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Chou, J.

Publications and source records attributed to Chou, J..

Delivering laser performance conditions to enable fusion ignition, and beyond at the National Ignition Facility

On December 5th, 2022, controlled fusion ignition was demonstrated for the first time at the National Ignition Facility (NIF), a major achievement in the field of Inertial Confinement Fusion (ICF) requiring a multi-decadal effort involving broad national and international collaborations. To drive the fusion ignition reaction with the compressed fuel capsule, that yielded 3.15 MJ of nuclear energy [1], the NIF laser delivered a high-precision pulse shape with 2.05 MJ of ultra-violet (UV) laser energy and a peak power of 440 TW. This laser energy was an increase of ~8 % compared to that delivered on the previous “threshold of ignition” record yield experiment (1.37 MJ of yield for 1.89 MJ of laser energy) on August 8th, 2021. Here we explain how the results of our extensive research in laser technology and UV optics damage mitigation led to major improvements in the NIF laser, enabling this energy increase along with additional accuracy, precision, and power balance enhancements. Furthermore, we will discuss on-going efforts that have enabled operations at 2.2 MJ of UV energy as well as potential new initiatives to push the laser performance –accuracy and delivered energy– to even higher levels in the future as previously demonstrated on a small subset of NIF beams.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY

The Potential for Collocated AGLP and ERBE data for Fire, Smoke, and Radiation Budget Studies

One month of the Advanced Very High Resolution Radiometer (AVHRR) Global Area Coverage (GAC) Land Pathfinder (AGLP) data from September 1985 are used to examine the spatial and temporal distribution of fires over four major ecosystems in South America. The Earth Radiation Budget Experiment (ERBE) scanner data are used to examine the top of atmosphere (TOA) shortwave and longwave fluxes over smoke generated from biomass burn- ing. The relationship between the AGLP-derived Normalized Difference Vegetation Index (NDVI) and the ERBE-estimated clear sky albedos are also examined as a function of the four ecosystems. This study shows that the grassland areas in South America have the highest number of fires for September 1985, and their corresponding NDVI values are smaller than the tropical rainforest region where the number of fires were comparatively small. Clear sky statistics accumulated during the days when smoke was not present show that clear sky albedos derived from ERBE are higher for grassland areas when compared to the tropical rainforest. The results show that the AGLP can be used to determine the spatial and temporal distribution of fires along with vegetation characteristics, while ERBE data can provide necessary information on broadband albedos and regional top of atmosphere radiative impacts of biomass burning aerosols. Since the AGLP data are available from 1981 to the present day, several climate-related issues can be addressed.

Christropher, S. A.

The Potential for Collocated AGLP and ERBE Data for Fire, Smoke, and Radiation Budget Studies

One month of the Advanced Very High Resolution Radiometer (AVHRR) Global Area Coverage (GAC) Land Pathfinder (AGLP) data from September 1985 are used to examine the spatial and temporal distribution of fires over four major ecosystems in South America. The Earth Radiation Budget Experiment (ERBE) scanner data are used to examine the top of atmosphere (TOA) shortwave and longwave fluxes over smoke generated from biomass burning. The relationship between the AGLP-derived Normalized Difference Vegetation Index (NDVI) and the ERBE-estimated clear sky albedos are also examined as a function of the four ecosystems. This study shows that the grassland areas in South America have the highest number of fires for September 1985. and their corresponding NDVI values are smaller than the tropical rainforest region where the number of fires were comparatively small. Clear sky statistics accumulated during the days when smoke was not present show that clear sky albedos derived from ERBE are higher for grassland areas when compared to the tropical rainforest. The results show that the AGLP can be used to determine the spatial and temporal distribution of fires along with vegetation characteristics, while ERBE data can provide necessary information on broadband albedos and regional top of atmosphere radiative impacts of biomass burning aerosols. Since the AGLP data are available from 1981 to the present day, several climate-related issues can be addressed,

Christopher, S. A.

