GPU Computing for Longwave Radiation Physics: A RRTM_LW Scheme Case Study

2011 ◽  
Author(s):  
Fengshun Lu ◽  
Xiaoqun Cao ◽  
Junqiang Song ◽  
Xiaoqian Zhu
Keyword(s):  
Gpu Computing ◽  
Longwave Radiation ◽  
Radiation Physics

scholarly journals Influence of Northwest Cloudbands on Southwest Australian Rainfall

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Nicola Telcik ◽  
Charitha Pattiaratchi
Keyword(s):  
Longwave Radiation ◽  
Reanalysis Data ◽  
Temperature Data ◽  
Sea Surface ◽  
Northwest Coast ◽  
Total Cloud Cover ◽  
Site Specific ◽  
Australian Continent ◽  
Average Rainfall

Northwest cloudbands are tropical-extratropical feature that crosses the Australian continent originating from Australia’s northwest coast and develops in a NW-SE orientation. In paper, atmospheric and oceanic reanalysis data (NCEP) and Reynolds reconstructed sea surface temperature data were used to examine northwest cloudband activity across the Australian mainland. An index that reflected the monthly, seasonal, and interannual activity of northwest cloudbands between 1950 and 1999 was then created. Outgoing longwave radiation, total cloud cover, and latent heat flux data were used to determine the number of days when a mature northwest cloudband covered part of the Australian continent between April and October. Regional indices were created for site-specific investigations, especially of cloudband-related rainfall. High and low cloudband activity can affect the distribution of cloudbands and their related rainfall. In low cloudband activity seasons, cloudbands were mostly limited to the south and west Australian coasts. In high cloudband activity seasons, cloudbands penetrated farther inland, which increased the inland rainfall. A case study of the southwest Australian region demonstrated that, in a below average rainfall year, cloudband-related rainfall was limited to the coast. In an above average rainfall year, cloudband-related rainfall occurred further inland.

Introduction to GPU Computing and CUDA Programming: A Case Study on FDTD [EM Programmer's Notebook

2010 ◽  
Vol 52 (3) ◽  
pp. 116-122 ◽  
Author(s):  
Danilo De Donno ◽  
Alessandra Esposito ◽  
Luciano Tarricone ◽  
Luca Catarinucci
Keyword(s):  
Gpu Computing ◽  
Cuda Programming

HIGH PERFORMANCE AND SCALABLE RADIX SORTING: A CASE STUDY OF IMPLEMENTING DYNAMIC PARALLELISM FOR GPU COMPUTING

2011 ◽  
Vol 21 (02) ◽  
pp. 245-272 ◽  
Author(s):  
DUANE MERRILL ◽  
ANDREW GRIMSHAW
Keyword(s):  
High Performance ◽  
Gpu Computing ◽  
State Of The Art ◽  
Design Strategies ◽  
Kernel Fusion ◽  
Parallel Prefix ◽  
Scan Data ◽  
Many Core ◽  
Global Data

The need to rank and order data is pervasive, and many algorithms are fundamentally dependent upon sorting and partitioning operations. Prior to this work, GPU stream processors have been perceived as challenging targets for problems with dynamic and global data-dependences such as sorting. This paper presents: (1) a family of very efficient parallel algorithms for radix sorting; and (2) our allocation-oriented algorithmic design strategies that match the strengths of GPU processor architecture to this genre of dynamic parallelism. We demonstrate multiple factors of speedup (up to 3.8x) compared to state-of-the-art GPU sorting. We also reverse the performance differentials observed between GPU and multi/many-core CPU architectures by recent comparisons in the literature, including those with 32-core CPU-based accelerators. Our average sorting rates exceed 1B 32-bit keys/sec on a single GPU microprocessor. Our sorting passes are constructed from a very efficient parallel prefix scan "runtime" that incorporates three design features: (1) kernel fusion for locally generating and consuming prefix scan data; (2) multi-scan for performing multiple related, concurrent prefix scans (one for each partitioning bin); and (3) flexible algorithm serialization for avoiding unnecessary synchronization and communication within algorithmic phases, allowing us to construct a single implementation that scales well across all generations and configurations of programmable NVIDIA GPUs.

