Science Discussions and questions : part 1

In this part I’ll be discussing the interactions I had regarding the new problems on science

There is a paper on impact of Aerosols by Tegen et al (http://www.nsstc.uah.edu/~naeger/references/journals/Sundar_Journal_Papers/1998_JC_Miller.pdf) which says that the precipitation decreases in the Arabian Sea due to Aerosols, but the change in temperature is only on land as they are using an AGCM in which the SST is constant. As we have a coupled model the effects on Ocean can also be checked.

Another issue in the Nature geoscience paper by V Vinoj(http://www.nature.com/ngeo/journal/v7/n4/pdf/ngeo2107.pdf) is that he says that the dust induced atmospheric heating over North Africa and Arabian Peninsula rapidly modulates the monsoon rainfall over central India. Its not very clear as to how this takes place.

Another problem of interest that can be studied is the impact of Sea Salt over Arabian Sea on the precipitation that takes place over Western Ghats.

Other refernces

http://www.nature.com/nature/journal/v380/n6573/abs/380419a0.html

Advertisements

Introduction – Cloud and Precipitation Microphysics – Jerry M Straka

Areas which combine to form the Cloud Microphysics subject

cloud dynamics, cloud microphysics, cloud optics, cloud electrification, cloud chemistry, and the interaction of cloud and precipitation particles with electromagnetic radiation (i.e. radar).

Aims of the book

  1. the development of various parameterizations of cloud and precipitation microphysical processes;
  2. and when possible the exploration of the basic theories necessary for their development

Scale of the cloud processes involved are:

  1. Aitken aerosol particles O(10^-2 mm) to
  2. giant aerosol particles O(10^0 mm) to
  3. ultra-giant aerosols and cloud particles O(10^1 mm) to
  4. drizzle and snow crystal particles O(10^2 mm) to
  5. rain, snow aggregate, and graupel particles O(10^3 to 10^4 mm) to
  6. hail particles O(10^4 to 10^5 mm)

Thus nearly six orders of magnitude in size must be covered.

This is similar to studying

  1. The development of small wind swirls O(10^-1 m) to
  2. dust devils O(10^0 to 10^1 m) to
  3. cumulus clouds O(10^2 to 10^3 m) to
  4. convective clouds such as thunderstorms O(10^3 to 10^4 m) to
  5. mesoscale phenomena such as large thunderstorm complexes and hurricanes O(10^5 m) to
  6. synoptic scale phenomena such as Rossby waves O(10^6 m) all relative to one
    another

Types of microphysical parameterization models

Lagrangian trajectory parameterization models

Lagrangian trajectory parameterization models are the type of models that can incorporate the most detailed microphysical information based on observations, physical experiments, and theoretical considerations of any parameterization model for hydrometeor growth

Bin parameterization models

They have bins (i.e. small divisions) representing the spectrum of drops from very small cloud droplet sizes (4 mm) to larger raindrops (4 to 8 mm) for parameterizations of rain formation.

Each bin is usually exponentially larger than the previous size/mass bin owing to the wide spectrum of liquid-water drops that are possible, which ranges over three orders of magnitude.

An Example

For liquid-water drop sizes, bins often will increase by 2, 2^1/2 , 2^1/3 , or 2^1/4 times the previous size bin over 36, 72, or 144 bins (or any number required for a converged solution), starting with particles of about 2 to 8 mm in diameter and increasing to a size that contains the spectra of rain, ice, snow, graupel, and hail.

Bin parameterization size-spectra can also be made for other hydrometeor species including ice crystals, snow crystals, snow aggregates, graupel, frozen drops, and hail with similar bin spacing. Some models also have bins for aerosols and track solute concentrations. At a min-
imum, the number concentration must be predicted with these schemes, though mixing ratio and reflectivity can be predicted or calculated. Considering number concentration with mixing ratio prediction improves the results against using just number concentration

Bulk parameterization models

Bulk microphysical model parameterizations are some of the most popular schemes available owing to much reduced computational cost compared to most bin models for use in three-dimensional models.

