Abstract A two-dimensional version of the Pennsylvania State University mesoscale model has been applied to Winter Monsoon Experiment data in order to simulate the diurnally occurring convection observed over the South China Sea. The domain includes a representation of part of Borneo as well as the sea so that the model can simulate the initiation of convection. Also included in the model are parameterizations of mesoscale ice phase and moisture processes and longwave and shortwave radiation with a diurnal cycle. This allows use of the model to test the relative importance of various heating mechanisms to the stratiform cloud deck, which typically occupies several hundred kilometers of the domain. Frank and Cohen's cumulus parameterization scheme is employed to represent vital unresolved vertical transports in the convective area. The major conclusions are: Ice phase processes are important in determining the level of maximum large-scale heating and vertical motion because there is a strong anvil componen...

Numerical study of convection observed during the Winter Monsoon Experiment using a mesoscale two-dimensional model [presentation]

Black carbon in soot is an efficient absorbing agent of solar irradiation that is preferentially emitted in the tropics and can form atmospheric brown clouds in mixture with other aerosols. These factors combine to make black carbon emissions the second most important contribution to anthropogenic climate warming, after carbon dioxide emissions.

Global and regional climate changes due to black carbon

There is a direct influence of global warming on precipitation. Increased heating leads to greater evaporation and thus surface drying, thereby increasing the intensity and duration of drought. However, the water holding capacity of air increases by about 7% per 1°C warming, which leads to increased water vapor in the atmosphere. Hence, storms, whether individual thunderstorms, extratropical rain or snow storms, or tropical cyclones, supplied with increased moisture, produce more intense precipitation events. Such events are observed to be widely occurring, even where total precipitation is decreasing: 'it never rains but it pours!' This increases the risk of flooding. The atmo- spheric and surface energy budget plays a critical role in the hydrological cycle, and also in the slower rate of change that occurs in total precipitation than total column water vapor. With modest changes in winds, patterns of precipitation do not change much, but result in dry areas becoming drier (generally throughout the subtropics) and wet areas becoming wetter, especially in the mid- to high latitudes: the 'rich get richer and the poor get poorer'. This pattern is simulated by climate mod- els and is projected to continue into the future. Because, with warming, more precipitation occurs as rain instead of snow and snow melts earlier, there is increased runoff and risk of flooding in early spring, but increased risk of drought in summer, especially over continental areas. However, with more precipitation per unit of upward motion in the atmosphere, i.e. 'more bang for the buck', atmo- spheric circulation weakens, causing monsoons to falter. In the tropics and subtropics, precipitation patterns are dominated by shifts as sea surface temperatures change, with El Nino a good example. The volcanic eruption of Mount Pinatubo in 1991 led to an unprecedented drop in land precipitation and runoff, and to widespread drought, as precipitation shifted from land to oceans and evaporation faltered, providing lessons for possible geoengineering. Most models simulate precipitation that occurs prematurely and too often, and with insufficient intensity, resulting in recycling that is too large and a lifetime of moisture in the atmosphere that is too short, which affects runoff and soil moisture.

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Changes in precipitation with climate change

Climate change projections for the Mediterranean region

Anthropogenic aerosols are intricately linked to the climate system and to the hydrologic cycle. The net effect of aerosols is to cool the climate system by reflecting sunlight. Depending on their composition, aerosols can also absorb sunlight in the atmosphere, further cooling the surface but warming the atmosphere in the process. These effects of aerosols on the temperature profile, along with the role of aerosols as cloud condensation nuclei, impact the hydrologic cycle, through changes in cloud cover, cloud properties and precipitation. Unravelling these feedbacks is particularly difficult because aerosols take a multitude of shapes and forms, ranging from desert dust to urban pollution, and because aerosol concentrations vary strongly over time and space. To accurately study aerosol distribution and composition therefore requires continuous observations from satellites, networks of ground-based instruments and dedicated field experiments. Increases in aerosol concentration and changes in their composition, driven by industrialization and an expanding population, may adversely affect the Earth's climate and water supply.