Assessing the Skill of an All-Season Statistical Forecast Model for the Madden–Julian Oscillation

2008 ◽  
Vol 136 (6) ◽  
pp. 1940-1956 ◽  
Author(s):  
Xianan Jiang ◽  
Duane E. Waliser ◽  
Matthew C. Wheeler ◽  
Charles Jones ◽  
Myong-In Lee ◽  
...  
Keyword(s):  
Real Time ◽  
Longwave Radiation ◽  
Forecast Model ◽  
Boreal Winter ◽  
Madden Julian Oscillation ◽  
Predictive Skill ◽  
Regression Parameters ◽  
Extended Range ◽  
Forecast Time

Abstract Motivated by an attempt to augment dynamical models in predicting the Madden–Julian oscillation (MJO), and to provide a realistic benchmark to those models, the predictive skill of a multivariate lag-regression statistical model has been comprehensively explored in the present study. The predictors of the benchmark model are the projection time series of the leading pair of EOFs of the combined fields of equatorially averaged outgoing longwave radiation (OLR) and zonal winds at 850 and 200 hPa, derived using the approach of Wheeler and Hendon. These multivariate EOFs serve as an effective filter for the MJO without the need for bandpass filtering, making the statistical forecast scheme feasible for the real-time use. Another advantage of this empirical approach lies in the consideration of the seasonal dependence of the regression parameters, making it applicable for forecasts all year-round. The forecast model exhibits useful extended-range skill for a real-time MJO forecast. Predictions with a correlation skill of greater than 0.3 (0.5) between predicted and observed unfiltered (EOF filtered) fields still can be detected over some regions at a lead time of 15 days, especially for boreal winter forecasts. This predictive skill is increased significantly when there are strong MJO signals at the initial forecast time. The analysis also shows that predictive skill for the upper-tropospheric winds is relatively higher than for the low-level winds and convection signals. Finally, the capability of this empirical model in predicting the MJO is further demonstrated by a case study of a real-time “hindcast” during the 2003/04 winter. Predictive skill demonstrated in this study provides an estimate of the predictability of the MJO and a benchmark for the dynamical extended-range models.

scholarly journals Building a Tropical–Extratropical Cloud Band Metbot

2012 ◽  
Vol 140 (12) ◽  
pp. 4005-4016 ◽  
Author(s):  
Neil C. G. Hart ◽  
Chris J. C. Reason ◽  
Nicolas Fauchereau
Keyword(s):  
Southern Africa ◽  
Longwave Radiation ◽  
Laplacian Operator ◽  
Cloud Band ◽  
Blob Detection ◽  
Object Based ◽  
Multiscale Interactions ◽  
Meteorological Features ◽  
Labeling Method

Abstract An automated cloud band identification procedure is developed that captures the meteorology of such events over southern Africa. This “metbot” is built upon a connected component labeling method that enables blob detection in various atmospheric fields. Outgoing longwave radiation is used to flag candidate cloud band days by thresholding the data and requiring detected blobs to have sufficient latitudinal extent and exhibit positive tilt. The Laplacian operator is used on gridded reanalysis variables to highlight other features of meteorological interest. The ability of this methodology to capture the significant meteorology and rainfall of these synoptic systems is tested in a case study. Usefulness of the metbot in understanding event-to-event similarities of meteorological features is demonstrated, highlighting features previous studies have noted as key ingredients to cloud band development in the region. Moreover, this allows the presentation of a composite cloud band life cycle for southern Africa events. The potential of metbot to study multiscale interactions is discussed, emphasizing its key strength: the ability to retain details of extreme and infrequent events. It automatically builds a database that is ideal for research questions focused on the influence of intraseasonal to interannual variability processes on synoptic events. Application of the method to convergence zone studies and atmospheric river descriptions is suggested. In conclusion, a relation-building metbot can retain details that are often lost with object-based methods but are crucial in case studies. Capturing and summarizing these details may be necessary to develop a deeper process-level understanding of multiscale interactions.

scholarly journals Drought Detection over Papua New Guinea Using Satellite-Derived Products

