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Anvil Life BEST

To create, place the clay anvil form and 8 ingots in the furnace or bloomery. Using charcoal or hardwood billets to heat the Furnace to 1500, wait for the clay anvil form and the ingots to heat all the way up, then select it from the "Smelt" menu.

Anvil Life

Example of the cloud-tracking algorithm. (top row),(third row) A sequence of infrared images with the relative time in hours indicated above. (second row),(bottom row) Similar to the top and third rows, but marked to illustrate the cloud-tracking algorithm. An example cold core is shown in blue shading. The cold-core peak is defined as the time at which the cold core reaches its maximum area. The red circle shows the associated anvil region. The algorithm detects multiple cloud objects in this scene, but only one is shown for clarity. The frames are centered on 4S, 150E, and the first frame was measured at 1030 UTC 24 Jun 2016. Data are from Himawari.

Diurnal variation of the life cycle of anvil clouds. Cloud objects identified by the tracking algorithm are sorted into a day and a night composite in which the cold-core peak occurs between 0600 and 1200 LT and between 2100 and 0300 LT, respectively. Insolation and OLR averaged over the anvil region are plotted as a function of cloud age. A cloud age of zero corresponds to the cold-core peak. Error bars show the 95% confidence interval for the mean. Data are from Himawari.

Probability of lightning occurring within the anvil region plotted as a function of cloud age. A cloud age of zero corresponds to the cold-core peak. As in Figs. 6 and 7, anvil cloud objects from the day and night composites are shown separately. Lightning data are from the World Wide Lightning Location Network.

A variety of satellite and ground-based observations are used to study how diurnal variations of cloud radiative heating affect the life cycle of anvil clouds over the tropical western Pacific Ocean. High clouds thicker than 2 km experience longwave heating at cloud base, longwave cooling at cloud top, and shortwave heating at cloud top. The shortwave and longwave effects have similar magnitudes during midday, but only the longwave effect is present at night, so high clouds experience a substantial diurnal cycle of radiative heating. Furthermore, anvil clouds are more persistent or laterally expansive during daytime. This cannot be explained by variations of convective intensity or geographic patterns of convection, suggesting that shortwave heating causes anvil clouds to persist longer or spread over a larger area. It is then investigated if shortwave heating modifies anvil development by altering turbulence in the cloud. According to one theory, radiative heating drives turbulent overturning within anvil clouds that can be sufficiently vigorous to cause ice nucleation in the updrafts, thereby extending the cloud lifetime. High-frequency air motion and ice-crystal number concentration are shown to be inversely related near cloud top, however. This suggests that turbulence depletes or disperses ice crystals at a faster rate than it nucleates them, so another mechanism must cause the diurnal variation of anvil clouds. It is hypothesized that radiative heating affects anvil development primarily by inducing a mesoscale circulation that offsets gravitational settling of cloud particles.

Deep convective cloud systems typically contain extensive upper-level anvil clouds that spread laterally from the convection. It has long been recognized that these clouds are fundamental to the radiation budget and general circulation of the atmosphere, but understanding the complex interaction of processes within them has proven to be challenging (Houze 1982; Hartmann et al. 1984; Ramanathan et al. 1989). For instance, most of the ice in fresh anvil clouds occurs as crystals that are large enough to fall out of the upper troposphere within a few hours, yet anvils typically persist for much longer (Mace et al. 2006; Jensen et al. 2018). Some feedback processes must therefore exist to extend the cloud lifetime. The feedbacks may involve radiative heating, latent heating, cloud microphysics, turbulence, or mesoscale circulations, but the links between these processes are not fully understood.

One process that has been suggested to affect anvil development is the interaction among radiative heating, microphysics, and circulation within the cloud. Numerous modeling studies have investigated this process, and they generally suggest that radiative heating acts to extend the lifetime of elevated ice clouds (Starr and Cox 1985; Fu et al. 1995; Tao et al. 1996; Dobbie and Jonas 2001; Durran et al. 2009; Dinh et al. 2010; Harrop and Hartmann 2016; Hartmann and Berry 2017; Hartmann et al. 2018; Gasparini et al. 2019). However, some studies suggest that radiative heating may have little influence on anvil clouds or that it accelerates cloud decay (Boehm et al. 1999; Seeley et al. 2019). It is difficult to rule out any of these possibilities because current models are very sensitive to the parameterization of ice microphysics (Feng et al. 2018; Hartmann et al. 2018; Wall and Hartmann 2018; Gasparini et al. 2019). Understanding how anvil clouds interact with radiation would therefore help to validate and improve the treatment of ice microphysics in numerical models.

While ice nucleation in aged anvil clouds can be important in numerical simulations, it is unclear how often it occurs in nature. Nucleation events have been observed at the boundaries of anvil clouds where the concentration of preexisting ice is small enough that it does not constrain supersaturation. For instance, Jensen et al. (2009) measured an anvil cloud that had regions with numerous small crystals at cloud top, which appeared to be caused by ice nucleation in turbulent updrafts or gravity waves. Gallagher et al. (2012) measured a predominance of small bullet-rosette crystals at the lateral edges of an anvil, indicating that the crystals grew in the upper troposphere and perhaps nucleated near the cloud edge. Other field studies suggest that ice nucleation may be rare within anvil clouds, however (Lawson et al. 2010, 2019). A key goal for evaluating the microphysical cycling theory is to determine how often fresh nucleation of ice crystals occurs within aged anvil cirrus.

We analyze observations from the warm-pool region of the tropical western Pacific Ocean, where anvil clouds are common. Observational data are derived from polar-orbiting satellites in the A-Train constellation (Stephens et al. 2002), ground-based radar from the Atmospheric Radiation Measurement Program (Ackerman and Stokes 2003), and the Himawari-8 geostationary satellite (Bessho et al. 2016). The datasets and study region are described below. 041b061a72

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