Geology topics

K.J. Remick

Publications and source records attributed to K.J. Remick.

3 recordsLinked to original sources

USGS2007

Statistical modeling of storm level Kp occurrences: Solar cycle modulation

We consider the nonstationary, statistical modeling of the occurrence in time of large Kp geomagnetic storms over the course of multiple solar cycles. Previous work showed that wait times between storms can be represented by an exponential density function, consistent with the realization of a Poisson process. Here we also assume a Poisson process, but to account for solar cycle modulation of storm likelihood, we assume an occurrence rate given by a parametric constant plus a simple sinusoidal function of time. Parameter estimation is accomplished using maximum likelihood, yielding good fits to the Kp data. We find that the relative phase between storms and sunspots depends on storm size. We quantify previous observations that small storms tend to occur during the declining phase of the solar cycle, while large storms tend to occur very close to solar maximum. We predict average wait time between storms and the storm occurrence rate up through the year 2018.

Space Weather↗

USGS2007

Magnetic indices

Magnetic indices are simple measures of magnetic activity that occurs, typically, over periods of time of less than a few hours and which is recorded by magnetometers at ground‐based observatories (Mayaud, 1980 ; Rangarajan, 1989 ; McPherron, 1995 ). The variations that indices measure have their origin in the Earth's ionosphere and magnetosphere. Some indices having been designed specifically to quantify idealized physical processes, while others function as more generic measures of magnetic activity. Indices are routinely used across the many subdisciplines in geomagnetism, including direct studies of the physics of the upper atmosphere and space, for induction studies of the Earth's crust and mantle, and for removal of disturbed‐time magnetic data in studies of the Earth's deep interior and core. Here we summarize the most commonly used magnetic indices, using data from a worldwide distribution of observatories, those shown in Figure M31 and whose sponsoring agencies are given in Table M1 .

Book chapter↗

USGS2006

Statistical modeling of storm-level Kp occurrences

We consider the statistical modeling of the occurrence in time of large Kp magnetic storms as a Poisson process, testing whether or not relatively rare, large Kp events can be considered to arise from a stochastic, sequential, and memoryless process. For a Poisson process, the wait times between successive events occur statistically with an exponential density function. Fitting an exponential function to the durations between successive large Kp events forms the basis of our analysis. Defining these wait times by calculating the differences between times when Kp exceeds a certain value, such as Kp ??? 5, we find the wait-time distribution is not exponential. Because large storms often have several periods with large Kp values, their occurrence in time is not memoryless; short duration wait times are not independent of each other and are often clumped together in time. If we remove same-storm large Kp occurrences, the resulting wait times are very nearly exponentially distributed and the storm arrival process can be characterized as Poisson. Fittings are performed on wait time data for Kp ??? 5, 6, 7, and 8. The mean wait times between storms exceeding such Kp thresholds are 7.12, 16.55, 42.22, and 121.40 days respectively.

Geophysical Research Letters↗