–570, 2000. doi:10.1175/1520-0434(2000)015<0559:DOTCRP>2.0.CO;2.

NBS+17

D. Nerini, N. Besic, I. Sideris, U. Germann, and L. Foresti. A non-stationary stochastic ensemble generator for radar rainfall fields based on the short-space Fourier transform. Hydrology and Earth System Sciences, 21(6):2777–2797, 2017. doi:10.5194/hess-21-2777-2017.

PvGPO94

M. Proesmans, L. van Gool, E. Pauwels, and A. Oosterlinck. Determination of optical flow and its discontinuities using non-linear diffusion. In J.-O. Eklundh, editor, Computer Vision — ECCV '94, volume 801 of Lecture Notes in Computer Science, pages 294–304. Springer Berlin Heidelberg, 1994.

PCH18a

S. Pulkkinen, V. Chandrasekar, and A.-M. Harri. Fully spectral method for radar-based precipitation nowcasting. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 12(5):1369–1382, 2018.

PCH18b

S. Pulkkinen, V. Chandrasekar, and A.-M. Harri. Nowcasting of precipitation in the high-resolution Dallas-Fort Worth (DFW) urban radar remote sensing network. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 11(8):2773–2787, 2018. doi:10.1109/JSTARS.2018.2840491.

PCH19

S. Pulkkinen, V. Chandrasekar, and A.-M. Harri. Stochastic spectral method for radar-based probabilistic precipitation nowcasting. Journal of Atmospheric and Oceanic Technology, 36(6):971–985, 2019.

PCvLH20

S. Pulkkinen, V. Chandrasekar, A. von Lerber, and A.-M. Harri. Nowcasting of convective rainfall using volumetric radar observations. IEEE Transactions on Geoscience and Remote Sensing, pages 1–15, 2020. doi:10.1109/TGRS.2020.2984594.

RFvHP06

N. Rebora, L. Ferraris, J. von Hardenberg, and A. Provenzale. Rainfarm: rainfall downscaling by a filtered autoregressive model. Journal of Hydrometeorology, 7(4):724–738, 2006. doi:10.1175/JHM517.1.

RL08

N. M. Roberts and H. W. Lean. Scale-selective verification of rainfall accumulations from high-resolution forecasts of convective events. Monthly Weather Review, 136(1):78–97, 2008. doi:10.1175/2007MWR2123.1.

RC11

E. Ruzanski and V. Chandrasekar. Scale filtering for improved nowcasting performance in a high-resolution X-band radar network. IEEE Transactions on Geoscience and Remote Sensing, 49(6):2296–2307, June 2011.

RCW11

E. Ruzanski, V. Chandrasekar, and Y. Wang. The CASA nowcasting system. Journal of Atmospheric and Oceanic Technology, 28(5):640–655, 2011. doi:10.1175/2011JTECHA1496.1.

See03

A. W. Seed. A dynamic and spatial scaling approach to advection forecasting. Journal of Applied Meteorology, 42(3):381–388, 2003. doi:10.1175/1520-0450(2003)042<0381:ADASSA>2.0.CO;2.

SPN13

A. W. Seed, C. E. Pierce, and K. Norman. Formulation and evaluation of a scale decomposition-based stochastic precipitation nowcast scheme. Water Resources Research, 49(10):6624–6641, 2013. doi:10.1002/wrcr.20536.

ZR09

P. Zacharov and D. Rezacova. Using the fractions skill score to assess the relationship between an ensemble QPF spread and skill. Atmospheric Research, 94(4):684–693, 2009. doi:10.1016/j.atmosres.2009.03.004.