Search NASA⌕ Search

Engineering topics

Andrew Lacis

Publications and source records attributed to Andrew Lacis.

An Efficient and Accurate Algorithm for Computing Grid-Averaged Solar Fluxes for Horizontally Inhomogeneous Clouds

A computationally efficient method is presented to account for the horizontal cloud inhomogeneity by using a radiatively equivalent plane parallel homogeneous (PPH) cloud. The algorithm can accurately match the calculations of the reference (rPPH) independent column approximation (ICA) results, but use only the same computational time required for a single plane parallel computation. The effective optical depth of this synthetic sPPH cloud is derived by exactly matching the direct transmission to that of the inhomogeneous ICA cloud. The ffective9 scattering asymmetry factor is found from a pre-calculated albedo inverse look-up-table that is allowed to vary over the range from -1.0 to 1.0. In the special cases of conservative scattering and total absorption, the synthetic method is exactly equivalent to the ICA, with only a small bias (about 0.2% in flux) relative to ICA due to imperfect interpolation in using the look-up tables. In principle, the ICA albedo can be approximated accurately regardless of cloud inhomogeneity. For a more complete comparison, the broadband shortwave albedo and transmission calculated from the synthetic sPPH cloud and averaged over all incident directions, have the RMS biases of 0.26% and 0.76%, respectively, for inhomogeneous clouds over a wide variation of particle size. The advantages of the synthetic PPH method are that (1) it is not required that all the cloud subcolumns have uniform microphysical characteristic, (2) it is applicable to any 1D radiative transfer scheme, and (3) it can handle arbitrary cloud optical depth distributions and an arbitrary number of cloud subcolumns with uniform computational efficiency.

cloud inhomogeneity↗

Seasonal and Dayurnal Planetary Albedo Variability from Six Years of DSCOVR EPIC Data

Deep Space Climate Observatory (DSCOVR) measurements of Earth’s reflected solar radiation from the Lissajous orbital position near the Lagrangian L1 point provide continuous monitoring of the Earth’s sunlit hemisphere. CERES-based angle models were used to convert the near-hourly reflected radiances of the EPIC images into a climate-style planetary albedo data-point over the sunlit hemisphere. Integration over the sunlit hemispheres averages out the meteorological weather noise, but retains the seasonal and planetary-scale variability. As the Earth rotates, this generates variations in the Earth’s planetary albedo that are precisely aligned in longitude, which constitutes the dayurnal cycle. This dayurnal variability in the planetary albedo arises from planetary-scale changes in cloud radiative properties that can be directly compared to similarly sampled climate GCM output data. Six years of EPIC data have been analyzed, showing characteristic patterns in the seasonal and dayurnal variability of the Earth’s planetary albedo. Much of the seasonal change in planetary albedo is associated with the changing DSCOVR viewing geometry and the change in solar declination. But throughout the year, the highest planetary albedos are observed over the Central Asia (Iraq) longitude, while the lowest planetary albedos occur over the Central Pacific longitude. For these longitudes, the relative seasonal changes in the planetary albedo are slowly varying and anti-correlated. Dayurnal amplitude maxima tend to occur during the July-September timeframe, with April-May and December exhibit distinct minima in the dayurnal amplitude. West Africa and the West Pacific longitudes likewise exhibit anti-correlated seasonal variability, while they also undergo anti-correlated short period oscillations. On the other hand, in nearby longitudes, there are short period spikes in planetary albedo of a few-days duration, as well as longer period oscillations that may range from a week to several months, that generally tend to be correlated.

Planetary Albedo↗