**Figure 1.**
(**a**) European sites releasing radiosonde balloons twice a day (00 Zulu and 12 Zulu); and (**b**) sounding data close to Kirov airport on 20 June 2018 from ground to 7984 m.

**Figure 1.**
(**a**) European sites releasing radiosonde balloons twice a day (00 Zulu and 12 Zulu); and (**b**) sounding data close to Kirov airport on 20 June 2018 from ground to 7984 m.

**Figure 2.**
A full, crowded version of the Herlofson’s nomogram that typically confuses users who are overwhelmed by lines and numbers.

**Figure 2.**
A full, crowded version of the Herlofson’s nomogram that typically confuses users who are overwhelmed by lines and numbers.

**Figure 3.**
A simplified version of the Herlofson’s nomogram produced by our interactive environment, displaying only isotherms (parallel to the yellow bands) and dry adiabats (green dashed lines). It is easy to grasp that the temperature axis is rotated by 45° and that isotherms exhibit a large angle (around 90°) with dry adiabats.

**Figure 3.**
A simplified version of the Herlofson’s nomogram produced by our interactive environment, displaying only isotherms (parallel to the yellow bands) and dry adiabats (green dashed lines). It is easy to grasp that the temperature axis is rotated by 45° and that isotherms exhibit a large angle (around 90°) with dry adiabats.

**Figure 4.**
(**a**) The nomogram skew-T, log-P. The x-axis, temperature, is rotated 45° (skew-T), the y-axis, pressure, has an inverted scale (the higher is the pressure, the lower is the altitude) and it is logarithmic (log-P), to compensate the nonlinear relationship between pressure and altitude; the nomogram is very far from the axes origin. (**b**) The temperature state curve (red) and the humidity dew-point curve (blue).

**Figure 4.**
(**a**) The nomogram skew-T, log-P. The x-axis, temperature, is rotated 45° (skew-T), the y-axis, pressure, has an inverted scale (the higher is the pressure, the lower is the altitude) and it is logarithmic (log-P), to compensate the nonlinear relationship between pressure and altitude; the nomogram is very far from the axes origin. (**b**) The temperature state curve (red) and the humidity dew-point curve (blue).

**Figure 5.**
Air warmer than atmosphere rises along a dry adiabat reaching its dew-point; after that, it rises along a wet adiabats and generates a dangerous cloud that will likely produce a thunderstorm.

**Figure 5.**
Air warmer than atmosphere rises along a dry adiabat reaching its dew-point; after that, it rises along a wet adiabats and generates a dangerous cloud that will likely produce a thunderstorm.

**Figure 6.**
Overview of the IVAN Web application. The left side shows the Herlofson’s nomogram, the central part presents detailed sounding data, configuration commands and the main atmospheric indicators, while right side reports several detailed sounding indices.

**Figure 6.**
Overview of the IVAN Web application. The left side shows the Herlofson’s nomogram, the central part presents detailed sounding data, configuration commands and the main atmospheric indicators, while right side reports several detailed sounding indices.

**Figure 7.**
(**a**) Exploring the state curve (sc), sounding points, and making explicit how to read the values of the curve; (**b**) dealing with dry adiabats; and (**c**) dealing with wet adiabats.

**Figure 7.**
(**a**) Exploring the state curve (sc), sounding points, and making explicit how to read the values of the curve; (**b**) dealing with dry adiabats; and (**c**) dealing with wet adiabats.

**Figure 8.**
(**a**) Exploring state curve (sc) and dew-point (dpc) curve; (**b**) carefully introducing the notion of iso-humidity w.r.t. dew-points curve; and (**c**) carefully introducing the notion of iso-humidity with respect to the state curve, better clarifying its meaning.

**Figure 8.**
(**a**) Exploring state curve (sc) and dew-point (dpc) curve; (**b**) carefully introducing the notion of iso-humidity w.r.t. dew-points curve; and (**c**) carefully introducing the notion of iso-humidity with respect to the state curve, better clarifying its meaning.