The Potential for Collocated AGLP and ERBE Data for Fire, Smoke, and Radiation Budget Studies

One month of the Advanced Very High Resolution Radiometer (AVHRR) Global Area Coverage (GAC) Land Pathfinder (AGLP) data from September 1985 are used to examine the spatial and temporal distribution of fires over four major ecosystems in South America. The Earth Radiation Budget Experiment (ERBE) scanner data are used to examine the top of atmosphere (TOA) shortwave and longwave fluxes over smoke generated from biomass burning. The relationship between the AGLP-derived Normalized Difference Vegetation Index (NDVI) and the ERBE-estimated clear sky albedos are also examined as a function of the four ecosystems. This study shows that the grassland areas in South America have the highest number of tires for September 1985, and their corresponding NDVI values are smaller than the tropical rainforest region where the number of fires were comparatively small. Clear sky statistics accumulated during the days when smoke was not present show that clear sky albedos derived from ERBE are higher for grassland areas when compared to the tropical rainforest. The results show that the AGLP can be used to determine the spatial and temporal distribution of fires along with vegetation characteristics, while ERBE data can provide necessary information on broadband albedos and regional top of atmosphere radiative impacts of biomass burning aerosols. Since the AGLP data are available from 1981 to the present day, several climate-related issues can be addressed.

Christopher, S. A.

Validation of satellite retrievals of cloud microsphysics and liquid water path using observations from FIRE

Cloud effective radii (r(sub e)) and cloud liquid water path (LWP) are derived from ISCCP spatially sampled satellite data and validated with ground-based pyranometer and microwave radiometer measurements taken on San Nicolas Island during the 1987 FIRE IFO. Values of r(sub e) derived from the ISCCP data are also compared to values retrieved by a hybrid method that uses the combination of LWP derived from microwave measurement and optical thickness derived from GOES data. The results show that there is significant variability in cloud properties over a 100 km x 80 km area and that the values at San Nicolas Island are not necessarily representative of the surrounding cloud field. On the other hand, even though there were large spatial variations in optical depth, the r(sub e) values remained relatively constant (with sigma less than or equal to 2-3 microns in most cases) in the marine stratocumulus. Furthermore, values of r(sub e) derived from the upper portion of the cloud generally are representative of the entire stratiform cloud. When LWP values are less than 100 g m(exp -2), then LWP values derived from ISCCP data agree well with those values estimated from ground-based microwave measurements. In most cases LWP differences were less than 20 g m(exp -2). However, when LWP values become large (e.g., greater than or equal to 200 g m(exp -2)), then relative differences may be as large as 50%- 100%. There are two reasons for this discrepancy in the large LWP clouds: (1) larger vertical inhomogeneities in precipitating clouds and (2) sampling errors on days of high spatial variability of cloud optical thicknesses. Variations of r(sub e) in stratiform clouds may indicate drizzle: clouds with droplet sizes larger than 15 microns appear to be associated with drizzling, while those less than 10 microns are indicative of nonprecipitating clouds. Differences in r(sub e) values between the GOES and ISCCP datasets are found to be 0.16 +/- 0.98 micron.

Rossow, W.

Clustering, randomness, and regularity in cloud fields. 4: Stratocumulus cloud fields

To complete the analysis of the spatial distribution of boundary layer cloudiness, the present study focuses on nine stratocumulus Landsat scenes. The results indicate many similarities between stratocumulus and cumulus spatial distributions. Most notably, at full spatial resolution all scenes exhibit a decidedly clustered distribution. The strength of the clustering signal decreases with increasing cloud size; the clusters themselves consist of a few clouds (less than 10), occupy a small percentage of the cloud field area (less than 5%), contain between 20% and 60% of the cloud field population, and are randomly located within the scene. In contrast, stratocumulus in almost every respect are more strongly clustered than are cumulus cloud fields. For instance, stratocumulus clusters contain more clouds per cluster, occupy a larger percentage of the total area, and have a larger percentage of clouds participating in clusters than the corresponding cumulus examples. To investigate clustering at intermediate spatial scales, the local dimensionality statistic is introduced. Results obtained from this statistic provide the first direct evidence for regularity among large (more than 900 m in diameter) clouds in stratocumulus and cumulus cloud fields, in support of the inhibition hypothesis of Ramirez and Bras (1990). Also, the size compensated point-to-cloud cumulative distribution function statistic is found to be necessary to obtain a consistent description of stratocumulus cloud distributions. A hypothesis regarding the underlying physical mechanisms responsible for cloud clustering is presented. It is suggested that cloud clusters often arise from 4 to 10 triggering events localized within regions less than 2 km in diameter and randomly distributed within the cloud field. As the size of the cloud surpasses the scale of the triggering region, the clustering signal weakens and the larger cloud locations become more random.

Lee, J.