A satellite view of aerosols in the climate system

Rainfall and aerosols play major roles in the Earth climate system and substantially influence our life. Here, the focus is on the local near-surface aerosol/rainfall correlations with time-scales of minutes to days. We investigated 29 experiments including 14 specific rain events, with time resolutions of daily and 60, 30, 10 minutes at ten stations in Israel and California. The highest negative correlations were consistently at a positive lag of about 140-160 minutes where a positive lag means that the aerosol time-series follows that of the rain. The highest negative value is suggested to be the probable outcome of immediate scavenging along with the rise in aerosol concentration after rain depending on aerosol sources, hygroscopic growth and transport. The scavenging dominance is expressed by the mostly negative lag-correlation values in all experiments. In addition, the consistent lack of significant correlation found at negative lags suggest a weak aerosol effect on precipitation (Gryspeerdt et al., 2015).

An Unknown Maximum Lag-Correlation Between Rainfall and Aerosols at 140–160 Minutes

Technical Report Series on Global Modeling and Data Assimilation, Volume 32

An analysis of pollution homogeneity has been conducted to distinguish between remote and local pollution which contributes to month to month changes in aerosol optical depth (AOD) over the Taiwan area. This was carried out using both AERONET measurements at six monitoring sites in Taiwan and NASA MERRA-2 reanalysis, over the 15-year period from 2002 to 2017. As a measure of air pollution homogeneity we used the AOD standard deviation: the more homogeneous the spatial distribution of air pollution, the lower the AOD standard deviation is. Using this approach, we found that, over Taiwan, in autumn, inhomogeneous local air pollution is predominant, while, in spring, homogeneous remote air pollution from south-east Asia dominates. In autumn, when inhomogeneous aerosols from local sources dominate, the AOD standard deviation is essentially higher than that in spring, when homogeneous aerosols from remote sources dominate. Our approach allowed us to distinguish between homogeneous remote and inhomogeneous local sulfate air pollution of similar optical properties and chemical composition.

Distinguishing Between Remote and Local Air Pollution Over Taiwan: An Approach Based on Pollution Homogeneity Analysis

The Po Valley in Northern Italy is frequently affected by high PM10 concentrations, where both natural and anthropogenic sources play a significant role. This work was aimed at giving a proper account of the contribution of Saharan dust to air quality in the Po Valley. This was carried out by improving the boundary conditions of the mesoscale 3D deterministic Transport Chemical Aerosol Model (TCAM) on large-scale transport of Saharan dust, daily predicted over the Mediterranean region. A case study of the integration of the TCAM and DREAM models was implemented over the Po Valley. The results show that the use of improved boundary conditions leads TCAM to better performances, both in terms of correlation and mean errors: TCAM was able to more accurately reproduce high PM10 concentrations observed in the Po Valley during particular dust events.

Improved CTM Boundary Conditions Using DREAM Desert Dust Forecasts: A Case Study over the Po Valley

The Supercomputer Toolkit constructs parallel computation networks by connecting processor modules. These connections are set by the user prior to a run and are static during the run. The Technion's Toolkit prototype was used to run a simplified version of the PSU/NCAR MM5 mesoscale model [9]. Each processor is assigned columns of the grid points of a square in the (x,y) space. When n x n columns are assigned to each processor its computation time is proportional to n 2 and its communication time to n. Since the Toolkit's network computes in parallel and communicates in parallel, then, for a given n, the total time is independent of the size of the two dimensional array or the area over which the weather prediction takes place. A mesoscale forecast over the eastern Mediterranean was run and measured; it suggests that were the Toolkit constructed from ALPHA processors, 10 processors would do a 36 h prediction in only about 13 minutes. A 36 hours prediction with full physics for the whole earth will require 2 hours for 80 ALPHA processors.

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Pinhas Alpert

Papers

An Unknown Maximum Lag-Correlation Between Rainfall and Aerosols at 140–160 Minutes

Technical Report Series on Global Modeling and Data Assimilation, Volume 32

Distinguishing Between Remote and Local Air Pollution Over Taiwan: An Approach Based on Pollution Homogeneity Analysis

Improved CTM Boundary Conditions Using DREAM Desert Dust Forecasts: A Case Study over the Po Valley

Numerical Weather Prediction on the Supercomputer Toolkit