**Figure 9.**
(**a**) Relationship between sounding points and state and dew-point curves; (**b**) evolution of raising air along dry and wet adiabats; and (**c**) computing condensation altitude.

**Figure 9.**
(**a**) Relationship between sounding points and state and dew-point curves; (**b**) evolution of raising air along dry and wet adiabats; and (**c**) computing condensation altitude.

**Figure 10.**
The e-learning slide (translated into English) teaching the air temperature gradient and the nomogram isotherms usage from the Herlofson module version.

**Figure 10.**
The e-learning slide (translated into English) teaching the air temperature gradient and the nomogram isotherms usage from the Herlofson module version.

**Figure 11.**
The e-learning slide (translated in English) teaching the air temperature gradient and the nomogram isotherms usage using an image from the IVAN system, in which all irrelevant concepts (i.e., dry adiabats lines, wet adiabats lines, iso-humidity lines, and humidity scale) were removed to simplify the learning activity.

**Figure 11.**
The e-learning slide (translated in English) teaching the air temperature gradient and the nomogram isotherms usage using an image from the IVAN system, in which all irrelevant concepts (i.e., dry adiabats lines, wet adiabats lines, iso-humidity lines, and humidity scale) were removed to simplify the learning activity.

**Figure 12.**
Answering a question along the e-learning activity using the Herlofson module. Images come from the STEIN system [

20] that automatically collects answers, reading time, and low-level user actions.

**Figure 12.**
Answering a question along the e-learning activity using the Herlofson module. Images come from the STEIN system [

20] that automatically collects answers, reading time, and low-level user actions.

**Figure 13.**
Answering the same question shown in

Figure 12 using the IVAN module.

**Figure 13.**
Answering the same question shown in

Figure 12 using the IVAN module.

**Figure 14.**
Box-plots reporting effectiveness, evaluated by the number of corrected answers normalized to 10, i.e., score, completion time, efficiency, and perceived usability. The red line represents the median, while the dotted line represents the mean. The box-plot on the left shows the distribution of the average scores obtained by counting participants’ correct answers and normalizing that value to 10. The two box-plots in the middle depicts the distribution of the average time spent to complete the experiment (in min) and the ratio score/time, respectively. The box-plot on the right shows the average scores of the PSSUQ questionnaire. A between-subjects one-way ANOVA, detailed in the **Results** Section, confirmed a significant positive effect of using IVAN images on Score and Time.

**Figure 14.**
Box-plots reporting effectiveness, evaluated by the number of corrected answers normalized to 10, i.e., score, completion time, efficiency, and perceived usability. The red line represents the median, while the dotted line represents the mean. The box-plot on the left shows the distribution of the average scores obtained by counting participants’ correct answers and normalizing that value to 10. The two box-plots in the middle depicts the distribution of the average time spent to complete the experiment (in min) and the ratio score/time, respectively. The box-plot on the right shows the average scores of the PSSUQ questionnaire. A between-subjects one-way ANOVA, detailed in the **Results** Section, confirmed a significant positive effect of using IVAN images on Score and Time.

**Figure 15.**
Top bars: errors of users along the nine questions. It is quite evident that, for simple questions (Q1–Q7), the two groups performed in a similar way, with a percentage of errors around 20%; conversely, the most challenging questions, Q8 and Q9, requiring complex diagram navigation, exhibit a very high rate of error for the Herlofson group (errors were 100% and 94%, respectively) and a high error percentage for the IVAN group (errors were 56% and 44%, respectively). Bottom table: Means and p values of score and completion time for each question; cells highlighted in yellow represent significant differences ($p<0.05$).

**Figure 15.**
Top bars: errors of users along the nine questions. It is quite evident that, for simple questions (Q1–Q7), the two groups performed in a similar way, with a percentage of errors around 20%; conversely, the most challenging questions, Q8 and Q9, requiring complex diagram navigation, exhibit a very high rate of error for the Herlofson group (errors were 100% and 94%, respectively) and a high error percentage for the IVAN group (errors were 56% and 44%, respectively). Bottom table: Means and p values of score and completion time for each question; cells highlighted in yellow represent significant differences ($p<0.05$).