top of page

setlife.com Group

Public·2 members

"Station 19" Under The Surface(2018)


Andy: I think I have to move out of my dad's place.Maya: I don't know what Miller said, but yes, I approve. Andy: It's time.Maya: Way past.Andy: I mean he's feeling better, he can take care of himself, and I need to do this, right away, before I chicken out and keep living there another 30 years. Maya: Have you told your dad yet? Andy: No, God, how do I tell him? What do I tell him?Maya: You say, "Dad, I've never lived out from under your roof. I need to be an adult now, so I'm moving in with Maya, and I feel confident that you can start folding your own boxers all by yourself."




"Station 19" Under the Surface(2018)


Download: https://www.google.com/url?q=https%3A%2F%2Furlcod.com%2F2uhpHk&sa=D&sntz=1&usg=AOvVaw2ADxZwzy2nvIISkRYJoSPF



Sullivan and Andy tell Evan that there's still no sign of Max. Andy makes a plan of where to go next, but Sullivan says planning is his part. Andy asks for permission and he grants it. Andy then calls the station and asks for an update on the blueprints. Pruitt asks Andy what the plan is. Andy tries to keep it positive, so Pruitt switches to Spanish so Sullivan won't understand and they talk about Sullivan. There's a handprint on the side of the storm drain, so they change direction to go where Max is heading.


While the overall pattern looks similar, the α scores for RH are slightly poorer compared to the temperature ones. However, α is still less than 1, except for a few stations over the mountains. As with the temperature, this poorer performance seems to arise mostly from phase errors. In particular, ρ is rather low for the water vapor mixing ratio, suggesting a deficient simulation of the near-surface moisture variability. A possible explanation is an incorrect representation of the observed precipitation and evaporation. Figure 8 shows the WRF and NICAM daily accumulated precipitation bias over the 3-day period. By and large, WRF tends to overestimate the observed precipitation and NICAM underestimates it. A possible explanation is the use of a double-moment cloud microphysics scheme in WRF: as highlighted in section 2c, double-moment schemes are known to overpredict moderate and heavy rainfall events when compared to single-moment microphysics schemes such as that employed in NICAM (e.g., Otkin et al. 2006; Hong et al. 2010). The biases have a larger magnitude mostly over the northeastern part of the country, possibly due to an incorrect representation of the topography, where the α values for the water vapor mixing ratio are lower.


As was the case for the winter period, and in line with other studies such as Gunwani and Mohan (2017), both WRF and NICAM generally underestimate the observed cloud cover, as concluded by visually comparing the two (not shown) and in line with other studies such as Schwitalla et al. (2019) and Wehbe et al. (2019), leading to enhanced downward shortwave radiation fluxes at the surface and warmer daytime air temperatures. The exception is when heavier than observed precipitation amounts are predicted, as seen by comparing Figs. 11 and 12 with Fig. 8. An example of this is for NICAM at Abu Dhabi, station 31 in Fig. 1c. At this station, the model predicts 22 mm of rainfall at the end of the day on 13 April, associated with the cooling tendency giving a daily mean temperature over the 3-day period roughly 2.24C below that observed (Fig. 14). In addition, and at a few inland stations, NICAM predicts lower nighttime temperatures than those observed, possibly due to clearer skies and enhanced radiative cooling and/or the deeper soil bottom and groundwater table depth highlighted in section 2c. Numerical models also exhibit nighttime cold biases over desert regions due to excessive longwave radiation fluxes at the surface, which can be corrected by employing a more sophisticated radiation scheme (Zittis and Hadjinicolaou 2016). A higher spatial resolution can also alleviate the temperature biases by allowing for a better representation of the topography and simulation of the observed cloud cover. The colder nighttime temperatures explain why the daily mean temperature bias is negative at some of the sites in Figs. 11 and 12. Despite biases of comparable magnitude, however, the α scores are generally lower (i.e., more skillful model predictions) for this event, in particular for WRF. An inspection of the ρ and scores showed that the improvement in α is mostly due to an increase in ρ. In April, the daylight hours are longer and the Sun is higher in the sky when compared to December that, together with the drier conditions observed in this period, leads to a larger magnitude temperature diurnal cycle, which both models seem to be more capable of simulating (not shown). 041b061a72


About

Welcome to the group! You can connect with other members, ge...
bottom of page