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Nicolas Le Moine
,
Frédéric Hendrickx
,
Joël Gailhard
,
Rémy Garçon
, and
Frédéric Gottardi

, complementary to cross-validation data. However, as mentioned earlier, in this independent analysis it is not possible to easily feed the interpolation scheme back with the discrepancies between observed and simulated streamflow time series. This can be a problem if the quality of the forcings is deemed insufficient for the applications projected. Fig . 1. Comparison of the independent vs joint calibration of hydrometeorological parameters. (a) In the independent analysis, the drift parameters , allowing

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Kaniska Mallick
,
Andrew Jarvis
,
Joshua B. Fisher
,
Kevin P. Tu
,
Eva Boegh
, and
Dev Niyogi

ɛ = Δ/( Δ + γ ). From the above equation, Dividing both sides of Eq. (19) by λE , we get Dividing the numerator and denominator of the right-hand side of Eq. (19) by PE PT , we get According to Priestley and Taylor (1972) , where Φ can also be expressed as Φ = ( λE /EF). Therefore, Now, substituting this expression of from (22) into (21) and after some algebra, Replacing between (17) and (23) , we can express EF in terms of conductance: After some algebra, the final expression

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James D. Brown
,
Dong-Jun Seo
, and
Jun Du

were obtained for comparison. The RFC QPEs are less uniform than the CCPA QPEs, comprising a range of dates, accumulation periods, basin averaging techniques, and data sources, including gauge-based, radar-based, and gauge-adjusted radar estimates. The quality control also varies between RFCs, with some RFCs (notably NWRFC) employing custom station weights when deriving the MAPs for hydrologic simulations (see below). Nevertheless, the RFC and CCPA observations are highly correlated, with

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Yang Lu
,
Susan C. Steele-Dunne
, and
Gabriëlle J. M. De Lannoy

contained in SMAP TB observations for surface turbulent heat flux estimation in comparison with that from SMAP soil moisture retrievals, through assimilation with GOES LST data, and to provide insight into the differences in using horizontally or vertically polarized TB data. This paper is structured as follows: section 2 introduces the datasets and model framework, including the state propagation model and radiative transfer model as well as the bias correction approach. The model simulation

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Jerald A. Brotzge
and
Kenneth C. Crawford

Algebraically solving for G gives If we assume the heat capacity, C, is invariant across the soil layer, then we finally arrive at Fig . 1. Map of the ten OASIS super sites which are equipped with net radiation, ground heat flux, and eddy correlation instrumentation. The ARM site is collocated with the mesonet site facility at Foraker (FORA) in northeastern Oklahoma Fig . 2. At the EC site, (a) closure (%) and (b) residual (W m −2 ) of the energy balance plotted as a function of the

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P. Reggiani
and
A. H. Weerts

The next procedural step is to map the respective variates into the normal space through the application of the normal quantile transform (NQT) (e.g., Kelly and Krzysztofowicz 1994 ). The application of the NQT yields Gaussian surrogate variates in the normal space. In the normal space, expressions for moments of distributions are obtained analytically and relationships between statistical variables, as necessary for deriving the likelihood, can be fitted via (multi)linear regressions. Parametric

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David W. Pierce
,
Lu Su
,
Daniel R. Cayan
,
Mark D. Risser
,
Ben Livneh
, and
Dennis P. Lettenmaier

should have little effect on extreme statistics given enough samples. These arguments will be addressed theoretically ( section 3a ), by an empirical analysis using hourly gauge observations to construct a synthetic once-daily observed time series ( section 3b ), and via a direct comparison between extreme statistics of L13 , the original station data, and the new unadjusted dataset introduced here ( section 3c ). a. How time adjustment alters precipitation statistics Precipitation can have

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