Mandana M. Khaiyer

Advanced retrievals of multilayered cloud properties using multispectral measurements

Received 6 June 2004; revised 2 September 2004; accepted 4 October 2004; published 13 April 2005. [1] Current satellite cloud retrievals are usually based on the assumption that all clouds consist of a homogenous single layer despite the frequent occurrence of cloud overlap. As such, cloud overlap will cause large errors in the retrievals of many cloud properties. To address this problem, a multilayered cloud retrieval system (MCRS) is developed by combining satellite visible and infrared radiances and surface microwave radiometer measurements. A two-layer cloud model was used to simulate ice-over-water cloud radiative characteristics. The radiances emanating from the combined low cloud and surface are estimated using the microwave liquid water with an assumption of effective droplet size. These radiances replace the background radiances traditionally used in single-layer cloud retrievals. The MCRS is applied to data from March through October 2000 over four Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) sites. The results are compared to the available retrievals of ice water path (IWP) from radar data and show that the MCRS clearly produces a more accurate retrieval of ice-over-water cloud properties. MCRS yields values of IWP that are closest to those from the radar retrieval. For ice-over-water cloud systems, on average, the optical depth and IWP are reduced, from original overestimates, by approximately 30%. The March–October mean cloud effective temperatures from the MCRS are decreased by 10 ± 12K,whichtranslatestoanaverageheightdifferenceof � 1.4km.Theseresultsindicatethat ice-cloud height derived from traditional single-layer retrieval is underestimated, and the midlevel ice cloud coverage is over classified. Effective ice crystal particle sizes are increased by only a few percent with the new method. This new physically based technique should be robust and directly applicable when data are available simultaneously from a satellite imager and the appropriate satellite or surface microwave sensor.

A 10 year climatology of cloud fraction and vertical distribution derived from both surface and GOES observations over the DOE ARM SPG site

[1]xa0Analysis of one decade of radar-lidar and Geostationary Operational Environmental Satellite (GOES) observations at the Department of Energy (DOE) Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) site reveals that there is excellent agreement in the long-term mean cloud fractions (CFs) derived from the surface and GOES data, and the CF is independent of temporal resolution and spatial scales for grid boxes of size 0.5° to 2.5°. When computed over a a 0.5 h (4 h) period, cloud frequency of occurrence (FREQ) and amount when present (AWP) derived from the point surface data agree very well with the same quantities determined from GOES for a 0.5° (2.5°) region centered on the DOE ARM SGP site. The values of FREQ (AWP) derived from the radar-lidar observations at a given altitude increase (decrease) as the averaging period increases from 5 min to 6 h. Similarly, CF at a given altitude increases as the vertical resolution increases from 90 to 1000 m. The profiles of CF have distinct bimodal vertical distributions, with a lower peak between 1 and 2 km and a higher one between 8 and 11 km. The 10 year mean total CF, 46.9%, varies seasonally from a summer minimum of 39.8% to a maximum of 54.6% during the winter. The annual mean CF is 1%–2% less than that from previous studies, ∼48%–49%, because fewer clouds occurred during 2005 and 2006, especially during winter. The differences in single- and multilayered CFs between this study and an earlier analysis can be explained by the different temporal resolutions used in the two studies, where single-layered CFs decrease but multilayered CFs increase from a 5 min resolution to a 1 h resolution. The vertical distribution of nighttime GOES high cloud tops agrees well with surface observations, but during the daytime, fewer high clouds are retrieved by the GOES analysis than seen from the surface observations. The FREQs for both daytime and nighttime GOES low cloud tops are significantly higher than surface observations, but the CFs are in good agreement.

Top‐of‐atmosphere radiation budget of convective core/stratiform rain and anvil clouds from deep convective systems

[1] A new hybrid classification algorithm to objectively identify Deep Convective Systems (DCSs) in radar and satellite observations has been developed. This algorithm can classify the convective cores (CC), stratiform rain (SR) area and nonprecipitating anvil cloud (AC) from the identified DCSs through an integrative analysis of ground-based scanning radar and geostationary satellite data over the Southern Great Plains. In developing the algorithm, AC is delineated into transitional, thick, and thin components. While there are distinct physical/dynamical differences among these subcategories, their top-of-atmosphere (TOA) radiative fluxes are not significantly different. Therefore, these anvil subcategories are grouped as total anvil, and the radiative impact of each DCS component on the TOA radiation budget is quantitatively estimated. We found that more DCSs occurred during late afternoon, producing peak AC fraction right after sunset. AC covers 3 times the area of SR and almost an order of magnitude larger than CC. The average outgoing longwave (LW) irradiances are almost identical for CC and SR, while slightly higher for AC. Compared to the clear-sky average, the reflected shortwave (SW) fluxes for the three DCS components are greater by a factor of 2–3 and create a strong cooling effect at TOA. The calculated SW and LW cloud radiative forcing (CRF) of AC contribute up to 31% of total NET CRF, while CC and SR contribute only 4 and 11%, respectively. The hybrid classification further lays the groundwork for studying the life cycle of DCS and improvements in geostationary satellite IR-based precipitation retrievals.

Satellite Data Support for the ARM Climate Research Facility, 8/01/2009 - 7/31/2015

This report summarizes the support provided by NASA Langley Research for the DOE ARM Program in the form of cloud and radiation products derived from satellite imager data for the period between 8/01/09 through 7/31/15. Cloud properties such as cloud amount, height, and optical depth as well as outgoing longwave and shortwave broadband radiative fluxes were derived from geostationary and low-earth orbiting satellite imager radiance measurements for domains encompassing ARM permanent sites and field campaigns during the performance period. Datasets provided and documents produced are listed.