These microphysical parameterizations are based on number distribution functions such as mono dispersed, negative exponential, gamma, and log-normal distributions, to name a few, for each hydrometeor species’ size distribution. These distributions are normalizable and integratable over complete size distributions of diameter from zero to infinity, or partial distributions (most common with the gamma distribution) from diameters of 0 to D1 meters or D2 to infinity meters or even D1 to D2 meters. Typically, mixing ratio and number concentration are predicted with these parameterizations. Whilst reflectivity can be predicted, it can be used to obtain an estimate of the gamma distribution shape parameter of the size distribution as a function of time.

Hybrid bin parameterization models

Hybrid bin parameterizations have many of the qualities of both bulk and microphysical model parameterizations, however growth and loss parameterizations are done differently than direct integration of spectrum interactions such as, for example, collection of one hydrometeor species by another species. Instead, the mixing-ratio and number-concentration distribution functions are converted to bins and computations are done with a bin model; then results are converted back to bulk microphysical model parameterization mixing ratios and number concentrations as described by some distribution function. With these models an attempt is made to capture the “supposed” accuracy of bin models in a bulk microphysical model parameterization without the memory storage of the full bin model. One shortcoming with hybrid bin parameterizations compared to bin parameterizations is that the bin parameterization solution is not carried from timestep to timestep, in particular the bin parameterization size spectra.

Warm-rain parameterizations

Warm-rain processes include the development of precipitating rain without the presence of ice water. However, clouds can have both warm-rain processes and cold-rain processes occurring simultaneously, both in the same and in different locations. Following closely the ideas put forth by Cotton and Anthes (1989), the basic physics that need to be included in
a warm-rain parameterization are the following in some fashion or other. These concepts are to some extent based on bin parameterizations of warm-rain processes, but are quickly becoming more commonplace in bulk microphysical model parameterizations.

The sequence of processes are :

  1. The nucleation of droplets on aerosol particles
  2. Condensation and evaporation of cloud droplets as well as drizzle and raindrops
  3. The development of a mature raindrop spectrum by collection of other liquid species(including cloud droplets, drizzle, and raindrops themselves)
  4. The inclusion of breakup of raindrops
  5. The occurrence of self-collection in the droplet and drop spectra
  6. The differential sedimentation of the various liquid drop species within the species, for example, rain from different sources.

Cold-rain and ice-phase parameterizations

More difficult than that for warm-rain parameterizations, and warm-rain processes

Cotton and Anthes (1989) point out that many of the ice microphysical processes are not parameterizable in terms of results from bin models, theoretical consideration, or empirical fits to observations without considerable uncertainty.

Again following Cotton and Anthes (1989), to as reasonable an extent as possible, the following processes should be included in some fashion or other.

  1. Homogeneous freezing of cloud drops into ice crystals.
  2. Primary, heterogeneous ice nucleation mechanism such as contact freezing, deposition, sorption, and immersion freezing nucleation.
  3. Secondary ice nucleation mechanisms such as rime-splintering ice production and
    mechanical fracturing of ice.
  4. Vapor deposition and sublimation of ice particles.
  5. Riming and density changes of ice particles.
  6. Aggregation of ice crystals to form snow aggregates.
  7. Graupel initiation by freezing of drizzle and subsequent heavy riming.
  8. Graupel initiation by heavy riming of ice crystals.
  9. Freezing of raindrops, with smaller particles becoming graupel particle embryos owing to riming, and larger particles possibly becoming hail embryos.
  10. Graupel and frozen drops becoming hail embryos by collecting rain or heavy riming.
  11. Wet and dry growth of hail.
  12. Temperature prediction of ice-water particles.
  13. Density changes in graupel and hail.
  14. Shedding from hail during wet growth and melting.
  15. Soaking of hail and graupel particles during wet growth and melting.
  16. Melting of ice-water particles.
  17. Mixed-phase liquid- and ice-water particles.
  18. Differential sedimentation of the various sub-ice species and within a given species.

For details on the Microphysical processes such as riming go to

http://www.atmo.ttu.edu/schroeder/ATMO_1300/Notes/chapter7.pdf

http://www.cas.manchester.ac.uk/resactivities/cloudphysics/results/riming/

https://en.wikipedia.org/wiki/Bergeron_process

https://en.wikipedia.org/wiki/Cloud_physics#Supersaturation