2020 ◽  
Vol 12 (23) ◽  
pp. 3859
Author(s):  
Zhi-Weng Chua ◽  
Yuriy Kuleshov ◽  
Andrew B. Watkins
Keyword(s):  
Papua New Guinea ◽  
El Niño ◽  
El Nino ◽  
Standardized Precipitation Index ◽  
Longwave Radiation ◽  
New Guinea ◽  
False Alarms ◽  
Vegetation Health ◽  
The Impact

This study evaluates the World Meteorological Organization’s (WMO) Space-based Weather and Climate Extremes Monitoring (SWCEM) Demonstration Project precipitation products over Papua New Guinea (PNG). The products evaluated were based on remotely-sensed precipitation, vegetation health, soil moisture, and outgoing longwave radiation (OLR) data. The satellite precipitation estimates of the Climate Prediction Center/National Oceanic and Atmospheric Administration’s (CPC/NOAA) morphing technique (CMORPH) and Japan Aerospace Exploration Agency’s (JAXA) Global Satellite Mapping of Precipitation (GSMaP) were assessed on a monthly timescale over an 18-year period from 2001 to 2018. Station data along with the ERA5 reanalysis were used as the reference datasets for assessment purposes. In addition, a case study was performed to investigate how well the SWCEM precipitation products characterised drought in PNG associated with the 2015–2016 El Niño. Overall statistics from the validation study suggest that although there remains significant variability between satellite and ERA5 rainfall data in remote areas, this difference is much less at locations where rain gauges exist. The case study illustrated that the Vegetation Health Index (VHI), OLR anomaly and the Standardized Precipitation Index (SPI) were able to reliably capture the spatial and temporal aspects of the severe 2015–2016 El Niño-induced drought in PNG. Of the three, VHI appeared to be the most effective, in part due to its reduced incidence of false alarms. This study is novel as modern-day satellite-derived products have not been evaluated over PNG before. A focus on their value in monitoring drought can bring great value in mitigating the impact of future droughts. It is concluded that these satellite-derived precipitation products could be recommended for operational use for drought detection and monitoring in PNG, and that even a modest increase in ground-based observations will increase the accuracy of satellite-derived observations remotely.

scholarly journals Use of GPU Computing for Uncertainty Quantification in Computational Mechanics: A Case Study

2011 ◽  
Vol 19 (4) ◽  
pp. 199-212 ◽  
Author(s):  
Gaurav ◽  
Steven F. Wojtkiewicz
Keyword(s):  
Parallel Computing ◽  
Uncertainty Quantification ◽  
Graphics Processing Units ◽  
Computational Mechanics ◽  
Gpu Computing ◽  
Single Instruction Multiple Data ◽  
Performance Constraints ◽  
Multiple Data ◽  
Graphics Processing

Graphics processing units (GPUs) are rapidly emerging as a more economical and highly competitive alternative to CPU-based parallel computing. As the degree of software control of GPUs has increased, many researchers have explored their use in non-gaming applications. Recent studies have shown that GPUs consistently outperform their best corresponding CPU-based parallel computing alternatives in single-instruction multiple-data (SIMD) strategies. This study explores the use of GPUs for uncertainty quantification in computational mechanics. Five types of analysis procedures that are frequently utilized for uncertainty quantification of mechanical and dynamical systems have been considered and their GPU implementations have been developed. The numerical examples presented in this study show that considerable gains in computational efficiency can be obtained for these procedures. It is expected that the GPU implementations presented in this study will serve as initial bases for further developments in the use of GPUs in the field of uncertainty quantification and will (i) aid the understanding of the performance constraints on the relevant GPU kernels and (ii) provide some guidance regarding the computational and the data structures to be utilized in these novel GPU implementations.

CPU/GPU computing for long-wave radiation physics on large GPU clusters

2012 ◽  
Vol 41 ◽  
pp. 47-55 ◽  
Author(s):  
Fengshun Lu ◽  
Junqiang Song ◽  
Xiaoqun Cao ◽  
Xiaoqian Zhu
Keyword(s):  
Gpu Computing ◽  
Wave Radiation ◽  
Radiation Physics ◽  
Long Wave ◽  
Gpu Clusters ◽  
Long Wave Radiation
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