What is variable land ? ( Class 10 Geography )
Answers
Explanation:
We use a large‐eddy simulation model with a nested domain configuration (297 and 120 km wide) and an interactive land surface parameterization to simulate the complex population of shallow clouds observed on 30 August 2016 during the Holistic Interactions of Shallow Clouds, Aerosols, and Land‐Ecosystems campaign conducted in north‐central Oklahoma. Shallow convective clouds first formed over southeast Oklahoma and then spread toward the northwest into southern Kansas. By the early afternoon, the relatively uniform shallow cloud field became more complex in which some regions became nearly cloud free and in other regions larger shallow clouds developed with some transitioning to deeper, precipitating convection. We show that the model reproduces the observed heterogeneity in the cloud populations only when realistic variations in soil moisture are used to initialize the model. While more variable soil moisture and to a lesser extent cool lake temperatures drive the initial spatial heterogeneity in the cloud populations, precipitation‐driven cold pools become an important factor after 1300 CST. When smoother soil moisture variations are used in the model, more uniform shallow cloud populations are predicted with far fewer clouds that transition to deeper, precipitating convection that produce cold pools. An algorithm that tracks thousands of individual cumulus show that the more realistic soil moisture distributions produces clouds that are larger and have a longer lifetime. The results suggest that shallow and deep convection parameterizations used by mesoscale models need to account for the effects of variable land‐atmosphere interactions and cold pools.
Plain Language Summary
Models that resolve boundary layer turbulence and clouds have been used extensively to better understand processes controlling the life cycle of shallow convective clouds. Because of their computational expense these models usually employ relatively small domain sizes, usually less than 50 km wide, and constrain the atmospheric forcing so that the predicted clouds are nearly uniformly distributed in space. We employ a more realistic modeling approach to represent the observed complex cloud distributions over Oklahoma on a day during a recent atmospheric sampling campaign. The model results suggest that the observed cloud distributions were caused by two processes that can occur at the same time. During the morning, spatial variations in soil moisture perturbed the heating patterns and altered the timing and intensity of cloud formation. Then during the afternoon cold pools further perturbed the clouds, producing clear skies in some regions and enhancing cloud formation in other regions. While cooler air from evaporating precipitation suppresses cloud formation, cloud formation is enhanced at the edges of the expanding pool of colder air. These processes are missing or treated simply in numerical representations of convective clouds by operational forecasting and climate models that may affect predictions of cloudiness and initiation of precipitation.