## 1. Introduction

[2] This paper readdresses the question of the spatial correlations between the deviations of foF2 from the monthly median, ΔfoF2, because of their importance to the emerging global assimilative models of the ionosphere. The correlations have been discussed previously by *Rush* [1976] in terms of the requirements for an ionospheric observational network to be used for short-term forecasting of radio propagation conditions. With the advent of the GPS navigation system, most effort in this area has been concentrated on the correlation between the deviations of total electron content, ΔTEC. One of the key papers on ΔTEC was that by *Klobuchar and Johanson* [1977]. A recent paper [*Shim et al.*, 2008] presents a very detailed analysis of the ΔTEC correlations of worldwide observations of GPS TEC (for 2004), and provides extensive references to earlier papers.

[3] The earlier studies of spatial correlations ignored the effects of disturbances, treating all observations as part of a statistical ensemble with a continuous spectrum of disturbances. However, this approach can overestimate the correlation lengths because of the impact of outliers caused by storms. In this study, the observations have been grouped into two broad ranges: (1) all the observations, including storms, so that their impact can be demonstrated and (2) observations for quiet to moderately disturbed conditions (Ap < 25). The bulk of days for which global models are used will fall into this latter regime.

[4] *McNamara and Wilkinson* [1986] drew attention to the importance of separating the data into magnetically quiet and disturbed days, since lumping the data together can lead to correlation coefficients that apply to neither the quiet nor disturbed days. For example, a single disturbed day in a month that produces a large enhancement at one location and a large depression at another can change a correlation coefficient for the month from positive to negative. This negative correlation coefficient is clearly not relevant to the other 29/30 (quiet) days of the month. The program used to analyze the deviations in foF2 will optionally ignore any days with Ap > 25 (that we describe rather loosely as “quiet” days), which is the mode of operation used for the present study. It might be argued that a much lower value of Ap should be used to define a magnetically quiet day. However, the data sample sizes would then be reduced drastically. The Ap index itself is not an ideal index because it provides only a very simple measure of the changes to the Earth's magnetic field. The *Shim et al.* [2008] analysis was for intervals in 2004 that were generally magnetically quiet. However, *Rush* [1976] and *Klobuchar and Johanson* [1977], do not appear to have distinguished between quiet and disturbed days.

[5] The ionosondes providing the observations of foF2 described in this paper are located in Australia and Papua New Guinea, as shown in Figure 1 and Table 1. The Macquarie Island values of foF2 were not actually included because of the large number of values missing due to spread F echoes on the ionograms. The station order is basically alphabetical, except that Hobart was included at a later date (after the station numbering in the analysis program had been set). Like Macquarie Island, Hobart also has a large number of missing foF2 values.

Station | Site | Latitude | Longitude | Dip Latitude |
---|---|---|---|---|

1 | Brisbane (Australia) | −27.53 | 152.92 | −38.2 |

2 | Canberra (Australia) | −35.32 | 149.0 | −48.6 |

3 | Darwin (Australia) | −12.45 | 130.95 | −23.2 |

4 | Learmonth (Australia) | −22.25 | 114.08 | −36.6 |

5 | Port Moresby, PNG | −9.4 | 147.1 | −18.0 |

6 | Mundaring (Australia) | −31.98 | 116.22 | −49.0 |

7 | Norfolk I. (Australia) | −29.03 | 167.97 | −37.0 |

8 | Townsville (Australia) | −19.63 | 146.85 | −29.8 |

9 | Vanimo, PNG | −2.70 | 141.30 | −11.2 |

10 | Hobart (Australia) | −42.92 | 147.32 | −58.1 |

[6] The ionosonde data available from the IPS Radio and Space Services database (see the acknowledgments) were all manually scaled by experienced personnel, often by the ionosonde station operators. Each datum is in the standard URSI format QxxxD described by *Piggott and Rawer* [1972], and slightly modified over the years by international agreement. The “Q” is a qualifying letter that qualifies the scaled value, xxx, and “D” is a descriptive letter that provides information on why the value was qualified. For foF2, the values are given in units of 0.1 MHz, and the important qualifying letters are D (greater than), E (less than) and U (uncertain). All qualified values of foF2 have been set to zero and ignored in all the analyses. The nominal scaling error for manually scaled values of foF2 is 0.1 MHz.

[7] Section 2 of the paper gives examples of “deceptive” or storm-contaminated correlations that arise when the disturbed days are included. These examples are deceptive in that they are the result of a large storm, and thus are not typical of what happens on the ∼90% of the days of the months that are magnetically quiet (or nonstorm). Storm effects that give either a depression or enhancement at both locations can have the effect of enhancing the correlation coefficient above its value for the other days of the month. Storm effects with opposite signs can switch a positive correlation that is representative of the quiet days to a negative correlation that is not representative of either set of days.

[8] Section 3 gives the Brisbane-Canberra (942 km apart) correlation coefficients for each month of 2004, and shows that the correlation coefficients are significantly lower for magnetically quiet months. Some of the low correlation coefficients can be traced to low variances of foF2 at one or both of the ionosonde stations. The correlation coefficients have seasonal variations that are described in section 4.

[9] One of the main interests in studies of the foF2 correlation coefficients is to determine the rate at which the correlation coefficients decrease with increasing station separation, and this is discussed in the section 5. While this variation is very irregular, the correlation coefficients were found to decrease approximately linearly from ∼0.7 at ∼1000 km to ∼0.4 at 3000 km. The east-west correlation coefficients were found to be larger than the north-south coefficients.

[10] Section 6 discusses the correlation lengths that can be inferred from the correlation coefficients. The correlation lengths derived from the correlation coefficients given by *Rush* [1976] are significantly larger than those derived in this paper. Section 7 presents an overall summary of the results of the paper. A companion paper [*McNamara*, 2009] discusses the correlations of foF2 for station separations less than the minimum separation for the Australian ionosondes, which is 857 km.