From a34c89f8e25fb40f6ce7aacc93d4a7fa7626d548 Mon Sep 17 00:00:00 2001 From: John Halley Gotway Date: Mon, 2 Aug 2021 13:17:14 -0600 Subject: [PATCH] Per #1673, making changes requested by Eric. --- met/docs/Users_Guide/appendixC.rst | 3 ++- met/docs/Users_Guide/grid-stat.rst | 2 +- 2 files changed, 3 insertions(+), 2 deletions(-) diff --git a/met/docs/Users_Guide/appendixC.rst b/met/docs/Users_Guide/appendixC.rst index b9da4f2b9d..0feeff67e1 100644 --- a/met/docs/Users_Guide/appendixC.rst +++ b/met/docs/Users_Guide/appendixC.rst @@ -1184,7 +1184,8 @@ The range for ZHU is 0 to infinity, with a score of 0 indicating a perfect forec ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Called "G" and "GBETA" in the DMAP output :numref:`table_GS_format_info_DMAP` -See :numref:`grid-stat_gbeta` for a description of these statistics. + +See :numref:`grid-stat_gbeta` for a description. Let :math:`y = {y_1}{y_2}` where :math:`y_1 = n_A + n_B - 2n_{AB}`, and :math:`y_2 = MED(A,B) \cdot n_B + MED(B,A) \cdot n_A`, with the mean-error distance (:math:`MED`) as described above, and where :math:`n_{A}`, :math:`n_{B}`, and :math:`n_{AB}` are the number of events within event areas *A*, *B*, and the intersection of *A* and *B*, respectively. diff --git a/met/docs/Users_Guide/grid-stat.rst b/met/docs/Users_Guide/grid-stat.rst index f85cc964c8..b5eeb5afed 100644 --- a/met/docs/Users_Guide/grid-stat.rst +++ b/met/docs/Users_Guide/grid-stat.rst @@ -127,7 +127,7 @@ The statistics derived from these distance maps are described in :numref:`Append :math:`\beta` and :math:`G_\beta` ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ -See :numref:`App_C-gbeta` for the equations for :math:`G` and :math:`G_\beta`. +See :numref:`App_C-gbeta` for the :math:`G` and :math:`G_\beta` equations. :math:`G_\beta` provides a summary measure of forecast quality for each user-defined threshold chosen. It falls into a range from zero to one where one is a perfect forecast and zero is considered to be a very poor forecast as determined by the user through the value of :math:`\beta`. Values of :math:`G_\beta` closer to one represent better forecasts and worse forecasts as it decreases toward zero. Although a particular value cannot be universally compared against any forecast, when applied with the same choice of :math:`\beta` for the same variable and on the same domain, it is highly effective at ranking such forecasts.